Untod State*
fiwiromnantal FrancOo*
          AthanaOA 30613
  eft and 0<
Water Quality
Assessment:

A Screening
Procedure for Toxic and
Conventional Pollutants in
Surface and Ground
Water—Part I
(Revised—1985)

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                                                       EPA/600/6-85/002a
                                                       September 1985
                   WATER QUALITY ASSESSMENT:
                A Screening Procedure for Toxic
                  and Conventional  Pollutants
                  1n Surface and Ground Water
                         (Revised 1985)
                            Part 1
                              by

W.B. Mills, D.B. Porcella, M.J.  Ungs, S.A. Gher1n1, K.V.  Summers,
            Llngfung Hole, G.L. Rupp, and G.L.  Bowie
                   Tetra Tech, Incorporated
                 Lafayette, California  94549

                             and

                          D.A. Halth
                      Cornell  University
                    Ithaca. New York 14853

                         Produced by:

                        JACA Corporation
              Fort Washington, Pennsylvania 19034

                    Contract No. 68-03-"131
            Prepared 1n Cooperation with U.S.  EPA's

               Center for Water Quality Modeling
               Environmental  Research Laboratory
                       Athens, Georgia

              Monitoring and Data Support Division
            Office of Water Regulations and Standards
                        Office of Water
                        Washington, O.C.
                      Technology Transfer
        Center for Environmental Research Information
                      Cincinnati, Ohio
               ENVIRONMENTAL RESEARCH LABORATORY
               OFFICE OF RESEARCH AND DEVELOPMENT
              U.S. ENVIRONMENTAL PROTECTION AGENCY
                      ATHENS, GEORGIA   306i3

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                                DISCLAIMER
     Mention of trade names or commercial products does not constitute endorse-
ment or recommendation for use by the U.S. Environmental Protection Agency.
                                     -if-

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                                 ABSTRACT


      New technical developments in the field of water quality assessment and
a  reordering of water quality priorities prompted a revision of the first two
editions of this manual.  The utility of the revised manual Is enhanced by
th« Inclusion of methods to predict the transport and fate of toxic chemicals
In ground water, and by methods to predict the fate of metals in rivers.  In
addition, major revisions were completed on Chapter 2 (organic toxicants).
Chapter 3 (waste loadings), and Chapter 5 (impoundments) that reflect recent
advancements In these fields.

     Applying the manual's simple techniques, the user is now capable of
assessing the loading and fate of conventional  pollutants (temperature,
biochemical oxygen demand-dissolved oxygen, nutrients, and sediments) and
toxic pollutants (from the U.S. EPA list of priority pollutants) in streams,
Impoundments, estuaries, and ground waters.  The techniques are readily
programmed on hand-held calculators or microcomputers.  Host of the data
required for using these procedures are contained in the manual.

     Because of its size, the manual  has been divided Into two parts.  Part
I contains the Introduction and chapters on the aquatic fate of toxic organic
substances, waste loading calculations, and the assessment of water quality
parameters in rivers and streams.  Part II continues with chapters on the
assessment of Impoundments, estuaries, and ground water and appendices E, H,
I, and J.  Appendices D, F, and G are provided  on microfiche in the EPA-printed
manual.  Appendices A, B, and C, which appeared in the first two editions,
are now out of date and have been deleted.

     This report is submitted in fulfillment of Contract No. 68-03-3131 by
JACA Corp. and Tetra Tech, Inc. under the sponsorship of the U.S. Environ-
mental Protection Agency.  Work was completed as of May 1985.
                                      -111-

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                               TABLE OF CONTENTS



Chapter                                                                     Page

                                     PART I


       DISCLAIMER	    11

       ABSTRACT	   111

       LIST OF FIGURES (Part I)	   x11

       LIST OF TABLES (Part M	   x1x

       ACKNOWLEDGEMENTS 	 xxv11

  1    INTRODUCTION 	      1

       1.1      BACKGROUND	      1

       1.2      PURPOSE AND SCOPE	      1

       1.3      METHODOLOGY APPLICATION 	      3
       1.3.1    Base Maps	      3

       1.4      LIMITATIONS 	      3

       REFERENCES 	      4

  2    AQUATIC FATE OF TOXIC ORGANIC SUBSTANCES 	      5

       2.1      INTRODUCTION	      5
       2.1.1    Background	      5
       2.1.2    Comparison of Conventional and Toxic Pollutants  	      5
       2.1.3    Water Quality Criteria	      7
       2.1.4    Frequency of Discharge of Toxic Substances from
                Industries	      7
       2.1.5    Physical  and Chemical Characteristics of Toxic
                Organic Compounds	    18
       2.1.6    Scope and Organization of Chapter	    18

       2.2      SCREENING METHODS FOR TOXIC ORGANIC COMPOUNDS 	    24
       2.2.1    Modeling the Fate of Toxic Organlcs	    24
       2.2.2    Use of Assessment Techniques as Screening Tools	    29

       2.3      SPECIATION PROCESSES	    41
       2.3.1    Acid-Base Effects 	    41
       2.3.2    Sorptlon on Suspended Sediments 	    46

       2.4      TRANSPORT PROCESSES 	    58
       2.4.1    Solubility Limits 	    58
       2.4.2    Volatilization	    59
                                      -V-

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Chapter                                                                     Page


       2.5      TRANSFORMATION PROCESSES	    77
       2.5.1    Biodegradation	    77
       2.5.2    Photolysis	    95
       2.5.3    Hydrolysis	   129

       REFERENCES	   137

  3    WASTE LOADING CALCULATIONS 	   142

       3.1      INTRODUCTION	   142

       3.2      BACKGROUND POLLUTION LOADS	   142

       3.3      NONPOINT SOURCE MODELS  	   150

       3.4      RURAL RUNOFF LOADS	   151
       3.4.1    Source Areas	   151
       3.4.2    Runoff	   152
       3.4.3    Erosion and Sediment	   160
       3.4.4    Chemical Loading Functions for Rural Runoff  	   178

       3.5      SALT LOADS IN IRRIGATION RETURN FLOWS  	   207
       3.5.1    Description	   207
       3.5.2    Estimation of Return Flows	   209

       3.6      URBAN RUNOFF LOADS	   215
       3.6.1    Annual Urban Runoff and Combined Sewer Loads	   215
       3.6.2    Event Loads In Urban Runoff  	   219

       3.7      GROUND WATER WASTE LOADS	   231
       3.7.1    Characteristics	   231
       3.7.2    Water Balance	   233
       3.7.3    Nitrate Loads to Ground Water from Waste Application
                Sites	   233
       3.7.4    Leaching of Organic Chemicals 	   239

       3.8      ATMOSPHERIC WASTE LOADS 	   245
       3.8.1    Dry Deposition	   245
       3.8.2    Wet Deposition (Precipitation Scavenging)  	   253

       3.9      POINT SOURCE WASTE LOADS	   253
       3.9.1    Municipal Waste Loads  	   254
       3.9.2    Industrial Waste Loads	   262

       REFERENCES	   273

  4    RIVERS  AND STREAMS	   278

       4.1       INTRODUCTION	   278
       4.1.1    Scope	   278
       4.1.2    Significance of  Problem Areas  	   279
       4.1.3    Applicability to Other  Problems  	   282
       4.1.4    Sources of Pollutants	   283
       4.1.5    Assumptions	   283
       4.1.6    Data Requirements	   286
       4.1.7    Selection of Season	   287
       4.1.8    River Segmentation	    289
                                      -vl-

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Chapter                                                                     Page

       4.1.9     Mixing  Zones	    294
       4.1.10   Water and  Pollutant  Balances	    296
       4.1.11   Hand  Held  Calculator Programs	    306

       4.2       CARBONACEOUS  AND  NITROGENOUS OXYGEN DEMAND	    306
       4.2.1     Introduction	    306
       4.2.2     BOD Decay  Rate	    310
       4.2.3     Mass  Balance  of BOO	    313
       4.2.4     Typical  Solutions  	  .....    315
       4.2.5     Other Simplifying  Procedures.  .  .	    317
       4.2.6     Interpretation of  Results  	    321

       4.3       DISSOLVED  OXYGEN	    321
       4.3.1     Introduction	    321
       4.3.2     Dissolved  Oxygen Mass Balance  	    323
       4.3.3     federation Rate	    323
       4.3.4     Effect  of  Dams on  Re aeration	    330
       4.3.5     Dissolved  Oxygen Saturation  	    331
       4.3.6     DO-BOD  Interactions  	    333
       4.3.7     Dissolved  Oxygen Calculations  	    335
       4.3.8     General  Dissolved  Oxygen Deficit  Equation  	    340
       4.3.9     Photosynthesis and Respiration	    341
       4.3.10   Benthic  Demand	    345
       4.3.11   Simplifying  Procedures 1n  Dissolved Oxygen
                Calculations	    347

       4.4       TEMPERATURE	    354
       4.4.1     Introduction	    354
       4.4.2     Equilibrium Temperature 	  ....    355
       4.4.3     Calculation of Equilibrium Temperature	    358
       4.4.4     Screening  of  Thermal  Discharges  	    371
       4.4.5     Longitudinal  Temperature Variation	    381
       4.4.6     Diurnal  Temperature  Variation  	    383
       4.4.7     Low Flow and  Temperature	    383
       4.4.8     Interrelationships Between Temperature Prediction
                Tools	    385

       4.5       NUTRIENTS  AND EuTROPHICATION POTENTIAL	    3«7
       4.5.1     Introduction	    387
       4.5.2     Bas1c.Theory	    388
       4.5.3     Estimating Instream  Nutrient Concentrations  	    390
       4.5.4     Nutrient Accounting  System	    392

       4.6       TOTAL COLIFORM BACTERIA 	    395
       4.6.1     Introduction	    395
       4.6.2     Mass  Balance  for Total  Coliforms	    396

        .7       CONSERVATIVE  CONSTITUENTS  	    400
        .7.1     Introduction	    400
        .7.2     Mass  Balance  for Conservative Constituents	    400

        .8       SEDIMENTATION	    402
        .8.1     Introduction.	    402
        .8.2     Long-Term  Sediment Loading from Runoff	    405
        .8.3     Bed Material  Load	    405

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Chapter                                                                     Page


       4.9      TOXIC SUBSTANCES	   417
       4.9.1    Methods of Entry of Toxic Pollutants Into Rivers	   417
       4.9.2    Vertical  Distribution of Sorbate Within Rivers	   420
       4.9.3    Transport and Transformation Expre  •ans for Toxicants
                In Rivers	   426

       4.10     METALS	   457
       4.10.1   Introduction	,	   457
       4.10.2   Water Quality Criteria, Bd:
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Chapter
       5.7.2     Stratification	    Ill
       5.7.3     Sedimentation	    115
       5.7.4     Eutroph1cat1on	    123
       5.7.5     Hypo11mnet1c DO  Depletion  	    128
       5.7.6     Toxicants	    133

       REFERENCES	    136

       GLOSSARY OF  TERMS	    139

  6    ESTUARIES	    142

       6.1       INTRODUCTION	    142
       6.1.1     General	    142
       6.1.2     EstuaMne  Definition	    143
       6.1.3     Types  of Estuaries	    143
       6.1.4     Pollutant  Flow In  an  Estuary	    145
       6.1.5     Estuarlne  Complexity  and Major  Forces  	    149
       6.1.6     Methodology Summary	    151
       6.1.7     Present Water-Quality Assessment	    153

       6.2       ESTUARINE  CLASSIFICATION	    155
       6.2.1     General	    155
       6.2.2     Classification Methodology	    155
       6.2.3     Calculation Procedure 	    155
       6.2.4     Stratification-Circulation  Diagram  Interpretation  ....    157
       6.2.5     Flow Ratio Calculation	    163

       6.3       FLUSHING TIME CALCULATIONS	    165
       6.3.1     General	    165
       6.3.2     Procedure	    165
       6.3.3     Fraction of Fresh  Water Method	    170
       6.3.4     Calculation of Flushing Time  by Fraction  of  Freshwater
                Method	    171
       6.3.5     Branched Estuaries and the  Fraction of  Freshwater
                Method	    176
       6.3.6     Modified Tidal Prism  Method 	    176

       6.4       FAR FIELD  APPROACH TO POLLUTANT DISTRIBUTION IN
                ESTUARIES	    184
       6.4.1     Introduction	    184
       6.4.2     Continuous Flow  of Conservative Pollutants	    185
       6.4.3     Continuous Flow  Non-Conservative Pollutants  	    197
       6.4.4     Multiple Waste Load  Parameter Analysis	    204
       6.4.5     D1spers1on-Advect1on  Equations  for  Predicting
                Pollutant  Distributions 	    207
       6.4.6     PMtchard's Two-Dimensional Box Model  for Stratified
                Estuaries	    216

       6.5       POLLUTANT  DISTRIBUTION FOLLOWING DISCHARGE FROM  A
                MARINE OUTFALL	    226
       6.5.1     Introduction	    226
       6.5.2     Prediction of  Initial  Dilution	    227
       6.5.3     Pollutant  Concentration Following Initial  Dilution.  ...    248
       6.5.4     pH  Following Initial  Dilution 	    250
       6.5.5     Dissolved  Oxygen Concentration  Following  Initial
                Dilution	    255

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Chapter                                                                     Page


       6.5.6    Far Field Dilution and Pollutant Distribution 	   257
       6.5.7    Farfield Dissolved Oxygen Depletion 	   263

       6.6      THERMAL POLLUTION 	   266
       6.6.1    General	   266
       6.6.2    Approach	   267
       6.6.3    Application	   269

       6.7      TURBIDITY	   274
       6.7.1    Introduction	   274
       6.7.2    Procedure to Assess Impacts of Uastewater Discharges
                on Turbidity or Related Parameters	   276

       6.8      SEDIMENTATION	   282
       6.8.1    Introduction	   282
       6.8.2    Qualitative Description of Sedimentation	   282
       6.8.3    EstuaMne Sediment Forces and Movement	   283
       6.8.4    Settling Velocities 	   287
       6.8.5    Null Zone Calculations	   291

       REFERENCES	   295

  7    GROUND WATER	   300

       7.1      OVERVIEW	   300
       7.1.1    Purpose of Screening Methods	   300
       7.1.2    Ground Water vs. Surface Water	   301
       7.1.3    Types of Ground Water Systems Suitable for Screening
                Method	   302
       7.1.4    Pathways for Contamination	   303
       7.1.5    Approach to Ground Water Contamination Problems  	   305
       7.1.6    Organization of This Chapter.	   309

       7.2      AQUIFER CHARACTERIZATION	   310
       7.2.1    Physical Properties of Water	   310
       7.2.2    Physical Properties of Porous Media 	   310
       7.2.3    Flow Properties of Saturated Porous Media 	   319
       7.2.4    Flow Properties of Unsaturated Porous Media  	   323
       7.2.5    Data Acquisition or Estimation	   329

       7.3      GROUND WATER FLOW REGIME	   345
       7.3.1    Approach to Analysis of Ground Water Contamination
                Sites	   345
       7.3.2    Water  Levels and Flow Directions	   346
       7.3.3    Flow Velocities and Travel Times	   353

       7.4      POLLUTANT TRANSPORT PROCESSES 	   363
       7.4.1    Dispersion and Diffusion	   363
       7.4.2    Chemical and Biological Processes Affecting  Pollutant
                Transport	   374

       7.5      METHODS FOR PREDICTING THE FATE  AND TRANSPORT OF
                CONVENTIONAL AND TOXIC POLLUTANTS 	   382
       7.5.1    Introduction to Analytical Methods	   382
       7.5.2    Contaminant Transport to Deep Wells	   390
       7.5.3    Solute  Injection Wells:  Radial  Flow	   396
                                       -x-

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Chapter
Page
7.5.4

7.5.5
7.5.6

7.6
7.6.1
7.6.2
7.6.3
Contaminant Release on the Surface with 1-D Vertical

Two-Dimensional Horizontal Flow with a Slug Source. . . .
Two-Dimensional Horizontal Flow with Continuous

INTERPRETATION OF RESULTS ..... 	

Quantifying Uncertainty 	
Guidelines for Proceeding to More Detailed Analysis . . .
REFERENCES 	
References Sited 	
Additional References on Ground Water Sampling 	
APPENDIX A.
APPENDIX B.
APPENDIX C.
APPENDIX D
APPENDIX E
APPENDIX F
APPENDIX G
APPENDIX H
APPENDIX I
APPENDIX J



IMPOUNDMENT THERMAL PROFILES 	
MODELING THERMAL STRATIFICATION IN IMPOUNDMENTS 	
RESERVOIR SEDIMENT DEPOSITION SURVEYS 	
INITIAL DILUTION TABLES 	
EQUIVALENTS BY COMMONLY USED UNITS OF MEASUREMENTS. . . .
ADDITIONAL AQUIFER PARAMETERS 	
MATHEMATICAL FUNCTIONS 	

403
410

417
423
423
424
429
435
435
444
A-l
B-l
C-l
0-1
E-l
F-l
G-l
H-l
1-1
J-l
                                     -xl-

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                                 LIST OF FIGURES
                                      PART I
Figure                                                                      Page
II-l     Environmental Fate of a Toxic Pollutant	     6
IIr2     Spedatlon, Transport and Transformation Processes 1n the
         Aquatic Environment	    25
11-3     Flow System Representations	    27
II-4     Isotherms for Adsorption of a Hydrophobic Pollutant on
         Sediments	    49
11-5     Relationship Between K   and Octanol-water Partition
         Coefficient ( KQW) of Energy-related Organic Pollutants	    52
II-6     Correlation of Aqueous Solubility with Octanol-water Partition
         Coefficient	    53
II-7     Relationship Between KQC and KQW for Coarse Silt	    54
II-8     Range of Validity of Henry's Law	    63
II-9     Schematic Representation of Volatilization from Solution Phase
         to Liquid Phase	    65
11-10    Mlcroblal Transformations of Phenoxy Herbicides	    80
11-11    Ultraviolet Absorption Spectrum of Naphthacene .... 	    98
11-12    Spectral Distribution of Solar Energy Outside the Earth's
         Atmosphere and At the Earth's Surface	    99
11-13    Solar Radiation 1n the United States 	   101
11-14    Photochemical Pathways of an Excited Molecule	   107
11-15    Direct Photochemical  Reactions of 2,4-0 Ester,
         Benz(a)anthracene, and Pentachlorophenol 	   108
11-16    Comparison of Solar Irradiance with the Absorption Spectra
         of a Compound Which Does Not Directly Photolyzt, a Compound
         Which Does Directly Photolyze, and a Substance Which
         Initiates Indirect Photochemical Reactions 	   110
11-17    Chromophrolc Groups which Absorb Sunlight	   114
11-18    Major Processes which Influence Photolysis of Pollutants 1n
         Natural Waters 	   115
11-19    pH Dependence of Hydrolysis Rate Constants	   131
III-l    Background Concentrations of Nitrate-Nitrogen, BOD, Total
         Phosphorus, and Dissolved Solids 	   144

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Figure                                                                       Page






111-2    Background Levels of pH, Suspended Sediment, Total Conforms.

III-3

III-4

III-5

III-6
III-7
III-8
III-9

111-10
III-ll
111-12
111-13

111-14
111-15
111-16
111-17
111-18
111-19
1 1 1-20
111-21
111-22

111-23
111-24
111-25
111-26

Background Concentrations of Chloride, Iron •»• Manganese,

Relationships between Streamflow Nitrogen Concentrations

Relationships between Streamflow Phosphorus Concentrations


The Nonpolnt Source Loading Process 	
SCS Curve Number Runoff Equation 	 ,
Mean Annual Row Crop Runoff 1n Inches for Selected Curve

Average Annual Eros1v1ty Indices for Eastern U.S 	 ,
Average Annual Eros1v1ty Indices for Western U.S 	
Values of "a" for Equation 1 1 1-14 	 ,
Sediment Delivery Ratio as a Function of Watershed Drainage


Phosphorus (as P20s) 1n the Surface Foot of Soil 	

Collection of Irrigation Drainage 	 	

Mean Annual Precipitation 1n Inches 	
Conceptual Model of Depression Storage 	 ,

Mean Annual Potential Evapotranspl ration Minus Precipitation
1n Inches 	 	


Nitrogen ( NH4-N and NO^-N) 1n Precipitation 	 ,

145

, 146

147

148
. 149
. 151
. 154

, 159
, 162
163
175


182
182
209
210
. 211
217
. 224
. 232

. 234
, 236
243
, 247
. 254
                                      -X111-

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                                      Page
111-27

IV-1

IV-2

IV-3
IV-4

IV-5
IV-6
IV-7

IV-8

IV-9

IV-10
IV-11
IV-12
IV-13
IV-14

IV-1 5
IV-16
IV-17
IV-18

IV-1 9

1V-20
IV-21

IV-22
Influent Copper Concentrations to Wastewater Treatment
Plants as a Function of Percent Industrial Flow 	
Illustration of River Segmentation Procedure on the James
River 	
Hypothetical River Having a Variety of Pollutant Sources
and Sinks 	
River Segmentation for BOO Distribution 	
Pollutant Discharge where Initial Mixing Occurs a Fractional
Distance Across the River 	

Sketch of Snake River from Helse to Nee ley, Idaho 	
Example of Flow Rate Information Tabulated 1n U.S. Geological
Survey's Water Data Report 	 	
Example Set of User's Instructions for Hand-Held Calculator
Programs 	 	 	
The BOO Curve for Oxidation of Carbonaceous Hatter and Curve




Hypothetical BOD Waste Loadings 1n a River 	
Variability of Dissolved Oxygen by Season for 22 Major Water-
ways, 1968-72 	
Reaeratlon Coefficient as a Function of Depth 	
Reaeratlon Coefficient for Shallow Streams, Owen's Formulation .

Characteristic Dissolved Oxygen Profile Downstream from a

Flow Process of Solution to Dissolved Oxygen Problem 1n

Dally Dissolved Oxygen Variation 1n Two Rivers 	
Flow Process 1n Reach by Reach Solution to Critical Dissolved

Hypothetical River Used in Example IV-9 	

262

291

292
293

295
300
302

304

307

310
311
312
313
318

322
325
326
327

335

336
o43

349
353
-x1v-

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IV-23    Mechanisms of Heat Transfer Across a Water Surface 	    356

IV-24    Schematic of Site No.  3 Cooling Lake	    357

IV-25    Observed Temperatures, Site No. 3, July 18-July 24>  1965 ....    358

IV-26    Comparison of Computed Equilibrium and  Ambient  Temperatures
         with Observed Mean Diurnal  Temperature  Variations  for Site
         No,  38 July 18-July 24, 1966	    359

IV-27    Mean Daily Solar Radiation  Throughout the U.S.  for July
         and  August	    361

IV-28    Mean Dewpoint Temperature Throughout the United States for
         July and August	    368

IV-29    Mean Daily Wind  Speeds ( mph) Throughout the United States
         for  July and August	    369

IV-30    Idealization of  a Run-of-the-River Power Plant  	    372

IV-31    Downstream Temperature Profile for Completely Mixed  Stream,
         T-E/Tm_E vs. r	    382

IV-32    Measured Air and Water Temperatures for the Santa Ana River
         near Mentone, California, In June 1979	   384

IV-33    Measured Dissolved Oxygen Concentration and Predicted Satur-
         ation Concentration for the Santa Ana River near Mentone,
         California 1n June 1979	   385

IV-34    Flow Duration Curve, Hatchie River at Bolivar,  Tenn	   386

IV-35    Frequency of Lowest Mean Discharges of Indicated Duration,
         Hatchie River at Bolivar, Tenn	   387

IV-36    Three River Temperature Profiles  	   388

IV-37    Total Collfonn Profiles for the Willamette River	   397

IV-38    Salinity Distribution 1n a Hypothetical River	   401

IV-39    Division Between Wash Load and Bed Material Load	   404

IV-40    *  and  T  for DuBoys Relationship as Functions of Median
         Size of Bid Sediment	   406

IV-41    Hydraulic Rad11  for Different Channel Shapes 	   409

IV-42    User Instructions for Yang's Sediment Transport Equation ....    412

IV-43    Program Listing  and Sample Input/Output for Yang's Sediment
         Transport Equation 	    413

IV-44    Sediment Discharge as  a Function of Water Discharge  for the
         Colorado River at Taylor's  Ferry 	    416
                                      -xv-

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Figure                                                                      Page


IV-45    Sediment Discharge as a Function of Water Discharge for the
         Nlobrara River at Cody, Nebraska 	   416

IV-46    Toxicant Concentrations Following Initiation and Cessation of
         Point Source	   421

IV-47    Vertical Equilibrium Distribution of Suspended Solids 1n a
         River	   422

IV-48    Vertical Distribution of Relative Solute Concentration,
         K S  - 10	   424
          P a
IV-49    Vertical Distribution of Relative Solute Concentration,

         Va " 10°	   42A

IV-50    Instrean Transformation Processes Analyzed for Toxicants ....   430

IV-51    Location Hap of Hudson River, New York	   437

IV-52    Hypothetical Concentration Distributions of Finitely Soluble
         and Infinitely Soluble Toxicants 	   440

IV-53    Hypothetical Distribution of Toxicant at Various Locations
         Following a Spill	   443

IV-54    Illustration of Hypothetical Spill  Incident	   447

IV-55a   Chloroform Concentration 1n Water Column for First 60 Hours
         Following a Spill 16.3 Miles upstream	   453

IV-556   Chloroform Concentration In the Mississippi River at a Location
         16.3 Miles Below the August 19. 1973 Spill 	   454

IV-56    Summary of Screening Procedures for Metals 1n Rivers 	   459

IV-57    Measured Total and Dissolved Coooer Concentrations 1n Flint
         River, Michigan, During August  . J81 Survey	   470

IV-58    Extent of Priority Pollutant Contamination 1n Chattanooga
         Creek Waters	   471

IV-59    Comparison of Observed and Predicted Mercury Concentration
         Calculated from a Dilution Model for the North Fork Ho1ston
         River	   474

IV-60    Station Locations on Coal Creek and Slate River, Colorado. ...   476

IV-61    Physical Processes Influencing the Fate of Metals 1n Rivers. .  .   483

IV-62    Relationship Between Stream Velocity, Particle Size, and
         the Regimes of Sediment Erosion, Transport, and Deposition . .  .   486

IV-63    Comparison of Predicted and Observed Total Metal Concentrations
         1n Flint River. Michigan (August 1981)	   490

IV-64    Total Z1nc, Copper, and Cadmium 1n the Hint River	   491
                                      -xv1-

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                                                                            Page
IV-65    Framework for River Model  MICHRIV	    493
IV-66    Suspended Sol Ids  and Total  Metal  Concentrations  1n  the  Flint
         River,  Michigan,  (March  1982)	    504
IV-67    Suspended Sol Ids  and Total  Metal  Concentrations  In  Flint  River,
         Michigan (August  1981)	    508
IV-68    Definition Sketch of Idealized Reservoir 	    511
IV-69    Definition Sketch Used  1n  Example IV-23	    514
IV-70    Relationship Between Metal  Concentration 1n  Water Column  and
         1n Bedded Sediments During a NonequlHbMum  Adsorption  Period.  .    517
IV-71    River System for  Example IV-24 	    521
IV-72    Spedatlon of Metals 1n  the Aquatic Environment	    526
IV-73    Relative Characterizations of  Environments by  pe and  pH	    527
IV-74    Activity Coefficient and Ionic Strength Relatloi.nips for
         Typical  Ions and  Specific  Ions	    529
IV-75    Ionic Strength Versus Specific Conductivity  for  Surface Waters  .    530
IV-76    Typical  Adsorption Curves  for  Metal Cations  and  Anions  for a
         Range of pH and Adsorbent  Levels	    534
IV-77    Partition Coefficient for  Copper  1n Streams	    538
IV-78    Periodic Table of the Elements	    540
IV-79    pe/pH Stability Field Diagram  for Arsenic at 25°C	    542
IV-80    Cadmium Spedatlon as a  Function  of pH 1n the  Presence  of
         1.55 m2/l S102(s), Cdt  « lO"6*!	    544
IV-81    pe/pH Diagram Showing Stability of Chromium  Species for
         Crt - IO-SM	    545
IV-82    pe/pH Diagram Showing Areas of Dominance of  Five Species  of
         Copper  at Equilibrium at 25°C  and 1 atm	    546
IV-83    Copper  Spedatlon 1n the Presence of Inorganic Ugands; and
         1n the  Presence of Inorganic Ugands and an  Adsorbing Surface,
         1.55 m2/l S102(s)	    547
IV-84    Effect  of Humlc Add on  Partitioning of Copper	    549
IV-85    Lead Spedatlon 1n the  Presence of Inorganic Llgands; and
         1n the  Presence of Inorganic Llgands and a Solid Adsorbing
         Surface, 1.55 m2/l S102(s)	    550
IV-86    The pe-pH Diagram for Hg,  Showing Predominant  Species 1n
         Solution for Concentrations of Total  Hg Greater  than  5  ug/1.  .  .    551

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Figure                                                                      Page

IV-87    Nickel Carbonate and Nickel Hydroxide Solubility Phase Diagram     553
IV-88    Zinc Spec 1 at 1 on 1n the Presence of Inorganic Ugands and an
         Adsorbing Surface	   554
IV-89    Zinc Solubility:  Z1nc Hydroxide; Zinc Carbonate; and Zinc
         Silicate	   555
IV-90    Water Resources Regions of the United States 	   557
IV-91    Example Procedure for Superposition of Adsorption	   592
                                      -XV111-

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                                 LIST OF TABLES



                                     PART I






Table                                                                       Page
II-l
II-2

II-3

1 1-4
II-5
1 1-6
II-7

II-8
II-9

11-10
11-11

11-12

11-13

11-14

11-15
11-16

11-17
11-18
11-19

11-20

11-21


Proposed Criteria for Toxic Substances Designated to Protect
Aquatic Life 	
EPA List of 129 Priority Pollutants and the Relative Frequency
of These Materials in Industrial Wastewaters 	
Most Commonly Discharged Priority Pollutants 	
Selected Characteristics of Various Aliphatic Hydrocarbons . . .
Various Characteristics of Selected Pesticides 	
Selected Characteristics of Polychlorlnated Blphenyls and

Selected Characteristics of Monocyclic Aromatic Hydrocarbons . .
Selected Characteristics of Various Polycyclic Aromatic
Hydrocarbons 	
Expressions for Toxic Pollutant Levels In Various Water Bodies .
Relative Importance of Processes Influencing Aquatic Fate of
Organic Priority Pollutants 	
Occurrence of Acids and Bases 1n Neutral and Charged Forms as

pKa and pKb Values for Selected Toxic Organic Acids and
Bases and Vaues of pK* for Water 	
Procedure for Calculating Fraction of a Compound which Is In

Procedure for Calculating Partition Coefficient 	
Relationship of Dissolved and Sorbed Phase Pollutant Concentra-
tions to Partition Coefficient and Sediment Concentration. . . .
Henry's Law Constant for Selected Hydrocarbons .... 	
Henry's Law Constants for Selected Compounds 	
Typical Values of Pollutant Volatilization Rates in Surface
Waters 	
Comparison of Tabulated and Predicted Values of Diffusion
Coefficients for Selected Pollutants 	
Volatilization Rates of Several Priority Pollutants 1n
12 Rivers 	
6

8

16
17
19
20

21
22

23
30

33

44

45

47
55

56
62
69

69

70

73
                                      -xlx-

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Table                                                                       Page

11-22    Procedure for Predicting Volatilization Rate 	    74
11-23    Relative Volatilization Mass Fluxes of Several  Chemicals  1n
         Saturated Solutions	    77
11-24    Size of Typical  Bacterial  Populations 1n Natural  Waters	    84
11-25    Summary of the Characteristics of the Two General  Types of
         B1odegradat1on:   Metabolism and Cometabol 1 six	    85
11-26    Potential B1odegradab1l1ty of Organic Pollutants  1n an Aerobic
         Environment	    88
11-27    B1odegradat1on Rate Constants under Aerobic Conditions 	    90
11-28    Calculated Solar Radiant Energy Flux to a Horizontal  Surface
         under a Clear Sky	   100
11-29    Calculated Solar Irradiance In a Water Body Just  Beneath  the
         Surface, Annual  Mean at 40°N	   102
11-30    Contributions to Light Attenuation Coefficient  	   105
11-31    Disappearance Quantum Yields, *
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Table                                                                       Page

III-6    C Factor Values for Permanent Pasture, Range and Idle Land . .  .   169
111-7    C Factor Values for Undisturbed Forest Land	   170
UI-8    C Factor Values for Mechanically Prepared Woodland Sites ....   171
III-9    Practice Factors (P) Used 1n Universal Soil Loss Equation. ...   172
111-10   Expected Magnitudes of Single-Storm Eros1v1ty Indices	   173
III-ll   Heavy Metal  Concentrations 1n Surflclal Materials in the United
         States	   183
111-12   Representative Dissolved Nutrient Concentrations 1n Rural
         Runoff	   188
II1-13   Mean Bulk Densities and Available Water Capacities 	   195
II1-14   Organic Carbon Partition Coefficients for Selected Pesticides.  .   195
111-15   Octanal-Water Partition Coefficients for Selected Pesticides .  .   197
111-16   Mean First Order Decay Coefficients for Selected Pesticides. .  .   198
111-17   First Order Pesticide Decay Coefficients for Selected
         Pesticides and Soil Conditions	   199
111-18   Mean Daylight Hours per Day	   213
II1-19   Saturation Vapor Pressure as Function of Temperature 	   214
111-20   Pollutant Concentration Factors for Annual Loading Functions .  .   218
111-21   Runoff Curve Numbers (Antecedent Moisture  Condition  II)  for
         Urban Areas	   222
II1-22   Urban Sediment (Solids) Accumulation Rates	   226
II1-23   Concentrations of  Conventional Pollutants  in Urban Sediment. .  .   228
II1-24   Concentrations of  Metal in Urban Sediment	   228
111-25   Concentrations of  Mercury and Organic Compounds  in Urban
         Sediment	   229
II1-26   Typical Values of  Crop Nitrogen Uptake  	   238
111-27   Mean Soil Properties	   24?
111-28   Atmospheric Contributions of Nitrogen and  Phosphorus In
         Precipitation	   246
II1-29   Field-Measured Dry Deposition Velocities 	   249
111-30   Average Monthly Atmospheric Levels of Four Pesticides
         at Storteville, Mississippi	   252
                                       -xx1-

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Table                                                                       Page

111-31   Typical  Influent Municipal  Waste Concentrations	   255
111-32   Municipal  Hastewater Treatment System Performance	   256
111-33   Median and Mean Phosphorus  and Nitrogen Concentrations
         and Median Loads 1n Wastewater Effluents Following Four
         Conventional  Treatment Processes 	   257
111-34
111-35
111-36
111-37
111-38
111-39

Metal Concentrations and Removal Efficiencies in Treatment
Plants at Selected Cities 	
Influent Variability Analysis at Moccasin Bend Wastewater
Selected Pollutant Mass Percent Removals at Moccasin Bend
1981 Effluent Concentrations from Five Southern California
Occurrence of Priority Pollutants 1n POTW Influents and
259
260
263
264
265

         Effluents for Pollutants Detected 1n at Least 10 Percent
         of the Samples	   266
111-40   Median Percent Removals of Selected Pollutants through POTW
         Treatment Processes	   269
111-41   Industrial  Categories and Frequently Detected Priority
         Pollutants  by Category	   271
IV-1      Reference Level Values of Selected Water Quality Indicators
         for U.S. Waterways	   279
IV-2      Condition of Eight Major Waterways 	   280
IV-3      Water Quality Problem Areas Reported by States 	   282
IV-4      Example River Water Quality Standards	   283
IV-5      Water Quality Parameters Commonly Monitored by States	   284
IV-6      Annual Phosphorus and Nitrogen Load for Selected Iowa River
         Basins	   285
IV-7      Major Waterways:  Seasonal Flow Analysis. 1968-72	   288
IV-8      Water Quality Analyses for River Screening Methodology 	   289
fV-9     Experimental Measurements of Transverse Mixing 1n Open Channels
         with Curves and Irregular Sides	   297
IV-10    Suggested Configuration for Water and Nutrient Balance Table .  .   299
IV-11    Solution to Snake River Water and Phosphorus Balance Problem .  .   305

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Table                                                                        Page
IV-12
IV-13

1V-14
IV-15
IV-16
IV-17
IV-18
IV-19

IV-20
IV-21
IV-22
IV-23
IV-24

IV-25
IV-26

IV-27
IV-28

IV-29
IV- 30

IV-31
IV-32
IV-33

IV-34
IV-35

Municipal Waste Characteristics Before Treatment 	
Comparison of Predicted and Observed Reaeration Rates on Small

Typical Hydraulic Properties, Patuxent River 	
Solubility of Oxygen 1n Water 	
Dissolved Oxygen Saturation Versus Temperature and Altitude. . .
0 /L. Values Versus D./L and k,/K, 	
CO Q Q Q L.
Vc Versus °o/Lo and ka/kL 	
Some Average Values of Gross Photosynthetlc Production of

Average Values of Oxygen Uptake Rates of River Bottoms 	
Compilation of Information In Example IV-8 	
Critical Travel Time Results 	
Net Long Wave Atmospheric Radiation, H 	
an
Saturated Water Vapor Pressure, e , Versus Air Temperature,
T , and Relative Humidity. .... 	
a
B and C(B) as Functions of Temperature 	
Summary of Solar-Radiation Data for Mlneola, Brookhaven, and
the Connetquot River Sites 	

Eutrophl cation Potential as a Function of Nutrient

Regional Stream Nutrient Concentration Predictive Models ....
Total Nitrogen Distribution 1n a River in Response to Point
and Non-Point Source Loading . 	
Total CoHfonm Analysis 	
Salinity Distribution in a Hypothetical River 	
Relationship of Total Suspended Sediment Concentration to
Problem Potential 	
Sediment Grade Scale 	
Computing 0/T for Determining the Hydraulic Radius of a
Parabolic Section 	
308

328
329
332
333
338
339

342
347
350
352
362

363
364

365
374

390
393

395
397
402

404
407

408
                                     -XX111-

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Table                                                                       Page
 IV-36    Relationship Bet**en Width to Depth Ratio of a Graded Stream
         and the Suspended and Bed Load Discharge	   409

IV-37    Characteristics of  the  Colorado  and Nlobrara Rivers	    415

IV-38    Methods of Introduction of Toxic Organic Compounds Into
         Rivers, and Fate 1n Terms of  Volatilization  and Sorption ....    418

IV-39    Mass of Contaminated Sediments and Equivalent Water Depth as
         a  Function of Depth of  Contamination	    436

IV-40    Water-Soluble,  High Density (p > 1), Immiscible Chemicals. ...    445

IV-41    Water Quality  Criteria  for Selected Priority Metals for
         Protection of Freshwater Aquatic Life	    460

IV-42    Typical Concentrations  of Metals in Several  Soils and in the
         Earth's Crust	    462

IV-43    Average Concentration of Metals  in Various  Types of Rock and
         Deep Ocean Sediments	    463

IV-44    Ranges of Concentrations of Dissolved  Minor Elements Measured
         at NASQAN Stations  During the 1975 Water rear, Summarized by
         Water Resources Regions	    465

IV-45    Ranges of Total Concentrations of Minor Elements Measured at
         NASQAN Stations During  the 1975 Water  Year,  Summarized by
         Water Resources Regions	    466

IV-46    Summary of Case Studies	    468
                                                         •
IV-47    Summary of Metal and Suspended Solids  Concentrations in
         Flint River, Michigan	    469

IV-48    Inorganic Priority  Pollutants Detected in Chattanooga Creek,
         September 1980	    472

IV-49    Mercury Concentrations  in Water, Suspended  Matter, and Bed
         Sediments Immediately Upstream and Downstream of Former
         Chi oral kali Plant on North Fork  Ho Is ton River	    473

IV-50    Strews Selected for 1980 U.S. EPA Field Surveys and Metals
         Anticipated to be Present in  Excess of U.S.  EPA Recommended
         Aquatic Life Criteria	    475

IV-51    Comparison of Mean  Total Concentrations of Selected Metals
         in the Slate River  Versus U.S. EPA Calculated Acute Water
         Quality Criteria for Aquatic  Life	    477

IV-52    Metal  Concentrations in Bottom Sediments of Saddle River.
         New Jersey, and In  Adjacent Soils	    478
                                      -xxiv-

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Table                                                                       Page
IV-53

IV-54

IV-55

IV-56

IV-57

IV-58
IV-59
IV-60
IV-61

Average Heavy Metal Concentrations by Particle Size for
Sediments of the Saddle River, New Jersey 	
Lead Concentrations in Streams Tributary to Cayuga Lake,
New York 	
Summary of Cadmium, Zinc, and Copp«r 1n Partlculates Carried

Summary of Soluble Cadmium, Z1nc, and Copper 1n Tributary
Streams of Cayuga Lake 	
Boundary Conditions and Point Sources to Flint River for
August 4-7, 1981 	
Summary of Screening Procedures for Metals 1n Rivers and Lakes .
Source Data Required for Example IV-24 	
Summary of Results of Example IV-24 	
Linear Partition Coefficients for Priority Metals 1n Streams


479

480

481

482

489
499
521
522

536
IV-62    Speciation of Priority Metals Between Dissolved and Adsorbed
         Phases as a Function of Suspended Sol Ids Concentrations in
                                                                            537
IV-63


tV-64
IV-65
IV-66
IV-67
IV-68
IV-69
IV-70
IV-71
IV-72
IV-73
IV-74
IV-75
IV- 76
Summary of Metal Speciation in Oxidizing and Reducing
Environments, Solids Controlling Solubility, and pH-pe
Combinations Conductive to Metal Mobilization 	
Characteristics of River Waters Chosen for Analysis 	
Metal Speciation in the Hudson River 	
Metal Speciation in the Ogeechee River 	

Metal Speciation In the Ohio River 	
Metal Speciation 1n the Mississippi River 	
Metal Speciation 1n the Missouri River 	
Metal Speciation in the Brazos River 	
Metal Speciation In the Columbia River 	
Metal Speciation 1n the Sacramento River 	

Metal Speciation In Woods Lake Outlet 	
Metal Speciation In Penobscot River, Maine 	


541
558
, , 560
562
564
567
569
. . 572
. . 575
. . 577
. . 579
. . 581
. . 584
. . 585
                                      -XXV-

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Table                                                                       Page

IV-77    Me':i  Spec1at1on 1n  St. Harys River, Florida	   587
IV-78    Metal  Spec 1 at 1 on in Grand River, South Dakota	   588
IV-79    Metal  Speclatlon in Pecos River, New Mexico	   589
IV-80    Summary of Data Requirements for Screening of Metals 1n Rivers  .   599
                                      -xxvl-

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                             ACKNOWLEDGEMENTS

     This publication 1s the result of the labors  of a number of Individuals
who contributed to both this document and the previous editions.  Majo.r
contributors to previous editions are David Dean (waste loadings), Walter
Prick (estuaries), Kendall  Haven (estuaries), Robert Hudson (organic  toxicants),
and Stanley Zlson (lakes).   JACA Corporation designed a new, condensed format
and prepared all text and artwork for this third edition.
     In addition, all of the Individuals 1n the U.S. EPA who supported this
work, especially Mr. Tom Barnwell, Ms. Carol Grove,  Mr. Bill Vocke, Dr. James
Falco, Mr. Orvllle Macomber, and Mr. Robert Ambrose, must  be thanked  for
their Input, consideration, and patience.
                                -xxv11-

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                                 CHAPTER  1

                                INTRODUCTION
 1.1   BACKGROUND
      In  1977, the United States Environmental Protection Agency published Mater
Quality  Assessment:  A Screening Method for Mondesignated 208 Areas (Z1son, e_t a]_.,
1977).   This document was Intended as a simplified methodology that Mater quality
planners in nondeslgnated 208 areas could use to perform preliminary assessments of
surface  water quality.  The methods addressed both point and nonpolnt sources of
pollutants Including nutrients, sediments, dissolved oxygen deficits, temperature,
salinity, and conforms 1n rivers, lakes, and estuaries.  The methodology was applied
to the Sandusky River 1n northern Ohio, to the Ware, Patuxent, and Chester Rivers 1n
Virginia and Maryland, and to the Occoquan Reservoir 1n Virginia.  Test results were
favorable (Dean et_ _aj_., 1981). and some urban pollutants 1n streams, lakes and estuaries.
       In 1982 the screening methods were revised and updated to Include toxic organic
chemicals 1n surface waters (Mills Q £l_., 1982).  The methods were demonstrated for
a formaldehyde spill 1n the Russian River, California (Mills and Porcella, 1983), and
for synfuel contamination of rivers (Mills and Porcella, 1984).

1.2  PURPOSE AND SCOPE
       Due to Increased emphasis on contaminant transport 1n ground waters and on
contamination by heavy metals In all natural  waters, the screening methods have been
expanded to address these Issues.  This report contains a simplified methodology which
can be used by planners or engineers to perform preliminary assessments of toxic and
conventional  pollutants 1n surface and ground waters.  Conventional pollutants Include
suspended sediments, nitrogen, phosphorus, conform bacteria, BOD, temperature, and
dissolved oxygen deficits.  The 129 EPA priority pollutants are Included 1n the sections
on toxic chemicals.  Much data are supplied by figures and tables 1n the text and
appendices.  An additional source of data for many rate constants used 1n this manual
1s Bowie et_^i-. 1985.  All  the algorithms are Intended to be used on desk-top calcu-
lators, or on microcomputers.  Many of the environmental chemistry, ground water, and
river algorithms have been put on microcomputer (Mills •££!... 1985).
     Where Instructive, Introductory material has preceded the actual  presentation of
water quality assessment methodologies.  This 1s aone to orient the planner toward
pertinent background material, as well as to clearly state limitations of the method-
ologies due to assumptions and simplifications.  Further, example calculations are
Included to Illustrate the Ideas being presented.  These examples are designed
to unify the theory that has preceded 1t, as well as 1n some cases to Introduce
new but  related Ideas.
                                       -1-

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     The units most commonly used in this report are those that  historically
appear in the literature.  Often, the units are not metric.  Consequently  an
English-metric-conversion appendix is included at the end of this  report.
Many equations are presented with both English and metric constants.
     The report is divided into six major chapters (two through  seven).  A brief
description of the content of each chapter Is presented in the following paragraphs:
        •    Chapter 2 deals with the environmental chemistry of toxic organic
             chemicals.  Processes considered Include photolysis,  hydrolysis,
             volatilization, blodegradation and adsorption. The  purpose of the
             chapter 1s to provide an understanding of the processes and to provide
             procedures for estimating associated rate and equilibrium constants.
        •    Chapter 3 addresses methods to estimate pollutant loads from nonpoint
             and point sources for both toxic and conventional pollutants.  Pro-
             cedures include load estimation for single events and annual  loads from
             agricultural, forested, and urban areas.
        •    In Chapter 4, impacts of point and nonpoint sources of conventional and
             toxic pollutants in rivers are addressed. Conventional  pollutants
             include BOO-00, temperature, coll form bacteria, nutrients, and sediment
             transport.  Fate of toxic organic chemicals is assessed with consider-
             ation being given to the Importance of volatilization, sorption and
             first order degradation.  Metals are also assessed, and emphasis is
             given to nine priority metals.  MINEQL 1s used to predict aqueous
             solubility and sped at ion of the metals in natural  waters around the
             country.  Methods are also presented to handle large spills of toxic
             chemicals having density the same as or different from the receiving
             waters.
        •    Chapter 5 contains methods for assessing water quality in Impoundments.
             The topics covered are sediment accumulation, thermal stratification,
             BOD-DO Interactions, eutrophication, and fate of toxic materials.  The
             physical/chemical processes governing the fate of toxicants as well as
             biological uptake and bioconcentration are considered.
        •    In Chapter 6, methods are presented for estuary classification, flushing
             time prediction, and transport of conservative and non-conservative
             pollutants and dissolved oxygen in we11-mixed estuaries.  For stratified
             estuaries, Prltchard's box model 1s used to determine the distribution
             of conservative materials.  Additionally, methods are presented to
             calculate Initial dilution from a waste water discharge and pollution
             distribution at the completion of and subsequent to Initial dilution.
        •    Chapter 7 presents the methodology necessary to predict the transport
             and fate of ground water contamination from typical sources.  Sets of
                                        -2-

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             tables are provided to give representative values and methods of measure-
             ment for the required ground Mater hydrology and transport parameters.
             In addition, five analytical models are presented with worked out
             examples to show how contaminant sources such as solute Injection wells,
             leaky ponds, landfills, and spills can be handled.

1.3  METHODOLOGY APPLICATION
     For each category 1n the methodology, the six conceptual steps shown below can
be followed to screen a river basin:
        t    Obtain necessary tools and data to make calculations
        t    Identify problems that are obvious from Inspection of the data
             base
        •    Determine the state variables which will be screened
        •    Apply procedures and compare where possible to observed data
        •    Consider consequences of errors
        •    Reevaluate and make recommendations for further analyses or remedial
             actions.
The techniques 1n the screening procedure are designed to Interact which
makes them Ideal  for use as an analytical tool for river basin surface waters
which may Include rivers, lakes, and/or estuaries.  Although the procedures may
Interact, they can be applied Individually and with Identified data sets for
specific case studies.

1.3.1  Base Maps
     The first step In the screening process can be to obtain large scale topographic
maps of the study area.  These can be used to determine which water bodies are to be
examined and to establish an order of study.  Once this has been done, selected small
scale (7 l/2-m1nute or 15-nrinute series) topographic sheets can be obtained.  On
these, the planner can locate and mark point source discharges, regions of specific
kinds of land use, population centers, and Industrial complexes.  Use of overlays or
push pins may be helpful  In preparing these displays.

1.4  LIMITATIONS
     The processes which govern the fate of pollutants 1n the environment are com-
plex. Any methodology, particularly one designed for hand calculation or microcomputer
applications, cannot be Inclusive of all of these processes.  An attempt has been made
1n each chapter to cover the assumptions under which algorithms are developed.  Users
should be aware of the assumptions, potential  errors, and limitations of the tools
presented.  Mien deficiencies are noted or the methods deemed Inappropriate, the user
should be prepared to use a higher level analytical  tool.

                                        -3-

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                                REFERENCES


Bowie, G.L., W.B. Hills, D.B. Porcella, C.L. Campbell, J.R. Pagenkopf, G.L. Rupp, K.M.
     Johnson, P.W.H. Chan, S.A.  Gherlnl.  1985.  Rates, Constants, and Kinetics Fortnu-
     latlons 1n Surface Water Quality Modell": (Edition 2).  For U.S. Environmental
     Protection Agency, Athens,  GA.

Dean, J.O., W.B. mils and O.B.  Porcella.  1981.  A Screening Methodology for Basin
     Wide Water Quality Management.  Symposium on Unified River Basin Management.  R.M.
     North, L.B. Dworsky and O.J. Allee, eds.  May 4-7, 1980, Gatllnburg, TN.

Mills, W.B., V. Kwong, I. Mok, and M.J. Ungs.  1985.  Microcomputer Methods for
     Toxicants 1n Ground Waters  and Rivers.  Proceedings on the 1985 Conference on
     Environmental Engineering.   American Society of C1v1l Engineers.

Mills, W.B. and O.B. Porcella.  1984.  Screening Methods for Synfuel Chemicals 1n
     Aquatic Environments.  Journal of Environmental Management, Vol. 18, pp 297-307.

Mills, W.B. and O.B. Porcella.  1983.  Screening for Organic Toxicants In Aquatic
     Environments.  Proceedings  of the 1983 National Conference on Environmental
     Engineering.  American Society of C1v1l Engineers.

Mills, W.B., J.D. Oean, D.B. Porcella, S.A.Gherlnl, R.J.M. Hudson, W.E. FHck, G.L.
     Rupp, and G.,.. Bowie.  1982.  Water Quality Assessment:  A Screening Procedure for
     Toxic and Conventional Pollutants.  Prepared for U.S. Environmental  Protection
     Agency Center for Water Quality Modeling, Environmental Research Laboratory,
     Athens. Georgia and Monitoring and Data Support Division, Office of Water Regula-
     tions and Standards, Washington, DC.  Volumes I and II.  EPA-6QO/6-82-Q04a,b,c.

Z1son, S.W., K. Haven, and W.B.  Mills, 1977.  Water Quality Assessment:  A Screening
     Methodology for Nondeslgnated 208 Areas.  U.S. Environmental  Protection Agency,
     Athens, GA.  EPA-600/9-77-023.
                                       -4-

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                                       CHAPTER 2
                        AQUATIC FATE OF TOXIC ORGANIC SUBSTANCES

 2.1   IMTRODUCTION
 2.1.1   Background
      Today's  technological society generates enormous quantities of chemicals both as
 products  for  consumption  and as waste.  As the volume and number of chemicals has
 Increased, numerous unintended adverse effects of these chemicals have been observed
 1n the  environment.  Because of the potential hazard that exposure to these compounds
 poses to  biota, the levels of toxic and carcinogenic substances 1n the environment
 have  become Important criteria for evaluating environmental quality.
      The  level, or concentration, of a toxic compound 1n the environment depends on
 the quantity  added to the environment and the processes which Influence Its fate.
 "Transport" processes tend to distribute chemicals between the atmospheric, aquatic,
 and soil  environments depending on the affinity of the compound for each phase.
 "Transformation" processes within each phase chemically alter pollutants to forms of
 lesser, equivalent, or sometimes greater toxldty.  These processes occur at rates
 which are specific to each chemical and to each environmental compartment.  The sum
 of these  processes and their Interactions, as Figure II-l Illustrates, determines the
 environmental  fate and consequent exposure of biota to a toxic pollutant.  The fate
 of toxic  substances 1n the aquatic environment 1s the concern of this chapter.  The
 algorithms presented 1n this chapter have recently been programmed on microcomputers
 (mils  et al_., 1985).
 2.1.2  Comparison of Conventional and Toxic  Pollutants
     Toxic substances frequently exhibit properties which are quite different
 from the  properties of conventional aquatic pollutants.  It 1s worthwhile to compare
 these differences in order to better appreciate the problem of analyzing Impacts of
 toxicants In  surface water systems.  Table II-l shows some of the more Important
 differences.
     Typically, one to two dozen pollutants and water quality parameters are
classified as "conventional".  Until  the past several  years, these parameters
 (e.g.  800, nutrients)  have received most of the attention of water quality
planners.   In contrast  to the small  number of conventional  pollutants there are
thousands  of toxicants  and many more synthetic chemicals art continually being
developed.  Potentially, any of these toxicants could enter the environment.
     Even though there are relatively few types of conventional  pollutants, numerous
 sources combine to routinely discharge large quantities.  However, because many
 surface water bodies have a capacity to assimilate conventional  pollutants (  e.g.
 BOO) without apparent adverse effects, this practice 1s, within limits,  both accept-
 able and  pragmatic.  Toxic substances, on the other hand, can cause adverse effects
                                          -5-

-------
               SOURCE
                               TRANSPORT AND

                               TRANSFORMATION
                                        CHEMICAL
                                        EXPOSURE
FIGURE II-l
                             ENVIRONMENTAL  FATE OF A Toxic
                             POLLUTANT (AFTER HAGUE, 1980;
                                TABLE II-l

           BRIEF  COMPARISON OF CONVENTIONAL AND TOXIC POLLUTANTS
          Conventional
                                      Toxic
One to two dozen pollutants fall  into
this category

Often large quantities  required to
produce impact (e.g.  thousands
Ibs/day)

Concentrations often  expressed as
ppm (mg/1)

Often travel in dissolved  form
Mean residence time within water
bodies often equal  to  or  less
than the mean residence time of
moving waters

Many biodegrade into harmless
substances
                             Thousands fall into this category;
                             many more being synthesized

                             Small quantities can produce
                             impact  (e.g. few Ibs/day )
                             Concentrations often expressed as
                             ppb  (ug/1), or in smaller units

                             May  be  highly sorted to suspended
                             and  bedded sediments

                             Can  reside in bedded sediments
                             for  years
                             Many  are  transformed to chemicals
                             which are also toxic; others are
                             resistant to degradation and
                             bioconcentrate
                                    -6-

-------
even at low discharge rates.
     Concentrations of conventional pollutants are most often expressed In units of
ppm (or mg/1).  Because of the small quantities of toxicants which are typically
released, concentrations are often expressed 1n the ppb (orMg/l)  range,  or In even
smaller units.  This represents at least a thousandfold difference relative to
concentrations of conventional pollutants.  However, because toxic substances present
1n small amounts can adversely Impact the environment, these small concentrations can
not always be Ignored.
     Many conventional pollutants are transported in dissolved form.  The mean
residence times of dissolved, conservative pollutants 1n a system Is equivalent to
the mean residence time of water in the system, which is:
        •    The hydraulic detention time for freshwater lakes
        •    The travel time for freshwater rivers
        •    The flushing time for estuaries.
Many toxic chemicals strongly sorb to suspended and bedded sediments and consequently
can become a part of the Immobile sediments In the bed.  The residence time of such
chemicals can be on the order of years.  Therefore, depending on the properties of
the toxicant the period of impact can greatly exceed the period of discharge (e.g., a
PCB spill may occur in a few minutes, but quantities of the PCB may remain in Immobile,
bedded, sediments for years).  Consequently the recovery period of a system can be
years.

2.1.3  Mater Quality Criteria
     As previously Indicated, toxicants are presented In the environment 1n quanti-
ties which are often measured in the ppb range.  Such small concentrations are often
foreign to many workers In the field.  When data or model  predictions contain concen-
trations In the ppb range, the significance of the toxicant level 1s not always
obvious (I.e., there 1s no "feel" as to whether the concentration 1s large or small).
Proposed criteria for toxic substances can serve as a basis to gauge the significance
of observed or predicted levels.  Table 11-2 shows proposed criteria for numerous
toxicants.  Since proposed criteria evolve over time the criteria shown 1n the table
are not necessarily the most current.  Nevertheless, their function remains:  to
provide a comparison with levels observed or predicted 1n real systems.  The data in
these tables come from the "Red Book" (U.S. EPA, 1976) and the Federal Register,
March 15, 1979; July 25, 1979; October 1, 1979; and November 28, 1980.  Criteria
designed to protect human health, for'levels of toxicants  In domestic water supplies,
are available from these same sources as well.

2.1.4  Frequency of Discharge of Toxic Substances from Industries
     Numerous organizations, Including the U.S. Department of Transportation and the
U.S. Environmental Protection Agency, continually collect  and analyze data on the

                                          -7-

-------
                    TABLE 11-2



PROPOSED CRITERIA FOR TOXIC SUBSTANLlS DESIGNATED



           TO PROTECT AQUATIC LIFE

Acenaphthene
Acroleln
Acrylon1tr1le
Aldr1n/D1eldr1n
Ant1*ony
Arsenic
Asbestos
Benzene
Benzldlne
Berylllw
CadriuM
Carbon Tetrachlorlde
Chlordane
Chlorinated benzenes
Chi orobenzene
1,2,4 - Trlchl orobenzene
1,2,3,5 - Tetrachl orobenzene
1,2,4,5 - Tetrachl orobenzene
Pentachl orobenzene

24 Hour
Average
LD»
•2ic
2600C
0.0019
1600
40C
LD
LD
LD
5.3C
d
620
0.0043

1500"
210"
170"
97h
16"
Freshwater
MaxlMi* "Red Book"
1700*
6fil»
7550*
2.5 0.003
9000
440*
LD
530*
2500
130* 11. -1100
e 0.4-1.2*
4.0-12.09
1400
2.4 0.01

3500"
470"
390"
220"
36"
Saline Water
24 Hour
Average
710C
LD
LD
0.0019
LD
LD
LD
700C
LO
LD
4.5
2000
0.0040

120"
3.4"
2.6"
9.6
1.3h
MaxiMM "Red Book"
970*
55*
LD
0.71 0.003
LD
504>
LO
5100*
LD
LD
59 5.0
4000
0.09 0.004

280"
7.8"
5.9"
26
2.9h
                       -8-

-------
TABLE ii-2
(Continued)

Chlorinated Ethanes
1,2 - Dichloroethane
1,1,1 - Trichloroethane
1,1.2 - Trichloroethane
1,1.1,2 - Tetrachloroethane
1,1.2,2 - Tetrachloroethane
Pentachl oroethane
Hexachloroethane
Chlorinated taphthalenes
Chlorinated Phenols
4 - Chlorophenol
2,4,6 - Tri chlorophenol
Chloroalkyl Ethers
Chlorofom
2 - Chlorophenol
Chromium (Hexavalent)
Copper
Cyanide
DDT

24 Hour
Average
,,9/1

3900*
5300*
310*
420*
170*
440*
62*
29

45
52
LD
500
60
0.29
5.6
3.5
0.00023
Freshwater
Maximum "Red Book"

8000*
12000*
710*
960*
380*
1000*
140*
67

180
150
LD
1200
180
21 100
1 J
52 5.0
0.41 .001
Saline Water
24 Hour
Average

880*
240*
LD
LD
70*
38
7.0*
2.8

LD
LD
LD
620*
LD
18
4.0
LD
0.0067h
Maximum "Red Book"

2000*
540*
LD
LD
160*
87
16*
6.4

LD
LD
LD
1400*
LD
1260
23 j
LD 5.0
0.021* .001
-9-

-------



01 chl orobenzenes
1,2 - Dlchlorobenzene
1,3 - Dlchlorobenzene
1,4 - Dlchlorobenzene
3,3' - D1chlorobenz1d1ne
01 chl oroethyl enes
1,1 - 01 chl oroethyl ene
1,2 - 01 chl oroethyl ene
2,4 - Dlchlorophenol
01 chl oropropanes and Dlchloropropenes
1,1 - Dlchloropropane
1,2 - Dlchloropropane
1,3 - Dlchloropropane
1,3 - 01 chl oropropene
2,4 - Olnethyl phenol
D1n1trotoluenes
2,3 - Olnltrotoluene
2,4 - Olnltrotoluene
1,2 - D1phenylhydraz1ne
Endosulfan


24 Hour
Average
,9/1

44
310"
190"
LO



0.4

410
920
4800
18
38

12
620
17
0.042
TABLE 11-2
(Continued)
Freshwater
Maximum "Red Book"

99
700"
440"
LO

11600
11600
110

930
2100
11000
250
86

27
1400
38
0.49 0.003

S
24 Hour
Average

15"
22"
15h
LO

224000
224000
LU

LD
400"
79
5.5"
LD

4.4"
LO
LD
LU

aline Water
Nax1«u« "Red Book"

34"
49"
34h
LO



LD

LD
910"
180
14h
LO

10"
LD
LD
LD 0.001
-10-

-------



Endrln
Enthyl benzene
Fluoranthene
Haloethers
4 - bromophenylphenly ether
Halowethanes
Chloromethane
Bromome thane
Dlchloromethane
TrlbroMomethane
Kept ac hi or
Hexachlorobutadiene
Hexachl orocycl ohexane
Llndane
Other Isomers
Hexachl orocycl opentadl ene
I sophorone
Lead
Mercury (total)



24 Hour
Average
»9/l
0.0023
LD
250"

6.2

7000
140
4000"
840*
0.0038
LD

0.080
LD
0.39
2100
k
0.2
TABLE 11-2
(Continued)
Freshwater
Maximum "Red Book"
M9/l ^g/1
0.18 0.004
LD
56U1'

14

16000
320
9000*
0.52 0.001
LD

2.0
LD
7.0
4700
1 m
4.1 0.05



24 Hour
Average
M9/1
0.0023
LD
0.30

LD

3700"
170"
^OQh
180
0.0036
LD

LD
LO
LD
97
25*>
0.10


Saline Water
Maximum "Red Book"
0.037 0.004
LD
0.69

LD

8400*
380"
4400*
420
0.053 0.001
LO

0.16
LO
LD
220
ees5
3.7 0.10
-11-

-------
TABLE 1 1 -2
{Continued}



Naphthalene
Nickel
N1 trobenzene
Nit rop he no is
2 - NUrophenol
4 - Nitropheno)
2,4 - Dlnltrophenol
2.4 - 01 nltro-6-Mthyl phenol
2.4,6 - Trlnltrophenol
N-N1 trosod 1 phenyl Ml ne
Pentachlorophenol
Phenol
Phthalate esters
Polychlorlnated blphenyls
Polynuclear aromatic hydrocarbons
Selenlm
Silver
2.3,7,8 - Tetrachlorodlbenzo-p-dloxln
Tetrachloroethene

24 Hour
Average
M9/1
LD
n
480

2700*
240*
79"
57h
1500*1
LD
6.2
600
LO
0.014
LD
35
0.0090
LO
310
Freshwater

MaxlMM "Red Book"
«q/l «'
3400^
LD
14
3400
LO 3.0
2.06 0.001
LD
260 p
1.9 p
LO
700
Saline Water
24 Hour
Average
«9/l
LD
7.1
53

LD
53
37"
LD
15C&
LD
3.7
LD
LD
0.030
LO
54
0.26

79

HaxIniM "Red Book"
0Q/1 -g/1
LD
140 p
120

LD
120
84"
LO
340^
LD
8.5
LD
LD
10* 0.001
LD
410 p
2.3 p

180
-12-

-------



Thalllua
Toluene
Toxaphene
Trichloroethene
Vinyl chloride
Z1nc



24 Hour
Average
*9/l
LO
2300h
0.013
1500
LO
47
TABLE 11-2
(Continued)
Freshwater
Maximum "Red Book"
*g/i *g/i
LD
5200h
1.6 0.005
3400
LD
q P



24 Hour
Average
-9/1
LD
100
LD
LD
LD
58


Saline Water
NaxlMM "Red Book*
• 9/1 »g/l
LD
230
0.07 O.OOb
LD
LD
170
Source:  The criteria In this Table are fro* the following  sources:
         •  "Red Booka (U.S. EPA 1976)
         •  Federal Register on these dates:
            March 15. 1979 - July 25. 1979 - October 1.  1979 -  November  28.  1980
aLD denotes lack of data.
bAcute toxlclty level.
cChrooic toxlclty level.
dlhe value In »g/l should not exceed exp [1.05 In (hardness) -8.53] where  hardness  Is expressed in *g/l as
 CaC03.
eThe value 1n Mg/l should not exceed exp [1.05 In (hardness) -3.73] where  hardness  1s expressed In mg/l
 as CaC03.
f0.4 mq - 1.2 «g/l for cladocerans and salmonld fishes.
94.0 mg - 12.0 mg/1 for other, less sensitive aquatic life.
nValues derived using procedures other than the guideline.
                                                    -13-

-------
                                                   TABLE 11-2
                                                   (Continued)
*The value In Mg/l should not exceed exp [0.94 In (hardness) -1.23 ]. Mhere hardness  Is  expressed  In mg/1
 as CaCOj.
JFor freshwater and marine aquatic life. 0.1 times a 96 hr LC5Q as determined  through nonaerated
 bloassay using a sensitive aquatic resident species.
kThe value In  *g/l should not exceed exp [2.35 In (hardness)-9.48] where hardness  1s expressed In mg/1 as
 CaC03.
'The value In  *g/l should not exceed exp £1.22 In (hardness)-0.47] where hardness  Is expressed 1n mg/l as
 CaC03.
•0.01 tines the 96 hour LCso value, using the receiving or comparable water as the diluent and soluble lead
 measurements (using an 0.45 micron filter) for sensitive freshwater resident  species.
"The value 1n *ig/l should not exceed exp [0.76 In (hardness)  +1.06] where hardness  1s expressed In mg/1
 as CaC03.
°The value 1n *g/l should not exceed exp [0.76 In (hardness)  +4.02] where hardness  1s expressed In mg/1
 as CaC03.
PFor marine and/or fresh water aquatic life. 0.01 of the 96 hour LC$Q as  determined  through bioassay
 using a sensitive resident species.

-------
discharge of toxtc substances.  Table 11-3 summarizes the results of a study reported
by Keith and Tel Hard (1979) which shows the frequency of detection of the 129
priority pollutants in industrial wastewaters.  A total of 32 industrial  categories
were analyzed for organics and 28 for metals.  The number of samples ranged from 2532
to 2988.  Table 11-4 summarizes the most commonly discharged priority pollutants.
Table 111-53, shown in the next chapter, provides a breakdown by industry of the
occurrence of priority pollutants in industrial effluent.
     It is common in this country for numerous Industrial plants to release their
effluents into a single water body.  Because of this situation a question that natur-
ally arises is:  Based on the number and type of industries located on the water
body, what kinds of toxic chemicals are likely to be discharged there?  If the
industrial categories of each plant are known, the probability that a particular
pollutant is discharged from at least one of the plants is:

                                             j • 1. M                    (II-l)


where
        fjj  »  relative frequency of discharge of pollutant type j from plant type
                i, expressed as a percent
        PJ   «  probability that pollutant type j is discharged from at least
                one of the n plants located on the water body
        M    -  number of toxic substances being analyzed.
     If the industrial categories of the plants are not known, then the probability
that a particular pollutant is discharged can be estimated using Table 11-3 together
with the following formula:
where
        9j  -  percent of samples containing pollutant j
        PJ  •  probability that pollutant j is detected in at least one of the n
               discharges.
Equation II-l is obviously the more accurate of the two formulae, because 1t Is
based on a knowledge of the types of Industries which discharge.  Although the
above equations provide Information on the likelihood that different chemicals
ar discharged Into the environment, and thus can be used to prioritize Investi-
gative efforts, they do not predict quantities of pollutants which are discharged.
Chapter III can be used to generate that type of Information.
                                         -15-

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                           TABLE 11-3
EVA LIST OF 129 PRIORI"Y POLLUTANTS AND THE RELATIVE FREQUENCY OF
            THESE MATERIALS IN INDUSTRIAL WASTEWA'ERS
                 (After Keith a«* Tell-lard, 1979)
J^Ui1

1.2
1.7
2t.l
2*. 3
11.7
7.7
S.O
t.S
10.2
1.4
7.7
l.t
4.2
0.4
l.S
40.2
Ni**«r »f
IndultruK
Cilt;3M«i
Purgtibli
S Acrelft*
10 Acrjrlonl trill
2S Itflitn*
21 Telvtn*
24 Ctn/ICtmtnt
14 CtrMfl tttrtcn1er1d«
10 Chlprobtnitflf
It 1.2-OicnlorctlMnt
2S l.l.l-TncMorsitnin*
I l.l-D1cMore«tft«nt
17 l.l-0>cMorottnyltnt
12 1,1.2-TncMcrotinint
13 1 .l.Z.2-"«trjcMorcttn«n«
2 Chtoroctntn*
1 ?-lMor«ftnjl vinyl ttntr
21 Chlerofern
Piretflt HucOtr •<
S«.T9ltt* Ctttyorttt
Orginici
j 1
1.0

1 1.2-OtcMero»ro0«n«
S 1.3-OUnloro;rop«M
J«. 2S HttAylint entertdt
1.
0.
t H*tfiyl chlerld*
1 H«tn») ftrofliM
1. 12 IromferB
4. 17 OlcKlaroDr&rcnttStn*
f. 11 TrtcMarofluOrc^tmini
0.
4 OUMerodlfluorantthint
2. IS Ct)orod)brc.oo-«t'U/i«
10. It TttricMorettHyltnt
10. 21 Trlcnlorctliyltnt
0. 2 Vinyl cnlcrld*
1.1 11 1.2-tr«nt-DlcMprattn/1l bcnt/1 pntntUu
A<1d txtrtctlblt
2S Phenol
11 2-N1tropn«nol
4-Nltrepixno)
2.4-Olnitraaninel
4,1-01 nltro-o-crtf a)
I Ptnticfcloropntntl
PKtICtd
•-EndotulfiM
l-(ndOtvlfin
Cndeiul'*" iwl'ttt
•-DC
*-!«
4-lHC

Aldr<«
OtfUrU
4.4--OOC
4, 4 --000
4. 4*. DOT

(ndrf H
(Mrtn ildthyd*
{.7 11 riuartnt
7.2 12 Duortnthtnt
S.I
1 Chryttn*
7.1 14 tyrtnt
._ , ,, ( Pntn»nthrt«t
10. < 1* |Antnrie«n«
2.3
l.t
j g
1.2
O.I
0.2
O.I
0.1
0
0.2
1.1
O.I
0.1
1.2
0.1
0.1
1.4
fratnlc toaooundi
I.I 1
Itnioltlantxrictnt
Itnzo ( b ) t 1 uprtntntn*
Bcniofk )f luorAnt^f nc
ItfltoitlPyrtnt
Indtnot 1 .2 ,3-c .d}pyr«nt
01bcntpU.h)intAriceM
l*flia(t.».1 )pt r/ltn«
4-Chloropncnjrl pr>tnyl ttrxr
3.3'-Oicn)0roMn;td>n«
Itnttdtn*
bit(2-Chlerett*iyl )cth«r
1 .2-0)p^tn]rlh)raralln•
h«i*cAlorocjrlclo9tnt«dicnt
M-N1 troiodtpntnjr 1
-------
TABLE II-3  (continued)
•i iMultrttl
Saoplts Citcgorit*
Hgtai!
11. 20 Antinonjr
It. It Aritnic
M. II ••rrlllui
ill 21 Chromiw
SI. 2( Co»t*r
43. 27 Lia<
J3.4 It ToUl C7«n<«n HMHIfl
i Ikt p«rc«nt tf IM*ltt rMrtltfttl tM MMMr »f ttatt thit CM»»niH
tftt tout «t «' 11 Avfutt !»'*. Nu««rt •' t<»ltl r»g»* fr«a IS!
* • :at*l if II tiKuitrul c«ttc>ri» t'1 i.uiitftrnt Mrt in«t/t*i
TABLE II
MOST COMMONLY DISCHARGED
Pollutant
Non-He taTs
B1s (2-Ethylhexyl) Phthalate
Chloroform
Methyl ene Chloride
Total Cyanides
Toluene
Benzene
Phenol
DI-n-Butyl Phthalate
Ethyl benzene
Naphthalene
Phenanthrene and Anthracene
Metals
Copper
21 nc
Chromium
Lead
Nickel
FvrcMt IhMbtr »f
•f l»««»irui.
S^cplti Cattgorles
U.S 20
M.7 27
11. t 21
22. » 2»
11.2 11
M.» 2«
Not •»«1\»bU
Mot Jv«iUb)«
•at f*un« In ill iirfln ti Ml
I t» int irttk th* ixrtft *•>•«
f«r er{«nict «•< II Itr rttlll
-4
PRIORITY POLLUTANTS
Percent of
Samples

41.9
40.2
34.2
33.4
29.3
29.1
29.1
18.9
16.7
10.6
10.6

55.5
54.6
53.7
43.8
34.7

Mtreury
Ntcfctl
Stltntun
Stlvtr
2IMC
Mbtttat ((^brvui)
Tetil pn«fMlt
CD it •*• ««*)/it« itr t itn.


Percent of
Industries

91
88
78
59
88
78
78
72
75
56
50

100
100
100
96
%
         -17-

-------
2.1.5  Physical and Chemical Characteristics of Toxic Organic Compounds
     The most Intensively investigated toxic pollutants, as a group, are the priority
pollutants.  Because of the greater availability of data on priority pollutants from
such sources as Callahan et^ al_. (1979), 0111 Ing e£ aK (1975) and Mackay and Lefnonen
(1975), data are presented for organic priority pollutants In the following categories:
        •    Halogenated Aliphatic Hydrocarbons (Table 11-5)
        •    Pesticides (Table 11-6)
        •    Polychlorlnated Blphenyls (Table IJ-7)
        •    Monocycllc Aromatic Hydrocarbons (Table 11-8)
        •    Polycycllc Aromatic Hydrocarbons (Table II-9).
The properties of the pollutants tabulated in Tables II-5 through II-9 are:
        •    Vapor pressure, Torr (1 Torr • 1 mm-Hg)
        •    Solubility
        •    Octanol-water partition coefficient (KQW)
        •    Volatilization half-life
        •    Qualitative statement of the Importance of sorptlon.
     Specific information is included in the tables for volatilization and sorptlon
because of the demonstrated Importance of these processes In governing the fate of
many pollutants.  In particular, for the approximately 103 organic priority pollutants:
        •    Sorptlon processes are Important for 60
        t    Sorptlon Is not Important for 28
        •    It is not certain 1f sorptlon 1s Important for the remaining 15
        •    Volatilization Is Important for 52
        t    Volatilization is not important for 44
        t    It is uncertain 1f volatilization 1s Important for the remaining 7.
     The volatilization half-lives presented In the tables were typically measured
under a specific set of laboratory conditions, and consequently are shorter than in
most natural systems.  Other useful properties such as molecular weight and specific
gravity are  available 1n standard references  such as  Perry  and Chllton  (1973).

2.1.6   Scope and  Organization  of  Chapter
     The  complexity  of the  transport  and  transformation  processes which  Influence  the
fate of toxicants  require additional  analytical tools  beyond those  required for
conventional pollutants.  This chapter  develops these analytical  tools  1n  a general
way that  is  applicable to rivers,  lakes,  and  estuaries.   Individual  chapters  on the
various surface water types refine  these  tools  further and  provide  a  framework  within
which  to  use them.   When  used  together,  the various chapters 1n  this  document should
help the  user  to both understand  and  quantitatively represent the processes  Influenc-
 ing the aquatic fate of  a pollutant.
     This chapter presents  both a general  overview of the screening approach  for
                                          -18-

-------
                         TABLE 11-5
SELECTED CHARACTERISTICS OF VARIOUS ALIPHATIC HYDROCARBONS
Malogenjted *i ipnitlc Vapor
Hydrocarbons
CMorometnane
Dicilorowe thane
TricMoromethane (chloroform)
letracMoromethane
(carbon tetrechlorloe)
CMoroet**"*
1 ,1-OichVoroethane
1,2-OtcMoroethene
1,1.1-Tnchloroethane
1.1.2-TrlcMoroethane
1 .1 ,2.2- Tetracnloroethane
weiacnloroetnane
Chloroetxene
(vinyl chloride)
l.l-OKMoroethene
1,2-trans-O'cMoroethene
frichloroethene
TetracMoroethene
1,2-Otchloropropane
1,3-OicMoropropene
MeiacMorobutadiene
MeiacMorocyciooentadiene 0.
nronawiiune
Bro«odichloro«e thane
01 bromoehlorome thane
Tnbromouwthane
Dtchlorodt'luoromethene
TrlcMorofluoro«» thane
Pressure (Torr)
at 20*C
3700
362
ISO
90
1000
180
61
96
19
S
0.4
2660
591
200
57.9
14
42
25
0.15
081 at 2S*C
1420
SO
IS
10
430C
6«7
a Stirring in an open container of depth
Solubility
64SO-72SO "9/1
at 20*C
13000-20000 -9/1
at 2S*C
8200 Kg/I at 20*C
78S «9/l at 20*C
S74Q «9/l at 20'C
5500 M9/) at 20*C
8690 119/1 at 20-C
440-4400 119/1 at 20*C
4SOO 119/1 at 20*C
2900 *9/l at 20*C
SO «9/l at 22*C
60 «|/l at 10*C
400 -9/1 at 20*C
600 "9/1 at 20*C
1100 «g/ 1 at WC
1SO-200 «9/l
2700 119/1
2700 "9/1
2
0.8 B9/1
900«9/1
-
-
JOOO-9/'
280-9/1
1100 «9/l
65 M> at 200 RPM (D111
***
8
20
93
400
)S
60
30
ISO
ISO
360
2200
4
30
30
200
760
190
95
5500
10*
10
7$
120
200
US
3400
ing et^ tl_. .
VolatlHtation
Half-Life
27 -mutes*
21 -InvtCS*
21 minutes*
29 -Inutes*
21 ..n«t«'
22 -Inutes*
29 minutes'
20 minutes'
21 minutes*
56 minutes*
45 minutes*
26 minutes'
2Z -inutes*
22 minutes*
21 .mutes*
26 minutes*

-------
                                                TABLE II-6



                            VARIOUS CHARACTERISTICS OF SELECTED PESTICIDES
Pesticide
Ac role In
Aldrtft
Chlordane
000
DOC
DOT
DleldrU
CiMJosul f M
EMlrU
HeptacMor
Heptachlor Cpoilde
Heiachlorocyclotexane
Llndane
Isophorone
TCOO
Toxaphene
Vapor Pressure (lorr)
220 at 20*C
330 at 30*C
2.3«10'5 it 20«C
««HT6 at 2S*C
1»10*5 at 25*C
10.2-18.9KlO-7 «t WC
1.2-6. 5* JO'6 at 20'C
l.SuKT^at 20'C
l.«»10*7 at 25*C
l.&ilO'7 to
2.»*10-7 at 20*C
l«W5 at 25*C
2x10' 7
3*10'4
-
io*5-io-^
10^-10'd
0.38
-
0.2-0.4
Solubility
20.81 at 20*C
17-180 ppb at 2S'C
O.OS6-1.8S pp«
20-100 ppb at 2S*C
1.2-140 ppb at 20*C
2-85 ppb
184-200 ppb at 2S*C
100-2CO ppb at 20*C
220 ppb at 25'C
56-180 ppb at 25*C
200-350 ppb at 25*C
0.70-21.3 Pfm at 2S*C
5-12 pp* at 2S*C
12000 w*
0.2 ppb
0.7-3. pp*
*o*
0.8
M10
600
106
5»105
I04-106
-
4»I03
4xl05
-
-
104
5*103
50
-
2000
Volitil i/ation
lUlf-l. ife
Uncertain
FtM hours to
few days
Several weeks
1 day to 1 Month
1 to 10 hours
4 hours -1 Meek
Ftx hours to
few days
11 days-1 year
-
-
-
-
100-200 days
Probably great
-
-
Sorptlon
Important?
No
Yes
Probably
Tes
Yes
res
Probably
res
Uncertain
Probably
Probably
Probably
Probably
No
res
res
•Conditions described  in C«ll
-------
                                                       TABLE 11-7
                      SELECTED CHARACTERISTICS  OF POLYCHLORINATED BIPHENYLS  AND RELATED  COMPOUNDS
VoUtlllutlon
PCIs tntf Ml* ted
Conpounds
Aroclor 1016
Aroclor 1221
Aroclor 1232
Aroclor 1242
Aroclor 1248
Arocter 1254
Aroclor 1260
Percent
CMorlM
41
21
32
42
48
54
60
OensUv
1.33
1.15
1.24
1.35
1.41
1.50
1.58
Vapor Pressure
•t 25 C-(Torr)
4xlO~4
6.7x10°
4x10-3
4»10'4
4.9xlO'4
7.7X10'5
4xlO'5
Solubility
•9/1
0.42
15.
1.45
0.1-0.3
0.054
0.01-0.06
0.0027
*ow
2xlO*-3xl05
600- 104
1.5xl03-3xl04
I04-4xl05
MO6
xlO*
>106
Hilf-Uvei
In
laborttor/
(hrs)*
9.9
-
-
12.1
9.5
10.3
10.2
loss in .
N«tur«l Systems
3.6t After 24 hours
4.2S ifter 24 hours
-
-
-
-
34S-67S After 12 weeks
   2-cMoroMpfctht 1 •*•
0.017
6.47
*At M*C In 1 a3 of Mttr, 1 • 4Mp (ttocKay M* Lttnontn, 1975).
bCondUlons described In CalUhan tt_ «i- (1979).
                                                           -21-

-------
                        TABLE 11 -»



SELECTED CHARACTERISTICS OF MONOCYCLIC AROMATIC HYDROCARBONS
Monocyclte AroMttcs Vapor Pressure (Torr) Solubility
Benzene
Chlorooetuene
1 ,2-OicMorooenxene
Heiachlorobenzerte
Ethylbeniene
Toluene
2,4-Otnttrotoluene
2. 6-OlnUro toluene
Pentachloro phenol
2-Hltrophenol
4-NUrophenol
2.4-Otnltrophcnol
4.6-0*nitro-o-cresol
'fttctar and ieinonen (197!
coefficients of ?0 c«/hr
95. at 25'C
MO at 20*C
1.5 it 25*C
10-5 ,t 20«c
7
29 *f25'C
0.001 at S9*C
low
0.0001
1.0 at 49*C
2.2 at 146*C
-
and 3000 c«/hr fur
1800 M9/I at 25*C
^500 mq/}
145 «g/l
•WO yg/l
152 *9/l
535 «g/l
270 «9/l at 22*C
i300 «9/l
14 »g/l
2100 «9/l at 20*C
16000 «g/l at 2S*C
5600 «g/1
, <•;) on water deplti of 1 l ion
liiH'Orlinl '
Uncertain
Probably
Probably
Yes
Probably
Probably
Yes
Yes
Yes
Yes
Yes
Yes
Yes
                             -22-

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                            TABLE 11 -9



SELECTED CHARACTERISTICS OF VARIOUS POLYCYCLIC AROMATIC HYDROCARBONS
Polycyclic AroMtics
AceMphthene
Acenaphthylene
Huorene
Nipkthilene
Anthracene
Fluor tntheiM
Pfcenanthrene
Benzo(a)anthracene
Benzft[b]flueranthene
8enzo[kJfltMraathene
Chrysene
Pyrene
Benzo[ gh1]perylene
8enzo[i]pyrene
Dlbenzo[i ]inthricene
1 ndeno[ 1 . 2 . 3-cd ]pyrene
Vipor Pressure (Torr)
10-3-10-2 at 20'C
10-3. nr2 «t 20'C
10-3.10-2 .t 20«C
.0492
2*10'* at 20'C
10-* to 10'4 at 20'C
t.BilO-4 at 20'C
5xlO*9 at 20'C
11"" to 10'* at 20'C
9.6x10'" at 20'C
10-11 to 10'* it 20'C
6. 9* 10' 7 at 20'C
MO'10
5x10-9
•vlO' 10
MO' 10
Solubility
3.4 *9/l it 25'C
3.93 «g/l
1.9.9/1
32. mg/\
0,05-0.07 «9/l it 25'C
0.26 119/1 at 25'C
1.0-1.3 1*9/1 at 25'C
0.01 mg/\ at 25'C
-
-
0.002 *9/1 at 25'C
0.14 *9/l at 25'C
0.00026 mg/\ it 25'C
0.0038 «g/l it 25'C
0.0005 «9/l it 25*1
-
"ov,
21.000
12.000
15.000
2.300
28.000
340.000
29.000
4xl05
4x10*
7»10*
4xlOs
2x10^
10 7
10*
10*
5xl07
Volil'iluat ion
Iwportinl?
Less thin sorptton
Less thin sorption
Less thin sorptton
Less thin sorption
Probibly
Probibly Not
Probibiy Not
No
Probibly Not
Probibly Not
Probibly Not
Probibly Not
Probibly Not
Probibly Not
Probibly Not
Probibly Not
Wplion
Invariant?
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
                                -23-

-------
toxicants and a detailed description of the processes Included in the screening
methodology.  The various topics are organized as follows:
        Screening methods for toxic organic substances
        Speciation processes
        1)  Acid-base effects
        2)  Sorptlon
        Transport processes
        1)  Solubility limits
        2)  Volatilization
        Transformation processes
        1)  B1odegradat1on
        2)  Photolysis
        3)  Hydrolysis.
Lyman €*£]_. (1982) and Mabey et^ al_. (1984) provide additional 1nfo"-iation that can
be used to evaluate the importance of these processes.

2.2  SCREENING METHODS FOR TOXIC ORGANIC COMPOUNDS

2.2.1  Modeling the Fate of Toxic Organlcs
     The goal of this screening methodology for toxic pollutants is to help the user
Identify surface water oodles where toxicants could reach hazardous levels.  Multiple
approaches for Identifying pollution problems are possible, e.g. extensive field
measurements, statistical correlations of discharges and pollutants detected in
rivers, computer simulation models, etc.  The approach taken here is to present
simple methods for assessing the fate of toxicants.
     The  application  of  any method  necessitates  the  use  of  judgment  on the part of
those  applying  1t.   In  almost  every  case,  the user must  estimate many of  the methods'
Input  parameters on the  basis  of  limited data.   Consequently,  even the projections  of
detailed  computer  models  such  as  EXAMS  (Burns, et_ al_.,  1981)  and PEST (Park, e£ aj_.,
1980)  are only  as  good  as the  accuracy  of  the assumptions made by their developers
and  users.   Thus,  the goal  of  the materials  presented herein  1s  twofold:   to present
simple methods  and to provide  the background  necessary to make knowledgeable judgments.
     Predicting  aquatic  fate of pollutants Involves  several steps.   The steps  des-
cribed 1n the  remainder  of  this section  Include:
        •   Determination  of  Fate-Influencing Processes
        •   Delineation of Environmental  Compartments
        •   Representation of Hydrologlc  Flow
        •   Mathematical  Representation of  Speciation Processes
        •   Mathematical  Representation of  Transport and Transformation  Processes
        •   Determination  of  Pollutant  Load  and Mode of Entry into  the Aquatic
             Environment.

                                         -24-

-------
   IN CLOW
volatilization
	V
                                           H
                                        HydfOlyttt
                                      A«t»orp»KX>-D«t
-------
             Kdvection.  Hydraulic flows transport pollutants which are dissolved or
               sorted on suspended sediments into and out of particular aquatic
               habitats.
             Volatilization.   Organic  pollutants  may  enter  the  atmosphere  from
               a  water body,  thereby  reducing aquatic concentrations.
             Sedimentation.  Deposition of  suspended  sediments  containing  sorted
               pollutants,  as well  as  direct  sorption onto  or desorption from bottom
               sediments can  alter pollutant  concentrations.
        Transformation Processes
             Blodegradation.   Microbial  organisms metabolize  pollutants, altering
               their toxicity in the  process.
             Photolysis.  The absorption of sunlight  by  pollutants  causes  chemical
               reactions which affect  their toxlcity.
             Hydrolysis.  The reaction of a compound  with water frequently produces
               smaller,  simpler organic products.
             Reduction-Oxidation.  Reactions  of organic  pollutants  and  metals
               which involve  the subtraction  or addition of electrons  strongly
               influence their environmental  properties. For organics, nearly
               all  significant redox  reactions are microbially  mediated.
        Bioaccumulation
             Bioconcentration.  Uptake of toxic pollutants  into biota  via  passive
               means, e.g.  absorption  through fish gills.
             Biomagnification.  Uptake of toxicants into biota  via  consumption
               of contaminated food.
     Once the pertinent  processes have been identified,  the physical compartments ti-
the environment between  which the transport processes act must  be delineated.   For
most water bodies,  compartments representing  the  atmosphere,  bottom sediments,  and
one or more water elements  are sufficient.   These methods are capable  of representing
transport of pollutants between the atmosphere and a  water  body. But  rather than
calculating atmospheric concentrations of a pollutant, these methods generally  assume
them to be close to zero unless available data Indicate otherwise.   Bottom sediments,
however, frequently accumulate high levels  of organic pollutants.  Because of the
difficulty of modeling the behavior of toxicants  in sediments,  usually  assumptions
which approximate only the removal  or addition of a pollutant to the water column are
made.  These approximations are presented in  the  Individual chapters on each water
body.
     The next step In assessing the aquatic fate  of toxic pollutants 1s to represent
the advectlon or flow of water.  Figure II-3 illustrates a  representation  of rivers
as a segregated flow system and lake  layers as completely mixed flow systems.
Although these models are simple, they serve  as adequate first-approximations of  real
                                          -26-

-------
            COMPLETELY MIXED FLO*
                 NATURAL SYSTEM:
                                                         LAKE
                 IDEALIZATION:
                                            MIXED FLOW
            SEGREGATED FLOW
                 NATURAL SYSTEM:
                                                         RIVER
                 IDEALIZATIONS:
                                                         PLUG FLOW

                                                         FLOW WITH
                                                         AXIAL DISPERSION
                    FIGURE  11-3  FLOW SYSTEM  REPRESENTATIONS
systems.   Refinements and  limitations of these flow system models are considered in
the individual  chapters on rivers, lakes, and estuaries.
     The transport  and transformation processes responsible  for the removal of a
pollutant from the  water column are considered next.  First-order rate expressions
adequately represent all of the processes considered here.   The first-order decay of
                                         -27-

-------
a pollutant by a process 1s represented as follows:

                   Rate of Pollutant Removal « ki  • Cj                     (II-3)

where
        k^  »  first-order rate constant for process 1
        CT  •  total concentration of pollutant.
The rate constant for a process is specific to both the chemical it acts upon
and the local environment in which 1t acts.
     When all the first-order processes acts independently, the total rate of pollut-
ant removal 1s:

                   Total Rate of Removal « ky • CT                         (II-*)

where

                   *T " kvm + kS + kB + kp + kH                            (11-5)
and
        kvm  "  Soec1fic mixed-body volatilization rate constant
        k,   •  specific rate constant for removal to bottom sediment
        kg  •  specific rate constant for biodegradation
        kp  •  specific rate constant for photolysis
        kH  «  specific rate constant for hydrolysis.

The addltlvity of processes which are first-order with respect to pollutant concentra-
tion is particularly convenient for analysis.
     Many of the decay processes are Influenced by the chemical state of the toxicant.
For example, sorbed pollutants cannot volatilize.  Mathematical representations of
equilibria between two species of a chemical can be reduced to the following type of
equation.  This type of equation serves well at the low solute concentrations en-
countered in waste waters and natural waters:

                             Ci • Mj Cj                                  (II-6)
where
         C,    •  concentration  of  form 1
         K,.,   •  equilibrium  constant
         C,    «  concentration  of  form j.
      It 1s also  convenient to  know the fraction of the  total  pollutant  concentration
which is In  a  given state:

                             «4  - £i                                      (H-7)
                                   CT

                                          -28-

-------
where

        CT  -  c + cs
        C.,  «  concentration In state 1
        C   -  total dissolved phase pollutant concentration
        Cj  *  total sorbed phase pollutant concentration.
     To complete the assessment of the aquatic fate of a pollutant the mode of entry
Into the aquatic environment must be considered.  Many pollutants enter In dissolved
or sorbed form from a point source.  In this case, a simple mixing computation 1s
sufficient to determine the Initial concentration of a pollutant in the water body.
Other cases Include spills, non-point sources, and desorptlon from sediments.
Chapter 4 presents methods for dealing with these cases.
     The user may now reckon the concentration of a pollutant 1n a given water body.
The equations which yield the desired results are specific to each surface water type
and are developed 1n the Individual chapters on lakes, rivers, and estuaries.  An
equation representative of those 1n each chapter 1s presented 1n Table 11-10.  The
Individual chapters go Into greater detail  about factors Influencing rate processes
and Interactions with other Important phenomena In each water body (See Sections 4.9,
5.6, 6.4.3, and 6.4.5).

2.2.2  Use of Assessment Techniques as Screening Tools
2.2.2.1  Making Conservative Assumptions
     With the computational methods presented In this document, the user could
produce a relatively complete analysis of the aquatic fate of a pollutant.  The goal
of this screening method, however, 1s to determ1ne--w1th a minimum of effort—whether
toxicants are likely to reach problem levels In surface water bodies for either
existing or projected loading rates.  The user can minimize the effort expended In
screening a pollutant by starting with a simple approach which Incorporates conserva-
tive assumptions about the fate of a pollutant.  Conservative assumptions are designed
to yield higher calculated environmental concentrations than probably exist 1n the
real system.  If these higher concentrations are below the water quality criterion
under consideration, a violation of the standard Is unlikely.  If the Initial  predic-
tions are higher than the standard, the user may successively refine the approach
until It becomes apparent that either the standard will be met or that a more detailed
study Is necessary.
     Three levels of refinement 1n assessing the aquatic fate of a pollutant are
considered here.  In order of Increasing complexity, they are:
        1)  Treating the pollutant as a conservative substance
        2)  Considering transport and spedatlon processes
        3)  Considering transformation, transport, and spedatlon processes.
Each approach has advantages and limitations which the user should consider. By
                                         -29-

-------
                                       TABLE 11-10

                         EXPRESSIONS FOR TOXIC POLLUTANT LEVELS
                                 IN VARIOUS WATER BODIES
         Water Body
        Expression for Steady-State
          Pollutant Concentration
        Ri vers
        (Chapter IV)
        Impoundments
        (Chapter V)
    CQ exp
      (IV-115)
                           where  x « distance downstream
                                  U » river velocity
                                  C - total dissolved phase concentration
C -C1n/(l
(V-47)
                           where T  « hydraulic residence time
                                 C  « total dissolved and sediment phase
                                      concentration
        Estuaries
                      (VI-33)
                                    r.
                            1
               -kt
                                                    (VI-34)
                           where C. - concentration in segment  i
                                 f. • fraction of fresh water in segment  i
                                 r, - segment i exchange  ratio
                                 t  - time expressed  1n tidal cycles
following this sequence of refinements, the user should be able to eliminate cases
where water quality problems are unlikely with a minimum of time and effort.

2.2.2.2  Treating the Pollutant as a Conservative Substance
     The simplest approach to estimating the concentration of a toxic pollutant Is to
assume it behaves conservatively (I.e. does not undergo reaction):
        kT-0
Unless an Internal source of the pollutant exists, this approach will yield the
highest possible pollutant levels since pollutant decay and removal processes are
neglected.  The obvious advantage of this approach 1s that it requires no chemical or
environmental data to evaluate rate and equilibrium constants.  The only data needed
are pollutant loads and hydrologlcal parameters.  Its major drawback 1s that it
neglects the possibility of a compound accumulating in another environmental compart-
                                          -30-

-------
merit, especially bedded sediments.  This could result 1n the underestimation of the
duration of the exposure of an aquatic habitat to a chemical.  Although the duration
of exposure may be underestimated, water column concentrations would not exceed the
upper limits predicted by this approach at any time during the exposure period.
The fate of conservative pollutants In rivers, Impoundments, and estuaries 1s
discussed In Sections 4.1.9, 5.6.1, and 6.4.

2.2.2.3  Considering Transport and Sped at 1 on Processes
     This refinement Incorporates those processes which Influence pollutant transport
out of the aquatic environment but neglects those processes which chemically alter
the compound.  Transport processes strongly depend upon chemical speciation, which
therefore must be included.  The rate constant for first-order pollutant attenuation
In -"is approach is:
where
        k.
             «  specific mixed body volatilization rate constant.
        k.   «  specific rate constant for removal to bottom sediment
          _
         vm
This approach requires more Information on the properties of the toxicant and the
environment than when the pollutant 1s assumed to behave conservatively, but the
necessary data are much more readily available than those required to characterize
transformation processes.  Nearly all the chemical data necessary to characterize
acid-base equilibria, sediment sorptlon, solubility limitations, and volatilization
for the organic priority pollutants are presented 1n tables In Sections 2.1.5,
2.3.1, and 2.4.2.  The necessary environmental data can usually be obtained or
estimated with a minimal amount of effort.  Because of the demonstrated Importance of
transport processes and the relative simplicity of assessing them, this Is a good
Intermediate step between the simplest and most complicated approaches.
     Transport and speciation processes are applied specifically to rivers. Impound-
ments, and estuaries 1n Sections 4.9, 5.6, 6.4.3, and 6.4.5.

2.2.2.4  Considering Transformation, Transport, and Speciation Processes
     The most complex model which the user can employ using these screening methods
Includes consideration of transformation, transport, and speciation processes.  With
this approach, the rate constant for first-order attenuation of a pollutant 1s:
                                          -31-

-------
where
        kn  •  specific rate constant for blodegradatlon
         D
        kp  «  specific rate constant for photolysis
        k^  «  specific rate constant for hydrolysis.
     The inclusion of the degradative processes (i.e. biodegradation, photoly-
sis, and hydrolysis), considerably increases the chemical and environmental data
required to model a compound's fate.  Rather than accurately determining all the
constants for speciation, transport, and transformation, the user should first
ascertain which processes are the most significant for a compound.  As a first step
the user should obtain data on the properties of the chemical which influence its
aquatic fate from this document or other sources.  From compound specific aata, it is
usually possible to eliminate some processes from consideration.  For organic priority
pollutants, consulting the ratings of the relative Importance of aquatic processes
for the fate of each compound, Table 11-11, may aid the user in eliminating unimport-
ant processes.  Once the most significant processes have been identified, the user
should collect the environmental  data necessary to determine site specific constants.
These site specific constants are then applied in the appropriate equation for each
water body type to obtain the best estimate of the actual pollutant concentrations in
the environment that these methods are capable of making.  (See Sections 4.9. 5.6,
6.4.3, and 6.4.5).
     Frequently, kinetic and equilibrium constants will depend on the values of
parameters which the user must estimate (e.g., pH).  In such cases, assuming conserv-
ative values 1s the best policy.  However, calculations using a range of values may
Identify processes for which a more careful determination of the key environmental
and chemical parameters 1s warranted.
     Example II-l is an overall example for this chapter.  It demonstrates the
Initial steps a user would take In applying these methods to assess the fate of a
particular organic pollutant.  The example follows the three level analysis described
above and also draws upon some of the procedures for specific environmental processes
which are developed later in this chapter. This example can serve as a guide to
evaluating the importance of the various fate Influencing processes for a particular
pollutant.
                                         -32-

-------
                                     TABLE 11-11


                     RELATIVE IMPORTANCE OF PROCESSES INFLUENCING
     AQUATIC  FATE OF ORGANIC PRIORITY  POLLUTANTS  (After  Callahan et aj_.,  1979)
Compound Process









PESTICIDES
Acrolein
Aldrin
Chlordane
DDD
DDE
DDT
Dleldrin
Endosulfan
Endrin and
Heptachlor
Heptachlor


S §
*•> <->
c •£ "S
0 — *•
.;: ~ 01
** ** Ol
Q. <0 IB
U "~ O
o o •*•
10 >• CO
_ + +
+ + ?
+ + ?
+ + .
•f +
•f +
•f +
and Endosulfan Sulfate + + *
Endrln Aldehyde ? ? ?
+ +
Epoxide + - ?
u
at e
u o
Q. j
**
1 •
•f +
+ . +
? •*• -
•f . +
? ++ +
? - *
Hexachlorocyclohexane (a.8.6 Isomers) + ? + ._-
-Hexachlorocyclohexane (Llndane) +.+..-
Isophorone
TCDD
Toxaphene
?
•f
+ + +
*
? - *
•f
PCBs and RELATED COMPOUNDS
Polychlorlnated Biphenyls
2-Chloronaphthalene

HALOGENATED ALIPHATIC HYDROCARBONS
Chloromethane (methyl chloride)
Dlchloromethane (methylene chloride)
Tr1chloron»ethane (chloroform)
Tetrachloromethane (carbon tetrachlorlde)
Chloroethane (ethyl chloride)
1,1-Dichloroethane (ethylldene chloride)
1,2-Dichloroethane (ethylene dlchlorlde)
1,1,1-Trlchloroethane (methyl chloroform)
1,1,2-Trlchloroethane
1,1,2,2-Tetrach1oroethane
Hexachloroethane
Chloroethene (vinyl chloride)
l,l-D1chloroethene (vinyl1dene chloride)
l.2-trans-D1chloroethene
Trlchloroethene
Tetrachloroethene  (perchloroethylene)
l,2-D1chloropropane
l,3-D1chloropropene
Hexachlorobutadlene
Hexachlorocyclopentadlene
Bromomethane (ntethyl bromide)
_
.
.
?
_
.
.
_
•>
I
?
?
+
?
.
_
+
•»•
+
+
•»•
+
•f
•f
+
+
?
.
•f
+
+
_
?
?
.
?
?
?
.
.
.
?
_
?
?
+
.
.
_
.
.
.
.
.
.
-
?
.
-
.
.
•f
+
+
•f
+
                                         -33-

-------
TABLE 11-11 (continued)
Compound Process

c c
O 0
 4)
a  CO
Bromodichloromethane ? ? ?
Dibromochloromethane ? * ?
Tribromomethane (bromoform) ? * ?
Dichlorodif luoromethane ? +
Trichlorof luoromethane ? * -
HALOGENATED ETHERS
Bis(choromethyl) ether ?
Bis(2-chloroethyl) ether +
Bis(2-chloroisopropyl) ether *
2-Chloroethyl vinyl ether + ?
4-Chlorophenyl phenyl ether + 7 ?
4-Bromophenyl phenyl ether + 7 ?
Bis(2-chloroethoxy) methane - - ?
MONOCYCLIC ARQMATICS
Benzene + *
Chlorobenzene * +
1,2-Oichlorobenzene (jj-dichlorobenzene) + + .
1,3-Dichlorobenzene (jrj-dichlorobenzene) + + ?
1,4-Oichlorobenzene (£-dichlorobenzene) + + .
1,2,4-Trichlorobenzene + *
Hexachlorobenzene +. - -
Ethylbenzene 7+7
Nitrobenzene +
Toluene +• + 7
2,4-Oinitrotoluene +
2,6-Dinitrotoluene *
Phenol + +
2-Chlorophenol - - 7
2,4-Dichlorophenol . . +*
2,4,6-Trichlorophenol ? - ?
Pentachlorophenol + - +
2-Nitrophenol ...
4-Nitrophenol +
2,4-Oinitrophenol •*•
2,4-Oimethyl phenol (2,4-xylenol) 7
p-chloro-m-cresol 7
4,6-Oinitro-o-cresol *
PHTHALATE ESTERS
Dimethyl phthalate + - *
Diethyl phthalate * - *
01-n-butyl phthalate + - *
01-n-octyl phthalate + - *
Bis(2-ethylhexyl) phthalate * - *
Butyl benzy phthalate + - +
t;
w ®
5 ^j

— •— 3
* ^ i
>. >i 3
— — u
° ° «

f, ^H -^
0. I| CO
7 - +
? - +
? - •*•
? - ?
?

++
?
?
•»•
4- . -f
•f . +
+ 7

.
+
? ? *
? - *
? - +•
.
.
•»
.
* - ?
+ ? ?
-
+•
.
7
K
. ^U
++
++0
•f
•»»*
•M- 7 7

+
+
•f
•4-
•f
4
           -34-

-------
                               TABLE  11-11  (continued)
Compound Process
4^
J
C
0
•*•
19
0
••—
4-1
a.

a
i/)
r^
.^
^j
lO
*•
o
3»
C
0
•^
•O
U
O1
OJ

o

m
w
^.

o
i

*^f
fH
t .
o
<—
a.
^
o

<-»
1/1
£
^
O
L.
^
^1
z
*v
i
u

4Q
0

a
POLYCYCLIC AROMATIC HYDROCARBONS
Acenaphthenec
Acenaphthylene
Fluorene
Naphthalene
Anthracene
Fluoranthene^
Phenanthrene
Benzo(a)anthracene
Benzo(b)fluoranthene
Benzo(k)fluoranthenec
Chrysene
PyreneC
Benzo(ghi)perylene
Benzo(a)pyrene
Oibenzo(a,h)anthracene
Indeno(l,2,3-cd)pyrene

NITROSAMINES AND MISC. COMPOUNDS
Dlmethylnltrosamlrte
Diphenylnitrosamine
Di-n-propyl nitrosamlne
Benzidine
3,3'-Dichlorobenzidine
l,2-01phenylhydrazine (Hydrazobenzene)
Acrylonltrile
•f
•f
+
•f
•f
•f
•f


*
4-
•f

•f

•f

•f

+•

•f
       +•*•
       •f
       •f
       •f
                                   Key to Symbols:
•M- Predominate fate determining process        - Not  likely  to  be  an  Important  process
 + Could be an important fate process          ? Importance  of  process  uncertain  or not
                                                known


Notes

a Blodegradation is the only process known to  transform  polychlorinated  biphenyls
  under environmental conditions, and only the lighter compounds  are measurably
  biodegraded.  There is experimental evidence that  the  heavier polychlorinated
  biphenyls (five chlorine atoms or more per molecule) can  be  photolyzed by
  ultraviolet light, but there are no data to  indicate that this  process is operative
  in the environment.

b B%sed on information for 4-n1trophenol.

c Based on information for PAH's as a group.   Little or  no  information for these
  compounds exists.
                                         -35-

-------
                                  EXAMPLE  II-l
                  Pentachlorophenol in the Aurum Mirth Watershed                        I
                                                                                       i
        Pentachlorophenol enters the Aurum Mirth River from a continuous point         j
    source.  The  river  is the sole tributary to Lake Castile.  After mixing at          j
    the  point of  entry, the concentration of pentachlorophenol in the river 1s
    20 «g/l.  The travel time from the point of contamination with pentachloro-         ;
    phenol  to Lake Castile is about 6 days.  The mean hydraulic residence time          I
    in Lake Castile  is  10 days.                                                         I
        Use the  screening methods to determine which chemical and environmental        |
    parameters are of the greatest importance for predicting the fate of penta-         j
    chlorophenol  in  the watershed's surface waters.
    1)   TREATING  PENTACHLOROPHENOL AS A CONSERVATIVE SUBSTANCE                          j
        The first step in the  screening method is to assess the fate of penta-         |
    chlorophenol  treating it as  a conservative substance.  Sections 4.1.9, 5.6.1, and   j
    6.4  discuss the  fate of conservative pollutants in rivers, lakes, and estuaries.
    In this case, we assume no further dilution of the pentachlorophenol occurs in
    either the lake  or the river.  Consequently, the conservative pollutant approach    |
I    predicts a mean  concentration in the river and lake of 20 ug/1.
i
|        Table 11-2  lists a proposed water quality standard for pentachlorophenol.
j    The  24 hour mean concentration must be less than 6.2 ug/1.  Since 20 tfg/l  exceeds
    this standard, a second level assessment is in order.
        Prior to applying the next two levels of analysis it is worthwhile to
;    check Table 11-11 for the relative importance of the different  transformation and
|    transport processes.  Table  11-11 summarizes the influence of the aquatic  processes ,
I    on pentachlorophenol as follows:                                                    ]
|           t     Sorption - Important process                                           i
j           •     Volatilization  - Not an Important process                              |
j           •     B1 ©degradation  - Important process                                     |
           t     Direct Photolysis - Important process                                  j
           •     Hydrolysis - Not an Important process                                  :
j           •     Bloaccunulatlon - Important process.
I         It will be Instructive to compare these statements to the results of          ;
I    the  screening methodology.                                                          j
I    2)   CONSIDERING  TRANSPORT AND SPECIATION PROCESSES                                  !
!        To analyze  transport and sped at1 on processes, first examine each process for  .
'    Its  potential influence on the fate of pentachlorophenol.                           ;
I                                                                                       I
                                         -36-

-------
Spedatlon Processes
     Acid-Base Effects (Section 2.3.1).  The chemical and environmental parameters
governing acid-base effects are:
     •    Chemical Parameters:
              pKa or P1^ ' Ac1d or oase equilibrium constants
     •    Environmental Parameters:
              pH - Hydrogen 1on concentrations.
     The pK  of pentachlorophenol 1s 4.74, as shown In Table 11-13. According
to Table 11-12, at least 90 percent of the pentachlorophenol will be 1n the
anlonlc state at pH's greater than 5.74.  As long as the pH 1n the Aurum Mirth
River and Lake Castile remain above 5.74, the properties of pentachlorophenol as
measured for neutral waters will remain unaffected.  But, because pH's below 5.74
could significantly alter the behavior of the compound, 1t 1s Important to deter-
mine actual surface water pH values.

     Sorptlon (Section 2.3.2)   The key environmental and chemical parameters which
Influence sorptlon are:
     •    Chemical parameters:
              K   - Octanol-water coefficient
               ow
              S^ - solubility  1n water
     •    Environmental Properties:
              Suspended sediment concentration
              Organic carbon content of the suspended sediment.
     Table 11-8 lists the solubility and octanol-water coefficient of
pentachlorophenol  as:
        S   - 14 mg/1
        Kow ' l°5
Assuming an organic carbon content of 2 percent for the suspended sediments,
calculate K  using Equations 11-18 and 11-16:
        Kp - (.02) (.63)  (105) • 1300
According to Table 11-16, greater than 10 percent of the pentachlorophenol
will  be 1n the sorbed state at suspended sediment concentrations exceeding
100 mg/1.  The relatively strong sorptlon of pentachlorophenol  dictates that
the suspended sediment concentration In the Aurum Mirth River and the sediment
trapping efficiency of Lake Castile be Investigated further. Sorptlon of            !
pentachlorophenol potentially affects both Us speclatlon and Its transport         j
rates.                                                                              I
                                                                                    i
Transport Processes                                                                 j
     Solubility Limitations (Section 2.4.1).  The most Important chemical           I
                                       -37-

-------
 and environmental  factors  which  influence  solubility of  a compound are:
      •    Chemical  Parameters:
               S..  -  Aqueous equilibrium  solubility
      •    Environmental  Parameters:
               T -  Temperature
               Salinity.
      Table 11-8 lists  the  solubility  limit for  pentachlorophenol as 14 mg/1
 (14000 wg/ij.   At  no point in  the  Aurum Hirth watershed  should the solubility of
 pentachlorophenol  restrict the ability  of  the aqueous  phase to transport  it,
      Volatilization (Section 2.4,2).  The  most  significant chemical and environ-
 mental properties  which  influence  volatilization are:
      •    Chemical  Parameters:
               *u  •  Henry's Law Constant
                H
      ».    Environmental  Parameters:                                                  j
               k  -  P.eaeration  constant                                               '
                V  -  Wind  speed                                                        j
                Z  -  Mixed depth of  water body.                                        j
     It is possible to estimate the Henry's Law  Constant  for  pentachlorophenol        j
from its vapor pressure and aqueous solubility  using Equation  11-32.   However,  it
is simpler to rule out  volatilization  as a significant  transport  process  on the       ;
basis of the volatilization half-life  of 100 days given 1n  Table  11-8.  Because       \
laboratory volatilization half-lives -.-e shorter than the true environmental          j
values, it 1s safe to assume the  environmental  half-life will  be  much  greater than   |
100 days. Given a  total system mean hydraulic residence time  of only  16 days         |
(6 * 10), volatilization can be safely neglected.                                    j

Summary
     Acid-base equilibria and sorptlon significantly Influence the transport         j
and sped at ion of pentachlorophenol in the aquatic  environment. Acid-base effects
do not influence the near-neutral volatilization and photolysis rate  constants
presented  in this document as long as  pH's remain above 5.7.   Sorptlon 1s a          '
potentially Important sped ation process. Consequently, the pH values  and suspended  I
sediment concentrations should be determined 1n order to accurately evaluate these   |
processes.                                                                           |
     The strong tendency of pentachlorophenol to sorb on sediments may result In     j
sedimentation serving as a significant removal  process In Lake Castile.  The
absence of net sediment deposition in  the river Implies that  transport processes
do not reduce pentachlorophenol concentrations  In the Aurum Mirth.  Thus, the        j
second level analysis predicts a total concentration of 20«g/l of pentachlorophenol  I
 In the Aurum Mirth  River with lower levels possible In the lake.   Because the

                                       -38-

-------
  predicted river concentrations exceed the standard, the third level  model  1s
  necessary.
  3)  CONSIDERING TRANSFORMATION, TRANSPORT, AND SPECIATION PROCESSES
       To consider transformation, transport, and speculation processes, the trans-
  formation processes which were neglected in the level two analysis must be examined
  for their potential importance in influencing the rate of pentachlorophenol
  degradation.
  Transformation Processes
       Blodegradation (Section 2.5.1).  The key chemical and environmental  variables
  which influence biodegradatlon are:
       Chemical Parameters:
           Metabolic Pathway (growth or co-metabolism)
           kg  - Blodegradation rate constant
        Environmental  Parameters:
            Bacteria)  population  size
            State  of  adaptation
            Inorganic  nutrient concentrations  -  Phosphorus
|            Dissolved  oxygen
j            Temperature
            Pollutant  concentration.
;        According  to  Table  11-26, pentachlorophenol  1s  potentially biodegradable,
)  although  adaptation may  be slow.   The  reported  specific  rate  constant  values, 0.1
I  to  1.0  per  day, In  Table 11-27 are  in  the  same  range  as  the 0.05  to  0.5 per day
|  values  suggested  in Table 11-26.   Although  both  rate  constants were  determined
  under laboratory  rather  than environmental  conditions, they do indicate that
  pentachlorophenol can degrade very  rapidly.
        Table  11-27 also indicates that pentachlorophenol 1s used by bacteria as a
,  growth  substrate.   Thus, the time  required  for adaptation is  of primary concern.
j  The most  important  environmental factors  for  determining whether microorganisms 1n    '
I  the Aurum Mirth watershed will adapt to degrade  pentachlorophenol are  previous
|  exposure, time, and the  actual concentrations of  pentachlorophenol 1n  the surface     !
|  waters  (too  low— no enzyme Induction;  toe high— may  have toxic effect  on mlcroblota) ,|
j       Photolysis (Section 2.5.2).   The  key chemical and environmental characterls-     I
•  tics  Influencing the rate of photolysis are:                                          |
       •    Chemical  Properties:                                                        I
                 kdo " Near-surfac*  rat« constant
                «(x) - Light absorption coefficient of pollutant
                  * - Quantum yield
                                          -39-

-------
     0    Environmental Properties:
              I - Solar radiant flux
              Z - Mixed depth of water body
              K - Diffuse light attenuation coefficient
                  a)  Z$(J - Seech 1  disc depth
                  b)  C   - Suspended sediment concentration
                      C.Q. - Dissolved organic carbon concentration
                      C  - Chlorophyll pigment concentration.
     According to Table 11-32, the  near-surface photolysis rate constant  for
ptntachlorophenol 1s .46/day.  The  size of the rate constant Implies  that photolysis
would be an Important factor 1f the water bodies are not too deep or  too  turbid.
Thus, U 1s Important to gather Information on the water depths,  and  to estimate
the  light attenuation  coefficients and the solar radiant flux 1n the Aurum Mirth
watershed.
     Hydrolysis  (Section 2.5.3).   The Important parameters Influencing the
rate of hydrolysis  are:
     Chemical Parameters:
         ka*  St* kb " Ac1d> neutral • and °*se catalyzed hydrolysis
                       rate constants
     Environmental  Properties:
         pH - Concentration of hydrogen 1on 1n the water bodies.
     Table 11-40 gives add and base hydrolysis rate constants for pentachlorophenol
of 1.1 x 10   and 3.3 liter mole"  day.  The neutral rate constant 1s
S.8 x 10"3 per day.  The same table lists a half life of 100 days at  pH • 7.
Because the add catalyzed rate constant 1s large, significantly higher rates
could occur at lower pH's.  Using  Equation 11-85, the rate constant for pH « 5
1s:
        ku -  1.1 x  10* (10"5) + 5.8 x 10"3 * 3.3 (10~9)
                    .1
           «  .23 day l
At this lower pH, degradation by abiotic hydrolysis would be very rapid.   Thus,
determining the  pH  1n  the Aurum Mirth River and Lake Castile Is very  Important.
Summary
     The consideration given to transformation, transport, and spedatlon processes
Indicates the following processes  are of potential Importance to the  fate of
pentachlorophenol 1n the Aurum Mirth watershed:
        e     Acid-base effects
        e     Sorptlon
        e     B1odegradat1on
        e     Photolysis
        e     Hydrolysis.

                                        -40-

-------
   Since the three transformation processes are potentially Important,  there 1s
   a good possibility that the Initial pentacnlorophenol  concentration  of 20*ig/l
   will be reduced below the 6.2 ng/1  standard.  Therefore further analysis as
   presented in the specific water body sections is warranted.
        The results of this example agree with the summary of rate processes given In
   Table 11-11 except for the case of  hydrolysis.  This demonstrates that the process
   summary table can serve as a useful guide but should be supplemented with actual
   data whenever possible.
                            END OF EXAMPLE II-l
2.3  SPECIATION PROCESSES

2.3.1  Acid-Base Effects
     The fate of toxic organlcs which are either acids or bases  can be strongly
affected by the concentration of hydrogen Ions in a water body.   It Is therefore
necessary to have a means for estimating this Influence.   This section will  first
present a brief review of acid-base equilibria and then will  give a technique for
quantifying the influence of hydrogen ion concentration on the behavior of toxicants.

2.3.1.1  Acid-Base Equilibria
     Acids by definition donate hydrogen Ions, H*, to solution.   Bases, by
definition, accept hydrogen ions from solution.  2-N1tropheno1,  one of the 129
priority pollutants, Is an add and donates hydrogen ions as  shown by the following
reaction:
               OH
         2-nitropnenol           2-n1trophenolate           +   hydrogen Ion
              (HP)                     (P-)                         (H«)
     Acid-base reactions are extremely fast and can be represented by equilibrium
expressions.  For the above reaction the expression would be:
                                          -41-

-------
                                      i_L,K                           (n-io)
                                     [HP]       *
where
        [H*]  «  concentration of hydrogen ions,  moles/liter
        [P~]  •  concentration of nltrophenolate  ions,  moles/liter
        [HP]  -  concentration of undissociated nitrophenol, moles/liter
        [K ]  «  an equilibrium constant for acid dissociation  (also called
          o
                 an acidity constant).
     The extent to which any acid will  donate hydrogen ions to the  solution  depends
on how many hydrogen ions are in solution (the concentration  of hydrogen  ions)  and on
the strength of the acid.
     The concentration of free hydrogen ions in natural waters can  range  from about
  -4      -10
10   to 10    moles per liter.  Hydrogen ion concentrations are normally
expressed in pH units.  In dilute solutions, such as natural  waters,  pH is  defined as
the negative logarithm of the molar hydrogen ion concentration (pH »  •^09iQ [H 3).
For the above two concentrations the pH values are 4 and 10.
      The  strength  of an acid  is  quantified  by the equilibrium constant, K .
                                                                         u
For very  strong acids (those  which most readily donate hydrogen 1or»s) the value of
this  constant  is greater than unity.   Included in this group are strong acids such as
hydrochloric and nitric add.  Toxic organic acids, though, are generally weak acids
                              -3        -9
and have  K  values between  10    and 10  . K, values are typically expressed in terms
           a                                 a
of  negative base ten logarithms. When  this  approach is used the equilibrium constants
are called  "pKa" (pKa - -log1Q Ka).
      When  the  pH of a solution is the  same  as the pK,  value of an add (I.e., pH
                                                    d
«  pKJ, 50  percent of the add will have  donated  Its hydrogen ions to the solution
    Q
and will  exist  as  a charged anlonlc species.  For pH values greater than the pK
                                                                               Q
value  by  one or more units, the  acid will have donated essentially all of its hydrogen
ions  to the solution and will exist in the  anlonlc form (I.e., P").
      Tne  extent to which any  base will  extract hydrogen Ions from solution depends
upon  the  concentration of hydrogen ions  In  solution (pH) and on the strength of the
base.   The  strength of a base is quantified by an equilibrium constant, K. .  For
very  strong bases  (those that most readily  extract hydrogen Ions from solution) the
value  of  K. is  of  the order of 1. Toxic organic  bases  are generally weak and have
Kb values between  10   and  10"   .  In  a manner similar to adds, *b is typically ex-
pressed  in  terms of negative  base ten  logarithms  and 1s called "pK," (pKfa •
      Water itself  can behave  as  a weak acid or a  weak  base:
                                         -42-

-------
        H_0 5=» H* + OH"  (acidic behavior)
        H20  *  H*5=* H.o"   (basic behavior)
Note that [H*]-[OH~] « K
where   [OH~]  -  the concentration of hydroxide ion, moles/1
        Kw     *   io'14, at 20°C
        pKw    a   14, at 20°C.
     When the pH of a solution equals the value (pK  - pKfe) of a base, 50
percent of the base has accepted hydrogen Ions and will exist as a charged
cationic species.  For pH values greater than one unit above the value of
(pK  - pO, essentially all of the base will exist 1n electrically neutral
form (e.g. NH_).   For pH values less than the value of (p*w - pKb) by 1
or more units, the base will essentially exist in the electrically charged cationic
form (e.g., NH*).
     Table 11-12 summarizes the behavior described above for acids and bases.
Values for pK  and pK.  for selected toxic organic acids and bases and values
°f P*w are given in Table  11-13.  Additional pK, values can be found In
     W                                         A
Donigian et_ al_.  (1983).
     Since toxic organics almost always exist in very low concentrations and are at
best only weak acids or weak bases, they will have little influence, if any, on the
pH values of  the water.  The hydrogen Ion concentration of the water will, however,
determine whether  acids or bases exist in neutral or Ionic forms.
     Values of pH  for natural waters can be obtained from the USGS, the U.S. EPA, and
state and local agencies.  Waters with low alkalinities (e.g., _<_ 50 mg/1 as CaC03,
or 1 mill1equivalent/11ter) are quite susceptible to changes in pK due to  natural
processes such as  photosynthesis and respiration and even to relatively small additions
of strong acid or base. Selection of representative pH values for such waters will
require more data  than for systems with higher alkalinities where less change in pH
can be anticipated.

2.3.1.2  Quantifying the Influence of pH on Toxicant Volatilization
     Only electrically neutral species are directly volatile. Volatilization rate
expressions must therefore use as the concentration of toxicant only that  fraction
which is electrically neutral (non-Ionic).  The fraction of an acid or base which Is
In the non-Ionic form can be determined by use of the expressions given below:
     For organic acids:
                                         -43-

-------
                                      TABLE 11-12

                 OCCURRENCE OF ACIDS AND BASES IN NEUTRAL AND CHARGED
                        FORMS AS A FUNCTION OF pH, pK , AND pK.
                                                    d        D
                Adds
               Bases
   Definition:  Hydrogen ion donors
Definition:   Hydrogen ion acceptors
Example:
  HN03  —t* H *

General  Reaction:
                                            Example:
                                              NH.  +  H*  -^

                                            General Reaction-.
                 NH,
HP — •»•

•kU
PK+3
O
"*'
pK -2
PV3
H + P"
Sped at 1 on:
Fraction in
Neutral Form
0.001
0.01
0.09
0.5
0.91
0.99
0.999


Fraction in
Ionic Form
0.999
0.99
0.91
0.5
0.09
0.01
0.001
8 * H — •»- BH
Speciation :
Fraction in
pH Neutral Form
PVPV3 0<999
P^V2 °'99
pK -pK.+l 0.91
pK -pK 0.5
pK -pK.-l 0.09
pK^-pl^-2 0.01
PVPV3 °'001




Fraction in
Ionic Form
0.001
0.01
0.09
0.5
0.91
0.99
0.999




     For organic bases:
                                 B°  "
where
                             (H-12)
        aAo  "  tht dec1ma1  fraction of the organic add  which  1s  In  the  elec-
                trically neutral  (noo-ionic) form
        "Bo  "  th* decimal  fraction of the organic base  which  is  in  the  elec-
                trically neutral  (non-1onlc) form
        A    •  the total  dissolved concentrations  of the toxic organic add  (e.g.,
                HP+P~), also called the analytical  concentration of A
        B    •  the total  dissolved concentration of the  toxic  organic base (e.g.,
                BH* + B).  also called the analytical  concentration of B.
The rate expressions then  become  in gent-al  form:
                                         -44-

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                                TABLE 11-13
             pKa AND pKfa VALUES FOR SELECTED TOXIC ORGANIC

              ACIDS AND BASES AND VALUES OF pK  FOR WATER
        Acids

Phenol
2-Chlorophenol
2,4-Dlchlorophenol
2,4,6-Trichlorophenol
Pentachlorophenol
2-N1trophenol
4-N1tropheno1
2,4-D1nitrophenol
2,4-D1methylpheno1
4,6-01nitro-o-creso1
        Bases
    10.0
     8.52
      .85
      .99
7.
5.
4.74
7.21
7.15
Senzidlne
     4.09
    10.6
     4.35
  9.34, 10.43
Seawater
14.63 at 5"C
14.53 at 10°C
14.35 at 15°C
14.17 at 20°C
14.00 at 25°C
13.82 at 30°C

14.03 at 5°C
13.81 at 10°C
13.60 at 15°C
13.40 at 20°C
13.20 at 25°C
13.00 at 30°C
Notes:

  4 All pKa values from Callahan ej aj (1979).

  b All pKb values from Weast and Astle (1980).

  c pK^ values from Stumm and Morgan (1981) and from Dlckson and R1ley (1979).
                                   -45-

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     and

                                    R    «   >
-------
                                   TABLE  11-14

                  PROCEDURE FOR CALCULATING  FRACTION OF A COMPOUND
                     WHICH IS  IN THE  NEUTRAL (NON-CHARGED) FORM
        1.   Decimal  fraction of a compound which is In the
            neutra[  (non-charged) form"
            F.T

            For  Organic  Bases     %  • -   « - : - r       (2)
                                    Bo   B      *
        2.   Procedure

            a]   Find the  pH value of the water, pH •
            a)   For an  organic add, use Table 11-13 to find the
                p«A value  of  the organic acid, pK. « _ .

            c)   For an  organic base, use Table 11-13 to find the
                pK   value  of  the organic base,
            d)   Also  use  Table 11-13 to find the pKL, value for water,
                 K  -
       3.  Substitute:   For  organic  acids  substitute pH and
           p*A into equation 1.   0.  «	.


                         For  organic  bases  substitute
           pH, pic, and  pKy  into  equation  2.  o    • 	
           Note:  10° •  l   (any number  to  the  zero power equals  1)
       4.  For approximations of  the  decimal  fraction of a compound
           which 1s 1n the  neutral form  use Table 11-12.
fates of sorbates and  solutes  can  be significantly different.  Sorbates are trans*

ported along with sediments, and can be deposited in river or lake beds to remain

Indefinitely.  Sorbates  are in many ways protected from transformation processes

which would otherwise  affect the solute.  For example:
                                         -47-

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        •    Microblal degradation rates can be reduced.  Steen et^ al_. (1978)
             performed tests which showed that sorptlon of toxicants to suspended
             sediments renders some compounds unavailable for biodegradatlon 1n the
             adsorbed state.
        •    Volatilization is diminished.  Since volatilization of a chemical
             occurs from the dissolved phase, the sorbate Is not directly available
             for volatilization.  Rather, the sorbate first desorbs before 1t
             volatilizes.  Example 11-4 Mill show the significant influence of
             sorption on volatilization.
        •    Direct photolysis of pollutants adsorbed on suspended particles is
             inhibited in some cases.   Further, suspended solids deposited on
             the bed of a river, lake, or estuary, receive very little radiation
             for photolytlc reactions.
     The net interaction between the surface of a solid and sorbate can result  from a
variety of forces, including coulomblc attraction. Van der Waals forces, orientation
energy, induction forces, hydrogen bonding, and chemical forces (Reinbold et al.,
1979).  In the case of many organic compounds, the solute-solvent Interaction  is
often weak so that even a weak sorbate-sorbent attraction can result fn sorptlon.
This type of sorptlon is referred to as hydrophoblc sorptlon because of the Importance
of the weak solute-solvent attraction.  Hydrophoblc sorptlon will be the topic  of
much of the following discussion, but  1t 1s preceded by brief discussions of equi-
librium Isotherms and sorption kinetics.

2.3.2.2  Adsorption Isotherms
     Adsorption Isotherms describe the relationship between the amount of chemical
sorted and the equilibrium solution concentration.  The most commonly used Isotherms
are:
        •    Langmuir Adsorption Isotherm.  This equation was originally developed to
             describe adsorption of a  gas to a solid surface, but has been used to
             describe solid-liquid sorptlon.
        •    Freundllch Adsorption Isotherm.  This empirical equation 1s based  on
             surface-free energy and monolayer capacity.
        •    Linear Adsorption Isotherm.  This equation assumes that there 1s  a
             linear relationship between the concentrations of solute and sorbate at
             equilibrium.  It 1s valid for dilute solutions.
Figure II-* shows example comparisons  between the three Isotherms, and Includes
the equations which describe each isotherm.  The quantity X 1s the amount of sorbed
chemical per mass of sediment, and CM  1s the amount of dissolved chemical per
                                          -48-

-------
         I
         c

         I
         91

         I
5000 r-
     I
4500 •-
           4000 —
3500 r
3COO
                              Linear Isotherm
                                                Freundlich Isotherm
                                                  X -kf-Cw1'"
         o<
                    0.5    1.0    1.5    2.0    2.5    3.0    3.5    4.0    4.5    5.0
                                Cw (ug dissolved chemical/? solution)
      FIGURE  11-4    ISOTHERMS FOR ADSORPTION OF  A HYDROPHOBIC  POLLUTANT
                       ON  SEDIMENTS

volume of solution.  The remaining variables are unknown parameters required to
define the relationship between X and Cw.  The linear Isotherm has one unknown
parameter (K ), while both the Freundlich and Langmulr Isotherms have two unknown
parameters (kf,n and m,b, respectively).
     For the purposes of this document, analyses will  mostly deal  with dilute
aqueous solution In the range where the linear Isotherm 1s generally valid.  This
approach has the advantage of requiring that one unknown parameter (K ) be
evaluated, rather than two, and of being easier to manipulate mathematically.
Section 2.3.2.4 will present methods of predicting the unknown parameter K .

2.3.2.3  Kinetics of Adsorption
     Sorptlon of organic pollutants 1s often treated as a process  which achieves
rapid equilibrium so that expressions of kinetics are not needed.  The equilibrium
approach will  be used in the remaining chapters of this document.   However, a brief
                                         -49-

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Introduction will be given of sorptlon kinetics.
     Studies of sorptlon kinetics are apparently  few, with the result  that  parameters
required in rate expressions are 111  defined and  applicable only  under a  specific  set
of conditions.  Under these constraints, klretlcs expressions  become less attractive
unless the user can determine values of the rate  constants which  apply to the specific
system being Investigated.
     Most typically, kinetics expressions for sorptlon and desorptlon  are chosen to
be first order.  Specifically:
expresses the kinetic expression for the solute and

                                        S|£--kdx                         (IMS)

for the sorbate.  The concentrations X and Cw are not necessarily equilibrium
concentrations.  In these two equations, the rate constant for adsorption 1s k.
                                                                              o
and for desorptlon is k^.  When the rates of adsorption and desorptlon are equal,
Equations 11-14 and 11-15 can be equated, with the result that X • K C ,
where Kp . ka/kd<
     Karickhoff (1979) Investigated the sorptlon and desorption of organic pollutants
and found that a very rapid component of adsorption preceded a much slower component
of adsorption, and that first order kinetics were obeyed during each of the two
periods.  For the fast process, the time constant was found to range from 4 to 30 per
hour, while for the slow process the time constant ranged from 0.06 to 1.5 per hour.
Approximately half of the sorptlve equilibrium was realized within minutes, while the
slower component required days or weeks to complete.  The slower second period was
visualized as diffusive transfer to sorptlon sites that were Inaccessible directly to
the bulk water.  Thus, equilibrium conditions are more likely to be rapidly attained
when the number of easily accessible surface sites exceeds the amount of available
sorbate, e.g.  when suspended sediment concentrations are high.

2.3.2.4  Partition Coefficients for Organic Chemicals Obeying Linear Isotherms
     The single unknown parameter, K , which relates the sorbate and solute
for linear isotherms Is called th« partition coefficient.  A number of studies
have been completed which develop empirical relationships for partition coeffic-
ients 1n natural sediments.  Several of these studies will be summarized here.
Theoretically based methods of estimating partition coefficients exist, such as
a  thermodynamic approach described 1n Pavlou (1979);  however, these will not
be discussed here.
                                          -50-

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     Karlckhoff §1 il- (1979) examined the sorptlon of aromatic hydrocarbons and
chlorinated hydrocarbons on natural  sediments.  They found It  convenient to relate
the partition coefficient directly to organic carbon content of the sediments as
follows:

                                  Kp - KocxQC                               (11-16)

where
        Knr »  partition coefficient expressed on an organic carbon basis
        xoc "  mass ^ract^on °' organic carbon In sediment.
These workers were able to expand this relationship to segregate the Influence
of particle size as follows:
where
        f    •  mass fraction of fine sediments (d < 50 urn]
        x   «  organic carbon content of coarse sediment fraction
        x   »  organic carbon content of fine sediment fraction.
     KaMckhoff et al . (1979) were able to relate K._ to the octanol-water
                ~ " --                              Ut
partition coefficient  and to the water solubility by the following relationships:
where
        KQw  •  octanol-water partition coefficient (concentration of chemical in
                octanol divided by concentration of chemical In water, at equilibrium)
and

                              KQC - -0.54 log Sw + 0.44                      (11-19)
where
         SM  -  water solubility of sorbate, expressed as a mole fraction.
 The water  solubilities of the compounds examined ranged from 1 ppb to  1000 ppm.
      Hassett et al .  (1980) found a similar relationship between K   and K
             — — •—                                               oc      ow
 for organic energy-related pollutants.  Figure  1 1-5 shows the relationship. Data from
 KaMckhoff et_  aj_.  are Included  1n the plot for comparison.
      Prior to  the  work of Karlckhoff et^^K, Chlou et^ aK  (1977) Investigated
 the relationship between octanol-water partitioning and aqueous solubilities for a
 wide  variety of chemicals Including aliphatic and aromatic hydrocarbons, aromatic
                                          -51-

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       7


       6

       5

   *84
    ^Jt
    ^5
   —  3

       2
                  1234567
                                       log  KOH

     REFERENCE:   HASSETT £i  AL. (1980)

   FIGURE 11-5  RELATIONSHIP BETWEEN KQC  AND OCTANOL-WATER PARTITION

                  COEFFICIENT  («ow)  OF ENERGY-RELATED ORGANIC POLLUTANTS
adds,  organochloMne and organophosphate pesticides,  and polychlorlnated blphenyls.
Their results,  shown 1n Figure II-6, cover more than eight orders of magnitude  1n
solubility  and  six orders of magnitude  1n the octanol-water  partition coefficient.
The regression  equation based on  this figure 1s:
log
                                 «  5.00 - 0.670 log
(11-20)
where
              solubility, tntimol/1.
Bowman and  Sans (1983) report additional K   versus S^ relationships.  Leo et
                                        ow         w                    —
al. (1971)  have tabulated K   values  for thousands of organlcs.  Subsequent to

their work  1n  1971, they have determined K.  values for many  additional com-
                                        ow
pounds.

     Brown  and Flagg (1981) have  extended the work of KaHckhoff it.il. *** developing

an empirical relationship between K   and K   for nine chloro-s-tr1az1nt and
                                 Ow      OC
d1n1troanH1ne compounds.  They plotted their results, along  with those of Karlckhoff

•t •!•. >s  shown 1n Figure II-7.   The combined data set produces the following

correlation:
                                       -52-

-------
                c.0'
               3 '0s
               I"'
                 10
                   r*    ro1   io-
                                         (0    10*    IO*    10*   10*    »0*
                                  Solubility in Woltr
                REFERENCE:   CHIOU EI AL,    (1977)
               FIGURE  11-6   CORRELATION  OF AQUEOUS  SOLUBILITY
                              WITH  OCTANOL-WATER PARTITION  COEFFICIENT
                        log  K   • 0.937 log K   - 0.006
                             oc
                                                                            (H-21)
The linear correlation between  K   and K   for the compounds studied by  Brown
                               UC      OW
and Flagg has a larger factor of  uncertainty than those studied by Karlckhoff
et al.  Other relationships  between  K   and K   for specific groups of
"™ ^"~                               OC      OW
compounds are reported 1n  Karlckhoff (1984).
     The previous paragraphs  have shown how the partition coefficient K   can b«
predicted for organic hydrophoblc compounds which obey a linear Isotherm relationship.
First, K   1s predicted based on  either water solubility or the octanol-water
partition coefficient.  Tables  II-5  through 11-9 shown earlier contain K  values
for a number of compounds.   Then  based on an estimate of organic carbon  fraction 1n
the fine and coarse sediments,  K  can be estimated from Equation 11-17.   This
procedure Is summarized 1n Table  11-15.
2.3.2.5  Solute and  Sorbate Fractions
     The relative  amount of pollutant sorbed and dissolved depends on both the
suspended sediment concentration and the partition coefficient,  and at equilibrium 1s
given by:
                                                                           (n-22)
                                     4; •
                                         -53-

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                                                         AND FLAGG (1981)
                                                  KARICKHOFF ET  AL,  (1979)
               0  Q50  100  !JO  200 Z.SO  JOO  J.SO  «.00  4.50  5.00  5.50  5.00 630
                                       LOG Kow

              Note:  The actual error bands for this figure are probably
                    greater than  indicated here  due to error in the
                    measurement of K   .
                                    ow
where
      FIGURE  11-7
RELATIONSHIP BETWEEN  KQC  AND Kow FOR  COARSE SILT
               total  dissolved  phase  concentration
               C.*CS
               xs
               partition coefficient
               suspended sediment  concentration, on a part per part basis
               mass of sorbed pollutant  per mass of suspended sediment.
Equation 11-22 can be Illustrated more  vividly by tabulating ranges of K
and  S values.  Table 11-16 shows this  Information.  Partition coefficients and
suspended sediment concentrations range from  10° to 10.  For the lowest
value of the partition coefficient nearly all of the pollutant 1s present in the
dissolved form, regardless  of the suspended sediment concentration. Also, for low
suspended sediment concentrations, nearly all of the pollutant is dissolved, unless
the partition coefficient is extremely  large.  When relatively high partition
coefficients and sediment concentrations occur simultaneously, then most of the
                                         -54-

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                                 TABLE  11-15
               PROCEDURE FOR CALCULATING  PARTITION COEFFICIENT
1.   Partition Coefficient
      P    oc

2.   Procedure
3.
                    Xs   * f xf  1
                     oc       oc J
                                                                         (1)
     a.   Find KOW (octanol-water partition coefficient)
c.

          (1)  Use Tables II-5 through II-9
                for priority pollutants.  K
                OR, 1f the value 1s not tabulated
          (2)  Estimate K^ by:
               log KW . 5.00 - 0.670 log Sw •
               where S  » solubility, t*mole/l
                            .      *	,	 x 10
                              molecular weight
               Use Tables II-5 through II-9 to find Sw (mg/1)
     b.   Find K
                OC'
     *oc • °-63 Kow
                                                                         (2)
          Estimate:
          (1)  f (mass fraction of silt or clay) • _ ,  (0
-------
                                   TABLE 11-16

               RELATIONSHIP OF DISSOLVED AND SOR8ED PHASE POLLUTANT
                    CONCENTRATIONS TO PARTITION COEFFICIENT  AND
                              SEDIMENT CONCENTRATION
*p
10°




101




102




103




A
104




S (ppm)
1
10
100
1000
10000
1
10
100
1000
10000
1
10
100
1000
10000
1
10
100
1000
10000

1
10
100
1000
10000
VCT
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
0.9
1.0
1.0
1.0
0.9
0.5
1.0
1.0
0.9
0.5
0.1

1.0
0.9
0.5
0.1
0.0
1

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                       	 EXAMPLE  II-3
         Determine the fraction of benzo(a)pyrene  that  1s  dissolved  1n a  system
    containing 300 ppm suspended solids.   The suspended sediments are 70  percent
    fines (d < 5"  Mm) and the weight  fraction of  organic  carbon is  10 percent of
    the fines ana 5 percent of the sand fraction.
         From Table 11-9,  the solubility  of benzo(a)pyrene is  0.0038 mg/1, and
    the octanol-water  partition coefficient 1s 10  .   If,  for the moment,  the
    octanol-water partition coefficient is Ignored,  Equation 11-20 can be used
    to predict K   based on i
    be converted to mole/1:
to predict KQW based on solubility.  The solubility of 0.0038 mg/1  must
             (0.0038 rng/1) (HT3  g/ng)
              - 0.015 umole/1

   From Equation 11-20,  the predicted octanol-water partition  coefficient  1s:
        log K   - 5.00 - 0.670 log (.015)
                « 6.22
   so K~ " 106'22,  which 1s acceptably close to the tabulated value  of  10 .
   Using the tabulated K    K   Is computed from Equation  11-18:
                        ow   oc
        K   • 0.63xl06
         oc
            • 630,000
   From Equation 11-17,  the partition coefficient becomes:
        Kp «  630,000 [0.2 (1-.7)  (.05) +  0.7 (.10)]
           >   46,000
        The suspended sediment concentration for the system  1s 300  ppm,  or 300-10"
   parts per part.   Using Equation 11-22,  the fraction  of  benzo(a)-pyrene  which  1s
   dissolved Is:
j        UT     1 + 300 •  10"° •  46,000
           • 0.067 or about  7 percent
.   Consequently, most of  the benzo(a)pyrene 1s  present  as  sorbate.
I
I	END  OF  EXAMPLE  II-3
                                         -57-

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2.4  TRANSPORT PROCESSES

2.4.1  Solubility Limits
     The concentration of a compound in a natural  water,  and therefore the rate of
transport by that water, can be limited by Its equilibrium solubility.  The aqueous
solubility of organic compounds ranges widely:

                                         Aqueous Solubility at 25°C
                              (mass which will dissolve in i liter of water)
               Compound       	(in milligrams)	
               Sucrose                         2,000,000
               Benzene                             2,000
               Toxaphene                               2
               Chrysene                                0.002
     Non-polar compounds have limited solubilities In polar solvents such as water.
The solubility of toxic organic compounds 1s generally much lower than for Inorganic
salts.  Equilibrium solubilities for toxic organic compounds are given in Tables 11-5
through 11-9.  Solubility increases with temperature for most organic compounds,
typically by a factor of about 3 from 0°C to 30°C.
     Drganics are generally less soluble 1n sea water than in fresh water as can be
seen in the tabulations below (Rossi and Thomas, 1981):

                                           Solubility at 25°C
                                    Distilled Water        Sea Water
                    Compound            (mg/1)              (mg/1)
                    Toluene             S07                  419
                    Acenapthene           2.41                 1.84
                    Pyrene                0.13                 0.09
     In the absence of colloids or micelles, the maximum amount of a toxic organic
substance which can be held in the water column under equilibrium conditions 1s just
the aqueous equilibrium solubility $w, plus the equilibrium amount of solute
sorted on suspended matter:

                                 CT  -  Sw + fs (Sw)                        (11-23)

where
         CT     *  total amount of compound which can be held 1n a natural
          1                                                 .1
                   water at equilibrium conditions, i>g liter

         Sw     -  equilibrium aqueous solubility, *g  liter"1
         f (S  )  •  equilibrium amount of sorbate on suspended matter; a
                   function of S  .   f  1s the sorptlon Isotherm  function.

                                          -53-

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If a linear sorption isotherm 1s used, as is commonly the case for trace constituents
(see Section 2.3.2), the above expression becomes:

                                  CT  1  Sw (1 * Kp S)                      (11-24)

where
        K   «  linear partition coefficient (see Section 2.3.2.4), liter Kg"1
         S  »  the "concentration" of suspended matter (sorbent),  Kg liter
     The inequality results in the above equation because at high  solute concentrations
linear Isotherms overpredlct the amount of solute so r bed. The use  of linear sorption
Isotherms (a common practice for trace constituents) 1s adequate at pollutant  concen-
trations which are equal to, or less than, one half of the equilibrium solubility.
When linear sorption isotherms are used, e.g. those with the simple partition  coeffic-
ient approach (K ) presented in Section 2.3.2, one must then check to insure that
the aqueous pollutant concentration 1s less than or equal to one-half of its equi-
1 Ibrium solubi 1 ity.

2.4.2  Volatilization

2.4.2.1  Introduction
     Volatilization is defined as the transfer of matter from the  dissolved to the
gasec.i phase.  A considerable number of toxic substances volatilize in the natural
environment.  Volatilization rates depend on the properties of the toxicant and on
the characteristics of the water body.  If a toxicant 1s "highly volatile", then
obviously volatilization Is an important process affecting the fate of the toxicant.
However, even for toxicants which are considerably less volatile,  volatilization
cannot always be Ignored.  This 1s because the fate of a toxicant  Is governed  by a
variety of processes.  If volatilization proceeds as fast as other competing mechanisms,
even though all  the rates might be slow, then volatilization will  Influence the fate
of the toxicant.
     Methods will be provided 1n this section to predict the volatilization rate for
toxic organic substances, which volatilize according to the following relationship:
                         .    v  (c -    )  .  -k;   (C -     )                (II.25)

where
        C   «  concentration of toxicant 1n dissolved phase  (concentration of solute)
        KV  «  volatilization rate constant in units of length/time
        KY  »  volatilization rate constant 1n mixed water body In units of
               time"1
                                          -59-

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        Z   •  mixed depth of water body
        P   «  partial pressure of toxicant in atmosphere above the water body  being
               investigated
        KH  •  Henry's Law constant.
For many applications the partial  pressure of the compound in the atmosphere  is zero,
so that Equation 11-25 simplifies  to:

                                   -i£  »   -k'  C                          (H-26)
                                    3*       V

     *n alternate form of Equation 11-26 is in terms of the total  pollutant concentra-
tion, CT, and the site specific volatilization rate constant, kym:


                                   1TT  ' ^  CT                       (II-2?)
where
                                            k   a
                                     k   ,   .v   *                         (11-28)
                                      vm      Z

where
         aM  «  fraction of toxicant present in dissolved phase.
The following sections will illustrate how to predict the volatilization rate for
toxicants of either low or high volatility.  But first, a brief discussion of Henry's
Law is required.

2.4.2.2  Henry's Law
     Henry's Law is an expression  which relates the concentration of a chemical
dissolved in the aqueous phase to  the concentration (or pressure)  of the chemical  in
the gaseous phase when the two phases are at equilibrium with each other. One common
method of expressing Henry's Law is:

                                P   -  ^                               (11-29)

where
         P  •  equilibrium partial pressure of pollutant in atmosphere above  the
               water, atm
        C   •  equilibrium concentration of pollutant in the water, mole/m
                                          3
        Ky  •  Henry's Law constant, atm m /mole.
Henry's Law in this form is valid for pollutants present in concentrations up to 0.02
expressed as a mole fraction.  For compounds with molecular weights greater  than 50
g/mole, a mole fraction of 0.02 represents a concentration of at least 55,000 mg/1.
                                          -60-

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Typically toxic pollutants 1n the environment are present at levels  far below this
concentration.
     Table 11-17 contains values of Henry's Law constants for a number of  selected
hydrocarbons.  In the table, Henry's Law constant 1s expressed 1n units of atm
m /mole.  However, In the literature Henry's Law constant can be defined In
numerous ways.  A second, widely used method of defining Henry's Law constant 1s:

                                     <  «  .£                               (H-30)

where
        C   •  molar concentration In air,  mole/m
        «•  «  alternate form of Henry's Law constant,  dlmenslonless.
         n
Equations 11-29 and 11-30 are related as follows:
where
        T. «  temperature of water, °K.
        Ru - universal  gas constant.
This relationship 1s based on the Ideal  gas law.  Equation 11-31 1s useful  because of
the frequent necessity  to convert literature data from one set of units to  another.
     Henry's Law constant can be estimated for slightly soluble compounds
(mole fraction <_ 0.02)  by the following  expression:

                                                P  x MW
                                                       w
where
        P   »  saturation vapor pressure of pure compound 1n Torr
        MM  •  molecular weight
        S   •  solubility In water 1n ppm.

     Figure  II-8 Illustrates the limits of Henry's Law for an acetone-water mixture.
Henry's Law  1s obeyed by acetone 1n  region 8 (mole fraction of acetone <0.1) and by
water  In  region A  (mole fraction of  acetone >0.95).  Notice that the generally
accepted  limit of  validity of Henry's Law (mole fraction £0.02) corresponds to
concentrations of  34,000 mg/1 to 227,000 mg/1 for compounds with molecular weights
between 30 to 200.  Thus Henry's Law is likely to be applicable In nearly all  cases
of concern In the  natural environment.  For pollutants which happen to be largely
soluble,  however,  care must be taken to calculate Henry's law by some method other
than Equation 11-32.
                                         -61-

-------
                 TABLE 11-17



HENRY'S LAW CONSTANT FOR SELECTED HYDROCARBONS

Oltftnt
Ac*tyl*n«t
EtMn* (f)
Propcnc If)
1-Buttn* (9)
l-P«nt»«t (I)
l-*«i*nt (t)
2-H«ptr«c ropyn« If)
l-Sutyn« (f)


CyclMtktntt
Alk*n»i
C/c ) opt nttft* (i)
Cycloheatn* (t)
Mflliy)cyClPO«fiUnt (t)
^ttn/tcyclph*x*M (t)
PrQpylcyclop«nt«n* (t)
Isobulint (f)
IsOPtnurw (t)
2-N*tH;lp«nt*M (t)
2-»tetftytH«iu«« (t)
2.2-DiB*thyl(wntarM (l)
3-Mttr.ylhtpt4n« (i)
2.2.4-:ri»iftHytp««t«n« (*)
PolycMpnnttM
Aroclor 1242
Aroclor 1748
Aroclor 12S4
Aroclor 12(0




• TlttM in MtlMttO' VCllMt
Si

ConttMt
0.214
0.232
0.2M
0.398
0.412
0.418
0.905
0.0110
0.0194




0.18?
O.I9C
0.3*7
0.42*
0.893
1.24
1.3*4
1.73
.42
.IS
.71
.04
.93*
3.5 1 10°
7 . 1 1 10*'




b«M4 on k, •


^ (CW.T,*
20.
20.
20.
20.
20.
20.
20.
19.8
20.




20.
20.
20.
20.
20.
20.
20.
20.
20.
20.
20.
20.
20.
15. »
18.9
18.9
19. t






AroMtiCt
8*«"«"*
Htthiiw (t)*
Ethan* (r)
PropaM (t)
•-BuUnt (f)
n-ftnttM (t)
n-Ht>M4 (t)
»-HtpUM (t)
•-OcUnt (t)
•-Mono* (t)
D«CMM (t)
Dootcint (t)
T«tr«d«can« (t)
,„,,-.
DOT
Al«rtn
EndHn
HepucMor
CMor(UM
TOMPtltM
20 oa/hr tnd k • 3000 o»/hr.
S;
tltni^ * s LMt
Co«tt*nt
5.49»1(TJ
i.MilO*}
8.73«10-3
S.27»10*3
1.4S»10*J
4.2S«10'4
*.3*«10'4
2.28J110-4
2.3SJUO"4
l.tSUO"''
1.4talO-*


O.MS
0.499
0.707
0.947
1.28
1.8S
2.07
3.22
3.29
4.13
7.12
1.14

-9UO-6
.o»io-'
.4*10-*
.»*io-'
.S.10-3
uio-5
0.1



k, (c^M>)*
19.4
19. S
19. f
19.4
19.8
14. i
lt.0
n.f
11.9
18.2
9.1


20.
20.
20.
20.
20.
20.
20.
20.
20.
20.
20.
20.
20.
1.9
0.01
0.02
0.80
0.0*
18.
4.8
19.8

                      -62-

-------
 Consider acetone-water mixture
                o    o*    CM   o-e   0-8   K)
                  Mole fraction of acetone
Henry's Low Is obeyed:
     by acetone when mole  fraction  of  acetone  £0.1 (Region B)
     by water when mole fraction  of acetone   >0,95 (Region A)
General range of validity:  mole  fraction  <0.02
     MW             Concentration when  mole fraction
                       0.02
      30
      75
     100
     200
 3UOOO mq/1
 85000 mg/1
113000 mg/1
227000 mg/1
      FIGURE II-8   RANGE OF VALIDITY  OF  HENRY'S  LAW
                           -63-

-------
     Tables II-5 through II-9 presented vapor pressure and solubility data for the
organic priority pollutants, which can be used to predict Henry's Law constant.
Although Equation 11-32 is not valid for highly soluble chemicals, generally  the
toxicants of interest nere are only slightly soluble,  so that the expression  is
adequate..  The dimensionless form of Henry's Law constant is expressible as:
                                      16.04 P  x MW
All variables have been previously defined.
                                  EXAMPLE 11-4
                       Henry's Law Constant for Chloroform

        Calculate Henry's Law constant 1n the two forms expressed by Equations
    11-32 and  11-33.  Chloroform  (also called trlchloromethane or CHCl^) has
    the following properties:
           Vapor pressure   » 150 Torr (from Table 1 1-5)
           Solubility       • 8200 ppm at 20°C (from Table II-5)
           Molecular weight      »           12 (carbon)
                                             1 (hydrogen)
                                        3 x 35.5 (chlorine)
                                        Sum - 119
    From Equation 11-32:

                   150x119            -i
             H    760x8200
   From Equation  11-33, at 20«C  (293°K):

                  16.04x150x119
                     8200x293

 j   Henry's constant, expressed as K^, had been found experimentally to be
 •   0.12,  the  same as predicted here.

 I ----- ENO OF EXAMPLE  II-4
 2.4.2.3   Two  Film  Theory of  Volatilization
      When a chemical  volatilizes  from water, the  process can be visualized as a mass
 transfer  occurring over several distinct  steps.   Figure 11-9 presents a schematic
                                          -64-

-------
               Toxicant  concentration
                 Vapor phase
           U-^
                  Direction of  movement
            •. '• •   Gas dim '.'.  •' . • •       ''    '

      FIGURE  11-9
SCHEMATIC REPRESENTATION OF VOLATILIZATION
FROM  SOLUTION  PHASE TO  LIQUID  PHASE
representation of the process.  The concentration of the chemical  1s  C  In the bulk
liquid solution.  As the chemical  moves upward 1n the bulk solution It  moves through
a thin "liquid film" where a concentration gradient develops because  the transfer
rate Is limited by diffusion.  The dissolved chemical  then volatilizes  and passes
through a thin "gas film", where again transfer may be limited, before  reaching the
bulk vapor phase.
     At the Interface between the gas and liquid films the concentrations 1n the
liquid (C^} and In the gas (Pc1, expressed as partial  pressure) are assumed
to be In equilibrium and to obey Henry's Law:
                             rc1
                                               (11-34)
                                       -65-

-------
In the absence of net accumulation at  the interface  the mass  flux from one phase must
equal the mass flux from the other, or:
where
        F    •  flux of chemical  1n z direction
        k ,   •  mass transfer coefficient 1n the  gas  phase across  "gas film"
        k^   •  mass transfer coefficient 1n the  liquid  phase  across  "liquid
                film"
PC, Pc1, C,  C^ are defined 1n Figure 11-9.
Since it Is  not convenient to measure the partial  pressure and concentration at the
Interface, 1t 1s worthwhile to develop expressions for bulk transfer  coefficients,
given by:

                                                         -                     {n-36)
 where
         k    •  overall  volatilization rate defined  for  the  gaseous phase
         ky1   •  overall  volatilization rate defined  for  the  liquid phase
         S    •  saturation concentration of chemical  1n  equilibrium with PC
         P'   *  partial  pressure in equilibrium with C.
 Combining Henry's Law equilibrium expressions  with Equations  ..-35 and  11-36 the
 overall volatilization rates become:
J ___ L.i + J_
k     R T   k,,   k .
 vg    u     11    gi
                                                                             (11-37)
 and
                                   1
                                  kvl
                                              (11-38)
 Of the two expressions, normally Equation 11-38 1s  more  useful  for the purposes
 of this document because the pollutants being  analyzed are  1n  the aqueous phase.  To
 simplify terminology Equation 11-38 will  be rewritten as:

                                       .     .     R T
                                      -L._L + -JL_                        (II-39a)
 or

                                                                            (II-39b)
                                          -66-

-------
where the second subscripts to each  variable have been dropped.  The voKtll 1zat1on
rate, ky, is the same as shown earlier 1n Equation 11-25 and depends on k  ,
Kj^, and  ki .
     There are two special  cases  of  Equation 11-39, depending on the value of  Henry's
Law constant.  They are:
                             .  for large  K   (liquid-phase limited)
                           Ck ,  for small  1C  (gas-phase limited)
                            nu             n
                                            (II-40a)
                                            (II-40b)
 10 maice Equation 11-40 usable, "large"  and  "small" values of K^ have to be
 defined.  For cases when the liquid phase 1s  limiting the transfer rate, a large
 fraction, R, of the total  resistance exists in  the liquid phase, or:
                                                                          (11-41)
 Similarly when the gas phase is limiting:
                                      Ml      l     l
                                     R  r  "R  r*rr
                                      \kv/     \kl    KHkg
                                            (11-42)
 Equations 11-41 and 11-42 can be rearranged  to express Henry's Law constant explicitly:
                               k    R
                               _I 	  , for liquid-phase limited
                               kg  1-R
                               if
                               _L ll£   , for gas-phase limited
                                           (II-43a)
                                           (II-43b)
At this point  values  for R,  k1, and k  must be specified.  "Typical"  values
of k  and k1  for surface waters are In the range of 20 cm/nr and  3,000  cm/nr,
respectively.   For R  values  of 0.83, 0.90, and 0.95, the phase limiting values of
Henry's Law constants, converted to units of at* m /mole using Equation 11-31,
are as follows:
                            Henry's Constant (atm-m'/mole)
                   R

                 0.83

                 0.90

                 0.95
Liquid-phase Limited
     7.8 x 10'*
     1.4 x 10-'
       3 x 10-*
Gas-phase Limited
    3.3 x 10'.s
    1.8 x I0's
    8.4 x 10'*
                                         -67-

-------
Hence, for Henry's Law constants larger than about 1.0 x 10   atm  m /mole
most of the resistance to volatilization lies in the liquid phase, and  for  Henry's
Law constants less than about 1.0 x 10   atm m /mole, most  of  the  resistance
lies in the gas phase.  When either of the two phases controls  the volatilization
rate, then the simplified Equation 11-40 can be used in lieu of Equation 11-39.  The
data in the tables presented earlier can be used to predict lenry's Law constant and
then to decide whether the gas or liquid phase limits volatilization.
     Based on the two-film model there are two methods which can be used to estimate
volatilization ratas.  One approach is considerably more simple than the other.  The
simpler approach is based on the following reasoning. Using "typical"  values  of
k^ and k , ky can be estimated based solely on KH as the independent variable,
where K.  75 allowed to vary over its potential range of values. As Table  11-18
shows, KH can vary by at least seven orders of magnitude.   Based on this variabil-
ity of Henry's Law constant, Table 11-19 presents the associated volatilization
rates.  As Henry's Law constant increases, the volatilization  rate approaches
20 cm/hr, the liquid phase limiting rate.  As Henry's Law constant decreases, so does
the volatilization rate, with the lower limit being zero.
     The second method of predicting ky is based on finding k   and k^  individually,
rather than assuming typical values.  The gas-phase transfer rate  can  be  found based
on the evaporation rate of water as outlined  in Mills (1981).   Mills showed that:
                                     k '•  700  V                             (11-44)
where
        k-  »  gas transfer rate for water vapor, cm/hr
        V   -wind speed, m/sec.
This expression was derived from an empirical  relationship shown in Linsley et^ aK,
(1979) for the evaporation of water.  Liss (1973) conducted measurements in an
experimental basin and found that:

                                      ic' «  1000  V                           (11-45)

where the units are the same In Equation 11-44.  Considering that the approaches used
to develop Equations 11-44 and 11-45 are different, their agreement 1s good.  Still
other relationships exist between k' and V (e.g. Rathbun and Tai, 1983).
     The values of k  and k- are related by penetration theory (Bird et
al. 1960) as follows:
                                       kg
                                          -68-

-------
                                   TABLE 11-18
                   HENRY'S LAW CONSTANTS FOR SELECTED  COMPOUNDS
                   Compound
Henry's Law Constant (atm-m3/mo1e)
             Vinyl  Chloride
             Carbon Tetrachloride
             Toluene
             Aroclor 1254
             Flourene
             DDT
             Dieldrin
                3.7
             2 x 10'2
            6.7 x 10'3
            2.8 x NT3
            2.4 x 10'4
            3.9 x 10'5
            2.0 x 10'7
                                TABLE 11-19
             TYPICAL VALUES OF POLLUTANT VOLATILIZATION RATES
                             IN SURFACE  WATERS
^(atm-mS/mole)
10°
10-1
10-2
10-3
io-4
10-5
io-6
10-7
I K^dlmenslonless)
41.6
4.2
4.2 x 10-1
4.2 x 10-2
4.2 x 10-3
4.2 x IO-4
4.2 x 10-5
4.2 x 10-6
kv(cm/hr)*
20.
20.
19.7
17.3
7.7
1.2
0.1
0.01
kv( I/day)**
4.8
4.8
4.7
4.2
1.8
0.3
0.02
0.002

Liquid-film
limited
t
1

Gas-film
limited
 *Us1ng kq - 3000 cm/hr
        k* « 20 cm/hr.
**For water depth »  l m.
                                       -69-

-------
where
        D    «  diffusion coefficient of pollutant In air
         a
        0    «  diffusion coefficient of water vapor 1n air.
         wv
Diffusion coefficient data can be found in such references as Perry and Chilton
(1973), or estimated using the W1lke-Chang method, also In Perry and Chilton.   If an
analytical  method is used to estimate diffusion coefficients, note that it is  easier
to predict the ratio of two diffusion-coefficients than to predict each coefficient
individually because some of the required Information cancels out of the ratio, and
consequently is not needed at all.
     In many cases it 1s acceptable to approximate the ratio of diffusion coefficients
as follows:
                                      wv
                                                                           (11-47)
where
        MM  •  molecular weight of pollutant.
Table 11-20 Illustrates the difference between calculating the diffusion coefficient
ratio by using tabulated data from Perry and Chilton and by using Equation 11-47.
The percent differences between the ratios range from 1 to 27 percent and average  15
percent.  This agreement 1s acceptable for screening purposes.  Combining Equations
11-46,  11-44, and 11-47, the final expression for k  (1n units of cra/hr) 1s:
                                   TABLE 11-20
            COMPARISON OF  TABULATED AND PREDICTED VALUES  OF  DIFFUSION
                      COEFFICIENTS FOR SELECTED POLLUTANTS
    Pollutant
           Diffusion Coefficient  Perry A
             Perry                CMHon
Molecular  ft Chilton  Predicted
 Height    (c«2/sec)  (cm2/$ec)
                                                             Predicted
                                                                         Percent
Chlorobenzene
Toluene
Chloroform
Naphthalene
Anthracene
Benzene
113
92
119
128
178
78
0.075
0.076
0.091
0.051
0.042
0.077
0.088
0.097
0.086
0.083
0.070
0.106
.58
.59
.64
.48
.44
.59
.63
.66
.63
.61
.56
.69
9
12
1
27
27
17
                                         -70-

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                                      kg  •  700 [£) V                       (H-48)

This expression 1s valid for rivers, lakes, and  estuaries.
     The liquid phase transfer coefficient  k^  can be predicted  based  on  the
reaeratlon rate, *a, for the system.  The relationship  proposed by  Smith gt aK
(1981) 1s:
                                      ' 3  \n
                                "l
k'  ,   0.5 < n < 1              (11-49)
where
        DW   •  diffusion coefficient of pollutant 1n  water
        DO   •  diffusion coefficient of dissolved oxygen 1n  water
          2
        ka'   »  surface transfer rate of dissolved oxygen, expressed  1n  the
                same units as k^.
In other chapters of this report, the federation rate  Is presented as  k.,
                                                                      0
defined as:

                                        ka-ka'/z                          (n

where
        Z  •  nrixed depth of water body.
For rivers the mixed depth Is the total  depth, while for estuaries the mixed depth  Is
the total depth only 1f the estuary 1s well  mixed*.  Otherwise,  it  1s  the depth  to the
pycnocllne.  Similarly for lakes, the mixed  depth can  be less than the total depth,
and can be chosen to be the depth of the epIHmnlon.
     The exponent n varies as a function of  the theoretical approach  used  to develop
Equation 11-49.  If film theory Is used. I.e., the film Is considered  to be a laminar
sublayer, then n « 1.  If penetration or surface renewal  theory 1s used, n * 0.5.
Using experimental  approaches, researchers have found  n to vary from  0.5 to t.O.
Since the movement of water In natural water bodies 1s generally turbulent, the
parameter n can be chosen to be 0.5.
     Perry and Chllton (1973) provide data and methods to predict  the diffusion
coefficient of a pollutant 1n water.  The Othner-Thakor relationship,  described
In Smith et,al_.  (1981) can also be used. As an approximate  approach, by  using
the square root of the molecular weights the following expression  results:
     A recent study (Rathbun and Tal,  1981)  used  a  tracer technique to predict the
volatilization rates of four priority  pollutants  from  12 different rivers.  That

                                         -71-

-------
study provides an opportunity to compare, even 1f only to a limited degree,  some
of the methods presented here against field results.  Table 11-21 briefly  summarizes
the results of Rathbun and Tal (1981).  As shown by the values of Henry's  Law constant
for the four pollutants, each pollutant 1s liquid phase United,  since all  Henry's
Law constants exceed 1.0 x 10   atm • /mole.  The study results were unable
to predict differences 1n volatilization rates for the four pollutants, and found
that the best predictive expression was:

        ky •  0.655 k;

Based on Equation 11-51 the screening Methods predict:

        kv" 0.7|£ to 0.8 k^

where the range reflects the variability 1n Molecular weight among the four pollutants.
     If the default value of 20 cm/hr, suggested earlier 1n this  section were used  as
a rough estimate of the volatilization rate for liquid phase limited pollutants,  this
value would fall within the observed range of 1.5 to 24 cm/hr.  It appears that the
screening methods presented here generate acceptable estimates of volatilization
rates.
     Table 11-22 summarizes the two methods presented In the manual for calculating
the volatilization rate constant ky.  The first approach Is more simplified and
1s based on typical values of k  and k,.  In the second approach, k  and
kj are calculated rather than assumed.

2.4.2.4  Volatilization Half-Life
     Numerous researchers have 1n the past calculated the volatilization half-life of
toxicants under controlled laboratory conditions.  The result of some of this work
was shown earlier 1n Tables 11-5 through 11-9.  Typically, researchers have used the
following expression to calculate the half-life:

                                           0.693Z
                                      V—T~                           (1I"
                                               v
where
        *l/2  "  n*1f"H'* (t1*e required for the concentration of the contami-
                 nant to decrease by half).
 It 1s  Important to understand that the volatilization half-life of a toxicant
 varies according to the environmental conditions.  Under controlled laboratory
                                           -72-

-------
                                      TABLE  11-21
            VOLATILIZATION RATES OF SEVERAL PRIORITY POLLUTANTS IN 12 RIVERS3
Pollutant
Benzene
Chloroform
Methyl ene Chloride
Toluene
Study results showed:
Henry's Constant
(atm-m'/mole)
5.5 x 10'1
2.9 x 10' '
2.7 x 10~J
6.7 x 10-J
k - 0.655 k'
Molecular Weight
M9
78
85
92

           Range of values for 12 rivers:   1.5  to  24 on/hr
           Screening method predicts:  k  » 0.7  k'  to 0.8 k
                ~ •   -                   Y         o
          aRathbun, R.E. and  D.Y.  Tai.   1981.  Techniques  for  Determining
           the Volatilization Coefficients of Priority  Pollutants  in Streams,
           Water Research.  Volume  15,  pp.  243-250.
conditions, where the depth of water 1s extremely  small,  t. ,-  can be extremely
small.  If the water depth Increases by 100 fold,  for example,  so does t^.g.
     The volatilization half-life 1s affected by  suspended  sol Ids 1n the system.
When suspended sol Ids are present.  Equation 11-52  should  be modified to:
                                             z          4                       MT c
                                         r - (I+SJCJ                       d1'5
                                         Ky           r
where
        S   •  suspended solids concentration
        K   •  partition coefficient.
The partition coefficient 1s the ratio of the sorbed  pollutant  concentration to the
dissolved phase concentration.  A method to predict K  was  discussed earlier 1n
Section 2.3.2.  Since the toxicant which sorbs  to  the sediments  Is not directly
available for volatilization, the total  flux of volatilizing particles decreases.
The following example Illustrates now  sorptlon  can Influence the half-life.
                                         -73-

-------
                    TABLE  11-22
PROCEDURE FOR  PREDICTING VOLATILIZATION RATE
1.   limit:  Htwy-i it, Comunt (Twit II-H)
2.   rrocM^rt;  Utt T«»lo Il-l»
J.   »MiiU:  ^ («/*•)•	
    To eoiw«rt U wltt *f Mr Mr
        *t (Mr My) • k, (oW»r) • $g • 	
           Mttft
                  II:
1.   I "But: Htwy'i L*i CoMtdt (^. (W « «J/««1«) •
I.
          (•Mftttan rit« (», o^V, or
          »«ttr U*mr«t«rt (T, °t) •
          •«ttr Mitli (1. aittrtl •
                              (It* i
                           t.i •
k.   MM:  k, (€»/<«•) . 700 (Jj)  »
           (Mr H,, • TOO     «
                                                      (t)
                                                      (1*1
                                    V
                       ^     x—v
                    (S)  '.-
               Mf):
                                            -«  1- "I   ('*i
                           -74-

-------
 ------------------- EXAMPLE  II-5  -----   -        - j

        The following data for hexachlorobenzene  were obtained from Table II-8:
!          Solubility  »  20  *«g/l                                                     !
j          Vapor pressure  •  10"5 Torr at 20°C                                        \
I          Kw  »106.                                                                I
|  Under the conditions reported In the work  of Mack ay and Lelnonen (1975):            |
j          L   -  1  m
                  8 cm/hr • 8 x 10   m/hr.
   Hence:
i                 0.693 x 1   n ,                                                      j
!            Vex io-> ' 8'7 hours                                                !
I                                                                                      I
I   Note that the half-life Is small  even though  the  vapor  pressure  Is only 10"         |
|   Torr.  The results Indicate that  the vapor pressure  1s, by  Itself, not necessarily  j
j   a good Indicator of the Importance of volatilization.                               j
        Now, consider the following  conditions which might be  encountered 1n a
   river:
'           k  (reaeratlon rate)  •  0.5/day                                            |
            *                                                                         -
           Suspended sediment concentration   •   550  ppm                               I
           K   •  5 x 104                                                             I
j           Depth  -1m.                                                             |
,                                                                                      i
I   The expression  of  volatilization  half-life modified to account for the presence of  j
I   the suspended solids  1s:                                                            I
                                                                                      i
•   From Equation  11-51,  the  liquid-phase transfer rate for hexachlorobenzene Is:         '


!               /32V                                                                 !
i           ki  "   75T    x  0.5 x  1  »  0.29 m/day » 0.01 m/hr • 1 cm/hr                   i
I            I   \ &O3 /                                                                  I
,               \    /                                                                  i
I                                                                                       I
I                                                                                       *
J   Henry's Law constant can be estimated based on Equation 11-32.   Using the data       !
I   presented earlier:                                                                  I
                       28S   1.9 x 10"" atm-mVmole
            H    760  x  .02

           or
           K'H «  7.8  x  10"',  dlmensionless
                                         -75-

-------
I   Using a default value of 3,000 cm/hr for k ,  the volatilization  rate 1s:
I           ky  = 1  cm/hr
i
I   The half-life becomes:

                                      """
   A comparison of half-lives shows that:
           t  •  8.7 hours under laboratory  conditions
           t  •  75 days under Instream conditions.
   This example Illustrates that half-lives  are not  always extrapolatable from
   one type of system to another due to the  combined difference 1n sorpflon  effects
   and volatilization rates.
                             •- END OF EXAMPLE 11-5 -•
2.4.2.5  Flux of Volatilizing °o11utants
     The preceding sections have provided techniques for predicting  volatilization
rates of pollutants.  Obviously, If the volatilization rate of one pollutant  exceeds
that of a second pollutant, then the first pollutant 1s more volatile than  the
second.  However, this criterion alone does not determine whether volatilization  Is
Important 1n a specific situation.  The volatilization flux 1s the rate  at  which  mass
1s transferred to the gaseous phase from the liquid phase and 1s given by the follow-
ing expression:

                         Flux - kv c - —                                JI-54)


                              • kyC, when P • 0                          (11-55)

where
        C  •  concentration of pollutant 1n water as solute
        P  *  partial  pressure of pollutant 1n atmosphere.
Hence both the volatilization rate and the dissolved phase concentration have to  be
considered jointly to predict the flux being volatilized,  "able 11-23 Illustrates
                                          -76-

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                                       TABLE  11-23
    RELATIVE VOLATILIZATION MASS FLUXES OF SEVERAL CHEMICALS  IN SATURATED  SOLUTIONS
Henry's Law
Constant
Chemical (atm-m3/mo1e)
Carbon Tetrachloride
ODT
Oieldrin
Phenanthrene
2.3 x
3.9 x
2.0 x
1.5 x
ID'2
io-5
io-4
io-3
Volatilization
Rate Constant Solubility
(cm/hr) (ppm) K^ Flux Ratio
20.
3.9
0.02
9.6
785 400 1
.002-. 085 10'-106 5xlO'-2xl06
0.2 - 4 x IO6
1.0 29,000 2 x IO3
aThis  Is  the  ratio of  volatilization  flux  of a  saturated  solution  of carbon
  tetrachloride  to the  volatilization  of the specified chemical.
these principals for several  chemicals.  The volatilization rates  for  these  pollutants
range from a high of 20 cm/hr for carbon tetrachloride to a low  of 0.02 cm/hr  for
dleldrln.  Anthracene has a volatilization rate constant  of 18 cm/hr,  90 percent as
high as the volatile carbon tetrachloride.  However, the  solubility of anthracene  In
water Is much lower (0.06 ppm versus 785 ppm).  Hence If  each  of these two chemicals
were to volatilize from saturated solutions, the flux of  carbon  tetrachloride  would
be 15,000 times as great.  The same type of comparison can be  made for DOT and carbon
tetrachloride.  The volatilization rate constant for DOT  1s relatively high  (about 20
percent that of carbon tetrachloride), but the solubility 1s so  low that the ratio of
volatilization flux would be about 100,000:1.
     These comparisons have not considered the relative differences In sorption
characteristics of the pollutants.  Since only the solute volatilizes, the volatiliza-
tion flux of a pollutant which 1s mostly sorted to suspended material  1s lower than
1n the absence of suspended material, all other factors remaining  the  same.  Tables
II-5 through 11-9 show the octanol-water partition coefficient,  which  provides a
measure of relative Importance of sorption for the four pollutants.  Because both  DDT
and anthracene have higher octanol-water partition coefficients  than does carbon
tetrachloride, the ratio of   Utilization of mass fluxes Is likely to be even
greater than calculated above for natural systems containing suspended material.

 2.5   TRANSFORMATION  PROCESSES

 2.5.1   Blodegradatlon
                                          -77-

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2.5.1.1  Introduction
     Microorganisms are ubiquitous in the aquatic environment.  Microbes are also
very active chemically due to their ability to supply energy for reactions through
normal metabolic processes and to catalyze reactions through enzymatic activity.
Chemical reactions which proceed very slowly or not at all in the absence of biota
occur at rates of up to eleven orders of magnitude faster In the presence of biological
enzymes.  Some of the reactions catalyzed by microorganisms transform or degrade
organic pollutants.  Frequently, microbial degradation, or blodegradation. is the
most important, if not the only process which can decompose an organic pollutant in
the aquatic environment.
     Although microbial communities catalyze countless reactions, many of them fall
into a few classes of Important reactions.  Oxidative reactions make up one very
important class of biochemical reactions.  The hydroxylation of aromatic compounds,
such as benzene, 1s an example of an oxidative reaction which generates polar com-
pounds from non-polar ones:
                                                            OH
                                        Enzyme
                       Benzene
Catechol
An extremely Important oxidative reaction unique to microbial organisms is aromatic
ring fission:
                                                                     CHO
Microbes  also  catalyze  reductive  reactions.   A notorious  example  is  the
dehydrochlorination  of  DOT to  produce  DOE:
          ci
                                       Eniv
                    DOT
                                          -78-

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 2.5.1.2.1  Metabolism of Growth Substances
      Heterotrophlc bacteria degrade certain organic compounds to provide the energy
 and carbon required  for their growth.  Many toxic substances function as growth
 substrates for bacteria In a manner similar to naturally occurring organic compounds.
 These growth substrates are identifiable by their ability to serve as the sole carbon
 source for a bacterial culture.  The metabolic transformation of these growth sub-
 strates generally results in relatively complete degradation or mineralization, thus
 detoxifying toxic growth substrates.  The detoxifying effect and relatively rapid
 rates of growth metabolism Imply that potential growth substrates pose a lesser
 threat to the environment than compounds which cannot be used in this way (Tiedje,
 1980).
     Before the utilization of a compound can begin, the microbial community must
 adapt Itself to the  chemical.  Investigations of biodegradation of a compound to
which the biota have not been recently exposed, both 1n the field (Spain e£ aK 1980)
 and 1n the laboratory (Shamat and Haier, 1980) have shown the existence of a lag time
 (lag phase) of 2 to  50 days before the microbial community acclimates.  Since the
 degradation of a growth substrate Is relatively rapid once a microbial population has
 adapted to it, Tiedje (1980) has suggested that the primary concern in assessing
 biodegradation of such substances should be the conditions and time period required
 for adaptation or acclimation.
     The lag time depends on several biological and environmental  constraints.  The
primary constraint is the development of a sufficiently large bacterial population
which is capable of  utilizing the pollutant as a growth substrate.  Frequently,
 specific organisms with specific enzymes are required to metabolize a pollutant.  The
processes of species selection and enzyme induction by which a microbial  community
adapts itself to a pollutant require time.  The adaptation time 1s Influenced both by
prior exposure of the community to a pollutant and the initial  numbers of suitable
species. Spain e_t_ £k (1980) have demonstrated that prior exposure to a compound
reduces or eliminates the adaptation period.  Thus, lag times 1n pristine environ-
ments should be much longer than in locations which have been chronically exposed to
a compound.  In addition. Ward and Brock (1976) have shown that lag time preceding
the onset of petroleum degradation depends on the initial  size of the bacterial
population.  Water with larger microbial  communities should require relatively
shorter times to develop a viable population of degraders.   High microbial  biomass
levels are associated with higher BOD, concentrations.
     The presence of more easily degraded carbon sources may delay the adapta-
tion of a microbial  community to the metabolism of a pollutant.  Ward and Brock
 (1976) found that microorganisms in lake water metabolized added glucose completely
before degrading hydrocarbons.   This diauxic pattern may result in longer lag times.
     A final  factor which Influences lag time Is rhe concentration of the pollutant
                                         -81-

-------
In the water.  There may be concentration thresholds below which adaptation does not
take place.  (For example, no adaptation for metabolism of 4-n1trophenal  occurred at
concentrations below about 40 xg/1 (Spain et^ al_, 1981).  Too high a pollutant concen-
tration, on the other hand, may be toxic to the microbes (Tabak et^ aU, 1981).  The
user should be aware of these possibilities when extremely low or high concentrations
are Involved.
     Once the microblal community has adapted to the organic pollutant, 1t 1s of
Interest to know the rate at which blodegradatlon occurs.  Kinetic expressions for
compounds used as a growth substrate can be relatively complicated since both the
substrate and bacterial concentrations change with time.  The Honod equation has been
used to describe the degradation rate of a compound which serves as a sole carbon
source:
                       d£
                       dt
dJL
dt
        "max
          Y
B
(11-56)
where
        C     •  pollutant concentration
        B     •  bacterial concentration
        f     •  blomass produced per unit C consumed
        •'max  *  maximum specific growth rate
        Ks    •  half-saturation constant.
     Frequently, the Honod equation 1s reduced to a second-order blodegradatlon
expression by assuming C «K . 1n which case:
-    • k
  dt    82
                                          B
                                             (H-57)
where
                 second-order  blodegradatlon  rate  constant
                 "max
      Although Monod  kinetics  accurately  describe  some  laboratory  results, they  are
 Inapplicable 1n  the  environment  due  to the  presence  of other  carbon  sources.  As a
 simple  alternative,  first  order  kinetics are  frequently  applied:
                                                                              (11-58)
where
             »   first-order blodegradatlon  rate constant.
                                          -82-

-------
Enzymes can catalyze otherwise slow hydrolytic reactions as well:

                        s                                   s
                ;CHo)_P_s-cHcooc2Hs — fcsuas - fc  (cHo)— P— S-
                   32__-2s —    - fc    3z
                              CHCOOC.,HS

                    N*l«th
-------
         MICROBIAL TRANSFORMATIONS OF TOXIC CHEMICALS
                 (Potential  Toxin)
                   O(CH2)3COOH
(Less "oxic Substance)
         OH
                  Cl
                  OCH2CH2OSO3H
                         f-CI
                  Cl
            (Potential  *oxin)
                                    * H0 + Cl'
         Source: Alexander (1980)
      FIGURE  11-10  MICROBIAL TRANSFORMATIONS OF  PHENOXY HERBICIDES
2.5.1.2  Rates of B1odegradat1on 1n the Environment
     The rate at which a compound blodegrades in the aquatic environment depends  on
Its role In mlcroblal metabolism.  Some organic pollutants serve as  food sources
which provide energy and carbon for growth and cell maintenance when metaboi.zed  by  a
microorganism.  In other cases, microorganisms transform the pollutant,  but  are
unable to derive energy for growth from the reaction.   These two metabolic patterns,
growth metabolism and cometabollsm, exhibit distinct characteristics and rates of
degradation. Because of the Important differences between these two  types of blodegra-
datlon, they are treated separately 1n the following discussion.
                                         -80-

-------
This first-order expression 1s analogous to the equation commonly used for the
decay of 300 (see Chapter 4).  Larson (1981) has shown that first-order kinetics
which include a lag phase (lag time) represent the degradation of growth substrates
reasonably well at initial bacterial concentration of 10  cells/ml  or less,  a
condition which is usually met 1n tht environment.

2.5.1.2.2  Cometabolism
     Microorganisms also degrade compounds which they c?.-iot use as a nutrient
or growth substrate through cometabolism.  Cometabolism is thought  to occur when
enzymes of low specificity alter a compound to form products which  the other enzymes
in the organism cannot utilize.  The metabolites formed in the process are structurally
similar to their parent molecules and frequently retain their toxlcity.  In  some
cases, the product of cometabolism can be used as nutrients by other organisms,  but
often these intermediate products accumulate (Alexander, 1980).
     The kinetics of microbial cometabolism differ significantly from that of
growth metabolism.  Often no lag occurs before cometabolism begins.  The degradation
rates, though, are generally slower than the fully adapted rates of growth metabolism
(Tledje,  1980}.  Since cometabolism does not provide the microbes with any energy,  it
has  no effect  on  the  population  size.   The  rate  of  cometabolism, however, is  directly
proportional  to the  size  of  the  microbial population.   Paris  et_ aj_.  (1981) showed
that  a second-order  rate  law  described  microbially  catalyzed  hydrolytlc  reactions:


                               -dT-kB2-B-C                              (I1'59)
Since the  bacterial  population,  B,  Is independent of the  rate of cometabolism,
It  is possible to reduce  Equation 11-59 to  a  first-order  law by making the  following
substitution:

                                S • "H •  •                                  (U-60)
      In  order to  use literature values  of  the second-order blodegradation rate
constant in  Equation 11-60, It Is necessary to make an estimate of the size  of  the
bacterial  population.  Since different  techniques of bacterial  enumeration  can  yield
results  which vary over several  orders  of magnitude, it 1s Important to use  estimates
of  B based on the same method used to calculate k.^.  Table 11-24  lists bacterial
densities  which are typical  of lakes and rivers.  Obviously, large uncertainties  1n
environmental  rates of cometabolism exist  due to the wide range of possible  bacterial
densities.  Generally, the user should make conservative  assumptions unless  other
data, e.g.,  a high BOD, Indicate larger bacterial densities.
                                          -83-

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                                     TABLE II-24

                SIZE OF TYPICAL BACTERIAL POPULATIONS IN NATURAL WATERS
Water Body Type
01 i go trophic Lake
Mesotrophic Lake
Eu trophic Lake
EutropMc Reservoir
Dys trophic Lake

Lake Surficial Sediments
40 Surface Waters
Stream Sediments
Rur River (winter)
Bacterial Numbers (cells/ml)
50- 300
450- 1,400
2000-12.000
1000-58,000
400- 2,300
Q in
8x10* - 5xl0iu cells/g dry wt
500-lxlO6
107-108 cells/g
3xl04
Ref.
a
a
a
a
a

a
b
c
d
     aWetzel  (1975).  Enumeration techniques unclear
      Paris et il.  (1981).  Bacterial enumeration using plate counts.
     °Herbes  I Schwa 11  (1978).  Bacterial enumeration using plate counts.
      Larson  et £l_.  (1981).  Bacterial enumeration using plate counts.
2.5.1.2.3  Summary
     Table 11-25 suMMrlzes some of the major differences between growth metabolism
and cometabol1sm.  Although the exceptions to the generalizations about each process
are numerous and some compounds can undergo both processes, the distinction between
the metabolic processes can serve a useful function 1n a screening method.  The
generalizations about each process suggest the following approaches when the user has
some knowledge of a compound's metabolic pathway:
        Cometabol1sm
             a)  Find a second-order rate constant and estimate b1amass density.
                 Apply Equations 11-59, 60.
             b)  When a) 1s not possible, assume cometabol1sm 1s negligible. I.e.,
                 k- 0.
                                         -84-

-------
                                                               TABLE  11-25

                                  SUMMARY OF THE  CHARACTERISTICS OF  THE  TWO GENERAL  TYPES OF
                              BIODEGRADATION:  METABOLISM AND COMETABOLISH (After  Tiedje.  1980)
         Topics
                                          Metabolism lor Growth
                                                                Cometabo li'-m'
Distinguishing characteristics
Degradation rates

Behavior at low pollutant
  concentrations

Acclination
Relation of degradation  kinetics
  to total  biomass.  e.g.  decay
  rate - k_- •  B  • C

Extrapolation
If feet of added carbon
Organism will  qrow en  i.ibtlliut'  as  solo f.
  source.  Generally ultimate  degradation.

High rates.

Possible anomalous behavior  due  to  threshold
  for eiuyme induction.

Major effect-  lay m*y  be  quite variable or
  lengthy due  to low initial density of
  degraders. and perhaps  starvation stale
  of organises in natural  sample.

Likely not valid, use first-order kinetics.
                                      General: expect eventual degradation in nature.
                                        Quantitative: difficult to be precise because  of
                                        growth kinetics and acclimation effects,  but
                                        My not be  important problem, because of
                                        generally  fast rates.
Diauxic pattern — More easily metabolized
  substrates are used first.
Oru,*  <>n  subst.inre as sole C source.
  Accumulation of  intermediate  products  likely.

Generally slow rates.

No anomalous behavior,  rales  are  first order  in
  pollutant concentration.

Often no effect; rarely causes  induction, may
  increase tolerance to toxic chemical.
                                                                                           May be valid since activity of interest  is  often
                                                                                              proportional to general biomass.
Measure kinetic parameters accurately:  because
  of the generally slower rates,  extrapolations
  will be made over longer tines, and  thus measured
  parameters need to be accurate.  Also environ-
  mental influence factors, e.g.  temperature. pH,
  play a more Important role.

Generally effect is proportional  to microbial
  population unless specific carbon source happens
  to induce or inhibit activity of interest.
 •Alteration of a substrate, for purposes  other  than  growth, e.g. for detoxification.
                                                                 -85-

-------
        Growth Metabolism
             a)   Find a first- or second-order rate constant.
             b)   Estimate a range of lag times.  For chronically  exposed water
                 bodies, assume that no lag time (t, )  occurs.   For water bodies
                 not recently exposed (within 200 days), proceed  as follows:
                 1.  Estimate lag time using available Information.  If no Information
                     1s available use a range of 2-20 days.
                 2.  Assume adaptation occurs as follows:
                     Rivers     - At travel times < t. ,  kn • 0
                                                     L   0
                                - At travel times >. t,,  ko >* 0

                     Lakes      - For well mixed lakes,  first determine C at time »
                                  t, , Ct  due to all processes except
                                  blodegradatlon.  Then using Ct   as C0 solve
                                  for Ct with a modified time, t^, (t^ • t -
                                  t,}.  (Use equations 1n Section 5.6.1)
                                - For stratified lake use only the volume through
                                  which the Inflow passes (e.g.,  the hypo11mn1on
                                  volume) 1n calculating the hydraulic residence time
                                  (TM).  Then proceed as above.
                     Estuaries  - Consider all processes except blodegradatlon
                                  through that downstream segment for which \, as
                                  measured from the Injection point, becomes greater
                                  than tL.  Thereafter Include blodegradatlon.
When no data on which metabolic pathway a compound follows are available, the
user should apply any available kinetic Information and allow for the possibility of
a lag phase prior to the onset of degradation.

2.5.1.3  Chemical Properties Influencing Blodegradatlon
     The chemical properties of a compound determine whether microbes can potentially
utilize It as a growth substrate or not.  Compounds which serve as bacterial  growth
substrates usually decay more rapidly than those which microbes cometabollze.  Thus,
significant differences 1n the aquatic fate of pollutants can arise depending on
which degradation process takes place.
     Unfortunately, 1t 1s not possible at this time to predict whether a toxic
compound 1s a potential source of energy and carbon solely on the basis of Us
chemical structure.  Rather, the b1od«gradab1l1ty of a compound 1s usually Investi-
gated 1n laboratory tests (Gilbert and Lee, 1980).  Compounds which are growth
substrates should be able to serve as sole carbon sources for a mlcroblal community.
Compounds which cometabollze should degrade only In the presence of another carbon
                                         -86-

-------
source.  A systematic study of the metabolic pathways of the priority pollutants Is
desperately needed.
     Table 11-26 contains the results of a preliminary degradation test on the
organic priority pollutants (Tabak et_ a_l_., 1981).  Because the experimental  conditions
were so favorable for blodegradatlon, the tests serve as a good Indicator of a
compound's potential blodegradabHlty.  Since the pollutants were not the sole carbon
sources, no conclusions can be reached about their metabolic pathways.  Some Informa-
tion on the rates of adaptation and decay, through, can be extracted from the results.
     The adaptation summary results may be used as follows:

         •    Rapid Adaptation (D) - Use a range of adaptation times from zero days
              upward depending upon conditions described above
         •    Gradual  Adaptation (A) - Use a range of adaptation times from 7 days to
              more than 20 depending upon the conditions described above.
      The rate summary results represent estimates of the blodegradatlon rate constants
 assuming the compounds decay according to first-order kinetics.  General values
 presented at the bottom of the table are gross estimates and should only be used  1f
 no better data 1s available.  The rate constants should represent an upper limit  for
 blodegradatlon rates  by adapted populations observed 1n the environment.
      Table 11-27 contains literature values of blodegradatlon rate constants.
 Where possible, the likely metabolic pattern has been Indicated.  Some of these
 constants were measured under environmentally relevant conditions.  In general,
 rate constants should be compared with those 1n Table 11-27 before use.

 2.5.1.4  Environmental  Influences on Blodegradatlon Rates
      Environmental  conditions strongly Influence the metabolic activity of a nrfcroblal
 population.   The environment affects the types of metabolic reactions microbes are
 able to carry out,  the availability of nutrients for these  reactions, and the rates
 at which these reactions occur.   The environmental  variables which are responsible
 for these effects are discussed 1n the following sections.

 2.5.1.4.1  Temperature
      In general, a molecule must have an energy greater than a threshold or activation
 level  1n order for 1t to react  chemically.   Since Increasing the temperature Increases
 the number of molecules which have this minimum energy, both blotlc and abiotic
 reactions generally proceed more rapidly at higher temperatures.   However,  because
 enzymes catalyze most biochemical  reactions and mlcroblal  populations can adapt to
 changes 1n ambient temperatures, the temperature dependence of nrtcroblally  mediated
 reactions 1s complicated.
                                          -87-

-------
                 TABLE II-26

POTENTIAL 8IODEGRADABILITY OF ORGANIC POLLUTANTS
            IN AN AEROBIC ENVIRONMENT
            (After Tabak  et al.,  1981)
T.it CMMM4

A*tK«ttM

Inarr

TII« COTMM

*tixvr
^^—•*i*
Ult
!««•«« rr
A^H^X«&
H»tUI«tt
Al«r<.
ottiin*
CM.r«M*
DOT ».»'
(W ».»'

000 •.»'

lM*i»lf*«-ll(M
tit**t»l 'M-MU
CMMvlfM t»MlU

H...OU
Kt-1221
KI-12S
KI-1242

ChlorMtKM**
1 ,l-Otckl*rw«MM
1.2-Otckl*r««U4M
1.1.1-Trlelil.f^tM..
1.1.2-THcM.rMtMM
1.1.2 .2-Ttlr«cftUrwtk*M
WuckUrMtMM

Nttiijrl*** cklsrKt

lr«»<»l*rmtMM
C«rM« Utr.t*l.n«i
CM>rtftr<

OU«l*r**rWM»tft«M
Irwcftn
C>Hr««>riaat«IM
f n c» Urtfl wrMttMM

•,,-C.c.Un-a,.) HMT
2-CkUrMt*yl «1«yl «t*»r
4^»l»f»«1*»r' *tk*v
I
»
I
N
•

II

*
II
«

*
0
0
II


»
1
1
c
1
0

0

0
0
A

i.
k
1
N

1
0
I
0
0
0
0
0

0

0
a
0
tCI'l MH
0
2
2
0
H4lO«M(t« 1

1
t
1
1
0
2

2

2
2
1

I
1
0
0
"I'fl
I
I
0
CMH*
-t.l.cM.r
Mt»t«cM.r tpo.t*.
N.uchlonxyclok.1**.
N*i*CHl or«cjr< 1 ohiiMt
l-IMC-Mtl
HtucM or»cytl »Mi*M
«-lMC-«*ltl
HtiKkUrvtyC 1 oMtu*t
iiJUiifT" °'"»r»tthrlt««-c1l
1.2-OtcKlDrotthylt«<-triM
THcM.n>,th,lw.
Tttr«ehl*nwt»rl*M
CM»r»»r«M««l
1.2-0«cM*r«RriMm
CkUr^r<*rltMi
1 ,i-0*tl*loro^f^»rlnn

Htuc* 1 *r*. 1 , }-»vt««l«*«
Ck1er«(t •




•MIM tttan
«.*rwM«»Mi>r1 MMr
l«|.(l^kl*fMtk.iy) MtMM
•1|.<2-ckUr«lM*f»»r1) itk*»
*
N
II
H
K

II

II
D


,
N
N
0


A
1
1
A
A

*

A

0

0





II
•
D
0
0
0
0
a

a

0
2


0
0
0
2


2
1
1
1
1

1

1

J

2





0
0
2
                     -88-

-------
TABLE 11-26 (Continued)
T«t Compound

Nni»««
ChloroMflun*
IJ-O.cMorootnitn.
1 . J-Olc" 1 orvbdJtnt
1,4-OUhlorobo'iltno
l.J .4-TrlchlorOMnjmt

H.ml
2-CMoro pAtnol
2,4-Dtcnioro P^tnol
2 ,4 ,6-Tnchloro pftenol
HM.chloro ph»ol
2.4 OMtftyltMMl
AdllCttlM Ittt

*MC>«MC A^.
0 2
0 2
T |
T 1
: 1
T 1
nxnol U Co*pou
D 2
0 2
0 2
0 2
A 1
9 2
Tilt Coaoound S^» l«tt

0
2
2
2
1
1

2
2
2
2
0

Pfttlulllt Clttrt
Oinvtnyl pnthlUtt
OUthyl pficn«l<((
01-fl-butyl pnt"*l*lf

Mgthilt"*
/*tn.ptr,...r
Actntpntnyltnt
Afltnr«c»"«
flM.mi.r**

• ItrOM—ti
»ropyl«ni«t

0 2
D 2
0 2
^olycrcl le Aroattu "i
0 2
0 2
0 2
A 1
0 2
Nltrote Antnti «nd H1iciH<

• 0

I1l-(2**thyl htiyl] pAtnllitt A
Dt-n.octyl pntMlttd A
lutyl ftMlyl pntntlitt D
.drocJrBO"!
n,or,~. A
n>«)rmh«« A-
l.2-l*«lMtnr>ctn« H
Pyrtim D«
CHrystno A*
»•«,> Co^ountt
Su»,..tut<^ M.<^
"pNrooo
1 2-01pn«nylhvdrii1ni T
1
1
2

I
2
0
2
1



1
H-ltltroiOdlplOTylMtOf D 2

Ittvltl Of '•••• U «1
conditions, *nt tttt *
dur4tio« • 28 3«y».
Kfy to r*ft S^«iry
II Sot l.)n'fKjntl
D Sia.ni f i c«nt dtor
0* S«*t it 0 *ic»pt
A Slant'ic^nt dtof
A* S«"t H A «ic»pt
1 Slow e«9r4tf«tion
C V*^y llow t}»<)r«d
I Si9»i'iC4i( 3»qr
1*1 to l«tf Su«Mry
(fry crudt «»tl"4tn
0 do ii»>M ftccnt
1 . OS d< y * < h .
2 k, > 5 ««y''.

(1111) ntlnf lunch vr«s d 2t djyt
.44 1 ion .ith ^r.dMl tdJOtttlon fpl1o«*d »r «««<*pti

of flrit-ordtr blodtf rcdit lo» rttt contt<«tl ««y M
dtfr«d«Cioi< rttt
< .i d«y . u>* .01 d«y*
utt .5 d«y


on (toilclty).

•••> froa tht I*for«
-------
                      TABLE 11-27
BIODEGRADATION RATE CONSTANTS UNDER AEROBIC CONDITIONS
Mtt ConitMt felt Contunt
CtWeu~I (B| ctH"' 4*»''l (l/4*y)
2.4-0 lutoirttnyl mtr 1.2>10"S3 l.JilO"2"
*l«tmor> I.U10"*1 1.1.10'"1
CMIarprootiMi ».2>!0"IO<3 *.2ilO"7<1
Furt4«n J.4.10"3 2.4ilO'5U
StF.S'fl* 2.4ilO"8 2.4S10"5*4
>oljrcMorti»«lt4 1 1 phtnj 1 1
iroclor 1221 - .«'*
Aroelor ;01* - .2'
iroclor 12*2 - .!5IZ
»rocl0r !254 - .l'
4-Chloropmoyl pncnyl tthtr • Oil- OU
•owe cue *rxiMttc»
Nttrot>*nltn« • .7<2
2-Ch'oroto.^, 4.5.10-80 i.talO'*
»h»no)'c ConpOu'>4>
«^x>] - 4.'2
».(2
2-CMor»fl*>ttiol - 1.'*
.3
2.4-DlchlaropMfMl - . S(
.l(*
(2
1."
2.4.0lWthylpMHOl - 1."
2.4-DtnltrbpftfflOl - .2
2.4,4-f-'»itro9»««ol • 0
FMh«l«U Ctttrt
DlMttiyl l.hlO"* .12"
01-tthyl 7.7ilO"* 7.7IIO*4*1
0<-£-outyl 7. 0«10*7 7.0x10
OI-«-octyl 7.4UO"9 7.4I10"6*1
01-(2-»th,lH,,,l l.OklO"10 l.telO'7
I.taW^4
lntjrl Mflljrl - >.M
H«ir.|.ift
S3
t.JilO2
l.lilfl6
3 « 104
3 s 1C4

.1
3.S
45
7.
43-(3
.2
1.
1.U103
.2
.1
.7
2.3
1.4
«
7
.7
.7
3.S

,,
t.fellP
l.OklO3
t.lilO4
i.klO*
a
<2
T
Nf«n«t» MM i» •
TMMfttur* troirth
(•C) Sufttr.t.? Uptriaxiul Con*ltioni
20 ' Mturtl jr'«Ct atttr UnOltt
20 '•« Mturll turfKt «*t*r »*»0lt«
20 ^ Mtural tuvf«ct ««ttr sonelti
> t i
•

' * ACCltMtt* Ktlv4tM lluOVt
7 ' ACCltMtt* •Ctl«4t« t>u«1*
teeh^tM sctivstrt Hudi*
7 7 AccliMtM KttoitM iluOft
7 ' II. «r m»ttr; Log • 5-13 4«yl
7 7 tctUtttd tlu«|t
20 >tl M«ptM «ti«it« tlu4;t. COO 4«
7 7 Mturil iurfKt utter twwlt
20 >tt MtotM «cti»«t*o tlu«t«. COO 9«<
' 7 PolluUO MMT Mttr
20 '•» M*»tM «ctt«it*4 ilud««
1 'Sod umntto*
20 >tt MwtM icttottM ily««t. COO 4K
2$ 7 Mturtl ltt M**tM; Nutritot Iretti
20 Tt* MMtM 4ct<.itM llu«t«
20 Ttt MwtM KtUltM tlv«f*
20 M ActlMtM ll«*tt
? 7 »
T T 7
77 »
? 7 7
T 7 ?
T T I1*tr Mt*r
T 7 »l¥«r Mt«r
•tf
t
t
i
t
»

c
c
c
c
c
c
:»j 4
t
:ij 4
c
4
C
:•> 4
c
f
f
4
4
4
1
,
f
t
f
C
C
                         -90-

-------
                                             TABLE  11-27  (Continued)
*8? 't
»att C-wstant *antnrtnf J.I«IO"6 3. blO'3"
r0 CoxooviiX
I Rfff V^VA( f1 i/»ww
n«) 1 <• L t f f Tfwcf* CM^C G^Qot^
144/1) CO Sufrtir«tf * lipv^tinfntit CcntfUons

4.0 1? TCI Cof>t**'njt*d *tre*" ted^**f«tt
1.7.103 12 > rr.tl.n. ,.r,»- ,,di-^ll
;.8.10: 12 ttt Cant«ffin«tra >tr»«. ttO'-<«<*otl
M»i02 » 7 T


V

h
h
h
fl
c
h
h
li
k
c
IJ    rirtt-O'df rttf  conttjnt CC'-Out« ull"9 Cgu*tl»n 11-40 
-------
     It 1s common practice to represent the temperature dependence of blodegradatlon
using the following empirical formula:

                               k (T)  • k (T )  •  3 (T~V                    (11-61)
                                B       B  o     B
where
        icB{T)   •  specific blodegradatlon rate constant at temperature - T
        kg(T )  •  specific blodegradatlon rate constant at temperature - T
        T       •  ambient temperature, °C
        T       «  reference temperature, °C
        e»      •  temperature coefficient for blodegradatlon.
     The results of Larson et^ aj_.' (1981/'and Ward and Brock (1976) show that the
rates of n1tr1lotr1acetate and hydrocarbon blodegradatlon Increased approximately
two-fold over a ten degree temperature  range (9g » 1.072).  Either this value or
the standard value of 1.047  for BOD decay 1s adequate for screening purposes.

2.5.1.4.2  Nutrient Limitation
     Microbes require nutrient such as  nitrogen and phosphorus 1n order to metabolize
an organic substrates.  Several researchers have suggested that Inorganic nutrient
limitation 1s a significant  factor influencing blodegradatlon rates in the aquatic
environment  (Ward and Brock, 1976;  Roubel and Atlas, 1978;  Herbes and Schwa 11,
1978).  Ward and Brock (1976) found a high correlation between hydrocarbon degradation
rates and phosphorous concentrations  in  natural waters.  The data fit a saturation
relationship of the Michael 1s-Menten  type:

                                                •°277 ' c«                   in  ti\
                          k  (C  ) « k  (C *)  • 	2_                 (11-62)
                           B  P     B   p     1 •»•  .0277  •  C
where
        *0(C  )   •  specific blodegradatlon rate constant at dissolved
         D   p
                    inorganic phosphorus concentration, C
        C        •  dissolved Inorganic phosphorus concentration, *g/1
        ko(c«*)  "  non-nutrient limited blodegradatlon rate constant.
         D   p
     This relationship should serve as  a good Indicator of possible phosphorus
limitation of b1odegradat1c« in the environment.  Generally surface waters downstream
of domestic  sewage treatment plants are not limited in either nitrogen or phosphorus.
Equation 11-62  should be  applied only when other nutrients such as carbon and nitrogen
are not limiting.
                                         -92-

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2.5.1.4.3   Sorption of  Substrates
      Many organic  pollutants adsorb  strongly on  sediments,  {See Section 2.3.2.
The difference  in  the physical and chemical environments between sorbed and dissolved
pollutants  is  likely to influence their  availability to microbial organisms.  Baughman
et_ £j_.  (1980) showed that the dissolved  fraction  of tne compounds studied was avail-
able  to biota  for  degradation whlls  the  sorbed fraction was  not.  In such cases, trse
rate  of disappearance of the pollutant  is:
                dCT
                dT =   kB  •  Cw   "  %  •  kB  ' CT                               (11-63)

where
        CM  *   the pollutant concentration in the aqueous phase
         aw •   the decimal fraction of the total  analytical pollutant concentra-
                tion wnich 1s in the aqueous phase (a   «  1 - fraction sorbed).
      It is well known,  however, that bacteria grow very readily on surfaces and that
increasing available surface area in the form of clays and sediments can increase
rates of microbial metabolism.   If specific information regarding the effects of
sorption on the rates of biodegradatlon  are not available for a compound, it is  best
to assume that  sorption does not change  this rate.

2.5.1.4.4  Solubility
     Wodzinski  and Bertalini (1972) have shown that in the dissolved state, napnthalene
and biphenyl were degradable while in the pure crystalline state they were not.
Thus, sparingly soluble compounds could degrade slowly for this reason alone.  The
extent to which this phenomenon applies to other biodegradatlon reactions has not
been established.  The  user may assume that only dissolved chemicals are degraded.

2.5.1.4.5  £H
     The hydrogen ion concentration also Influences rates of biodegradatlon. Each
bacterial  species has a pH range for which it is best suited.  Thus, at different pH
values, different species may exist, or a given species may metabolize the pollutant
at a different  rate.  Hambrlck e£ al_. (1980) found that the mineralization rate of
naphthalene in  oxidizing sediments varied in the proportions 1:6:5 at pH 5. 6.5, and
8.  The same study found that the mineralization rates of octadccane varied in the
proportions 4:5:7 at the same three pH's.  Until  more general rules for predicting pH
effects are available,  the user should assume biodegradatlon rates are Independent of
pH in the pH range 5-9  and decrease outside this range.

2.5.1.4.6  Anoxlc Conditions
     As the concentration of dissolved oxygen in  natural  water is depleted, metabolic
pathways shift.  When the dissolved oxygen concentration drops to about 1 mg/1,  the
rate of biodegradatlon  becomes dependent on oxygen concentration In addition to
                                          -93-

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substrate concentration and the rate of degradation starts to decrease.   At  a  dis-
solved oxygen concentration of about 0.5 to 1.0 mg/1  nitrate begins  to substitute for
molecular oxygen as an oxldant.
     When oxygen 1s depleted, anaerobic metabolism prevails with Us generally
lower energy yields and growth rates.  Host organic substances are blodegraded
more slowly under anaerobic conditions.  Rate constants derived for  oxygenated
systems are no longer appropriate;  their use may overpredlct the amount of
degradation.
     Exceptions do exist to the rule of slower degradation under anoxlc conditions.
Reactions such as dehydrochlorlnations and reductive dechloMnations lead to much
higher degradation rates for many chlorinated hydrocarbons.  Example compounds
Include Undane, heptachlor, pentachlorophenol, and some one and two carbon
chlorinated alkanes.
  	EXAMPLE II-6	1
                                                                                       j
                         BiodegradablHty of Naphthalene                               j

        Evaluate the blodegradablHty of naphthalene discharged into  the Lepldoptera
   River by a point source just upstream from Northvilie's sewage treatment  plant.
   Assume the following water quality parameters at the upstream discharge:             j
           Temperature           « 10*C                                                I
           Suspended sediment    « 10 mg/1                                             I
           Inorganic phosphorus  •  5 Mg/1                                             j
           Dissolved oxygen      •  5 mg/1.                                             j
        First, check the potential blodegradabil1ty of naphthalene 1n Table  11-26.      j
   The table indicates that naphthalene degrades rapidly, k« •  .5 day  , and
   that bacteria adapt quickly to 1t.                                                  !
        Next, examine Table 11-27 for further Information on naphthalene's blodegrada-  {
   bllUy.  Naphthalene Is a potential growth substrate.  In addition, the data  1n      I
   this table concur with the rapid degradation rates suggested by Table 11-26.   In     |
   sediment, which had been previously exposed to naphthalene,  a blodegradation  rate    i
                        i                                                              '
   constant of 0.14 day   was measured.  As  one would expect for a growth sub-          j
                                                               j    i                  '
   strate, degradation rates are much lower, e.g., k. < 4 x 10   day  , in sites
   not previously exposed to naphthalene.
        Since naphthalene 1s a growth substrate, estimating the adaptation time
   1n the Lepldoptera River 1s a primary Issue.  Because the point source continuously
   discharges naphthalene Into the Lepldoptera River, it Is safe to assume that  the
   bacterial  populations have adapted.
        In a complete analysis, the user would check whether the oxygen 1s depleted
                                         -94-

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   from the river.   If so,  degradation  could  be neglected  until  dissolved  oxygen
   levels  exceed  1.0 mg/1  again.
        Sorption by suspended sediment could potentially reduce the rate at which
   naphthalene biodegrades.  Table II-9 gives a K   for naphthalene of 2,300.
   Using Equations  11-16 and 11-18 and assuming a suspended sediment organic carbon
   content of 2 percent, the partition coefficient is:
           Kp  -  (.02) (.63) (2,300)
               «  29
   At the suspended sediment levels in the Lepidoptera River 10 mg/1. Table 11-16
   shows that sorptlon will not significantly reduce water rolumn concentrations  of
   naphthalene.  Although phosphorus levels are low, assume carbon is the growth-      |
   limiting substrate.                                                                 |
        Finally, the degradation rate is adjusted to the river water temperature        j
   using Equation 11-61:                                                               '
           *B  -  0.14  • 1.072(1£M2)                                                  j
               »  0.12 day"1                                                           j

  	  END OF EXAMPLE 11-6  	,	•
2.5.2  Photolysis

2.5.2.1  Introduction
     The sun provides the aquatic environment with a large supply of energy. Substances
which absorb sunlight transform much of Its radiant energy Into thermal energy.  But,
molecules which absorb sunlight In the ultraviolet and visible portion of the spectrum
may gain sufficient energy to Initiate a chemical reaction.  Plants use very specific
photochemical reactions to provide energy for the synthesis of sugar from carbon
dioxide.  In other photochemical reactions, the absorption of light leads to the
decomposition of a molecule.  The latter type of reaction, known as photolysis,
strongly influences the fate of certain pollutants In the aquatic environment.
     F jtolysls Is truly a pollutant decay process since It Irreversibly alters the
'•-acting molecule.  However, the products of the photochemical decomposition of a
toxic compound may still be toxic.  For example, Irradiated 2,4-D esters form 2,4-D
add, a priority pollutant, 1n aerated waters {Zepp et_ aj_., 1975).  Upon Irradiation,
DDT reacts to form DDE, which persists in the environment longer thai? DDT (Tinsley,
1979).  Thus, even though the methods In this section assume that pollutants Irrevers-
ibly decay through photolysis, the planner should remember that the decomposition of
a pollutant does not Imply the detoxification of the environment.
     The rate at which a pollutant photolyzes depends on numerous chemical and
environmental factors.  The light absorption properties and reactivity of a compound,

                                          -95-

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the light transmission characteristics of natural  waters, and the Intensity of solar
radiation are some of the most important factors Influencing environmental  photolysis.
These factors will be covered by the following discussion.  Understanding these
factors facilitates the computation of rate constants and the identification of
pollutants likely to photolyze - the final  two topics of this section.

2.5.2.2  Factors Influencing Photolysis in the Aquatic Environment

2.5.2.2.1  Photochemical  Reactions
     All chemical reactions which occur at finite rates require the reacting molecule
to gain sufficient energy to become "activated" or form a reactive Intermediate.  In
dark or thermal reactions, the thermal energy of the environment supplies the activa-
tion energy.  In photochemical reactions, the absorption of light provides the
activation energy.
     The "activated" molecules In photochemical reactions differ in Important
respects from those of thermal reactions.  Thermally activated molecules usually
remain  in the normal or "ground" electronic energy state, whereas photochemically
activated molecules exist in higher, "excited" electronic states.  Because of the
excess  energy and the alteration of the chemical bonds of photoactivated molecules,
the range of potential reaction products is much greater than that for thermally
activated molecules.
     The mechanism by which photoactivated molecules form and react is divided
into three steps:  1) the absorption of light to produce an electronically excited
molecule, 2) the "primary photochemical processes" which transform or de-excite the
excited molecule, and 3) the secondary or "dark" thermal reactions which the Inter-
mediates produced in step 2 undergo (Turro, 1978).
     The mechanism of photochemical reactions provides a convenient structure for
a discussion of the factors which influence photolysis in the aquatic environment.
Environmental factors affecting the absorption of light, step 1, will be considered
first.  Then, the factors influencing the fate of molecules which become excited by
the absorption of light, steps 2 and 3, are discussed.

2.5.2.2.2  Light Absorption
             "Only that light which is absorbed by a system can produce
             chemical changes (Grotthaus-Oraper Law)." ,
                                                     '-lasstone, 1946)
     As this "first law of photochemistry" implies,  it 1s necessary to know the rate
at which reacting molecules absorb light in order to determine the rate of a photo-
                                          -96-

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 chemical  reaction  1n  the  environment.   The  following factors which influence light
 absorption  In  the  aquatic environment  are discussed here:   1) molecular absorption of
 light,  2) solar  radiation,  and  3)  light  attenuation in  natural waters.

 2.5.2.2.2.1  Molecular  Absorption  of Light
      3oth light  and molecules have quantized energies.  Light interacts with matter
 as  quanta with energies inversely  proportional  to  their wavelengths. A molecule has
 quantized internal energy states associated with the configuration of its electrons
 and the  rotation and  vibration  of  its  chemical  bonds.   Since a molecule can absorb
 light only as  a whole photon, light absorption  is  possible  only  if the energy of the
 photon  corresponds to the energy change  of  an allowed transition between tne molecule's
 Internal energy  states.   Consequently,  the  probability  of a photon being absorbed
 varies  strongly with  wavelength of the ^ight 1n a  way that  is unique to every chemi-
 cal  species.
      To  initiate a chemical  reaction,  the absorbed light must be sufficiently
 energetic to cause a  change  in  the absorbing molecule's electronic structure.
 Generally, radiation  with wavelengths  in the ultraviolet-visible range, or shorter,
 has sufficient energy to  Initiate  photochemical reactions while  radiation witn
 wavelengths in the infrared  range,  or  longer, does not.  Thus, the ultraviolet-visible
 light absorption properties  of  a chemical are of primary interest in photochemistry.
      Photochemical reactions in the aquatic environment depend on the rate at which
 molecules 1n aqueous  solution absorb light.  According  to Beer's Law, the rate of
 light absorption by a single compound  (Ift)  in a cross-section of solution with
 Infinitesimal  thickness (Az) is proportional to the concentration of the light
 absorbing specie (C), I.e.,

                            I (z) - I(z)  • 2.3  • •:  • C  • iz                   (11-64)
                             a
 where
         I(z)   •  Intensity of the  light at a depth z in the solution
         e      •  base 10  molar  extinction coefficient.
•e reflects the probability of the  light being absorbed  by the dissolved molecules and
 therefore varies with the wavelength of the Incident light as shown In Figure 11-11.
 Absorption spectra, such  as  shown  here, contain Information necessary to compute the
 rate  at which  pollutants  absorb radiation available in  the environment.

 2.5.2.2.2.2  Solar Radiation
      The only  radiant energy available for absorption by pollutants In the aquatic
 environment comes from the sun.  The sun emits radiation of nearly constant Intensity
                                          -97-

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               10*
               10*
                                                   I
182
                        200
250
   300
(nm)
                                              400
500
         Sourct: U.V. At Us of Orq«n1c Compounds.
        FIGURE  11-11     ULTRAVIOLET ABSORPTION SPECTRUM OF NAPHTHACENE
and spectral distribution.  But, gasts and particles 1n the earth's  atmosphere alter
the Incoming solar radiation through scattering and absorption.   Scattering of the
direct solar bean creates the diffuse or sky radiation visible at the  earth's surface.
Absorption of both diffuse and direct radiation reduces the Intensity  of  solar
radiation reaching the earth.  Since the strength of absorption  and  scattering
depends strongly on the wavelength of the light Involved,  the  Interaction of sunlight
with the atmosphere alters the spectral  distribution of solar  radiation as well, as
Figure 11-12 shows.
     The composition of the earth's atmosphere and the geometrical relationship of
the sun and earth change over time causing the solar radiation Incident upon the
earth's surface to vary as well.  A comparison of the total  solar 1rrad1ance under
clear skies at various times, seasons, and latitudes (Table 11-28) to  the extra-
                                         -98-

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                                                Key.
                                                  a)  Spectral distribution of sun's
                                                     radiation at edge of outer
                                                     atmosphere
                                                  b)  Spectral distribution of sun's
                                                     radiation at earth's surface
                                                                             3000
                                   Wavelength 
-------
                                      TABLE 11-28

    CALCULATED SOLAR RAOIAMT ENERGY  FLUX TO A  HORIZONTAL  SURFACE  UNDER A  CLEAR  SKY
                                     (langleys/day)
Latitude
30°N
40°N
50°N
Time
Of Day
Mean1
Mid-Day*
Mean
Mid-Day
Mean
Mid-Day
Season
Spring
680
2100
650
1900
590
1700
Summer
750
2200
740
2100
710
1900
Fall
530
1700
440
1400
330
1000
Winter
440
1400
320
1000
190
650
Annual
Mean
600
1900
540
1600
460
1300
       Mean values represent calculated seasonal means under a clear sky.  These
       should represent upper limits for solar radiant energy at sea level.
       Reference:  Weast and Astle (1980).

       Mid-Day values represent mid-day flux extended over a 24-hour period.  These
       assume an atmospheric turbidity of 0, precipitable water content of 2 on,
       and an atmospheric ozone content of .34 on NTP.  Reference:  Robinson (1966).
that the fraction of the solar energy In the ultraviolet region decreases with
Increased attenuation of light by the atmosphere.  The fraction of the energy which
is visible remains relatively constant.  For the purpose of this document, it is
sufficiently accurate to assume that the reduction in UV-visible radiation is propor-
tional to the reduction in the total flux.

2.5.2.2.2.3  Light Attenuation in Natural Waters
     Just as the earth's atmosphere reduces the intensity of solar radiation reaching
the earth's surface, natural waters reduce the intensity of radiation available for
absorption by aquatic pollutants.  The first process which reduces the availability
of light in the water column is reflection.  In most cases, the surface of the water
reflects less than 10 percent of solar radiation (Zepp and Cline, 1977).  Reflection
also alters the solar spectrum slightly.  A calculated spectral distribution of solar
radiation, expressed in photons, immediately below the surface of a water body 1s
presented in Table 11-29.
                                         -100-

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      BAN DAILY  SOLAR RADIATION (Langleys),  ANNUAL
FIGURE 11-13      SOLAR RADIATION IN THE UNITED STATES
                                                          Ref: US Dept. Com. (1968)
                         -101-

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                             TABLE 11-29

         CALCULATED SOLAR  IRRADIANCE  IN A WATER BODY OUST BENEATH
                     THE SURFACE, ANNUAL MEAN AT 40°N
Wavelength^
(nm)
300
310
320
330
340
350
360
370
380
390
400
410
420
430
440
450
460
470
480
490
500
510
520
550
600
650
700
750
800
Photon Spectral
W(X)C
(101* photons cm2 sec'ren1)
.00303
.0388
.113
.181
.211
.226
.241
.268
.294
.366
.526
.692
.712
.688
.814
.917
.927
.959
.983
.930
.949
.962
1.00
1.04
1.07
1.08
1.07
1.03
.988
Irrad1ancea
W'(X)d
(10 photons cm2 sec1)
.0303
.388
1.13
1.81
2.11
2.26
2.41
2.68
2.94
3.66
5.26
6.92
7.12
6.88
8.14
9.17
9.27
9.59
9.83
9.30
9.49
9.62
10.0
52.0
53.5
54.0
53.6
51.5
49.4
Estimated reference solar flux, I  • 540 lang leys/day. 0Q • 1.0

^Centric wavelength of  waveband X nm in width,
 for 300 . 550, X«50 nm

cMean irradiance over wavelength Interval of width X.

^Integrated irradlanc*  over wavelength Interval  of width X.
Reference:  Burns et al. (1981).
                                    -102-

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     As solar radiation penetrates deeper into natural waters, it is absorbed
and scattered by participates, dissolved substances, and water itself.  Measure-
ments of  lignt attenuation in natural waters have been based on the decrease of
solar irradiance, which includes both collimated and scattered light.  Lambert's
Law expresses the decrease in the irradiance, I(z), i.e., the total flux incident
upon an element of surface divided by its area, with depth z, as follows:
                                        • K • I(z)                            (11-65)
                                  az

where
        K  -  diffuse light attenuation coefficient.
The diffuse attenuation coefficient can be expressed as a sum of terms account-
ing for absorption, a, and backward scattering of light, s.  (Smith and Tyler,
1976):

                                   K • Da + sfe                               (11-66)

where
        D  »  radiance distribution function.
Usually, s. is small compared to the absorption term.  The absorption term
constitutes part of the beam attenuation coefficient, a, which can be measured
in a spectrophotometer:

                                   a • a + s  + s                            (11-67)
                                            b    T
where
        sf  •  the forward scattering coefficient of the solution.
     The inclusion of the distribution function, D, In Equation (11-66) accounts for
the difference In mean light pathlength of collimated and diffuse light.  Perfectly
diffuse light has a mean path through an element of water which 1s twice as long as
that of a  beam of light.  The distribution function, generally Increases asymptotic-
ally with  depth due to the Increasing fraction of the total  light which Is scattered.
In water bodies where scattering can be Ignored, D has a value of 1.2.  Miller and
Zepp (1979) reported that the mean value of D for six sediment laden waters was 1.6.
     The diffuse light attenuation coefficient of natural waters differs greatly due
to variations In the types and amounts of particles and dissolved substances In the
water.  Miller and Zepp (1979). Zepp and Schlotzhauer (1981), and Smith and Baker
(1978)  have Investigated the contributions  of suspended sediments, dissolved organic
carbon, and chlorophyll  pigments to the light attenuation coefficient,   by using
Equation (11-66)  to integrate the results of these  investigations, and assuming
                                         -103-

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backscattering to be negligible. Burns et_ al_.  (1981) derived the following expres-
sion to estimate the diffuse light attenuation coefficient:

                              chl  a)  *  (a     • DOC)  +  (a    •  SS)              (11-68)
                                         DOC           ss      J

where
        aw     «  absorptivity of water
        a,     »  absorptivity of chlorophyll-a pigment
         o                                    *"
        chl a_  •  concentration of chlorophyl l-a_ pigment
        aOOC   "  absorptivity of dissolved organic carbon
         DOC   -  concentration of dissolved organic carbon
        a      •  absorptivity of suspended sediments
        SS     »  concentration of suspended sediments.
Each absorptivity term varies with the wavelength of light, as shown in Table 11-30.
     1•ffuse light attenuation coefficients can also be estimated using turbidity
Indicators such as Secchi disc depth.  Empirical  studies have shown that the diffuse
light attenuation coefficient 1s inversely proportional to the Secchi disc depth,
Zsd:

                                    K »  -*-                                 (11-69)
                                         *sd

The proportionality constant. R, has a value between 1.44 and 1.7 for visible
light, I.e. 400-800 nrn.  In the middle ultraviolet portion of the spectrum, i.e. near
312 nm, R has a value of 9.15 (Zepp, 1980).

2.5.2.2.3  Fate of Excited Molecules
             "Each molecule taking part in a chemical reaction which 1s a
          direct result of the absorption of light takes up one quantum of
          radiation (Stark-Einstein Law)."   (Glasstone, 1946)
     According to this "second law of photochemistry", the extent to which a photo-
chemical reaction progresses depends on the number of quanta of light absorbed.  Each
absorbed photon produces an electronically excited molecule which can undergo numerous
processes. Including reaction.  Factors which Influence the fraction of excited
molecules which undergo reaction, called the quantum yield, comes first 1n the
following discussion of the fate of excited molecules.  Then, the two major classes
of  enviromental photolysis reactions, direct and sensitized, are discussed.

2.5.2.2.3.1  The Quantum Yield
     Although all photochemical reactions are Initiated by the absorption of a
photon, not every absorbed photon  Induces a  chemical reaction.  Besides chemical

                                         -104-

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                                 TABLE 11-30

                CONTRIBUTIONS TO LIGHT ATTENUATION COEFFICIENT
Waveband
Center
(nm)
300
310
320
330
340
350
360
370
380
390
400
410
420
430
440
450
460
470
480
490
500
510
520
550
600
650
700
750
800
a a
w
(nrl)
.141
.105
.0844
.0678
.0561
.0463
.0379
.0300
.0220
.0191
.0171
.0162
.0153
.0144
.0145
.0145
.0156
.0156
.0176
.0196
.0257
.0357
.?477
.0638
.244
.349
.650
2.47
2.07
a b
a
69.*
67.*
63.*
61 *
58.*
55.
55.
51.
46.
42.
41.
39.
38.
35.
32.
31.
28.
26.
24.
22.
20.
18.
16.
10.
6.
8.
3.
2.
0.
aooc
] [(mg/1)-1 m-1] [(
6.25
5.41
4.68
4.05
3.50
3.03
2.62
2.26
1.96
1.69
1.47
1.27
1.10
0.949
0.821
0.710
0.614
0.531
0.460
0.398
0.344
0.297
0.257
0.167
0.081
.
.
.
-
'".1
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
^Source:  Smith and Baker (1981)
 Source:  Smith and Baker (1978)    Calculated using aa « K?/0,
 0 • 1.2                                                   *
^Source:  Zepp and Schlotzhauer (1981)
aSource:  Miller and Zepp (1979).   Calculated using ass « KS/D.
*
 Denotes  extrapolated  values.
                                      -105-

-------
reactions, possible processes which excited molecules may undergo Include the reemls-
sion of light through  fluorescence and phosphorescence, the Internal conversion of
the photons' energy Into heat, and the excitation of other molecules, as shown 1n
Figure 11-14.  The fraction of absorbed photons which cause the desired reactlon(s)
Is termed the quantum yield, *

                        moles of a given species formed or destroyed
                   0  =  	          (11-70)
                        moles of photons absorbed by the system

     The quantum yields for photochemical  reactions 1n the solution phase exhibit two
properties which greatly simplify their use:
        •    The quantum yield 1s less than or equal to one
        •    The quantum yield 1s Independent of the wavelength of the absorbed
             photons.
     Although exceptions to these rules exist, they are rare for photochemical
reactions 1n the aquatic environment.
     Environmental  conditions Influence photolysis quantum yields. Molecular oxygen
acts as a quenching agent (see Figure 11-14) in some photochemical reactions, reduc-
ing the quantum yields (Wolfe «1 «J_., 1978).  In other cases,  1t has no effect or may
even be a reactant.  In any case, rate constant and quantum yield measurements should
be performed In water with oxygen concentrations representative of environmental
conditions.
     Suspended sediments also Influence rates of photolysis.  Not only do suspended
sediments Increase light attenuation, but they change the reactivity of compounds
sorted on them (Miller and Zepp. 1979).  Sorptlon may either Increase or decrease a
compound's reactivity depending on the reaction 1t undergoes.   This effect, however,
1s of secondary Importance in comparison to the Increase 1n light attenuation by the
suspended sediments (Burns et^al_., 1981).  Thus, the effects of sorptlon will be
neglected.
     Chemical sped at1 on also affects rates of photolysis.  Different forms of an
organic acid or base may have different quantum yields, as well as absorpt1v1t1es,
causing the apparent photolysis rate of the compound to vary with pH.  The possibility
of this should be kept In mind when the pK  of a photolyzlng compound Is 7 + 2.
Except where stated otherwise, data contained herein may be assumed Independent of pH
over the range of values observed 1n natural waters.
     Photochemically Initiated reactions may show a temperature effect depending upon
the actual mechanisms  Involved.  General methods for predicting this effect have yet
to be developed.  Users of this screening manual should assume thermal effects on
photolysis to be negligible.
     Quantum yields vary over several orders of magnitude depending on the nature of
the molecule which absorbs light and the reactions  1t undergoes.  The two major

                                         -106-

-------
                                                         A, +hMt
                                                                Chemical raaction
                                                            A. + Q'

                    Chemical reaction
                             AO - ground itaie of rtactant molecule
                             A* - eicittd tlate
                            Q8 - ground ttatt of quenching molecule
                            Q* - excited tute

             FIGURE  iI-14     PHOTOCHEMICAL PATHWAYS OF  AN EXCITED
                                 MOLECULE,   EXCITED MOLECULES DO NOT
                                 ALWAYS CHEMICALLY REACT,

classes of photochemical reactions of interest in the aquatic environment are direct
and sensitized photolysis.  A closer examination of each reaction type follows.

2.5.2.2.3.2  Direct Photolysis
     Direct photolysis occurs when the reacting molecule Itself directly absorbs
light.  The excited molecule can undergo various types of reactions.  Including
fragmentation,  reduction, oxidation, hydrolysis, acid-base reaction,  addition,
substitution, Isomerization, polymerization, etc. Figure 11-15 shows  examples of the
reactions undergone by three toxic substances which directly photolyze.
     The quantum yield for the direct photolysis, *,, of a compound is a constant
defined as follows:

                                     *   - ~/r                            (II-71)
                                      d    dt/ 'ad
where
        C    »  concentration of the compound
        IJd  •  rate at which the compound absorbs light.
Table 11-31 lists several disappearance quantum yields for direct photolysis of

                                         -107-

-------
                  OCHyCOR
                      Cl
                       Sunlight/
OCH?COR
                  Cl
      fc)
                                                                        +  R - C.
                                                                                *OH
                                            Cl
   FIGURE  11-15     DIRECT  PHOTOCHEMICAL REACTIONS  OF (A)  2,4-D  ESTER,
                      (B) BENZ(A)ANTHRACENE, AND (c)  PENTACHLOROPHENOL,
aquatic pollutants.
     By comparing molecular absorption  spectra with the spectral  distribution
of sunlight,  1t  1s possible to determine whether or not a compound may directly
photolyze.  Benzene, as shown In Figure II-16a, does not directly photolyze because
1t does not absorb light above 275 nrn.  Naphthacene, shown 1n Figure  II-16b, does
directly photolyze because of Its strong absorptivity 1n the sunlight region of the
spectrum. Humlc adds. Figure II-16c,  by virtue of their absorption of sunlight may
Initiate Indirect, or sensitized, photochemical reactions.
                                        •108-

-------
                     TABLE  11-31



DISAPPEARANCE QUANTUM YIELDS,  ca  FOR DIRECT PHOTOLYSIS
Compound
Polycyclic Aromatic Hydrocarbons
Naphthalene
1-Methyl naphthalene
2-Methylnaphthalene
Phenanthrene
Anthracene
9-Methyl anthracene
9,10-Dlmethylanthracene
Pyrene
Fluoranthrene

Chrysene
Naphthacene
Benz(a)anthracene
Benz(a)pyrene
2,4-D Esters
Butoxyethyl ester
Methyl ester
Carbaryl
N-Nitrosoatrazine
Trlfluralin
OMDE
aZepp and Schlotzhauer (1979)
bZepp et ah (1975)
;^ Reference

.015
.018
.0053
.010
.0030
.0075
.0040
.0021
(313 nm) .00012
(366 nm) .000002
.0028
.013
.0033
.00089

.056
.031
.0055
.30
.0020
.30
Slolfe et aj.. (1978)
dZepp and CUne (1977)

a
a
a
a
a
a
a
a
a
a
a
a
a
a

b
b
c
d
d
d


                       -109-

-------
IMMMONI
                      Sunlight  /
                      Sp«ctPU« /'
                                      j      1
     «ClO
                                             FIGURE  11-16
                                             COMPARISON  OF SOLAR  IRRADIANCE
                                             WITH THE ABSORPTION  SPECTRA OF
                                             (A> A COMPOUND WHICH DOES  NOT
                                             DIRECTLY PHOTOLYZE,  (B)  A
                                             COMPOUND WHICH DOES DIRECTLY
                                             PHOTOLYZE,  AND 
-------
2.5.2.2.3.3  Sensitized Photolysis
     Sunlight can cause the degradation of aquatic pollutants by  means  other  than
direct photolysis.  A light-absorbing molecule can transfer Its excess  energy to an
acceptor molecule causing the acceptor to react as 1f It  had absorbed the  radiant
energy directly.  This reaction mechanism, known as photosensitizatlon, contributes
to the degradation of aquatic pollutants when suitable light absorbing  substances, or
pnotosensitizers, are present. 2,5-D1methyl furan 1s an example of a compound  which
degrades by sensitized photolysis.  It does  not react when exposed to sunlight in
distilled water but degrades rapidly in waters containing natural hunlc acids (Zepp
et_a]_. 1981a).
     Numerous substances, Including humic acids, titanium dioxide, and  synthetic
organic compounds, can sensitize photochemical reactions.  But, most potential
sensitizers occur at such low environmental  concentrations that they have  negligible
effects on photolysis rates.  Humic acids, the naturally  occurring by-products of
plant matter decay, frequently attain concentrations of 1-10 rag as carbon  per liter
in natural systems.  Humic adds strongly absorb sunlight with wavelengths shorter
than 500 nm, as the absorption coefficients  for dissolved organic carbon,
in Table 11-27, indicate.
     The quantum yield for photosensitized reactions, * , 1s defined 1n a
manner similar to the quantum yield for direct photolysis:

                                 *  .:*£/,
                                  s    dt/  «s
where
        C    «  concentration of the pollutant
        I    •  rate of light absorption by  the sensitizing molecule.
         as
The quantum yield for sensitized photolysis, however, Is  not constant but  depends on
the pollutant concentration, such that:
where
        Q   »  a constant.
This 1s due to the fact that the probability of the sensitized molecule donat-
ing its energy to a pollutant molecule Is proportional  to the concentration of
the pollutant molecule.  Published values of Q are very rare.  Zepp et  a_K   (1981b)
report a Q of 19 (mol/1)"  for the photosensitized oxidation of 2,5-dimethylfuran.
                                         -Ill-

-------
2.5.2.2.4  Preliminary Screening of Direct Photolysis
     As the preceding discussion Indicates, a  number of  environmental  parameters
influence pnotolysls.  The following sections  show that  the procedure  for  calculating
the photolysis rate can be quite Involved.  Therefore, a preliminary screening which
attempts to determine whether photolysis rates are likely to be  significant  or
Insignificant (without actually calculating the rate Itself) 1s  useful.
     If i« 0 (I.e. 1f the molecule does not absorb solar radiation)  for  290  ~730 nm, then direct photolysis 1s probably unimportant.   Refer-
ences which contain \* values (1n addition to  Table 11-32 of this  document)  Include
Lyman et_ aj_. (1982), FMedel  and Orchln (1951), Hershenson (1966)  and  Kamlet (1960).
The Kamlet reference 1s a series of 20 volumes from 1960 to present  and  contains  \*
values for many thousands of organlcs.
     It should be recognized that small 9,, or  small  «  .„ are not good  1nd1-
                                         U          TOO A
cators of tne Importance of photolysis.  For example,  consider the tabulations
below:
        *d (benzo[a]pyrene)  »  0.00089 at  x-  313 nm
but
              "  13,000;  X •  347 nm
              •  24,000;  X -  364 nm
        «max  *  29,000; X-  384 nm
and
        "do (near sur'»c« photolysis rate)  »  17./day
The quantum yield for benzo[a]pyrene Is small (0.00089) considering that quantum
yields can be as high as 1.0.  However, the near surface photolysis rate (I.e.  the
photolysis rate 1n a very thin layer of clear water)  1s 17./day,  a very  large  rate.
This result Is caused by the high extinction coefficients for benzo[a]pyrene,  and  It
1s evident that photolysis can be Important for this  compound.
     Now consider the case of small  «
                                     nH X
     For naphthalene :

        'max  "  25° at  x"
but
        *d  •  0.015
and

        "do  '  °'2/da*
                                         -112-

-------
For the small c^^ (250), the near surface photolysis rate is 0.2/day.  While
this is not an extremely large rate, it may also not be negligible either, depending on
the particular environmental condition.
     Certain categories or groups of chemicals are likely to be poor absorbers  of
sunlight.  A number of these groups are shown below:

                        Group                _ Examples _
                      alcohols               R-OH:  ethyl  alcohol
                      ethers                 R-O-R':   diphenyl  ether
                      amines                 R-NH-lprlmary ) :  methyl ami ne
                      nltrlles               R-CN:  hydrogen cyanide
                      (cyanides)
For these groups, photolysis 1s likely to be unimportant.  Other groups, however, do
tend to absorb sunlight.  Figure 11-17 shows a number of these groups.
     A final  preliminary screening Is to compare an estimated upper limit photolysis
rate (e.g., using*.  »  1) against other first-order rates  which have already
been calculated.  If these rates are high enough, the photolysis rate, even under
optimal light-absorbing conditions, may be relatively small  and therefore negligible.
For example,  an upper limit photolysis rate which is  calculated to be 20 percent  as
large as a hydrolysis rate is relatively Insignificant.

2.5.2.3  Computing Environmental  Photolysis Rates
     The overall  rate at which a pollutant photolyzes in the aquatic environment  is
the sum of the rates of direct and sensitized photochemical  reactions.  At the  low
pollutant concentrations observed in the environment, the rates of both  direct  and
sensitized photolysis are proportional to the concentration  of the pollutant.   Thus,
photolysis follows a first-order rate law:
                                    .  -kp  •   C                            (11-74)
                                dt       p

where
        kp  *  overall photolysis rate constant, day*
            •  kd ' 's
        k^  •  direct photolysis rate constant, day
        k$  •  sensitized photolysis rate constant, day" .
Due to the complexity of the units for the parameters in the photolysis  section,  it
is essential that the user employ the specified units in each equation.   All  resulting
first-order photolysis rate constants have units of day  .
                                         -113-

-------
                                                             r«
                            Oroop             (nm)
*C-O Ulctehydt. ktiont)
X-s
-N-N-
-NO,
rY^l
^sX*X^
f^N^^V^
kAJ^
O-o

;c-c-c-o
1 I
295
460
347
278
311
270

360
440
300
330

10
WMfc
18
10
250
MOO

6000
20
1000
20

                 SOURCE:   CALVERT  AND  PITTS
        FIGURE 11-17   CHROMOPHROIC  GROUPS  WHICH  ABSORB SUNLIGHT

     The determination of  rate constants for direct and sensitized  photolysis
1s the subject of  the remainder of this section. Section  2.5.2.3.1  Includes a
derivation of the  equations  for k  and k . Sections 2.S.2.3.2 and 2.5.2.3.3
describe how to calculate these constants on the basis of near surface  rate constants
or molecular absorption spectra.

2.5.2.3.1  Derivation of Rate Constant Equations

2.5.2.3.1.1  Direct Photolysis
     Figure 11-18  shows the  major processes which Influence direct  photolysis of
pollutants 1n natural waters and Indicates data requirements.  This figure can be
translated Into mathematics  as follows:
     Light absorption within a small wavelength band AX:
     Light absorption In  a  water body of depth Z;
                                         -114-

-------
                  PROCESS
                                      DATA
       LIGHT ABSORPTION BY POLLUTANTS:
       MUST BE  IN ULTRAVIOLET-VISIBLE
       SPECTRUM FOR PHOTOLYSIS TO OCCUR
                                   EXTINCTION

                                  COEFFICIENT,C
       LIGHT ATTENUATION IN  NATURAL
       WATERS:   LIGHT REMAINING
       AVAILABLE  FOR PHOTOLYSIS
       DECREASES  WITH OE"TH
                                     DIFFUSE

                                   ATTENUATION

                                INEFFICIENT, K
LIGHT UTILIZED FOR PHOTOLYSIS:
ONLY A FRACTION OF THE AVAILABLE
LIGHT is USEC FOR PHOTOCHEMICAL
REACTIONS



I^REACTION
QUANTUM YIELD,
•o
            PREDICTION OF DIRECT
            PHOTOLYSIS RATE:  K-
FlGURE  11-13
MAJOR PROCESSES WHICH  INFLUENCE PHOTOLYSIS
OF  POLLUTANTS  IN NATURAL WATERS
                                 -115-

-------
     Photolysis rate for wavelength  band
             a e,w,
              X A  A

The equation for direct  photolysis  becomes:

                                             y1     y   i-e'*'z     (              (11-75)

where                                        °
        Z   •  mixed depth of water body,  m
        \,  •  700 nm
        V   »  300 nm
        j   »  conversion factor «  1.43 x  10    mole-cm  -sec-1   -day
        «   •  base 10 molar extinction coefficient  of pollutant, 1 mol" cm"
        C   •  concentration of pollutant, mol/1
        0   •  radiance distribution function
        M   •  photon irradiance near the  surface, photons cm" sec" nm"
        K   •  diffuse light attenuation coefficient  of  the water, m"1


Equation  11-75 can be written In summation notation  as:

                                    700        l-e""2
                     d    "        A-290  X X    KZ                           (II~
Equation  (11-75)  incorporates the assumption  that C, K,  and  0 are  independent  of
depth.

2.5.2.3.1.2  Sensitized Photolysis
      The  rate at  which a compound decays through  sensitized  photolysis  1s  propor-
tional  to the rate at which sensitizing molecules absorb light.  The  rate  at which
sensitizers absorb light 1n the aquatic environment  Is:
 where
                             j'as  (X)  ' C$  (z}'°(^ *w(x) '« "      dxdz
         I,    •   rate  of  light absorption by sensitizers, elnstein 1" day"
          as
         a    •   base  e absorotion coefficient of the sensitizer, e.g.,
                 1  m
         C    •  concentration  of  sensitizer, e.g., mg-DOC/1.
                                         -116-

-------
The rate constant for sensitized photolysis of a compound,  k ,  is then:
k
Al -K
/ 1 - *
a • * •
V 7
A
0
                                                                             (II-78a)
Equation il-78a includes the assumptions that C , K, and D are independent
of depth and that Q  is independent of wavelength.
     In terms of summation notation, this equation becomes:
                                          ^              .
                               J-Q$'0-C$- Z  as  • W  •  l~*ml               (II-7Sb)
2.5.2.3.2  Use of Near Surface Rate Constants
     Experimental data for direct photolysis are generally reported as near surface
rate constants, as in Table 11-32.  Near the surface of a water body (K-z £0.2),  the
mean irradiance is approximately equal  to the surface irradiance.  This fact  permits
Equation 11-75 to be simplified to the following expression which defines the near
surface rate constant, k  :

                                                     ,'•1
                          kdo  '  2'3  ' *d  '  °o
where
         k.    «   near-surface direct  photolysis  rate constant, day"
         D     •   radiance  distribution  near  the  surface  (approximate value •
                 1.2).
     According  to  Equation  (11-79),  the  near  surface  rate constant is  Independent of
the  properties  of  the  water  It  1s measured  In,  except for the small variation
in 0 .   Thus, when the difference In solar  irradiance between the experimental
and  environmental  conditions  is accounted  for,  the user can  apply a near surface rate
constant to  other  bodies  of water using  the following expression:
                                         -117-

-------
                TABLE 11-32
NEAR-SURFACE DIRECT PHOTOLYSIS RATE  CONSTANTS
CJTOura"
•:',;, c'.ic Arctic -yd'ocarcon
Naphthalene
1-Metnylnapntnalent
C-f'«tny Intpntnalene
An-.nracere
9-v«tn>:antnr«cer.e
?. 1 3- jimetny; anthracene
Pyrene
f luOranthren*
Cr-rysene
Nacn'iacene
Serioi a,pyre«e
Ben^aianthracent
Caroarate 'esticidts
CarOaryl
Sropharr
Chlororopna*
dutnyl ester
di.n- Butyl ester
d'-"-octyl ester
di-, 2-etnyih«,yl , ester
2,--; Esters
ButOiyethyl ester
methyl ester
HtucMorocydoMiitMimt
Pentachlorophenol (anion)
3,3' -dichlorob«nzidint
N-nitrosoatrtzine
Triflural in
DHOEi l.;-B'SlP-««tnylpn«nyl 1)-
Notes
1
*30
.23
.?6
.31
2.3
22 ;
130.:
48.3
24. C
79
3.3
490.3
31.0
28.0
.32
<.OC3
<.006
5.1C"3
S.1C"3
S.1C'3
5.1C'3
050
.030
94.
46
670.
300
30.
17
'o-"
210C
21CC
210C
2100
21CC
2100
210C
21CC
2 IOC
2100
2100
2100
2 ICO
2100
740
740
600
600
60C
600
60C
420
420
540
600
2000
1800
1800
2200
"«
1 Parenthetic conwnts a'ter nan* of compound Indicate »nen tne for*
Of th« coapound undergoing photolysis IS something other than th*
neutral fonr
2 Estimated Solar rlu« • usually nign estiiutes to give conservative
photolysis rates.
j Wavelength o' Ria>i«wi sunlight absorotion


• Indicates the i«*«irx*i o' tne absorption spectrv ", used
j
•>! Inn,
310
312
320
3i3
36C
380
400
330
-
320
440
380
340
313
-
-

-
.
J18'
,ef
i
t
a
a
a
a
i
a
a
a
a
a
a
b
c
c
d
d
d
d
d
e
e
f
f



















280- 3 JO* f
.
-
f er»nces :
a ) Z»pp
B) 2*pp,
d) uolfe
e) Zepp
'! CalU
9! >PP
9
9
9
and Sc>
(1978)
et ai
«i 11
*t a_T
nan e_i
and C! '



(1978)
iwao:
:i979!
aj_ 1979
.n, ;1977
                 -118-

-------
                                700        , .-K2
                             o  y.  e,3.
so:
                               \-T90_   "                                    (II-80D)

                               "•

                         -.   PI    l-e'K(K*)Z                              (II-SOc)
                             °oro
                      k  - k    • i-  • J  • ^-?'                             (II-80d)
                      Kd   Kdo   T    D     K(,;*)Z
where
        I   •  total  solar radiation (1 angleys/day)
        IQ  *  total  solar radiation under conditions at which kd  was
               measured (1 angleys/day)
        \*  *  wavelength of maximu- light absorption, i.e. wavelength where the
               product «(\)'W(\) is greatest.
     This approximate express'"- is valid if the following assumptions are suffici-
ently accurate:  1) the solar irradiance at a wavelength is a constant fraction of
the total  solar irradiance (Park e£ a_l_. , 1980) and 2) the light attenuation coeffic-
ient, K, 1s constant  over the range of wavelength that the compound absorbs solar
radiation at nigh rates (Burns et^ a_l_. , 1981).
     Although it is possible to derive a similar expression for sensitized photolysis,
variation in the absorptivity and reactivity of natural  humic substances  make extra-
polations based on the concentration of  dissolved organic carbon subject  to large
errors.  An approach  taken by Zepp (1980) was to correlate the sensitized photolysis
rate constant with the absorbance of a solution at 366nm.  Such an empirical  relation-
ship was found for 2, 5-
-------
shown 1n a step-wise fashion In Table 11-33.  Note that the effects of water depth
and light attenuation can be estimated based on water-body characteristics from Table
11-34.  Thus the method essentially consists of multiplying several numbers together
to find k..
         d
     If kd(j, which Is required to use the method outlined in Table 11-33, 1s not
directly obtainable, 1t can be calculated from Table 11-35 and then used in con-
junction with the near-surface approach described above.  One advantage of using the
near-surface approach (in addition to Its simplicity) 1s that the photolysis rate In
different classes of natural waters can be readily evaluated using Table 11-33, once
k.  has been calculated a single time.
     In some cases, the near-surface approach may not be applicable.  Equations
II-80a through II-80c show some of the simplifications required to develop a near-
surface approach.  Photolysis rates for chemicals which have multiple *    values
                                                                       max
within the wavelength range 290 nm < x.<700 nm should not be calculated using the
near-surface approach.  Rather, the direct approach outlined In Table 11-37 should be
used 1n conjunction with the procedure shown in Table 11-36.
     Very little emphasis is given here on rates of indirect photolysis because
little data are available on indirect photolysis rates.  Table 11-38 summarizes the
pertinent work of Zepp (1977).  Zepp found that the near-surface half-life for
Indirect photolysis for several chemicals 1n Okefenokee Swamp waters was very short:
from 0.02 hr to 7 hrs.  The near-surface rate constant translates to between 2.4/day
to 830./day.  However, on a depth-averaged basis, four of the five photolysis rates
are below 0.06/day.  Only for pentacene Is the depth-averaged photolysis rate
high (5.8/day).  Thus, the same factor (humic material) that is responsible for the
high near-surface rate constants, is also responsible for the small depth-averaged
values because much of the sunlight 1s rapidly absorbed near the water surface.  For
this reason, and because of the lack of data. Indirect photolysis 1s ignored in these
assessment procedures.
                                          -120-

-------
                                 T/WLE  11-33

                       SUMMARY  OF  NEAR  SURFACE APPROACH
 1.    Predictive  Equation:
 2.    Find:

           k
            do
                - See Table 11-32,  or
                - See Table 8-12,  p.  8-38,  lyman jet .al.., where  half-Hves  are
                  given:
                                  do
                      (1.2-1.6)

                      (1.2)
      I   « 	 (500-700  langleys/day)

      o

      X*
IQ - 	 (500-2100 langleys/day;  see Table  11-29)
           -  Table 11-32
           -  Table 8-5,  p. 8-14,  of'Lyman  et _aj,
           -  FHedel  and OrcMn,  1951.
           -  Hershenson, 1966.
           -  Kanlet (ed.),   1960.


 3.    Knowing A*  and  Depth of Water  body,  Z, Find
                                   K(X*)Z

      Table  11-34  shows  some  typical values of this expression.


4.   Find k, using equation shown In step 1.

5.   Suppose kd(J Is not known from experimental  studies.   It can be

     calculated fro* the procedure shown 1n Table 11-35.
                                    -121-

-------
   TABLE  11-34
             -K(X*)Z
RANGE OF
         1-e
Depth of Water (m)
Mnm) Water Type*
300 A
B
C
D
340 A
8
C
D
380 A
B
C
D
420 A
B
C
0
460 A
B
C
0
500 A
B
C
0
a
Water Type chla
A 0.0
B 0.001
C 0.01
0 0.1
1
0.9
0.5
0.1
0.03
0.9
0.7
0.2
0.04
1.0
0.8
0.2
0.05
1.0
0.8
0.3
0.06
1.0
0.8
0.3
0.07
1.0
0.8
0.3
0.07
(rnq/1)
(Lake Tahoe)
(eutropMc)
2
0.8
0.4
0.06
0.01
0.9
0.5
0.08
0.02
1.0
0.6
0.1
0.02
1.0
0.6
0.1
0.03
1.0
0.7
0.2
0.3
1.0
0.7
0.2
0.4



(highly eutropMc)
3
0.8
0.2
0.04
0.009
0.9
0.4
0.06
0.01
1.0
0.5
0.07
0.02
1.0
0.5
0.09
0.02
1.0
0.6
0.1
0.02
1.0
0.6
0.1
0.02
DOC (mq/1
0.0
0.1
0.5
2.0
5
0.6
0.14
0.03
0.005
0.8
0.2
0.03
0.007
0.9
0.3
0.04
0.009
1.0
0.4
0.05
0.01
1.0
0.4
0.06
0.01
0.9
0.4
0.07
0.01
*



10
0.4
0.07
0.01
0.003
0.7
0.1
0.02
0.004
0.9
0.2
0.02
0.005
0.9
0.2
0.03
0.006
0.9
0.2
0.03
0.007
0.9
0.2
0.03
0.007
SS (mq/1)
0.0
0.5
5.0
20.0
      -122-

-------
                           TABLE 11-35
              DIRECT PREDICTION OF NEAR SURFACE RATE
Predictive Equation:
                                     700
                   k,n ' 2.3 J*J>
                    do         
-------
                                                  TABLE  11-36
                         PROCEDURE FOR CALCULATING DIRECT PHOTOLYSIS RATE CONSTANT
                            FOR  A REFERENCE  LIGHT  INTENSITY  OF 540 LANGLEYS/DAY
.tm-t/t*
.•I'M*4
.IM-M14
.M.-"
.«*••***
.iii-M**
I.M-M*4

I.M-M*4
t.ll-M14
I.M-M*4
I.W-M*4
MKI14
LII-M*4
.11 V
               M-i-M1'
M.I-M*4
M.i-M*4
M.I-M*1
i
*






















1_
' • ' 10 II 12
» . (iTii . •&,,.., &'» . J8h^ £!, . ,!&,„ ti'U • tr''i
.Ml M. in *M
.1* W. t.M iM
.MM M. •• «.„
.M* M. IM AH
.MM M. I.M i.M
.•>» M. IM tM
.MM M. >» ai(
.MM M. 1 • (.n
.«• «. I.M (H
.•N «. 1 «* IH
.•M M. 'ill §M
.•U M. 1 M ^H
.•M M. I.M (M
.•M m. im n,
.•M M. IM ,„
••» » ••«« I.N
flM M. 1 ftM
.MM M. I-MI
.MM M. I.Nf r-
.MM M. in* ^M
.MM M IMI ^M
Mi 1
•*" «.»

13 14 IS
^
U • **M * f






















i 	 1


1. UMrfMi »,
•*"
^"h^VH*
. 	 ,w»*r
i. Mr • IIMI MMKW M«r
M. 1. • Ml limnKHn

•i " %' U * ' ***

MlMrf I'l
II). ll-lt. • III l
-------
                                TABLE 11-37
            DIRECT PREDICTION OF DEPTH -i'/ERAGED PHOTOLYSIS  RATE
•    Predictive Equation:
                                    A-700       ,   -KZ
                      k, - 2.3 j*J)  £   eiHi±:£	AA
                       0         °  A-290  *  A   KZ
•    Data Required:
          !•   'd
          2.   D
          3.   e^  versus A
          4.   Wx versus X
          5.   Hater body characteristics:  depth,  chla, DOC,  SS
•    Approach:   Use Table 11-36
          a)  Enter A versus c In column  5 and appropriate  rows, and
              calculate cWAA 1n column 6.
          b)  Enter D (column 7),  chU  (column 9),  DOC  (Column 10),  and
              SS (column 11)  1n appropriate rows.
          c)  Calculate K (column  12) for appropriate rows.
          d)  Knowing water depth  Z,  calculate appropriate values for
              column 13.
          e)  Transfer column 6 entries  to column  14.
          f)  Multiply column 13 entries  by column  14 entries  and
              record In column 15.
          g)  Sum column 15 entries and  use Equation 1 on  RHS  of sheet
              to find kd.
                                  -125-

-------
                                  TABLE 11-38
                ESTIMATED HALF-LIVES FOR INDIRECT PHOTOLYSIS OF
                      ORGAHICS IN OKEFENOKEE SWAMP WATER*
Organic
Naphthacene
Pentacene
H1st1d1ne
Tryptophan
Methlonlne
Half-Ldfe
(hr)15
7
0.02
2
2
3
Near-Surface
Rate Constant
U/dav)D
2.4
830.
8.3
8.3
5.5
Depth-Averaged
Rate Constant
fl/day)r
0.01
5.8
0.06
0.06
0.04
        *Zepp, R.G. et_ al., 1977.  Singlet Oxygen 1n Natural Waters.
        Nature, Vol. 267.
        Near-Surface (1 cm) rate constant
        C0epth-averaged rate constant.  Assume humlc materials
         12 «9/l, depth • 3m.
	  EXAHPLE 11-7 	

                   Computation of Photolysis Rate Constants

      Compute  the mean annual photolysis rate constant for the p«st1dde carbaryl
 1n  a  hypothetical  river near Fresno. California.  Use both the evaluation of
 Integral  and  near  surface  rate constant methods described above.  Assume the
 following physical and chemical parameters apply to the river:
         Mean  depth • 2 m
         Suspended  sediments • 10 mg/1
         Hu«1c add • 2 mg-DOC/1
         Chi orophyl1 a » 0  mg/1
      Zepp (1978) reported  a quantum yield, *., of .0060 and the follow-
 1ng absorpt1v1t1es, «, for carbaryl:
                                       -126-

-------
             Wavelength (nm)              Absorptivity  (M'm")
                  30U                             918
                  310                             356
                  320                             101
                  330                              11

A.  Near Surface Rate Constant Method
     Table 11-32 contains the following  information regarding  carbaryl :
        kd  « .32 day"1
        IQ  •  2100 langleys/day
        X*  «  313 nm.
     According to Figure 11-13, the mean annual  solar  irradiance at  Fresno,
California is 450 langleys/day.
     Assume that the radiance distribution function under reference,  D ,
and environmental, D, conditions have values of  1.2 and  1.6  respectively.
     To calculate the light attenuation  coefficient at the wavelength of maximum
light absorption, 313 nm, we  use Equation 11-68  and the  data in  Table 11-30, at
310 nm:
        K - 1.6 (.105 * 67 -  0 + 5.41 •  2 + .35  •  10)
          * 23.1m"1
     When the water absorbs nearly all  of the incident radiation,  I.e.,
kZ _>_ 3, the following approximation is  valid:
         1  -    KZ ,  1
This approximation can be applied to Equation 11-76 and Equation II-8CW.   It both
simplifies the calculations and eliminates the dependence of the rate constant  on
the radiance distribution function, D, In cases where the light attenuation
coefficient Is calculated from D, as in this example.  In such a case,  the user's
choice of a value of D does not affect the result.
     Using this approximation In Equation (II-80d), the mean photolysis rate
constant 1s computed to be:
                     L .  450 . 1.6 .    1
           •  2.0 x 10'3 day'1
     This example demonstrates the significant difference,  100 fold  in  this
case, which may exist between near surface and mean photolysis rate  constants.
The strong attenuation of light by the river water was the  primary cause of
the reduction In rates.
                                      -127-

-------
I   B.  Evaluation of Integrals
I        The absorption data for carbaryl Indicate that we need to concern ourselves
|   only with light of wavelength 300-330nm 1n order to determine a mean rate constant.
j        First, we assume that D has the same value as above, -1.6.  Then, we compute
j   the light attenuation coefficients using Equation 11-68 and the data In Table
j   11-36.

!       •       ••[•••(•„•     3 for all  wavelengths of Interest, use the approximation discussed
   1n part A.

          X           c             W x 10'14                         c.H,
        (nm)      (M^cm"1)      (photons/cm2/s)       (K-Z)           TT
        300         918               .0303           51.6          .539 x  10  14
        310         356               .388            46.2        2.99  x  10  14
        320         101              1.13             41.4        2.76  x  10  14
        330          11              1.81             37.4          .532 x  10  14
                                                             £ « 6.82  x 10  14
                                                             1

        Given that the quantum yield Is .006, the mean photolysis rate constant
   can be computed using Equation 11-82 and the above Information:
           k., • 2.3 • 1.43 x 10"16 • — •  .0060 • 1.6 • 6.82 x 1014                    j
            d                        540                                                !
              • 1.8 x 10"3 day"1                                                        '
I        The small difference between the rate constants calculated 1n parts A           [
j   and B 1s due to the difference 1n the reference solar Intensities.  The assumption   |
j   made here that the spectral  distribution of solar energy 1s Independent of Intensity!
                                          -128-

-------
   1s only approximately true.  Consequently, the greater the discrepancy  between  the
   reference and local  solar Intensities,  the greater the error 1n  rate  constants
   that can be expected.  When the local  exceeds  the reference Intensity,  the  actual
   rate constant Is probably higher than the calculated  value.  When the reference
   exceeds the local  Intensity, the actual  rate constant Is  probably lower than
   cal culated.
                               END OF EXAMPLE 11-7
                                                                                    -J
2.5.3  Hydrolysis
     Some toxic compounds can be altered by  direct  reaction  with  water.   The  chemical
reaction of a compound with water 1s called  hydrolysis.   Typically  1n  hydrolysis
reactions hydroxide replaces another chemical  group.
     An example hydrolysis reaction for a toxic organic  compound  1s  given below:
      Carbaryl
                             H20
Water,
a-Naphthanol
                               Ho  NCH:
                                CO-
Methyl ami ne +• Carbon
              Dioxide
     Generalized hydrolytic reactions of organic compounds are presented 1n Table
11-39.
     Hydrolysis reactions alter the reacting molecules but do not always produce less
noxious products.  For example the more toxic 2,4-0 add Is produced from the hydrolysis
of certain 2,4-0 esters.  Alternatively the hydrolysis of carbaryl  (shown above)
produces less toxic products, I.e. a-naphthanol and methyl amine.
     Hydrolysis products may be more or less volatile than the original  compound.
Hydrolysis products which Ionize may have essentially zero volatility depending upon
pH.  Hydrolysis products are generally more readily blodegraded than the parent
compounds, although there are some exceptions.
     Hydrolysis reactions are commonly catalyzed by hydrogen or hydroxide Ions.  This
produces the strong pH dependence often observed for hydrolysis reactions.  Examples
of this dependency are shown 1n Figure 11-19, where the logarithms  of reaction rate
constants (KH) are plotted versus pH.  The hydrolysis rate of carbaryl  can be
seen to Increase logarithmically with pH. The rate at pH • 8 1s ten times that at pH
• 7 and 100 times that at pH - 6. The hydrolysis rate of parathi on  1s high at low pH
                                         -129-

-------
                                    TABLE  11-39



             GENERALIZED  HYDROLYTIC REACTIONS OF ORGANIC  COMPOUNDS
SsiCTAr.T REACTION CONDITIONS
CAaaoxv_;c ACID ESTERS ACIDIC, NEUTRAL,
n BASIC
/,
R-C'c-R'
AMIDES ACIDIC, BASIC
^°
R~C
i
i
H
CARBAMATES ACIDIC, BASIC
H
i
Rir
n.
C-O-R'
n
0
CRGANOPHOSPHATES BASIC (AciDic,
('AND DERIVATES) NEUTRAL)
0
RO-P -or
l
OR
HALOGENATED ALKANES NEUTRAL, BASIC
R
/C~~X
R'
R"
PRODUCTS
CARBOXYLIC ACID * ALCOHOL
. Q
sS
R-C^ * R'OH
CARBOXYLIC ACID * AMINE
//Q H\
R-cf * ,11
N0ll / NR'

AMINE * ALCOHOL * CARBON DIOXIDE
R-n/H R'0" ^
\
H


PHOSPHATE Di ESTER * ALCOHOL
0
RO — P — OH ROH
i
OR

ALCOHOL * HAL IDE ION
R
R1 — C— OH X
1
R"
SOURCE:   l.J. TiusLEY,  CHEMICAL CONCEPTS IN POLLUTANT BEHAVIOR,  J.  WILEY, Nex YORK (1979).
                                        -130-

-------
                                         O  Parsthion
                                         0  Carbaryl
                                         O  Chloromethant
                                            2.4-0 (2-butoxyettiyl
                                            wttr)
FIGURE 11-19  PH DEPENDENCE OF HYDROLYSIS RATE  CONSTANTS
                            -131-

-------
values, reaches a minimum at pH * 6, and then Increases with Increasing pH.   The
hydrolysis rate of chloromethane shows minimal  dependence on pH over the range
presented.
     Adsorption can aiso Influence hydrolysis rates.  Adsorption of an organic
molecule protects It from acid or base catalyzed hydrolysis (Wolfe, 1981).   The
amount of adsorption can be predicted using the principles presented 1n Section
2.3.2.
     M1crob1a1ly mediated hydrolysis reactions  are responsible  for the breakdown of
many complex molecules, Including natural  polymers such as cellulose.   Microorganisms
catalyze hydrolysis reactions 1n the process of using organic compounds as energy
and/or carbon sources.  In come tab ol 1 SHI microbes may hydrolyze  toxi - organic  com-
pounds to hasten their removal from cell protoplasm.  N1crob1al1y me_.ated processes
are covered under the general heading of blodegradatlon 1n Section 2.5.1.  Here only
abiotic hydrolysis 1s treated.
     Abiotic hydrolysis reactions are represented by rate expressions  which  are first
order 1n the concentration of the compound being hydrolyzed:

                                   R  •  !£- -k   C                             (11-82)
                                       3t     H  T
where
        R   -  th«
                  -1
R   •  the rate of hydrolysis,  mole liter"  sec"   or *g  liter"
               sec
               specific hydrolysis rate constant, sec"
        Cy  •  the dissolved plus sorbed phase  concentration of compound C
               mole liter"1 or *g liter"1.
     In the literature KH Is typically defined as:
                               *   »  k   *  k   [H*>  k   [OH~]                     (11-83)
                               nna        b

      In this document the specific hydrolysis rate constant, KH, 1s defined
to  Include  the effects of adsorption:


                           k   - k  * a  /k   [H*> k   [OH*]) 1                  (H-84)
                            H  L n     w  \ a        b      /J
where
                                                           "
        <*H      •  the decimal fraction of the total amount of compound C which Is
          the neutral hydrolysis rate constant, sec
          the decimal fraction of the total amount c
          dissolved  (Calculation procedures In Section 2.3.2)
          the add catalyzed hydrolysis rate constant, liter mole"
          sec"1


                                 -132-

-------
         [H*]   »  the molar concentration of hydrogen Ion, mole liter"
                   ([H*] * lo"pH)
         kb     •  the base catalyzed hydrolysis rate constant,  liter mole"
                   sec"1
         [OH" J •  the concentration o' hydroxide 1on, mole liter"
                   [OH"] - lO^-'V » 10(PH"14).
Equation 11-84 1s a convenient definition of *H because specific rate  constants
which act on the dissolved and total concentrations do not have  to be used  separately.
     Values for the three rate constants kn, kflf kfa for selected compounds
are presented in Table 11-40.  Additional  values can be found in the literature (e.g.
Mabey and Mill, 1978).  The three constants can also be determined by simple labora-
tory tests.
     Water body pH values must be obtained for hydrolysis reactions which are pH
dependent (i.e. those for which ka ^ 0 and/or k.  ^ 0).  It should be
noted that 1n poorly buffered waters (alkalinity £50 mg/1  as CaCOO, pH values
may change by 1-2 units daily due to natural processes alone.  In these cases either
additional  data must be gathered to characterize the system's pH regime or  conserva-
tively low values of kH must be used.  Table 11-41 summarizes the procedures.
                                EXAMPLE 11-8
1        A biodegradation rate constant, kg for the fungicide Captan has  been            j
   given as 0.5 per day.  Compare this with the abiotic  hydrolysis  rate  constant,
!   kH, at pH « 8.4, a temperature of 25°C, and with 90 percent  of the compound
|   adsorbed on suspended matter.  Values for ka, k&,  and kn  can be  found               !
I   in Table 11-31.                                                                     |
j           ka - 0                                                                      I
j           kb - 4.9 x 107 day'1                                                        j
i           "n ' !•
            (   -fa  (k  [H+]  + k  [OH~]j] + k
             H  L* \  «       b    /Jn
   thus
          [OH'] i 10PH-14 - la8'4'14 - lO-5'6 - 2.51 x
           H -[(1.0-0.9).(4.9 x 107 x 2.5 x lo"6)] * 1.6
             "12.3* 1.6  - 13.9 day"1
                                         -133-

-------
                      TABLE 11-40

HYDROLYSIS RATE PARAMETERS AND ESTIMATED ENVIRONMENTAL
                   HYDROLYSIS RATES
Njrfroljr
{n«atu)fo«
HtetiCKtor ?
C«rh«rrl
»ro*M

CMorfropfcta
2.4-0(2-l*t*>jr«tk/l ««ttr) 1.7
2.*-0(N*tk)rl ttur)
•iritnion 1.3»UT*
PhOMWt T
D«U for T
NtlitMon 1
Ct»tM
•trlllnt 3.4
"""""""
CMorwvtk***
CMorottlM**
OlcMertMtk***

rrtcklorMtt-M
1 ra*ot \ e k 1 c rovthwt
0 1 k rocock 1 e r«B tkww
TrlkrMMMtkM
H,,.cMorMnl«MHU41«M
M«lo««««ti« Conn
H;(ch)*r«M,tkjrl) ttMr

2-Ckl.rwtkrl «1i«yl ttktr 3.U10*
Mthtdtt (tttrt
0«*tk)r1 «t*r 1.
Otltkyl ttUr 1.
Oi-^-kwtyl t»ttr 1.
0>-«-« liter 1.
*1 T*
H»tickl|ra>l>»Ml 1.1,10
••Ut
*'• Mf<*tl> rtt* MrMMvr iwt it*** M4 n«t tttta
*•' M«*tit nr» «r «try ixll r«t« ttrtttttr
Uiiumi «t «i. (1*71)
wifi «t Jf.Tnii)
i*** jrff' (\m\
r.r* g iT. UMOt
mMy**«4 Mill (l»7t)
« Milf* (t ll- (1HO)
III lati Nriaturt K>«r»lyi<«
kB(tey ) kt(l'«"ltey"') k^ltey" )
3.J,10S 3.S,10"Z
T » .7
4.1,WS 4.3,10'2
.M 1.1,10**
J
1.7 1.7,10''
2.I.101 .2*
l.S,10* .11
J.I, 10° 2.44,10J J.»,10"J
? ? 2.3
? ? 1.2
T ' l.iilO'2
l.l 4.»,107 S.I
l.t . I.I
t.lilO0 31. 2.»>10'1
J.»,10"* 12. 3.1J10'1
1.I.10'1 - 1.1,10'*
2.1*10 1.1*10* 2.li)0*
j
1.0 1.0*10
1.4.101 1.4.10'1
It. t.filO**
It. J.fclO"4
4.U10** - 4.1*10**

1.1*10' - l.iilO1
•
3.U10'1

l.0,lfl3 I.OmlO*4
l.lilO1 l.tiU**
*.1,10* ».1,10"S
1.4,10J 1.4,10'*
l.t I.I*U'7
t.tuio'1 3.1 i.iiir1

•til t>M tet4 1* i if ii tail




Wttll
MtM (»*•')
V (ten)
21
1.
11.
1.1, 107
tf
4.0,10*
2.7
4.1
1.1,10*
.30
.M
11.
.13
.10
2.7110*
3.4,10*
20.
31.
2.1,10s
ft
1.3,10*
S.0,10*
1.0,10S
2.5.101
14.

4.5.10**
.
1.1*10

1.2II01
3.7.101
7.I.101
4.l,103
7.2*10*
1.0,10*






Mf.
t0^'
27
XI
27
27

27
21
21
T
20
20
20
27
21
n
21
25
25
25

25
25
25
25
25

20

25

30
M
30
JO
*
1






..f














f
f
f
,
f

f
f
f
f
*

*

*

f
f
t
•

t






                          -134-

-------
                               TABLE 11-41

            PROCEDURE FOR CALCULATING HYDROLYSIS RATE CONSTANT
1.  Hydrolysis Rate Constant
            ' [kn + - (kaCH+]  *
2.  Procedure

    a)  Find the hydrolysis rate parameters.   Use Table  11-40.

                        1                  liters                liters
         k  •	day, k  «	mole day,  k.  •  	mole day



    b)  Does the compound soro?    (Table 11-11,  Column  1)

        If it does, find, <* , the fraction of the total  amount of
                           *  compound which is not sorbed
          *   r
              "r   1   *pa

        If it does not sorb set
                                      Section
    c)  If the hydrolysis 1s acid catalyzed (a k   vajue  exists)
        determine the hydrogen ion cencentration;  [H  ].


          CO  - io'pH - 10' —


    d)  If the hydrolysis is base catalyzed (a k.  value  exists)
        determine the hydroxide ion concentration, [OH"].


         [OH"] -10     ^  • 10"( - " - J  • 10" -

        Note:  pKy • 14.2 for freshwater at 20aC
                   • 13.4 for seawater at 20*C

                          (More precise values for pic. >re givtn
                           in Table 11-13)

3.  Substitute  kn,  aw, ka,  [H*]. kb> [OH~] into equation  (1)  above.
                                -135-

-------
I   Comparing kH to k«:                                                                 I
,              n     t>                                                                 i

•           Ha  .  IL1  . 27.8                                                        :
I           kfi      O.S                                                                I
I   Comparison of kH with kg  for  the above situation shows that the abiotic             I
j   hydrolysis rate 1s about  28 tines faster than the blodegradatlon rate.   Blodegra-    j
j   datlon could be neglected  here with minimal effect on the results.                   j
*                                                                                      '
I	ENQ QF EXAMPL£ n_8	1
                                         -136-

-------
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                                         -141-

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                                 CHAPTER 3
                         WASTE LOADING CALCULATIONS
3.1  INTRODUCTION
     Receiving water bodies are subject to waste loads from point sources, nonpolnt
sources and atmospheric deposition.  Point sources are identifiable discrete dis-
charges from municipal, institutional Jid industrial  waste water collection and
treatment systems.  Nonpoint sources (also known as diffuse or distributed sources)
are associated with land drainage which enters a water body through dispersed and
often poorly.defined pathways.  Atmospheric waste loads are chemicals and paniculate
matter which settle from the atmosphere or are scavenged by precipitation.  These
distinctions are not absolute.  For example, municipal waste water may be applied to
the land and become nonpolnt source pollution in runoff and percolation.  Similarly,
chemicals in precipitation may become a portion of a nonpolnt source runoff load.
     This chapter describes computational methods or "loading functions" for esti-
mating waste loads to both surface waters and aquifers.  These methods share several
attributes:
        •    Required computations are relatively straightforward.
        •    Necessary data for the functions are generally available.  Much of these
             data are provided in this chapter.
        •    Notwithstanding computational ease and data availability, use of the
             functions is not trivial.  Considerable Information regarding the
             physical characteristics of the study area must often be compiled.
        •    The accuracy of loading functions Is not high.  In general, the best
             results are obtained when input parameters are based on local pollutant
             data, such as chemical concentrations in sediment, runoff and wastewater.
     The loading functions presented 1n this chapter are appropriate for water
quality screening studies in which the approximate magnitudes of waste loads are
needed.  In situations requiring higher precision, waste loads must be based on
monitoring programs and detailed process modeling.
     Tie chapter places major emphasis on nonpolnt sources.  Point source loads
can often be obtained from available water quality monitoring data.  Atmospheric
loads are also best determined by monitoring; reliable computational methods are
not available to handle such major problems as acid rain.  By contrast, monitoring of
nonpoint sources 1s often infeaslble and as a result, a number of procedures have
been developed and tested for calculation of nonpolnt source loads.

3.2  BACKGROUND  POLLUTION LOADS
     Background  water  quality "represents the chemical and biological composition
of surface waters which would result from natural causes and factors" (Novotny and
                                         -142-

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Chester*, 1981).  A comparable definition could be given for groundwater.  The
concept of background water quality or pollution is somewhat artificial.  Few, if
any, water bodies in the United States remain unaffected by human activity.  For
example, synthetic organic compounds are routinely found in streams and lakes far
from any obvious source.   In spite of this ambiguity, estimation of background
loads is a useful component of water quality planning.  These loads represent
a baseline or minimum level of water pollution wnich cannot be eliminated by local or
area-wide water quality management.
     Background pollution  levels can be measured by water quality sampling of surface
waters in upstream portions of watersheds which are free of human activity and in
aquifers in undeveloped areas.  In the absence of such local data, very crude esti-
mates can be determined from the Information given in Figures III-l, 2, and 3.  These
figures show mean surface  water concentrations of selected water quality parameters
obtained from the U.S. Geological  Survey's Hydrologic Benchmark Network (McElroy e£
al., 1976).  the concentrations are based on water quality samples from 57 monitoring
locations considered free of human disturbance.  More accurate concentration data for
nutrients are available from the U.S. National Eutrophicatlon Survey (Omernik, 1977).
Nitrogen and phosphorus concentrations 1n streamflow are grouped according to land
use and location 1n Figures III-4 and 5.  Concentrations for the "90% Forest" category
can be assumed to represent background concentrations.
     Annual mass background loads to surface waters are obtained by multiplying
concentrations by streamflow values.  Average annual streamflow values  for the United
States are shown in Figure III-6.  Obviously, when local streamflow data are available
they are preferable to the regional values given in Figure  III-6.
                         	EXAMPLE  III-l	

                           Background  Loading  Estimates
        Determine  the  annual  background  loads  of  BOO  and  total  phosphorus  from
   a  50 km2  watershed  In  northern  Illinois.
   Solution:
        From Figure  Ill-l(b), background  BOD concentration  Is  3.0  mg/1  1n  northern
   Illinois.   Total  phosphorus  concentrations  can  be  determined from  the  National
   Eutrophicatlon  Survey  data In  Figure  III-5.  Northern  Illinois  Is  1n the eastern
   area shown 1n Figure  111-5,  and  the total phosphorus concentration for  the 90
   percent Forest  category  1s 0.011 mg/1.  Average annual  streamflow  for  the area  Is
   10 in (Figure  III-6)  or  0.254  m.
                                         -143-

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(A)
 (B)
 (C)
(D)
 FIGURE  II1-1  BACKGROUND CONCENTRATION (MG/L)  OF  (A)  NITRATE-NITROGEN,  (B)  BOD,
              (C)  TOTAL  PHOSPHORUS  AND (D)  DISSOLVED  SOLIDS  (MC£LROY  EI AL,  1976)
                                       -144-

-------
         'I
      (A)
FIGURE III-2 BACKGROUND LEVELS OF (A) pH, (B) SUSPENDED SEDIMENT (MG/L>
             (C) TOTAI  COLIFORMS (MPN/100 ML) AND (U) SULFATE  (MctLKOY EJ AL, 1976)
                                         -145-

-------
   (A)
(B)
     (0
 (D)
FIGURE II1-3 BACKGROUND CONCENTRATIONS OF (A)  CHLORIDE  (MG/L),  (B)  IRON + MANAGNESE  (UG/L),
             (C)  TOTAL  HEAVY METALS (UG/L) AND (D) ARSENIC + COPPER + LEAD + ZINC (UG/L)
             (McELROY EI AL,  1976)
                                           -146-

-------
   Foreil
  £75%
  For««l
  >SO%
  Forest
  £50*
Agriculture
  >7S%
 Agriculture
   >90%
 Agriculture
4S
I*
40
                                    land Us* by Region
                                            VI.
                               Mean Tola! Nitrogen and Mean
                           Inorganic Nitrogen Stream Concentration*
                                         Del* lt»m 730 '
                                                                    wo(««iK«di
                                                             ill*
                         ) t •»•
                         1741
                                                     3005
.^•.'.•.1 I.V3I
                                                   1.t31
                                7.344
                                                                   in»i§«nic nil>af*n 
-------
     Forott
     >7S%
     Forort
     >50%
     Forott
     > 50%
   Agriculture
   Agriculture
   Agriculture
        land U«e by Region
                VI.
  M«on Total fhotpharu* and Moon
OrthopKotphoru< Stroom Concontrotjon*
                                                           Mi*
                                           Milligram* p*r Liter
FIGURE  111-5 RELATIONSHIPS  BETWEEN STREAHFLOW PHOSPHORUS CONCENTRATIONS  AND LAND USE  FROM
              THE  NATIONAL EUTROPHICATION SURVEY  (OMERNIK, 1977)
                                               -148-

-------
FIGURE 111-6 AVERAGE ANNUAL STREAMFLOH  IN  INCHES  (!IN
              (LANGBEIN EJ AL,  1949)
- 2.54CM )
                             -149-

-------
I        Noting that:
(           1 mg/1 « 0.001 fcn/<«3
I           1 *m2 . I06m2
j   annual  runoff is
I           0.254 (5
I   Background loads are
I           BOD:
I           Phosphorus:   0.011(0.001)(12.7) 106 - 140
i
'—	———	—	END OF EXAMPLE III-l
           0.254 (50) 106« 12.7 106m3.
           BOD:          3 (0.001)(12.7) 106 • 38,100 kg/yr
3.3  NONPOINT SOURCE MODE.
     The nonpolnt source loading process 1s Illustrated 1n Figure III-7.  Precipi-
tation, in the form of rain or snowmelt. comes 1n contact with a "waste" product
located on the land surface or within the soil.  Portions of the waste are trans-
ported In runoff and percolation to streams and groundwater aquifers.  Nonpolnt
source wastes are any potential pollutant which comes 1n contact with drainage.
Examples Include chemicals 1n urban dust and road Utter, agricultural fertilizers,
pesticides and animal manures, road de-1dng salts, sanitary landfill wastes, eroded
soil, mining slag piles, septic tank effluents, lawn chemicals and toxic wastes 1n
lagoons and land disposal facilities.
     Nonpolnt source pollution 1s associated with random hydrologlc events.  Combined
with the dispersed nature of drainage patterns, this randomness produces waste loads
-nich are difficult to monitor, and hence most loading estimates are obtained from
mathematical models.  The foundations of all nonpolnt source models. Including the
loading functions discussed herein, are equations to predict water movement, especi-
ally runoff and percolation.  These equations are supplemented by methods to calcu-
late sediment movement, and together the two components describe nonpolnt source
transport, since pollutants are either dissolved in a water flux or attached to
sediment.  The third model component 1s a procedure to estimate the dissolved and
solid-phase (sediment-attached) concentrations of the pollutant.  In the loading
functions, these concentrations are obtained empirically or derived from simple mass
balances.  In more analytical, and hence complex models, concentrations are obtained
from mechanistic descriptions of chemical and biological processes.
     Both average annual and single event loads can be estimated by nonpolnt source
loading functions.  The former are useful when the effects of pollution are determined
by long-term mass loads to a water body.  Groundwater quality problems are often of
this type.  Also, several simple lake eutrophlcatlon models require annual phosphorus
loads as Input.  Conversely, major storm events exert the most significant Impacts on
streams and rivers, and estimates of single event nonpolnt source loads are necessary.

                                         -150-

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                     PRECIPITATION
  GROUNDWATER
                                            GROUNDWATER
                                              DISCHARGE
                FIGURE  1 1 1-7  THE  NONPOINT SOURCE LOADING  PROCESS
     The most comprehensive estimates  of  nonpolnt source loads are obtained from
continuous simulation models such  as HSPF,  STORM, SUMH and CREAMS which have been
developed under sponsorship of  the U.S. Environmental Protection Agency, Army Corps
of Engineers and Department of  Agriculture.   Since these models require computer
facilities and extensive data structures, they  are beyond the scope of this manual.
Nevertheless, the simulation models  are based on the same computational concepts
presented In this chapter,  particularly those used for single event loading functions,
     Succeeding sections of this chapter  present loading functions for rural runoff,
Irrigation return flows, urban  runoff  and groundwater.

3.4  RURAL RUNOFF LOADS
     Nonpolnt source waste  loads to  surface waters In rural areas include runoff
from cropland (including pasturs and range), forests, barnyards and feed lots, waste
land application and storage facilities,  construction sites and mining operations.
Cropland and forest runoff  are  emphasized in this section, since these nonpolnt
sources are widespread, and their  associated loading functions have been most ex-
tensively developed.  Runoff loads from the other sources can in principle be esti-
mated by procedures similar to  the loading  functions used for cropland and forest,
but data are often lacking  to implement the calculations.

3.4.1  Source Areas
     Nonpolnt source waste  loads  in  runoff  can  be estimated for several different
spatial scales.  The most fundamental  unit  of analysis is a source area, which is a
land area wit* sufficiently homogeneous soil  and pollutant characteristics so that
                                        -151-

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runoff loads can be considered uniform.  A farmer's field Is often considered a
single source area and associated runoff loads are sometimes referred to as "edge-of-
Meld" loads.  Larger scales of analysis consist of aggregations of source areas or
watersheds.  Waste loads are transported from source areas by rivulets, ditches,
streams and other drainage paths to eventually exit the watershed 1n streamflow.
During this transit, portions of the wastes may be removed from the water flux
by settling, adsorption, filtering or biochemical  processes.  The total watershed
waste load 1n streamflow consists of these attenuated runoff sources plus waste loads
from groundwater discharge.
     Pollutants 1n runoff may be 1n dissolved and solid-phase forms, with the latter
consisting of participate material, or pollutants that are attached to sediment.  The
general loading function forms are:
                   Dissolved
                   pollutant
                   waste load
Runoff water
volume
Dissolved
pollutant
concentration
(III-D
                   Solid-phase  m  Sediment     Solid-phase pol-
                   pollutant    "  flux      x  lutant concentration
                   wasteload                    (concentration in
                                                sediment)
                                            (Hl-2)
     Sections 3,4.2. 3.4.3 and 3.4.4 describe methods for computing runoff volumes,
sediment flux and pollutant concentrations, respectively.

3.4.2  Runoff
3.4.2.1  SCS Curve Number Equation
     The U.S. Soil Conservation Service's curve number equation (CNE) 1s a standard
procedure for estimating storm runoff (Mockus, 1972; Ogrosky and Mockus, 1964).  The
equation 1s:

                       Q • (P-0.2S)2/(P+0.8S) for P _> 0.2S               (III-3)

where
        Q  •  runoff (cm)
        P  •  precipitation (rainfall * snowmelt, cm)
        S  •  water retention parameter (cm).
     The 0.2S 1s  an Initial precipitation abstraction, and hence 1f P < 0.2S,
Q  1s assumed to be zero.
     The retention parameter S 1s computed from dlmenslonless curve numbers (CN)
which  are functions of soils, cover, management and antecedent moisture:
                                         -152-

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                           S - (2540/CN) - 25.4                             (III-4)

The general form of the equation is shown 1n Figure 111-8.
     Although the CNE 1s most frequently applied to rainfall runoff, it may be used
for snowmelt conditions.  SnoMnelt water can be estimated by the degree-day equation:

                                 M » 0.45T                                   (III-5)

where
        M  »  snowmelt water (cm)
        T  »  mean air temperature (°C).
If T<0, M«0.  Also, M must not exceed the water content of the accumulated snowpack.
The degree-day factor (0.45)  1s an average value (Stewart £t a]_., 1976) and should Of
replaced by a location-specific value when available.
     Since dally weather data are used for Equations III-3 and III-5. calculated
runoff is the total runoff for a specific day.

3.4.2.2  Curve Number Selection
     Curve numbers describe the hydrologic condition of land surface at the
time of a precipitation event.  The combined effects of soils, management and cover
are shown 1n Table III-l for "average" antecedent moisture conditions.  Most soils in
the United States have been classified In one of four hydrologic groups.  Listings
are available in Mockus (1972) Ogrosky and Hockus (1964) and Soil  Conservation
Service (1975).  The qualifiers "good," "fair" or "poor" in Table III-l indicate the
extent to which cover and soil management conditions will minimize runoff.  For
example, continuous growth of a corn silage on the same site every year will deplete
soil  organic matter and encourage runoff.  Conversely, corn grain In a rotation with
hay or under no-till  conditions will minimize runoff.  Similarly, clear-cutting
of woods accompanied by extensive disturbance of the soil surface by log skidding is
a "poor" management practice.
     The "woods" category In Table III-l may be used for vegetated forest areas.
Runoff for roads, logging trails and landings should be based on curve numbers for
the "roads and right-of-way"  category.  Those curve numbers are also appropriate
for construction sites.
     The fourth, and most Important factor in curve number selection is the wetness
of the soil.  If precipitation falls on soil  that has been Inundated by previous
storms, Infiltration Is much  less and runoff Is much greater than  would be the case
for dry soil.   Three different antecedent moisture conditions are specified for the
CNE:  I (dry),  II (average),  and III (wet).  Antecedent  moisture is approximated by
the five-day antecedent precipitation, which Is the total precipitation (rain -f
                                         -153-

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 HYDROLOGY:  SOLUTION OF  RUNOFF EQUATION
                                                                PI 0 lo H incfet*
                                                                Q«0 lo 6 inch«t
                                  4       »      «      7

                                    RAINFALL  (P) IN  INCHES
, Vktoi;
   «tMl raMll
TMtelM« (toll,
                              |* Ira*  ilva
                              Mi
                                                           mm. ooM0*«tMN mva
                                                                                    IS KWI
FIGURE  I]1-8  SCS CURVE  NUMBER  RUNOFF EQUATION  din  - 2.54CM)
                                         -154-

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                              TABLE III-l

RUNOFF CURVE NUMBERS  FOR AVERAGE  ANTECEDENT MOISTURE  CONDITIONS

                            (Mockus,  1972)

Lar; ,se
or -;jver
Fl'.'.C*
Rcw crcos





Sr-a 1 1 grjin





Close-seeded
leg-res :r
ro:j; • :i
meadow


Past-re or
ran;e




Measow
woe as


Far-steads
Roads and
(hara sjr'ace,
•So-l V-.;
A

~reat.~ent Hydro ICOtC
Stra;:it row
St'iTpt row Peor
Strji;-t row Gocc
Cc^tr-red Poor
r»^»~ ra* Gc'""
Terriced Poor
'er'ace: Good
St'j'cnt row Poor
S:r>-:.-t row Good
Cc"tc-red Poor
r;r;;v,--ed GcOd
Terraced Poor
Terrjces Gooc
Strai;-t row Poor
Strjig-: row Good
Co"t:.red Poor
Cor:;jr»a Gocc
Ter'jced Poor
Ter'jceo Gooc
Poor
Fair
Good
Cort:-red Poor
Cert;. red Fair
Cor,:;, red Good
Good
Poor
Fair
Good
—
--

Oe<
Lowest Rjnoff Potential: Includes

A
77
72
67
70
65
66
62
65
63
63
61
61
59
66
53
64
55
63
51
66
49
39
47
25
6
30
45
36
25
59
74

if'sti;"
deep sanos
^rc,c=:
8
86
81
78
79
75
74
71
76
75
74
73
72
70
77
72
75
69
73
67
79
69
61
67
59
35
58
66
60
55
74
84


xi tn ve

C
?:
S3
35
a:
82
3C
73
31
33
32
a:
79
78
85
3;
83
76
ec
76
36
79
74
81
75
70
71
77
73
70
82
90


ry 1 it:le silt

0
;-
91
3?
£i
3-
82
81
88
37
Ss

s:
s:
89
85
85
S3
S3
3C
3?
3-
ec
SS
63
79
75
S3
79
77
86
92


and :'j/
            also deep, rapidly permeable loess.

            Moderately Low Runoff  Potential:  Mostly  sandy  soils  less sees '."jn  -V.  tri
            loess less ceep or less  aggregated than «.  out  tne grcus is a «r-c'^ 145  a:;v
            averagc infiltration after tnorougn wetting.
                   ely mgn Punof  Potentijl:  Cor-or^ej  shall;- soils
                   rao^e ciJy jnc col'Dus. '.noLin less  :njn  :nose sf »
            has telflw-avcrjge inf 1 1 fat:cn after oresJl.rj tion.
            H'g-e?'. Puno" foten:-ai;   Inc'.ces -ost'y  ;;a>s of 115" s^I'1'-:  ;er  cs*1
            tne 5':^o alio 'nc'.Jes  s:r» sruiiow soils  -i;n oeir!/  im^e-'-Bei^'e Sjt"r
            near ;r.c sur'jce
                                   -155-

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snowmelt) 1n the five days preceding a storm.  Approximate limits for the three
antecedent moisture conditions are given In Table III-2.  Different limits are
specified for growing and dormant season since evapotransplration dries the soil  much
more rapidly during the growing season.  In absence of more specific Information, the
growing season may be assumed to consist of months for which average air temperature
1s 10*C or above.  Antecedent precipitation Is an Inadequate criterion during snowjnelt,
however, and for such events condition III 1s always assumed (Ha1th and Tubbs,
1981).
     The curve numbers for condition II, or CN2 are given In Table III-l.  The curve
numbers for the other two conditions, I and III respectively, can be obtained from
the equations given by Hawkins (1978):

                          CN1 • CH2/(2.334-0.01334CN2)                       (III-6)

                         CM3 - CN2/(0.4036 + 0.0059CH2)                      (IH-7)
                                     TABLE 111-2

               ANTECEDENT MOISTURE LIMITS FOR CURVE NUMBER SELECTION
                             (Ogrosky and Mockus, 1964)
                                                  5-Day Antecedent
                    Antecedent                     Precipitation
                Moisture Condition              	(cm)	
                                                Dormant     Growing
                                                Season*     Season

                        I                        <1.3        <3.6
                        II                      1.3-2.8     3.6-5.3
                        III                      >2.8        >5.3
                * During snowmelt, condition III 1s always assumed
                 regardless of antecedent precipitation.
                                         -156-

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                                EXAMPLE  111-2	•	—

                              Cropland  Runoff

     A three-day rainstorm falls on a 30-ha soybean field during early August.
The crop is continuously grown  (no rotation) In straight  rows.  The soil  1s in
hydrologic group B.  Pie relevant prec'oitation 1s as follows:
        Date       August 123456789
        Rain (cm)      0        0    0    0    0   3.8   5.1   0.3    0
Determine the runoff from this  stonm.
Solution:
     The crop 1s a row crop planted 1n  straight rows and  In  poor hydrologic
condition.  From Table III-l, the curve number for condition 2 Is  CN2 • 81 for
soil group B.  Solving Equations III-6  and III-7 for CN1 and CN3,  we have
CN1 - 64.6 and CN3 - 91.9.
     The three-day storm begins on August 6.  On that day, 5-day antecedent
precipitation 1s 0; hence the soil  Is In the driest antecedent moisture condition.

Thus:
        CN • CHI - 64.6
and from Equation 111-4:
        S » (2540/64.6) - 25.4
          - 13.9 cm.
Since precipitation exceeds  initial  abstraction, 0.2S « 2.78 cm,  runoff occurs as
predicted by Equation III-3:
        Q - (3.8-2.78)2/(3.8 + 0.8(13.9))
          « 0.07 cm.
     On August 7, 5-day antecedent  precipitation is  3.8 cm,  which  during the
growing season corresponds to CN -  CN2 - 81 (Table 111-2).  Thus:
        S • (2540/81) - 25.4
          » 5.96 cm.
Rain exceeds 0.2S • 1.19  cm,  and
        Q - (5.1 - 1.19)2/(5.1 + 0.8(5.96))
          - 1.55 cm.
     On the final  day,  5-day  antecedent  precipitation 1s 3.8 + 5.1  •  8.9 cm,
CN • CN3 • 91.9 and S - 2.24 cm.  Since the 0.3 cm of rain dots not exceed
the Initial abstraction of 0.2 (2.24)  «  0.45 cm, no  runoff occurs.
                                      -157-

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I        The storm summary  1s  as  follows:
I
Day
8/6
8/7
8/6
Total
Rainfall
(cm)
3.8
5.1
0.3
9.2
Runoff
(cm)
0.07
1.55
0 	
1.62
        The 1.62 cm of runoff over the 30-ha field can  be  converted  to  runoff
            3                                2                                          I
   volume (m )  by noting  that 1  ha •  10,000 • ,  and hence  1  cm  on  1  ha  •  0.01
   (10,000)  • 100 m3.   This  runoff volume Is 1.62(30){100) • 4660  m3.                   (
        This example Illustrates three Important characteristics of  runoff:             |
           e    Runoff 1s a  nonlinear function of precipitation; I.e.,  runoff  1s  not    I
                a constant portion of precipitation.                                   |
           •    Runoff 1s generally a small  fraction of precipitation,  particularly     j
                during the growing season.                                              '
           •    Runoff 1s dramatically dependent on antecedent  moisture conditions.
I	END OP EXAMPLE III-2
 3.4.2.3  Annual Runoff
      The CNE 1s only applicable to  Individual storm events, and this  1s a limitation
 in nonpoint source studies for which annual taste  loads are required.   In such cases
 annual runoff estimates are necessary.   The only My to produce such  estimates 1s to
 use Equation 111.3 to calculate runoff for each storm 1n a year, and  sum the
 resulting values for the year.  If  an average annual runoff Is needed, the process
 must  be repeated for each of a number of years.  The repeated use of  Equation 111.3
 for all storms  1n a multi-year period 1s not difficult (see for example Ha1th and
 Tubbs, 1981), but 1t 1s a continuous simulation modeling process that can only
 be Implemented  on a computer.
      Average annual runoff for row  crops has been  calculated by Stewart jet ^K (1976)
 for the eastern united States.  A simulation model based on the CNE was run using
 10-25 years of  dally weather data from 52 locations.  The simulation  runs were based
 on straight row com 1n good hydrologlc condition  on the four different soil groups.
 Fallow or bare  soil conditions were assumed during the spring.  Results of the
 simulations are shown 1n Figure III-9.   The four soil groups correspond to CM2 • 67,
 78, 85 and 89.  These runoff values should generally be appropriate for any row
 crop. Runoff for situations with curve numbers falling between any two curve numbers
 can be determined by linear Interpolation.
                                         -158-

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(A)
 (B)
(C)
(D)
     FIGURE  111-9 MEAN ANNUAL Row CROP RUNOFF IN INCHES
                  FOR SELECTED CURVE NUMBERS, A;  CN2-67,
                  B:   CN2-78; C:   CN2-85;  D:   CN2-89, (1 IN
                  - 2.54CM) (STEWART    A, 1976)
                              -159-

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3.4.2.4  Watershed Runoff
     Runoff from a source area such as a farmer's field or logging road 1s given by
Equation I[1-3.  Runoff from an entire watershed 1s the sum of runoff from all
source areas within the watershed.  If we define:
        (L  •  runoff from source area k (cm)
        AK  »  area of source area k (ha)
        AT  -  total watershed area (ha)
        a^  »  fraction of watershed covered by source area k • A^/AT
then watershed runoff Q(cm) 1s:

                                     0 • Z \ Qk                              (III-8)


Watershed runoff volume V(nr) 1s:

                            V - 100 Z \ Qk

                              - 100 ATZ a.  QL                                (IH-9)
                                       k  *

     Equation 111-8 or 111-9 require computation of runoff Qfc from each
source area.  An alternative and simpler procedure 1s to determine a weighted average
curve number:

                             CN - z \ CN.                                     (111-10)
                                  k  *   K

and compute watershed runoff directly from Equations 111-3 and 111-4.  In Equation
111-10 CN.  1s the curve number for source area k.
     The second procedure (average curve number) generally produces slightly  lower
watershed runoff estimates than Equation 111-8 due to the nonlinear nature of the
CNE.  In any case, note that watershed runoff 1s only one component of streamflow.
Additional  components Include groundwater discharge and point sources.

3.4.3  Erosion and Sediment
     Erosion 1s the rwoval of soil particles by wind and water, and sediment Is the
partlculate matter which 1s carried and eventually deposited by wind and water.  Our
concern here 1s with water pollution, and the prediction of sediment loads or yields
1n streamflow.  Upstream erosion of soil surfaces and stream channels 1s the  source
of streamflow sediment yields.  However, watershed sediment yield, as measured 1n
streamflow at the outlet of the watershed, 1s generally substantially less than the
                                         -160-

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total upstream erosion since much of the transported sediment has been deposited
or filtered from the water.  Near a sediment source, nearly all eroded soil becomes a
sediment mass flux.  For example the sediment yield 1n runoff from a corn field is
approximately equal to the eroded soil mass from the field.  However, as the runoff
travels from the field In drainage ditches and stream channels, portions of the
sediment are removed, until only a fraction remains to exit the watershed.
     Erosion of the land surface by sheet and rill erosion is the major source of
solid-phase pollutants In surface waters, and most of this section is accordingly
devoted to prediction of this sediment source.  Although channel erosion may also be
a significant component of sediment yield, 1t Is not generally considered a pollution
hazard and will not be considered In the following discussion.
3.4.3.1  The Universal  Soil Loss Equation
     The Universal Soil Loss Equation (USLE) 1s an empirical  equation which was
developed to predict average annual  soil  loss by sheet and rill erosion from source
areas (Wischmeier and Smith, 1978).  The equation, which was obtained by statistical
analyses of over 10,000 plot-years of erosion field research data Is:

                            X - 1.29 E(K)(ls)C(P)                            (III-ll)

where
         X  •  soil loss (t/ha; 1 t « 1 tonne - 1000 kg - 2205 1b)
         E  •  rainfall/runoff eroslvlty Index (10  m-tonne-cm/ha-hr)
         K  »  soil credibility (t/ha per unit of E)
        Is  «  topographic factor
         C  -  cover/management factor
         P  >  supporting practice factor.
The three factors Is, C. P are dimensionless.  The 1.29 1s a conversion constant to
obtain metric units.
     The USLE Is an Important component of loading functions for runoff waste loads
because Its parameters have been evaluated for a wide range of conditions and many
Important pollutants are transported on eroded soil.  For example, most organochloHne
pesticides are very strongly adsorbed to soil  particles.  Procedures for determining
the USLE parameters are presented In the following subsections.

3.4.3.1.1  Rainfall/Runoff Eroslvlty
     The eroslvlty term E 1s related to rainfall intensity.  Average annual values
for the united States have been computed  by U1schme1er and Smith (1978) and are given
in Figures 111-10 and 11.  The values of E 1n these figures are In English units
(102 ft-tons-1n/ac-hr)  and can be converted to the metric units of Equation
III-ll by multiplying by 1.735; I.e. E (metric)  - 1.735 E (English, Figures 111-10,

                                         -161-

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FIGURE 111-10 AVERAGE ANNUAL EROSIVITY  INDICES  (ENGLISH  UNITS)
              FOR EASTERN U.S. (WISCHMEIER AND  SMITH, 1978)
                            -16?-

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                    W.H. WischiMicr. SEA. 1976
FIGURE  Ill-ll  AVERAGE ANNUAL EROSIVITY  INDICES (ENGLISH UNITS)
               FOR WESTERN U,S,  (WISCHMEIER AND SMITH,  1978)
                               -163-

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11).  For example the erosivlty for northern Maine Is  E  »  1.735 (75)  «  130.
     It can be seen from Figure 111-10 that  the intense  rainstorms  of the Southeast
produce the M -*>est levels of erosivity in the United  States.   In  contrast,  erosivity
in much of the western mountain region (Figure 111-11)  is  less  than 10  percent  of  the
southeast values.
3.4.3.1.2  Soil  Erodlblllty
     Typical  values of K are given in Table III-3 as a function of soil texture and
organic matter content,  values for specific soils are available from local  Soil  and
Hater Conservation Districts and state offices of the Soil  Conservation Service.

3.4.3.1.3  Topographic Factor
     The topographic factor Is, 1s related to the angle of slope o and  slope length  x
(m) by:

                Is - (0.045x)b (65.41 sin2« * 4.56 sin 9 + 0.065)             (111-12)

The slope angle 8 is obtained from percent slope, s by:

                              9 « tan'l(s/100)                               UII-13)
                                                                                   in
For example, a slope of s • 8 percent has a slope angle of 6  • 4.6°.  The exponent
Equation 111-12 1s given by b - 0.5 for s > 5, b - 0.4 for 3.5 <_ s <_ 4.5, b « 0.3
for 1 <_ s <_ 3, and b « 0.2 for s £ 1 (Wischmeier and Smith,  1978).
     Research data support Equation 111-12 for x <_ 100 m and  s <_ 18. although In
practice H is often applied beyond these limits.

3.4.3.1.4  Cover/Management Factor
     The covtr/managment factor C describes the protection  of the soil  surface by
plant canopy, crop residues, mulches, etc.  The maximum C value 1s 1.0,  corresponding
to no protection.  Cropland C values change dramatically during the year 1n response
to planting operation*, "jp growth and harvest.  Although C values have been de-
termined for each of these stages (H1schme1er and Smith, 1978). generalized annual
values such as those given 1n Table 111-4 are more suitable  for loading  functions.
     Hischmeler and Smith (1978) have also developed C factors for construction
sites; pasture, range and idle land; undisturbed forests; and mechanically prepared
woodland sites.  These C values are given in Tables 111-5 through III-8.  Note that
cover factors are so small for undisturbed forest and pasture or range with good
ground cover that these erosion sources can generally be neglected 1n water quality
studies.
                                         -164-

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     TABLE 111-3





 SOIL ERODIBILITY,  K



(Stewart et al,  1975)
Texture
Sand
Fine sand
Very fine sand
Loamy sand
Loamy fine sand
Loamy very fine sand
Sandy loam
Fine sandy loam
Very fine sandy loam
Loam
S11t loam
Silt
Sandy clay loam
C1 ay 1 oam
Sllty clay loam
Sandy clay
Sllty clay
Clay

0.5X
0.05
0.16
0.42
0.12
0.24
0.44
0.27
0.35
0.47
0.38
0.48
0.60
0.27
0.28
0.37
0.14
0.25

Organic Matter
2%
0.03
0.14
0.36
0.10
0.20
0.38
0.24
0.30
0.41
0.34
0.42
0.52
0.25
0.25
0.32
0.13
0.23
0.13-0.29

4%
0.02
0.14
0.28
0.08
0.16
0.30
0.19
0.24
0.33
0.29
0.33
0.42
0.21
0.21
0.26
0.12
0.19

        -165-

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                            TABLE 111-4

    GENERALIZED VALUES OF THE COVER AND MANAGEMENT FACTOR, C,
IN THE  37 STATES EAST OF  THE ROCKY MOUNTAINS (Stewart et al , 1975)

nt Qup. rotation, and rruru|emenl ^
no

Bate viluv tominuout faltow, (illcd up and down slope
CORN
1 C. RdR. fall TP. conv (I)
2 C. RdR. ipruif TP. conv ( 1 1
3 C. RdL fall TP. conv ill
4 C. RdR. »i iecdm(. tprinf TP. conv ( 1 1
5 C. Rd L. tundmf . tpnnf TP. conv ( 1 1
6 C. fall trued ttalkt. iprutf TP. com ( 1 )
7 Cltitojc >•» < Rd L. fall TP> 1 2 )
8 C. RdL fall <.h«cl spnn* disk. 40- JOT re 1 1 )
9 Cltibpel. * »x teeding. no-till pi in t-k * III
MI ClRJL>-»(RdL spring TPn2)
1 1 C. (all th/ed -k vkhcat. 9O-70 . r,. il)
21 C-CC W-M-M. no-nil |«I 2d A .ird C(6(
22 C^-M. RdL TPfor C. duk lor » (3)
23 CO* M-M. RdL no-till pi 2d C(5)
24 C-* MM KdL. TPfor C. di»k for Vk 14)
25 l-»-M-M-M. RdL TPfor C. duk tor W(5)
26 C. no-nil pi 01 ^-k vxt. 95-80-4 rt (I )
COTTON4
27 Col. ionv (Vhrtlvrn PUiruM 1 i
28 Col. conv (SoulhHI)
MbALMDW
29 Crau A Lcfumr mix
30 Alfalfa leipodcu or Set leu
3 1 Swvci c luver
SORGHUM. ORAIN (WcMctn PUinv/
32 RdL *pr«f TP. ionv (I)
33 No-ti)l pi m threaded 70-5Ovb rr
Prod urn
H,fl,
C
1 00

0 54
50
42
40
38
35
31
24
20
2U
19
17
16
14
12
1 1
087
076
IfeS
062
061
055
051
U39
032
017

0.42
34

0 INM
02(1
025

043
1 1
ivn> level
Mod
value
IU..

062
$v
52
49
48
44
35
3d
24
2S
>
23
24
2'J
1 '
1 X
14
13
II
14
1 1
095
094
1)74
U6I
05 ^

0 49
40

001



0 53
IK
                               -166-

-------
                                         TABLE   111-4 (Continued)
                                                                                               ProduLIivid level
                                Crop, rotation, and management "
 no                                                                                           High           MoO

4


SOYBt*-NS
34
35
36
3*
VUlbAT
38
39
40
41
4:
43
44
45
46
4"
48
49
B. RdL spring TP. ion* 1 1 )
C-B. TP annuall> . conv I 2(
B. no-iiU pi
C-«. no-till pi. fall silted C sulks 1 2)

W-l . f»ll TP-iller V* (2)
W-l . stubble mukh. 500 Ihs u C)
U-h. nubble mulch. 1000lb»rc Ol
Sptin| U RdL. Sepl TP. .onv ils A S DakHl)
Winter *. RdL. Auf TP. coin (kjnM ( 1 )
Spring U . >iubbk mulch. 750 Ibs re 1 1 )
Spring v..  and is noi t complete list of cropping systemt CK potential practice*. Values of C differ
tilth  tjinfill pattern tnd pbniuif dates. These {cneralized values show approximately the relative crouon-redutBif efftcliveneo of
various crop systems, but locanorutly derived C vaJues should be uMd for conKrvation pianninf at the field level. Tables of local
•ilucs axe available from the Soil Conservation Service
   ' Hjfh level it exemplified by k>n|-icrm yield averages pealer than ?S bu. corn or 3 tons frasv^nd-kfume hay.oi col ton manafe-
meni that regularly  provide^ .orn                                                M  • grass A legume hay
c-k  • chemiully lulled                                     pi  - ptanl
conv - conventiorul                                         W  -wheat
col  -cotton                                              we - winter cover
Ibs re     • pounds of crop residue per acre renaming on surface after MW crop seeding
% re       • percentage of soil surface covered by residue mukh 
-------
                    TABLE  111-5

    C FACTOR VALUES FOR  CONSTRUCTION SITES
          (W1sctme1er and Smith,  1978)1
is,"

Nan*
Straw or Way,
ti*d dawn by
ancharing and
tacking
•a>pm«nt3
Oa.






CrwiHad it***.
U ta m in


Oa.


Wood chip*

Da.


Oa.



Mulch
r*«f p*r acr*
0
1.0
1.0

1.3
1 J
2.0
2.0
2.0
2.0
2.0
2.0
2.0
135
135
135
135
240
240
240
7
7
12
12
12
25
25
25
25
land
SI***
'•«•<»
all
1-5
6-10

1-3
6-10
1-5
6-10
11-15
16-20
21-25
26-33
34-50
<16
16-20
21-33
34-50
<21
21-33
34-30
<16
16-20
<16
16-20
21-33
<16
16-20
21-33
34-50
Factor
C

1.0
0.20
.20

.12
.12
.06
.06
07
.11
.14
.17
.20
.05
.05
.05
.05
.02
.02
.02
.M
.0*
.05
.05
.05
.02
.02
.02
.02
limit2
*••«
—
200
100

300
130
400
200
150
100
73
30
35
200
150
100
75
300
200
150
75
50
150
100
75
200
150
100
75
     fr*«a  •*
                           Oi»»Up»d ky an ialaragancy work*
apaliiatUn rota or
               Ida ipoaftodi
Wfcon thfc  Co* u  ascoorfod.
          ilurttning  a*  HM
                         •wlcfc  b M« a«cnar*d ta  KM Mil,  C
                         i!o*o* of laih n«»4ng ^ «•!««
    040 iht»ld ba takan al d*i»al« tfca wWvo* gi«M in tfci*
                        -168-

-------
                               TABLE  111-6

C  FACTOR VALUES FOR  PERMANENT  PASTURE.  RANGE AND  IDLE  LAND
                   (W1schme1er and  Smith,  1978)1
V«geletive coneoy
Tyi»e e,«d t»n* -•
height' e,». .
No appreciable
canopy
Toll weeds or 25
short brush
with overage
drop foil height 50
•f 20 in
75

Apprecioble brwth 25
or bushes, with
overage drop foil
height of 6tt ft 50

Cover tnot centocfs
Percent
Type*
C
W
C
W

C
W
G
W
C
W

C
W
0
0.45
.45
.36
.34

.24
M
.17
.17
.40
.40

44
.34
30
0.20
.24
.17
.20

.13
.16
.10
.12
.It
M

.16
.19
40
0.10
.15
.09
.13

.07
.11
.04
.09
.09
.14

.01
.13
Ik* toil lurfoCC
oreund
40
0.042
.091
.031
.013

.035
.076
.032
.061
.040
.M7

.031
.012
cover
M
0.013
.043
.013
.041

.012
.039
.011
.031
.013
.042

.012
.041

95+
0.003
.011
.003
.011

.003
.011
.003
.011
.003
.011

.003
.011
                         75    C     .21   .14  .M  .036  .012  .003
                               W     .21   .17  .17  .071  .040  .011

     Trees,  but  no       25    G     .42   .19  .10  .041  .013  .003
        opprvtiobl* low         W     .42   .23  .14  .019  .042  .011
        bruih. Average
        drop fall height   50    G     .39   .11  .09  .040  .013  .003
        •f  13 It                W     .39   .21  .14  .017  .042  .011

                         75    C     J*   .17  .09  .039  .012  .003
                               W     Jo   JO  .13  .M4  .041  .011
        ' Til* thtod C *«lvet •UU*M thof the vegetation and mvkch  ore
     randomly  dntribwtod  over  the  entire  ore*.
       ' Canopy height it mooMtrad  a*  the overoge  loll height  of water
     drop* fading froM the canopy  to  the grovnd.  Canopy effect ii in-
     versely  proportional  lo drop foil  height  and  U negligible  If  foil
     height eiceedi 33 ft.
       ^Portion  of total-area tvrfoce that would be hidden  front view by
     canopy  in a  vortical projection (a bird't-eye view).
       *G: cover  at  lurfoce  h grott.  graulike  plants,  decoying coav
            poctod dwff.  or  litter at  toast 2  in deep.
        W:  cover  at  surface is  mottly  broadleof herbaceous plants  (a*
           weeds with little  lateroUoel  network near the surface) or
           undecayed residues or  bath.
                                    -169-

-------
                                      TABLE  111-7

                      C FACTOR  VALUES FOR UNDISTURBED FOREST  LAND
                             (Wischmeler and Smith,  1978)
Percent of Area
Covered by Canopy
of Trees and
Undergrowth
100-75
70-45
40-20
Percent of Area
Covered by
Duff (litter) at
least 5 on deep
100-90
85-75
70-40
Factor
C
0.0001-0.001
0.002-0.004
0.003-0.009
3.4.3.1.5  Supporting Practice Factor
     The supporting practice factor P measures the effect of traditional soil  conser-
vation practices on cropland erosion.  Values of the P factor are given 1n Table
II1-9.  Note that two different types of practice factors apply to terracing.   For
example, for a doucle terrace (n-2) on a 6 percent slope, P • 0.5/Y7- 0.35.   The
value Indicates the amount of erosion from the soil  surface.  However, approximately
80 percent of the eroded soil 1s trapped 1n the terraces  channel  and does not  leave
the source area.  Hence, for purposes of estimating nonpolnt source loads, the
practice factor Is 0.2(0.35) • 0.07.

3.4.3.2  Single Event Erosion Estimates
     Although the USLE was developed for average annual erosion estimates, nonpolnt
source studies often require waste loads for specific storm events.  When this 1s the
case, the eroslvlty term E 1n Equation 111-11 must be determined for the storms 1n
question.  Three different methods may be used to obtain these eros1v1t1es.
        Method l;  Direct computation from rainfall Intensities.
     The most analytical approach Involves the use of rainfall Intensity data  di-
rectly to compute storm kinetic energy and maximum Intensities.  This procedure, as
described In Wischmeler and Smith (1978) Is generally too cumbersome for screening
studies.
        Method 2:  Design storms.
     Wischmeler and Smith (1978) have analyzed rainfall data throughout the United
States to determine frequencies of E values.  The results are given 1n Table 111-10.
and may be used to determine the soil erosion associated with storms of various
                                         -170-

-------
                             TABLE  111-8

C  FACTOR VALUES FOR MECHANICALLY PREPARED WOODLAND SlUS
                  (H1scl»e1er and Smith,  1978)
Site
Diihod, roVed.
or bedded4




lur«ed* 	




Mulch
cover'
No««
10
20
40
60
•0
Mo.e
10
20
40
60
10
Oruia (hopped' None





10
20
40
60
10

loit
f«celtent
NC WC
053
.33
.34
.17
.11
.05
.35
.31
.If
.14
.Ot
.04
.16
.15
.12
.Of
.06
.03
0.30
.15
.13
.11
.01
.04
.10
.10
.10
.Of
.06
.04
.07
.07
.04
.06
.05
.03
tancUMo*? and weed «e»«>3
Good
NC
0.72
.46
.34
.33
.15
.07
.36
.34
.If
.14
.Of
.05
.17
.16
.12
.Of
.06
.03
WC
0.27
.20
.17
.14
.11
.06
.10
.10
.10
.Of
.07
.04
.07
.07
.06
.06
.05
.03
Fair *oor
NC
0.15
.54
.40
.27
.11
.Of
.31
.36
.21
.15
.10
.05
.20
.17
.14
.10
.07
.03
WC
0.32
.24
.20
.17
.14
01
.12
.11
.11
.Of
.01
.04
.Of
.01
.07
.06
.05
.03
NC
O.f4
60
.44
.10
.30
.10
.45
.36
.27
.17
.11
.06
.2f
.23
.11
.11
.07
.04
WC
0.36
.36
.22
.If
.15
.Of
.17
.16
.14
.11
.0*
.05
.11
.10
.Of
.07
.05
.04
                                       * Porconlogo  ol turtmtf covered by  roilduo U co«locl  wild  the,
                                     loll.
                                       * f*t»ttxt  toN condJllo* — Highly liable  toll oggiogoUi U lop-
                                     i*ll with («•»«  lr»o rood and IllUf mliod U.
                                         Good — Moderately ttobU  toll ao,gregolei U lop toil or highly
                                     trable ugycegatei (» tubieJI (laptofl removed during roVUgt, oftly
                                     lf«ei of Illler mliod U.
                                         fair — HtftMy umlobU toll  *ggr*gotet U toptoil or nodoiateiy
                                     liable oggrogoloi IN iub«olt, no lilUr mlicd1 U.
                                         foor — No (optod,  blgMy •rodlbU toll  ofgrogatti l» >vb«o'l, *•
                                     Illltf Mliitd U.
                                        3
                                         NC— No li*
                                         WC — 75 p*«*nt  cover of gran  and wetdi having  on ovcrogo
                                                   drop loll VotgM of 3D In.  for lnt*rm*dlol* p«ri**l-
                                                   ag*i of tovor, lAUrpolali b*lw«t« <«lum«i.
                                        4 Modify  lti» tiiltd C  valwoi 01 tollowi  lo  account for •••cli or
                                      iwrloct rowgko«>» and oglngi
                                        Hut year ofur  1r*olM*nli mwillply Ililtd C  volv«i  by 0.40  lor
                                          rough  lurfoco (d*pr*iiioni  >o l»(i  by 0.4] for Mod*rol*ly
                                          rough/ ood by O.K>  IW tmoorh (d*pr*i>io»>  < J In).
                                        for | |o 4  yoori  ofl»r lr«atm*nli Multiply H«Ud  (acton by 0.7.
                                        for 4-f-  !• I y*«rii MO l«alo 6.
                                        More Itian I y««fli uio lobU 7.
                                         for foil ]  ycorti  ut«  C volu«i •« lliUd.
                                         f«r 1-f to I yoan alter  Irealmenli u>« labl*  o.
                                         More ifco*  I y*ori after treotmenli UM l«blo 7.
                               -171-

-------
                                               TABLE 111-9

                    PRACTICE  FACTORS (P)  USED  IN UNIVERSAL  SOIL  LOSS EQUATION

                                         {Stewart  et «]_,  1975)
              Practice
                                                             L»nd ilop« (percent)
                                      1.1-2
  2.1-7
                                                                  7.1-12
                                                                               12.1-18
                                                                 (Factor P)
                                            K.I-24
Con louring (Pc>

Contout stria cropping (P^l
   R.R-M-M1
   R.W-M-M
   R-R-W-M
   R-W
   R-O

Contout listing or ridge planting
(Pel)

Contour terracing (P,)

No support practice
                                     0.60
                                     0.30
                                     0.30
                                     0.45
                                     0.32
                                     0.60
0.30
0.23
0.23
0.38
044
0.30
 0.30          0.25

30.6/>/T        0.5/VrT

 1.0           1.0
0.60
0.30
0.30
0.45
0.32
0.60
0.30

0.6/>/T

1.0
                                            0.80
                                            0.40
                                            0.40
                                            0.60
                                            0.70
                                            0.80
                             0.40

                             0

                             1.0
0.90
0.45
0.45
0.68
0.90
0.90
                                                                                              045
                                                                                               1.0
   I R • rowcrop, w • fall-seeded gram. O • spring-seeded grain. M * meadow. The crops are grown in rotation and co arranged on
the field thai towcrop strips are always separated by a meadow or winter-grain strip.
    Thrsc P| values estini»te the. amount of soil eroded to the terrace rnannels and are used for conservation planning. For prediction
   iff. f i*l*4 «j»r4 •••«••* I thai 9. IM lit«* •*•» fmut* it*t u**J Kw ft ^
  ie field thai towcrop uript are always separated by a meadow or wmirr-jram strip.
  2 Thrse Pt values estim»ie the amount of soil eroded to the terrace rnannels and are i
of off-field sediment, the P( values are multiplied by 0.2.
   3n • number of approaimitdy equaJ-length intervals into which (he field slope is divided by the terraces. Tillage operations must
be parallel to the terraces.
  return periods.   Note  that  the English  units  E values given 1n  Table  111-10 must  be
  multiplied  by 1.735 to obtain the  metric E used 1n  Equation III-ll.
           Method  3;   Eros1v1t1es from dally rainfall  data.
        Richardson  et aU (1983) developed  a regression equation for eroslvlty based on
  dally rainfall data.   Converting their  results to the units of  E 1n Equation III-ll,
  the  expected values of E for a dally rainfall  R (cm) Is:
                                          E •  6.46a  R
                                                       1.81
                                                                                            (III-U)
  The  coefficient  "a" varies  with location and  season.   R1 chardson «rt £l_. (1983)
  determined  cool  season  (October-March)  and warm season (April.September) coefficients
  for  the locations shown fn  Figure  111-12.
                                                  -172-

-------
                                                   TABLE  111-10


              EXPECTED MAGNITUDES Of SINGLE-STORM  EROSIVITY INDICES  (ENGLISH UNITS)

                                        (Wiscltneier  and  Smith.  1978}

                                                10
                                                                                                                10

  t»4
       H««*«
       •<
II»MW,
  MICK
 T»m
 O«
                           f7
                           49

                           49
                           41
                           99
                           II
                           11

                           a
                           17
                           II

                           73
                           II
                           17
94
41
fl
n
0
if
77
14

74
14
If
14
49

17
91
U
II
49
11
                                  in
 U
 4f
 44
 n

 11
 11

 14
 II
 II

 13
 47
 17

t!4
m
114

 a
 to
 ti
 n
in
 7t

 49
 4f
 14
 10
 If
 O

 10
 99

 41
 V

 44
 47
 40
 41
 49
 4f
              110    140
              111    in
              111    141

              101    199
              til    1*
               M     17
              101    197

               14     4*
               a     M

               u     tr
               40     M
               U    113

               JO     44
               73    »4
               U    >0»

              100    04
              144    301
              TOO    U3
 fl
 74
1M

709
 ft

101
 77
 tl
 If
 14
 71

 M
 41

 41
 7t

 41
 41
 44
 47
 fl
 74
 Ul
 14
 191
 in
 777
 190

 191
 101
 101
 114
 4f
 »4

 71
 14
 71
 M
 77
 II
 Tf
 14
114
101
ltd
               170
               1f4
               177

               147
               711
               101
               149

               41
               94

               111
               177
               193

               7*
               173
 777
 794
 901

 114
 lit
 119
 144
 9JI
 147

 in
 17f
 130
 141
 17
 117
 U
 M
III
111

 11
109

101
140
tTf
lit
                                                                  C«tf 4>rvllU

                                             37
                                             47
                                             39
                                             II
                                             14
                                             U
                                             41

                                             n
                                             11
                  Mabwi
                   C«rfb«M
                                             II
                                             4f
                                             fl
                                             47
                                             17
                                             JI
                                             It
                                                                                                  49
                                                                                                  It
101
 U
 74
 O
 74
 n
 O
171
1U

 47
 f7
111

114
 77
 49
                                                                                      100
                                                                                      I5»
                                                                                      114
tit
tie

tit
 u
                                                                Ml
                                                                  OwkH*
                                                                  FMWCM
                                                                 (•*••• Or .
104
11
14
U
It
41
17
If
U
11
If
14
11
17
U
4t
14
4*
tt
9
a
M
11
43
ir
41
4
7
„
34
14
11
10
It
If
n
M
77
77
If
77
01
11
11
11
It
u
14
U
JI
"
fl
(4
"
M
49
u
U
11
47
1
11
14
11
37
M
O
It
714
Tf
7t
4(
40
U
43
41
n
4J
94
14
13
jf
JI
tl
40
171
U
111
77
41
If
fl
70
14
14
11
14
74
14
If
74
4J
770
171
14
44
St
lOf
17
41
41
14
43
M
n
ji
41
101
»0
111
toj
114
n
7f
117
111
17
104
N
*•
41
n
47
7t
P4
41
330
141
44
M
tl
199
n
»
to
41
It
49
n
41
n
ITT
109
174
170
141
107
n
in
140
\V)
114
14
M
fl
111
n
ff
114
77
                                                         -173-

-------
                                               TABLE  111-10  (Continued)
                                                                                                                           >•
                                                                                                                                  20
h«>*MI
l«

»»
i*
2*
I*

II
14
U
U
13
IJ
 n
 it
 37
 13
 »f
 30
 U

 37
 33
 30
 37
 27
 31
 U

 44
 44
 47
 14
 47
17
I*
30
23
30
23
        27

        44
  4
 21
                                     14
                                     }4
                                    a
                                    31
 u
 Jl
 77
 17

 37
 II
 14
U
U
40
4S
30
M
70
O
4*
34
U
3f
33
3f
33
  n
  u
  T*

  II
  It

  30
  34
  34
  It
  M
  33
  3i
too
 74
110
13*
 VI
 U

 40
 O
 U
 M
 77
 44
 43

l«7
 00
MJ
O7
MO

 13

 U
 M
 U
 4J
 U
              Ul

               43
 f7
MI
                        14
                        44

                        47
                        47
                        *
                        4»
                        u
                        «
                        Jt

                        72
                      131
                       »3
                      137
                      147
                       77
                       S3

                       J»
                       71
                       41
                       77
                      100
                       a
                       9

                      Ul
                       n
                      134
                       U

                       4J
                       a
                       •»
                               117
                               134
                               131

                               II
14
JO
41
43
                               4J

                               17
                              144
                              10
                              !«•
                              3O*
                              103
                               41
                               »4
                              143
                               70
                               74

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                              1U
                              M3
                              30»
                              114

                               10

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                               Jl
                               tl
                               47
                               II
                               43

                             114
                                                                              c*r
CMMi
                    1*
                    it
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                    3*

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                                              104
                                               n
                                               at
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                                               so
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                                                »
                                              nr
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                                              103
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                                                                                                          3J      «•
                                                                               t44
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                                                                       us
                                                                       104
                                                                       n
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                                                                       a
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                                                                       n
                                                                                                                                  240
                                                                                                                                  its
                                                                                                                                  in
                                                                                                                                  is

                                                                                                                                   n
                                                                                                                                   41
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                                                                                                                                  11'
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                                                                               70
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                                                                      14*
                                                                      Ju
                                                                      144
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                                                                       I*
                                                                      as
                                                                       77
                                                                       4*
                                                                      144
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                                                                      141
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                                                                       U
                                                                      1O3
                                                                       41

                                                                        I

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                                                                                                                                  »!•
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                                                                                                                                  ur
                                                                                                                                  Itt
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                                                                                                                                  t»4
                                                                                                                                  1*3
                                                                                                                                  204
                                                                                                                                  I«
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                                                                                                                                  tJ
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                                                                                                                                  14
                                                                                                                                  14
                                                             -174-

-------
            COOL  SEASON (OCT.-MAR.)
           WARM  SEASON  (APR,-SEPT,)
FIGURE 111-12 VALUES OF "A" FOR EQUATION  11
              (RICHARDSON £j_ AL, 1983)
                      -175-

-------
     When cropland erosion estimates are made for single storm events, the cover/
management factor should 1n principle be selected for the crop stage corresponding to
the time of year 1n which the storm occurs.  The procedures for estimating seasonal
C values as described 1n Wlschmeler and Smith (1978) require crop development In-
formation which 1s usually not available 1n screening studies, and hence the annual C
values given  In Table III-4 are often used for single event estimates.

r	EXAMPLE  III-3	1
I                                                                                       I
j                            Soil  Erosion Computations                                  j

i                                                                                       i
        Compare annual soil erosion values in central Michigan and southern Louisiana  •
   for a com field with the following characteristics:                                !
;           •    Soil:  silt loam, 41 organic matter                                    [
I           e    Slope:  61, 100 m length                                               I
I           •    Moderate productivity, residues left, fall turn-plowed                 I
|                conventional management                                                I
j   For both locations, determine  annual soil erosion with no conservation practices    j
   and with contouring.                                                                •
   Solution;                                                                           j
'        Soil  erosion 1s determined by Equation 111-11:                                 j
|           X  - 1.29 E (K)  (Is) C  (P)                                                   j
j   From Figure 111-10, ero$1v1t1es (1n English units) for the two locations are        j
   approximately 100 (Michigan) and 500 (Louisiana).  Multiplying by the metric
!   conversion 1.735, we have E »  174 and 868.  Other parameters are:
j           K  - 0.33 (Table  III-3)                                                      !
I           C  • 0.52 (Table  III-4, line 3).                                             I
|   From Table III-9, P • 0.5 for  contouring and 1.0 with no practices.                 I
j        The 6 percent slope corresponds to  e « tan'^O.Oe) • 3.43° (Equation           |
j    111-13) and the Is factor from Equation  111-12 Is:                                  j
•           Is  « [0.045(100)]°'5 (65.41 $1n2  3.43 + 4.56  sin 3.43 + 0.065)               j
'               • 1.21.
!   Thus 1.29  (K)(ls)C(P) •  0.268  without contouring and 0.134 with contouring.         !
I   Soil erosion for the two locations and  practices:
j
j                                  No practice       Contouring
j                       Michigan    46.6 t/ha         23.3 t/ha
;                       Louisiana  232.6 t/ha         116.3 t/ha
                            —  END OF  EXAMPLE  111-3
                                         -176-


-------
3.4.3.3  Watershed Sediment Yield
3.4.3.3.1  Annual Yields
     Watershed sediment yield due to surface erosion 1s:

                                Y - sd  r  Xk Ak                             (111-15)


where
        Y   •  annual sediment yield (tonnes/yr)
        X.   «  erosion from source area k as given by Equation III-ll (t/ha)
        A.   «  area of source area k (ha)
        S.  »  watershed sediment delivery ratio.
     The sediment delivery ratio Srf Is a factor which accounts for the attenuation
of sediment through deposition and filtering as It travels from source areas to the
watershed outlet.  Although a number of different relationships have been proposed
for Sd, the simple function of watershed drainage area given In Figure 111-13
remains the most generally accepted procedure.

3.4.3.3.2  Seasonal Yields
     Equation 111-15 1s appropriate for annual sediment yields and should not be
used to determine event or seasonal watershed sediment yields.  Large watershed
sediment yields often do not coincide with major erosion periods.  For example, 1n
the eastern United States, most soil erosion 1s caused by late spring and summer
Intense rainstorms, but most sediment discharge occurs during late winter and early
spring runoff.  The reason for this 1s that runoff during erosive periods 1s often
Insufficient to transport eroded soil far from a source area.  Subsequent large
events "flush" portions of the accumulated sediment from the watershed drainage
network.
     Although general procedures are not available for estimating seasonal sediment
                                                                          2
yields, the following approach produced satisfactory results for an 850 km
watershed In upstate New York (Halth et ±L, 1984).
     Sediment yield 1n month m, Y  (tonnes), 1s assumed to be proportional to
 12
0~   where 0  1s the watershed runoff (cm) during month m.  The annual
sediment yield Y, as given 1n Equation 111-15, 1s likewise proportional to QT,
where
                                       12   . .
                                  QT - S  0*'*                             (111-16)
                                         -177-

-------
                                                                   1000
                                     DRAINAGE  AREA  (km*)
            FIGURE 111-13 SEDIMENT  DELIVERY RATIO As A FUNCTION  OF
                            WATERSHED DRAINAGE  AREA (VANONI,  1975)
Thus:
or
        Y/Y -  0*"
         OT      m
                                        .2
                                                                            (111-17)
     Equation 111-17 was  used  to  estimate monthly sediment yields over a 25-month
period for the 850 tan2 West  Branch  Delaware River Basin 1n upstate New York.
Comparisons with measured sediment  yields Indicated that the estimated mean monthly
sediment yield was within 12 percent  of the observed value.  Based on correlations
between monthly estimated and  observed sediments yields, Equation 111-17 explained 92
percent of the observed monthly variations (Halth et _£]... 1984).

3.4.4  Chemical  Loading Functions for Rural Runoff
     As suggested 1n Section 3.4.1, loading functions for rural runoff are equations
that multiply dissolved and  solid-phase pollutant concentrations by volume or mass
fluxes of runoff water or sediment, respectively (Equations III-l and III-2).
Procedures for calculating runoff and sediment yield were described 1n Sections 3.4.2
and 3.4.3.   It now remains to  outline procedures for determining pollutant concen-
trations 1n  runoff and sediment.
                                        -178-

-------
     The principal pollutants 1n rural  runoff arc nutrients (nitrogen and phosphorus),
heavy metals and synthetic organic pesticides.  Although most of these chemicals  have
both solid and dissolved phases it is convenient to divide them Into three categories,
based on their main transport phase in runoff:
        •    Solid phase; chemicals which are strongly associated with sediment.
        •    Dissolved phase; chemicals which are dissolved in runoff.
        •    Distributed phase; significant chemical  quantities are transported in
             both solid-phase and dissolved forms.
Loading functions for the first two c.  .egorles are straightforward; empirical  esti-
mates are used for the chemical concentrations.  Runoff of distributed-phase chemi-
cals is more difficult to model since dissolved and solid-phase concentrations are
influenced by adsorption equilibrium phenomena.
     Solid-phase chemicals include organic nitrogen,  particulate phosphorus and heavy
metals.  The assignment of metals to this category is arbitrary, since dissolved
forms are often present under acidic conditions.  However, it 1s assumed here that
the primary sources of metals in rural  runoff are metal-based pesticides which are
tightly bound to soil particles (Weber, 1975).
     The dissolved chemical group includes only inorganic nitrogen and soluble
phosphorus.   Inorganic nitrogen in drainage is mostly nitrate-nitrogen, and this Ion
does not adsorb to soil particles.  Phosphorus 1s a special case.  Most phosphorus in
runoff 1s solid-phase, but dissolved phosphorus 1s directly available to plants and
algae and hence cannot be neglected in eutrophlcation studies.  The loading functions
for solid-phase and dissolved phosphorus are operational means of describing complex
soil chemistry.   There Is a continuous set of  reactions that relate fixed, adsorbed
and soluble phosphorus forms.  Although it 1s  possible to model this behavior  (Donigian
and Crawford, 1976;  Knisel, 1980; Tubbs and Haith, 1981), such models are neither
simple nor especially accurate.
     Distrlbuted-phase chemicals include most  organic pesticides.  Models for  runoff
of these chemicals are considerably more complex than the solid-phase and dissolved
chemical loading  functions.   Indeed, the term  "loading function" Is used advisedly,
since models of these adsorbed chemicals are comparable to the continuous simulation
models discussed  in  Section 3.3.

3.4.4.1  Loading  Functions for Solid-Phase Chemicals  (Organic Nitrogen, Participate
         Phosphorus, Heavy Metals)
     The loading  function for solid-phase chemicals in runoff from a source
area is:

                                  LS • 0.001 Cs X                             (111-18)
                                         -179-

-------
where
        LS •  solid-phase chemical load In runoff (kg/ha)
        Cs •  concentration of chemical 1n eroded soil (sediment) (mg/kg)
        X  «  soil loss (t/ha).
The "0.001" in Equation 111-18 1s a dimensional conversion constant.  Soil loss Is
given by the Universal Soil Loss Equation (Equation 111-11) on either an annual or
single event basis.   In determining a source area's contribution to watershed chemical
loading. LS must be modified by a sediment delivery ratio (Section 3.4.4.1.2).
     Equation 111-18  1s often considered to be an estimate of total chemical load
rather than just the  solid-phase portion.  The assumption 1s essentially correct for
heavy metals since they are tightly bound to soil particles.  Moreover since most
soil nitrogen 1s In the solid-phase organic form and most soil phosphorus 1s partlc-
ulate, solid-phase nutrient loads will generally be a very large portion of total
loads.
3.4.4.1.1  Solid-Phase Chemical Concentrations
     The concentration Cs Is :?st determined by direct measurement.  Samples
may be taken of sediment depositions 1n fields and drainage ditches.  These samples
are subsequently analyzed for total concentrations of heavy metals, organic nitrogen
or participate phosphorus In the sediment.  Stream flow suspended solids samples 1n
rural  watersheds free of point sources and urban drainage may also be used.  When
sediment sampling Is  1nfeas1ble. procedures described In the following subsections
may be used to obtain approximate concentration estimates.

3.4.4.1.1.1  Organic  Nitrogen and Partlculate Phosphorus
     Nitrogen and phosphorus concentrations In eroded soil are generally larger than
comparable concentrations 1n uneroded or 1n situ soil.  This 1s due to the selective
nature of the erosion process.  Lighter organic matter and clay particles are more
readily eroded than heavier sand and silt.  Since nutrients tend to be associated
with these light particles, sediment Is "enriched* with nutrients compared to the
soil from which 1t originates.  A sediment nutrient concentration can thus be related
to the comparable concentration 1n soil by an enrichment ratio;

                                    Cs • en C1                               (111-19)

where
        en  •  nutrient enrichment ratio
        C1  •  nutrient concentration  1n |ni situ soil (mg/kg).
     Soil nutrient concentrations are  sometimes available from soil surveys or
extension specialists.  Nitrogen concentrations may be Inferred from soil organic
                                          •180-

-------
matter percentages by assuming that organic matter is 5 percent nitrogen (Brady,
1974).  Thus, for nitrogen C1 a 0.05(X OM/100)106 - 500 (X OM), where % OH is
percent organic matter in the soil.
      Very rough estimates of soil  nutrient concentrations can be obtained from the
general maps shown in Figures 111-14 and 15.  Figure 111-15 indicates soil  content of
P-Or which is 44 percent phosphorus.  To use Figures 111-14 and 15, we note
that  IS • 10,000 mg/kg, and hence for
        Nitrogen:    C1 « (% N)104
        Phosphorus:  C1 » 0.44 (X P^JlO4.
     Although these nutrient concentrations are for total nitrogen and phosphorus,
they may be used for organic nitrogen and particulate phosphorus since these nutrient
forms are so dominant In the soil.
     Nutrient enrichment ratios are 1n principle event-specific, since they are
related to the degree of erosion which occurs during a storm.  With very small
storms, only the finest soil particles are eroded, and the enrichment ratio is high.
Conversely, large storms erode all soil  particles, and the enrichment ratio approaches
one.  Based on analyses of many field studies of nutrient transport, Menzel (1980)
suggested the relationship:

                                 en . 7.39/Sed0'2                            (111-20)

in which Sed is the sediment discharge (kg/ha) during the storm event.  Equation
111-20 gives values of en ranging from 2.94 at Sed * 100 kg/ha to 1.35 at
Sed - 5000 kg/ha.
     Equation 111-20 can be used directly for single storm loading estimates by
letting Sed • 1000 X, since the units of soil loss X are tonnes/ha.  The equation 1s
not suitable for annual loads.  For these loads, a midrange value of en • 2.0 Is
appropriate (Ha 1th and Tubbs, 1981).  In summary:

                      | 2.0 for annual loads                                  ,...
               en •                   ,                                      (111-21)
                      I 7.397(1000 H)    for single event loads

For very large soil  losses (X > 22 t/ha), Equation 111-21 will give en < 1.0 for an
event.  When this occurs, tn should be stt equal to 1.0.

3.4.4.1.1.2  Heavy Metals
     The U.S. Geological  Survey has analyzed soil samples from 863 sites in
the United States for heavy metals.  The results, as summarized by McElroy ££ a]_.
(1976), are given in Table III-ll.  These concentrations may be used directly as Cs
In Equation 111-18 since 1 ppm • 1 mg/kg, and It may be assumed that no metals
enrichment of sediment occurs (McElroy et aK, 1976).

                                         -181-

-------
                                                                NITROGEN
                                                                *rcint N
                                                                l*Mffici*nt Dot*
                                                                in** aos
                                                                0.05-0.09
                                                             ^O.K>-OI»
                                                             (JJ 0.20 and 0**

FIGURE  111-14 NITROGEN  IN  SURFACE FOOT  OF  SOIL (PARKER,  EI  AL.,  1946)
 FIGURE  111-15 PHOSPHORUS  (AS P205>  IN  THE  SURFACE FOOT  OF  SOIL
                (NOTE:  P205 Is 44Z PHOSPHORUS) (PARKER  LL AL, 1946)
                                 -182-

-------
                                      TABLE  111-11





         HEAVY METAL CONCENTRATIONS  IN SURFICIAL MATERIALS IN THE UNITED STATES



                                  (McElroy et al, 1976)



Element
Arsenic
Barium
Cadmium
Cerium
Chromium
Cobalt
Copper
Iron
Gallium
Germanium
Cold
Hafnium
Indium
Lanthanum
Lead
Manganese.
Molybdenum
Neodymlum
Nickel
Niobium
Palladium
Platinum
Rhenium
Scandium
Strontium
Tantalum
Tellurium
Thallium
Thorium
Titanium
Uranium
Vanadium
Ytterbium
Yttrium
Zinc
Zirconium

Arithmetic
Average
(PP-.)
• •
554
--
86
53
10
25
25,000
19
--
--
--
--
41
20
560
< 3
45
20
13
--
--
--
10
240
--
--
--
--
3,000
--
76
4
29
54
240

•nalysli
Range
(ppm)
< 1,000
15-5,000
< 20
< 150-300
1-1,500
< 3-70
< 1-300
100-100,000
< 5-70
< 10
< 20
< 100
< 10
< 30-200
< 10-700
< 1-7,000
< 3-7
< 70-300
< 5-700
< 10-100
< \
< 1<>
< 30
< 5-50
< 5-3,000
< 200
< 2,000
< 50
< 200
300-15,000
< 500
< 7-500
< 1-50
< 10-200
< 25-2,000
<: 10-2.000

Conterminous
U.S.
(ppm)
^ m
430
--
75
37
7
IB
18,000
14
—
--
--
--
34
16
340
--
39
14
12
--
--
--
8
120
--
--
--
--
2,500
--
56
3
24
44
200
Geometric means
West of 97th
meridian
(ppm)
— —
560
--
74
38
8
21
20,000
18
--
--
--
--
35
18
389
--
36
16
11
--
--
--
9
210
--
--
--
--
2.100
--
66
3
25
51
170

East of 97th
meridian
(ppm)
— —
300
--
78
36
7
14
15,000
10
--
--
--
--
33
14
285
--
44
13
13
--
--
--
7
51
--
--
--
--
3.000
--
46
3
23
36
250
  Total
30,099
21,991
23,858
19,263
Note:  "--" Indicates all analyses shoved element  to be below  detectable  limits.
                                          -183-

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3.4.4.1.2  Watershed Loads of Solid.Phase Chemicals
     The annual watershed load of a solid-phase chemical 1n rural runoff Is the sun
of the attenuated runoff loads from all source areas 1n the watershed.  Since these
chemicals travel with sediment, attenuation (I.e., transport loss) 1s described by
the sediment delivery ratio, S^:

                             WLS «  Sd  r LSfc /^                              (111-22)

                                 ' °-001 Sd  = Csk Xk Ak

where
        WLS  -  annual watershed solid-phase chemical load  In rural  runoff  (kg/yr)
        IS.   •  solid-phase chemical load 1n runoff from source  area  k  (kg/ha)
        A.    •  area of source area k  (ha)
        Cs.   •  solid-phase chemical concentration 1n eroded soil (sediment)  from
                source k (mg/kg)
        X.    •  soil loss from source  area k (t/ha).
     Single event loads cannot be estimated by Equation  111-22 due to the sediment
transport variations discussed In Section 3.4.3.3.2.  However, seasonal loads may be
calculated by assuming them to be proportional to seasonal  sediment  yields.   From
Equation 111-17, we know that the ratio of monthly watershed sediment yield  Yffl
to annual yield Y Is:

                                  VY " ^'2/QT                            (HI-17)

where Q^ 1s watershed runoff 1n month  m(cm) and QT 1s given by Equation 111-16.
Thus If WLS 1s  the annual chemical  load given by  Equation  111-22, then  WLS  .
                                                                          IH
the load (kg) 1n month m, 1s:

                                 WLSm  " 
-------
Thus when soil  chemical concentrations are uniform, monthly chemical loads can be
obtained directly from monthly sediment loads.
 	 EXAMPLE III-4 	
                                                                                       I
                     Watershed Sediment and Phosphorus Loads                           '
                                                                                       I
        The West Branch Delaware River Is an 85,000 ha watershed in south-central New  |
   York that drains into Cannonsvllle Reservoir.  Soil erosion Is a major phosphorus   j
   source to the reservoir.  Major land uses contributing erosion are as follows:      j

               Land Use              Area (ha)      Mean K(ls)CP                       !
           Corn                        3,430            0.214                          \
           Hay                        13,085            0.012                          1
           Pasture                     5,093            0.016
           Inactive Agricultural        3,681            0.017
           Logging Roads                  20            0.217                          j
   Determine:                                                                          j
        a)   Average annual sediment yield (tonnes/yr)
        b)   Average annual solid-phase phosphorus input to the reservoir (kg/yr)
                                                                                       j
   Solution:                                                                           j
        a)   Average annual sediment yield is given by Equations 111-15 and 111-11:

                                   Y - S, z X.  A.                             (111-15)  I
                                        u i   K  K                                      '
                                                                                       I
                              Xk « 1.29 E (PC) (Is) C (P)                     (III-ll)  (
                                                                                       i
   There are five different source areas, each with their associated K (Is) C          j
   (P) values.  Rainfall/runoff erosivity is approximately 125 (Figure 111-10).
   Converting to metric units:
                                                                                       I
           E - 1.735(125) » 217.                                                       •
   Soil erosion x. , from each source area 1s:
                                                                                       I
          •    Corn:                    1.29(217) 0.214 - 59.9 t/ha                    '
          •    Hay:                     1.29(217) 0.012 • 3.4 t/ha                     I
          •    Pasture:                 4.5 t/ha                                       I
          •    Inactive Agriculture:    4.8 t/ha                                       j
          e    Logging Roads:           60.7 t/ha                                      [
                                                                     2                 '
  The sediment delivery ratio S, is approximately 0.065 for an 850 km
                                        -185-

-------
I  watershed  (Figure  111-13).   Sediment yield  is:                                       I
I           Y  - 0.065  [59.9(3430) +  3.4(13,085) * 4.5(5,093)                             I
I                     * 4.8(3681) + 60.7(20)]                                           j
j              • 18,960 tonnes/yr                                                         j
j        b)    Phosphorus load 1s:

                             LS • 0.001 S,S Cs.  X.  A                         (111-22)   !
I                                         u  .   K   K  r-                                  -

J   Since no other Information  is available, phosphorus concentrations  are  obtained      I
I   from Figure 111-15.  New York soils are  0.10 -  0.19 oercer-   ,0  .   using  a mid-      |
|   range value of 0.15 percent  and  recalling that  P-O, is  44  .ercent phosphorus,        j
j   we obtain  a soil phosphorus  level of:                                                '
I           C1 - 0.44(0.15) 104                                                          j
|              « 660 mg/kg                                                               j
j   Using an enrichment ratio of 2.0 (Equation  111-21), Cs  - 2.0  (660)  -  .320           j
j   mg/kg.
   we must assume that Cs  Is the same for all  source areas and hence:
I           %                                                                            I
j        LS    - 0.001  Cs Sd Z Xk Ak
j              • 0.001  Cs Y                                                               j
              - 0.001(1320)(18.960)  - 25.000 kg/yr.                                      •

!	END  OF EXAMPLE  III-4	-I

3.4.4.2  Loading Functions for  Dissolved Chemicals (Inorganic Nitrogen and Soluble
         Phosphorus)
     The loading function  for dissolved nutrients  in runoff from a  source  area
Is:

                                     LD - 0.1  Cd Q                           (111-25)

where
        LD  -  dissolved chemical  load 1n runoff (kg/ha)
        Cd  •  concentration of dissolved chemical  in runoff  (mg/1)
        Q   •  runoff from source area (cm).
The "0.1"  in Equation 111-25 1s a dimensional  conversion constant.  For event
loads, Q 1s given by  Equation III-3.  The loading function may also be used  for
annual  loads provided annual  runoff values such as those shown 1n Figure 111-9 are
available.
                                         -186-

-------
3.4.4.2.1  Dissolved Nutrient Concentrations
     Concentrations of dissolved nutrients in runoff vary with soil  cover.   Representa-
tive concentrations are given in Table 111-12.  Concentrations for fallow,  corn,
small grains, hay and pasture are flow-weighted average concentrations measured in
runoff over several years- from large field sites 1n South Dakota (Dornbush, et al.,
1974).  Forest concentrations are the National Eutrophication Survey values for
inorganic nitrogen and orthophosphorus given 1n Figures III-4 and 5 for 90% forested
watersheds.
     In the northern U.S., cropland which has manure left on the soil surface,
particularly during snowmelt, is likely to have significantly higher dissolved
nutrient concentrations in runoff than unmanured cropland.  The concentrations for
manured fields given in Table 111-12 should be used for snowmelt runoff from fields
which have received winter applications of manure.
     Although the representative concentrations given in Table 111-12 should be
replaced by local data whenever possible, such data are unavailable 1n most water
quality screening studies.  However, since the concentrations in Table 111-12 are
comparable to other values reported 1n the literature (see for example Baker, 1980),
it is unlikely that use of the representative concentrations would produce  large
errors in loading esfmates.
  	  EXAMPLE III-5 	

                 Single Event Runoff, Sediment and Nitrogen Load

        During the growing season a 7.0 cm rainstorm falls on the Louisiana cornfield
   described in Example III-3.  The field has an area of 10 ha and Is planted in
   straight rows.  The soil  Is in hydrologic Group B and 1s in poor  hydrologic
   condition.  This storm was preceded by 5.5 cm of rain four days previously.
   From Example III-3, the soil  has an organic matter content of 4 percent  and the
   USLE parameters for this  field are:
           K « 0.33, Is • 1.21,  C « 0.52 and P « 1.0
   Determine:
        a)   Storm runoff (cm)
        b)   Soil loss (tonnes)
        c)   Solid-phase and dissolved nitrogen in runoff (kg).
   Solution:
        a)   Runoff Is given by  the Curve Number Equation (Equation  III-3).  The
             curve number for straight row, poor hydrologic condition, soil B is CN2
             • 81 (Table III-l).  According to Table III-2, the preceding 5.5 cm of
                                         -187-

-------
                                      TABLE  II1-12

            REPRESENTATIVE  DISSOLVED NUTRIENT CONCENTRATIONS  IN  RURAL  RUNOFF

Soil Cover
Fallow*
Corn4
Small Grains*
May*
Pasture*
Inactive Agriculture1*
Eastern U.S.
HI 
-------
     where in this case E 1s the event eroslvity given by Equation  111-14:       i
        E - 6.46 a R1'81                                                        |
     The nearest location for the "a" value is State College,  Mississippi        |
     (Figure 111-12), which has a warm season value of a • 0.51.   Erosivity     j
     is thus:
        E - 6.46(0.51)(7)1<81 • 112                                             j
     Soil loss Is:
                                                                                I
        X - 1.29(112)0.33(1.21)0.52(1)                                          j
          - 30 t/ha
     Over 10 ha, the loss Is 30(10) « 300 tonnes.
c)   Solid-phase nitrogen loss (kg/ha) is:                                      j
                                                                                I
                            LS • 0.001 CsX                           (111-18)   j
                                                                                i
     where                                                                      :

                              Cs - en C1                             (111-19)   !
     and                                                                        )
                                                                                i
                          en - 7.39/(1000X)°'2                       (111-21)   I
                                                                                j
     As described In Section 3.4.4.1.1.1, soil nitrogen concentration C1        j
     (mg/kg) can be estimated by assuming that organic matter 1s 5 percent      :
     nitrogen.  The field's 4 percent organic matter gives a nitrogen concen-
     tration of:
                         fi                                                      I
        C1 • 0.05(0.04)10° • 2000 mg/kg                                         •
     The enrichment ratio for the storm 1s:
        en » 7.39/[1000(30)]°*2 • 0.94                                          j
     Since this Is less than 1.0, we set en - 1.0, and the solid-phase
     nitrogen concentration 1n sediment is:                                     ;
        Cs • 1.0 C1 • 2000 mg/kg
     The solid-phase nitrogen load Is:
        LS • 0.001(2000)(30) • 60 kg/ha
     or 600 kg for the 10 ha field.                                             !
     The dissolved nitrogen load Is:                                            I
                                  -189-

-------
I                                     LD - 0.1 CdQ                            (111-25)   I
j                                                                                        I
j             where from Table 111-12, Cd « 2.9 mg/1 for corn.  He/ice:                   j
|                LD » 0.1(2.9)(4.9) - 1.4 kg/ha                                          \
j             or 14 kg for the 10-ha field.                                              j
i                                                                                        i
	END OF EXAMPLE III-5	•

3.4.4.2.2  Watershed Loads of Dissolved Chemicals
     Since all runoff from watershed source areas 1s transported to the watershed
outlet (see Section 3.4.2.4), 1t 1s assumed that dissolved nutrient loads are-not
attenuated.  Watershed load 1s thus the sum of the source area loads:

                                 WLD « 0.1 Z  Cdk  Qy  \                         (111-26)

where
        WLD   »  annual or  event  watershed dissolved  chemical  load  1n  rural  runoff
                (kg)
        Cd.   •  dissolved  chemical concentration 1n  runoff  from  source  area
                k  (mg/1)
        Q.    -  runoff from  source area  k  (cm)
        A)(    •  area of source area k (ha).

3.4.4.3   Loading Functions for Distributed Phase Chemicals  (Pesticides)
      Runoff of pesticides  can be described by the same  general  loading  functions used
for nutrients and  metals  (Equations  111-18 and  111-25).  However,  the estimation
of dissolved  and solid-phase concentrations  1s more  difficult for  pesticides.   All
pesticides are adsorbed to some  extent by  soil particles, and hence dissolved  and
solid-phase concentrations cannot be determined  Independently.   Also, these concen-
trations  are  dynamic,  since  pesticides are decomposed or  decayed by photochemical,
chemical,  and microbiological process.   Decay rates  are often sufficiently  high that
most  of a  pesticide will  have decomposed within  several weeks of application.   A
final complicating factor  Is the large number of pesticide  compounds  currently 1n
use,  each  with Its own properties and characteristic behavior 1n the  soil.
      It follows that pesticide concentrations In runoff cannot  be  estimated by simple
empirical  methods, since  they depend on  the  relative timing of  applications and storm
events, and the specific  adsorption and  degradation  properties  of  the pesticide.
However relatively simple  equations can  be used  to describe the  adsorption  and decay
phenomena, and calculations  can  be made  for  each storm  event  following  a  pesticide
application.  The  following  subsections  describe such a model and  also  provide model
                                          -190-

-------
parameters for a large number of pesticides.  The model  estimates pesticide load
runoff events from a source area; i.e., a small  catchment with uniform  soil,
hydrologic and chemical characteristics.  Methods are not available to  aggregate
these source area loads Into total  watershed load.

3.4.4.3.1  Pesticide Runoff Model
     The pesticide runoff model  developed by Haith (1980)  is based on a  pesticide
mass balance of the surface centimeter of soil.  On day t  after a pesticide applica-
tion PQ (g/ha) to the surface soi,  layer, the pesticide content is:

                               pt  " Po "Pf-1^  *APt                       (HI-27)

where
        P    « pesticide in surface centimeter on day t (g/ha)
         '                              .1
        k    » pesticide decay rate (day  )
        AP   « additional pesticide application (1f any) on day t (g/ha).
     Equation 111-27 is a standard exponential or first-order decay model.
If a previous storm and/or pesticide application  was made  on some day T prior
to day t, then:

                              Pt - PT exp [k$(t-T)] +&Pt                     (111-28)

where
        PT  •  pesticide content after storm event or application on day f (g/ha).
Total pesticide P.. is divided into adsorbed  (solid-phase)  and dissolved  forms
based on a linear adsorption equilibrium relationship.

                                     Pt - At + Dt                            (111-29)

and

                                      «t • KDdt                              (111-30)
where
        Aj  •  adsorbed (solid-phase) pesticide 1n surface centimeter on
               day t (g/ha)
        D,  -  dissolved pesticide In surface centimeter on day t (g/ha)
        at  •  adsorbed pesticide concentration on soil particles (mg/kg)
        d(  •  dissolved pesticide concentration  In solid  water (mg/1)
        KO  «  pesticide partition or distribution coefficient (I/kg).
If a rainfall or snowmelt event sufficient to fill the surface layer's volumetric
                                         -191-

-------
available Mater capacity w (cm/cm) occurs on day t. then D,. Is given by 100 *
                                                          *•        3
dt and A( Is lOOb a( where b Is the surface soil bulk density (g/cm ).
Substituting these relationships Into Equations II 1-29 and 111-30 produces:

                              \ - [1/(1 + w/K0b)]Pt                         (111-31)

and
                                                                             (1 11-32)
If runoff occurs on day t, portions of \ and 0( will be removed by water
and sediment movement.  The solid-phase loss Is the product of adsorbed concentration
and soil  loss.  Since a( • /L/100b, we have

                                  PXt » (At/100b)Xt                          (IIJ-33)

where
        P)L  •  solid-phase pesticide in runoff on day t (g/ha)
        )L   •  soil  loss (sediment) in runoff on day t (t/ha).
Dissolved pesticide losses are distributed into runoff, percolation and a residual
which remains in the surface layer after a storm.  These components are assumed
proportional to the distribution of rainfall Rt (cm) plus snowmelt M, (cm)
into runoff, percolation, and available soil water.  Considering only events for
which R  + Mt > w, runoff loss of dissolved pesticide Is:

                              PQt • COt/(Rt * Mt)] Ot                        (1 11-34)

where
        PQj  «  dissolved pesticide 1n runoff on day t (g/ha)
        Q    •  runoff on day t (cm).
     Assuming that the surface layer Is dry prior to the event, percolation loss of
dissolved pesticide from the layer Is [(^ + Mt - (^ - wj/ff^ * Mt)]Dt, and
dissolved pesticide remaining in the soil after the event 1s [w/(Rt * Mt)] Ot<
Pesticide remaining In the surface layer 1$:

                         Pt* • Pt - P*t - U-»/(\ + \)1 Ot                 (1 11-35)
     Equations 111-33 and 111-34 are the basic loading functions for solid-phase
and dissolved pesticide In runoff.  For the solid-phase loads, X^ In Equation
111-33 1s the eroded soil from the source area as given by the Universal Soil Loss
Equation, (Equation III-ll).  The remainder of Equation lil-33,   /lOO b, 1s
                                         -192-

-------
the pe.stldde concentration in eroded soil or sediment.   In the dissolved pesticide
loading  function.  Equation 111-34, Q  is  runoff from the  source area determined
by the Curve Number Equation  (Equation  III-3), and \/(\ * \) is the dissolved
pesticide  in runoff.   These loading functions are of the  same  form as the solid-phase
and dissolved chemical loading functions  of  Sections 3.4.4.1 and 3.4.4.2.

3.4.4.3.2  Computational  Steps
     The pesticide runoff model is implemented by a set of sequential computations:
         1.   The day of initial pesticide application is  designated t • 0 and P
             is set equal to  the application to the surface centimeter (g/ha).
         2.   On each day  t «  1,2,... following application, a  check is made to see if
             an "event" occurs.  An event is either (i) a new  pesticide application
             or (ii) a precipitation (rain •»• melt) amount exceeding the soil's
             available water  capacity.   If no event occurs, the computations proceed
             to the next day.  If there  is an event, the  current pesticide content of
             the soil   is determined by Equation 111-28.
         3.   If Rt * Mt > w,  then pesticide  leaching will occur, and the
             following steps  are required:
             a.  Dissolved pesticide Ot  is obtained from  Equation 111-32.
             b.  Runoff Qt is computed by Equation 111-3.  If  Qt » 0,
                 go to step e.
             c.  Dissolved pesticide runoff  PQt is determined  from Equation 111-34.
             d.  Adsorbed (solid-phase)  pesticide runoff  PX( is obtained from
                 Equation 111-33 with soil loss Xt given  by Equation III-ll
                 and adsorbed pesticide A given by Equation 111-31.
             e.  Soil  pesticide level  is  updated to P* by Equation 111-35.
                 Note that Equation 111-35 may predict substantial pesticide losses
                 in percolation even if no runoff occurs  and hence P)L and
                 P(L are both zero.
These computational steps are repeated for subsequent days following a storm until
the surface pesticide level P  becomes negligible.  Often the  combined effects of
decay and leaching will remove virtually  all pesticide from the surface layer within
several weeks of application.

3.4.4.3.3.   Data for the Pesticide Runoff Model
     Four types of data are required for  pesticide runoff calculations:  daily
weather records, Universal Soil Loss Equation parameters and runoff curve numbers,
soil  properties and pesticide parameters.  The first two categories have been dis-
cussed In previous sections.   The soil  properties needed are available water capacity
(w) and bulk density (b).  These parameters are often given In county soil  surveys.
                                         -193-

-------
Representative values of w and b for several  soil  textures are given 1n Table 111-13.
These data are mean bulk densities for 207 soils and mean available water capacities
for 154 soils reported by Baes and Sharp (1983).
     Pesticide application rates, timing, and mode of application cannot be general-
ized.  This Information can only be obtained  from local  or regional pest control
specialists.  Mode of application refers to surface applied versus soil Incorporated
pesticide.  The model describes pesticide behavior Into the surface centimeter of
soil  and hence the application P  or &P  are  the chemical additions to that
surface layer.  For example, 1f 3000 g/ha of  pesticide 1s applied to the soil and
Incorporated to a depth of 5 cm (2 1n.), the  application rate for the surface layer
Is 3000/5 * 600 g/ha {assuming complete mixing In the soil).  Conversely, If the
pesticide 1s left on the soil surface, the entire 3000 g/ha Is contained In the
surface centimeter.

3.4.4.3.3.1  Pesticide Partition Coefficients
     Pesticide adsorption 1s generally considered to be related to soil organic
matter.  A genera! relationship given by Rao  and Davidson (1980) 1s:

                                  K0 • HOC (%OC/100)                         (I 11-36)

where
        Kg.  •  pesticide partition coefficient for organic carbon
        tOC  •  organic carbon of the soil, measured as a S .
     Table 111-14 lists Kg* values which have been summarized by Rao and Davidson
(1982) from a number of studies.  The table entries are means and coefficients of
variation (standard deviation/mean, :s a percent).  The mean values can be used to
estimate a partition coefficient for any soil.  For example, the KQ value for
atrazlne 1n a soil  rfth 2 percent organic carbon 1s:
        KJJ - 163 (2/100) • 3.26
     Soil organic matter percentage, 10M, 1s  often more readily available than IOC.
In such cases, IOC may be estimated as 59 percent of organic matter (Brady, 1974):

                                     %OC • 0.59 (%OH)                        (111-37)

     When KQJ values are unavailable, they may be Indirectly measured by the
octanol-water partition coefficient Kgy.  Rao and Davidson (1980) derived
the regression equation:
        log Kgg • 1.029 log K^ - 0.18
or
                                         -194-

-------
                                  TABLE  111-13


              MEAN BULK DENSITIES AND AVAILABLE WATER CAPACITIES

                             (Bass and Sharp, 1983)


Soil Type
Silt Loam
Cl ay and Cl ay Loam
Sandy Loam
Loam

Bulk
Density
b (g/cm3)
1.33
1.30
1.50
1.42
Available
Water
Capacity
w (cm/cm)
0.22
O.U
0.14
0.19
                                    TABLE 111-14


          ORGANIC CARBON PARTITION COEFFICIENTS FOR SELECTED PESTICIDES

                             (Rao  and  Davidson,  1982)
P««cicl
-------
                                    KQC » 0.66 K^j029                      (111-38)

Values of K^ for selected pesticides are given 1n Table 111-15.

3.4.4.3.3.3  Pesticide Decay Rates
     Pesticide decomposition In the soil  Is related to moisture,  temperature and pH.
Unfortunately, the only Information usually available 1s a simple pesticide half-life,
which 1s the mean number of days required for 50% of the original  pesticide to
decompose In the soil.  Decay rate k$ can be obtained from half-life using
Equation 111-27 (with A?t • o).  Since at t « half-life, Pt • 0.5 PQ:
        Pt - 0.5 P0 - P0 exp (-k$t)
and half-life 1s given by:
            -ln(0.5)/k$
or
                               k$ • 0.69/Half-l1fe (days)                     (111-39)

     Mean decay coefficients from Rao and Davidson (1982)  are given In Table 111-16
for 32 pesticides.  Three different rates are given for many of these chemicals.
When available, the "field" coefficient should bt used, since It 1n principle most
closely corresponds to actual runoff conditions.  The starred {*) lab rates are  the
second choice, since they also measure decomposition of the original  compound.   The
remaining lab rates attempt to describe the complete decay of the pesticide and  Its
decomposition products.  These "total decay" rates may be used If a very conservative
runoff estimate Is described, but the nature, toxldty and fate of most Intermediate
pesticide decomposition products are so poorly understood that 1t 1s  probably mis-
leading to model them with a simple first-order decay rate.
     The mean decay coefficients given 1n Table 111-16 are supplemented by the
specific k  values given 1n Table 111-17.  The latter were summarized from a
large number of decay studies by Nash (1980).  Since the coefficients 1n Table  111-17
are often unique to specific soil types, pH and organic matter contents, they are
perhaps less useful In screening studies than the mean values 1n Table 111-16.
However, many commonly-used pesticides are not listed 1n Table 111-16, and In such
cases the data In Table 111-17 may be the best available Information.
                                         -196-

-------
                               TABLE III-15


     OCTANOL-HATER PARTITION COEFFICIENTS  FOR SELECTED  PESTICIDES

                         (Rao and  Davidson,  1982)
  r««ticid«
  A. INSECTICIDES

  ALDICAXB
  ALTOS ID
  CARBARYL
  CHLORDANE
  CHLORPYRIFOS
  CHLORPYRiros
  CHLbRTTRIFOS
  cHLowYitiros, METHYL
  CHLORPYlliros, METHYL
  ODD
  OPE
  DOE P.P
  DOT
  DOT p,p
  DOVP
 OIALirOR
 DIAZZNOM
 DICKLOmmllOM
 DICIFOL
 DIEL0RZM
 DINOSEB
 EMDRIN
 mOXYCHLOR
 nuinonzoM
 KB
 UPTACKLOR
 LETTOrOS
 LEPTOPHOS
 LDOAKE
KAMTVXON
KRBOKTL
KCTBOXrOLOR
Krnm.
PARATBIOH
rERKETHRUf
 S.OOOOOE400
 1. 76000E-H)2
 6. 510OOE+O2
  2.07000E402
  2.10«OOE-K)3
  2.0S900E-H)3
  6.60000E-KX
  1.28825E-HD5
  1.97000E-K»3
  2.M170E-KM
  1.15000E-KJ5
  7.34450E-KK
  4.89779E-KI5
  3.70000E+O5
 1.
 4.
 1.
 1.
 3.
 4.
 1.
 1.
 1.
2.
1.
7.
FMSALONE
raostET
   9SOOOE4O2
   69780E-KM
   03200E-KJ3
   M038E-H15
   46100E-K33
   93000E+03
   9«OOOE-K)2
   61900E-H)3
  HOOOE-H33
   29900E4O3
   MOOOC+06
   WMOE-H33
 4.12200E-H33
 2.04174E-M)*
 «.43000E-K)2
 2.JOMOE402
 7.7«OOOC402
 1.20000C401
 2.050001403
 1.20000E-K>3
 2.07MOE+03
 *. 435001403
 7.5JOOOI402
•.23000E-HU
1.W530E-KM
t. 760001402
P«»tlcld«
PROPOXUR
ROWEL
TERBUFOS
TOXAPHENE
B. HERBICIDES
ALACHLOR
ATRAZINE
ATRAZINE
BXPENOX
BROHACIL
CMLORAKBEN
CBLOROPROPHAM
DALAPON
DALAPON, NA SALT
DICAKBA
DICKLOBEMIL
DZURON
HOKUXON
KSMA
NITIOrEM
PARAQUAT .2110.
PICLORAM
PROPACHLOR
PROPANIL
SDUZIME
TEMACIL
TtirtURALZV
2.4-0
2.4-D
2.4-D
2.4. 5-T
2.4.5-T. B0m ISTZI
2.4,5-T ocm urn
C. rONCICXDKS
BEMOHTl
CAPTAB
rcr
K
ow
2 . 80000E-K)!
7.M580E'HX
1.67000E-H)2
1 . 69SOOE+03

4 . 34000E402
2.I2000E402
2.26000E402
1.740OOE402
1.04000E402
1.30000E401
1.16000E+03
5.70000E400
l.OOOOOE+00
3.00000E400
7 . 87000E402
6.50OOOE402
1.33000E402
I.OOOOOE-04
1.24SOOE4Q3
l.OOOOOE+00
2.00000E400
4.10000E401
1.06000E402
>B0000E401
.800001401
.15000E403
.16000X402
.4300OI402
.46000C402
.000001400
.4OOOOI404
.OMOOC402

2.640001402
3.300001401
1.429001404
                                  -197-

-------
                        TABLE  II1-16
MEAN FIRST  ORDER DECAY COEFFICIENTS FOR SELECTED PESTICIDES

                  (Rao and Davidson. 1982)
Ratt Coeff. (day'1)
P«*Clcl4«

Mean
ZCV
A. HERBICIDES
2.4-D


Lib.*
Ub.
Field
0.066
O.OS1
3.6
74.2
23.3
S3. 3
Pesticide

Race Coeff. (day'1)
Hean
xcv
1. INSECTICIDES
PARATHIOff


Ub.*
Field

HETHTL FAIATHION Ub.*
2.4,5-T


ATRAZ1NE


SDtAZIME


TRIFLUJALW
Ub
Ub


UOHACIL



TIXIACIL


LINUXOM


OIUKOM


DICAM3A



PICUJHAN
DAUtfON
TCA
CLYFHOSATE
PARAQUAT
Ub.
Ub.*

Ub.*
Ub.
Field
Ub.*
Field

Ub.*
.* (anaerobic)
. (chain)
Fitld

Ub.*
Ub.
Field

Ub.«
Ub.
Field
Ub.*
Field

Ub.
Field

Ub.*
Ub. (ring)
Ub. (chain)
Field
Ub.*
Ub.
Field
Ub.*
Ub.*
Field
Ub.*
Ub.
Ub.*
Field
0.029
0.035

0.019
0.0001
0.042
0.014
0.022

0.008
0.025
0.0013
0.02

0.0077
0.0024
0.0034

0.013
0.00*5
0.006
0.0096
0.0034

-
0.0031

0.022
0.0022
0.0044
0.093
0.0073
0.0008
0.033
0.047
0.039
0.073
0.1
0.0006
0.0016
0.00013
31.7
82.9

47.4
70.4
33.3
71.4
93.3

63.5
.
.
63.0

49.4
116.2
100.0

33.3
124.0
55.0
19.8
41.2

-
38.1

80.2
-
-
16.1
38.9
111.3
51.5
-
103.4
121.0
93.0
-


DIAZ UWM


FOMF05
HAIATBIOK

PflORATC


CAUonnun

Uk.*

CARJARYL
Field

Ub.*
Ub.

Ub.*
Ub.*

Ub.*
Field

Ub.*
Ub.
(anaerobic)
Field
Ub.*
Ub. (Chain)


DOT
Ub.*
ALDRIM and
DZEL0R0T


CKDUN

Field

Ub.*
(anaerobic)

Ub.*
Field

Ub.*
(anaerobic)
Field (aerobic)
Field

pvt ftwft ftfT
urtMatot
LWSAJtt
tab.
C. FPMC1CIOP
PC?
Ub.
CATTAII
(anaerobic)

Field
Ub.*
Field
Ub.*
(anaerobic)

Ub.*
(anaerobic)
Field
Field
0.029
0.057

0.16
0.046

0.023
0.022

0.012
1.4

0.0084
0.01

0.047
0.0013
0.026
0.016
0.037
0.0063
0.10

0.00013
0.0035

0.013
0.0023


0.03
0.0015
0.0053

0.0024
0.011
0.0046
0.0026
0.0046

0.02
0.07
0.05
0.231
48.3
101.8

-
-

108.7
-

-
71.4

•
30.0

87.2
-
30.0
87.5
36.
101.
79.

130.
82.

-
100.0


53.3
-
-

104.2
119.6
-

60.0
44.3
-
•Theae racea are baaed on ch« dlaappearaace of »olv«nt-  extr actable parent
 incubation condition*. ualea« atated otharviae.

                                            -198-
                                                                 under aerobic

-------
                            TABLE  111-17



           FIRST ORDER  PESTICIDE DECAY COEFFICIENTS FOR
              SELECTED PESTICIDES AND SOIL CONDITIONS

                            (Nash, 1984)
    Ptstlcl*
                   In*
 •AS 34IOF-
     r
               -tottlitf Soil
                      $0(1
 Al MM or
 Mrttratt
 Anonle
t.4-0
              -taff
              taff
2.4-0 iMKtyl
 Mttr • vim.
2.4-0 Itooctyl   toff
 ostor • «1w.
2.4-0 IMKtyl
 Mtor •
                            •1
                            I
•It

•11
                                      (1)
                 WW1C10M

                 A«wi(t Flnvoti
                 Afontt
                                            NOMICIOCS
                                                           (kf/M)
                             O.OiO
                              .14M
                                        .0023
                                                                    .07M
            44

            44
            14
            2.0
                                            14 MM
                                            U Jvfy
                                            3D July
                                                                    .OH4
                                                                    .0*1*
                                                                   4013
                                            V«r1e«s
                                      4.S
                                      44
                                      44  ton*
                                      34  n «»4140
                                                             4S
                                                             4
                                        4W2
                                        4217
                                              items

                                      24  «r«t

                                      34  Forttt

                                      34  ftrwt

                                      24  ftrcn

                                      34  Uofcocftory 30*C
                                                             4     4407
                                                             4     4W7
                                                             4     .1733
                                                                  >47M
                                                             4     .13M
                                                                   47M
                                                             4     .1733
                                                                  >47M
                                                           IS      4*4«
                                      34  Ub«nt«ry 10*C
                                      34
34

34

34

34
II
124

12.1

U.I

12.1

12.1
4731
4417

UOOl

49S1

4SSS

jaw
                               •199-

-------
                          TABLE  III-17  (Continued)
     't*t!cfd«
                              50"
                     T»Pt
                                            vV
                                                     Crop
                                                                «oo1lc«tlon
                                                                   rate
 2.4-0 (sooetyl
  tstor • aalne.
 01ehlerproe«—
 Olcftlorprep
               •-OuocMU
                •OuacMU
                               si

 OlcMorprop	—Cross Ttabers  1
                               el
                               el
                               e
                               1
                               »1e
                               s1l
                               ill
                               »U
                               fs
 OtnUrwIne
 Oturon—	Norfolk
 OluroA————*0»cttur
 CFTC--
 Crrc-
•FlvcfclortMn
riucMortUn
 IsoorooaHfl-—
 Isooropa) In——
                 eisiM
 Isooropallii"' -— Ocfclay
 IsoorttoaUfi
K«rowtl1«tt	-cl

             *••* • 1C
U
11 Huron-
LlmroiH
L1 Huron	——
Li
                     •Is
                     -cl
                   -0>S
Natr1fe«t1«
   BO*
   at*
                        el
                        cl
                     -•1
                     -si
•Ural to

•1traU»
                                     • .4
                                     7.5
                                     7.0
                                     1.7
                                     7.2
                                     4.7
                                     4.7
                                     •.3
                                     C.J
                                     7.0
                                     7.0
                                     7.0
                                     7.0
                                     7.0

                                     4.1
                                     «.$
                                    4.7
                                    4.7
                                    4.7
                                    4.7
                                    «.J
                                    i.3
                                    7.S
                                    7.0
                                            (X)
                                                  NEUICIKS
                                            3.2   Loboritory
                                                                  12.S
                                                                           0.0257
                                            3.3   Forest
                                            2.8   firtss
                                            3.8   Forest
                                            4.0   laboratory
                                            4.S   Laboratory
S.I   Various
l.C
                                           2.1
                                           2.»
                                             .«
                                           2.2

                                           1.1
                                             0   Carrots
                                              0   larley
                                                 SorfHw
.J
.1
.1


-5.2
k$.2
.45
.IS .
:
«

1

l.M
3.3»
1.12



J


t$ •
3 4 4
3 4 ;
1 7 j
34 ]



2.24
4.48
2.24
4.41

.0578
.0864
.0(93
.0193
.0193
.0064
.0072
.0220
.,.0248
'.0070
L/.0045
.0023-
...003*
S/.0054
.0040
.0304
.0214
.0275
.0057-
.0282
.0118
S/.0104-
.0231
,.0047
'.0280
• .0039
'.00(1
1771
^..1070
/.02W
.0231
.0248
.00211
.0040
.0075
.0073
.005*
.00f2>
                                           2.1
                                           2.f
                                           2.1
                                           t.t
                                            .1
                                            .f
                                           4.0
                                           4.S
                                                 Laboratory
                                                 Laboratory
                                                                           .09M-
                                                                           .OOM
                                                                  1.12     .0110
                                                                  1.12     .0079
                                                                  2.24     .0090
                                                                  2.24     .0024
                                                                   .Si     .0155
                                                                  1.12   ,..00»1
                                                                        2S.OOS4-
                                                                           .0083
                                                                           .0144.
                                                                           .0058
                                                                   .81     .0394
                                                                   .15     .0394
                                                                         . ..0025
                                                                           .
                                                                        I^.OOSC
                                     -ZOO-

-------
                          TABLE 111-17  (Continued!
      f«st1c1d»
                                son
                      Typa
                                        pH
                                                   Crop or   Application
                                                  condition*    ratt	
                                                   HERBICIDES
  Ptbulata	fctglna e
  •tbulata	-Utyburn 1
  Mclora*	Scot 1.  oxbowt
  Victor*.	Various
  rlclora*	Nova Scotia cl
  rlclora*-—--—So»trt«t tl
  Mcloraa-	farln el
  Mclora*-	Chandler f si
  r1clora»————Qitstor 1
  Mclora^———-- ChMttr 1
  f 1 c 1 oram-	Varl out
  Plcloraia—-~~—OuacMta el
  Ptclora*	-OuacMta cl
  Mclora*——Cross Tlattrs 1
  rrofluralln
  Profluraltn
 •oMtrynt-—-~—~s1
 Propazl *»••••'	tl
 Propazlnt
                    to tl
                              cl
 S1 !»«»--
 SI 1 vox
 $11vo*
 SlMzInt
 Slauzliw
 SlMZlM
 SlMZlnt
 TobvthlurM	Various
                     91 «)Ck  C «
                   |,tniistert

 T«b«th1urw»~      rtllutttrt
Tobuthlu

Ttbuthl
             HoMton Hack
              Mic Ptllvsttrt
             Houston Hack
              Ittlc Ntlusttrt
            Mawtto* Hack
 Trial 1at».
 Trlallata-
 Trial latt
 Trial! at>
              Mglna c
              Coarto si
                artt si
             Owachlta si
 TH a II ata—--Me/bum
 Trial lata-
•2
 2
 2
 2
 2
.S-T-
,5-
,$-7	Cross Tlafctrt 1
,5.T-~~~-Faii«ii el
,5-T-—••OMHidltr fit
7.5
7.0



4.8
6.3
S.5
5.8
5.8
Various



7.0
4.8
(.5





7
7
4.1
I.S

7.0



4.0
4.5



2.9
1.9
1.7
1.9
1.9
3.3
2.8
3.8

2.0
1.0
2.0


3.3
Z.8
3.8
2
2
1.0
2.0

2.0



Laboratory
Laboratory
Various


Pillow
Orchard grass
Orchard grass
Orchard grass
Orchard grass
Forest
Crass
Fortst




Lcttuct

Fortst
Grass
For*st
Mont
Kont


Crow*
Una r rn nr .if
NOncropPtQ
Com
In siirfac*
runoff water.
In turfact
••lltts.
.85
.65


4.8
4.48
2.24
2.24
2.24
4.48
.05
.6
.(
.6






6
6
6
3 4
3 4




.025
2.24
2.24
a 0396
.0396
.0025
If .00772
.0044
.0050
.0354
.0258
.0268
.0269
I/. 004
I/. 0019
.0044
. .0028
4/.0047
U .0051
.0238
.0108
.0056
. .0061-
i/.otss
.0330
.0495
.0462
I/ .0074
.0083
.0116
.0062
.0539
A^9
.062
.0187
.002*
.0060
.0427
                                              In turfact      . ,.
                                               broadcast  spray:'*




7.S
7.0
7^
7.0
6.$
7.1



6.3
S.S




4U>
4.S
2.0
2.0

4.*2
3 *3
2.8
3.8
1.9
1.7
In otlltts
In surface
band pellets.
•roadcast Iff
soil stray.
Laboratory
Laboratory
•arley
Ih^hA
HOUV
HOMO
MOM
Fortst
Crass
Fortst
Orchard grass
Orchard grass
2.24
2*4
.*^
2.24
.CS
.65
1.7
3.4
2^
2.2
.6
.6
.4
2.24
2.24
.0201

.0517

.0624

.0069

.0090
.0110
.0144
.0067
.0088
.0053
.0289
.0330
.0330
.0508
.0495
                                     -201-

-------
                    TABLE  111-17  (Continued)
                            Son
                                         9*
                                                 Crw «r
2.4.S-T	CMttw 1
2.4.S-T	Ossster !
Trlfl«r«1t*

TrtflwiU*	feed il
Tr1Mw*1t»—-UH MM
7rlflnr«)l»	Ory Mil

rrtflwraltn	-Oe*l«r  *<1
Trtrmr»H«u——«c*Ujr  til
Tr1flw«U»~——Orttty  tfl
Trtflwatln——tlwrfttjltf ft
                  efUU f»
                ttf IM C
AUIcar*
A»«le«r»
AUicir*
A1«r<*
A1«rln
               NMUO* cl
            — MMitto* el
               MM«to
-------
                   TABLE  111-17  (Continued)
?*it!c!S*
                          Soil
                                pH
                                        ON
          Crop or
         conditions
                                                              r«t*
                                                  msecncioes
 AxtaptioiMthyl	Vlnoy 1
 l*rw1ck si                       Vofttablts
 •roaopftot—-------Coopos It*
 Caroaryl
 Cartarjrl	Udalpwr cl       7.1      l.(    Various

 Carfear/1	Jot»n«r si        l.(       .2*   Various


 Carftofuran	Takt sll        8.S
 CCA-12223;-	stl           4.8      1.0
 C6A-1222321	Sll           t.5      2.2
 Cklordano——	Itmlck  si
 Qi lordano———COBCOS Ut
 CDlorfonvlMfHOS
 OlaztnoA———-Ca«p«tUt
 OlulnoA	Sultan sll         (  7      3.1     25*C
 ~Carr<«fto« sll        Olsktf          Fallow
                                                                       O.OCT4
                                                                        .CIO!
                                                                        .04U
                                                                        .0605
                                                             S.O
                                                             S.O

                                                             7.4 IHC
                                                             7.4 INC
                                                             7.4 IHC
                                                             7.4 WC
                                                            15.0

                                                            15.0


                                                            10.0



                                                             2.0
OloloVln—......Ia*j«r1al sc
01tlO>1n	Noltvtllt fsl
Oltldrln	-Coo««s1tt
                              7.*

                              4.«
                              *.$
»,p'-OOT	
f.t'-OOT	4nM s»l
>.»'-OOT	-C*torjvt11« «Kk
• ,p*-OOT—»—— •--Narlttta si
O.»'-OOT	r«i fsi
i.p'-OOT	Nl«| sll
p.p* -DOT	Muck
P.P'-OOT—......COMMICt Sll
1.0
 .S

1.0
2.0
                                      1.1
                                        .1
                                     74. S
                                      2.0
                                        .1
                                      J.I
                                     40.0
                                                                  4.S
                                                                  4.5

                                                                 20.0
                                                                 20.0
                                  .0021
                                  .0140

                                Tof 1»
                                  .0098
                                7 of If
                               1^.0006
                               
-------
                      TABLE  111-17 (Continued)
    Ptsttctt*
                             ten
                                          ON
                                                   Crop or
                                                  COMUtwi*
                                                              r«tt
                                          (tj
».
»
»
 .OOT	C«r
•-OOT
•-OOT
•-OOT-	C«rr1iift«M t<1
rrlMto*
H1w« id
                        (11
                                  01 tk*
                            mstcTicioes

                              FtllM
•.»'-OOT	fantkk (t
OfattttotU——-Cooposltt
0l«i       frtntm* *)
mi«UH«i....... OtolMM c
N«1«U(
MrtkWttttw.
                •«1
                    itte
                                                             (kf/h«)
   4.
   4.
  11.
   4.

  11.
  11.
17 OOT
                                                             1.)
                                                                     1/0
                                                                       /0.0024
                                                                       27 .0044
                                                                         .0001
                                                      .0011
                                                      .00»
                                                    if .00014
                                                      .0007
                                                    l/.OOOM
                                                      .OMO
                                                      .1M4
                                                      .0142
                                                      .0014
                                                      .0012
                                                      .0001
                                                      .001$
                                                      .0014
                                   4.«
                                   «.S
                                   t.s
                                  ?.t
                                  ;.•
                                          1.0
                                          2.0
                                          1.0
                                           .$
                                                ZtytU
                                                FtllM
                                                              10
                                          10
                                          to
                                                              11 .«
                                                              11.2
                                                              11.2
                                                              1.12
                                                                         .0022
                                                                         .0032
                                                                         .002S
                                                                         .OS7I
                                                                         .1155
                                                                         .OISi
                                                                         .0021
                                                                         .0025
                                                                         .0021
                                                                      I/ .0004
                                                                         .OOM
                                                                         .0022
                                                                         .0024
                                                                         .0017
                                                                       .0011
                                                                       .0014
                                                              11.2
                                                              11.2
                                                              11.2
                                                              11.2
                                                              11.2
                                                      .0147
                                                      .02M
                                                      .0074
                                                      .02U
                                                      .02*4
PiriUtw
^•rttJilc*.
  in
7
                                          1.1
                                          J.I
                                          4.7

                                          1.0
                                          2.0
                                          1.0
                                          1.0

                                           .4
                                                    2.441*
                                                    1.24*1
                                                     .4152
                                                    1.M32
                                                    l.MM
                                                     .04M
                                                     .010*
                                                     .049*
                                           S.C
                                          u
                                                            10
                                                                        .0033
                                                                        .2207
                                                                        .2931
                                                                        .024*
                                                                      4/.OS4
                                                                      I/ .0044
                                  -204-

-------
                          TABLE  III-17  (Continued)
     Pestlcio*

                                            OK
                                                 Crop  or  Application
                                                condition*   ratt
 ParatMon	Joon*r si

 Parathlon———Macho til
 Parathlon-"•—-•-Cfim* c
 ParatMon	Nad*ra tl
•ParatMon---—~lav«tfl tl
 tarathlon	Santa  Lucia til
 Parath Ion	ft 1
 Parathlon———•• tic I
 Parathlon	—e
 Parathlon	tl
 Phmthottt———~ -f 11

 Phcnthoat*————c
 PlMnthoatc————-t 1
 Phoratt-——Sacramento wck
 Phoratt——-Sacravtnto peat
 Phoratt——-S«cr«wnto ptat
PHorUt	Takt  til
 Phorat*——-— StcraMflto t
Phoratt———Stcrcanito c
Zlnophos	Sultan til
Zlnopnot	Sultan til
Zlnepho*	Sultan til
Zlnophos	Sultan til
Zlnopnot	Sultan tl)
Zlnopnot
                                     8.<
                                     8.5
                                     S.S
                                     8.1
Zlnophot
Dlcltloftntlilon—Co^otltt
Tr Icfcloraut*—CoMpot Itt
 I/
I/
1'  r

If  '
if
If  Ottthyl
                Mtttr.
                                                 IKSCCTICIOCS
                                         .21
                                                               (*!/"•)
                     10
T of 8
0.0727
7 of 7
                                                                            .
                                                                            .1306
                                            0.8
                                            2.1
                                            2.3
                                            1.8
                                             .8
                                            2.1
                                            2.3
                                            1.8
                                                                         I'.'llSO
                                                                            .out
                                                                     If'JSSi
                                                                        «*<«
                                                                       .2*14
                                                                       .2MS
                                                                       !0141
3.1
3.1
3.1
3.1
                                                            13
                                                            13
                                                            13
                                                            10
                                                            13
                                                            13
                                                                           .0040
                                                                         */.0043
                                                                         l^oosi
                                                                         1^.0078
                                                                            A*W
                                                   15*C
                                                                       .01M
                                                 KMTICIOCS
                                                                       .OOH
                                                                       .0133
                                                                       .0208
                                                                       .0075
                                                                       .0031
                                                                       .0050
                     coMCMtrati fomlatlon.
                                                        p*»tphorotl»1o«U.
                                     -205-

-------
	 EXAMPLE III-6 	

                               Pesticide Runoff

      Two pesticides, carbofuran and atrazlne, have been applied to a cornfield at
 planting time.  Carbofuran 1s an Insecticide used to control  corn rootworm and
 atrazlne 1s a herbicide for need control.  Three days after each pesticide has
 been applied at 4000 g/ha, a 4.5 cm storm occurs which produces 0.2 cm of runoff
 and 0.6 t/ha of sediment.  The soil has an organic natter content of 31, bulk
 density of b * 1.3 g/cm  and available water capacity of w - 0.2.  Determine
 the runoff losses of each pesticide.
 Solution:
 Partition coefficients KO are determined from K^. values in Table 111-14
 (Atrazlne, K^. - 163; Carbofuran, K^. • 29.4):
                                                                                     I
                                 Kg « KQC (IOC/100)                        (111-36)  !
                                                                                     I
 where                                                                               I
         *OC  •  0.59 10M (Equation 111-37), or %OC • 0.59(3) -1.77                 j
         Kp   •  163(.0177) « 2.89 (Atrazine)                                        j
         Up   •  29.4 (0.0177) » 0.52 (Carbofuran)                                   j
 Decay coefficients k{ (field values) are given In Table 111-16:
         k$  •  0.042     (Atrazlne)                                                 !
         ks  •  0.016     (Carbofuran)                                               j
 Total adsorbed and dissolved pesticide 1n the surface centimeter are given          I
 by Equations 111-27, 111-31, and III-32.  Assuming the pesticide Is left on         j
 the soil surface, Initial levels for both pesticides are P  » 4000 g/ha.  For       j
 day t « 3:                                                                          j

                                                                                     i
 Atrazlne:                                                                            j
         P3     -  4000 exp   [-0.042(3)3   •  3526 g/ha
         w/ty -  0.2/2.89(1.3)  • 0.0532                                             !
         A3     •  [1/(1  *  0.0532)]   3526 -  3348 g/ha                                  \
         03     •  Cl/(l  *  1/0.0532)]  3526  -  178  g/ha                                 I
 Similarly,  for Carbofuran:                                                           |
         P3   •  3813 g/ha                                                             j
         A3   •  2942 g/ha                                                             j
         D3   «   871 g/ha
                                       -206-

-------
        Solid-phase and dissolved losses  are given by:
                                     (A3/100b)X3
   where
                             PQ3 •  CQ3/(R3  * M3)]03
           X3 «  0.6  t/ha
           Q3 «  0.2  cm
           R3 «  4.5  cm
           M3, snowmelt, is  obviously  zero.
   Atrazine:
   Carbofuran:
                •   [3348/1.3(100)]0.6 -  15.5 g/ha
                •   (0.2/4.5)178 «  7.9 g/ha
           PX3   »   [2942/1.3(100)]  0.6  «  13.6 g/ha
           PQ3   -   (0.2/4.5)  871  -  38.7 g/ha
   In Summary:
                                     (111-33}  |
                                               i
                                     (111-34)  j
                       Losses  in
                     Runoff  (g/ha)
                      Solid-phase
                      Dissolved
                      Total
Atrazine
  15.5
   7.9
  23.4
Carbofuran
   13.6
   38.7
   52.3
                               END OF
      111-6-
3.5  SALT LOADS IN IRRIGATION RETURN FLOWS

3.5.1  Description
     Pollution of surface waters by salty Irrigation drainage water 1s a problem 1n
many arid regions.  As shown In Figure 111-16, water may be diverted from a river to
water crops in an Irrigation district.  Portions of the diverted water are lost from
the diversion canal  through seepage and evaporation, and most of the remaining water
1s applied to crops 1n the Irrigation district.  Much of this applied water Is
consumed by plant evapotransplration (ET) and the excess passes through the soil to
be collected by tile drainage and returned to the river.  This drainage water
has a much higher salt concentration than the Irrigated water.  As the water moves
through the soil, it retains Its salt mass, but due to ET, the water volume 1s
dlmlnl shed.
                                         -207-

-------
     Return flow salinity can be computed  by  assuming  a  steady-state  condition 1n
wh1ch:
      Salts applied in irrigation  »  Salts removed in drainage
       v -sR
or
                                             SQI/R                             (111-40)
where
        s   -  irrigation water salinity (mg/1)
        s   m  return flow salinity (mg/1)
        I   *  irrigation application (m /day)
        R   «  return flow (m /day).
     Salt concentration or salinity is  measured  either as  dissolved  solids  (mg/1) or
electrical conductivity («mno/cm or mmho/cm).   In  the Western  U.S.,  an  average
conversion factor is 1000 * mho/cm « 640 mg/1.  Water  fluxes, such  as  I  and  R  refer  to
total water movement over the irrigation season  and can be measured  in  length or
volume units.  For example,  if I is given in centimeters,  it is  converted to  cubic
meters by l(nr) • I{cm) 100 A, where  A  - irrigated area (ha).
     When the irrigation diversion is taken from a river,  as in  Figure  111-16,
s  is the salinity of the river water.   The return flow salinity given  by Equa-
tion 111-40 obviously exceeds s  since  R •<  I.   The river salinity  after the
return flow is:
                                   s  (0 - D) + sR
                              »;•  n  O.D + B                            (III-4l)

where
        s'   «  river salinity after return flow (mg/1)
          o                                      3
        0   «  river flow prtor to diversion (m /day)
        0   •  Irrigation diversion (m /day).
      Since s'  > s , the  river  1s saltier for the next downstream user.   As
            o    o
successive Irrigation districts withdraw and return water, the river becomes pro-
gressively saltier until  It  1s no  longer suitable for municipal  or agricultural
use.
      Variations of the salinity problem  Include pimping of Irrigation water from
aquifers  and unsteady-state  or transient leaching of soil  salts.  In the former case,
s   is the aquifer salinity.   The salty drainage flow might be discharged to
surface waters as in Figure  111-16 or allowed to percolate through the soil, thus
producing saltier groundwater.   Transient  salt leaching often occurs when soils are
 initially irrigated or reclaimed.  Until a  steady-state situation 1s reached, the
                                         -208-

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                                          RIVER
               DIVE*
        LOSSES
     (SEEPAGE,
  EVAPORATION)
SION
                                                                 IRRIGATION
                                                                RETURN
 IRRIGATION
                                   DRAINAGE
                                                   FLOW
                                   EVAPOTRANSPIRATION
              FIGURE 111-16 COMPONENTS  OF AN  IRRIGATION SYSTEM
salt load 1n  return flow may exceed the  salts applied 1n irrigation.

3.5.2  Estimation of Return Flows
     Equations  111-40 and 111-41 may be  used directly when return flow volumes R
are known.   However, accurate return flow measurements are often unavailable and
Indirect  estimates are necessary.  A general procedure for computing  return flows Is
shown In  Figure  111-17.
     Design factors for Irrigation systems  Include irrigation efficiencies, diversions,
leaching  fractions and ET.  Hater losses 1n the diversion system are  Indicated by a
delivery  efficiency, E.:
                                      I
                     EdD
(111-42)
To prevent salt  buildup 1n soil which would  Injure plants. Irrigation applications
must exceed crop water needs so that applied salts way be washed fro* the  soil  In
drainage.  The leaching fraction 1s the fraction of Irrigation application which 1s
used to control  salinity, or the ratio of drainage to Irrigation.  As shown  1n  Figure
111-17:
                                    LF - (I  -  E)/I

                                        -209-
                                                      (111-43)

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                                      RIVER
              DIVERSION
                                                           RETURN]
       LOSS
                                                 EVAPOT
                        IRRIGATION  •
                  OilVERSION  ,  DELIVERY
                         EFFICIENCY
                                                        RANS,
                                    DRAINAGE "
                           IRRIGATION  - EVAPOTRANS,
                        WATER TABLED.. _^
                                                                   FLOW
                                        TILE DRAIN
              FIGURE  111-17  COLLECTION OF  IRRIGATION  DRAINAGE
              Irrigation leaching fraction
                       .3,
where
        LF  -
        E   •   crop ET (mj/day)
Since return flow  (R) consists of the drainage  water collected In tile drains,
ft « I - E and  LF - R/I - R/EdD.  Thus:
                                           (LF)EdD
                                                                           {111-44)
and rearranging  Equation 111-40:
                                           S0/LF
                                                                           (111-45)
     If irrigation  diversion 0, delivery efficiency E. and leaching fraction
LF are known,  return  flow volume and salinity  can be estimated by Equations  111-44
and 111-45.  If LF  1s unknown. It can be determined from Equation 111-43,  pro-
vided E, crop  ET, 1s  available.  Since E depends on crop mixture and local weather
conditions, It Is best obtained form  jcal  irrigation specialists.  In the absence of
such data, E may be estimated from potential  ET.  Potential ET, or PE, 1s  a maximum
ET which occurs when  the soil Is covered with a dense cover such as alfalfa  and water
1s not limiting. Thus potential ET 1s a function of the atmosphere's ability to
absorb water.   Actual ET Is generally less  than PE, but by letting E • PE. we obtain
a conservative overestimate of return flow  salinity.
     Potential ET can be determined from pan evaporation data or empirical equations.
Figure 111-18  shows average annual pan evaporation  for the U.S.  Potential ET Is
                                        -210-

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FIGURE 111-18 HEAN ANNUAL PAN EVAPORATION IN INCHES UIN = 2,Slew) (KOHLER EI AL,  1959)
                                         -211-

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approximately 701 of pan evaporation.  To use the data from Figure 111-18.  we must
assume that all annual PE occurs 1n the growing season.  Growing season PE  may also
6e estimated from Hamon's (1961) equation:

                                PE • (0.021 H2p)/(T + 273)                   (111-46)

where
        P£  •  potential ET (cm/day)
        H   *  mean number of daylight hours per day during period of Interest
        T   »  mean air temperature during period of Interest (°C)
        p   »  saturation water vapor pressure at temperature T (millibars).
Values of H and p are given in Tables 111-18 and 19.  The "period of interest" for
irrigation studies is the irrigation season.
   	EXAW>LF  ni-7	

                              Irrigation Return Flows

        A 3000 ha irrigation district diverts an average of 350,000 m /day of
   water from a river 1n the Irrigation season.  During this time, the mean river
   flow 1s 1,000,000 m  /day.  The delivery system 1s 80 percent efficient
   and the district operates at an average leaching fraction of 0.3.  The river
   water salinity is 200 mg/1.
   Determine:
           a)   Return flow volume and salinity
           b)   River salinity downstream of the return flow.
   Solution:
           Data for the problem:
                 D   -  350,000 m3/day
                 Q   •  1,000,000 m3/day
                 so  -  200 mg/1
                 Ed  -  0.8
                 LF  •  0.3
           a)   From equation 111-44, return flow 1s:
                 R  - 0.3(9.8)(350,000)
                    • 84,000 m3/day
                 with salinity given by Equation 111-45:
                 S  « 200/0.3 » 667 mg/1
                                         -212-

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                                       TABLE  111-18


                                MEAN DAYLIGHT HOURS PER  DAY
Latitude
 North      Jan    Feb    Mar    Apr    Hay     Jun     Jul     Aug    Sep    Oct    Nov    Dec


  46        8.7    10.0   11.7   13.4   14.9    15.7    15.3   14.0   12.3   10.6   9.1    8.3

  46        8.9    10.2   11.7   13.3   14.7    15.4    15.0   13.8   12.3   10.7   9.3    8.5

  44        9.2    10.3   11.7   13.2   14.5    15.2    14.8   13.7   12.3   10.8   9.5    8.8

  42        9.3    10.4   11.7   13.1   14.3    15.0    14.6   13.6   12.3   10.9   9.7    9.0

  40        9.5    10.5   11.8   13.0   14.1    14.7    14.4   13.6   12.2   11.0   9.8    9.2

  38        9.7    10.6   11.8   13.0   14.0    14.5    14.3   13.4   12.2   11.0   10.0   9.4

  36        9.9    10.7   11.8   12.9   13.8    14.3    14.1   13.3   12.2   11.1   10.1   9.6

  34        10.0   10.8   11.8   12.8   13.7    14.2    14.0   13.2   12.2   11.2   10.2   9.8

  32        10.2   10.9   11.8   12.8   13.6    14.0    13.8   13.3   12.2   11.2   10.4   10.0

  30        10.3   11.0   11.8   12.7   13.5    13.9    13.7   13.0   12.2   11.3   10.5   10.1

  28        10.5   11.1   11.8   12.7   13.4    13.7    13.5   13.0   12.1   11.3   10.6   10.3

  26        10.6   11.I   11.8   12.6   13.2    13.6    13.4   12.9   12.1   11.4   10.7   10.4

  24        10.7   11.2   11.9   12.6   13.1    13.4    13.3   12.8   12.1   11.4   10.9   10.6
                                            -213-

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                    TABLE 111-19





SATURATION VAPOR PRESSURE AS FUNCTION OF TEMPERATURE



                   (Jensen, 1973)
Temperature
<°C)
0
2
4
6
8
10
12
14
16
18
20
22
24
26
28
30
32
Saturation Water Vapor Pressure
(millibars)
6.1
7.1
8.1
9.4
10.7
12.3
14.0
16.0
18.2
20.6
23.4
26.4
29.8
33.6
37.8
42.4
47.5
                       -214-

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           b)   Downstream salinity is computed by Equation 111-41;

                      200(1,000,000 - 350,000} + 677(84,000}
                 s
                  o          1.000,000 - 350,000 * 84,000
                    • 255 mg/1
                            •- END OF EXAMPLE III-7
3.6  URBAN RUNOFF LOADS
     Nonpoint source pollution from urban runoff differs in several  ways from its
rural counterpart.  Runoff rates are usually much higher in urban areas due to the
distribution of impervious surfaces (pavements, roofs, etc.).  Urban runoff is
collected in separate storm sewers or combined sewers.  The later collect both runoff
and sanitary wastewater.  During a large runoff event, storm flow may exceed sanitary
flows by one or more orders of magnitude.  To avoid flooding from surcharged combined
sewers, combined sewer "overflows" are discharged directly to receiving waters.
These overflows are highly polluting since they contain runoff pollutants, raw
sanitary sewage, and scoured wastewater solids which were previously deposited in the
sewers.
     Urban runoff quality is influenced by human activities; Important determinants
are land uses and population density.  Land uses may be considered the "source areas"
in an urban watershed; tne total runoff load Is the sum of runoff loads from each
land use.
     Sections 3.6.1 and 3.6.2 describe equations for determining annual and event
pollutant loads.  The annual loading functions are highly empirical, but provide
estimates of pollutant loads from both separate storm sewers and combined sewer over-
flows.  Conversely, the event loading functions are more analytical, but describe
only runoff  (I.e., separate storm sewer load).
     Urban runoff and combined sewer overflow data are summarized by Huber, et al.
(1979) and E. C. Jordan Co. (1984).  Additional references on urban runoff computa-
tions include Novotny and Chesters (1980) and Klbler (1982).

3.6.1  Annual Urban Runoff and Combined Sewer Loads
     General urban loading functions have been proposed by Heaney, et^ a_l_. (1977), and
Heaney and Huber (1979) of the form:

                               L'-                                        (IIN47)
                                         -215-

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where
         L,  •  annual  load of pollutant due to runoff from land use k (kg/ha)
        afc  »  pollutant concentration factor (kg/ha-cm)
         F.  -  population density function
        vfc  -  street  cleaning factor
         P   -  annual  precipitation  fern).
Total pollutant  load from the urban  area is:

                                 L-2L)cAk                                   (111-48)

where
        L   «  annual  pollutant load  20 days, no street cleaning effects are apparent and V  -1.0.
Because most pollution load in.combined sewers is due to raw wastewater and sewer
scour, street cleaning will not significantly reduce loads, and Y.  • 1.0 for
combined sewers areas.
                                         -216-

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FIGURE 111-19 MEAN ANNUAL  PRECIPITATION IN INCHES (!IN = 2.5i4cM)  (OILMAN,  1964)
                                     -217-

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                                 TABLE  II1-20

              POLLUTANT CONCENTRATION FACTORS FOR ANNUAL LOADING

                      FUNCTIONS  (HEANEY AND HU8ER, 1979)
Pollutant (kg/ha-cm)
Land Use
Separate Sewers
Residential
Commercial
Industrial
Other Developed
Combined Sewers
Residential
Commercial
Industrial
Other Developed
BOD5
0.35
1.41
0.53
0.05
1.45
5.83
2.21
0.21
SS
7.2
9.8
12.9
1.2
29.7
40.6
53.0
4.9
VS
4.2
6.2
6.3
1.2
17.2
25.6
26.2
4.8
P04
0.015
0.033
0.031
0.004
0.061
0.138
0.291
0.018
N
0.058
0.131
0.122
0.027
0.239
0.539
0.504
0.066
                            •- EXAMPLE 111-8
                 Estimation of Annual Urban Pollutant Loads
     Consider a city of 4000 hectares of which 20 percent Is commercial, 10
percent Industrial, 65 percent residential and 5 percent 1s In other developed
areas.  The residential population density 1s 25 persons/ha.  Most of the dty
separate sewers but approximately 30 percent of the residential area still  has
combined sewers.  The streets are swept every five days In the commercial and
Industrial  areas and are not swept 1n the residential  areas.  The mean annual
precipitation  1s 105 cm.  Determine the average annual loads of nitrogen and
phosphate.
has
                                      -218-

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I   Solution:
|        The land use areas are:
          Commercial :    BOOha
          Industrial:    400ha
i          Residential:  780ha, combined
j                        1820ha, separate
          Other:        200ha
   Loads from each land use are given by Equation 111-47, with F  from Equation
'   111-49.  The street cleaning factor 1s:
'           V  • 5/20 »  0.25
I
I   in commercial/Industrial areas and Y  « 1.0 In all other areas.  The population
I   function for residential areas is:
!           Fk • 0.142  * 0.134(25)°'54
I              - 0.904
I   Loading calculations are summarized in the following table.
1                                       0)c (kg/ha-cm)       Lk (kg/ha)
I     Land Use          Ffc       Yk       N       P04       N       PO^
   Residential
     combined         0.904    1.0     0.239    0.061    22.69    5.79
     separate         0.904    1.0     0.058    0.015     5.51    1.42
   Commercial         1.0      0.25    0.131    0.033     3.44    0.87
   Industrial         1.0      0.25    0.122    0.031     3.20    0.81
   Other              0.142    1.0     0.027    0.004     0.40    0.06
   Total annual loads are obtained by multiplying each load Lfc by Its respective
   area as In Equation 111-48.
   Nitrogen:
           780(22.69) * 1820(5.51) * 800(3.44) + 400(3.20) * 200(0.40)
                      - 31,800 kg/yr
   Phosphate:
           780(5.79) * 1820(1.42) * 800(0.87) * 400(0.81) * 200(0.06)
                     « 8100 (cg/yr
   Over half the pollution load comes from the 780-ha combined sewer  residential
   area.
 '	END OF EXAMPLE  III-0	

3.6.2  Event Loads in urban Runoff
     Event loading functions for urban runoff  are based on general  procedures  proposed
by Any e£ £]_. (1974), many of which were  Incorporated 1n the  U.S.  Army  Corps of

                                          -219-

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Engineers urban runoff model STORM (Hydrologlc Engineering Center, 1977).  The basic
loading function 1s similar to that used for solid-phase rural  runoff loads (Equation
111-18).  Sediment (also referred to as "dirt and dust" or simply "solids") 1n runoff
1s multiplied by a pollutant concentration:

                                      L • 10"6 C Y                           (111-51)

where
        I  •  pollutant load In urban runoff (kg/ha)
        Y  •  sediment washed off the urban area during a runoff event (kg/ha)
        C  «  pollutant concentration 1n sediment (ppm: ng/g, or mg/kg).
Although Equation 111-51 1s often used for both dissolved and solid-phase pollutants,
we would expect It to be more accurate for the latter.
     Sediment washoff 1s limited by the total sediment which has accumulated on land
surfaces:

                                         Y - W X                             (111-52)

where
        X  •  accumulated sediment at the time of the storm (kg/ha)
        W  -  fraction of X which washes off during the storm.
     The washoff function is derived by assuming that washoff rate 
-------
where
        Q  »  total storm runoff  (cm).
     The washoff coefficient  1s determined by assuming 901 of accumulated sediment
will be washed off with 1.27cm (0.51n) of runoff (Amy et_ aj_., 1974).  Hence
0.1 X(0) - X(0) exp [- 1.27u] or  u - 1.8 cm"1.  The fraction of sediment washed off Is:
                                 m X(0)- X(h)
                                      X(0)
                                 • 1 - exp(-1.8Q)                            (111-56)

and Equation 111-51 can be written:

                           I • 10'6  [1 - exp(-l.SO)] C X                    (111-57)

     When this loading function 1s applied to an area with multiple land uses, either
loads are weighted from each area:

                                 L-£akLk                                   (111-58)

or weighted average concentrations and sediment accumulations are used:

                            CX - PgakXk][|akCk]                              (111-59)

where
        ak  •  fraction of total area In land use k
        Lfc  •  pollutant load from land use It (kg/ha) as given by Equation  111-57
        Xfc  »  accumulated sediment on land use k (kg/ha)
        C)(  •  pollutant concentration In sediment on land use k (rug/kg).

3.6.2.1  Runoff
     Two alternative procedures are used In STOW to compute storm runoff.   The  first
Is the U.S. Soil  Conservation Service's Curve Number Equation (Equation  III-3) as
described In Section 3.4.2.  Appropriate urban curve numbers for average antecedent
moisture conditions (CN2) are given In Table 111-21.
     The second option Is based on runoff coefficients and depression  storage:

                                    Q • CR(P . OS)                           (111-60)
                                         -221-

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                                 TABLE 111-21

             RUNOFF CURVE NUMBERS (ANTECEDENT MOISTURE CONDITION  II)
               FOR URBAN AREAS (SOIL CONSERVATION SERVICE.  1975)

                                                           Hydro!ogle  Soil Group
                  Land Use Description                         KBCD"
Open spaces, lawns, parks, golf courses, cmeteHes,  etc.
  Good condition:  grass cover on 751 or more of the  area      39   61   74  80
  Fair condition:  grass cover on 50% to  75% of the area      49   69   79  84

Commercial  and business area (85% Impervious)                 89   92   94  95

Industrial  districts (72% Impervious)                         81   88   91  93

Residential  :
  Average lot size        Average % Impervious
  1/8 acre or less                65                          77   85   90  92
  1/4 acre                        38                          61   75   83  87
  1/3 acre                        30                          57   72   81  86
  1/2 acre                        25                          54   70   80  85
  1 acre                          20                          51   68   79  84

Paved parking lots, roofs, driveways, etc.                    98   98   98  98

Streets and roads:
  Paved with curbs and storm sewtrs                           98   98   98  98
  Gravel                                                      76   85   89  91
  Dirt                                                        72   82   87  89
                                     -222-

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where
         P   -  storm precipitation (rainfall + snownelt, cm)
         DS  -  depression storage (cm)
         CR  »  runoff coefficient.
Equation 111-60 (which applies only for P > DS) suggests that precipitation must
satisfy  the available depression storage on plant surfaces and in mud puddles, pot
holes, etc., before runoff will occur.
     A conceptual  view of this runoff process is shown in Figure 111-20.  Depression
storage  DS is at a maximum value DS* when the land surface is completely dry, and the
depression shown in Figure 111-20 is empty.  However, previous events may have
partially filled depressions so that as in the figure, only a portion of DS* remains
to be filled.
     Depressions are assumed to be emptied by evaporation, and a general mass balance
is:
        DSt * Et  - Pt                         (I H-61)

0   <_   DS    £ DS*                          (111-62)
                      for
where
        DS   »  depression storage on day t (on)
        FV   »  precipitation on day t (rain + snowmelt, cm)
        £t   «  evaporation on day t (cm)
         ^«
        DS   *  maximum depression storage (cm).
Evaporation may be assumed equal to potential  evapotransplration and determined as in
Section 3.5.2.
     The depression storage computation (Equations 111-61,62) is a procedure for
describing antecedent moisture conditions.  *en the Curve Number Equation is used,
antecedent moisture is a function of 5-day antecedent precipitation.  In Equation
111-60, the water In storage on the land surface 1s the indicator of antecedent
moisture.
     Both maximum depression storage DS  and the runoff coefficient CR are
functions of the urban area's Impervious surfaces:

                                 CR - cr1 I * cr  (1-1)                      (111-63)

                                 DS* - ds1 1 * dsp (1-1)                     (111-64)
                                         -223-

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                               PRECIPITATION
                                      P
 DEPRESSION  STORAGE
            FIGURE 111-20 CONCEPTUAL MODEL OF  DEPRESSION  STORAGE
where
         I
         cr
          1
             cr.
        d$1 • dsc
 Default runoff coefficients used 1n STORM are  cr. « 0.90 and cr,
                                                '              P
                     fraction of the urban area which Is Impervious
                     runoff coefficients for Impervious and pervious  areas
                     maximum depression storage (on) for Impervious and  pervious
                     areas.
                                                                  0.15  (Hydrologlc
Engineering Center 1977).  Typical depression storage coefficients are ds^  •  0.15cm
and ds  • 0.60cn (Aron,  1982; Novotny and Chesters, 1980).  These values may  be used
when more specific local data are unavailable.
     Impervious fractions  are best estimated directly from aerial photographs or
land-use maps.  When these are  not available, regression equations based on population
density are sometimes used.  The equation given by Htaney and Huber (1979)  can be
approximated by:
                                   I • 0.069 PO
                                               0.48
                                                                            (111-65)
where
         PO
               population  density  (persons/ha).
3.6.2.2  Sediment
     Sediment and  pollutant  accumulation 1n urban areas 1s a complex  process which
depends on dally deposition  from the atmosphere and other sources, removal  by street
                                         -224-

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cleaning and washoff by runoff.   In order to estimate C and X in Equation  111-57, we
must begin by determining the sediment or solids accumulation.  This rate may be
measured by monitoring of storm sewer suspended solids data.  When these data cannot
be obtained, average values from previous urban monitoring programs must be used.
     Urban sediment data are often normalized with respect to the length of street
curbing.  This is because most of the dirt and dust which constitutes urban sediment
collects In street gutters.  Dally sediment buildup is:

                                        x » 2 Cl                             (111-66)

where
        x   •  daily sediment buildup (kg/ha-day)
        2   -  sediment accumulation rate (kg/km of curb per day)
        Cl   »  curb length density (km/ha).
     Curb length may be estimated as twice the total street lengths, and Cl is
obtained by dividing curb length by area.  Alternatively, the regression equation
given by the American Public Works Association (1974) may be used (converted to
metric units):

                               Cl  » 0.31 - 0.27(0.93)PD                      (111-67)

     Urban sediment accumulation rates from several sources are given in Table
111-22.  The rates given by Amy e£ £L, (1974)  and Sartor and Boyd  (1972) are mean
values based on data from a number of urban areas.  The STORM rates are suggested
default values for that model.  Although the Sartor and Boyd (1972) rates are larger
than the other two sets, they are generally comparable with the Amy Q t]_., (1974)
data.  The Sartor and Boyd rates are recommended for use in Equation 111-66 because
they are conservative and consistent.
     Sediment will accumulate at a dally rate x until  the streets are cleaned or a
runoff event occurs.  The dally sediment mass balance Is:

                                X.., - )L * x - v  . s.                      (111-68)
 where
         X»  •  accumulated sediment at beginning of day t (kg/ha)
         v   •  sediment removed In runoff on day t (kg/ha)
         S(  •  sediment removed by street cleaning on day t (kg/ha).
      If a runoff event occurs on day t, then from Equations 111-52 and 56:
                                          -225-

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                                      TABLE  111-22
                       URBAN SEDIMENT  (SOLIDS) ACCUMULATION RATES
                  Land Use
                    Any et         Sartor ft
                   aM!974)     Boyd (1972)*     STORM5
                          (all 1n kg/curbs-1 km-day)
Residential            42
Single-family
  residential
Multi-family
  residential
Commercial            21
Industrial
Light Industry       110
Heavy Industry        57
Parks
Open space           3.4
                                                    48*

                                                    66*

                                                    69*
                                                    127*
10

34

49
68
                                                                   22
     •Recommended values
     *C1ted In Novotny and Chesters (1980)
     bHydrolog1c Engineering Center (1977)
                                  Cl -
where
        0^  •  runoff on day t (cm).
Conversely, If the streets are cleaned on day t:
                                                               (111-69)
                                                                              (II1-70)
where
        e  »  street cleaning efficiency (fraction removed by cleaning).
It Is assumed that streets are not cleaned on the same day that  a  runoff event
occurs.
     Sediment accumulations and removal are Illustrated 1n the following example.
                                         -226-

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  --- EXAMPLE  III-9  -----   -  -------   -  - - -----

                     Urban Sediment Accumulation and Removal

        A stonm occurs on May 31 which removes all sediment  from an urban area.
   Subsequent storms occur on June 9 and June 15 which produce 0.5cm and  l.lcm
   of runoff, respectively.  On June 6, the streets are cleaned with an efficiency
   e « 0.4.  The daily sediment buildup is x - 80 kg/ha. How much sediment  1s  con-
   tained in the runoff from the June 15 storm?
   Solution:
        Letting May 31 be day t - 0, the next event is the cleaning on day  6
   (June 6).  Accumulated sediment Is X, • 6(80) • 480 kg/ha.
                                       o
   Cleaning removes:
           S& - 0.4(480) » 192 kg/ha
   and on June 7, remaining sediment Is:
           X7 • X6 - S6 * x
              - 480 - 192 * 80 - 368 kg/ha.
        For the June 9 runoff event,  X~ • 368 * 2(80)  » 528 kg/ha.   Sediment
   washoff from Equation 111-69 Is:
           Y9 • [1 - exp(-1.8(0.5))] 528
              - 313 kg/ha.
   On the following day:

           *10 * X9 ' Y9 * »                                                           j
               » 528 - 313 * 80
               « 295 kg/ha.                                                             !
        On June 15, X15 • 295 + 5(80)  • 695 kg/ha, and sediment washoff In the          }
   1.1 cm of runoff is:                                                                 I
                           1.8(l.l))] 695
                 599 kg/ha
                               END OF EXAMPLE 111-9
3.6.2.3  Pollutant Concentrations
     Pollutant concentrations in sediment can be obtained from sampling of sediment
accumulations 1n street gutters or sampling of storm sewer flows.  General values for
conventional pollutants are given In Table 111-23.  Concentrations of metals and
organic compounds are given 1n Tables 111-24 and 25.
                                         -227-

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               TABLE II1-23





CONCENTRATIONS OF CONVENTIONAL POLLUTANTS



IN URBAN SEDIMENT (SARTOR AND BOYD,  1972,



  CITED IN NOVOTNY AND CNESTERS, I960)


Land Use

Residential Commercial Industrial
Pollutant (ntgAg) (mg/kg) (mg/kg)





B005
COD
KJeldahl Nitrogen
NUr ate- Nitrogen
Phosphate-Phosphorus
9,200 8,300
20,800 19,400
1,700 1,100
SO 500
900 800
7,500
35,700
1,400
60
1,200
TABLE 1 1 1-24



Cd
Cr
Cu
Fe
Pb
Mn
N1
Sr
Zn
CONCENTRATIONS OF
(AMY,
Residential Commercial
(mg/k) (mg/k)
3.0 4.2
192 225
93 133
20,600 23.300
1.430 3.440
392 397
28 46
21 18
350 520
METAL IN URBAN SEDIMENT
et al_, 1974)
Industrial
Light Heavy
(nig/kg)
4.0 3.9
288 278
128 107
21.800 28.600
2.780 1.160
490 570
41 37
27 23
368 317


Weighted Mean
(mg/kg)
3.4
211
104
22.000
1.810
418
35
21
370
                  -228-

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                                     TABLE 111-25

                    CONCENTRATIONS OF MERCURY  AND ORGANIC  COMPOUNDS

                         IN URBAN SEDIMENT {AMY,  et  al,  1974)
Pollutant
Hg
Endrin
Dleldrin
PCB
Methoxychlor
DDT
Undane
Methyl Parathlon
DDD
Concentration
(mgAg)
0.083
0.0002
0.028
0.770
0.500
0.076
0.0029
0.002
0.082
3.6.2.4  Loading Computations
     The basic loading function for pollutants from urban runoff events (Equation
111-57) Is deceptively simple.  Storm runoff and sediment accumulation, which are
required by the loading function, depend on dynamic processes and are not easily
computed.  If the Curve Number Equation (Equation 111-3) 1s used for runoff, curve
numbers must be selected based on antecedent precipitation.  Conversely, the runoff
coefficient/depress Ion storage runoff equation (Equation 111-60) requires the dally
moisture calculations Indicated by Equations 111-61 and 62.  Sediment accumulation Is
determined using Equations 111-66, 68, 69, and 70.
     Event-based urban runoff loading computations are too complex to be routinely
done by hand.  Although the following example demonstrates that hand calculations are
possible, loading estimates are most efficiently done by computer.  Indeed, the
equations described 1n this section are the basis of the STORM computer model of
urban runoff waste loads.
                                         -229-

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.	EXAMPLE  111-10	
I
j                     Lead  In  Urban  Runoff  From a Storm  Event
i
        Estimate the  washoff  of  lead  from  a  200-ha  urban  area  during  a  2-cm  rain.
!  storm.   The area has a  population  density of 25  persons/ha  and  Is  601  residential
[  and 401  commercial.  The previous  storm 20 days  ago  washed  the  area  clean.
I  Streets  Mere cleaned 9  days ago  with  an efficiency of  551.   Dally  evaporation rate
|  during the 20-day  period was  0.2 cm/day.
I  Solution:
|        Since this 1s a multi-land  use area, we will use  weighted  loads as  1n
j  Equations  111-59 and 57.   Equation 111-60 will be used to compute  runoff:
I           Q - CR(P - OS)
|  To obtain runoff and depression  storage coefficients from Equations  111-63  and
j  64, the  Impervious fraction I must be calculated from  Equation  111-65:
j           I - 0.069  PD°'48
j            « 0.069(25)°'48  - 0.32
  Using the typical coefficients  for Impervious and pervious  areas given 1n Section
  3.6.2.1:
           CR  • 0.90(0.32) * 0.15(0.68) - 0.39
!           OS* - 0.15(0.32) * 0.60(0.68) • 0.46cm
I  Since maximum depression storage 1s 0.46cm, and  dally  evaporation  1s 0.2 cm/day,
I  depressions will dry within three  days.   Therefore,  on the  day  of  the  storm
|  DS •  0.46cm, and runoff 1s:
i
I           Q • 0.39(2-0.46) • 0.60cm
j  from  Equation 111-57:
i
!           L • 10'6 [1 - exp(-1.8(0.60))]  CX
I            • 0.66(10)"6  CX
k
|  Thus  661 of the accumulated lead (CX) 1s wished  off  by the  storm.
j        Dally sediment accumulation rates  can be obtained from Table  111-22.
j  Assuming that the  residential area 1s divided equally  between single-family and
:  multi-family residences, rates  are (48*66)/2 • 57 kg/km-day for the  residential
•  area  (601) and 69  kg/km-day for  the commercial portion (401).   The weighted
!  average  Is:
           z • 0.60(57) +  0.40(69)  •  61.8  kg/k»-d»y
j   Curb length density  from Equation  111-67  1s:
i           Cl  -  0.31  -  0.27(0.93)25 • 0.266  km/ha
                                         -230-

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   and daily loading 1s:
           x » 0.266(61.8) • 16.4 kg/ha.
        On day 11, when streets are cleaned, X « 11(16.4) « 180.4 kg/ha.  Cleaning
   removes 551, leaving 81.2 icg/ha.  On the storm day:
           X - 81.2 * 9(16.4) - 229 kg/ha.
        Lead concentrations, from Table 111-24, are 1430 mg/kg and 3440 mg/kg
   for residential and commercial areas, respectively, producing a weighted average

   °f:
           C - 0.60(1430) «• 0.40(3440) « 2234 mg/kg.
        Substituting these values of X and C in the loading function produces
   the lead load in runoff:
           L « 0.66(10)"6 2234(229) « 0.34 kg/ha
   or, over the 200-ha area:
           200(0.34) - 68 kg.
	END OF EXAMPLE 111-10	

3.7  GROUNDWATER WASTE LOADS

3.7.1  Characteristics
     Groundwater pollution Is of major concern because 1t endangers water supplies.
Organic chemicals, nuclear wastes, nitrates and other compounds may leach from such
sources as waste land application sites, storage lagoons, landfills, croplands.
lawns, gardens and construction sites.  The general characteristics of the problem
are shown in Figure 111-21.  The figure shows a "waste" which has been burled beneath
the soil surface.  This waste could be contaminants such as PCBs In a landfill,
septic tank drainage, fertilizers, pesticides, or toxic compounds In abandoned waste
dumps.  In other situations the wastes may be on the soil surface or contained In a
storage lagoon.  Chemicals are leached from wastes by percolation, and this leacnate
moves through the unsaturated soil zone to an underlying aquifer or saturated zone.
     Groundwater pollution Is often much more difficult to manage than pollution of
surface waters.  Since the water supply Is beneath the soil surface, pollution
effects are seldom visible.  When contamination 1s detected In samples from monitor-
ing wells or water systems, 1t 1s usually too late to eliminate the pollution source.
Chemical movement through the unsaturated zone Is relatively slow In the absence of
fractures or other Irregularities which channelize flows.  In many soils, pollutants
may move less than a meter per year.  A chemical which 1s detected In a well may have
begun Its transit from an abandoned waste dump 20 years ago.  Even If the dump 1s
subsequently excavated, a 20-year supply of the chemical remains In the groundwater

                                         -231-

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                   PRECIPITATION
          IRRIGATION
                                                            EVAPOTRANSPIRATION
            WASTE
^^••^     ~*^——M»"«=^    • •^•^^»~'^-     —   ^
                                                    UNSATURATED  ZONE
                                    PERCOLATION
                                     (LEACHATE)
                                                      WATER 'TABLE'
                           AQUIFER (SATURATED ZONE)
               FIGURE  111-21 POLLUTANT TRANSPORT  To AN  AQUIFER
transport "pipeline".   Compared to surface waters, the "flushing time" of aquifers 1s
very long.
     A further :omp1icat1on  1s the conservative nature of  many  pollutants 1n aquifers.
Aquifers lack  much  of  the  self-purifying or assimilative capacity of surface waters.
During transport  through the aerated unsaturated zone, chemicals may be removed from
leachate by  plant uptake,  volatilization, biochemical  decay  and adsorption.  However,
these removal  mechanisms are often greatly reduced or  eliminated once a chemical
reaches the  saturated  zone.
     Groundwater  pollution problems are complex, and they  are often analyzed by
computer models based  on the differential equations describing water and solute
movement through  porous media (Bachmat et_ al_., 1980).   These models are well beyond
the scope of this screening  manual.  The discussion In this  section Is limited to
simple procedures to estimate pollution loads to the saturated  zone.  Pollutant
movement 1n  the aquifer 1s not considered and steady-state,  uniform one-dimensional
flow 1s assumed.  Since the  time scale of groundwater  pollution 1s measured 1n years,
the loading  estimates  are  annual values.
     Succeeding subsections  discuss water balances, nitrate  loads from land applica-
tion sites and leaching of organic chemicals.
                                        -232-

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3.7.2  Water Balance
     Little downward movement of a chemical  Is possible in the absence  of  percolation.
Although some movement due to diffusion Is possible,  convection and  dispersion
associated with a water flux are the major transport  mechanisms in the  unsaturated
zone.  Based on the processes shown in Figure 111-21, percolation  is given by;

                                   0 - P * I  - E                              (111-71)

where
        Q  »  annual percolation (cm)
        I  »  annual irrigation (cm)
        P  -  annual precipitation (cm)
        E  «  annual evapotransplratlon (cm).


Equation  111-71 applies to a waste source In or on the soil surface which is not
contained within an Impermeable layer or storage lagoon.   In the latter cases,
percolation 1s equal to seepage or leakage through the layer or lagoon bottom.
     Mean annual potential evapotransplratlon minus precipitation 1s shown in Figure
111-22.  For a vigorous plant cover, ET is approximately equal to potential ET and
the values 1n Figure 111-22. converted to centimeters, can be used in Equation  111-71
to provide a simple screening device for groundwater pollution.  In  the absence of
Irrigation, negative values of E-P (I.e. P > E and hence Q > 0) Identify areas  of
potential groundwater pollution.  Conversely, nonlrrigated areas with positive  E-P,
and hence negllble percolation, are less likely to have contaminated groundwater.
     These conclusions apply only when a vigorous plant cover is maintained on  the
waste site to maximize ET.  A denuded or fallow site will produce little ET and
maximize opportunities for percolation.

3.7.3  Nitrate Loads to Groundwater From Haste Application Sites
     Municipal sewage and sewage sludges are often applied to land.   Land application
may thus eliminate a major surface-water pollution source, but It may also create a
groundwater pollution problem.  A major concern Is the leaching of Inorganic nitrogen.
In the form of nitrate, from the wastes and subsequent transport to the saturated
zone.  Nitrate Is extremely mobile In soils, and  since It Is toxic to Infants and
livestock, It Is often considered the most critical  pollutant from land application
systems.
     This subsection presents a simple nitrate loading calculation procedure adapted
from Ha 1th (1983).  The procedure estimates nitrate concentrations as nitrogen  In
percolation from the root zone of a land application site.
                                         -233-

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                                                                         0-5
FIGURE 111-22 MEAN ANNUAL POTENTIAL  EVAPOTRANSPIRATION MINUS PRECIPITATION  IN  INCHES
              (liN = 2,5<4CM)  (POUND  ET_ AL,  1976)
                                       -234-

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3.7.3.1  Model Description
     Components of the model are shown in Figure 1 1 1-23.  An annual  application of
nitrogen in waste is divided into organic and inorganic forms.  Inorganic nitrogen is
subject to volatilization losses, and the remainder is considered available for plant
or crop uptake and leaching.  Waste organic nitrogen consists of two components, a
labile or readily mineral izable fraction which is available for plants and leaching
during the first year following application, and a stabilized fraction which miner-
alizes at rates comparable to other forms of soil organic nitrogen.   The available
nitrogen supply thus consists of sludge inorganic nitrogen, rapidly  mineralized
sludge organic nitrogen and slowly mineralized so*1  and sludge organic nitrogen.
Since inorganic nitrogen in the soil  is rapidly oxidized to nitrate, 1t is assumed
that all available nitrogen is nitrate.
     Annual mass balances for soil organic nitrogen and available nitrogen are:

                                                                             (111-72)
                         At   - mOt + (l-v)lOOO N(l-F)Xt + alOOO

                              - mOt + 1000 N [(l-v)(l-F) + aF] Xt            (1 11-73)

where
        0.  -  soil organic nitrogen (including stabilized waste organic nitrogen)
               at beginning of year t (kg/ha)
        XT  •  waste application of dry solids In year t (t/ha)
        m   «  annual mineralization rate for soil nitrogen
        a   »  fraction of waste organic nitrogen mineralized during year of
               appl Icatlon
        N   •  nitrogen fraction of solids
        F   •  organic fraction of waste sol Ids
        Aj.  »  available nitrogen (nitrate-nitrogen) In year t (kg/ha)
        v   •  fraction of waste inorganic nitrogen which 1s volatilized.
     Nitrogen loss by leaching 1s the difference between available nitrogen and
crop uptake:

                                   4 • At - Cnt                             (1 11-74)

where
        Lt   »  nitrate-nitrogen leachate 1n year t (kg/ha)
        Cn   »  crop nitrogen uptake 1n year t (kg/ha).
     Since there are no additional removal mechanisms for nitrate once It passes
                                         -235-

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                      TOTAL APPLIED NITROGEN
     ORGANIC
    NITROGEN
                                    RATUD
                                MINIERAVIZATION
                SOIL  ORGANIC \MINERALIZATION
                  NITROGEN
                                                     VOLATILIZATION
              INORGANIC NITROGEN
                                                           ROP INTAKE
                    AVAILABLE  NITROGEN
                                              LEACHING »
                                          INPUTS-CROP UPTAKE
      FIGURE  111-23 NITROGEN DYNAMICS AT  A LAND APPLICATION  SITE
be tow the root zone,  L Is also the rtU rate-nitrogen waste load  to the saturated
zone, although 1f the water table Is well below the soil surface, the load  may not
reach the aquifer for several years.

3.7.3.2  Steady-State Loading Function
     The loading calculation given by Equation 111-74 1s complicated somewhat by
the need for sequential computations for soil  organic nitrogen by Equation 111-72.
However, after many years of waste application at  an average rate X (t/ha):
BX
                                            1"")  *
                             -«)  + BX/m
                                   (111-75)
                                      -236-

-------
where
         B  »   (l-a)lOOO N F, and 0Q is the initial soil organic nitrogen level.
The steady-state organic nitrogen level ff is BX/m or:

                                 TJ - (l-a)lOOO N F x/m                       (111-76)

     Substituting "0" into Equations 111-73 and 74 produces the steady-state
         function:
                              L - 1000NX [1 - v(l-F)]-Cn                     (111-77)

where
        L   •  annual steady-state nitrate-nitrogen load to groundwater (kg/ha)
        X   »  average annual solids application rate (t/ha)
        N   »  nitrogen fraction of solids
        F   »  organic fraction of waste nitrogen
        v   «  fraction of waste inorganic nitrogen which is volatilized
        Cn  m  average crop nitrogen uptake.

3.7.3.3  Loading Function Data
     Typical  values for crop nitrogen uptake are given in Table 111-26.  Volatiliza-
tion rates (v) are based on the ammonium content of the waste and the method of
application.   If the waste is sprayed or spread on the soil  surface, all ammonia can
be assumed to volatilize.  For example, if 701 of the inorganic nitrogen in the waste
is in the ammonium form, then v » 0.70.  Conversely, when wastes are injected or
otherwise directly incorporated 1n the soil, there is little opportunity for
volatilization and v « 0.
     Waste properties (X, N, F) will depend on the specific waste and the operation
of the disposal  site.
                                •-EXAMPLE  III-ll	
             Nitrate-Nitrogen  Load  from  a  Sludge  Land  Application  Site                  !
                                                                                       I
        Determine  the  steady-state  loading of  nitrate-nitrogen  from  a land  applica-     I
   tion  site  for sewage  sludge in central  Florida.   The  sludge  1s  spread  on fescue at   |
   an  annual  rate  of  lOt/ha.   The sludge solids are  51 nitrogen  and  701 of  the          j
   nitrogen  is  organic.   The Inorganic nitrogen 1s 90% ammonia  nitrogen.  Also
   estimate  the average  nitrate-nitrogen concentration in  percolation entering  the
   saturated  zone.
                                         -237-

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                        TABLE 111-26

               TYPICAL VALUES OF CROP NITROGEN
                    UPTAKE (POWELL, 1976)
          Crop                  Annual  Nitrogen Uptake (kg/ha)
Forage Crops
  Coastal Bermuda Grass                      540-670
  Reed Canary Grass                          250-400
  Fescue                                       300
  Alfalfa                                    160-250
  Sweet Clover                                 180
  Red Clover                                  90-140
  Lespedeza Hay                                150
Field Crops
  Com                                         170
  Soybeans                                   100-110
  Potatoes                                     220
  Cotton                                      70-110
  Wheat                                       60-90
  Sugar Beets                                   80
  Barley                                        70
  Oats                                          60
Forest
  Young  Deciduous {£ 5 yrs)                    110
  Young  Evergreen (^ 5 yrs)                     70
  Median and  Nature Deciduous                  30-60
  Median and  Mature Evergreen                 20-30
                               -238-

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   Solution:
        Equation  111-76 is used to determine steady-state loading:
            L - 1000NX [1 - v(l-F)]-Cn
   where X  « 10,  N « 0.05, F » 0.7.  Also, since the inorganic nitrogen is 901
   ammonia  and the sludge is spread on the soil surface, v » 0.9.  Crop uptake Cn is
   300 kg/ha from Table 111-26.
            L - 1000(0.05)10 [1-0.9(0.3)] -300
             * 65 kg/ha
        To  determine the nitrate-nitrogen concentration, percolation 0 must be
   estimated.  From Figure 111-22, E-P « -5in « -12.7cm for central Florida.
   Neglecting water in the sludge. Equation 111-71 indicates percolation
            0 - P-E - 12.7cm
   Since 1cm over 1 ha is 100 m , total percolation is 1270 m3, and the
   nitrate-nitrogen concentration 1s
            65/1270 « 0.051 kg/m3 - 51 mg/1
   which greatly e..eeds the drinking water standard of 10 mg/1.

   	—-—END OF EXAMPLE III-ll 	
3.7.4  Leaching of Organic Chemicals
     The potential for groundwater pollution from an organic chemical 1s determined
by adsorption and degradation processes.  Organic chemicals are partially adsorbed by
soil  particles, and movement of a chemical is retarded or slowed compared to the
movement of the percolation water.  Degradation of organic compounds by biochemical
processes and volatilization In the unsaturated zone will reduce the quantity of the
chemical so that only a fraction of the original compound will remain to enter an
aquifer.  If the chemical  Is strongly adsorbed  and rapidly degraded, and the water
table 1s well below the soil  surface, there Is  minimal  chance of groundwater contami-
nation.  Conversely, pollution 1s favored by any of the following conditions:  weak
adsorption, slow degradation, or high water table.

3.7.4.1  Adsorption
     Simple procedures for modeling movement of adsorbed chemicals are based on the
concept of a retardation factor, R (Freeze and  Cherry, 1979) which is defined as:

                                    R - u/u$                                 (111-78)
                                        -239-

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where
        u   »  mean water velocity (cm/yr)
        u   «  mean chemical (solute) velocity (cm/yr).
     Hartley and Graham-Bryce (1980) have shown that R 1s equivalent to the ratio of
total to dissolved chemical.  Consider a soil element with volume one cm3 containing
an organic chemical which Is both dissolved 1n soil  water and adsorbed to soil
particles.  Total chemical 1n the element 1s:

                                   C • fd + ba                               (111-79)

where
        C  •  total chemical (».g/cm3)
        d  «  concentration of chemical  1n the soil  water (eg/on )
        f  •  soil  water content (cm /cm )
        a  -  concentration of chemical  on soil particles Ug/g)
        b  «  soil  buU density (g/cm3).
If we assume a linear equilibrium adsorption relationship:

                                    a • KDd                                  (111-80)

where
        K_  •  adsorption partition or distribution coefficient (cm /g)
then the ratio of total to dissolved chemical 1s (fd + bK_d) /fd, or:

                                 R - 1 + (bKp/f)                             (111-81)
     The retardation factor Is thus a function of a chemical property {Kj and
two soil properties (b and f).  For flow 1n the unsaturated zone, the moisture
content f Is generally assumed to be field capacity.  Typical field capacities and
bulk densities are given 1n Table 111-27.  The partition coefficient K_ may bt
estimated from the octanol-water partition coefficient K   using Equations 111-38
and  111-36 as explained 1n Section 3.4.4.3.3.1.  Values of KQW for many organic
compounds are given In Chapter 2 of this manual.
     The retardation factor provides a general Indication of a chemical's mobility 1n
the soil.  For nonadsorbed Ions such as chloride and nitrate, R approaches unity and
the chemical moves at approximately the same velocity as the percolation.  For
strongly adsorbed chemicals, R 1s much larger than one and movement through the soil
1s slow compared to the percolation velocity (u  « u).
     The retardation factor also 1s used to estimate the distance which a chemical
moves in t years.  Thus, Z/X • ut/u t • R, or:

                                    X • Z/R                                  (II1-82)

                                         -240-

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where
        2  =  water displacement during time t (cm)
        X  «  chemical displacement during time t (cm).
Assuming plug flow, annual  water displacement (cm/yr)  due to percolation is:

                                   Z - J/w                                   (1 11-83)

where
        Q  «  annual percolation (cm)
        w  •  available water capacity (cm).
Available water capacity is used in Equation 1 11-83 rather than field capacity or
porosity since unsaturated soils drain to field capacity during percolation,  and  soil
water held below wilting point does not participate in the flow process.  Mean values
of w are given in Table 111-13 or may be computed from Table 111-27 as w • field
capacity - wilting point.
     Equations 1 1 1-83. 82 and 81 can be combined to estimate the mean annual  downward
movement of an organic chemical:

                                                                             (111-84)
                                     1 +
                                    TABLE  111-27

                     MEAN SOIL PROPERTIES  (BAES AND SHARP,  1983)
Soil Type
Silt loam
Clay and clay loam
Sandy loam
Loam
Bulk
Density
(g/cm3)
1.33
1.30
1.50
1.42
Field
Capacity
on3/cm3
0.35
0.36
0.22
0.32
Wilting
Point
on3/cm3
0.13
0.22
0.08
0.13
Porosity
cm3/on3
0.49
0.51
0.43
0.46
                                         -241-

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Due to dispersion, portions of the chemical will be displaced greater or lesser
distances than X.  If a chemical 1s Initially at the soil  surface, the location of
Its center mass after percolation Q 1s given by X (see Figure 1 11-24).
     The time required for the chemical center of mass to reach the aquifer, and
hence the mean travel time of the chemical through the unsaturated zone Is:

                                    T - 100H/X                               (1 11-85)

where
        T  •  mean time for a chemical to reach the water table (yr)
        H  •  depth to the water table (m) .

3.7.4.2  Degradation
     In the absence of chemical decomposition, even strongly adsorbed chemicals will
eventually reach aquifers.  The degree of groundwater pollution by an organic chemical
1s very much Influenced by degradation or decay rates.  Degradation of organic
compounds 1s discussed 1n detail 1n Chapter 2 of this manual.  A first order process
1s generally assumed such that:

                               C(t) • C(0) exp(-kst)                         (II 1-86)

where
        C(t)  •  chemical 1n the soil  at time t (g/ha)
        k     -  decay rate (yr"1).
     Equation 1 1 1-86 may be used to estimate the chemical  mass entering the saturated
zone.  From Equation 1 1 1-85, the average travel time to the water table Is T and
hence the chemical entering the saturated zone Is:

                               C(T) - C(0) exp(-ksT)                         (1 11-87)

where
        C(T)  -  chemical mass entering the water table T years after leaching begins
        C(0)  •  Initial chemical mass at the soil surface (g/ha).
     Equation 1 1 1-87 Is only approximate because due to dispersion, portions of the
chemical will require more or less time than T to reach the aquifer.  Moreover, decay
rates (k ) are uncertain for most chemicals.  Although representative values are
                                         -242-

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                                               SOIL  SURFACE
                                                           DISPLACED  CHEMICAL
                                                                   BAND
                                         CHEMICAL  CONCENTRATION

            FIGURE  111-24 DOWNWARD MOVEMENT OF A  CHEMICAL IN  SOIL
given In Chapter 2, most  reported rates were measured in  waste treatment systems and
surface waters.   Few data are available for estimation of decay  rates 1n the subsoil.

3.7.4.3  Groundwater Loads of Organic Chemicals
     Equations  111-84, 85 and 87 may be used to estimate  organic chemical loads to
aquifers.   Due  to the limitations of the equations (linear adsorption, first order
decay, dispersion, uncertain rates, homogeneous porous media), the calculated loads
should only be  considered "order-of-magnltude" estimates.
                                • •EXAMPLE 111-12
                  Napthalene Leaching from a Haste Storage  Site
        50,000 g/ha  of  napthalene Is leaching from an abandoned waste disposal
   site.   The site Is on a sandy loam with ft organic matter.  Water table depth 1s
   1.5m.   Mean annual percolation Is 40cm.  Based on the Information In Chapter 2,
   napthalene has  an octanol-water partition coefficient of K  • 2300 and a
                                                           ow
                                        -243-

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I   half-life of 1700 days.
|        How much napthalene will  reach the aquifer and what will  be the resulting
!   napthalene concentration at the water table surface?
|   Solution:
j        Equations  1 1 1-36,  37 and  38 must be used to estimate the  partition
   coefficient
                               K  -  K;    (XOC/100)                            (I II- 36)   .
                                                                                       !
                            XOC  •  0.59 (XOM)                                (111-37)   I
                                                                                       I

                                           i  n?<)
                               Koc " °'66 Kow                                (I II- 38)   |
   The organic carbon partition coefficient is:
           KQC  « 0.66(2, 300)  <     - 1900
           '.OC - 0.59(1)  - 0.59
           KD « 1900(0.59/100)  - 11.2
   Bulk  density (b),  field capacity (f)  and available water capacity  (w)  may be
   estimated from the data in  Table 111-27 for sandy loams:

           b - 1.5 g/cm3
           f • 0.22 cm3/cm3
           w • 0.22-0.08 » 0.14cm3/cm3.
        Annual napthalene movement is given by Equation 111-84:
|   Average time to reach the water table Is:
i
                                   T • 100 H/X                               (1 11-85)


           T - 100(1.5)73.7 - 40.5 yr .
   To use Equation 111-87 to calculate the napthalene remaining after 40.5 years, we
   must first determine the decay rate ks.  From Equation 1 1 1-86, when t « half-life
   » 1700/365 - 4.66 yr, C(t) • 0.5C(0).  Hence:
           0.5 • exp(-4.66kj
                           S
                                         -244-

-------
   or
           *s - -ln(0.5)/4.66 - 0.149
   Using Equation 111-87:
           C(T) - 50,000 exp [-0.149(40.5)]
                - 120 g/ha
        Thus  approximately 120 g/ha of the original  50,000 g/ha will  eventually
   leach into the aquifer.  The center of mass of the napthalene will  reach  the
   aquifer in a littje over 40 years.
        To determine the napthalene concentration in water at  the aquifer  surface,  w«
   must first divide the 120 g/ha into dissolved and adsorbed  components.   The
   retardation factor R is the ratio of total  to dissolved chemical.   Equation
   III-81 gives:
           R - 1  + bKD/f
             - I  * 1.5(11.2)/0.22 • 77
   The dissolved  napthalene mass is 120/R:
           120/77 - 1.56 g/ha
   Assuming this  rjss is dissolved in one year's percolation flow, 40cm «  4000m  /ha,
   the concentration is 1.56/4000 « 0.00039 g/m3 « 0.39^g/l.
                              END OF EXAMPLE 111-12
3.8  ATMOSPHERIC WASTE LOADS
     Atmospheric waste loads are direct mass inputs of pollutants from the atmosphere
to surface wate  -.  These loads occur as a result of both dry deposition and scaveng-
ing by precipitation.  For the purposes of water quality screening studies, atmospheric
loads are often considered constant, and are best determined by monitoring.  The sum
of atmospheric and background waste load (see Section 3.3), generally constitutes the
minimum pollution Input to a surface water body.
     Regional data are available for a limited number of pollutants.  Figure 111-25
and Table 111-28 Indicate atmospheric nutrient loads for regions in the U.S.

3.8.1  Dry Deposition
     Pollutants occur In the atmosphere as 1) particulates; 2) gases; or 3) dissolved
1n water vapor.  Cautreels and Van Cauwenberghe (1978)  give distribution coefficients
between the gas and particulate phases for 55 aliphatic hydrocarbons, polycyclic
aromatic hydrocarbons, phthalic add esters, fatty acid esters, aromatic acids  and
basic compounds.
     Both particulates and gases may settle out onto receptor surfaces.  For particles
                                         -245-

-------
                                             TABLE  111-26
                  ATMOSPHERIC CONTRIBUTIONS OF NITROGEN AND PHOSPHORUS IN PRECIPITATION
N Contribution in Kq/ha/yr
N03-N»HH4-N Total N

Northeastern U.S.
Southeastern U.S.
Midwestern U.S.
West/Southwestern U.S.
United States
LOW
5.7
1.5
0.2
1.7
-
lilalL
12.1
12.3
20.9
5.7
-
Low
5.7
-
1.7
9.0
-
lit ah
12.1
-
20.9
14.6
-
P Contribution in K
-------
                 .3kg/ho/yr
        l.0k«/ho/yr
                                    I Okg/ho/»r  ISkg/tio/yr   20 kg/ho/"
                 lOkg/ho/yf
FIGURE  HI-25 NITROGEN  (NHq-N AND NOj-N)  IN  PRECIPITATION,  (PERSONAL COMMUNICATION
               WITH MRI,  J.H.  CRAVENS, REGIONAL FORESTER,  U.S.D.A-FS EASTERN REGION, 1974)
                                          -247-

-------
< 0.3 *n in diameter, the major process 1s Brownian diffusion.   For diameters  0.5  to
5 un inert ial  impaction-i nterceptlon governs and for diameters  > 5 Mm,  gravitational
settling 's aoninant.  For gravitational  settling.  Stokes'  Law  may be used to
srec'ct :n« settling velocity.  Since Stokes'  Law is applicable only to quiescent
media, it should give an upper bound for V  (--e deposition velocity).   It 1s
stated as.
                                g (ad)* (•-»,)
                                          .111-88)
                                  18
where
        Vd  »  settling velocity (cm/sec)
        a   «  conversion factor (10" )
        g   «  acceleration of gravity,  981.46 (cm/sec )
        »   -  v ,co$lty of air, 0.000177 (g/cm-sec) at 10°C
        a   •  particle density, -2 (g/cm )
        f,  -  density of air, 0. 31243 (g/cm3) at 10'C
         a
        :   »  particle diameter (microns).
     For particles < 5 Mm 1n diameter Stokes   Law Is not  applicable and experimental
values for the deposition velocity should be  used.  Eisenrelch et_ £]_. (1981)  suggest
values of V  « 0.1 to 0.5 cm/sec for trace organlcs.  Some experimental values
are shown in Table 111-29.
     Once the settling velocity is known, the following procedure can be used to
predict the dry deposition loadings:
where
L « V. C  A f
     d  p
                                                                             (1 11-89)
        I   •  load of the pollutant delivered to the receptor surface as dry
               deposition (mass/sec)
        Vd  •  particle settling velocity (m/s«c)
        C   •  concentration of atmospheric partlcul ates (mass/m )
        A   •  projected receptor area (m )
        f   •  fraction (by mass) of the pollutant In the partlculates.
     Normally, smaller size particles are more chemically and physically reactive
than larger partlculates, and therefore pollutants will be associated with these
smaller particles.  Obviously the particle size to which pollutants are adsorbed
affects their atmospheric residence tine and, hence, loadings.  According to Heff
(1979), most polycycllc aromatic hydrocarbons are associated with partlculates in the
1 to 2 micron range.  Cautreeii and Cauwenberghe (1978) have shown that aerosol
                                         -248-

-------
                              TABLE 111-29
                FIELD-MEASURED DRY DEPOSITION VELOCITIES
                            (CT/S)
                                                         Sur'aca
PCS
 PCS


 PCS,  00r
   (gas  ?has«;

 PCS,  OCT

 PCS


PCS

  1015)

PCS
                             0.5
0.3-3


0.19


1.0

0.14


0.04
                                                     Mineral-oi*-caars:
                                                           p'ates
                                                     Estimated

                                                     Gl/cera'-coated
                                                        plates

                                                     Glycerin-water.
                                                        Al pans
                           0.43
  r:«:   Eisenreicn c: al..  1981
                                 -249-

-------
polycyclic aromatic hydrocarbons  are associated  with  particles of median diameter
from 0.7 to l.^nm.  In addition,  they give the  concentrations of 50 trace organic
compounds associated with different size  particles.   Higher weight polycyclic aromatic
hydrocarbons, aUanes, ana carboxylic acids had  significant mass fractions associated
with >1 um diameter particles.
                             — EXAMPLE 111-13
I                    Dry Atmospheric Deposition  of  Pollutants
!                            Adsorbed to Participates

        Estimate the maximum daily loading  of pyrene  to  a  watershed  having  an  area of
I     6 2
.   10 m  overlain by an air mass having a mean  daily  participate  concentration
I             3                                                             4
I   of 50 «g/m .  The average pyrene content of  the participates  is  1.0  x  10
I   Mg-pyrene/»»g.  Assume a deposition velocity  of  0.1 cm/sec.

   Solution:
   Compute the  daily dry deposited  load of  pyrene, using Equation 111-89:
I
           L •  V . C  A F
|                d  P

i             ,  o.ooi -2-  5M-   io6"2 i.o * io-4«9  pyrene  8640°scc
j                     sec   m                         u9        day
             -  4.32 x  105 Kg/day
I	END OF EXAMPLE 111-13
      Gas  phase  pollutants may also be deposited directly to the watershed surface.
 In  this case  the  loading equation is:

                                     L • V. C A                              (111-90)
                                          d

 where
        L  -   dry deposited load (mass/sec)
        Vd  •   gas deposition velocity (m/sec)
        A  •   receptor area («  )
        C  •   ambient concentration of the gas phase pollutant (mass/* ).
                                         -250-

-------
                              '—EXAMPLE  111-14-
             Dry Atmospheric Deposition of Gaseous Pollutants

     Estimate the annual deposition of toxapnene to a 1 na area at Stoneville, MS
during 1974.  >e mean monthly atmospheric concentrations are snown In Taole
II1-30.  Assume an averjse deposition velocity of 0.2 cm/sec for tie entire year.
Solution:

Month
n
1
2
3
4
5
6
7
8
9
10
11
12


Vd
(m/sec)
.002
.002
.002
.002
.002
.002
.002
.002
.002
.002
.002
.002

L •
Cn
(ng/m
10.
9.
19.
27.
44.
38.
175.
903.
524.
114.
32.
12.

12
T- u r »
- vd Ln A
3)
9
7
1
7
3
6
0
6
6
8
9
6

(m2)
io4
io4
io4
IO4
io4
io4
io4
IO4
IO4
IO4
io4
IO4

"n
(sec)
31
28
31
30
31
30
31
31
30
31
30
31

X
X
X
X
X
X
X
X
X
X
X
X

86400
86400
86400
86400
86400
86400
86400
86400
86400
86400
86400
86400

5
4
1
1
2
2
9
4
2
6
1
6
1
i
1
1
1
1
L '
(ng) 1
.84
.69
.02
.43
.37
.00
.37
.84
.72
.15
.71
.75
.01
X
X
X
X
X
X
X
X
X
X
X
X
,
io8 j
IO8

IO9 !
IO9 !
io9 I
IO9 1
IO10 |
IO10 i
109

!°08 !
IO11 '
ng/year I
i





or
1
101.4 g/ye«r j
                                       -251-

-------
1
i
i
i
i

i

i
i

i
i

i
i
i
i
i
1
i
i
:
'
i
•
i
i

i
i
i
i
i
i
i
i

IADLL U1-JU
AVERAGE MOHTHLY ATMOSPHERIC LEVELS OF
FOUR PESTICIDES AT STONEVILLE. MISSISSIPPI

in"
J««u4ry 1.
r«eru«ry 1. 1
N4rcn 2.1
Aenl 3.L
H«y 1.0
Jun« 0.9
July 5.2
August 10. 1
Wff'focr f 3
Oc:oe«r 4.0
No*t«A«r O.C
0*Ct«a«r 0.0
A»tr«9t 3.2

p»"
Itrnitry 0.0
Ftttrutry 0.0
M«rcn 0.0
April 0.0
M«y 0.0
Jun* 1.4
July 41.4
Aufutt 21k. 9
SOCftPMr 111.7
Octooer 1.4
K0«««*«r 0.0
0*c*ra«r 0.0
A.«rii;t 32.1
Sou ret Artflur tt 1^117


. i
Cndrin '««• )
1173 1174
3.1 0.2
0.1 9.2
0.7 0.4
0.7 3.5
1.2 0.7
3.8 0.7
0.7 9.3
5.0 27.2
1.4 11. 1
5.0 4.3
1.1 1.0
0.2 0.5
2.3 5.3
,
>•») *irt'Mon Inam' )
0.0 1.0
0.0 0.3
0.0 0.3
0.0 0.4
0.0 0.4
22.8 0.9
4.5 40.1
1Z1.3 341.1
711.1 1*7.9
17.1 Z.O
0.0 0.0
0.1 0.0
10.4 44.3
0



ior>
0.0
11.0
4«.3
47.4
3J.4
*4.2
400.7
1540.0
<27.f
17.1
9.3
0.0
2SI.4


10.1
12.4
tt.4
34.1
11. 1
11.2
117.3
515.3
371.1
37.4
14.3
4.3
11.5


rii.ii ..
To,,0*.*. («o,-'>
1Q71
0.3
0.0
14.8
10.8
W.3
101.9
41.1
248.8
O2. S
141.:
0.0
9.9
82.3
i
Total DOT (««• >
3.)
4.8
U.I
11.4
11.4
41.5
1.4
25 4
24.4
11.9
11.9
2.4
14.0




tan
10.3
1.?
19.1
27.7
4* 3
38.5
175.3
903.
at.
114.
32.
12.
159 5


3.3
3.6
7.4
7.7
It t
12.8
24.3
37.9
19.4
5.1
3.3
2.1
11.9



1
1
i
i
1
i
1
1

I
I

1
1

i
i

i
i


i
i

i
j
|
i


i

i
i
i
i
i
i
i
i
-252-

-------
 3.8.2   Met  Deposition  (Precipitation  Scavenging)
     Precipitation  falling through  the atmosphere tends to scavenge participates and
 absorb  gases so that it contains a  variety of substances.  Because of the volume of
 precipitation  which generally occurs, it may constitute a significant pollutant
 loading.  Load calculation for wet  deposition is given by:

                                   L • 10 C P A                                (111-91)

 where
        L   •   load  of  the pollutant delivered to the  receptor  as wet deposition
               (mass/sec)
        C   •   concentration of the  pollutant in precipitation  (mass/liter)
        P   •   precipitation rate (cm/sec)
        A   »   projected receptor area (m ).

 3.9  POINT  SOURCE WASTE LOADS
     The purpose of this section is to help users estimate waste loadings of toxic
 and conventional pollutants from municipal and industrial point sources.  Removal
 efficiencies and discharge concentrations are both provided.
     When possible  site-specific data should be used  in lieu of the guidance presented
 here.   Since permitted dischargers  are required to routinely .nonitor their discharges,
often the point source data required are available.
     When only a few measurements of effluent quality are available, those data may not
be representative of long-term averages.  Long-term averages are typically required for
most of the steady-state analyses contained In this document.  Figure 111-26, for
example, shows influent cadmium loading to the Kokomo, Indiana, wastewater treatment
plant (Yost e£ aj_., 1981).  Cadmium loading appears to exhibit a weekly cycle, with
 loadings the lowest on Sundays.  For this case, seven-day averages would be appropriate
for preliminary analyses.
     When using the data presented  in the following sections,  users should keep  in
 mind the variability of removal efficiencies and influent and  effluent pollutant
 concentrations between point sources.  The following  factors all contribute to
 effluent quality variability:
        t    Geographic location
        •    Climate
        •    Mixture of Influent sources (Industrial/domestic)
        •    Size of community
        •    Design flow rate versus actual flow rate.
                                         -253-

-------
          o
          •o
          C7>
          c
          •5
          o
          o
          6
          •o
          o
                20 ••
                15  ••
10 ••
                       (S)» Sundoy
                                     20   I    30l      |40    I  50 I     60
                   ssssssssss
            Ooy»   8-2  8-6    8-13   8-20  8'27  9'3   9-10   9'I7   9-24  KM
         FIGURE  111-26  INFLUENT CADHIUM  LOADING To  PLANT  DURING STUDY
                          (FROM  YOST £i AL,  1981)
3.9.1  Municipal  Haste Loads
     Table 111*31 summarizes  typical  Influtnt concentrations of conventional  pollutants
for wastewater treatment plants.   Concentration  ranges are shown for strong,  medium,
and weak wastewater.   Table 111-32 summarizes typical removal efficiencies of common
conventional  pollutants fro*  a  variety  of  wastewater treatment plant types.  Scheme
number 0 in the table denotes the  raw wastewater characteristics.  The table  shows
both percent  removal  and effluent  concentrations based on the characteristics of the
raw wastewater chosen.  The removal  efficiencies can be used for the range of concen-
trations shown previously In  Table 111-31,  assuming the plant Is operating within
design conditions.
     Table 111-33 summarizes  effluent phosphorus and nitrogen concentrations  for 662
primary treatment plants, trickling  filters, activated sludge plants, and stabili-
zation ponds.   The data were  collected  as  part of the National Eutrophlcatlon Survey
Initiated by  the U.S. Environmental  Protection Ageno 1n 1972 (Gakstatler et  al_.,
1978).  The user can  cross-compare effluent nutrient levels predicted based on joint
use of Tables 111-31  and 111-32 against the values 1n Table 111-33 to help get a typical
range of values.   Table 111-33  also  shows  per capita flow rates, per capita total
phosphorus loads, and per capita total  nitrogen  loads for each treatment type.  These
                                         -254-

-------
                                  TABLE  II1-31
               Tv?ICAL  INFLUENT  MUNICIPAL  WASTE  CONCENTRATIONS
                   Constituent
   Concentration

Strong  Medium**
Solids, total
Dissolved, total
Fixed
Volatile
Suspended, total
Fixed
Volatile
Settlable solids, (ml/liter)
Biochemical oxygen demand, 5-day, 20° (BOO, -20°)
Total organic carbon (TOC)
Chemical oxygen demand (COO)
Nitrogen, (total as N)
Organic
Free ammonia
Nitrites
Nitrates
Phosphorus (total as P)
Organic
Inorganic
Chlorides*
Alkalinity (as CaCO,)*
Grease
1,200
850
525
325
350
75
275
20
400
290
1,000
35
35
50
0
0
15
5
10
100
200
150
720
500
300
200
220
55
165
10
220
160
500
40
15
25
0
0
8
3
5
50
100
100
350
250
145
105
100
20
80
5
110
80
250
20
8
12
0
0
f
H
1
3
30
50
50
 •Values should b« increased by amount In carriage water.
"In tne absence of other data use medium strength data for planning purposes.
Source:   Me tea If and Eddy. 1979
                                     -255-

-------
                                 TABLE 111-32
               MUNICIPAL WASTEWATER TREATMENT SYSTEM PERFORMANCE
Influent:  see Scheme Number 0 for assumed characteristics.

                  Effluent Concentrations (mg/1), (X Total  Removal  Efficiencies*)
Scheme Number
    wast* water

      1

      2

      3

      4

      5

      6

      7
  BOD,
                    200(01)
  COD


500(01}
  55


200(0%)
130(35t)   375(25%)   100(251)

 40(80%)   125(75X)

 25(88%)   100(80%)

 18(91%)    70(86%)

 18(91%)    70(86%)

 13(94%)    60(88%)

  2(99%)    15(971)
PT, (mgP/T)     ft,.,  [mgN/TT
                                   10(0%)
00(25%)
30(85%)
12(94%)
7(96%)
7(96%)
1(99.5%)
1(99.5%)
9(10%)
7.5(25%)
7(30%)
1(90%)
1(90%)
1(90%)
1(90%)
                  40(0%)


                  32(20%)

                  26(35%)

                  24(40%)

                  22(45%)

                   4(90%)

                   3(92%)

                   2(95%)
 •Efficiencies for wastewater treatment are for the approximate concentration
  range, as measured by BOD,, of 100 £ BOO, £ 400, (mg/1).

••Scheme No.  Process
              No treatment
              Primary
              Primary, plus Activated Sludge (Secondary Treatment)
              Primary, Activated Sludge, plus Polishing Filter (High Efficiency
              or Super Secondary)
              Primary, Activated Sludge, Polishing Filter, plus Phosphorus
              Removal and Recarbonatlon
              Primary, Activated Sludge, Polishing Filter, Phosphorus Removal,
              plus Nitrogen Stripping and Recarbonatlon
              Primary, Activated Sludge, Polishing Filter, Phosphorus Removal,
              Nitrogen Stripping Recarbonatlon, plus Pressure Filtration
              Primary, Activated Sludge, Polishing Filter, Phosphorus Removal.
              Nitrogen Stripping Recarbonatlon, Pressure Filtration, plus
              Activated Carbon Adsorption
Source:  Neta Systems. 1973
                                     -256-

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                      TABLE II1-33



MEDIAN AND MEAN PHOSPHORUS AND  NITROGEN CONCENTRATIONS  AND



   MEDIAN LOADS IN WASTEWATER EFFLUENTS FOLLOWING  FOUR



CONVENTIONAL TREATMENT PROCESSES (Gakstatter  et  al .,  1978)
Treatment Type
Primary
Number of Sampl ed
Total Population
Ortho-P Cone.
(mg/1)
Total -P Cone.
(mg/1 )
Total -P Load
(kg/cap-y)
Total -N Load
(kg/cap-y)
Inorganlc-N Cone .
("9/1 )
Total -N Cone.
(mg/1)
Total -N Load
TN:TP Ratio
Per Capita Flow
(I/cap -d)
Plants
Served
Median
Mean
Median
Mean
Median
Median
Median
Mean
Median
Mean
Median
Median
Median

1,
3.5
4.0
6.6
7.7
1.1

6.4
8.3
22.4
23.8
4.2

473

086
•f
T
•»•
T
+
3.7
+
7
*
+
+
3.4
+
55
.784
0.29*
0.62
0.66
1.19
0.10

1.00
1.40
1.30
3.48
0.40

72
Trickl ing
Filter

3,
5.1
5.4
6.9
7.2
1.2

7.1
8.2
16.4
17.9
2.9

439

459,
+ 0
± °
«• 0
1 °
± °
2.9
* 0
± °
+ 0
*. 1
1 °
2.4
+ i
244
893
.21
.38
.28
.50
.05

.38
.60
.54
.23
.17

<»
Activated
SI udge

4,
4.6
5.3
5.8
6.8
1.0

6.5
8.4
13.6
15.8
2.2

394
244
357,138
* 0.24
+_ 0.40
+ 0.29
1 0.51
±0.06
2.4
+ 0.45
£ 0.69
* 0.62
*. 1.16
_* 0.15
2.4
± 26
Stao


3.9
4.8
5.2
6.6
0.9

1.3
5.5
11.5
17.1
2.0

378
il i zation
Pond
119
270,287
* 0.34
*_ 0.62
* 0.45
* 0.81
+_ 0.10
2.0
* 0.29
* 1.95
* 0.84
* 3.59
*. 0.26
2.2
1 38
•Value * 1 standard error.
                          -257-

-------
can oe used to generate loadings based on population served.   The typical  per capita
flow ranges Between 378 and 473 
-------
                             TABU  111-34




VEARLY AVERAGE PHOSPHORUS  REMOVAL PERFORMANCE  (Barlh and Stensel,  I9H1)
Plant
Angola. N.Y.

Ely. Minn.


Roanoke, Va.




Rochester, N.V.

Gladstone. Mich.

Grand Haven,
Mich.
Blue Plains. D.C.

Lima. Ohio

Marl borough, Mass.

Design
Capacity
3.1

1.0


35




20

1.0

3.2

330

18.5

5.5

Flowsheet
Extended aeration—solids
con tact- -tertiary filter
Primary — rock trickling
filter--solids contact--
tertiary filter
Primary --2-stage activated
s!udge--nitrif 1 cat ion- -
floccul at ion- -tertiary
filter

Primary --activated sludge

Primary—rotating biological
contactor
Primary --activated sludge
(domestic A tannery)
Primary--2-stage activated
sludge- -nitrification
Primary --activated sludge--
nitrification towers
Primary--2-stage activated
sludge- -nitrification
Chemical &
Addition Point
FeCU * polymer to
solids contact
Alum * polymer
before secondary
clarif ier
Pickle liquor to
1st stg. aeration
and alum/polyner
before floccul a-
tion basin
Alum before final
clarifier
Alum prior to RBC

Pickle liquor be-
fore primary
FeCI 3 to secondary

FeCl3 » polymer
prior to primaries
Alum or FeS04 to
Ist-stg. aeration
Performance
Intl.
Effl.
Infl.
Effl.

Infl.
Effl.



Infl.
Effl.
Infl.
Effl.
Infl.
Efl.
Infl.
Effl.
Infl.
Effl.
Infl.
Effl.
130
2
180
15

220
2



186
16
129
12
389
16
140
28
157
5
159
3
264
2
123
13

340
1



165
9
118
16
432
19
135
28
126
9
306
8
Phosphorus
, UH^/ 1 Kemoval
Total P Efficiency
6.8 87%
I). 9
3.8 841
0.6

11.9 981
0.2



6.3 87%
0.8
3.5 74%
0.9
5.0 88%
0.6
b.2 711
1.8
5.1 841
0.8
6.8 91%
0.6
                                 -259-

-------
                TABLE 111-35






METAL CONCENTRATIONS AND KEMOVAL EFFICIENCIES




   IN TREATMENT PLANTS AT SELECTED CITIES
City
Anderson,
Indiana

Buffalo.
New York

Dayton,
Ohio

Grand Rapids,
Michigan

Muddy Creek.
Ohio

Muncle.
Indl ana

Treatment
Received
Secondary
Treatment

Secondary
Treatment

Trickling
Filters

Secondary
Treatment

Conventional
Activated
Sludge
Secondary
Treatment


Influent, i*g/l
Effluent. **g/l
Reaoval Efficiencies. I
Influent, »g/l
Effluent. 1*9/1
Reaoval Efficiencies. I
Influent. 1*9/1
Effluent. »g/l
Reaoval Efficiencies. I
Influent. »g/l
Effluent. 1*9/1
Reaoval Efficiencies, i
Influent, ng/l
Effluent. Kg/I
Reaoval Efficiencies, I
Influent. »g/l
Effluent. 1*9/1
Reaoval Efficiencies. %
at
9.5
3.9
59
18
11.2
37.7
27
16
40.7
.
-
-
8
62.5
3
.
-
-
Cr
1180
142
88
208
78.6
62.2
_
-
-
400
136-325
19-66
-
-
-
240
53
78
Cu
2820
395
86
137
53.4
61.0
«
-
-
500
21S-435
13-57
.
-
-
260
83
68
Nt
2790
885
41
50
44.5
11.0
.
-
-
500
295-410
18-41
-
-
-
140
140
0
In ft
1500
375
75
337
704
41.3
.
-
-
1200
588-780
35-51
-
-
-
1150
345
70
Pb
160
4U
75
99
?5.9
73.8
.
-
-
-
-
-
-
-
-
9JU
167
82
                    -260-

-------
TABLE 111-35
(Continued)
City
Pittsburgh,
Pennsylvania

Uahtawa.
H*w«tt

Winnipeg,
Han.

Burlington.
Ontario

Average of 6 Cities
near Kansas City

Survey of 20 Plants
tn Ontario

Treatment
Received
Secondary
Treatment

Step
Aeration

Pure
Oxygen

Conventional
Activated
Sludge
.


.



Influent, ng/l
Effluent. »g/l
Removal Efficiencies,
Influent, «g/l
Effluent, ng/l
Removal Efficiencies,
Influent, »g/l
Effluent, cg/l
Removal Efficiencies.
Influent, *>g/l
Effluent. »g/l
Removal Efficiencies,
Influent, og/l
Effluent, eg/I
Re«oval Efficiencies.
Influent, »g/l
Effluent, *g/l
Removal Efficiencies.
Cd
21
J
I 67
5-65
2-21
I 59
.
-
I
6
1
I HO
20.2
-
I 16
20
-
ft 19
Cr
95
31
6/
12-18
8-12
32
166
53
68
29U
61
79
220
-
3;
971)
-
62
Cu
127
56
56
62-90
16-23
74
210
48
77
JIO
84
73
146
-
49
300
-
54
Ni
78
70
10
60-70
35-41
42
32
32
0
330
277
16
.
-
-
no
-
42
Zn
648
227
65
200-320
53-93
71
329
66
00
2400
552
77
733
-
47
ll?0
-
56
Fe Pb
119
23
81
1000- I 1HU 40- m
15U-I77 11-19
85 /3
117
60
49
1540 ?»0
416 16
73 93
210
-
4S
65HO 170
-
69 51
-261-

-------

                          r', \ '   '.
                        * *.  •'
3.00   10. X   40.30   W. 00
         : INDUSTRIAL BY
                                                  W.OO
                                                         100.00
  FIGURE  111-27 INFLUENT  COPPER  CONCENTRATIONS  To WASTEWATER TREATMENT
                   PLANTS As A FUNCTION  UF PERCENT INDUSTRIAL  FLOW

     Table 111-40 summarizes  removal efficiencies of a number of the pollutants as a
function of different  types of treatment.  There Is a significant increase in per-
centage removal  between  primary  treatment plants and secondary activated sludge
treatment plants for  each  of  the pollutants  in the table.

3.9.2  Industrial  Waste  Loads
     Compared  to municipal discharges,  effluent levels from industrial  sources are
less easily predictable  because  of  the  variety of categories and treatment processes
used.  Table 111-41 shows  35  major  industrial categories and frequently detected
priority pollutants associated with the categories.  Keith and Tel Hard (1979) have
estimated the  frequency  of occurrence of the priority pollutants 1n Industrial
wastewater.  Their results were  shown previously In Table 11-3.  If Industrial wastes
are thought to contribute  a significant percentage of pollutants to the water body
being analyzed,  the user should  try to  obtain more specific data on the industries
present.  Local  agencies can  provide effluent data for the Industries 1n question.
However, the industries  may not  be  required  to monitor for the specific pollutant(s)
of concern.  The Effluent  Guidelines Division of the U.S. EPA can also provide
guidelines for specific  categories  of pollutants.  They  have developed extensive
documentation  for each major  industrial category.  The "treatability manual" (USEPA,
1982 .  b, c, d)  is one such source  that contains data related to approximately 200
pollutants associated with industrial processes.  The manual contains the following
information:
                                        -262-

-------
                                  TABLE  111-36

   ;NF: ,ENT LIABILITY ANALYSIS  AT  MOCCASIN BEND WASTEWATER TREATMENT PLANT


3. -,-.-*-
. : . i : . 1 j j
3C icr. lor : benzene
,4-3ii-lsracer.zen«
Nap.-.thiiene
3is. :-£:!-.>• Ihexyi;
Pnthalate
3:-^-3_zvl ?s.tw.a'»te

?her.d.-.-.-.r«r.e
"e:ils
rhrc.r. :.a
Copper
Cyar. :c*
-eriury -g. 1)
N ' 1 C < « 1
Silver
Zir.c
Carver.: :or.al
3CC£
TSS"
1 Inf'.uent variability i
30
w
'-* t

13
:o
• T

i
23
88
1^1
25
52

201
5

17
2
5
4 1

12
5

^

225
77
83
303
73
5
332

303
232
inalvs
-~av Srud%-
Stancard
,'._j l'~"

\ .
-9
1 £
JO
1
18
86
325
51
87

155
7

22
6
8
11

15
14
8
2

527
25
84
270
76
2
164

115
93
is conducted on on
S-.x-: •-.-
lean


i -
4 "•
_•}


T
20
40
378
10
81

—a
2

100
1
i*
55

U
^
6
3

226
123
4747
333
98
21
486

435
327
oritv toxic ooi
:;.z-
-;.*?;*::.
_, c

3
— ?
" 3
i 7

• 7
30
236
^ ^
52

:c9
T

45
i
3
-5

7
•>
3
«

160
:»
loo-.
815
37
7
132

112
95
lutar.ts Qt:tc:td
  50 ptrctnt  of  th«  tia* or fr«at«r in addition to l«ad and cacr.iua  for  comb.r.«d
  36-day  period.
2 Cutl.er values were removed from data base.
                                    -263-

-------
                               TABLE  II I-37


              SELECTED POLLUTANT MASS PERCENT REMOVALS AT

               MOCCASIN BEND WASTEWATER  TREATMENT PLANT
                                                     Percent Ree»val
     Pollutant
              1
                              Primary
                              Treatment
                                                        Secondary
             Overall
Treatment   Treatnent
Volatiles
Benzene
1,1,1 -Tr ichlorethane
Chlorofora
1 ,2-Trans-Dichloroethylene
Etbylbeozene
Methyl en* Chloride
Tetrachlorethylene
Toluene
Trichloro«thylane

Acids
Phenol
2 ,4-Dichlorophenol

Base/Neutrals
1 . 2 , 4 -Tr ich 1 o robexuene
1 , 3-Dichlorob«ai«a«
Naphtha l«n«
Bii(2-Ethlyh«jtyl) Phthalac*
Di-S-Butyl Phthalat*
Di«thyl Phthalat*
?h«rvanthr«a«

Conv«nt iona 1 /Non-Convent local
BOOS
TSS"
                                                25
                                                 0
                                                21
                                                 0
                                                12
                                                21
                                                 0
                                                17
                                                IS
                                   7
                                  13
                                   1
                                   0
                                   0
                                  16
                                  25
                                  10
                                  42
                                  12
                                  14
                                   0
                                   0
                                   0
                                  40
                                   0
                                   0
                                  10
                                  30
                                             95
                                             75
                                             15
                                             69
                                             100
                                             49
                                             83
                                             70
    78
    80
    56
   100
    89
    47
    88
    86
    78
                                              92
                                              46
     79
     30
     88
     92
     77
      6
     36
     36
     86
     82
               56
               79
               80
               11
               69
              100
               49
               86
               75
 80
 82
 56
100
 87
 55
 91
 87
 87
               91
               47
 82
 40
 88
 91
 57
 44
  0
  0
 88
 87
 1 Priority toxic pollutants  listed w«r« detected  ia the influent wastewater
  50 percent of the tiSM or  greater  (with  the exception lead and cadBiuoi which
  were detected 46 percent of  the tis»e).
 2 Percent  r
  alone.
val based on MSS reaoval in activated sludge treatment units
                                    -264-

-------
                 TABLE 111-38






1981  EFFLUENT CONCENTRATIONS FROM FIVE SOUTHERN



    CALIFORNIA WASTEWATER  TREATMENT PLANTS
Hvoerlon

Flow MGD
General Constituents
(mg/1)
Suspended Sol Ids
Settled Sol Ids
BOO
011 * Grease
NH3-N
Organ1c-N
Total -P
MBAS
CN
Pnenols
Turbidity
Toxlcity (T.U.)
Trace Metals (*g/l)
Ag
As
Cd
Cr
Cu
Hg
Nl
Pb
Se
Zn
Chlorinated Hydro-
carbons (**g/1)
DOT

PCB
TICH
•except as noted
••Total solids
JWPCP
364


167
0.3
202
23.3
39.3
14.0
9.2
5.37
0.08
2.85
79
4.2

8.0
5.0
16.0
11.0
154.0
1.8
148.0
0.0
29.0
500.0


0.84

0.54
1.61

5 mile
369


77
0.9
169
22
16.1
7.3
6.9
4.12
0.08
0.06
63
0.81

25.0
12.0
17.0
54.0
200.0
0.7
108.0
50.0
1.0
217.0


0.050

0.76
0.94

7 mile
(Sludge)
4.72


7,100**


353
.
266
214
.
0.442
0.37
-
-

739.0
183.0
892.0
3.340.0
9,320.0
36.0
2,400.0
2.000.0
44.0
11.800.0


0.58

3.05
4.68

Orange
County
212


119
1.1
151
21.1
25.7
-
-
.
0.04
0.09
79
1.0

13.0
3.0
26.0
82.0
248.0
0.4
69.0
74.0
.
220.0


0.02

1.55
1.56

Point
Loma
130


114
0.95
161
29.3
27.7
-
-
4.38
0.013
0.073
53
1.3

13.0
5.0
8.0
43.0
133.0
0.8
7.5
136.0
.
190.0


0.084

0.665
0.816

Oxnard
17.7


56.9
<0.1
114
12.2
17.0
5.09
.
.
0.001
0.10
44
2.1

3.0
20.0
3.0
0.1
93.0
0.05
6.0
11.0
-
91.0


Not de-
tected
<0.033
<0.033

                    -265-

-------
                        TABLE  111-39

         OCCURRENCE OF  PRIORITY  POLLlfTANTS  IN POTW
      INF..-NTS AND EFFLUENTS  FOR  POLLUTANTS DETECTED
IN AT LEAST  10 PERCENT  OF  THE  SAMPLES (BURNS AND  ROE,  1982)
Parameter
Z1nc
Cyanide
Copper
Toluene
Chromium
Tetrachloroethylene
Methyl ene chloride
b1s( 2-Chloroethoxy)methane
Chi o reform
TMchloroethylene
1 ,1,1 -Trie hi oroethane
Ethyl benzene
Nickel
Phenol
Silver
Mercury
Di-n-butyl phthalate
Lead
1 ,2-trans-D1ch1oroethy1ene
Benzene
Butyl benzyl phthalate
Cadmi urn
01 ethyl phthalate
Napthalene
1, 1-01 chl oroethane
Pent ac hi orophenol

Number of
Sampl es
Analyzed
282
284
282
288
282
288
288
287
288
288
288
288
282
288
282
282
287
282
288
288
287
282
287
287
288
287

Number of
Times
Detected
282
283
281
276
268
273
266
265
263
260
244
231
224
220
208
196
185
176
179
175
165
157
151
142
89
84
INFLUENT
Percent of
Sampl es
Where
Detected
100
100
100
96
95
95
92
92
91
90
85
80
79
79
71
70
64
62
62
61
57
56
53
49
31
29

Units
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ng/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/l

Minimum
Value
Detected
22
3
7
1
8
1
1
2
1
1
1
1
5
1
2
200
1
16
1
1
2
1
1
1
1
1

Maximum
^al.e
9250
7580
2300
13000
2380
5700
49000
670
430
1300
30000
730
5970
1400
320
4000
140
2540
200
1560
560
1800
42
150
24
640
                             -266-

-------
TABLE 1 1 1-39
(Continued)
Parameter
>-8HC
1,1-Dichloroetnylene
1 ,2-01 chl orobenzene
Phenanthrene
Anthracene
1 ,4-Dichl orobenzene
Arsenic
1 ,2-Dichl oroethane
Antimony
Chl orobenzene
Dimethyl pnthalate
Methyl chloride
1 ,2,4-Trichl orobenzene
2, 4-Dimethyl phenol
Parameter
Cyanide
Zinc
Copper
Methyl ere chloride
Chromi urn
bis(2-Ethylhexyl) phthal ate

Number of
Samples
Analyzed
288
288
287
287
287
287
282
288
282
288
287
288
287
288

Number of
Samples
Analyzed
276
289
289
302
289
302

Number of
Times
Detected
75
74
67
57
52
49
43
42
39
36
33
33
28
28

Number of
Times
Detected
268
272
263
260
247
254
INFLUENT
Percent of
Sam pi es
Where
Detected
26
26
23
20
18
17
15
15
14
13
11
11
10
10
EFFLUENT
Percent of
Samples
Where
Detected
97
94
91
86
85
84

Units
ng/1
ug/l
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/1
ug/l
ug/1

Units
ug/1
ug/1
ug/l
ug/1
ug/l
ug/l

Minimum
Value
Detected
20
1
1
1
1
2
2
1
1
1
1
1
3
1

Minimum
Value
Detected
2
18
3
1
2
1

Maximum
Value
3900
243
440
93
93
200
80
76000
192
1500
110
1900
4300
55

Maximum
Value
2140
3150
255
62000
759
370
-267-

-------
TABLE 1 1 1-39
(Continued)
EFFLUENT
Number of
Samples
Parameter Analyzed
Chi oroform
Tetrachloroethylene
Nickel
Toluene
01-n-butyl phthalate
1,1,1-Trichloroethane
TMchloroethylene
v-BHC
Mercury
Phenol
Cadmi urn
Silver
Ethyl benzene
Benzene
Lead
Pentachl orophenol
01 chl o rob romone thane
01 ethyl phthalate
1 , 2-t rans-01 chl oroethyl ent
Antimony
Arsenic
Butyl benzyl phthalate
Selenium
1 ,l-01ch1oroethylene
302
302
289
302
302
302
302
303
288
302
289
289
302
302
289
301
302
301
302
289
289
302
289
302
Number of
Times
Detected
247
239
216
160
1S8
157
137
99
86
87
81
73
73
69
61
63
47
39
39
37
35
34
29
29
Percent of
Samples
Where
Detected Units
82
79
75
53
52
52
45
33
31
29
28
25
24
23
21
21
16
13
13
13
12
11
10
10
ug/l
ug/l
ug/1
ug/l
ug/l
ug/l
ug/l
"9/1
ng/i
ug/l
ug/l
ug/l
ug/l
ug/l
ug/l
ug/l
ug/l
ug/l
ug/l
ug/l
ug/l
ug/l
ug/l
ug/l
Minimum
Value
Detected
1
1
7
1
1
1
1
10
200
1
2
1
1
1
20
1
1
1
1
1
1
1
1
1
Maximum
Value
87
1200
679
1100
97
3500
230
1400
1200
89
82
30
49
72
217
440
6
7
17
69
72
34
150
11
-268-

-------
                      TABLE  111-40

    MEDIAN PERCENT REMOVALS  OF  SELECTED POLLUTANTS
THROUGH POTM TREATMENT PROCESSES (BURNS AND ROE,  1982)
Parameter
600
Total suspended sol Ids
Cadalua
Chroalui
Copoer
Cyanide
Lead
Mercury
Nickel
Silver
Zinc
Beniene
bls(2-Ethylhexyl)phthatate
Butyl bcniyl phthalate
Chloroform
Dt-n-butyl phthalate
Otethyl phthalate
Ethyl beftiene
Primary
(12)
(12)
(6)
(12)
(12)
(12)
(1)
(8)
(9)
(«)
(12)
(8)
(12)
M)
(ID
O)
(1)
02)
19
4S
IS
27
22
27
67
10
14
20
27
25
0
62
14
36
56
13
Secondary
Activated
Stud**
(22)
(22)
(*)
(22)
(22)
(22)
(2)
(8)
(IS)
(5)
(22)
(10)
(8)
(2)
(20)
(«)
(2)
(10)
90
90
as
84
84
(2
82
76
34
83
81
77
62
94
62
68
91
90
Secondary
Trickling
Filter
(S)
(S)
(1)
(3)
(S)
(S)
(1)
(2)
(2)
(2)
(5)
(3)
(S)
(1)
(SI
(5)
(0)
(*)
77
78
II
48
49
S7
20
56
47
S&
43
80
24
70
7S
SO
-
90
Secondary
0? Activated
S)ud4e
(3)
(3)
(2)
(3)
(3)
(3)
(1)
(3)
(2)
(2)
(3)
(2)
(3)
(3)
(3)
(1)
(0)
(3)
91
84
83
76
92
80
97
83
IB
80
ttl
87
64
84
SO
98
-
86
Secondary
(totaling
Biological
Contactors
(1) 92
(1) S8
(0) -
(0) -
(I) 97
(1) 96
(0) -
(0) -
(0) -
(0) -
(U 81
(0) -
(1) «6
(0) -
(0) -
(0) -
<0) -
(0) -
Secondary
Aerated
lagoon
(1)
(1)
ID
(1)
(1)
(1)
(1)
ID
ID
ID
(»>
(0)
(I)
ID
(0)
(1)
(0)
(1)
80
77
44
49
21
7
0
0
14
0
SI
-
23
93
-
SO
-
83
Parallel
Activated Sludye/trh
filter Plants
Activated
Sludne Side
«)
(4)
(2)
(4)
(4)
(4)
(0)
(2)
(4)
(2)
(4)
(I)
(4)
(1)
(1)
(1)
(0)
(3)
92
94
91
75
89
66
-
91
34
79
82
92
B7
80
75
97
-
97
Trkl
Flltei
(4)
(4)
(2)
(4)
(4)
(4).
(0)
(2)
(4)
(2)
(4)
(»
(4)
(1)
(4)
(3)
(0)
(4)
:kliny
illny
r Side
tt?
91
84
63
75
6tt
-
49
0
83
73
92
72
93
69
SO
-
89
Tertiary
IB)
(»)
(3)

-------
                                                                 TABLE  111-40
                                                                 (Continued)
         Parameter
                                                  Secondary
           Secondary   Secondary     Secondary      Rotating
           Activated   Trickling    0? Activated    Biological
•rleary     Sludge*       Miter      Sludge	Contactors
                    Parallel
            Activated  Sludge/trickllm)
Secondary         filter  flints
 Aerated    "HeTFvaTidTrickling
 lagoon     Sludge Side     Filler Side
!*_r-Ll*ri
Hethyiene chloride
Napthalene
Phenol
Tetrachloroethylane
Toluene
Trlchloroethylene
l.l.i-Trfcliloroethane
t , 2 -t rans -01 d» loroethy 1 ene
(12) 0
(4) 44
(It) 8
(12) 4
(12) 0
(12) 20
(10) 40
(9) 36
(M)
(6)
(15)
(20)
(21)
(20)
(17)
(19)
48
92
89
82
93
90
88
80
(S)
(0)
(0)
(S)
(S)
(S)
(S)
(4)
76
-
-
82
88
96
92
97
(3) 34
«0)
(3) 99*
(3) 75
(3) 99«
(2) 67
(3) 80
(2) 85
(0)
(0)
<»)
(U
(I)
0)
(0)
(0)
.
-
99»
50
99»
67
-
-
(1)
(0)
ID
(I)
(»
(1)
(1)
(0
96
-
50
91
89
97
91
88
(4)
(0)
(3)
(4)
(4)
(4)
(3)
(0)
52
-
89
76
97*
97
99*
-
(4)
(U)
(3)
(4)
(4)
(4)
(3)
(0)
„
-
94
b?
93
95
91

(«)
<4)
(b)
(8)
(«)
(/)
(/)
(3)
78
M
95
94
90
9/
%
W
*POTN 8. prcdoMlMntly (96 percent)  «ctlv«ted  sludge. MS  Included In the «ctlvtted sludge pUntj.

Note:  Nu»ber tn (  ) Is niMber of plants  with  c«lcul*tcd reao««ls.

       Only pltnts  with «ver«9« Influent  concent rat Ions gretter than three tl»es the oast frequent  detection  Mail of e«ch pollultnt are tn-

       cluded In re*o««l  calculations.
                                                                  -270-

-------
                                         TABLE  111-41


                       INDUSTRIAL CATEGORIES AND FREQUENTLY DETECTED

                              PRIORITY POLLUTANTS BY  CATEGORY
                     ill
*!
in
!!£
15
              r
-'2

III
ill
                                           H
                                                       i
                              i;a
                                                                          IT
M
                                 =ii!l£

      • * * i'C
      _ ^ ..if.Si
     l*lrw»l*ri«t
                                                                                  i  i
I.I.I
i.r
1.}
{.<
•if*
MCMMlW*
    *t*tyl
                                                                                      T T
                                                                                      ii^
Oi-»-«ctrl (HtMl«l«
                                                                                     TT
                                                                                     T J  I
'•(•
C •«•>••
ll
                                           -371-

-------
     
-------
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                                      -273-

-------
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Heaney, J.P. and  W.C. Huber,  1979.  Nationwide Cost of Wet-Weather Pollution
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                                        -274-

-------
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                                       -275-

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                                      -278-

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Weber J.B., 1975.  Agricultural Chemicals and Their Importance-as a Nonpoint
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     A Guide to Conservation Planning.  Agriculture Handbook  No.  537.  U.S.
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                                     -277-

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                                       CHAPTER  4

                                   RIVERS AND STREAMS
4.1  INTRODUCTION
     The purpose of this chapter Is to present simplified tools which c*n be
used to predict responses of rivers and strews to the Impact of pollutants.  The
introductory sections to the chapter should be read prior to solving any problems 1n
order to become familiar with the topics that will be covered and the limitations of
the formulations presented.
     Rivers throughout this country are subject to a wide spectrum of geological,
biological, cllmatolog leal, and anthropogenic Impacts which produce a variety of
water quality problems.  Approaches which provide guidance to the solution of these
problems, especially ones restricted to hand calculations, must be limited In scope.
The following guidelines have been used In selecting topics to be considered in this
chapter:  1. widely occurring problems, 2. those amenable to hand calculations, and
3. those for which planners can obtain sufficient data.

4.1.1  Sco
     The major problem areas to be considered are:
        e    Carbonaceous (CBOO) and nitrogenous (NBOO) biochemical oxygen demand
        e    Dissolved oxygen
        e    Temperature (with a discussion of low flow)
        e    Nutrients and eutrophteat Ion potential
        e    CoHform organisms
        e    Conservative constituents
        e    Sedimentation and suspended solids
        e    Toxic substances.
     Beginning 1n 1974, the U.S. Environmental Protection Agency has for several
years published the National Hater Quality Inventory which Is a compilation of
current water quality conditions and recent trends 1n the nation's rivers and lakes.
Several of the tables 1n that report series are relevant to this document and are
included here.  Table IV-1 Illustrates reference water quality levels used to de-flne
acceptable pollutant limits In U.S. waterways.  Table IV-2 shows water quality
conditions in eight major waterway* In the united States, while Table IV-3 summarizes
the most widely observed water quality problems 1n the U.S.  These tables will be
cited throughout this chapter.
     Local water quality standards, when they exist, are preferable to the general
guidelines provided in Table IV-1.  Table IV-4 shows exwple standards for dissolved
oxygen and water temperature for the states of Virginia and Maryland.  Parts of the
                                         -278-

-------
                                       TABLE IV-1
                    REFERENCE LEVEL VALUES OF SELECTED HATER QUALITY
                     INDICATORS FOR U.S.  WATERWAYS (U.S.  EPA, 1976}
               Parameter                         Reference Level
           Ammonia                          <_ 0.02 mg/1 as unionized ammonia
                                            ~      (for freshwater aquatic life)
           Color                            <_ 75 platinum-cobalt  units (for
                                                 water supply)
           Dissolved Oxygen                 I5-0 ffl9/1 (to maintain  fish
                                            ~     populations)
           Dissolved Solids                 <_ 250 mg/1 (for water supply)
           Fecal  Conforms                  log mean <_ 200 ptr ml over 30 days
                                            and 90 pefctnt <. 400  ptr ml (for
                                            bathing waters)~
           Nltrate-N                        <_ 10 mg/1  (water supply)
           pH                                between 6.5 and 9.0 (for freshwater
                                            aquatic life)
           Phenols                          <_ 1 ug/1 (for water supply)
           Suspended Sol ids and             shall not  reduce the  depth of the
            Turbidity                      compensation  point by more than
                                            10 percent (aquatic life)
           Total  Dissolved Gases            < 110 percent saturation (aquatic
                                                  life)
standards are significantly different from the reference levels In Table IV-1.   For
example the dally average dissolved oxygen standard for natural trout water for the
state of Virginia Is 7.0 mg/1, while S.O mg/1 Is recommended for the protection of
aquatic lift (Table IV-1).  Thus, whtn local standards exist, they should be used In
lieu of general reference levels.
4.1.2  Significance of Problem Areas
     Oxygen depletion Is ofttn the rtsult of excessive CBOO and N600 loadings par-
ticularly In combination with high temperature and low flow conditions.  Increased
nutrient loadings to streams which product elevated ambient conctntratIons can post
substantial potential for tutropMcatlon. The nutrient problem 1s currently ont of
the most widespread areas of conctrn regarding river water quality.  The health
                                         -279-

-------
  River
                                          TABLE   IV-2

                         CONDITION OF  EIGHT MAJOR WATERWAYS (EPA.1974)
  Har-Mful
 SubsUnces
    Physical
  Modification
 Eutrophicatton
   Potential
Mississippi
Missouri
Onto

Detroit are*
rivers
ColuMbta
Snake
UillaMtte
Trace wtals
present in Middle
river

High*, increasing
iron and
Manganese
Cyanide  present
but dtMtshtng
Severe gas super
saturation; SOM radio-
activity In lover river
Severe gas super-
saturation, signif-
cant pesticides
Significant sulfite
waste liquor fro*
pulp and paper wastes
High* turbidity and
solids below
Missouri River

High* suspended solids.
turbidity in Middle and
lower river

High* suspended solids
in lower river. sone
iMproveMents
Suspended solids
iMproving. local
teMperature effects
froM discharges

Occasional high*
temperatures
Turbidity froM
natural erosion,
agricultural practices.
reservoir flushing

High* turbidity at
high flow, high
tenperature in suMner
High*, increasing
nutrients but no
algae

High*, increasing
nutrients but no
algae

High* nutrients but
no algae
Snail Increase in
nutrients but no
algae

Nutrients discharged
to Lake Erie
decreasing
High* nutrients but
no algae, except for
sliMe growths in
lower river

Nuisance alga)
blooMS each
si
High* level of
nutrients but
not excessive algae
                                               •280-

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                                     TABlt IV-2 (continued)
  River

Mississippi
Missouri
Ohio
Tennessee
Detroit area
rivers
Columbia


Snake



UillaMtte
 Salinity, Acidity,
   and Alkalinity	

High* salinity, acidity
below Major
tributaries
High* dissolved salts
in aiddle and lower
river

Low* alkalinity
especially in upper
river
     Oxygen
    Depletion
 Health Hazards and
Aesthetic Deqraualion
Acids and chloride low,*
{•proving despite
large discharges

Approaches  ideal
for  fresh waters

High* dissolved
solids  fro* irrigation
in Middle river

Low* dissolved Mineral
salts,  improved pH
Oxygen-demanding
loads from large
cities evident
High* organic loads
from feedlots,
improved near cities

Occasional low*
dissolved oxygen near
Cincinnati and Pittsburgh

Low* BOO  and
decreasing COO in
reservoirs

Low* dissolved oxygen
only at Mouths of
area tributaries

Dissolved oxygen
close  to saturation

Dissolved oxygen
close  to saturation
 iMproved dissolved
 oxygen, no standards
 violations
Commercial fishing
eliminated in lower
river by phenols,
bacteria near cities

High* bacteria and
viruses present in wet
and dry periods

High* bacteria especially
in high population
areas

High* bacteria in small
areas near cities, low
radionuclides

Phenols decreasing,
bacteria unchanged-
to-higher

Very  low* bacteria
High* bacteria
below population
centers

High* bacteria, but
improving
*High (or low) relative to other rivers, or relative to other sections of river,  or to
 national reference levels.  Does not necessarily imply standards violations or
 dangerous condition.
                                                   •281-

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                                       TABLE IV-3
                     WATER QUALITY PROBLEM AREAS REPORTED 8Y STATES*
                       •JUMBcR RE PORT! i.G PROBLEMS/TOTAL (EPA, 1975)

deoletv.-
Eutropm-
cation
potential
Health
hazards
Sal inity,
acidity.
alkal inity
- ' 1 i r. '. : ; ,
' 'i - * 3
11/13

11/13

3/13
South
5/9
6/9

8/9

6/9
Great
Lakes
6/6
6/6

5/6

2/6
Central
6/3
8/8

8/8

6/8
Southwest
4/4
2/4

3/4

4/4
«est Islands
6/6 4/6
6/6 ./6

5/6 5/6

4/6 2/6
"otal
46/52
43/52

45/52

27/52
 Physical        7/13       3/9      3/6      8/8       3/4       6/6      5/6       35/52
 codification

 Harmful         6/13       6/9      5/6      4/8       4/4       2/6      3/6       30/52
 s^astances

 •  Localized or  statewide  problems  discussed by the States  in  their reports.
hazards category in Table IV-3 lists elevated co11 form  levels as a problem of par-
ticular concern in northeastern and Great Lakes States.  Salinity has been identified
as a major problem In the central and southwestern states.
     Because of their Importance, each of the problem areas described will be addressed
in this chapter.  As shown in Table IV-5, many states routinely measure the parameters
associated with these problems.  The total number of states responding to the survey
was 47.  Because of the routine surveys conducted, data are commonly available for
performing hand calculations. NBOO, though not directly measured, can be found from
measurements of organic and ammonia nitrogen.  Chloride concentration measurements
can be directly converted to salinity.

4.1.3  Applicability to Other Problems
     The tools which are presented In this chapter are designed to address specific
water quality problems.  However, a number of the tools, which are based on the  law
of mass conservation, can be directly applied to other problems with little or no
modification.  In the case of temperature prediction, an energy balance 1s used
(wi--ch is analogous to a mass balance).
                                         •282-

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                                     TABLE  IV-4

                         EXAMPLE RIVER WATER QUALITY STANDARDS
Class
Virginia
III
IV
V
VI
Mary! and
I
III
IV
Description

Coastal and Piedmont
Mountainous
Put and Take Trout Waters
Natural Trout Waters

Water Contact, Recreation
Natural Trout Waters
Recreational Trout Waters
Dissolved
Minimum

4.0
4.0
5.0
6.0

4.0*
5.0*
5.0*
Oxygen
Average

5.0
5.0
6.0
7.0

5.0*
6.0*
5.0*
Temperature, *F
TM TMAX

5 90
5 87
5 70
5 68

90**
68**
75**
       *These  values  apply except where  lower  values occur naturally.
     **These  apply outside the mixing zone.   If natural temperature of receiving
       water  is  greater than the standard, then that becomes the standard.	

     The degree of commonality of source and  sinks of  a particular  pollutant  (e.g.,
a nutrient) or water quality Indicator (e.g.,  dissolved oxygen)  is  responsible  for
the similarities and differences among the specific equations.   For example,  CBOO and
NBOO produce a similar general effect (oxygen  depletion),  generally have  similar
sources and sinks, and for purposes of this study are  assumed to follow first order
decay kinetics.  Conforms,  also assumed to decay by first order kinetics,  are
handled by the mass-balance approach.  Conservative substances  are  different  from
BOO and conforms In that they do not decay.   Finally,  there are some  Instances where
a more subjective analysis 1s Indicated and neither a  mass nor  energy  balance 1s
presented.
     Once the similarities among water quality parameters  are understood, handling
two seemingly different problems can often be  accomplished In a  straightforward and
similar fashion.   For example, the  distribution of toxic substances that  are  either
conservative or follow a first order decay may be evaluated  using techniques  described
for conservative substances  and conforms, respectively.

4.1.4  Sources of Pollutants
     Pollutant loadings originate from three general sources: point,  nonpolnt, and
natural.   Each of these can  constitute a major hurdle  In meeting the 1983 goals of

                                         •283-

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                                       TABLE IV-5
                                WATER QUALITY PARAMETERS
                        COMMONLY MONITORED BY STATES* (EPA.1975)
                                                      Number
                Parameter                            of States

              Flow                                      47
              Dissolved oxygen                          47
              Conform bacteria                         45
              Nitrogen (any form)                       39
              Phosphorus (any form)                     35
              pH                                        35
              BOO/COO/TOC                               27
              Water temperature                         29
              Turbidity                                 26
              Solids (any type)                         27
              Metals (any type)                         17
              Chlorides                                 19
              Alkalinity                                IS
              Conductivity                              16
              Color                                     11
              Sulfate                                   14
         *0n1y parameters listed by at least 10 States and specified as being
         part of each State's monitoring program are Included.

flshablc and swlmmable waters.   Specifically,  point  sources (30  states), nonpolnt
sources (37 states), and natural conditions (21 states)  are all  major contributors to
water quality problems (EPA.  1975).
     It Is imperative that the  capacity to assess  Impacts  of  nonpolnt sources be a
part of the hand calculation methodology for rivers.   Table IY-6 Illustrates the
Importance of nonpolnt source nutrient loading for selected rivers  In Iowa.  Up to 96
percent of the annual phosphorus load and up to 99 percent of the total  nitrogen  load
are from nonpolnt sources. Admittedly, quantification of nonpolnt source loads  Is
often difficult. Nevertheless,  simplified nonpolnt source terms  will be Included  in
some of the mass-balance formulations.  The methodology supplied In Chapter  III can
be used to estimate the nonpolnt source loading rates.

4.1.5  Assumptions
     In deriving the mass-balance equations, a number of asswptlons were made.
Users  should be aware of each assumption so that the tools are not  misapplied.  The

                                         -284-

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                                       TABLE IV-6
      ANNUAL  PHOSPHORUS AND NITROGEN LOAD FOR SELECTED IOWA RIVER BASINS {EPA,1975)
River
PHOSPHORUS
Floyd
Little Sioux
Char i ton
Des Moines
Iowa
Cedar
NITROGEN
Floyd
Little Sioux
Chariton
Oes Moines
Iowa
Cedar
•Orthophosphate
Total
(Ibs/year)
720,207
1 ,851 .632
879,916
5,621,007
1,723,975*
5,099,507
1,705,984
9,609,556
1,585.427
41.334,897
2,075.830
6.804,881
Point Sources
(Ibs/year)
29,807
129,088
48,203
586,015
103,445*
1,526.775
65.171
85.308
24,795
695,235
91.287
1,552,334
Percent of
Nonpoint Sources Total from
(Ibs/year) Nonooint Sources
690,400
1,722,544
831,713
5,034,992
1,620,530*
3,572,732
1,640,813
9.522.248
1.560,632
40.639,662
1,984,543
5,252,547
95.9
93.3
9C.5
S9.6
94.0
70.1
96.2
99.1
98.4
98.3
'95.6
77.2
most important assumptions are:
        •    The system is at steady-state.
        e    Dispersion is small compared to advection (I.e., plug flow is assumed).
        e    The river system is vertically and  laterally mixed.
        e    When pollutants decay, the rates are first order.
     The steady-state assumption Mans that conditions are not changing with time,
but only as a function of distance along the river.  The time scale or steady-state
generally should be on the order of a week or longer.  For example, the summer  low
flow period generally represents a steady-state  situation.  However, storm events, and
the dynamic responses of a river to them, must be considered a transient phenomenon.
     Dispersion effects can usually be neglected when pollutant  Input  into a river  is
continuous.  Under these conditions the plug flow assumption  is  reasonable because
the net dispersive transport  1s small.  However, when a slug of  pollutant Is dis-
charged instantaneously, dispersive transport Is Important since high concentration
gradients exist around the centrold of the discharged pollutant.
     The fully-mixed assumption presupposes that concentration gradients exist  only
In the direction of flow (longitudinal direction) and not  In either the vertical or
                                          285-

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lateral direction.  Tht final major assumption 1s that all decay rates can be approxi-
mated by first order kinetics.  This means that the decay rate of a substance 1s
proportional to the amount present.  First order decay 1s traditionally used 1n CBOO
computations, and occasionally in nitrogen oxidation.  The oxidation of inorganic
nitrogen actually prcr«eds in stages from ammonia-N to nitr<».«-N to nltrate-N.
However, for purposes of this report, the first order decay rate is acceptable for
N800 and conforms, as well as CBOO.  Before applying first order decay to other
substances, however, care should be taken to determine the validity of the assumption.
     For a few of the analyses which follow, several of the aforementioned assumptions
are relaxed.  In the discussion of mixing zones. Section 4.1.9, partial mixing is
discussed for wide rivers.  In the discussion on toxicants. Section 4.9, the spill
analysis requires that an unsteady- state situation be analyzed where the effects of
dispersion are Included.

4.1.6  Data Requirements
     Required in the analysis of most water quality problems  are one or more
types of data.  For example, strew velocity (U), volumetric  flow rate (Q), and
stream temperatures (T) are commonly needed.  Decay rates, specific to the particular
problem at hand, are also required.
     The U.S. Environmental  Protection Agency  has published two  documents (Bowie et
al_.. 1985  and Zison et. aj...  1978)  Intended  to  provide water quality modelers  with  a
comprehensive source of Information on rate constants and coefficients.   The  document
provides extensive Information on  both biological and water quality parameters  commonly
used in surface water modeling.  The contents  of the  document will be  useful  to tha
users of this document who are often faced  with  limited  information on process  rates
for the water bodies being analyzed.
     Stream  velocity 1s the most basic hydraulic parameter needed for  the analyses
presented  in this chapter.   Ideally, the  appropriate  stream velocity  1s the travel
time of neutrally buoyant particles over  the reach being  Investigated  divided by the
distance traveled.  Note that this concept  of  velocity  is different from  the  velocity
determined by:
 As defined by Equation IV-1, this concept of velocity exists only at the point  in  the
 river where the cress* sectional area is A.  If the point of measurement 1s not
 typical  of the reach being Investigated, then neither will  the velocity be typical.
 Consequently, should the user predict stream velocity based on cross- sectional  area,
 a loci'.ion typical of the Hver reach being Investigated should be chosen.
                                          -286-

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     An alternate method of predicting stream velocity, which does not depend on
either flowrate 0 or cross-sectional area A is Manning's Equation. A complete des-
cription of the use of this approach is given in many texts on surface water hydraul-
ics, one cf the best being Chow (1959).
     According to Manning's Equation stream velocity under uniform flow conditions is
expressible as:
where
        n   *  Manning's n
        S   -  slope, ft/ft
        RH  «  hydraulic rad* .$, ft.
Manning's n is the roughness of the stream bed, and can be predicted as outlined in
Chow (1959).  Barnes (1967) provides roughness data for 90 streams In the United
States, and includes cross-sectional areas and photographs of the streams investi-
gated.  The slope can be estimated using topographic maps to predict elevation
changes between two  locations and then overlying a string over the stream path to
predict distance.  The hydraulic radius (which is the ratio of the cross-sectional
area to wetted perimeter) can be estimated in terns of depth when the stream width is
much greater than the depth.  Specifically:
                 {depth, if channel cross-section is rectangular

                 2/3 maximum depth, if channel cross-section 1s parabolic
4.1.7  Selection of Season
     It is reasonable to expect that a particular water quality problem may be
more severe at one time of the year than another.  Table IV-7 shows that pollutant
levels can depend on season (summer or winter) and flow rate (high flow or low flow).
Dissolved oxygen problems, for example, are clearly associated with summer, low flow
conditions.  Consequently, for any particular pollution problem, users should strive
to perform the analysis under critical conditions.  Where planning Is performed with
consideration of the aggravated situation and where proper abatement action 1s taken,
it 1s likely that pollution concentrations will be below problem levels during other
times of the year.  If a problem In fact exists, then 1t 1s under these conditions
that it will be most pronounced.
     In the following sections, hand calculation methods for each problem area are
described with Illustrative examples.  Table IV-8 provides a summary of the material
presented.
                                         -287-

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                                                   TABLE  IV-7

                      MAJOR WATERWAYS:  SEASONAL  AND ROW ANALYSIS.  1968-72 (EPA,  1974)
    Parameters
Suspended solids
Turbidity
Color

AWMMIta
Nitrite
Nitratefas N)
Nitratejas NO,)
Nitrite plus nitrate
Or9«nic nitrogen
lot*I Kjeldahl nitrogen
loul phosphorus
ToUl phosphate
Dissolved phosphate

Dissolved solids(IOS°C)
Dissolved solids(>80°C)
Chlorides
Sulfates
Alkalinity
ph

Dissolved oxygen
BOOc
COO (.02SN)

Total colifonM(NFD)*
Total coliforas(Hfl)*
Total colifonHJNPN)*
fecal coliform(HF)*
fee*I coliforasJHPN)*
Phenols
Odor
 Winter.
High flow
    9
   13
   II

   14
    3
   I?
    8
    2
    3
    3
   10
    8
    6

    4
    3
    4
    S
    6
   IS

    0
   II
    6

    4
    8
    4
    6
    4
    S
    4
      >        Minter.        Summer.            Dominant
Low Flow   	Low Flow	High Flow	

 (number of reaches exceeding reference levels)**

   S              0             4
   4
               0
                I
 3
 1
 4
 3
 3
 6
 5
 3
 3
 3

 7
 8
IS
13
I?
 4

19
 6
 S

10
 6
 2
 6
 0
 0
 0
 7
 S
 8
 6
 2
 0
 0
 S
 S
 4

 6
 6
10
 S
10
 6

 0
 8
 3

 2
 2
 3
 3
 1
 I
 0
                                 3
                                 3
                                 2
                                 1
                                 0

                                 3
                                 2
                                 0
                                 S
                                 0
                                 4

                                 9
                                 I
                                 2

                                 S
                                 4
                                 3
                                 4
                                 0
                                 0
                                 0
                              High  flow
                              High  flow
                              High  flow
Cold weather
Low flow
Cold weather
Cold weather
Inconclusive
Ham weather
War* weather
Cold weather
Cold weather
Cold weather

Low flow
Low flow
Low flow
Marti weather. low flow
Low flow
Cold weather, high flow

Ham weather
Cold weather
Cold weather

Mam weather
High flow. warn weather
Inconclusive
Inconclusive
Cold weather
Inconclusive
Inconclusive
  •Membrane filter delayed.  membrane  filter  immediate, aost probable motor. ne*t>rane filter

 ••Reference levels are available  in  Table IV-I.  Thirty reaches were analy/ed during each  season.
                                                   •288-

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                                                 TABLE  IV-8

                       •JATER QUALITY  ANALYSES  FOR  RIVER  SCREENING METHODOLOGY
 •aur Quality  Constituent
  CoavuUtlOMl rretedurts
                                                                                                 dn  lnc)»d«d
iMttr  tMPtriturt
Caroonactous and nitrogenous
blocnMical  oxygtn dtaand
OmolvM Oxygen
                                 tquillbriuB ttBptraturt
                                 •txlng ttaptraturt
                                 teapertturt prof tit for point sources
100 prof 11ti  for point tourcts
100 prof Hit  »(th benthlc sourcts added
100 prof Mis  Kith both benthtc and nonpolnt
sourcts added

OOO-N800-00  profi It  for point tourcts
00 profiles Mltn pnotosyntnettc Myftfl
production «nd BtntMc upukt «ddtd
critic*l dtssolvtd oxygtn conditions
•istt 9 nutntnt
nutritnt profDtS for point  sourcts
nutrltnt prof11ts for nonpolnt sourctt
  nitrogtn/phosphorus r»tlos for
  9rontri llalutton
  nonpolnt sourct lotdlng ritti by
  Und ust typt
CoHfom
coll fora profllts for point  sourcts
col I for* profllts for nonpolnt sourcts

btd 1o*d
susptndtd lo*d
toUl load
                                                                             • dtciy rttts
                                                                              •tdlan btd ptrtlclt tilts for
                                                                              nuatrous
                                                                              critic*! shotr strtss
                                                                              itdlatnt transport propensity factor
                                                                              approiiMtt Md loM/wsptnd«d lo«d
                                                                              rtlatlonshtp
Toaicants
UilCMt profllts for point  and
nonpolnt sourcts
MSS  fix* »oUtH1»td, idvtcttd. and
transforatd
spill analysis of loo and high donsttjr
toxicants
tlM  rtqulrtd to d«sort toxicant fro*
btddad sodlMnts
- vapor prtssurt.  solublltty.xunol-
  •attr portion cotffldtnt for
  priority polluUnts
• Honry's L*n Constantr
  4.1.8   River  Segmentation
        Although  the  tools  presented in  this  chapter  are of a  simplified  nature they can
  be used to analyze complex  river  systems  (I.e., those which  have  a number  of differed
  point  and  nonpolnt sources  of pollution,  tributaries and withdrawals).   Analysis of
  these  systems  Is accomplished by  dividing  the  river Into segments.  The basic  tenet
  which  must be  followed  1s simply  this:  Segments are created  so that one of the
  analytical tools presented  in this chapter can be  used  to predict the  pollutant
                                                   -289-

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concentration profile within the segment.
     Analyses of river systems normally begin at a segment where the boundary
conditions are known, and proceed sequentially downstream.  Thus the results found
for one segment are used as the upstream boundary condition for the next segment.
Based on the tools in this chapter, the following rules should be followed when
segmenting:
        1.   Point sources of pollutants enter the river just above the upstream
             boundary of a segment.  Tributaries are treated as point sources.
        2.   Nonpoint sources enter a river throughout the length of a segment.
        3.   Pollutant concentrations at the upstream end of segments are obtained £>y
             mixing the pollutant concentration in the river with the contribution of
             the point source at that location (if one exists).  The location where
             mixing occurs 1s called a mixing r-ne.
        4.   Generally constant hydraulic variables (e.g., depth and velocity)
             are used throughout a segment.  If there is a gradual change in the
             hydraulic variables over distance, an average value can be used.  If
             there is an abrupt change in the variable, such as a velocity chanae
             caused by a significant deepenirg of the channel, then a new segment can
             be created at this boundary.
        5.   Decay rates, reaeratlon rates, and other rate coefficients remain
             constant within a segment.  If rate coefficients are known to change
             significantly from one location to another in a river, then different
             segments should be created.  This rule is consistent with rule  (*),
             •since rate coefficients are often functions of hydraulic variables.
                                  EXAMPLE IV-1
        Figure IV-la snows a stretch of the James River, located in Virginia.  On
   the stretch of the river shown, there 1s 4 tributary (Falling Creek), a sewage
   treatment plant (STP), and a nonpolnt source of runoff (agricultural).  Segment
   the river between locations A and B in order to determine the profile of a
   pollutant which 1s discharged from each of the three sources.
        First, it should be noted that often there Is more than one way to segment
   the river to successfully solve the problem.  The most obvious method will be
   Illustrated here.  Figure IV-lb shows the proposed solution. There are two mixing
   zones - the first around the treatment plant and the second around the tributary
   which Is treated as a point source.  The first  egment Is located from below the
   first mixing zone to above the second mixing zone, and has a nonpolnt source
   discharging throughout the length of the segment, consistent with rule (2).  The
   second segment Is located below the second mixing zone and continues downstream to
                                         -290-

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                                                      JAMES
A
I
' 1
) I
, /
r
> i
' i
i i
i i
• '
AGRICULTURAL 1(jNOfr
I B
                         (a) River Segment  Being Analyzed
                                           MIXING ZONE
                                                   JAMES RIVER
T
A' '
	 " — 1 — — \ — 	 1 — _
• i
1 1




1'
1
1 i
<
1
1
AGRICULTURAL RUNOFF
B
                         (b) Proposed Segmentation Scheme

             FIGURE  IV-1    ILLUSTRATION  OF RIVER SEGMENTATION
                             PROCEDURE ON  THE  JAMES RIVER.
I   location B, wnich is the  end of the nonpoint source.   If Falling Creek  had not       |
:   been present, a single segment and a slnqle mixing  zone would have been sufficient   j
<   to  analyze the problem.                                                            '

L	END OF EXAMPLE IV-1	'
                                        -291-

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     A second,  more  comprehensive example will illustrate a number of points  about
segmentat'on «ct  covered  in  the  previous example.  One of these points is  that  the
seamentat'3" scheme  used  can vary depending on the pollutant being analyzed.
                                 EXAMPLE IV-2
                                                                                  	1
        Segment  the  river  shown  in Figure .tf-2 beginning at location A and  continuing
   to  location B in  order  to determine th« instream BOD distribution.  How  would  the
   segmentation  differ when predicting the dissolved oxygen profile?
        Both  point  and nonpoint  sources discharge to the river in Figure IV-2.
   Several  flows are diverted, and the river width changes over parts of the reach
   being investigated.   Each of  the rules stated earlier will be utilized to segment
   the river  system.  Figure IV-3 snows one solution to the problem. Depending  on the
   distances  between the various sources of pollutants, which are not given in  the
                                        SMALL 0»M
                                                  n
                                                 AGRICULTURE
                                                               CONTI
                                                                          (COW Tl
                                                           ATTACHfO
                                                             ALOAC
                                   •CSCMVOI*
                                                   DIVtHTfO
FIGURE  IV-2
                           HYPOTHETICAL  RIVER HAVING A  VARIETY OF
                           POLLUTANT SOURCES  AND SINKS,
                                         -292-

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                                                                      (COWT)
                                              TTTT
                                               oivearto
       FIGURE  IV-3    RIVER  SEGMENTATION  FOR  BOD DISTRIBUTION,

problem,  it might be possible to combine some of the  segments.  The reservoir  is
assumed  to be  analyzed using the methods 1n Chapter 5,  and  so 1s not segmented.
     Mixing zones are Included around the four point  sources:  the food processing
plant, the tributary, the sewage treatment plant, and the pulp mill.  In segments
9 and 11  there appear to be a number of point sources and diversions.  Strictly
speaking, segments 9 and 11 do not  follow the rules presented earlier, which
require mixing zones around each point source. However,  the point sources and
sinks within segments 9 and 11 are  assumed to represent  equivalent nonpolnt
sources,  which act over the length  of each segment.  This approach can obviously
simplify  the analysis of complex river systems by decreasing the number of segments
analyzed. However, the analysis 1s more approximate  because the nonpolnt source
1s assumed to be uniformly distributed throughout the segment.  Example IV-5
presented later shows a specific application of the concept of an equivalent
nonpolnt  source.
                                     -293-

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         > segment 2 the presence of the small dam  is assumed not to influence
   *.*e 303 arc* Me, so that  its presence does not require a mixing zone. However if
       :-5>c'ved oxygen profile were being calculated, segment 2 would be divided
       .  '»c segments, with a mixing zone around the dam.  This division is required
   Decajse the Dissolved oxygen concentration can rapidly change [almost instantane-
   ously) as the water flows over the dam.  The dissolved oxygen concentration just
   below the dam should be used as the upstream boundary conditions for the next
   segment.  The specific information required to accomplish this is discussed  later
   in Section 4.3.
I         a second difference  in segmenting for dissolved oxygen occurs  in Segment 8.
:   The presence of the attached algae is assumed not to influence the  800 profile,
   but the algae are internal sources of oxygen.  Thus segment 8 would be subdivided
   at -.-e upstream location  of the attached algal growth.
I
I	END OF EXAMPLE IV-2	


4.L.9  fixing Zones
     A mixing zone, as used  in this document, 1s nothing more than a short reach of
a river  where a point source and river water mix.   It is often assumed, for both
simple and more complex approaches (e.g., QUAL-II computer model), that mixing  is
instantaneous and complete across the entire width  of the channel.  With several
exceptions, such an approach  is used in this document.
     Assuming complete mixing, the concentration of a pollutant  in a river after
IP i x i ng is:
                                c . CuQu * Cwqw                            (IV-3a)


                                  . CuQu * M/5.38                          dV-3b)
                                      Qw * Qu

where
         C   «  concentration of pollutant in river  following mixing, mg/1
         C   •  concentration 1n point source, mg/1
         C   •  concentration 1n river above point source, mg/1
         u                                       3
         0   «  discharge rate of point source, ft /sec
                                                              3
         0   »  flow rate of  river above point of discharge, ft /sec
         W   «  pollutant mass emission rate, Ibs/day.
The concentration C is the pollutant level 1n the mixing zones shown in the earlier
Figures  IV-1 and IV-3.  These concentrations become the upstream boundary conditions
for the  adjacent downstream segment.
                                         -294-

-------
            1 J 1 I _L L t 1 IJ L 1 I I I I 1 I I I I I I I I  I I  I I I I I I I I I I I I I I I I 1
       CONTAMINATED
         I I I I I I I I l\l I I I I I I I I I I I I I I I I I 1 1 I I I ( J I I I I I I I I I I I I
       FIGURE
                                                      POINT
                                                     [SOURCE,
                       POLLUTANT  DISCHARGE  WHERE  INITIAL MIXING
                       OCCURS A  FRACTIONAL  DISTANCE ACROSS  THE  RIVER,
     Although it  is  convenient to assume that complete mixing  occurs, this assumption
may be inaccurate for  wide  rivers, depending on the characteristics of the point
source outfall  and diffuser.  Figure IV-4 illustrates such a case.  The river is wide
enough so that  the wastewater is initially mixed with only a fraction of the total
river flow.   As the  po)lutant-riverwater mixture is transported  downstream mixing
continues until the  pollutant is completely mixed across the channel.
     The initial  pollutant  concentration at the point of discharge  is:
                           C «
                                  Q  * - o
                                   *   W gu
where
        Y
        "w
              fractional distance across river where Initial  mixing occurs.
All other variables  have been previously defined.
     The significance of Incomplete Initial mixing 1s that  pollutant concentrations
can be initially much higher than 1f complete mixing occurs.  For  example.  If the
upstream contribution of the pollutant 1s negligible (C   •  0)  and  If the fraction
of river flow which  initially mixes is far greater than  the wastewater flow (1 0 »0 ),
                                                                           W
then:
                                 C ' 7 'cm
                                                                          (IV-5)
                                        -295-

-------
        C    «  concentration of ocllutant  if  there  is  incomplete  initial mixing
        Zr   •  concentration of pollutant  if  there  is  complete  initial mixing.
If Y/W * C.I,  tnen the pollutant concentration following  incomplete mixing  is  10
times higher than if complete mixing  were to occur.
     The distance l  to complete mixing (see Figure  IV-4)  can  be estimated
(as an upper limit) by the following  expression:
                                  Lc   •  W'V  J                            (IV-6)

where
        L   •  distance below point source where complete mixing  occurs
        W   »  width of river
        J   •  river velocity
        e.  »  lateral diffusion coefficient.
Values of the lateral diffusion coefficient can be estimated  from the  data  given  in
Table IV-9.  Also, the foUowino predictive formula can be used:

                ^0.1-0.2, for a straight rectangular flume
                I
            •  <  0.25, for irrigation channels                             (IV-7)
                ^ 0.4-0.8, many natural channels

where
        D   *  mean depth of flow
        u*  •  friction velocity  • ^gOS
        S   •  slope of channel.
The actual distance L  Is probably less than that calculated  from Equation
IV-6 because of secondary mixing, river curvature, and initial momentum  of  the
discharge.  It is also sensitive to river width.

4.1.10  Mater and Pollutant Balances
     Many river systems are hydrologically complex.  Flow patterns are Influenced by
tributaries, nonpoint sources of runoff, flow withdrawals, as well as  point sources
of pollution.  If the planner Intends to perform water quality analyses  on  a basin-wide
scale, U  is probably prudent that a water budget be first completed.   A water budget
is a statement that:

                 g|  -  £ Inflows  -£  Outflows  -  0,  for steady-state     (IV-8)
                                         -296-

-------
                                       TABLE IV-9
                    EXPERIMENTAL MEASUREMENTS OF TRANSVERSE MIXING  IN
                      OPEN  CHANNELS WITH CURVES AND IRREGULAR  SIDES
C^nne' "if -CO'l Melr Cnejr 'r jns*t:'Se
I'jnnel •« 3 ; _• ;:e"':if": _^'x
• "'"•el ;ec~ft'y . »i , m; .'m'ii i"», .'•'sec ;."•
-«»;;; <;::;s;;"
LJOorltor/

-400rit3ry nootl
3' :n« IJsse' 'wei
[Jtt*1 ''•*'
^4ck*n2ie ^Tver
'rom C0r! S""SJO"
"••"«"-"9 	 -'M - ' I.TS co;* ::2 :*
Smooth sia«» md i . 3.097 o.ll - • : }f-: 19
Bottom; 3.15 n
boti sues
Smootn siaes «na 2.2 3.397 3.1] - . ; 3-: -
sot tor. 2.5 f
long grotns on
so tn siaes
Groins on s i a«i 1.22 0.9 3.13 :.3C78 - : -5-: '•
Gro'ns on sides 69.5 4.0 D.9* I.C75 • - 51
ind jentle cjrviturt
leneri'V ttruft i2«o 6.7 1.77 3.152 0.67 3 4
          er      3eiCi -neludtl one      210-270       4          5.4       3.08        1.1         34
          a'       90' jna cn« 130'
        wer,      Itntt/ -^«nder.n?        350       3.73-1  74   0.29-3.58  0.033-0.051              : 52-: i-
  29 i" rejCI S*1o»   river *ijh uO >.o

  »Si.f "mt
from:  Fischer, H.B.,  E.J.  List, R.C.r. Kob, J.  Imberger,  and N.H.  Brooks. 1979.
       Mixing in  Inland  and Coastal waters.  Academic  Press,  New York.
where
         S   »   storage In the river channel.
For the  steady-state situations, which are examined  here,  the water budget simply
states that  inflows to the system equal outflows  from  the  system.  A water budget
thus provides  a method of determining whether  the major flow contributions have been
accurately  assessed or not.  If a large Imbalance  in the water budget exists, accurate
evaluation  of  the major sources of pollutant might be  difficult to achieve.  An
accurate water balance helps to minimize the possibility of Inaccurate assessment of
pollutant concentration.  It does not eliminate the  possibility.
     Once a  water balance has been completed,  then a pollutant balance of a conserva-
tive pollutant can be developed based on the following relationship:
                       Flux   •  53  n°*     •«* steady-state                   (IV-9)
                               out
                                          -297-

-------
where the fluxes are the rates of entry and loss of the pollutant into and
out of the system, respectively.  One of the following two expressions can
be used to predict the mass loading rates:

                                    M • 5.38 C Q                           (IV-10)

where
        M  «  mass loading rate, Ibs/day
        C  «  concentration, mg/1
        Q  «  flow rate, ft3/sec
and
                                    M • 86.4 C Q                           (IV-11)

where
        M  »  mass loading rate, kgs/day
        Q  •  flow rate, m /sec.
When nutrient and water balances are developed, the following considerations should
De kept in mind:
        •     In most  instances  it  is probably  not possible  to develop  water  or
              nutrient balances  where inflows and outflows balance  to within  less  than
              10 percent of each other.
        0     The system's upstream boundary must be  included  in  the balance  as  a
              source and the downstream boundary  as a  loss.
        •     All sources  and  losses should be  mutually  exclusive of each  other.
        •     Choose system boundaries to  coincide with  locations of gaging  stations
              when possible.
        •     Try to use comparable periods of  record  of data.  This will  help  to
              minimize the impacts  of trends which could be  present in  one record  but
              not in another.
        •     It  is typically  easier to develop water  and mass balances on an annual
              basis, although  balances can be developed  for  each  season of the  year.
              However, if  the  system  1s not at  steady  state,  Inflows and outflows
              should not balance.
     Table  IV-10 shows  a  suggested method of tabulating the results of water and
pollutant balances.   Total nitrogen (TN)  and total phosphorus (TP) are the  pollutants.
All  flow rates  and  loading rates  are tabulated individually.  Once total  loading
rates  have  been  tabulated, the  percent contribution  from each source can  be  determined.
Percent contributions help to determine  the relative  Importances of each  source as  a
contributor  to  pollution, and can  provide a met nod to prioritize pollution  abatement
efforts.
                                          -298-

-------
                         TABLE IV-10



SUGGESTED CONFIGURATION FOR WATER AND NUTRIENT  BALANCE  TABLE

SOURCES
- UPSTREAM
- TRIBUTARIES
- IRRIGATION
RETURNS
- MUNICIPAL
- INDUSTRIAL
i
i
i
TOTAL
LOSSES
- DOWNSTREAM
- DIVERSIONS
TOTAL
SOURCES-LOSSES ,nA
X 1UU
LOSSES

FLOW RATE















LOADING RATE
TN I






























TP I






























                              -299-

-------
                                EXAMPLE IV-3
     Figure  IV-5 shows a hypothetical  river which has three tributaries,  a
nonpomt  source of runoff, and two diversions.  Develop a water balance for
this system.   The known flow rates are:
              Identification Number
                      1
                      2
                      3
                      4
                      5
                      6
                      7
                      8
Flow rate (cfs)
    2000
    4000
    1200
     200
     800
    1000
    2000
    6000
            FIGURE IV-5    ILLUSTRATION OF  WATER  BALANCE
                                     -300-

-------
I   The flowrates at locations 1,2,3, and 5 are assumed to comprise the inflow rates
I   to the system.  The total inflows are:
i
I
j                 Identification Number                  Inflows
j                          1                             2000 cfs
                          2                             4000 cfs
!                          3                             1200 cfs
!                          S                              800 cfs
I                        Total                           8000 cfs
|   The inflow from gage 4 is not needed because gage 5 is located further downstream
j   on the same tributary.  The outflows consist of diversions 6 and 7 and the down-
j   stream outflow past gage 8:

i                 Identification Number                  Outflows
!                          6                             1000 cfs
I                          7                             2000 cfs
j                          8                             6000 cfs
j                                                        9000 cfs
j        The inflows and outflows differ by 1000 cfs.   There are several  reasons
   for the Imbalance.   One, the flow rate past each gage is not measured perfectly,
   but differs by some degree from the actual flow rate.  Two, the gage at location 5
j   does not catch all  of the nonpoint source runoff,  so there is an additional inflow
I   to the system which has not  be quantified. Three,  depending on the size of the
|   reservoir,  direct precipitation and evaporation might be significant.
I	END OF EXAMPLE  IV-3	
     The following example Illustrates both a water and nutrient balance, and is
based on work performed by Tetra Tech on the Snake River in Idaho (Mills 1979).
                                - EXAMPLE IV-4
        Develop annual water and phosphorus balances for water year 1976 for the       j
   Snjice River from Heise, Idaho, to below American Falls Reservoir, a distance of     •
   150 miles.  A sketch 1s shown in Figure IV-6.  Estimate the phosphorus retention
   coefficient for American Falls Reservoir.  The retention coefficient is defined as:
           m Flux Input - Flux Output
         p        Flux Input
                                         -301-

-------
           Henrys  Fork
            near  RexDurg
                                     Blackfoot River
                                      near Blackfoot
                                     ( mciuoe  bypass canal)
                                                Portneul  River at  RocateHo
                                                      American Falls  Reservoir
                                                         Snake River at  Neeley
                                                                   RM713
   FIGURE  IV-6    SKETCH OF SNAKE RIVER  FROM HEISE  TO NEELEY,  IDAHO,

The required data are shown below:
        Surface area of American Falls Reservoir • 56,600 acres
        Evaporation rate In this part of United States • 33 Inches/year
        Precipitation -11 Inches/ytar
        Ground water Inflow Into Snake River:  500 cfs
        Ground water Inflow Into American Falls Reservoir:  2,100 cfs.
The total phosphorus concentrations were generated during the  study of Mills
(1979)  and are  provided  here:
                                       -302-

-------
                  Source                             mg/1
                  In rainwater                       0.03
                  Snake River near Helse             0.05
                  Henrys For..                        0.11
                  Blackfoot River                    0.26
                  Portneuf River                     0.68
                  Groundwater inflow                 0.23
                  Snake River near Neeley            0.08
     The surface inflow rates are gaged by the U.S.  Geological  Survey and are
reported in the U.S. Geological  Survey Water Data Report for Idaho (1976).  An
example of how the information is tabulated in these reports is shown in Figure
1V-7.  From an entry in the Table, the mean flow rate for water year 1976 1$ 8549
cfs at USGS 30307500, near Heise.  Rather than showing the remaining tabulations
from the USGS report the flow rates from water year 1976 will simply be tabulated,
as contained in the report.

                     Source                        Flow rate
            Blackfoot River                          453 cfs
            Henrys Fork                            3,235 cfs
            Portneuf River                           412 cfs
            USGS 13059500 (diversion)          2.333,700 ac-ft/yr
            USGS 13069000 (diversion)            800,900 ac-ft/yr
Based on this information the water and total phosphorus balances are calculated
and shown in Table IV-11.  The flow rates are all converted to units of cfs.  This
requires converting the precipitation, evaporation, and diversions to these units.
A precipitation rate of 11 Inches per year Is equivalent to 71 cfs:
     11 t 12 x 56600 x 43560 * 366 » 24 » 3600 - 71  cfs
The diverted flow in ac-ft/yr 1s converted to cfs as shown:
     USGS 13059500:  2333700 x 43560 « 366 » 24 » 3600 - 3214
The percent difference between Inflow rates and outflow rates 1s 4 percent.
     Based on these flow rates,  and the concentrations of  total phosphorus
presented earlier, the sources and losses of total phosphorus can be tabulated.
For example, the mass flux of total phosphorus flowing past Helse can be calculated
using Equation IV-10:
     M « 5.38 x 8549 x 0.05 • 2300 Ibs/day
Continuing in this manner, the sources and losses are as tabulated in Table
IV-11.  The large imbalance  1s caused by retention at American Falls Reservoir.
The phosphorus loading to the reservoir Is:
     9589 - 865 - 415  -  8309 Ibs/day
                                      -303-

-------
'39' 33" .  in
.259 •:
"*. 2*
                                                            , * 11 E .   Sonntvillt C0u"t».  HyarolOflU UnH
                                                           ;mil  "*iO  uO»trt«» '<•«•
                                           38 6 ««, jolt-tic 'n*a -««'yt * an . »na 1C Kilt Ml 5 ',1.186.3 uO.
                           -i-3t.
             it.at.  7.;-: «t  2.368
             S»' Stcona, «lttr '*«r
                    "tin iiluts
                                                                        1975 :a Stotwo*' 1976
                                                                                Jul
                                                                                                Sw

2 52
i * •
;
6 .-
9"
3 •?
3 43
i: i:
11
12 «-
13 li
14 I'
15 2i
16 11
1 * 11
;3 11
1? 11
2: i:
21 :3
i^ 3"J*
23 236
21 333
25 391
25 393
336
I'. 396
23 291
3: 35:
3 '. 333
-3U ;-:l
»* J r ; ' "
"4« "1.
"i" 391
ic- : •. '233;;
Mvi^ 532
ic--":f2::5C
j?"
191!
3933
3930
3933
3933
3913
3833
3790
3813
3813
36SC
3480
3323
3213
32::
329C
32:3
331:
31::
1523
33':
3373
3353
3333
3190
3390
3150
3520
••
137360
3573
3933
3123
212900
3S43
5 228530
J55C
3530
2560
3560
1710
3760
3760
3760
3780
3730
3780
3710
1720
3710
3723
3690
3630
368C
3673
3680
3680
3700
3700
3730
3690
3700
3671
3e7Q
3700
3730
111373
3689
3780
3550
226900
3708
228000
3723
3730
3750
3800
3800
3790
3780
3440
3590
3900
3910
3920
1900
3900
4060
4080
4090
4080
4040
4040
4Q40
4040
»060
4090
4090
4090
4100
4090
4100
4100
122610
3955
4100
3720
243200
1270
201100
4110
1143
4130
4130
4540
4773
4640
4713
44iO
4280
4273
4230
1943
1710
3750
3740
1673
3950
3953
3963
4000
4013
4013
3980
1990
1980
4000
4013
..
••
119480
4123
4773
3740
217300
3081
177230
4000
4800
5990
6150
6100
6120
6070
6123
6050
7890
8800
8800
8890
8550
8920
9443
978C
9723
9680
9820
9823
9933
10130
10100
10100
10000
9990
10400
10600
10500
259810
8380
loeoo
4000
515300
3054
187300
10900
11130
9160
9430
10400
117CO
12800
1*000
15400
16000
16130
16130
160CO
18000
16000
16200
163CO
16130
16600
17230
17300
17400
17400
174QO
17200
17130
17700
IS1CO
18230
--
450S20
15027
18233
9330
894200
6005
357300
1 8400
18400
186CC
18900
132::
18130
182C3
18130
1 82 CO
13800
18430
18233
1890:
19500
19400
19300
2040C
224;:
21800
21800
21800
21800
24200
24000
240CO
21900
240CO
222QC
2040:
197GO
637003
20545
242::
18130
1233000
25380
1591400
1900C
19130
laooc
14800
13800
10730
1070C
uooo
122CO
121BC
1210C
12030
11900
11BCC
1190C
11900
12000
1190C
11900
11900
11100
10700
1 01 00
9880
9400
9370
9140
9310
9110
--
363410
12113
19100
9110
720800
25000
1487100
9780
13000
10900
10500
13200
10200
10500
11500
12100
11900
11700
12100
12700
13500
11700
11600
11700
13600
11600
11600
11500
13500
11500
11500
13500
11500
11500
13500
13500
11500
333790
12438
13700
9780
764800
11610
817100
11200
12600
12000
10200
9880
9390
8640
8410
8260
8060
7670
7460
7420
7450
7440
7390
7440
7140
6950
6750
6680
6810
6250
5950
5810
5710
5690
5680
5690
5640
244770
7895
11200
5640
485500
5490
399100
5650
5960
6480
6940
7140
7140
7153
6990
6900
6920
7000
6960
6150
5800
5700
5720
5500
5290
5110
5290
5170
4910
4840
4840
4810
4820
4680
4580
4570
-•
176110
5870
7150
4570
349100
4677
278100
                                   7933   •«••  21700   "m  2940   *c-ft  5744000   •*««'  8015   *c-'t  5802600   '
|   .f  " .i'6   'otil  3129210  "MX  8549   Nt>  24200   "m  1120   Ac-Ft  6207000   NMX   8595   *c-Ft  6219600   |
.      * *0;.it*a '0'  t(or«q« in Jtcksox Likt 
-------
I
                                       TABLE  IV-11
           SOLUTION TO SNAKE RIVER WATER AND  PHOSPHORUS BALANCE PROBLEM

Sources
Snake River at Heise
Blackfoot River
Henrys Fork
Portneuf River
Ground water inflow into
Snake River
Ground water inflow into
American Falls Reservoir
Precipitation on American
Falls Reservoir
^^ Sources
Losses
USGS 13059500
USGS 13069000
Snake River at Nee ley
Evaporation
2~i Losses
( Losses
Flow
Rate (cfs)
8,549
453
3,235
412
500
2,100
15,320
Flow
Rate (cfs)
3,214.
1.103
11,360.
215.
15,892.
' '
TP Loading (Ibs/day)
2,300.
1,915.
634.
1,510.
619.
2,600.
11.
9,589.
TP Loading (Ibs/day)
865
415
4,890
-
6,170
   Since the phosphorus leaving the reservoir is 4890 Ibs/day, the retention coeffi-
'   cient is:
8309 - 4690
   8309
                               .41
   American Falls Reservoir retains a significant quantity of the phosphorus which
   enters the reservoir and consequently tends to keep phosphorus levels in the Snake
   River below the dam depressed compared with what they would otherwise be.
                                                                                       I
I	END OF EXAMPLE IV-4	'
                                         -305-

-------
4.1.11  Hand held Calculator Programs
     It nas become apparent that, after applying the river screening techniques
conta'r-eo 'n the original manual (Zison Q _a_l_., 1977) to real systems, a substantial
savings of Dcth time and effort could be realized by programming the major computa-
tional sequences.  To this end, these algorithms have been programmed on the Tesas
Instrument Tl-59 calculator ana are available upon request in a document prepared by
Tetra Tech (Mills H .ill. 1979)*.  To date the algorithms contained in Mills et al.
(1979) preti'Ct:
         •    Equilibrium temperature
         •    Longitudinal  instream temperature distribution
         •    Mixing  temperatures
         •    BOO profiles  for  point  and nonpoint  sources
         •    Reaeration  rates
         •    Dissolved oxygen  profiles
         •    waste  assimilative  capacity  and  critical  dissolved oxygen  levels
         •    Coliform profiles for point  and  nonpoint  sources
         •    Bed material  sediment transport.
      For each  program contained  in tre  document  the  following  information  is provided
for  the  user:
         •    A detailed  set of user  instructions
         •    A program  listing
         •    A sample  input/output sequence.
      An  example set  of  user  instructions  is  shown  in Figure  IV-8.   The  first 6 steps
are  for  data entry  and  the seventh is  for calculation  of  the required information.

4.2   CARBONACEOUS AND  NITROGENOUS  OXYGEN  DEMAND

4.2.1  Introduction
      Many  wastes discharged  Into waterways contain biologically oxidizable materials
 that exert an  oxygen demand  on waterway resources.  This  biochemical  oxygen demand
 (BOO) can  be  subdivided into  carbonaceous (CBOO) and nitrogenous (NBOD) components.
 Table IV-12 illustrates typical concentrations of NBOD and CBOD in untreated municipal
 waste.
      CBOO represents the amount of oxygen required by bacteria to stabilize organic
 matter under  aerobic conditions.  The reaction can be approximated by:
 * Attention:  W.B. Mills, Tetra Tech,  Inc.
   3746 Mt.  Diablo Blvd., Suite 300  Lafayette,  California  94549
                                          -306-

-------
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• • •' ' 	 • 	 i23
-.: :»,;
i : -tj
- •--.»- 3" ^-ce-.-j:^ •-. ivu- ;u»t
:?•(!.. s:,-:e 3' »: :-si3-. La .^g/;.]
,-1: :; . sc-ice a' ;;i'.::or. :, -j/t;
6 :-:»•• s:'f«r :f-je'«ijrt. T t'C;
:<.c.,i:» 4 no ditsliy:
« . ' / «I tin* to critic*] fl»fieit.
I
• cri-.ic*! dt'UU, 0. (ag/l)
TIONS
I t'.'t"
prc;rim


^

^•Q

°0
T







0




R/S

.,$
R/S

R/S
R/S
R/S
R/S

•°£3
i






























CiS'v.*'-
' 0

i
g
Q

C

0
C

*,
k<
lc
°c
               FIGURE  IV-8  EXAMPLE SET OF  USER'S  INSTRUCTIONS
                               FOR HAND HELD CALCULATOR PROGRAMS
This reaction assures  that  the  available organic matter  Is completely oxidized.
Bacteria, however, might  not  be able to completely oxidize all  of  the available
organic matter.   Equation IV-13 does Illustrate that oxidation  of  the nitrogen
is not included  as part of  CBOO.   The reduced nitrogen  1s oxidized to nitrate
in a two step process  as
                                          -307-

-------
                IV-12
••H/,:C:?AL WASTE  CHARACTERISTICS
Approx
Average Daily Flow
Sol ids
"otai
Total volatile
Total Dissolved
'otal Susoenaed
.clatile Suspended
Settleaole
BOD
Carbonaceous '5 aa/'
gal /cap/day

mg/1
mg/1
sig/1
Tig/ 1
mg/1
rng/1

mg/1
Caooracecus { j! f.-3te: mg/1
N- trocenous*
Si trogen
Total
Organic
Ammonia
Ni tri te » Nitrate
Phospnate
Total
Ortno
Poly
Total
Fecal
•Ultimate, Nitrogenous
mg/1

mg/ 1 N
mg/1 N
mg/l N
mg/1 N

mg/1 P04
mg/1 P04
mg/J i»04
mill ion org./100 ml
mi 1 1 ion org./lOO ml
oxygen demand, exclusive
125

800
400
500
300
130
150

180
220
220

50
20
28
2

20
'0
10
30
4
of C800.
Normal
Ranae
100-200

450-' 2:C
250-3C3
300-3CC
ICO-iCC
3G-200
-

1CC-450
'20-580
-

15--GO
5-35
10-60
0-6

10-50
5-25
5-25
2-50
0.3-17
              -308-

-------
              2NH3  +  302     nitrite-forming     ^   2N02" + 2H* «• 2H20         (IV-13)
                               bacteria

              2N02' «• 02  «•  2H+    nitrate-forming    ^  2NOj- „ 2H+              (IyM4)
                                   bacteria

Based on Equations  IV-13  and IV-14 the NBOO  is:

                          '  r      i   r        ^  \        r        "*
              NBOD  «  4.57;   I Org-Nj  + INH/  -  N  !  )+  1.14lN02" - N j          (IV-15)


Typically the nitrite concentration is negligible so  that:

                                 NBOD - 4.57 (TON)                            (IV-16)

where TON represents total  oxidizable nitrogen,  the sum of organic  and ammonia
nitrogen.  A typical  value of TON from Table IV-12 is 20 * 28  «  48 mg-N/1, which
corresponds to an NBOO of 220 mg/1.
     Typically in the bottle determination of CBOD and NBOO, the carbonaceous
demand precedes the  nitrogenous demand by 5 to 10 days, as shown in Figure IV-9.
This had  led workers to  believe that  nitrification can be ignored in river environ-
ments below a source of  pollution up  to a distance corresponding to a travel time of
five to  ten days.  Such  an  assumption might be invalid for several  reasons.  Given
that there are numerous  sources of pollution along many rivers a viable population of
nitrifying bacteria  may  already be present within the water column.  Second, nitrifers
can  grow attached to the bottom substrate.  Consequently, significant numbers can
exist just below the discharge  location and nitrification can proceed Immediately.
Nitrification by attached  bacteria 1s more  likely to be of significance In relatively
shallow, wide rivers, which have  stable bottom substrate (Mills, 1976).
     CBOO is a commonly  measured characteristic of waste water.   The CBOD used 1n the
formulations presented below 1s the ultimate CBOO.  Often CBOO is expressed as CBODj,
the  oxygen utilized  in a 5 day test.  The relationship between ultimate (CBOOL)
and  5-day CBOO can be approximated by:
                  CBOD 5
         CBOOL '  (T68-

This relationship assumes  a decay rate of 0.23/day, and may be different for effluents
from advanced wastewater treatment plants.
     The mass balance equation used  1n the CBOO analysis 1s exactly analogous to the
NBOO equation.  The  first  order decay rate assumption for NBOO stabilization  Is
necessary to maintain this  analogy, and is sufficient for hand calculations.
                                         -309-

-------
                 c   .   j   «  I   :   I  >«   e   <«  »  JJ  ii   2*  ?t  »
                                      '•"<» 3»»»

            FIGURE  IV-9    THE BOD CURVE,   (A) CURVE  FOR OXIDATION OF
                             CARBONACEOUS MATTER,   (B)  CURVE  SHOWING
                             INFLUENCE OF NITRIFICATION,

     Nitrification  (the  process  by which ammonia is oxidized  to nitrite,  and nitrite
to nitrate) is pH dependent  with an optimum  range of 8.0 to 8.5 (Wild,  1971).   If the
pH of tn< river ij  below 7.0, nitrification  is not Hkely to  be important.

4.2.2  BOD Decay Rate
     The decay rate for  CBOO will be denoted by kL and for NBOD by  kN.
Typical values of both k.  and k... Me between 0.1 and 0.6/day, with  0.3/day
                        L      ~
being typical,  k,  values  can, however, exceed the range given here.   Values of 1
to 3/day have b*en  computed  for  shallow streams (Thomann, 1972).  A figure  to be
presented shortly will show  how  k. depends  on depth.  The following discussion
will be directed toward  k, ,  but  in general  will also apply to k^.
     The disappearance of  BOO from a river  is a reflection of both  settling and
biochemical oxidation, as  shown  In Figure IV-10.  Biochemical oxidation can consist
of '^stream oxidation (k.L)  as well as absorption by attached organisms (k4L).  The
total oxidation rate then, is k., where:
The total loss rate k   is:
where k.. reflects  settling  losses.
                                        -310-

-------
              ri-OW
                                    I nit ream
                                    d«oxygtnation
                                         L-ULTIMATE BOO
                                                  Absorption by
                                                  attached organisms
              FIGURE  IV-IO
              MECHANISMS OF  BOD  REMOVAL
              FROM  RIVERS
Settling of BOO 's generally more prevalent  just  below a  sewage  discharoe  where
the discharged material  may contain a large  suspended  fraction.   As  this material  is
transported downstream the settling component  becomes  less  important  and the  reaction
rate k.  approaches the oxidation rate kd.   In  this  chapter,  the  settling component
will not be explicitly considered.   Neglecting settling will  tend to  cause estimated
instream 800 levels t; be somewhat  higher  than they actually might be along certain
portions of a river.   It should be  noted that  if  instream BOD data are used to
determine k.  (one such method will  be explained in  Figure IV-12)  then the
effect of settling is automatically included in k,  .
     F aure lv-11 illustrates the dependence of kL  on  river  depth.  The highest
deoxyqenation rates occur m shallow streams with stable, rocky  beds, reflecting
the significance of attached biological  organisms.  Bowie et al.   (1985) contains  observed
and predicted values  of k.  for various natural streams.
     The decay coefficients k.  and  kN are  both temperature  dependent  and
this dependence can be estimated by:
                       1.047(T-'°>
                                                                             (IV-17)
where
        '20
or kN at 20°C
        kT   «  k,  or kN at T°C
        T    •  water temperature, PC.
Numerous methods for computing k.  from  observed data are available (Nemerow,
1974).  One method entails the use of a semi-log plot.   The stretch of  river  contain-
•ig the data to be plotted must have a  constant stream area and  flow rate,  and  the
BOO loading must be from a point source located at a position that will be  called
x « 0.  Plotting the log of BOO concentration  versus distance generally produces a
                                         -311-

-------
          100
          10
         '005
                                                  Stobte, Rocky B*d
                                                 • Moderate Treatment
 03
DEPTH (FT)
                                                  Unstable, Sandy Channel
                                                 •Highly Treated Effluent
                                                  with Nitrification
                                                 100
                                              1000
        FIGURE  IV-11
•DEOXYGENATION COEFFICIENT AS  A FUNCTION  OF
 DEPTH,  (AFTER HYDROSCIENCE, 1971)
straight line with  slope of -k./U.  An example 1s shown  1n Figure IV-12.  Either
CBOD, or C800L can  be plotted as the ordlnate.  The slope should be converted
from base 10 logarithms as given in the semi-log plot  to base e  logarithms as needed
in the formulations used in this chapter.  The conversion is made by multiplying the
value for log base  10 by 2.303.
     Wright and McDonnell (1979) have more recently developed an expression for
instream 800 decay  rate based on the flow rate of the  river.  The exp"?sslon is:
                       ld(aiV)
                                           1f Q>80° cfs
                                            1f Q<800 cfs
                                                (IV-18a)

                                                (IV-18b)
                                        -312-

-------
             10.0
          O
          O
             10
                          4Mil««/Doy
                          -Slop* x U
                          2.9(flfi)
                          0.16/Doy
                           8
.?
 I DISTANCE (MILES)
 INPUT
16
24
32
36
        FIGURE 1V-12    EXAMPLE OF COMPUTATION OF KI  FROM STREAM
                          DATA  (FROM HYDROSCIENCE, 19/1)
This expression is particularly attractive because  the only hydraulic variable
required  is flow rate.  Other predictive techniques and rate data  from rivers
around  the country are contained 1n  Zlson e_£ _aK  (1978).

4.2.3  Mass Balance of BOD
     The  general mass-balance equation for BOO In rivers 1s:
             fe
                                     -  kL L
                                                                        (JV-19J
                                      -313-

-------
             *  CBOD (ultimate) remaining to be oxidized,  mg/1
        Q    »  volumetric flow rate,  ft /sec
        A    »  cross-sectional  area,  ft
        i-r   «  concentration of CBOD entering through an incremental  sideflow
                (distributed source),  ma/1
        Lrd  •  mass flux of CBOD entering, with no associated flow, mq/l/sec
        x    •  stream distance
        —   «  0 indicates that steady-state conditions are being assumed and
                thus no accumulation of material takes place at any point within the
                reach.
The NBOO equation is completely analogous in form to Equation IV-19:


                  ll  -  0  --ifcW) -V  "V  '**"rd
where
        N  »  the NBOO.
Nrd represents purely a mass flux of nitrogenous material, while Nr hr[)/A
is a source of NBOO entering the river reach through an incremental  sideflow.
Thus, in cases where a known distributed source of BOD significantly contributes
to a river reach under study, and the distributed flow (flow associated with a
distributed source) can be neglected, N   can be used in lieu of Nr (|^)/A-
Nrd can be estimated by determining the mass M of BOD entering a volume of
river water V in time T.  N  . is given by:
              M
        Nrd "^
     For any particular reach of a river under investigation the stream cross-
sectional area can be expressed by:
                                                    AQ  *  AAx                   (IV-21)
where
        AQ  •  stream cross-sectional area at upstream end of the reach
        Af  •  stream cross-sectional area at downstream end of reach
        x   •  distance downstream from beginning of reach
        x.   •  length of reach.
                                         -314-

-------
The cross-sectional  area need not be measured  directly,  but  can  be  computed  from:
        A . 0
     The cross-sect iona) area change can reflect a chanae in stream velocity,
perhaps due tc a bed slope increase or decrease.  The length of  the reach  under
investigation, x ,  is measured in river miles  along the  river's  centerline.
If use of a constant stream area is assumed,  then A.  • 0 and A » AQ throughout
the reach.

4.2.4  Typical Solutions
     Case 1:  The only sour^> of CBOD occurs  as a point  source at x «  0.   The
CBOO distribution is then expressed by:
where
        ,.   .  it
        UQ  •  stream velocity at x » 0
        LQ  «  ultimate BOO at the upstream end of the reach
        L   •  ultimate BOO at a distance x downstream
        The other terms have previously been defined.
The initial CBOO, LQ, must reflect both CBOO upstream of the reach as well
as that contributed by the point source in question.  It is given by:

                                   LA * W/5.38                          (IV.?3)
where
        w   *  mass rate of discharge of CBOO,  Ib/day
        Qu  «  upstream river flow, cfs
        QW  «  waste flow rate, cfs
        LU  «  upstream CBOO concentration, mg/1.

     Case 2:  For a point source of CBOO at x • 0 and a distributed mass  influx
of CBOO (with no associated flow) entering the  river throughout the reach, the
solution  1s:
                                                                           (IV-24)
                                         -315-

-------
where
        Lrfl  «  -nass rate of CBOO entering the reach per unit volume of river
                *ater, nig/I/day.

     Case 3:  A distributed flow enters the river carrying CBOD and a point source of
CBOO exists at x • 0.  The flow rate Q at a distance x 1s:
                 Q  ' °
                          * ' Q0 * V
where
        '0      \
The BOD distribution is given by (the river cross-sectional  area is assumed constant
throughout the reach):

where
        Lr  »  concentration of CBOO entering the river in the distributed
               flow, mg/1.
Case 3 can also be used to establish the effect a purely diluting inflow (I.e.
Lr» 0) would have on the CBOO distribution.

     Case 4:  For a point source at x • 0, a distributed source with associated
 inflow, and a mass flux with no associated flow (constant river cross-sectional
area), the solution is:
                        L  ,^,     t   -.  j  ...   -  i,  -ix-i    i          (IV-26)
                        uo
 where
             k,  A  * £n
        E.  • -i-5	1  . as in Case 3.
                                         -31S-

-------
4.2.5  Other Simplifying Procedures
     The formulations represented by Equations IV-22 through lv-26 offer a range of
options for examining BOO distribution in rivers.  However, there are additional
methods of estimating instream concentrations and determining whether or not signifi-
cant BOD levels exist.  Perhaps the simplest method is assuming that BOO does not
decay.  An upper limit of the instream concentration at ao> joint can then be deter-
mined by incorporating all known sources, and using the methods presented in Section
4.7.  If the computed instream concentrations are below a threshold pollution level,
then there is no need to apply Equations IV-22 through IV-26 because the inclusion of
a decay rate will only lower the concentrations.
     It may also be feasible, as a first estimate, to combine the CBOD and NBOD
equations into one, and use that equation to estimate the distribution of the
total oxygen-demanding material.  To do this, all source terms must include both CBOO
and NflOO.  One decay coefficient is used for both CBOO and NBOD decay.  The larger
decay coefficient of the two shoL'1 be used since that will produce the larger oxygen
deficit.
     In deciding which of Equations IV-22 through [V-26 to use for any analysis,
the purpose of the analysis as well as data availability should be considered.
If the main purpose  is to estimate differences  in stream concentrations caused
by various levels of abatement at a sewage treatment plant, the diffuse sources
of BOO need not be considered.  The resulting concentration difference can be
expressed as:
                                „ e*P \-r-   /A~* * A.  5-1  |               {IV-27»)
                      AL
                                   /Q  \Ei
                                                                            (!V-27b)
where
           »  the change in BOO concentration due to a change, ALQt in the
              initial concentration.
Equation IV-27A should be used for a Case 1 or Case 2 situation, and Equation IV-27B
for Case 3 or Case 4.  If an estimate of the absolute level of BOO 1s desired,
however, then the appropriate expression Including the nonpolnt sources should be
utilized.  It should be noted that If the diffuse sources of BOO are large then the
improvement of instream BOO concentrations by point source control will be relatively
minor.  In that case the planner should focus on nonpolnt source control.
                                         -317-

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                                     EXAMPLE 1V-5
                    Estimating BOD Distribution  in  a River

       Suppose the user wants to calculate the 800  distribution in the river
   Shown below in Figure IV-13.  There are nine point sources contributing BOD
iMixing
;  Zone
        d-4'
        BOD-lmg/l
        Q«300cf$
                                                                        Q«aOOcf*
                                                                        BOD»lmg/l
        FIGURE  IV-13
                                                    Mixing I
                                                     Zone  ;
     i               "N           n           rn m
HYPOTHETICAL  BOD WASTE  LOADINGS  IN A  RIVER
   in the stretch of river under consideration.   The ninth source is assumed to
   be a tributary, and contributes substantially  more flow than the other eight.
   Begin by dividing the river Into reaches.   The first reach (I) should include  the
   first 75 miles in which there is one point  source of BOD at the upstream end
   (source (1)).  Equation IV-22 1s applicable to that reach.  Now, there are several
   choices available regarding the division  of the river between sources (2) and  (8).
   One choice is to divide the 50 miles into mini-reaches similar to Reach I, and
   reapply Equation IV-22 seven more times.  A second alternative is to group adjacent
   point sources into fewer and larger sources, thereby requiring fewer applications
   of Equation IV-22.  A third alternative  is  to  assume that sources (2) through  (8)
   comprise one continuous distributed source,  the total pollutant loading of this
   equivalent source being equal to the sum of  the individual loads.   For this
   representation to be valid the sources should  be both evenly spread spatially  and
   be discharging comparable loads.   The third  alternative wi11 be examined here,
   and reach II will consist of the 50 miles following Reach I.   Equation IV-25 will
   be used to analyze Reach II.   Reach III, then, will begin just downstream from  the
   tributary (source (9)).
                                              -318-

-------
        For  Reach  I,  Equation  IV-22  is  first  solved.  Suppose the following charac-
   teristics of  waste source (1)  are  known:
           0  »   20  MGD  •  I-55  (2°)  cfs
              *   31  cfs
           w  '   5000 lo.  B005/day
   Reca! '  t^at:
                 L Q   *  rt/5.38
                  u  u
           U° "      Qu *°W
   w must  be in  ID.  BOD  ultimate/day:
           w  .   5000
                  .68
              *  7353  Ib. BODL/day
   then
              .  (1)  (300)  * 7353/5.38
            °        300 * 31
              «  5.0  mo/1
   The decay coefficient is estimated from  Figure  IV-11  as  0.4/day.   No correc-
   tion will be  made  for temperature.   Equation  IV-22 can now be expressed  as
   (for constant cross-sectional  area):
           L  »  5  exp
/	-±<
\(1.1)(24)(
                              1(3600)
   where  x  is  the  downstream  distance  in  feet.   Note  "ie  correction  needed  to
   convert  the decay  coefficient  from  units  of  I/day  to  I/sec.
        The results of  the above  equation for  selected  distances  downstream can
   be  expressed as follows:
X




(miles)
0
30
60
75
L(mq/l)
5.0
2.6
1.3
0.9
I
I        For Reach  II,  sources  (2)  through  (8)  are  assumed  to  contribute  the  following
|   loading:
I           BOO • 8000  Ib/day
j             0-120 MGO
               • 186 cfs
   The flow distribution,  Q, 1n Reach  II,  1s  then:
           Q-Q0+^£x
                   .
                                         -319-

-------
I   where x  is  in miles (from 0 to 50).  Lr, the average BOD.  concentra
|   tion  in  the  incoming flow is:
                8000  lb/day
            r     120 MGO     8.34  lb/day
!              « 8.0 mg/1
!   If the average depth in Reach I! is assumed to be 5 feet, then:
           k.  • .3/day
I            L
J   Final ly, E.  is computed:
           £,
                   0.3)(30

                   (50K5280)
   Then, using (. from the 75 mile point of Reach  I as L  :

                                        35
               u,n    /       H  n A / TI i \
           1- * ~r~
                                2.5
                         / ^11  1
                3.2 -  2.:
   In tabulated form:
                       x (ml)      Q (cfs)      L (mq/1)
                          0          331          0.9
                         20          O5          1.8
                         40          480          2.3
                         50          517          2.5
   Note that the BOO concentration 1s Increasing within this reach.
        For reach III, only enough Information 1s given to conpute the Initial
 I  concentration, utilizing weighted values for the 800 at the end of reach !.
 I  and that entering through the tributary (source (9)).
 I
 I          L  '
 I           Q
 I	p EXAMPLE  IV-5
                                            -320-

-------
4.2.6  Interpretation of -esults
     The most frequent use of 800 data in river water quality analyses involves
their relationship with the dissolved oxygen balance.  This relationship will
be discussed more fully in Section 4.3.  At this point it is sufficient to say
that  t  is necessary to predict the BOO distribution in a river in order to compute
dissolved oxygen concentrations.
     When a river receives a heavy load of organic matter, the normal processes
of self  purification result in a series of zones of decreasingly severe conditions
succeeding one another downstream.  Each zone contains characteristic animals and
plants (Nemerow, 1974).  A saproblcity system (saprobicity is a measure of biode-
gradable organic matter) has been developed that relates BOO concentrations  in
streams  to the degree of pollution there.  Correlations have been found, for example,
among BOD concentrations, coliform bacteria, and dissolved oxygen in rivers  (Sladecek,
1965).   Sladecek (1969) has assigned 5-day BOO values of 5 mg/1 to mildly polluted
conditions and 10 mg/1 to substantial pollution.
     Sources of drinking water are subject to restraints on the maximum allow-
able BOD that can be contained in raw water and still quality as a drinking water
source.  Further, the degree of treatment of the raw water is dependent on the
concentrations of certain constituents, such as BOD.  One reference  (HEC, 1975) has
stated that water having a 5-day BOO over 4 mg/1,  in combination with high levels of
other constituents, represents a poor source of domestic water supply.
     As  discussed above, BOO in a river can come from a number of sources, both
point and nonpoint.  Although BOO reduction from point source might  be easier
to accomplish than from nonpoint sources, there is no guarantee that BOO  levels
will be  substantially  lowered.

4.3  DISSOLVED OXYGEN

4.3.1  Introduction
     Historically, dissolved oxygen has been and continues to be the single  most
frequently used  indicator of water quality  in  streams and rivers.  Figure IV-14
shows the seasonal variability of dissolved oxygen in 22 major waterways  throughout
the  country  (EPA, 1974) from 1968 to  1972.  Invariably the  levels observed from June
to October are  lower than those observed  In January  to March.  This  Is due primarily
to the influence of temperature on the dissolved oxygen  levels.  Due to the  effect of
temperature,  summer  1s  the most critical  season  In terms of  organic  pollutant  assimi-
 lation In rivers.
     The  dissolved  oxygen calculations presented below range In complexity from
a  simple  CBOO-DO relationship to  a more general dissolved oxygen mass balance
Including CBOO,  NBOO,  photosynthesis,  respiration,  and benthic  demands.  It  should be
                                         -321

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  Reach
Hudson
Delaware
Susquehanna
Potomac
Alabama
Upper Ohio
Middle Ohio
Lower Ohio
Upper Tennessee
Lower Tennessee
Upper Missouri
Middle Missouri
Lower Missouri
Upper Mississippi
Mississippi  nr Min
Middle Mississippi
Lo*er Mississippi
Upper Arkansas
Lower Arkansas
Upper Red
Lower Red
Brazos
Rio Grande
Upper Colorado
Lower Colorado
Sacramento
Columbia
Snake
Willamette
Yukon
Boston Harbor
Chicago Area-Tributaries
Chicago Area-Lake Michlg
Detroit Area-Tributaries
Detroit Area-Rivers
          FIGURE IV-
Number of O.C
Stations
19
17
21
IS
'»
3
\
i
i
i
ipollslj
12
i
w
s
j
4
1
!
;
S
14
?
»
11
.1
S
7
•1es 3
:Mgan 'j
Mes J
•?
900 SEASONAL Grtattr
•""han
» ITS 350 5.25 700 E75 1050 12.50 400


#,^^_^_


— *-
— «t





«_
— 4





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UMK^ 	 ^^^^^1 IVtfl
KCY: ^^-~Ptrc«itil«
*->_- AAA^ ^^
MVQII OOTH^^^
^^•ri^l^AttA
^wwmw
^^

*,

._»_.
-^
* — ,._

•^H
	 « 	


^ ^ ^ ^ ^

#^^^_

* ._„ —



•^^




*_



T 	 * 	
^^_^^^_^^
* 	 »-.
•1^—

	 «*



»
VARIABILITY  OF DISSOLVED OXYGEN  BY SEASON FOR
22 MAJOR WATERWAYS,  1968-72 (EPA,  1974)
                                         -322-

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stressed, however, that the results calculated from any of the relationships provide
esimates only since each procedure incorporates various assumptions that might not be
fully met.  For example, waste loading inflows are assumed to remain constant in
quality  arc quantity over time.  In reality loadings probably vary over time.
Furthermore tne choice of system parameters involves a certain degree of judgment.
However, for any given situation, the planner can establish an envelope of possible
outcomes by different realistic choices of system parameters.

4.3.2  Dissolved Oxygen Mass-Balance
    «
     The general dissolved oxygen mass-balance equation that will be utilized
here is given by:
                                    - k,> - V * ka (Cs-C) ' Sb *  P-R        (IV'28)
where the new symbols  introduced are:
        C   «  dissolved oxygen concentration, mg/1
        ka  *  reaeration coefficient,  I/day
        C$  «  saturation value of dissolved oxygen, mg/1
        $b  »  benthic oxygen demand, mg/I/day
        P   •  rate of oxygen production  due to photosynthesis, nig/I/day
        R   •  rate of oxygen consumption due to  algal  respiration, mg/l/day.
Stated  in words. Equation IV-24 expresses the following  relationship:
At  steady state, the rate of addition of  dissolved oxygen to  a river due to reaeration
and  photosynthesis equals the depletion rate caused  by  the  net advectlve flow,
carbonaceous oxidation, nitrogenous oxidation, benthic  demands, and algal  respiration.
     Commonly, the dissolved oxygen mass-balance  equation 1s  expressed  In  terms of the
deficit, 0, which  is the difference between the saturation  and actual concentrations.

4.3.3  Reaeration Rate
     The atmosphere acts as  the major source for replenishing the dissolved oxygen
resources of rivers.   Reaeration tends to equilibrate the dissolved oxygen concentra-
tion in a river with its saturation value.  Most commonly, the dissolved oxygen
concentration is below saturation and there 1s a net Influx  of oxygen Into the river
from the atmosphere.   On occasion, due to the production of dissolved oxygen by
algae, rivers or streams can become supersaturated, in which case there 1s a net loss
of oxygen to the atmosphere.
     A number of expressions for the reaeration coefficient, k   have been
                                         -323-

-------
developed.   Several  are presented  here.   O'Connor's  formulation (Thomann, 1972)
states that:
                                        U)17*
                                               at  20*  c                       (IV-29)
where
        \  -  oxygen diffusivity • 0.000081  ft2/hr  at  20'C
        H   *  stream depth in ft
        U   «  stream velocity in ft/sec.
Expressed in English units:
                                   12.9 o          .                          (IV-30)
                               a
The above formula was verified on streams and rivers ranging in average depth
from 1 foot to 30 feet with velocities ranging from 0.5 to 1.6 fps.   Its use should
be limited to streams where the reaeration coefficient 1$ less than  12/day.  Figure
lv-15 illustrates how k^ changes with depth and velocity according to this
relationship.
      For shallow (0.4 - 2.4 feet), fast moving streams, the following expres-
sion developed by Owens (Thomann, 1972) is preferable, as the experimental  work
to develop this expression was done almost exclusively on shadow streams:
                                       ,,0.67
                             k.-zi-eVs  *tzo'c                        (IV"31)
                                       H1'85
where U  is in ft/sec and H Is  In feet.  A graphical representation of Equation
IV-31 is  shown in Figure IV-16.
     Covar (1976) snowed that there were certain combinations of  river depths
and velocities where a formula developed by Churchill  (Churchill  et jiK, 1962)
is more accurate than either the O'Connor or Owens formulations.   The Churchill
expression Is:

                       kt • 11.6U0'969 H'1-673 per day at 20*C              (1V-32)

The regions of validity, and the predicted values, for the three  formulations
are shown In Figure IV-17.
     Recent studies have suggested that the Owens expression overestimates  the
reaeration rate for particularly shallow streams (e.g., less than a  foot in depth).
Under these circumstances the Tslvoglou-Mallace method (Tslvoglou and Wallace, 1978)
                                         -324-

-------
            too
10
o
b
PJ
5
o
t-
REAERATION COEFFICIt
l§

: \
-
-
03
\^
\\\
\*\
^\\
N
i i i i i i i i
10
Rapid Turbulent
1.0 -2.0 FPS
Moderate
0.5 -1.0 FPS
Slow Stagnant
O.I -0.5 FPS
V
i i i i i i i i
100
                                                                     100 0
                DEPTH (FT)
       FIGURE  IV-15     REAERATION  COEFFICIENT AS  A  FUNCTION OF DEPTH
                         (FROM HYDROSCIENCE,  1971)
is more  accurate.  The expression 1$:
                            <
                             1^
7776.  US, 9 25'C, Q < 10 cfs
4665.6 US, «5*C, 10 < Q < 3000 cfs
2592.  US, 9 25*C, 0 > 3000 cfs
(IV-33a)
(IV-336)
(IV-33c)
where
        S  •  stream slope, ft/ft.
Table IV-13 compares predictions of Ts1voglou-Wallace with  observed values for
several  small streams 1n Wisconsin.  The agreement 1s good.
                                       -325-

-------
           4O
                         V-3trtom Vtlpcity (ft/Me)
               O.I
              DEPTH (FT.)
                                                                V-4.0
40
        FIGURE  IV-16   PBAERATION  COEFFICIENT FOR  SHALLOW STREAMS,
                         OWEN'S FORMULATION
                                EXAMPLE IV-6
                       Prediction of Reacratlon Rates

     In September,  1969. a  study was conducted to determine the reaeratlon
rate coefficients on  the Patuxent River In Maryland during the low flow period.
The study was carried  out on a seven mile stretch of the river below Laurel,
Maryland.  The stream  was divided Into seven segments, and the reaeratlon rate
determined for each segment.  A portion of the results are shown in the Table
IV-14.  Using the hydraulic data In the table predict the reaeratlon rates  using
the methods of Tslvoglou-Wallace and of Covar.
     Since the method  of calculating the reaeratlon for each reach 1s the same, an
example calculation will be shown for the first reach only.  Based on a velocity
of 0.39 ft/sec and  a  slope  of 0.0013 ft/ft, the Tslvoglou-Wallace method predicts
a reaeratlon rate of:
                                      -326-

-------
              C.

             I
   2    34   681
      Velocity  (ft./sec.)
                                                      3456
             FIGURE  IV-17
       REAERATION RATE VERSUS DEPTH
       AND VELOCITY  (FROM  COVAR,  1976),
        ka » 7776 x 0.39 x  0.0013
          - 3.9/day at 25*C
Equation IV-33a is used since Q  < 10 cfs.
     Using Figure IV-17 and a river depth of 0.8 feet  reveals that the Owens
formula  is applicable.   Applying Equation IV-31 shows  that:
       * 21'6
             0.39
                  067
             0.8
                 I 15
• 17.4/day at 20°C
                                    -327-

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                                   TABLE  IV-13
                      C OH PAR I SON OF PREDICTED AND OBSERVED
                 REAERATION RATES ON SHALL STREAMS  IN WISCONSIN*
Stream
Black Earth Creek
Mud Cretk tributary
Oodge Branch
Isabel le Creek
Madison effluent channel
Mill Creek
Honey Creek
West Branch Sugar River
Koshkonong Creek
Badger Mill Creek
Observed KS
(I/day at 25*C)
8.46
10.7
33.1
14.
2.06
3.31
18.4
42. 5
6.09
7.98
•Grant, R.S., 1976. Reaeratlon-Coeffldent Measurements
Streams 1* Wisconsin Using Radioactive Tracers... with
the Energy -Dissipation Model. U.S. Geological Survey.
Investigations. 76-96.
Predicted kft Using
Tslvoglou's Method
(I/day at 25°C)
7.8
4.2
34.6
-
4.1
2.2
27.4
36.4
4.8
9.1
of 10 Small
a Section on
Water Resources
The results for all the reaches are tabulated below.

                       REAERATION RATE (I/day)
                   Observed     TslvooJou-Wal lace     Owens
         Reach      (2S'C)           (25*C)           (20'C)
          1-2        3.9              3.9              17.4
          2-3        2.7              1.9               7.8
          3-4        3.3              3.8              10.7
          4-5        3.5              2.9               9.0
          5-6        2.4              1.5               7.2
          6-7        4.8              2.2              11.0
The predictions using  the Tslvoglou-Wallace method  are good for all reaches.
while Owens' method predicts values two  to three times too  large, and provides
evidence  that  Owens' method probably  should not be  applied  to extremely  shallow
rivers.
                                       -328-

-------
 I
 t
 I
 j                                                        TABLE  IV-14

                                              TYPICAL HYDRAULIC PROPLUTIES
 !                                           PATIMNT RIVLR (SCPUMIER, 1%'J)
 I	..  _   	      	
 '                                                                                          Mi'jiTal ion  U.i lc  (l/«l.iy)
 |
                        Flow        Length     Velocity      Depth        Slojie      Observed    (sivoi|lou-Vlj| l,u i     i.uv.ir
 I          Reach	cfs	fj	ft/sec        ft         li/li       (25"C)          (?'.>"()          (<'')()
m
°            1-2          9.8         5,400        0.39        0.80        .0013         3.9

2            2-3          9.8         4.200        0.22        1.00        .0011         ? .7

£            3-4          9.8         7,200        0.35        1.00        .0014         3.3

^            4-5         19.5         8,400        0.35        1.10        .0018         3.5

 !            5-6         19.5         6,600        0.25        1.10        .0013         2.4
 I
 j            6-7         19.5         4,800        0.37        1.00        .0013         4.H

 j
 j
 I
                                                             -329-

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     Temperature changes affect the reaeration rate, and the relationship can
be approximated by:
                                                       "                     (IV'34)

where
        v*3)T  «  tne reaeration coefficient at T °C.
In addition to temperature, substantial suspended sediment concentrations can
appreciably alter the reaeration rate  in streams (Alonso £t _a_K , 1975).  As an
approximation, ka decreases by 9 percent per 1,000 ppm increase in suspended
sediment up to a 4,000 ppm load. Beyond t*  dissolved oxygen deficit below dam, mg/1
        T   »  temperature, °C
        H   «  height through which the water falls, ft
        a   *  1.25 in clear to slightly polluted water; 1.00  in polluted water
        b   •  1.00 for weir with free fall; 1.3 for step weirs or cascades.
     An alternate equation developed from data  on the Mohawk River and Barge Canal  1n
New York State (Mastropietro, 1968)  1s as follows:

                                Da - Ob  «  0.037H Da                        (IV-36)
Equation IV-36 is valid for dams up to fifteen  feet high and for temperatures
in the range of 20* to 25*C.
     In handling  the problem of a dam, a new reach can be started just below the dam.
                                         -330-

-------
^3 car te calculated as the value that occurs at the end of the upstream reach.
Tne -e« ce*"':". 2fct v»nicn will Dec"* the deficit at the beginning of the next
"eicn.  ; :»!:./»*.e3 using either of the above two formulas.

-.3.5  :-s?:'«r: r«.vger. Saturation
     ~** ••»'.:?  it •ri<:i at-icsphenc reaeration occurs depends not cnly en k  . but
                                                                          c
a'so :- -."e :"'*'5'-e-ce between the saturation concentration C  and the  actual
c:-ncer*.r at 'on C.  """he saturation value of dissolved oxygen  is  a function of tempera-
ture, sa:i">ty, and oarometric pressure. The effect of salinity becomes  important  m
est^ar-i^e systems, ana tc a 'esser degree in rivers where nign irrigation return 'lo
ca"  'eac tc substantia1 salinity values.  Tab'e IV-15 depicts  the relationship
Between cxygen saturation and chlorinity.  The expression relating salinity and
;n i or-' m ty cmcert rat i en 'S:

                 SiHnity (°/  )  • 0.03 » 0.001805 chlorinity  fmg 1)         (IV-37)
        °'oc  *  parts per thousand.
     Tne temperature dependence (at zero salinity) can be expressed as:

                 :   »  14.65 - 0.41022T * 0.00791T2 - 0.00007774T3             (IV-38)

where T ~s 'r 'C.  "his relationship  is also found  in Table  IV-15 for zero
cn'r^-ae concentration.
             ic pressure affects C  as follows:
           /Pfa - P  \
CS  *  Cs  \ 760-P
                                                      \
                                                                              (IV-39)
wnere
        -s   «  saturation value at sea level, at the temperature of th« water,
                mg/ 1
        C '   «  corrected value at the alt'tude of the river, mg/1
        ".   •  barometric pressure at altitude, mm Hg
         w
        Pv   »  saturation vapor pressure of water at the river temperature, mm
                Ho
        E    «  elevation, feet.
Table lv-16 illustrates the variability of dissolved oxygen  saturation with  altitude
and temperature.  The significant effect of altitude is  apparent  and should  not  be
neglected.  For example, at a temperature of 20*C, the saturation value decreases
                                          -331-

-------
TABLE IV-15

SOLUS
ILITY OF OXYGEN IN WATER (STANDARD
Chloride Concentration
Tern.
i n
°C
0
1
2
3
4
5
6
7
3
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
3

14.6
14.2
13.8
13.5
13.1
12.8
12.5
12.2
11.9
11.6
11.3
11.1
10.8
10.6
10.4
10.2
10.0
9.7
9.5
9.4
9.2
9.0
8.8
8.7
8.5
8.4
8.2
8.1
7.9
7.8
7.6
7.5
7.4
7.3
7.2
7.1
5.000

13.8
13.4
13.1
12.7
12.4
12.1
11.8
11.5
11.2
11.0
10.7
10.5
10.3
10.1
9.9
9.7
9.5
9.3
9.1
8.9
8.7
8.6
8.4
8.3
8.1
8.0
7.8
7.7
7.5
7.4
7.3





10,000
Dissolved
13.0
12.6
12.3
12.0
11.7
11.4
11.1
10.9
10.6
10.4
10.1
9.9
9.7
9.5
9.3
9.1
9.0
3.8
8.6
8.5
8.3
8.1
8.0
7.9
7.7
7.6
7.4
7.3
7.1
7.0
6.9





METHODS ,
1971)
in Water - mg/1
15,000
Oxygen - mg/1
12.1
11.8
11.5
11.2
11.0
10.7
10.5
10.2
10.0
9.8
9.6
9.4
9.2
9.0
8.8
8.6
8.5
8.3
8.2
8.0
7.9
7.7
7.6
7.4
7.3
7.2
7.0
6.9
6.8
6.6
6.5





20,000

11.3
11.0
10.8
10.5
10.3
10.0
9.8
9.6
9.4
9.2
9.0
8.8
8.6
8.5
8.3
8.1
8.0
7.8
7.7
7.6
7.4
7.3
7.1
7.0
6.9
6.7
6.6
6.5
6.4
6.3
6.1





Difference
— per 100 mg
Chloride
0.317
0.016
0.015
0.015
0.014
0.014
0.014
0.013
0.013
0.012
3.012
0.011
0.011
0.011
0.010
0.010
0.010
0.010
0.009
0.009
0.009
0.009
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008





     -332-

-------
                                     TABLE IV-16

                             DISSOLVED OXYGEN SATURATION
                           VERSUS TEMPERATURE AND ALTITUDE
-«-n»ra-.j« ALTITUDE (ft)
' - «- \
0
5
10
15
20
25
30
35
0
14.6
12.3
11.3
10.2
9.2
8.4
7.6
7.1
2,000
13.6
11.9
10.5
9.5
8.5
7.8
7.1
6.6
4,000
12.5
11.0
9.7
8.8
7.9
7.2
6.5
6.1
6,000
11.5
10.1
8.9
3.0
7.2
6.6
6.0
5.6
8.000
10.5
9.2
3.1
7.3
6.6
6.0
3.4
5.1
from 9.2 fig/I to 7.2 mg/1 as the altitude increases from sea level to 6000 feet,
approximate elevation of Lake Tahoe and the Truckee River in California and Nevada

4.3.6  DO-BOD Interactions
     A widely used dissolved oxygen predictive equation 1s the Streeter-Phelps
relationship which predicts the dissolved oxygen concentration downstream from
a point source of BOD.  Assuming a constant river cross-sectional area, the dis-
solved oxygen deficit (C -C) can be expressed as:
where
        k   •  reaeratlon coefficient, I/day
         a
        DQ  «  initial deficit (at x « 0), mg/1
        D   »  deficit at x, mg/1
        LQ  •  initial BOO (at x « 0), mg/1
        k.   »  BOD decay coefficient, I/day.
L  and D  are found by proportioning BOO and DO deficit concentrations just upstream
                                         -333-

-------
of the waste discharge with the influx from the discharge itself.   As  presented  earl-
ier in the BOO section, I  is given by:
                                .      8 * LM Qu
                              0
where
        w        *  discharge rate of BOO, Ib/day
        L        *  concentration of BOO in the river upstream of the
                    waste discharge, mg/1
        Q        «  river flow rate upstream of discharge,  cfs
        0        «  flow rate of waste discharge, cfs
        Q*0   •  flow rate of river in the reach under consideration,  cfs.
W in Equation IV-41 should be expressed 1n terms of ultimate BOO, and not 5-day
BOO.
     The initial deficit is found from:
- C  . C*Qw * Cu°u . Dw°w * DuQu                   (IV.42)
                       0
                        o    s     n  > n       0  •»• 0
                                    w   xu       w    u

where
        C   •  concentration of dissolved oxygen 1n the waste, mg/1
        C   •  concentration of dissolved oxygen upstream of th« waste discharge,
               mg/1
        0   •  dissolved oxygen deficit  in waste, mq/1
        0   •  dissolved oxygen deficit upstream, mg/1.
In cases where information 1s lacklno, 0  can normally be assumed to be in the
range 1-2 mg/1.
     If NBOO 1s to be considered as well as CBOO, Equation IV-40 can be modified as
fo I lows :
              0 • 0Q exp
                                                                            <'»•">
If the decay coefficient of NBOO 1s approximately equal to that of CBOO, Equation
IV-40 can be utilized instead of the more complicated Equation IV-43.  In this case,
L  fn Equation IV-40 Is replaced by the sun of L  and N .

-------
4.3.7  Dissolved Oxygen  Calculations
     Calculation of  dissolved oxygen in rivers can proceed  as  shown  in Figure IV-19.
Tr«e planne-- "eeds to estimate the waste loading scheme  *or  the prototype, whether it
be 'cr i 21 ygir projecticn or for current conditions.   The river  system can then be
aivided into 'eaches and  by repeated use of Equation IV-40, dissolved oxygen calcula-
tions can be performed 'or each reach, starting from a  known boundary condition and
proceeding downstream.   All data and calculations should be succinctly and clearly
recorded to minimize errors.
     The dissolved oxygen profile downstream from a waste discharge  characteristic-
ally has a shape shown  in Figure IV-18.  If the reach is j'ong  enough, the dissolved
oxygen deficit will  increase to some maximum value, 0 ,  at  a distance x  (termed tne
critical distance).   0   is called the critical deficit.   Within any  reach there
will always be a minimum  dissolved oxygen value that occurs, but it  may  not be the
critical deficit, which  is defined as the minimum point  on  a dissolved oxygen sag.
The difference between the minimum and critical values  should be kept  in mind.  AS
one exampl- ~f the difference between the values, a reach may  have a dissolved oxygen
profile where concentrations are monotonically decreasing throughout the reach.  The
minimum DO wi11  then occur at the downstream end of the  reach, but this  will NOT be
the critical DO value, since DO is still decreasing in  the  downstream direction.
     The travel  time to  the critical deficit is given by:
                                                                             ;iV-44)
                      
-------
              projected Haste loading
                                                           CHterl* Met for
                                                          Hand  Calculations
                       Divide i-iver Into reaches
  scenario  !source/sink distribution)
                    Determine temperature independent
                       parameters  for each reach:
                          u,  Q,  d, A (as needed)
                    Determine reaction rates  at 2(r C:
                        V V  V se
                               for each reach
                  [  Incorporate temperature corrections |
                         Determine C  for each  reach
                                                    J
   Begin reachX
I    by-reach
\Calculat1ons J
  Calculate conditions at i»o
(upstream end of present reech)
                                                              Use Computer
                                                                  Model
                                                            Perform and record
                                                           desired calculations
FIGURE IV-19     FLOW PROCESS  OF  SOLUTION  TO  DISSOLVED  OXYGEN
                    PROBLEM  IN RIVERS
                                      •336-

-------
The distance downstream can be computed  by  knowing the trave1 time and flow ve'ocity:
                                          U  •  tc                            (IV-45)
 'he critical se''cit can be found from:
                       .V^      H . =3
-------
                                    TABLE  IV-17
                        DC/L0 VALUES VERSUS 00/LQ AND  ka

30
:: '4
•A n
•A 12
J» »4
' j i 35
.'2 37
•t 11
•t | 9:
1 91
?0 93
.'2 i 95
24 9t
2* M
:i 94
sc • ;i
32 ' 33
34 ;4
3t T6
31 • :•
4C ' *9
D 42
o
-w 44 : • '2
L ' •
o
41 5
SO : 17
6 1 ' 25
33
S : • 41
9 50
: si
' M
' 2 ' -5
• 3 '13
' 1 92
'5 2 30
i t 2 34
' ' 2 '7
< 1 2 26
' 9 2 34
2 3 2 43
2 2 52
. 3
to
tl
62
63
65
61
67
M
49
T '
'2
• I
•6
••
•8
M
ii
12
14
15
14

U
M

90
92
94
• 36
'3
20
2?
35
' 43
• so
SI
' 4t
i 75
1 >3
• 91
2 30
2 'A
I "

•: it
51 44
52 »S
5: 16
54 17
55 41
SI 44
57 SO
51 S-
54 52
SC 53
62 54
63 45
64 56
65 57
M 51
67 54
61 60
'C 41
62
'2 63
'3 65

•4 66
'6 47

61
•1 44
M '6
91 12
M If
' 35 97
' '2 ' 34
' 20 ' '3
'28 21
'34 '30
U ' 40
•3
•2
. ,,
• 10
90


; 9
19
40
40
41
42
13
44
45
15
41
47
41
44
SO
3!
52
53
54
55
Si
57
51

60
tl

12
63
tl
't
U
92
• x
• -o











35
M
31
37
31
34
40
40
41
42
43
44
41
47
41
44
SO
51
52
53
54

55
51

57
51
IS
72
tl
40












3
32
33
33
34
35
t
31
3'
31
34
31
41
42
43
44
IS
It
47
41
II
50

51
S3

54
55
U
70














5
3C
K
31
31
32
33
34
34
35
36
37
3*
31
34
40
tl
12
43
44
IS
46
47

44
SO

51
53
to
















21
21
24
24
30
3^
31
31
33
33
34
35
36
3'
31
34
40
41
42
13
44
IS

17
II

If
51
















k
21
26
2'
27
28
24
24
3C
3'
3'
32
33
34
35
34
37
31
34
40
41
42
44

45
47

41
50
















L
2
24
25
25
2t
26
2'
It
29
24
30
K
31
32
33
34
35
36
)7
31
40
4:
13

44
It



















2 3
23
23
21
21
25
26
.'6
.'»
<'
28
24
30
31
3:
32
31
35
36
37
39
40
42






















; 5 I ' 29 3 ' ! 3 3 « 3 ' ! j . i 3 i : - - •
22 21 2C '9 •!'•••« 5 • - -
22 2' 25 '9 1 S ' 4 4 S :
23 22 2' 2C » ' 1 " '• i
2) II 2' 2: "9 1 S - • « • •
24 2: 2' ;• <: 93 -. - • 4 • ;
24 23 22 2' 2C I". J ' ' • - •
.'5 24 23 22 r- 2: i ">
25 24 23 22 2' i' :: 9 9 ; :
26 25 21 23 22 ." '.' ::••••
2' U 25 21 23 22 .' ' 2' " '.'. <
28 21 25 21 21 .'3 12 12 '.' '.' .'.
29 21 2' 2t 26 25 .'S 21 .'1
30 24 28 27 •-• 26 .'6
31 3C 29 24 28 28
32 31 31 K 30
34 33 32 32
35 U 34
36 J4
31
























22 I 2 M 2 26
    5 '
        43  5S  57  54  61  63  tS  «7  64  71  73  7J
                                                       7 ?  I l  I )  IS  17  14
                                                                                 43  95


Q
0
L"
0




0 00
3 32
3 34
3 31
3 31
3 10
3 12
3 U
0 It
0 II
;]
13
U
It
'5
IS
it
'1
17
11
'3
'3
13
11
14
'S
15
l|
17
II
'2
:3
•3
U
14
14
IS
II
17
II
12
•2
1
13
13
14
14
IS
II

,,
1}
12
13
13
14
It
15
II

11
1!
II
U
13
13
14
15
II

11
11
11
II
12
13
It
II


11
II
11
11
U
U
13
11


11
11
11
U
II
12
13
1


10
11
H
11
H
12
13
11


10
'0
M
11
11
12
13
11


10
10
10
II
It
12
12



10
10
:o
11
,,
11
12



10
10
10
10
11
: I
12



Of
1C
1C
10
U
11
12



Of
Of
10
10
'0
11
12



Of
Of
Of
10
10
11
'2



Of
Of
Of
10
10
11




Of
Of
Of
Of
to
11




Of
9f
Of
Of
10
10




M
3f
04
34
'0
10




31
31
34
34
34
10




31 X
3i :i ;i
31 :a -.'.
34 :9 .;
39 :9 :»
•o : :




                                           -338-

-------
        TABLE IV-18
katr VERSUS D0/L0 AND k,/kL

..-.:. : i J 3
:; :i •> ~.i n -; :s •» • 22
: :•, •• -p j; ;i :i 	 9
- :? ;: s- so r x x i
:« :< ;: s< •» *9 M : M • •]
M :i iJ ii '1 M »i • :3 1 39
•; ' :* 44 94 'i Si M ' JO ' 3t
: ' N 4j jj '5 34 « M ' 33
u , :i ;a S3 '4 32 89 »S ' X
6 ; ;a 4- Si '2 3. 4' »2 97
3 i ;: 4- s " •> « M 93
:: M 4t s: •: " :3 J' 9 ; •: i, M 62
: : a i 12 ii sa
- ; .; j; ,j ,5
;. : :; 4 : 4 ;e ta •• 51
: « :; :; 9 J 5i li :. -
.-*.;;; ; ; 5- 53 u 43
;a :: ;» a ; :3 s: >t 19
; :. : -9 ' :' 48 43 35
: : •• :: * 42 j- 2) '1
: :« ;; ;i j



29
' 21
• :2
•  il 1 ii i M t 72 ' 'i
' 42 l 47 l 50 '54 t !7 : 6' i M 6*
' 17 t 41 -1 44 1.47 1 SO 1 51 i 1! M7
l 21 '21 IK l 12 ' H ' Ji l It ' 37
• 20 '22 -23 ' 2» 12! '21 '21 ' 2i
l 13 ' i! : 11 l It l it ' '1 ' '« ' H
' 37 l 37 ' C7 1 07 1 01 1 34 ' 32 M
1 00 ' 00 M 97 »i 92 » 14
91 92 K )7 |] 7| 'J M
H »1 «C H 70 U U **
78 74 i ' 71
•19 ' i> il i! M
•31 '14 11 '31 ' 11
21 ' 24 :3 ,'2 20
• i • • 39 : • :4 30
H J2 M J3 "
7» M it 5' 41
59 49 )» :s :9
V> it >
Ji

















', " ^
: :2
: *
: 5t
: M
: '3
3 '2
3 '*
0 't
3 18


2 :i
' )2
' M
it
' 53
' 37
' '1
97
70
M
; -i
. J
: :e
»4
J2
i9
' 54
' H
' 'i
92
62
22
it S "
9 5 5
i 31 2 :'
r 99
il U
. ,3 ...
' M ' 54
' JS 1 14
• 13 1 13
»' »x
53 42
35

! 9 i
? -4 2 It
2 31
(? '• n
• *2 i 73
' 54 : 14
1 33 1 Jl
l 07 1 03
H t7
29 ><


i ] 61
2 19 2 21
2 « 2 07
l 90 1 92
1 73 • 74
' 13 1 11
1 2» 1 27
99 94
Ctt ^«



t 7 (9
2.24 2 24
2 Of 2 11
i 91 > M
1 74 17!
l 52 l H
1 24 1 22
U 12
3* 21




2 21
2 U
l N
1 71
1 10
' 19
7!
0*


V
' 3
2 X
2 1!
i 97
'. 71
1 41
1 11
67



kL
71 77 T •
'3 ' ' ' J
2 12 2 11 t 17
2 It 2 11 2 20
' 91 1 H t.OO
1.7! • :! 17!
1 41 1 41 14!
Ill 1 07 1 01
il 47 li





2 »
2 21
2 01
1 7!
1 41
97
21





2 41
2 21
2 01
1 7!
1 41
9t
01





2 4]
2 24
2 02
1 7!
1 N
11






2 U 2 44 2 4| 2 M
2 24 2 27 2 21 2 X
2 01 2 31 2 54 2 31
1 74 1 74 1 71 17]
1 14 1 M 1 11 ' 21
71 70 12 SI






2 12 2 11 2 55
2 31 2 12 2 13
20! 2 M 2 0<
• :2 i *i • ':
• 24 '21 ' ''
40 2t :i




              -339-

-------
amount of BOO that can be discharged into a river without  causing  the  minimum  dissolved
oxygen level to fall below a specified  value.   In constructing  Tables  IV-17  and  IV-1B
extra detail was incorporated for DO/LO values between 0.0 and  0.5.   This  1s
necessary because most practical  problems fall within  this range.
     The following steps show how to use Table IV-17.
        I.    Find the reaeration rate (ka) and the BOO decay rate  (kL)
             for the river being investigated.
        2.    Find the BOO concentration in the river just below the point  of mixing
             («-o).
        3.    Find the dissolved oxygen deficit at this location (D0 »  C$ - C).
        4.    Compute ka/kL and D0/L0.
        5.    Using the ratios ka/kL and OO/LO, find 0C/L0 where Dc 1s  the  critical
             deficit.
        6.    Finally, calculate DC . (0C/L0) L0, and C^,, • Cs - Oc.
To use Table IV-18 complete these steps:
        1.-4.  Repeat steps 1 through 3 above.
        5.      Using the ratios ka/kL and 0Q/L0, find k,tc.
        6.      Calculate tc - (katc)/ka.

4.3.8  General Dissolved Oxygen Deficit Equation
     The most general dissolved oxygen mass-balance formulation to be presented
in this chapter  is  as follows:
                                                                       «•>)]
                                                                            "V-49)
where
        P   •  oxygen production rate due to photosynthesis, mg/l/day
        R   •  oxygen utilization rate due to respiration, mg/l/day
        S.  »  bent hie demand of oxyoen, mg/l/day.
The distance function f(x) expresses the cross-sectional area relationship throughout
                                         -340-

-------
the reach.  The area can increase or decrease linearly or remain constant.   The
general form of the relationship is:

        MO  •  AQ, . ;.A <2,2  , IA - A,  -Ao
                                      XL
where
        Af  «  area at x * XL
        A   «  area at x « 0
        XL  •  length of reach.
For a reach of constant cross-sectional area, AA« 0.
     In developing Equation IV-49 the following relationship for C800 was used
(as originally presented in the BOO section):
                                                 f(x) J  -   ^              (IV-22)
                                                      I     KL
An analogous expression for NBOO was also used.
     In Equation IV-49, the distributed sources and sinks (P, R, Sg, Lrd, NJ
are all mass fluxes, and no volumetric flow rate is associated with any of these
sources and sinks of dissolved oxygen.

4.3.9  Photosynthesis and Respiration
     The difficulty of accurately assessing the impact of photosynthesis and respira-
tion on the dissolved oxygen resources of streams is not readily apparent from  the
single terms appearing in Equation IV-49.  Of concern are both free floating and
attached algae, as well as aquatic plants.  The extent to which algae impact the
dissolved oxygen resources of a river is dependent on many factors, such as turbidity,
which on decrease  light transmlttance through the water column.  Additionally, the
photosynthetic rate constantly changes in response to variations in sunlight intensity
and is not truly constant as implied by Equation IV-49.  Hence  if algal activity is
known to be a significant factor affecting the dissolved oxygen balance, the use of a
computer model is recommended In order to accurately assess such influences.  For
example, in the Truckee River in California and Nevada, the diurnal variation of
dissolved oxygen has exhibited a range of from 150 percent saturation during the
daylight hours to 50 percent saturation at night due to algal photosynthesis and
respiration, respectively.  At the most, hand calculations can give estimates
of net dissolved oxygen production rates that then can be compared to the other
source/sink terms in Equation IV-28.  From this comparison the  significance of
each can be estimated.

                                         -341-

-------
                                     TABLE IV-19


                              • LUES OF  G30SS  =-OTOSY:,Th£TIC PRODUCTION OF
                              •TE;R --:::A:;:,,  1972 --,c THOVAS AND O'CC'imi, 1966)
                                         Gross  -roojction     Average -»iii
                                        '
           c-.ee Sr.er - Setter:                 9
           = :'.ed a'gae
        T:ca'  Creet - D-ator- Blo^r             6
        (5Z-:C9.10° diatoms/1 )

                                              3-7

        :-..=~-sn Ri.e- est-ary -            0.5-2.0
        Seattle, /.
        '.ejse 3:ver Syster -                0.3-2.4
        '.C'rf Carol ma

        3ive«- l.ei                           3.2-17.6                6.7-15.4

        'Orf. Carolina Streams                9.8                     21.5

        Laboratory Streams                  3.4-4.0                 2.4-2.9




     Table IV-19 presents some observed values of  photosynthetlc  oxygen production

••ates.   AS shown in the table, dissolved oxygen production is expressed in units  of

rate per unit area (gm/m -day).  To convert to units of concentration  per unit  time,

the algal production rate must be divided by river depth:
                                    P « I                                    (IV-50)
where

        ?  •  production rate of dissolved oxygen, gm/m2-day
        H  •  average river depth, meters
        P  -  production rate of dissolved oxygen, mq/l-day.
P can now be directly compared to other terms In Equation IV-28.
     By using a regression equation developed by Erdmann (1979a,  19796),  the produc-
tion rate of dissolved oxygen, P, can be determined directly if the diurnal  variation
of dissolved oxygen is known.  When water temperature 1s fairly constant  throughout
the day, the photosynthetlc oxyoen production rate becomes:


                                       P   •   24DO                            (IV-51)


                                         -342-

-------
s
o
01
CO
2
    12
    11
    O
                         CURVE A         •'
                          	• _	••"^
      /
                                                             WYMAN CREEK. CAUF
                                                             AUGUST 6.1962
                                                             AVERAGE O1 MG/L
                                                                              /"-•
              \.   •



                                                                  '-*•'
          X
 V
                                                  -•''
                                  -_.—-"—-         ^
                                   CURVE 8
                                                             RIVER IVELENGLANO
                                                             MAY 31. 1959
                                                             AVERAGE HD4 MG/L
                         1
                                             I
O6OO
O9CO
12OOI
15OO
 18OO
HOURS
21OO
                                                               24OO
                                                                         COCO    O6CO
       FIGURE IV-20   DAILY DISSOLVED OXYGEN VARIATION  IN Two RIVERS.
 where
        ADO  *  difference between  the dally maximum dissolved oxygen concentraf
                and the dally m1n1mun dissolved oxygen concentration, mg/1.

Since Equation  IV-51  Is based on regression analysis,  the units are not  consistent.
     The importance of  a constant water  temperature  1s  illustrated by Figure IV-20.
This figure  shows  the hourly variation of dissolved  oxygen over a 24 hour period  for
Wyman Creek  in  California  and for the Ivel River  in  England.   Both exhibit large
diurnal  dissolved  oxygen variations, although  the  reasons differ.  In Curve A (Ivel
River),  the  dissolved oxygen  level gradually increases  from 0600 hr to 1800 hr, and
then decreases  over the next  12 hours.  The cause  of the changing dissolved oxygen
 levels is a  net photosynthetlc oxygen production during the daylight hours, and a net
consumption  during evening  and night.  Curve B 1s  almost a mirror image  of curve  A
since the minimum  dissolved oxygen  levels occur during daylight hours and the maximun
during nighttime.  The  variations exhibited by curve B are principally caused by  a
changing water  temperature.   During the day this  creek absorbs considerable solar
                                        -343-

-------
radiation causing th« water temperature to rise and the dissolved oxygen saturation
level to decrease.  At night the creek cools off and the dissolved oxygen saturation
level increases.  Curve B then is free from the Influence of photosynthetlc effects,
so it would be erroneous to apply Equation IV-51.  Erdmann (1979a, 1797b) and Kelly
e_t jj_L (1975) provide more sophisticated methods to predict P when both photosynthetlc
and temperature effects occur concurrently.  Example IV-7 illustrates the utility of
Equation IV-51.
r 	 EXAMPLE IV-7 	 •
j i
1 Prediction of Photosynthetlc Oxygen Production Rate I
i
i On Mechuns River near Charlottesvl He, Virginia,
• collected the following data:
| Time of Day
1 (hours after midnight)
I 0.0
! 0.5
1 l-°
! 1.5
I 2.0
2.5
1 3.0
j 3.5
1 4.0
i 4-5
! 5.0
1 5.5
6.0
1 6.5
i 7.0
! 7.5
I S.O
' 8.5
1 9.0
; 9.5
1 10.0
j 10.5
! 11.0
1 11.5
12.0
1 12.5
i 13.0
1 13.5
1 14.0
! 14.5
| 15.0
; 15.5
1 16.0
I 16.5
1 17.0

Stream
Temperature. *C
23.3
23.3
23.4
23.4
23.5
23.5
23.5
23.5
23.4
23.4
23.3
23.2
23.1
23.0
22.9
22.8
22.7
22.7
22.7
22.7
22.8
23.0
23.2
23.5
23.6
24.3
24.8
25.3
25.5
25.5
25.9
26.1
26.1
26.1
26.1
i
Kelly .et *±. (1975) j
i
Dissolved !
Oxygen (mg/l) |
7.6 I
7.6 !
7.6 |
7.5 !
7.4 1
7.2 ;
7.3 1
7.3 |
7.3 !
7.3 |
7.3 ;
7.3 1
7.3 I
7.3 !
7.4 |
7.4 !
7.5 |
7.6 ;
7.7 1
7.8 I
8.0 !
8.1 |
8.4 '
8.5 1
8.7 ;
8.9 1
9.0 j
9.1 !
9.2 |
9.3
9.2 1
9.2 ;
9.2 1
9.1 I
9.0 '
                                         -344-

-------
                  Time  of  Day              Stream           Dissolved
             (hours  after  midnight)     Temperature,  *C      Oxygen  (mg/l)

                    17.5                   25.8               8.9
                    18.0                   25.8               8.8
                    18.5                   25.5               8.6
                    19:0                   25.3               8.5
                    19.5                   25.1               8.3
                    20.0                   24.8               8.2
                    20.5                   24.5               8.0
                    21.0                   24.2               8.0
                    21.5                   24.0               7.9
                    22.0                   23.8               7.6
                    22.5                   23.7               7.7
                    23.0                   23.6               7.7
                    23.5                   23.6               7.6
                    24.0                   23.5               7.5


        Using a sophisticated analysis, Kelly et_ _a_L  found the daily mean photosyn-

   thetic oxygen production  to be 4.40 mg/1.  Using the data shown above and Equation

   IV-51 estimate the daily  photosynthetic oxygen production, P (mg/l/day).

        The minimum dissolved oxygen is 7.2 mg/l, which occurs at 0230. The maximum

   dissolved oxygen is 9.3 mg/1 which occurs at 1430.  Hence:


       P - 2AOO - 2(9.3-7.2) - 4.2 mg/l/day


   This compares very well with the value found by KelJy e_£ jj_.  using a more

   sophisticated analysis, even though the stream temperature varies by a few

   degrees during the day.   Probably one reason for the good agreement is that

   the maximum and minimum values occur about 12 hours apart, which the method

   assumes they do.
	  END OF EXAMPLE IV-7
     Values of photosynthetic respiration vary widely, ranging from 0.5 gm/m /day

to greater than 20 gm/nr/day.  One suggested relationship between respiration and

chlorophyll ^ is given as (Thomann, 1972):



                  R(mg/l/day) - 0.024 (chlorophyll  a_) (ug/1)             (IV-52)

where

        1 ng/1 • 10"3 mg/1.

Chlorophyll ^ concentration is most commonly expressed in terms of ng/1.


4.3.10  Benthic Demand

     In addition to oxygen utilization by respiration of attached algae, benthic



                                         -345-

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deposits of organic material and attached bacterial growth can utilize dissolved
oxygen.  Table IV-20 illustrates some uptake rates.  As with photosynthesis, the
uptake rates are expressed in gm/m2-day.  To use these values in Equations IV-28 or
IV-49, division by stream depth (in meters) is necessary.  Temperature effects can be
approximated by:

                                                 ~'20                         (IV-53)

     The areal  extent of significant oxygen demanding benthic materials  is often
limited to the region just below the outfall vicinity. Although the oxygen demand may
be great over a short distance, it may be insignificant over larger distances.   The
response of rivers to areally limited benthic deposits is generally to move the
critical deficit upstream, but  not to lower its value significantly.
    Bowie et al. (1985) contains significantly more data and further discussion
of benthic oxygen demand in rivers.  Additionally Butts and Evans (1978)  conducted
extensive studies of sediment oxygen demand on 20 streams in Illinois.  They found
that benthic oxygen demand could be predicted as:


                       TB - 0.15T + 0.30S + 0.11 logN - 0.56                 (IV-54)

where
        Tg  •  benthic oxygen demand, g/m -day
        T   •  water temperature, *C
        0.  »  depth of sediment, inches
                                                 2
        N   »  number of macroinvertebrates per m .

They  found  that  N  typically ranged  from  10,000 to  1,000,000.  Within  this range
the sum  of  the  last  two  terms  is  between ^0.1, and  is negligible compared to the
first two  terms.   Under  these  conditions Equation  IV-54  simplifies to:
                                    0.15T + 0.30S                            (IV-55)

 The  depths  of  sediment  found during the study of Butts  and Evans (1978) ranged from 1
 to 17  inches.   Consequently Equation  IV-55 is applicable to streams which have fairly
 significant  benthic oxygen demands.   For cleaner streams Equation IV-55 probably
 overestimates  the benthic oxygen demand.
                                         -346-

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                                      TABLE  IV-20
                       AVERAGE VALUES OF OXYGEN  UPTAKE RATES OF
                         RIVER BOTTOMS (AFTER  THOMANN, 1972)
                                                   Uptake  (gms  02/m -day)
                                                           9 20°C
         Bottom Type  and  Location
Range
Approximate
  Average
         Sphaerotilus  -  (10  gm dry wt/M?)

         Municipal  Sewage  Sludge  -              2-10.0
         Outfall  vicinity
         Municipal  Sewage  Sludge  -               1-2
         "Aged"  Downstream of  Outfall
                      7

                      4

                     1.5
Cellulosic Fiber Sludge
Estuarine mud
Sandy bottom
Mineral soils
4-10
1-2
0.2-1.0
0.05-0.1
7
1.5
0.5
0.07
4.3.11  Simplifying Procedures in Dissolved Oxygen Calculations
     Using Equation IV-49 might be untenable for several reasons, such as lack
of available data, or because of the vol'jtninous calculations required to apply
it to a large number of reaches.  Several suogestions are offered here that should
simplify analysis of dissolved oxygen problems.
     Since the general scope of this section 1s to facilitate the determination
of existing or potential problem areas, the analysis should proceed from the simple
to the more complicated approach.  It may be adequate to analyze the dissolved oxygen
response to the most severe loadings first, neglecting those of secondary importance.
If such an analysis clearly indicates dissolved oxygen problems, then the inclusion
of any other pollutant discharges would only reinforce that conclusion.  More rigorous
procedures (e.g., a computer model) could then be employed to perform a detailed
analysis.
     Suppose the improvement of dissolved oxygen levels due to decreased loading from
a point source is of interest.  This is a common situation since it relates to the
design of  waste loading abatement schemes.  Such improvement can be estimated by:
                                         •347-

-------
                           exp
                                                                             (1V-56)
where
       ALQ  •  the change in the Initial BOO, ma/1
       AD   »  change In deficit in response toALQ.
Equation IV-56 was formulated from Equation IV-49 assuming that LQ and DQ are
the only changes of significance.

     Many rivers have a large number of point sources.   Although this 1s not necessar-
ily a complicating factor, a detailed analysis might be too time consuming for hand
calculations.  There are several possible alternatives  to deal  with this situation in
order to reduce the number of reaches to be analyzed.  The first, already mentioned,
is to consider only the significant pollutant sources.   Second, as was Illustrated in
Example IV-5, a number of uniformly distributed point sources can be considered as a
single distributed source.  Third, combining several adjacent point sources is also
possible, 1f the length of the reach under consideration Is.long relative to the
distance of separation between the point sources.  Analogously, a distributed source
can be approximated as a point source, contributing the same waste loading and
located at the center of the distributed source.
     It may be that the planner wants only to determine the critical dissolved
oxygen concentration in each of a series of reaches.  In this case no more than
two values of dissolved oxygen per reach need be calculated.  Figure IV-21 shows the
solution process to be followed.
     One final note on dissolved oxygen evaluations should be made here.  It may be
that if the planner is interested primarily in  locating dissolved oxygen problems, he
need not perform any computations.  This is especially likely where dissolved oxygen
data are available at various locations on the river.  Plotting dissolved oxygen time
trends may reveal when, as well as where, annual dissolved oxygen minima occur.
 	 EXAMPLE IV-8
'                  Determining River Assimilative Capacity from                         ;
I                            Tables IV-17 and IV-16                                     j
j                                                                                       j
j         Suppose the user wants to determine waste assimilative capacity (MAC) for a    j
j    river reach that has the following characteristics:                                 j
                                         -348-

-------
f
                           Go to next
                           reach
                               Find D
                               at x
                               D  - Dc

                                at
                               X « 0
                                                  Determine k  and k,
                                                  for each reach
                                                   /  Begin reach |
                                                   I  calculations!
                                                \
                                            Find Do,L0

                                            (at x - o)
                                                   Find tc. xc * Utc
FIGURE  IV-21   FLOW PROCESS  IN  REACH BY  REACH  SOLUTION  TO
                CRITICAL DISSOLVED OXYGEN VALUES
                               -349-

-------
I           Critical  dissolved  oxygen  concentration • 5.0 mg/l  (-user establishes this)   I
j           Initial  deficit  • 1.0 mg/l                                                   j
j           Average  velocity •  0.5  fps                                                   j
j           Average  depth  »  4 feet                                                       :
           Chloride  concentration  • 0
           Temperature  range » 10*C to  35*C                                             !
!   First,  ka  and  kL  need  to be found.   From  Figure IV-17,  ka (20*) • 0.8/day,           (
I   and  from Figure  IV-11, kL « 0.4/day.  At  any other temperature then, kfl and          I
|   k^ can  be  found  from the temperature relationships previously developed:
                              \  •  (kL)2Q  1.047   T'20                        (IV-17)    !

   Using  Table IV-15 the  dissolved  oxygen  saturation  concentration  within  the tempera-  I
   ture range of  Interest can  be  found.  This  Information  can  then  be  then compiled     |
   Into Table IV-21  shown below.                                                        ;
                                       TABLE  IV-21

                        COMPILATION OF INFORMATION  IN  EXAMPLE  IV-8
T
(°C)
10
15
20
25
30
35
s
(mg/l)
11.3
10.2
9.2
8.4
7.6
7.1
Cc
(mg/l)
5.0
5.0
5.0
5.0
5.0
5.0
(mg/l)
6.3
5.2
4.2
3.4
2.6
2.1
VDc
0.16
0.19
0.24
0.29
0.38
0.48
k /k.
a L
2.5
2.2
2.0
1.8
1.6
1.4
   Using  the values of DQ/DC and ka/kL, LQ can be found, which 1n
   this case Is  the WAC.

       Procedure
       1. Table IV-21 Is entered  at the appropriate *a/kL column. This is
          2.5 at  10*C.
       2. Next, the entry within  the ka/kL column  in Table IV-17  is fountf
                                         -350-

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           such  that:

              Do/Lo  -   °o   .   0.16
        Since the left-most  column  of  Table  IV-17  1s  DQ/L0  and  the entries  are
   D /L  ,  the ratio  of  these values 1s calculated  until  that  ratio equals 0.16.
    CO                                                n  nc
   For example,  try  DO/LQ  »  0.05.   Then DC/LQ  « 0.23  and ^§ » 0.22 > 0.16; too
   big.

           Try 0 /LQ »  0.04.  Then  DC/LQ « 0.23  and      •  .17; close  enough.
                D.
                 .                ,  ,
           Then _£ . .23,  or LQ , L_i . 27.4 mg/1
                 0
I   The results are tabulated below for the temperature range  10*C to 35*C.
I
j                 T('C)         WAC (mg/1)         DO/LQ

!                  10            27.4            0.04
I                  15            20.0            0.05
I                  20            15.0            0.07
j                  25            11.3            0.09
j                  30             7.6            0.13
                  35             5.4            0.19
.   LQ is directly related to the loading  rate of BOD,  as expressed earlier
j   in Equation IV-41:
1           WAC - (L )          - LuQ" * "crU1caW5.38
I                   ° critical          QU  + Qw
j   From equation IV-41  the critical waste loading W can be found.   If desired,
   this procedure can be repeated for different river  flow rates,  and WAC and
•   wcritical  found for tne various flows.  To do this,  different  average depths
,   and velocities will  be needed.  Generally this analysis 1s most applicable  to
j   minimum flow conditions,  as this 1s the most critical situation,  but higher flows
I   may be of  interest  to assess the benefits of flow augmentation decisions.   Novotny
|   and Krenke) (1975)  have used a 20 year, 3-day low flow In  analyzing the  Holston
j   River in Tennessee.   For further discussion of low  flow calculations refer  to
j   Section 4.4.6.
        In interpreting the results of this example the user  should be looking
,   more at trends rather than particular  results.  For example,  notice how  the
J   WAC decreases with increasing temperature.  For every 10*  increase the WAC
   is approximately halved.   A similar relationship between WAC  and flow rate
   could also be determined.
        Finally, using Table IV-18, the travel time tc can be determined to
                                         -351-

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   the point of critical  deficit.  The appropriate DO/LO and ka/kL values ar*
   used to find tc.   Table IV-22 illustrates these results.
                                    TABLE  IV-22
                           CRITICAL TRAVEL TIME RESULTS
T(°C)
10
15
20
25
30
35
VkL
2.5
2.2
2.0
1.8
1.6
1.4
VLo
0.04
.05
.07
.09
.13
.19
t.
1
1
1
1
1
0
ka
.4
.3
.2
.13
.0
.9
ka
.•63
.71
.8
.9
1.0
1.1
todays)
2.2
1.8
1.5
1.2
1.0
0.8

                              END OF EXAMPLE  IV-8  	
                                                                               	I
I	EXAMPLE  IV-9
I
              Critical Deficit Calculations for Multiple Reaches
        Suppose  the  critical deficit  in  each of  the  three  reaches of  the  river
   illustrated  in Figure  IV-22  is  to  be  determined.  The conditions upstream  of
   the  first discharge  are:
                T »  27'C                   Depth  »  5.0 feet
                Q «  600  cfs                D  » 1 ma/1
                U -  0.4  fps                Lu « 2 mg/1
   Using these  data,  along with the  solution process outlined  in Figure  IV-21,
   the  following procedure can  be  used:
        1.   Determine ka, !CL for each reach.  For  this example it will be
   assumed  that  the  average depth, velocity, and temperature  remain relatively
   constant  over the three reaches,  so that k  and k|_ are  also the same.

            kd (20)  » 0.5,  (from Figure IV-17)
            kL (20)  • 0.35,  (from  Figure IV-11)
   Using the temperature  correction:
            ka (27)  » 0.60,  (from  Equation IV-34)
            k   (27)  - 0.43,  (from  Equation IV-17)
                                         -352-

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1
! 1
1
1
1
j Ou=lmg/l
• ._>_.^^_— -
Qu=600cf» i
1
i
j
.Mixing ^Mixing . 1
Zone / Zone ^s j
' O (§)(§)'
i I 1
i 1
! ^ !
™^~ • • • • • i • "~^^ )
ii 1 1 •
i
/ I2MI. ^/ 4MI. \ 1
IN /|N A, \
! B.O.D.L=40mg/l B.QD.L=50mg/l B.O.DL=20mg/l |
1 Q'SOMGO Q»60MGD Q = lOMGD |
• FIGURE IV-22 HYPOTHETICAL RIVER USED IN EXAMPLE IV-9
I The saturation dissolved oxygen concentration at 27*C and 0% salinity is (from I
j Table IV-15) 8.1
i
2. For the
|
mg/ 1 . |
1
first reach, calculate L and D : !
00
, . (2M60Q) + (40) (50) (1.55) :
1 Lo
i
600 * (50)(1.55) !
I • 6.35 mg/1 j
i
j For lack of

better information about the dissolved oxygen characteris- I
j tics of the waste, it can be assumed that 0 « D * 1 mg/1. The location |
of the critical deficit can now be calculated using Table IV-18, or Equation j
! IV-45. In this ex«nple Table IV-18 will be used. To use that table, the follow- •
j ing ratios are needed:
I
' Do/Ln m
i 0 0
! and
I
ka/kL m
1 a L
1
1/6.35 - 0.16 j
.
1
0.60/0.48 - 1.3 j
i i
. From Table IV-18, k t - .92 or ;
I a c 1
i
1
i
1
te - .92/0.6 • 1.53 days j
, . (0.4) (1.53) (3600) (24) . , j
c 5280 '
1 Since xc < 12, the critical deficit actually exists, and is located 10 miles j
| downstream. From Table 1V-17 0 can be found by entering it with the same 1
j ratios used in Table IV-18. The result is: j
j r£ * .38 — Of - 2_£ mg/1 j
1 0
•— i
-353-

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I   3.   Before the critical conditions In reach 2 can be calculated,  the con-
|   ditions  at the upstream end  of that  reach must  be established.  The conditions  at
j   the  downstream end  of  reach  1  are:
j            D -  2.3 mg/1, from  Equation IV-40
            L »  2.6 mg/1  from Equation  IV-42
   The  conditions at the  upstream end of reach 2 are thus:
            L  . (2.6)  (677)  +  (60)  (1.55)  .        /}
             0           677+93                  *
   0  « 2.3 can be used for lack  of  better information on the dissolved oxygen
   concentration in the effluent  to  reach 2.  For use in Table IV-18, it is found
   that:

            VLo • '28
   so
            kat - .76
            tc  • .76/0.6 « 1.3 days
            xc  « 8.3 miles
   Since reach 2 is only 4.0 miles long, the critical deficit is not reached.
   Instead the maximum deficit will  occur at the downstream end of reach 2, where
            D - 3.3 mg/1  (Equation IV-40)
            L « 6.22 mg/1 (Equation  IV-22)

        4.   For the beginning of  reach  3, LQ and 0Q must be found:
            L  - (20)(10)(1.55) * (770.51(6.22) . fi 5   l}
             0          770.5 + (101(1.55)
   For D ,  it can be assumed that C   «  5.0 mg/1.  From Equation IV-41, then:
            0-81   (8.1 - 3.3) (770.5) * (5.0)(10)(1.55) . 3 -   „
             0    '                 770.5 + 15.5
   The calculations of critical conditions can now be made for this  reach, as
   for the previous two.
1	END OF EXAMPLE IV-9	

4.4  TEMPERATURE

4.4.1  Introduction
     The biota comprising an established aquatic ecosystem generally respond negatively
to significant abnormal temperature fluctuations.  Anthropogenic modifications of
rivers and streams can alter the thermal regime, most often by elevating the maximum
and mean water temperatures.  Repercussions of elevated temperatures are manifested
                                         -354-

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through a shift in the ecological balance and 1n the water quality of rivers.  For
example, there is a progression in the predominance of algal species from diatoms to
green algae to blue-green algae as water temperature increases through a specific
range.  Thermal discharges can increase the ambient temperature enough to alter the
predominant species to the undesirable blue-green algae.  Increased metabolic activity
of aquatic organisms, such as fish, also accompanies elevated temperature.  If the
increase is high enough, the results can be lethal.  Much data are available today
(e.g., Committee on Water Quality Criteria, 1972) which specify lethal threshold
temperatures for aquatic organisms.
     Water quality may be adversely affected through decreased solubility of dissolved
oxygen and increased biochemical reaction rates.  Adequate dissolved oxygen levels,
particularly at elevated temperatures, are critical because of the increased metabolic
activity.  Yet, as previously discussed the saturation concentration of dissolved
oxygen diminishes with rising temperature.  Worse still, is the concurrent low flow
condition which is associated, in many parts of the country, with the warm summer
months.  For example, in a study of 30 river reaches in the U.S.  (EPA, 1974), 20 had
lower flows in the summer months than in the winter.  This situation further reduces
assimilative capacity and usually results in the most critical dissolved oxygen
levels over the year.
     *an can alter the thermal regime of rivers by removing trees, changing the flow
regime, and by increasing thermal discharges.   Diversions of water from a river can
reduce the water depth, and increase the mean and diurnal fluctuation of stream
temperature.
     In Long Island, modification of the natural environment of streams has increased
average stream temperatures during the summertime by as much as 9 to 14*F (Pluhcwsi,
1968).  Concurrent temperature differences of as much as 14 to 18*F between sites on
the sane stream were observed on days of high solar radiation.  A principal factor
involved in these occurrences was the removal  of vegetation along the banks of the
streams, permitting significantly greater penetration of solar radiation.  Other
contributing factors cited by Pluhowski Included increased stormwater runoff, a
reduction in the amount of groundwater Inflow, and the introduction of ponds and
lakes.

4.4.2  Equilibrium Temperature
     If a body of water at a given Initial temperature is exposed to a set of con-
stant meteorological conditions, It'will tend to approach some other temperature
asymptotically.  It may warm by gaining heat or cool by losing heat.  Theoretically,
after a long period of time the temperature will become constant and the net heat
transfer will be zero.  This final temperature has been called the eauilibrium
temperature, E.  At equilibrium, the heat gained by absorbing solar radiation and
                                         -355-

-------
           » Shortwave solar radiation  (400-2800 BTU ft"2 day"1)
           Hfl • Long wave atmospheric  radiation (2400-3200 BTU ft"2 day"1)
               Hbr-Long wave back  radiation  (2400-3600 BTU ft"2 day"1)
*
                  H  « Evaporative  heat  loss  (2000-8000 BTU ft"2 day"1)
                                                                       "2
                                                            "1
                          Conductive  heat  loss or gain (-320-+400 BTU ft"  day  )
                            - Reflected  solar (40-200 BTU ft"2 day"1)
                               -  Atmospheric reflection (70-120 BTU ft"2 day"1)
                       i   i
             NET RATE AT WHICH HEAT CROSSES WATER  SURFACE
 Ha " Hsr "  Har)
                                           (Hbr ~  H
c + He)JBTU ft"2  day"'
          Absorbed Radiation (Ho)           Temperature  Dependent Terms
          Independent of Water Temperature
                                                     "
                                              -  W(es  -  ea)
      FIGURE  IV-23
          MECHANISMS  OF HEAT TRANSFER ACROSS A
          WATER  SURFACE (PARKER AND KRENKEL,  1969)
long-wave radiation  from the atmosphere will exactly balance  the heat  lost by back
radiation, evaporation, and conduction.
     These heat  fluxes  are  Illustrated in Figure IV-23 which  also  shows typical ranges
for the fluxes.   Some of these terms (H$, HJf Hjr,  HJr)  are  independent of water
temperature,  while the  remainder (Hj,r»Hc»He) arc dependent uP°n w«ter  temperature.
At equilibrium then, Hn (net transfer) equals zero, or:
HS * Hsr
                             Ha " V " Hbr
                                -H
                         (IV-57)
     In actuality,  the water temperature rarely equals the equilibrium tempera-
ture because the equilibrium temperature Itself is constantly  chanolna with the
local meteorological  conditions.  The equilibrium temperature  will rise during
                                        -356-

-------
the day when solar radiation  1s  greatest,  and fall to a minimum at night when
solar radiation 1s absent.
     A daily average equilibrium temperature may be computed using a number of
factors Including dally average  values  of  radiation, temperature, wind speed,
and vapor pressure.  The daily average  value will reach a maximum in midsummer
and a minimum in midwinter.   Since the  actual water temperature always tends to
approach, but does not reach  the equilibrium temperature, it will usually be
less than equilibrium 1n the  spring when temperatures are rising, and greater
than equilibrium in the fall  when temperatures  are dropping.  During a 24 hour
period, the equilibrium temperature usually rises above the actual water temperature
during the day and falls below the water temperature at night, forcing the water
temperature to follow a diurnal  cycle.
     The amplitude of the actual diurnal water  temperature  cycle  is generally
dampened significantly In comparison  to the amplitude of the equilibrium temperature
cycle due to the large heat capacity  of water.  A thermal discharge into a water body
will usually increase the actual daily  amplitude because of the water temperature
dependent terms In Equation  IV-57. This situation is illustrated in the following
example (Edinger, et al., 1968).  Figure IV-24  illustrates  a flow through a cooling
pond into which a thermal effluent is discharged (at Station B).
                                        Sto H.
                                  Sto.G.
                         Sto E
                        Sto
                                    Sto. C
                 FIGURE  IV-24
SCHEMATIC OF  SITE No,  3
COOLING  LAKE  (FROM EDINGER,
ET  AL,,  1968)
Temperature observations were recorded  at  Stations 8 through H at four-hour periods
for one week.   The findings  are  depicted  in Figure IV-25.
                                         -357-

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              120
            UJ
                      7/18    7/19  '  7/20
                   DAY (4 HOUR PERIODS)
            7/21
                         7/22    7/23
7/24
           FIGURE  IV-25
OBSERVED TEMPERATURES,  SITE No,  3,
JULY 18  - JULY 24,  1965  (EDINGER,
ET  AL,,  1968)
The highest temperatures  and  largest diurnal temperature variables are recorded  at
Station B.   The peak  temperature  at Station B occurs just after noon,  corresponding
to the peak loading from  the  plant.  At Station C the peak temperature is at  1800
hours, Indicating  the lag in  flow time from Stations B to C.  The peak temperatures
at the remaining stations are more Influenced by meteorological conditions, and  less
by the thermal  discharge.  The  relationship of the observed temperatures to the
equilibrium temperature over  a  24-hour period is shown in Figure IV-26.   Note the
amplitude of the equilibrium  temperature E  (33*F amplitude).  The average equilibrium
temperature, T, is approximately  91 *F.  A progression from Station B to Station
H indicates that the  daily water  temperature tends to approach the average equilibrium
temperature.
     Stations G and H,  and  the  ambient temperature TN, all reflect the predominating
influence of meteorological conditions.  When the ambient water temperature is above
the instantaneous  equilibrium temperature E, it tends to decrease, and when the
temperature is below  E, it  tends  to Increase.  In the early morning and late  evening
hours, when E is low, the water temperature decreases at these stations.  During
midday when E is higher,  however,  the temperatures at these stations increase.

4.4.3  Calculation of Equilibrium Temperature
     Studies (Edinger and Geyer,  1965) have shown that the equilibrium temperature of
a well mixed body of  water  can  be estimated by:
HR - 1801
                                        K - 15.7   fe  - C(B) * 0.26
                                        K (.26+3)  L a
                                    '•J
                                                  (IV-58)
                                        -358-

-------
                                Tn (Ambient Temp.)


                                E (Equilibrium)
                           8       12       16
                            TIME OF DAY (MRS.)
                                                          24
        FIGURE  IV-26
                            COMPARISON  OF COMPUTED  EQUILIBRIUM AND
                            AMBIENT TEMPERATURES V/ITH OBSERVED MEAN
                            DIURNAL TEMPERATURE VARIATIONS  FOR SITE
                            No. 3,  JULY 18-JuLY 24,  1966  (EDINGER,
                            ET AL,, 1968)
where
       E     »  equilibrium teperature, *F
       K     »  thermal exchange coefficient, BTU/ft  /day/'F

       HD    «  net  incoming short (H.J and lonq (H   ) wave radiation
        K             A              s n             o n
                BTU/ftVday

       T     -  air  temperature, *F
        O
       ea    «  water  vapor pressure of ambient air at air temperature, mmHg
       B     «  proportionality coefficient, mmHg/*F
       C(B)  >  value  dependent on B, mmHq.

The thermal exchange  coefficient K is expressible as:


                        K - 15.7 + (0.26 + B) f(u)                       I
                                                                         ::v-59)
where
        f(u)  «  a function of wind speed.
Different relationships  for f(u) have  been developed.   For purposes of  hand ca'cula-
tions,  the following  relationship will  be used:
                              f(u)  «  11.4u
                                                                         (IV-60)
                                       -359-

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where
        u  •  the dally average wind speed in mph.
     To calculate E using Equation IV-58 an Iterative procedure is needed,  since K,
B, and C(B) depend on E.  The following steps outline a solution procedure.
        1.   Data needed to start the procedure Include T ,  relative humidity,
                                                         a
             wind speed, and net shortwave solar radiation.   Figure IV-27 illustrates
             daily average solar radiation reaching the continental United  States for
             the months July and August.  It is during these months that stream
             temperatures usually reach their annual maxima.  These values  do not
             account for the albedo of water (the percent of incoming solar radiation
             that is reflected), but since this is small, it can be ignored.  Because
             of the variability caused by topography, vegetative cover, and other
             factors, local sources of information should be used when possible for
             solar radiation values.
        2.   Calculate H. - H   + H   (BTU/ft2/day).  If Figure IV-27 is utilized
                        K    Sn    an                    _
             for Hsn, convert from langleys/day to BTU/ft /day by multiplying by 3.7.
             H   can be estimated from Table IV-23 by knowing the air temperature
             and the cloud cover fraction (0.1 to 1.0).
        3.   Determine e  from Table IV-24 by entering with T  and relative
             humidity.
        4.   Choose an initial value for E.  The air temperature T  can be  the
             first guess.
        5.   Enter Table IV-25 for B and C(B) at E (*F).
        6.   Knowing u, f(u), and B, calculate K from Equation IV-59.
        7.   From Equation IV-58 make the next estimate of E (E   ) by evaluating
             the right hand side of that equation (call this result F(E)).
        8.   The next estimate of E is Enew - 0.3E + 0.7 F(E).
             (Note:  this choice of E    brings aoout a more rapid convergence to
             the answer than would use of E alone).
        9.   If  IEnew-Ei  <1'F. thenEMtui, - Enew.
             If  |E,._ - El  > 1*F, return to step 5 with E__, and repeat the procedure
                  new
             until the convergence criterion is met, namely, E,c»uai *
      Instantaneous, daily, weekly, or even  longer term average equilibrium temperature,
T, can be calculated by using mean meteorological conditions over the period of
 interest and following the solution procedure just outlined.  Calculating the daily
 average T under the most crucial annual meteorological conditions (usually occurring
 in July or August) yields the highest temperature about which that water body tends
 to naturally oscillate.  The repercussions of man's activities in terms of altering
T can thus be  estimated and analyzed for potential  impact.
                                          -360-

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  JULY
                                       CANADA
  I
           MEXICO
  AUGUST
                                                          ,490
                                                             o
          NOTE:  To convtrt L«ngltys/diy to BTU/ftVd«y, multiply by 3.7.
FIGURE  IV-27   MEAN DAILY SOLAR  RADIATION  (LANGLEYS)  THROUGHOUT
               THE U,S, FOR JULY AND AUGUST  (U,S,  DEPARTMENT
               OF COMMERCED 1968)
                               -361-

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               TABLE IV-23
NET LONG WAVE ATMOSPHERIC RADIATION, H
                                      an
Cloud
Cover
.1

.2

.3

.4

5

6

.7

8

.9

1.0

Tempera-
ture
35
65
35
65
35
65
35
65
35
65
35
65
35
65
35
65
35
65
35
66
"an
(BTU/Sq.
Ft/Day)
1685
2400
1694
2412
1708
2432
1728
2461
1754
2497
1785
2542
1822
2595
1865
2656
1914
2725
1968
?803
Tempera-
ture
40
70
40
70
40
70
40
70
40
70
40
70
40
70
40
70
40
70
40
70
Han
(BTU/Sq.
Ft/Day)
1790
2540
1799
2553
1814
2575
1335
2605
1863
2644
1896
2691
1936
2747
1981
2812
2033
28H5
2091
2967
Tempera-
ture
45
75
45
75
45
75
45
75
45
75
45
75
45
75
45
75
45
75
45
75
Han
(BTU/Sq.
Ft/Day)
1900
2688
1910
2701
1926
2724
1949
2756
1978
2797
2013
2847
2055
2907
2103
2975
2158
3053
2220
3139
Tempera-
ture
50
80
50
80
50
80
50
80
50
80
50
80
50
80
60
80
50
80
50
80
"an
(BTU/Sq.
Ft/Day)
2016
2842
2026
2857
2043
2881
2067
2914
2098
2958
2136
3011
2180
3074
2232
3146
2290
3228
2365
3320
Tempera -
lure
55
85
55
85
55
85
55
85
55
85
55
85
55
85
55
86
5S
85
55
85
H
an
(BTU/Sq.
Ft/Day)
2138
3004
2149
3019
2167
3045
2192
3080
2225
3126
2265
3182
2312
3249
2366
3325
2428
3412
2497
3509
Tempera-
ture
60
90
60
90
60
90
60
90
60
90
60
90
60
90
60
90
60
90
60
90
H
an
(BTU/Sq.
Ft/Day)
2266
3173
2277
3190
2296
3216
2323
3254
2358
3303
2400
3362
2450
3432
2508
3513
2573
«604
2646
3707
                   -362-

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                       TABLE  IV-24
SATURATED HATER VAPOR PRESSURE. e$, VERSUS AIR TEMPERATURE, Tfl,
                   AND RELATIVE HUMIDITY
'a
(°F>
35
40
45
50
55
60
65
70
75
80
85
90
95
100
V
(nmHg)
5.2
6.3
7.6
9.1
11.0
13.1
15.6
18.6
22.0
26.0
30.5
35.8
41.8
48.7
RELATIVE
0.1
0.5
0.6
0.8
0.9
1.1
1.3
1.6
1.9
2.2
2.6
3.1
3.6
4.2
4.9
0.2
1.0
1.3
1.5
1.8
2.2
2.6
3.1
3.7
4.4
5.2
6.1
7.2
8.4
9.7
0.3
1.6
1.9
2.3
2.7
3.3
3.9
4.7
5.6
6.6
7.8
9.2
10.7
12.5
14.6
0.4
2.1
2.5
3.0
3.6
4.4
5.2
6.2
7.4
8.8
10.4
12.2
14.3
16.7
19.5
0.5
2.6
3.2
3.8
4.6
5.5
6.6
7.8
9.3
11.0
13.0
15.3
17.9
20.9
24.4
H U M 1
0.6
3.1
3.8
4.6
5.5
6.6
7.9
9.4
11.2
13.2
15.6
18.3
21.5
25.1
29.2
1 D I T Y
0.7
3.6
4.4
5.3
6.4
7.7
9.2
10.9
13.0
15.4
18.2
21.4
25.1
29.3
34.1

0.8
4.2
5.0
6.1
7.3
8.8
10.5
12.5
14.9
17.6
20.8
24.4
28.6
33.4
39.0

0.9
4.7
5.7
6.8
8.2
9.9
11.8
14.0
16.7
19.8
23.4
27.5
32.2
37.6
43.8

1.0
5.2
6.3
7.6
9.1
11.0
13.1
15.6
18.6
22.0
26.0
30.5
35.8
41.8
48.7
                             -363-

-------
                                      TABLE IV-25

                        B AND C(B) AS FUNCTIONS  OF TEMPERATURE
Temperature
(°F)
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69

B
(mmHq/°F)
.286
.296
.306
.317
.328
.340
.352
.365
.378
.391
.405
.419
.433
.448
.464
.479
.496
.512
.529
.547
.564
.583
.601
.620
.640

C(B)
(mmHq)
-5.5
-4.5
-4.1
-4.2
-4.6
-5.4
-6.3
-7.5
-8.7
-10.0
-11.2
-12.5
-13.6
-14.7
-15.8
-16.7
-17.6
-18.3
-19.0
-19.6
-20.1
-20.7
-21.2
-21.7
-22.3

Temperature
(°F)
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
B n
(mmHq/°F)
.660
.680
.701
.722
.743
.765
.787
.810
.333
.857
.881
.905
.930
.955
.980
1.006
1.033
1.060
1.087
1.114
1.142
1.171
1.200
1.229
1.259
1.289
C(B)
(mmHq)
-22.9
-23.6
-24.4
-25.4
-26.5
-27.8
-29.3
-31.0
-33.0
-35.1
-37.6
-40.3
-43.2
-46.4
-49.7
-53.3
-57.1
-61.0
-64.9
-68.9
-72.9
-76.7
-80.4
-83.8
-86.8
-89.3
	 EXAMPLE  IV-10
                    Calculation  of Equilibrium Temperature

        On  Long  Island, New York,  studies done by Pluhowskl  (1968) have  Indicated
   that  shading  of  streams by  a natural  vegetative canopy can drastically  affect the
   shortwave  solar  radiation reaching  those  streams.  The results of  some  of his
   findings are  presented  1n Table IV-26.  In the simmer, when  leaves are  on the
   trees, the actual solar radiation reaching the Connetauot River can be  as low as
   29X of that reaching unobstructed sites at nearby Mlneola or Brookhaven.
        Suppose  the user  1s Interested  1n predictinc how the removal  of  the riparian
                                         -364-

-------
                                          TABLE IV-26


                                SUMMARV OF SOLAR-RADIATION DATA
                    FOR MINEOLA, BROOKHAVEN, AND THE CONNETQUOT RIVFR SITES
Mean-Dally Solar Radiation in Langleys:
for the Indicated Periods

Solar
Site
(1)
1
2
3
1

2
3
1
2
3
1
2
3
1
Notes :


Dates
(2)
Jan. 30, 31, 1967
Jan. 28, 29, 1967
Jan. 25, 26, 1967
Apr. 21-23, 1967
Apr. 16-18, 1968
Apr. 19, 20, 1967
Apr. 24-26, 1967
June 9-11, 1967
June 7, 8. 1967
June 12-14, 1967
Aug. 26-28, 1967
Aug. 22-24, 1967
Aug. 29, 30, 1967
Nov. 28. 29, 1967



Mineola
(3)
235
148
135
466
452
436
408
600
664
527
275
277
504
204



Brookhaven
(4)
244
130
135
464
502
386
411
599
671
523
260
328
484


Connetquot
River
Estimated
(5)
240
137
135
465
502
429
410
599
669
525
266
308
492
204

Connetquot
River
Observed
(6)
148
96
104
343
389
384
401
254
531
443
78
162
338
86

Ratio=
Connetquot River
Observed
Connetquot
River
Unobstructed
(7)
0.62
.70
.77
.74
.77
.90
.98
.42
.79
.84
.29
.53
.69
.42

Solar site 1  is typically heavily forested,  solar site 2 is moderately to heavily forested,
and solar site 3 is moderately forested.

Radiation data in column 5 are estimated unobstructed horizon values for Connetquot River
based on data from Mineola and Brookhaven (cols.  3,4).
                                                   -365-

-------
   vegetative cover might effect T.  Consider the period 22-24 August, 1967,  when
   the Connetquot River received 162 langleys/day of a possible 308 langleys/day of
   shortwave solar radiation.  Representative meteorological conditions at this time
   were:
                                            Ta . 65*F
                                            u  » 2 mph
                          Cloud cover fraction « 0.5
                             Relative humidity - SOX
        The steps in solving for T are as follows:                                     I
I           1.   Data have been gathered, as previously listed.                         |
j           2.   H$n » 162 (3.7) « 600 BTU/ft2/day.  This value assumes that the vege-  j
j                tative canopy blocks 47X of the solar radiation.  From Table IV-23,    j
j                Hin is (.5 cloud cover at 65*F) 2497 BTU/ft2/day.  Thus,
I                                                  ?
                     HB - 2497 + 600 « 3097 BTU/ftVday.
I                                                                                       I
           3.   At SOX relative humidity and an air temperature of 65*F, e  »          J
!                12.5 mmHg from Table IV-24.                                            J
I           4.   As an initial guess of E, assume E, « 65"F, the air temperature.       I
j           5.   From Table IV-25, B - .56, C(B) - -20.1                                j
j           6.   K » 15.7 + (.26 + .56) (11.4) (2) » 34.4                               j
I           7    c/c i . -0.05(65)2 A 3098 - 1B01 A 34.4 - 15.7                         j
;                 * 1'       34.4        337334.4(.Z6 * .56)                     |
I                      X [12.5 * 20.1 * .26(65)] - -.6.1 + 37.7 + 33.0 - 64.6           I
I           8.   E2 - .3(65) + .7(64.6) - 64.7                                          \
j           9.   Since lEj-Ejl < 1'F     I ' 64.7'F                                     j

j        Mow suppose the user wants to findT for no reduction in H$n due to shading.   j
I   Steps 1 through 9 again are repeated, using H   « 308(3.7) »                        I
.              j                                 *"                                     '
|   1140 BTU/ft /day, with otherwise the same meteorological conditions.  Without de-   I
j   tailing the calculations here, it is found that T « 74.7*. a 10"F Increase.          |
j        It is evident then that altering the solar radiation penetrating to the        j
j   stream can significantly change T.  Even more severe cases of repression of short-  j
<   wave radiation (as noted by the 71X reduction on 26-28 August, 1967, Table IV-26)
!   are possible, exemplifying the large differences which may be observed.
!                                                                                       I
I	ENO op EXAMPLE IV-10	J

     The approach Illustrated in Example IV-10 for predicting equilibrium temperature
is obviously time consuming, and has been programmed for hand held calculators in
Mills et .a_L (1979) .  A simplified approach is also available for predicting equi-
librium temperature (Brady ^ _aj_., 1969) and is described below.  The predictions are
usually within 3*F or less of those found by the more complicated approach.

                                         -366-

-------
      The  data  required for  the  simpler  approach  are:
        T^, dewpoint  temperature  (*F)
        U, mean daily wind  speed  (mph)
        H   net  incoming shortwave radiation (Btu/ft /day).
 Short wave solar  radiation  data were previously  shown in Figure  IV-27. The Climatic
 Atlas (U.S. Department of Commerce, 1968) contains compilations  of dewpoint tempera-
 ture  and  windspeed.   Figures  IV-28 and  IV-29 show these data for the months of July
 and August.  Figures  IV-27  through IV-29 provide the user with all the data needed to
 predict equilibrium temperature using the approach of Brady et al.
      To find the  equilibrium  temperature the following equations are applied
 sequentially:

                 COMPUTE ONCE   	>•   F(U)  -  70 * 0.7 U2                    (IV-61)

                                   _   T     - ^E, + TDW 2                  (IV-62)

                                        B     -  0.255  - 0.0085T *  Q.00020«T2    (iv-63)

                                        K    -   15.7 * (fi  *  .26 )  F(U)          (IV-64)

                                        Eui  "  TD * Hs '  K                    (IV-65)

The wind speed function f(U) is found once from Equation IV-61.  The dewpoint tem-
perature (T.)  is a convenient starting  choice as an initial  guess of the equilib-
rium temperature.   T can then be calculated from Equation  IV-62;   B from Equation
IV-63;  K from Equation IV-64;  and finally a new equilibrium temperature (Ei+t) from
Equation  IV-65.  If E^ and E^ differ by more than 1*F,  return  to Equation IV-62 with
E-+j and repeat the procedure until convergence is attained (usually within 2 or 3
cycles).
             ITERATE OVER
             THESE EQUATIONS
	 EXAMPLE IV-11 	

             Equilibrium Temperature Using Simplified Approach

     Determine the average daily surface water equilibrium temperature for Little
Rock, Arkansas during the month of August.  Based on Figures IV-27 through IV-29
the following data are found:
        Td  - 68'F
        U   - 7 mph
        HJn - (525M3.7) - 1943 Btu/ft2/day
                                       -367-

-------
                               JULY
                                                                 55
                                                                  65
                                                       75-
                            AUGUST
                            70
                                                      75-^75
FIGURE IV-23  MEAN DEWPOINT TEMPERATURE  (°F)  THROUGHOUT  THE
              UNITED STATES FOR JULY AND  AUGUST  (U,S,  DEPART-
              MENT OF COMMERCE, 1968)
                                -368-

-------
                          JULY
FIGURE IV-29  MEAN DAILY WIND SPEEDS  (MPH) THROUGHOUT  THE
              UNITED STATES FOR JULY  AND AUGUST  (U.S.  DEPARTMENT
              OF COMMERCE, 1968)
                            -369-

-------
   Assume as a first guess that E » T  »  68*F                                           I
   then:                                                                                j
I           f(U)  • 70 * .7 (7)2 • 104.                                                  I
1           T    - {Td + Td)/2 - 68*                                                    I
j           B    • .62                                                                  j
j           K    - 15.7 * (.62 + .26) (104)  « 107.                                       j
•           E    • 68 + 1943/107 - 86*F                                                 j
.   For the second Iteration:
I                                                                                       I
j           T » (86 + 68)/2 «  77
!           B - 0.81                                                                    !
!           K - 127                                                                     I
I           E « 83.3'F                                                                  I
•                                                                                       *
|   At the end of a third iteration E « 83.7*F,  so  convergence has been attained by     I
i                                                                                       i
|   three  iterations.                                                                   |
j       As a comparison, the  equilibrium  temperature will  also be calculated using     j
•   the longer approach.   The  required data  are:                                         '

\                 Ta  «80'F                                                            i
j                 Td  '68*F                                                            i
'                 U   - 7.
j                 Hsn - 1943                                                            -
I           sky cover • 0.5 (from climatic atlas)                                        \
|   A summary of  the procedure is:                                                      I
|           1.   Han - 2958                                                             !
I                H^  • 1943 +  2958 « 4901                                                I
j           2.   Since Td » 68*. e « 17.4                                                \
j           3.   Choose E » Tfl - 80*F                                                   j
j           4.   B      .881                                                            j
                C(B) - -37.6                                                            j
!           5.   f(U) - 70 + 0.7 (7)2 » 104
!                K    • 15.7 + (0.26 + .881)  (104)  • 134
|           6.   F(E) • 79.3                                                            !
j           7.   E • .3(80) *  .7 (79.3) -  80*F,  after one pass.                         I
j   Since  the starting guess of 80*F is virtually Identical  with the calculated value   |
j   at step 7, a second iteration is not required.   The two  procedures predict equi-     j
j   librium temperatures which differ by about  4*F.                                     j
,                                                                                       i
!	END OF EXAMPLE IV-11	1
                                         -370-

-------
     To estimate the effects of shad 1 no,  the incoming  solar radiation  should be
calculated first assuming no shading,  but otherwise  using  existing  meteorological
conditions for the time of the year of interest.   The  effects  of  shading  should be
superimposed upon this result ss a percent reduction.   The following  (Pluhowski,
1968) can serve as guidelines in estimating solar  radiation reduction:
        •    0-25 percent reduction:  shading generally restricted  to  early morning
             and late afternoon.
        t    25-50 percent reduction:   some sunshine penetration  in morning and
             evening.  Considerable sunshine between 1000  and  1400  hours.
        •    50-75 percent reduction:   very little sunshine penetration in morning or
             late afternoon.  Scn^e sunshine between  1000 and 1400 hours.
        •    Greater than 75 percent reduction:   very  little penetration  even at  noon.

4.4.4  Screening of Thermal Discharges

4.4.4.1  Introduction
     This section presents a set of procedures which can be used  to determine whether
the thermal discharge at a proposed power plant site or the discharge from the
expansion of. an existing site is likely to violate thermal standards.   Procedures are
presented to test for contravention of the following types of standards:
        t    The AT Criterion:  The increase In temperature of water  passing through
             the condenser must not exceed a specified maximum.
        •    The Maximum Discharge Temperature Criterion:   The temperature of the
             heated effluent must not  exceed a specified maximum.
        •    The Thermal Block Criterion:  The cross-sectional area of a  river
             occupied by temperatures greater than a specified value  must not exceed
             a specified percentage of the total  area.
        0    The Surface Area Criterion;   The surface area covered  by isotherms
             exceeding a specified  temperature increment (above ambient)  must not
             exceed a specified maximum.
Actual values associated with the above standards vary by political jurisdiction.
Accordingly, regulations must be consulted.
     The thermal discharge screening procedures are designed to address the following
questions:
        t    Is  the power plant, as proposed, acceptable at the candidate  location?
        •    What is the largest power plant that can be placed at the candidate
             location?  Eguivalently, can an existing power plant at  the  candidate
             location be expanded?
     The methods do not analyze interactions among multiple powerplznts on the same
river.  Such an  analysis can be rather more complex.  A report by Tetra Tech (1978)
                                         -371-

-------
             Intake Channel	^_J i |     1       '*  '  \ j.   	Outlet
                                                              Channel
                                     PLAN VIEW


           FIGURE  IV-30      IDEALIZATION OF A RUN-OF-THE-RIVER
                                POWER  PLANT

addresses that question.
     The methods developed to evaluate  in stream thermal criteria use heat balance
equations assuming a steady-state,  well  mixed system  at low flow.  The power plants
are assumed to employ once through  cooling,  as shown  1n Figure  IV-30.
     The selection of well mixed conditions  appears  to  be  justified. Studies by
Stefan and Gulliver (1978) on the Mississippi and Missouri Rivers  have dealt with  the
lateral mixing of thermal plumes which  were  released  at the shoreline and were not
Initially well mixed across the river.   The  Investigators  found that over a short
distance, thermal losses were negligible and that the well-mixed Isotherm (the
Isotherm that would result were the plume Initially  well-mixed  laterally  and ver-
tically) eventually extended across nearly the entire width of  the river, albeit  at
some distance downstream.  This Indicates that 1f the thermal block  criterion  1s  not
met for  the well mixed case, 1t Is not  likely to be  met for the shoreline discharge
either.  A similar conclusion can be reached regarding  the surface area constraint.
Thus,  at this  level of analysis, it Is  not necessary to consider the consequence  of
Incomplete lateral or vertical mixing adjacent to the shoreline discharge.
     One simplification which can be used at the option of the  user for the  surface
area calculation  should be mentioned.  Surface water that  1s  undisturbed  by  anthro-
pogenic  Influences (in a  thermal sense) approaches the  equilibrium temperature.   This
temperature  1s  dictated by natural meteorological conditions.   Surface water  tempera-
ture in  rivers, especially during steady  low-flow periods, can  be near equilibrium.
In calculating the surface area occupied by  Isotherms exceeding a  specified tempera-
ture,  it 1s necessary to know the equilibrium temperature. However, since the
procedure for calculating equilibrium temperature 1s  fairly complicated, considerable
savings  1n computational effort can be  obtained  by assuming the ambient water
1s at  Us equilibrium temperature.
     Some circumstances,  in addition to anthropogenic Influences,  tend to produce
ambient  temperatures different from eauilibrlum.   For example:
                                         -372-

-------
        •    Locally, large Quantities of groundwater may discharge into the river
        •    Hypo limn ionic releases from large reservoirs may occur nearby
        •    Snow melt may supply a substantial amount of inflow.
     As a result of the first two influences, the stream water temperature may be
lower than equilibrium since the source of the water comprising the stream flow has
been shielded from the heating effect of solar radiation.  Snow melt,  although not
likely to influence the river's thermal regime during the late summer,  can be important
through spring and into early summer in areas where high-mountain  snowpack exists
over most, or all, of the year.
     The screening procedure that follows assumes the river water,  once it has been
heated by the thermal plume, is above equilibrium.  This means that the water tempera-
ture will then decrease in the downstream direction, which is generally, but not
always, true.
     Table IV-27 shows the data needed to apply the thermal screening  methods.   The
symbols are defined in the table and suggested default values are  given for variables
where appropriate.   The variables are introduced in the table in the order they occur
1n the screening procedure.

4.4.4.2  Evaluating the Thermal Block Criterion
     The initial temperature elevation that results when the thermal plume becomes
well mixed with the river water is given as:
                                                                              (IV-66)

                                     !c ^ .  1    3.414 x 10*               (IV_67)
                                                    ^
where
        AT^  •  temperature elevation of the initially well mixed isotherm
                 CF)
        Q     •  flowrate of cooling water (m3/s)
                  e "  r '   '
        T     «  temperature of heated effluent (*F)
        T     •  temperature of river water upstream of power plant (*F).

        All other terms are defined  in Table IV-27.
To  f ind AT^, Equation IV-67 is solved.  If AT^ is less than the thermal block temper-
ature  increment (ATtb), the thermal block criterion is not contravened.  Otherwise,
it  is.
                                         -373-

-------
                            TABLE  IV-27

           DATA  NEEDED FOR THERMAL  DISCHARGE SCREENING
Variable
                  Term Definition
                                                   Default Value
  MWe
  P



  CP


 ATtb
AT,
  maxl
 'max 2


Temperature of heated effluent (*F)

Maximum legal allowable tempera-
ture of heated effluent (*F)

The lesser of ATMX, and
AT     i»f\     m*xl
ATmax2 ( F)

The maximum allowable flow rate
through the cooling system
                                            new fossil fuel
                                            plants:38
                                            nuclear plants:32

                                            new fossil fuel
                                            p1ants:48
                                            nuclear plants:6S

                                                   7(>10


                                                   1000


                                                   2.2


                                                   5



                                                  20
The isotherm defining the boundary
of the surface area for which legal
Units have been established (*F)

Mean velocity of the river
(m/s)

Mean hydraulic depth of river 1n
reach under consideration («)

Equilibrium temperature (*F)

Surface thermal transfer coeffi-
cient (Btu/d • »F • n»2)
                                                        .25Qp
                             -374-

-------
                                  TABLE IV-27 (continued)
               Variable
         Term Definition
Default Value
                  sa
                 Tra
               Relative
               humidity
                  sn
                 an
Surface area of river down to AT
isotherm (mO

Legal maximum surface area limit
which can be covered by  the AT
and greater Isotherms  (m2)

Average surface width of river
down to AT   Isotherm  (m)

River temperature just above where
a tributary joins the mainstem
CFJ

Temperature of tributary (°F)

Flow rate of tributary (m3/s)

Air Temperature (°F)
Wind speed  at  7 r.eters above
surface (m/s)

Net shortwave  solar radiation
(Btu/m2 • d)

Net long v.ave  solar radiation
(Btu/m2 . d)
4.4.4.3  Acceptability of  the  Temperature Rise Across the Condenser

         and of the Temperature  of  the Heated Effluent

     Whether these criteria  are  met or not depends on a number of factors,  such  as

the cooling water flow rate.   Since the cooling water flow rate can be designed  to  be
within a specified range,  it  is  determined here whether a feasible range exists  such

that the two above mentioned  criteria are met.
     The minimum acceptable  flow rate such that both temperature criteria do  not
exceed their standards is  as  follows:
                     
-------
     As an example of how ^Tmaxm^m is chosen, suppose the following conditions exist:
        Maximum  legal temperature rise across the condenser « 20*F
           Maximum legal temperature of the heated effluent • 86*F
                                  Ambient river temperature » 74*F.
From these conditions, ^Tmax2 (tne allowable temperature Increase across the condenser
such that the temperature of the effluent does not^ exceed the legal maximum) » 86*F -
74*F » 12*F.  So  Tmaxm1n » minimum (20*F, 12*F) - 12*F.  12'F must be chosen, then,
as the maximal temperature rise across the condenser.
     Once Equation IV-68 has been solved, the ratio of cooling water to river flow
should be checked so that the value 1s within acceptable limits.  Equation  IV-66 can
be rewritten as:
 Since AT    has been calculated from Equation  IV-67  and AT has been calculated  as
        wm
AT     . , the flow rate  fraction can be calculated  from Equation  IV-69.   If this
  maxmifn
 fraction exceeds  a certain  percent (e.o., 25  percent or some user defined value),
 then the cooling  water flow rate is too large to be acceptable.   If the flow rate
 fraction  is not excessive,  the actual  flow  rate can be chosen so  that:

                         

 where
         (Q )     »  maximum allowable cooling water flow rate (m/s)

 4.4.4.4  Evaluating  the  Surface  Area Constraint
      The  evaluation  of this criterion may require the user to perform considerably
 more calculations than for any of  the other prescreenlng criteria.   The two major
 complicating factors that are encountered are:   1.  determining the river equilibrium
 temperature, and  2.   evaluating  the  effects of tributaries.
      If 1t Is the case that AT   does not exceed AT   the surface area criterion
                               MH                   ) 4
 will not  be contravened  and no calculations have  to be performed.'  If AT_ exceeds
 AT  ,  the criterion  might be  exceeded.  In this  case  It 1s necessary to determine
 the distance from the location of  the thermal discharge to the downstream location
 of the AT   Isotherm.  This distance 1s given by:
                              -pC  Vd
                                         -376-

-------
where
        Tsa  '  *Tsa * Tr
        Twm  -  *m * Tr
Section 4.4.3 discusses procedures for predicting  K  and  E.   Once  K  and  E  are  found,
x   can be determined from Equation IV-71.   If one or  more  tributaries  exist  with
the distance x,,, then xc, should be recalculated  as discussed  in Section 4.4.4.5.
              s a        s a
     The surface area Included within this  reach  is:

                                  A - xe, •  W                                (IV-72)
                                       So

where
        A  »  surface area of the river from the  point of thermal
              discharge to xcl (m )
                            S o
        W  »  average river width in this reach (m).
If A < A   then the surface area criterion  is not  contravened.  Otherwise,
        s a
1t is.

4.4.4.5  Evaluating the Effects of a Tributary 1n  Mitigating Temperature  Within
         a Thermal Plume
     Tributaries, when they join a river subjected to  the  Influences of a thermal
plume, generally act to reduce the elevated river temperature.   They may  therefore
prevent the surface area constraint from being exceeded  when It otherwise would.
     Equation IV-71 assumes no tributaries  exist  throughout the reach defined
by x  .  If It 1s found that x   > xt (xt 1s defined below  under  Equation
IV-73) then 1t 1s necessary to examine the  Impact  of the tributary  flow on  the
surface area constraint.  This 1s done by computing  the  water temperature (°F)
just above the location where the tributary joins  the  mainstream  using the  following
equation:

                    Tr,  '   (Twm-E)«*p(PCpVd'*24.  360o) * E            (IV'73)

where
        Tra  "  r1ver temperature just upstream of tributary (°F)
        x^   •  distance from power plant discharge  to tributary  (m).
After the river has mixed with the tributary the  new river  temperature (°F) 1s
given by:

                                       . TraQr *  TtQt                        (IV-74)
                                   new     Q+ Qt
                                         -377-

-------
where
        T,  •  temperature of the tributary (°F)
         1                              3
        Qt  •  flow rate of tributary (m /s).
If:
                                      newl*Tsa + Tra                      
then this location marks the downstream location of the AT   Isotherm  and
the surface area A can be calculated using the distance x   as  the  distance
down to the tributary, xt-  Otherwise the AT   isotherm 1s located  further
downstream.  In this case Equation IV-71 1s reappHed (first making appropriate
adjustments to V and d) where the Initial  temperature Is  (Tr)new (which  was
T   in Equation IV-71) and the final  temperature 1s still  T  .   The distance  x,,  is
 *nn                                                        sd                 sa
determined by adding this additional  distance to xt.

4.4.4.6  Determining Whether the Thermal Block or the Surface Area  Constraint
         Is the More Limiting
     One of these two constraints may cause a greater limitation on power  plant
size than the other.   If AT.  < AT,, the thermal block constraint will
                           tb     sa
be more limiting, and there is no need to continue with the analysis in  this  part.
If, however, ATtb > AT$a, the surface area constraint may be more limiting.
To determine 1f It is, find AT^ (call 1* AT    ) using the following  equation:


                                                   '^sa
where
                             Tsa  '  E     exp   £Tvd .  24 0600 I  ' Tr       (IV-76)
                                   Tsa " *Tsa * Tr                           
                                        Sa_                                  (IV-78)
                                         U
If a tributary exists in the reach delineated  by x,.,  recompute  x,,  as  outlined
                                                  sd              sa
1n Section 4.4.4.5.
     If AT     < AT... , the surface area  constraint is  more  restrictive,  so
          WSJlid     tD ~
set AT   » AT    .   Otherwise set AT^. « AT... .
      fNn     WITiS a                   Win     tO

                                         -378-

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 4.4.4.7  Determining the Maximum Plant Capacity
      The maximum power plant capacity can be determined based upon the maximum
 well  mixed temperature elevation and the river flow rate.  It is given by:


                   414 x 1C6
                              e
                            « -^ •  DC  'AT  Q  •  	^5—                 (I)
                               C     p     "" r   3.4.4 x 106

 By using Equation  IV-80 and the maximum allowable AT   , the maximum capacity
 can be found.

 4.4.4.8  Readjusting the Maximum Cooling Water Flow Rate
      If the minimum acceptable  flow rate 1s greater than the maximum allowable,
 the power plant size must be reduced.  To do this, set:



 where
        Q0       «  actual cooling water flow rate (m /s)
                 «  maximum allowable cooling water flow rate (m /s).
                                                 (Q  )
                                 T   - AT     .    P max                      (IV-82)
                                  wm   u maxmin   Q
        ATmaxmin  "  AT calculated earlier.
          p
AT    is  recalculated by:
  wm
where
(Note:  the surface area and thermal block constraints are still met and need
net be recomputed.)
p	EXAMPLE  IV-12	

I
              Estimating AT Across  a Power Plant Heat Exchange 'Jr.it

I         Suppose  the  user wants  to determine AT for the Hartford E'ectric Light
I    Company's South Meadow Steam Electric Power Plant (a fossil fuel plant) located on
|    the Connecticut River. Data  available are (Jones £! _a_K , 1975):
i
I            Capacity	217 WM
|            Cooling water flow rate	341 ft3/sec
                                         -379-

-------
   where
           YC  -  62.4 BTU/ft3/8F
           QQ  -  flow rate, ft3/sec.
   Substituting the appropriate values Into the above equation, 1t 1s found that
   (using the known thermal loading to the cooling water):
j   Equation IV-83 Is not feasible to use when the thermal loading rate to the
j   cooling water Is unknown.  As an alternative approach, the following expres-
•   slon can be employed:

j                          AT . .1  . !i Mye  . _1_ .  3-4U3|0™*                (IV~84)

I   where
|           e    «  percent of total energy produced that 1s transmitted as
j                   electricity.  For new fossil fuel plants:  38 percent; for
j                   nuclear plants:  32 percent
           e    «  percent of total energy produced that Is dissipated through
                   cooling water.  For new fossil fuel plants:  48 percent;  for
'                   nuclear plants:  68 percent
                                          -380-
I           Waste heat discharged to cooling  water .  .  .  422 HW
|   Since the waste heat being dissipated  through  the cooling  water  1s  known, AT
j   can be calculated directly using that  value  in conjunction with  the  known  flow
j   rate.  Assume,  however,  that the waste heat  being discharged  1s  not  known.   It can
'   be estimated from the plant capacity as follows.  First, assume  the  plant  effid-    j
•   ency is 33 percent.  The rate at which fuel  Is burned when at  capacity  is  then:

j           — - 658 MW                                                                |
           .33
!   If 10 percent of the total energy is lost up the stacks, then  approximately
!   58 percent is dissipated through the cooling water, or:                              J
!           658 (.58)  «  382 MW                                                        !
J   Compared with the known  422 MW of heat discharged to the cooling water,  the          j
I   above calculation would  underestimate AT.                                           I
I   AT  1s  calculated  by:                                                                (
i                                                                                       i
i           AT « tnerTial  loadinc  rate  to  cooling  water 1n megawatts  x                 j

-------
I            MWe   «  capacity  of  power  plant  In megawatts electric.
j    Equation IV-84 predicts that AT  1s:
i
!                    1     58    -,,    1     3.414    106     ,, cor
|                   34T '  37   *217  6T4	1600—  '  17'5 F

'   AT 1s only about 1°F  less than predicted by  Equation IV-83.
I
I	END OF  EXAMPLE  IV-12	

 4.4.5  Longitudinal  Temperature  Variation
      If the  temperature  at  a  particular  location  1n  a  river  1s known, the  steady-state
 temperature  distribution downstream from that  point  can  be estimated by:

                               T  - E  	  /-.061  • Kx  i                    (IV_
                                  -  E   CAK  V   oCpUd
where
        T   «  temperature at x - 0, *F
        T   «  stream temperature at a distance x, where x is measured in miles
        E   »  equilibrium temperature, *F
        K   «  thermal transfer coefficient, BTU/ft2/day/*F
        U   -  stream velocity, ft/sec
        d   «  stream depth, feet
        P   -  water density, lb/ft3
        Cp  »  heat capacity of water, BTU/lb/*F (PCp - 62.4 BTU/ft3/*F).
     An important fact is revealed upon inspection of Equation IV-85.   Suppose
that a thermal discharge heats the ambient water to a temperature T ,  but
T  is  less than the instantaneous equilibrium temperature E.  In that  instance
the stream temperature will continue to rise exponentially downstream, approaching
E.  The rate at which T approaches E is dependent on the thermal transfer coeffic-
ient,  as well as stream velocity and depth.  Equation IV-66 is graphically illus-
trated in Figure IV-31.
f	  EXANPLE IV-13  	
i
j                               Use of Figure IV-31

I                                                                               ?
        Suppose an average dally thermal transfer coefficient, K,  of 200 BTU/ft /day
;   has been calculated.  The river of interest has an initial  temperature "excess"
I   (i.e., T -E > 0).  How far downstream will that excess be 50 percent of the
                                         -381-

-------
     FIGURE  IV-31      DOWNSTREAM TEMPERATURE PROFILE FOR COMPLETELY

                        MIXED STREAM, T-E/TM-E vs,  r (FROM EDINGER,

                        1965)                "
I
original?  Other  stream data:



       U    -  .5 fps


       d    « 4 feet


              62.4 BTU/ft3/*F
I          pl


-------
   x «      0
         rcCdU   (0.68) (62.4) (4) ( .5){24)(3600)
                                200
        3.6 x 104 *"eet - 6.9 miles
   The associated travel time is T » 3'6 jl 10  x -      hr - 20.4 hours

                                        '
                              END of EXAMPLE IV-13 --------------------- '
4.4.6  Diurnal Temperature Variation
     Although it is beyond the scope of this report to analyze diurnal stream temper-
ature variations, a few brief statements should be made.  Diurnal stream temperature
variations on Long Island, New York, were mentioned in Section 4.4.1.  Documentation of
large diurnal temperature variations is not limited to New York.  For example, studies
in Oregon (Brown, 1969), Hawaii (Hathaway, 1978) and California have revealed that
solar radiation entering shallow streams and rivers produces a significant difference
between maximum and minimum daily temperatures.  Figure IV-32 shows one such example on
the Santa Ana River near Mentone, California.  The water temperature varied by 17°F
over a period of 24 hours.  One significant effect of the temperature variation is its
effect on dissolved oxygen levels.  Figure IV-33 shows the measured dissolved oxygen
concentrations and predicted saturation levels over the same time period at the same
location on the Santa Ana River.  The dissolved oxygen concentrations ranged from a
high of 9.2 mg/1 to a low of 8.0 mg/1.  The variations were caused predominantly by the
temperature changes.  This illustrates several points:
        t    Temperature data concomitant  with dissolved oxygen data  might  be
             needed  to properly interpret  the  cause of dissolved  oxygen  variations  in
             shallow rivers  receiving  large  amounts of solar  radiation
        0    Removing riparian  vegetation  around shallow rivers tends to  increase  the
             daily maximum temperature and  decrease the daily minimum temperature
        •    Impacts on the  dissolved  oxygen  levels and indigenous biota  can  be
             significant.

4.4.7  Low Flow and  Temperature
     Evidence has previously been cited  in  this chapter to  show that  in many  parts  of
the country high temperature conditions  are  concomitant with  low flow.   The planner
needs to be able to  quantify better the  nebulous term  "low  flow"  to fruitfully  use
this concept  as  a planning tool.   For  example,  suppose a decision is  made  based  on
the low flow  condition of  this  year.   What  are the chances  that this  low  flow  will  be
                                         -383-

-------
          C
          UJ
                                                    KEY
                                                    ^^^^v
                                                    Air Ttrnperaturt
                                                    Wattr Temptraturt
                                                   0240
                                                   6/20
                                TIME OF DAY (Military Timt)
                                   0640
1040
        FIGURE  IV-32
MEASURED  AIR AND WATER TEMPERATURES  FOR
THE  SANTA ANA  RIVER  NEAR MENTONE,  CALIFORNIA,
IN JUNE 1979,
exceeded in the future?   If  they  are high, then any decision (e.g.  at particular
level of waste abatement  at  a  sewage treatment plant) based on the  observed  conditions
could have unexpected  deleterious results at a future time.  It is  paramount then,  to
predict how often flow will  fall  below a specified rate.
     Two measures or Indices of low flow that have be«n found useful  are flow
duration and low-flow frequency.   Although 1t Is beyond the scope of this report  to
explain 1n detail how to  develop  these measures, examples of each will be presented
that explain their utility.  The  majority of the material 1n this section 1s from
Cragwall (1966) who provides a discussion on low flow, and cites additional  references.
Many texts on engineering hydrology (e.g., Unsley et. ±K, 1958) also discuss low
flow.  Figure IV-34 shows a  flow  duration curve for the Hatchle River at Bolivar,
Tennessee.  The vertical  axis  1s  the dally discharge and the horizontal  1s the
percent of time a flow 1s equaled or exceeded.  For example, 95 percent of the time
from 1930-58 the flow exceeded 177 cfs.   It can also be assumed that this flow (177
cfs) will probably be exceeded 95 percent of the time 1n other years.  Thus  this
concept offers one means  by  which to quantify "low flow".
                                        -384-

-------
               10.0

               9.8

               9.6

               9.4

               9.2
1040
6/19
      KEY
      ObscrvKJ DO
      Saturation, C,
                         1440
         1840
2240
                  0240
                   6/20
TIME OF DAY (Military Timt)
0640
                                                                     1040
        FIGURE  IV-33
MEASURED DISSOLVED OXYGEN CONCENTRATION
AND  PREDICTED SATURATION CONCENTRATION FOR
THE  SANTA  ANA RIVER NEAR MENTONE,  CALIFORNIA,
IN JUNE 1979.
     A second  concept  Is the low flow frequency curve,  Illustrated In Figure IV-35.
This depicts the relationship between discharge and  recurrence Interval of different
duration flows.   For example the 7 day mean flow of  100 cfs can be expected to occur
once each 19 years.  Stated another way, since probability 1s the reciprocal of
recurrence Interval, 1n any one year there 1s about  a 5 percent probability that  a
seven day mean flow of less than 100 cfs will occur.  A commonly used flow for
analyses 1s the  7 day  mean flow at a recurrence Interval of 10 years, or 7Q10.

4.4.8  Interrelationships Between Temperature Prediction Tools
     The three major temperature prediction tools presented 1n Section 4.4 are:
        0   Water temperature alterations caused by a  power plant
        •    Equilibrium temperature
        •    Longitudinal river temperature profile.
                                        -385-

-------
           IQOOO
            1.000
          u
          UJ
          or


          5
          >,
                 PERCENT OF TIME INDICATED DISCHARGE
                 WAS EQUALLED OR EXCEEDED
           FIGURE IV-34
FLOW DURATION CURVE.  HATCHIE RIVER AT
BOLIVAR, TENN,  (FROM  CRAGWALL,  1966)
Figure IV-36 shows three river temperature profiles which Illustrate how these
tools can be used jointly.  Curve A represents  a temperature profile of a river
where a power plant  1s located a distance 0 below some reference point.  The  tempera-
ture on the river above the power plant Is T. which Is slightly below the equi-
librium temperature.  Due to the thermal  discharge from the power plant, the  river's
temperature 1s Increased to T4> above the equilibrium temperature.  Below the
mixing zone area, the water temperature gradually decreases toward equilibrium, as
the excess heat 1s dissipated Into the atmosphere.
     Curve B Illustrates the temperature profile of a river whose water comes
predominantly from the hypo11mn1on of a reservoir.  While In the reservoir the
water 1s Insolated from the solar radiation, so the temperature 1s below the  equi-
librium temperature.  As the water 1s withdrawn from the reservoir and begins to  flow
downstream, Us temperature Increases due to solar radiation and atmospheric  heating.
The temperature tends to approach the same equilibrium temperature (the two rivers
are assumed to be 1n the same geographic area).
     Curve C shows the temperature profile of river B which now has a power plant,
                                        -386-

-------
                 10000
                    RECURRENCE INTERVAL (YEARS)
          FIGURE  IV-35
FREQUENCY  OF LOWEST MEAN DISCHARGES OF
INDICATED  DURATION, HATCHIE  RIVER  AT
BOLIVAR, TENN,  (FROM  CRAGWALL,  1966)
similar to the one on river A, discharging Into It.  If the  flow rates of the two
rivers are the same, so 1s the Initial  temperature Increase  (I.e., T. - T. -
T^ - T_).   However, the temperature  of  the river continues to  Increase,
1n contrast to profile A, because  T- 1s less than E.  This Illustrates an
unusual, but entirely possible, situation where river temperature continues to
Increase below a thermal discharge.

4.5  NUTRIENTS AND EUTROPHICATION  POTENTIAL

4.5.1  Introduction
     Within the past decade the elements most often responsible for accelerat-
ing eutrophlcatlon - nitrogen and  phosphorus - have shown  generally Increasing
levels 1n  rivers (EPA, 1974).  Median concentrations Increased 1n the period from
1968 to 1972 over the period from  1963  to 1967 1n 82 percent of the reaches sampled
for total  phosphorus, 74 percent for nitrate, and 56 percent for total phosphate.
     These Increasing concentrations afford more favorable conditions for eutrophlca-
tlon, although many rivers with high nutrient levels do not  have algal blooms.  Algal
                                       -387-

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                 T«
              I
              s
                      A (Power plant prosont)
                                                        	E
                            B (R«l*««« from hypoHnwnon)
                                   DI8TANCI

            FIGURE  IV-36    THREE RIVER TEMPERATURE PROFILES

growth can be Inhibited  1n numerous ways.  For example, turbidity  can decrease light
transmlttance through water and effectively stop growth.  Decreasing  turbidity could,
however, have a deleterious side effect of promoting excessive algal  growth, unless
stream nutrient levels are concurrently decreased. High water velocity  can  also
prevent algae from reaching bloom proportions before they are carried out of the
river system. The eutrophlcatlon problem, then, 1s transferred to  the water body  Into
which the river empties.

4.5.2  Basic Theory
     Stumm and Morgan (1970)  have proposed a representation for the sto1ch1ometry of
algal growth:
106C0
                          16N03"  + HP042" * 122H20 * 18H*(+ trace
                                                    elements;  energy)
                               1C   H   0 '  N  P I  + 138 0
                               1  106  263  110  16  1'         2
                                algal protoplasm
                                                                            (IV-86)
                                        -388-

-------
where
        P  •  photosyntehsls
        R  -  respiration.

Observe that in the algal protoplasm the ratio of C:N:P i.s:

                        C:N:P • 106:16:1, by atomic ratios                   (IV-87)

                        C:N:P « 41:7:1, by weight ratios                     (IV-88)

     From the above two equations it can be inferred that only small amounts of
phosphorus are needed to support algal growth in relation to the amounts of carbon
and nitrogen required.  If phosphorus 1s not present in the amount required for algal
growth then algal production will be curtailed, regardless of how much of the other
nutrients is available.  Phosphorus 1s then termed growth limiting.  It 1s possible
for other elements, particularly nitrogen, and occasionally carbon or trace metals,
to be growth limiting as well (Stumm and Stumm-Zo)linger, 1972).
     Nitrogen uptake by algae is generally 1n the nitrate form if nitrate is available.
However, different types of fresh water algae can utilize either organic nitrogen or
inorganic nitrogen in the form of ammonia, depending on which is available (Stumm and
Stumm-Zollinger, 1972).  Algae typically require phosphorus in an inorganic form,
usually as orthophosphate ion (Kormondy, 1969).
     Some Indication of whether nitrogen or phosphorus is growth limiting may be made
by determining the weight ratio of the appropriate forms of nitrogen and phosphorus
found in a river, and comparing that with the stoichiometric ratio required for
growth.  This gives an Idea regarding the nutrient on which control efforts should
focus.  Specifically, let:

                                p	LIN]_                                 (IV-89)
                                    [OP04-P]

where
        [TN]      «  concentration of total nitogren in river, mg-N/1
        [OPO^-P]  -  concentration of orthophosphate, mg-P/1.
If R>10, phosphorus 1s more likely to limit than N.
If R<5, nitrogen 1s more likely limiting than P.
If 5
-------
Both Lehman, et al.  (1975)  and Lund (1965)  provide specific  algal  data  as  well  as
further discussions.
     The following table (Table IV-28)  shows an approximate  relationship between
total nitrogen and total phosphorus concentrations and the potential  algal  biomass
that can result.   Both nitrogen and phosphorus must be present  In  the amounts  shown
for the resultant growth to occur.

                                   TABLE IV-28

                         EUTROPHICATION POTENTIAL AS A
                       FUNCTION OF NUTRIENT  CONCENTRATIONS
p
(rcg-P/1 )
0.013
0.13
1.3
N
(mg-N/1 )
0.092
0.92
9.2
Dry Algal Cells
(mg/1)
1.45
14.5
145.0
Significance
Problem threshold
Problem likely to exist
Severe problems possible
4.5.3  Estimating Instream Nutrient Concentrations
     Because of the transformations that occur among the different nltogren and
phosphorus compounds it is not possible to conveniently track any particular form of
nitrogen or phosphorus through a stretch of river.  However, if total nitrogen and
total phosphorus can be considered conservative, a mass balance approach can be
easily formulated for these constituents.  In reality this assumption may not be met
for  a variety of reasons.
     For example, algae utilize nutrients, die, and settle to the bottom.  Although
there is a recycling of algal cell-bound nutrients, the settling rate may surpass the
rate of recycling.  Assuming total nitrogen and total phosphorus to be conservative
should give an estimate of the upper  limit of the  Instream concentrations of these
nutrients.
     The instream concentration of total nitorqen  (TN) or total phosphorus (TP)
resulting from a point discharge is (formulas w11 I be presented for TN only; those
for  TP are exactly analogous):

                             TN    ™uQu * TNwQw                            (IV-90.)
                             TN°      Q« * a*
                                   TNuQu * Wp/5.33                         (IV-90b)
                                             —
                                         -390-

-------
where
        TN   «  Instream TN upstream of discharge,  mg-N/1
        TN   «  concentration of TN in point  discharge, mg-N/1
        Q    •  flow 1n river upstream of point discharge,  cfs
        Q^   »  flow rate of point discharge, cfs
        TN   «  resulting Instream TN concentration,  mg-N/1
        w    «  loading rate of point source, Ib/day.
Tfie expression for TNQ 1s given by either Equation  IV-91A or  IV-91B.
                                                                      The
appropriate form to use will  depend  on  the  form of the available  data.
     To determine the Instream concentration of total  nitrogen  due  to  a  distributed
discharge, use:
                        TN
TN
                                          (TNr - TNQ)
                                                                            (IV-91a)
or
                             TN
                                   TNoQo  ,
                                              wx
                                            5.33  Q
                                                                            (IV-91b)
where
        TN
        TN
          o
        x
        Q
        QO
        AQ
                TN entering with the distributed flow, mg-N/1
                Instream TN at x « 0, mg-N/1
                distance downstream from the point source discharge
                stream flow rate at x, cfs
                stream flow rate at x « 0, cfs
                Incremental flow increase per unit distance, cfs/mile
        w    •  mass flux of TN entering the stream through the distributed source,
                1b/day/m1le.
     The choice of whether to use Equation IV-91a of IV-91b depends on the available
data.  Based on the approach detailed 1n Chapter III, the mass flux of nutrient
entering the stream (1n units of Ib/day/mlle) can be generated.  When this approach
1s used, then Equation !V-91b 1s applicable.
     To use Equation IV-91a the concentration of pollutant from the nonpolnt source
has to be known.  This can be accomplished using the approach of Omernlk (1977).
Nonpoint source nitrogen and phosphorus concentrations are predicted as fractions of
land use type or based on color coded maps if land use categories are not known.  The
data used to predict nitrogen and phosphorus concentrations were generated in a
National Eutrophication Survey (NES) program wherein a nationwide network of 928
nonpoint-source watersheds were monitored.  This method accounts for only the nonpoint
source contribution.  Consequently, if point source exist within the watershed, their
contributions must be Included as well in order to accurately predict instream
concentrations.
                                         -391-

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     Table IV-29 summarizes the predictive formulas developed by Omernlk  for total
phosphorus, orthophosphorus, total  nitrogen, and Inorganic  nitrogen.   The formulas
are regionalized by eastern, central, and western United States. Agricultural,  urban,
and forested lands comprise the Independent variables 1n the formulas.
     Qnernllc's analysis of the NES data Indicates that:
        e    Streams draining agricultural watersheds had considerably higher
             nutrient concentrations than those draining forested watersheds.
        e    Nutrient concentrations were generally directly proportional  to the
             percent of the land 1n agriculture and Inversely proportional  to the
             percent of land 1n forest.
        t    Mean concentrations of total phosphorus and total  nitrogen were nearly
             nine times greater 1n streams draining agricultural lands than 1n
             streams draining forested lands.
        •    Mean phosphorus concentrations In streams draining forested  watersheds
             1n the west were generally twice as high as those 1n the east.
        t    Total and Inorganic nitrogen 1n streams draining agricultural  watersheds
             were considerably higher 1n the heart of the corn belt than  elsewhere.
     As an alternative to the equations shown In Table IV-29, Omernik provides
three colored maps of nonpolnt source related concentrations of nutrients in streams.
They can be used where detailed Information necessary for more accurate prediction  1s
unavallable.

4.5.4  Nutrient Accounting System
      It may be desirable to determine the Impact of each nutrient source on the
total Instream concentration in order to distinguish among the major sources.
An accounting procedure utilizing Equations IV-90 and IV-91 can be developed to
do this.   The following steps outline the procedure.
        1.   Segment River.  Divide the river Into major segments.  These segment
             divisions may reflect waste  loading distributions or another convenient
             division scheme chosen at the discretion of the planner.  The segments
             are  not necessarily the same as the reaches that have previously been
             discussed (see Section 4.1).  The delineation of reaches as described
             earlier 1s based upon lengths of river having uniform hydraulic conditions.
             Segments, as used here, are  purely a convenient subdivision of the river.
        2.   Quantify and Locate Sources  of Nutrients.   The quantification of point,
             nonpolnt, and  natural sources on the ma1nstern and  tributaries should be
             accomplished using the best  available data.  Tabulation  can be performed
             for  each different season to reflect the discharge pattern characteristic
             of each season.  The quantification should  Include total nitrogen  and
             total  phosphorus.  Tabulate  data  in terms of average dally  input (Ib/day).
                                         -392-

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                               TABLE  IV-29


     REGIONAL STREAM NUTRIENT CONCENTRATION  PREDICTIVE MODELS




 Nutrient Fom    Model,  Correlation Coefficient and Multiplicative Standard
 'Region        Error


 Totil pnesonprtit

 Eatt      Log1(J (PCONC)  *  -1.8364 • 0.00971 (X agric « X urb)

                           r «  0.74. f « 1.85

 Central   loglfl (PCONC)  «-1.5697 » 0.00811 (X agric » X urb) -0.002312 (X for)

                           r «  0.70. f « 2.05

 West      Log1Q (PCONC)  =-1.1504 • 0.00460 (XagHc « Xurb)  -0.00632 (X for)

                         r » 0.70. f « 1.91

 Orthoohosohorus

 East      Log10 (OPCONC) « -2.2219 • 0.00934 (X agric » X urb)

                           r - 0.73, f « 1.86

 Ctntra)    Loglfl (OPCONC) « -2.0815 » O.OOE68 (X agric • X urb)

                           r « 0.63. f « 2.05

 We*t      Log,0 (OPC3NC) =• -1.5513 • 0.00510 (X agric « X urb) -0.00476 (X for)

                           r « 0.64. f « 1.91

 Total  nitrogen

 Ea*t      Log]0  (NCCHC) » -0.08557 • 0.00716  (X agric * X urb) -0.00227 (X for)

                          r «  0.85.  f  « 1.51

 Central    Log)(J  (NCONC) « -0.01609 « 0. OC399  (X agric » X urb) -0.00306 (X for)

                          r -  0.77.  f  - I.SO

 West       Log)Q  (NCCNC) - -0.03665 • 0 00«25  (X agric • X urb) -0.00376 (X for)

                          r *  0.61.  f  » 1.75

 Inorganic nitrogen

 East      Log)0  (1KCONC)  '-0.3479 « 0.00858 (X agric • X urb) -0.00584  (X for)

                         r « 0.84.  f « 1.93

 Central   Log]0  (INCCNC)  «  -0.5219 • 0.00*82 (X agric « X urb)  -0.00572 (X  for)

                           r «  0.71.f « 2 06

West      log)0  (INCSXC)  »  -0.6339 • 0.00789 (X agric « X urb)  -0.00657 (X  for)

                           r -  0.65. f » 2.45
From:   Omernik (1977)
                                     -393-

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             Characterize the location of the nutrient sources by  river mile.   For
             nonpolnt sources characterize by river mile at both the beginning
             and end of the source.
        3.   Perform Mass-Balance.  Sum the known sources to determine the total
             nutrient loading to each segment.  Then make the following comparisons:
             a.  Compare the total loading with the nutrient Input from the malnstem
                 at the upstream end of the segment.  This direct comparison permits
                 an assessment of the collective Impact of the nutrient sources
                 entering a segment and the upstream contribution of the malnstem.
             b.  Perform an intersource comparison to ascertain the relative Impact
                 of each nutrient source.  Express the results for each source as a
                 percent of the total loading.
     When a tributary has a high percent contribution steps 1 through 3 can be
repeated for the tributary Itself to track the sources of the nutrients.
     Apply Equations IV-90 and IV-91 to each reach within the segment to determine
the Instream nutrient concentration throughout the segment.  Once this Is done that
step can be repeated for the next reach.
     By applying this analysis one can determine the relative Impact of any discharge,
determined jointly by the flux of the nutrient and the discharge location.  Section
4.1.10 provided a detailed example problem which Illustrates the procedure.  A brief
example also follows.
I	EXAMPLE IV-14	
I
i                      Computing Total Nitrogen Distribution

I                                                                                       I
        This example Illustrates the use of Equations IV-90b and IV-916 In calculating j
   the total nitrogen distribution in a river.  Suppose the user has been able to
'   estimate the point and nonpolnt loading of total nitrogen in a river as shown In
I   Table IV-30.
i
|   If  these  loading  rates are estimated over a year, then the flow rates used
j   should also  be  average annual  flows.  To compute the concentration at mile
;   0,  Equation  IV-90b can be used:

                                '  0.25 mg-N/1
|                      T75T
i   where the following conversions were used:
I           1 MGD • 1.55 cfs
j           1 mg/1  «  8.34 Ib/MG
j   To  determine the  concentration  at  milepoint 9.99, use Equation IV-91b:
                                         -394-

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                                      TABLE  IV-30

                       TOTAL  NITROGEN DISTRIBUTION IN A RIVER IN
                     RESPONSE TO POINT AND NON-POINT SOURCE LOADING
          Reach
          Number
         River
         Mile-
         Point
   TN           TN           Q       TN Concen-
  Added*   Cumulative   Cumulative   tration
(Ibs/day)    (Ibs/day)     (cfs)      (mg-N/1)
            1

            2

            3

           4
           0
          9.99
         10.0
         14.99
         15.0
         20.99
         21.0
         26.0
  400 L
  500 D
   0
  700 D
  800 L
  650 D
   0
  900 D
  400
  900
  900
1,600
2,400
3,050
3,050
3,950
  300
  400
  400
  600
  700
  900
  900
1,000
0.25
0.42
0.42
0.50
0.64
0.62
0.62
0.73
       * "L"   indicates  a  localized or point source.  "D" indicates a d-i
         or non-point  source whose range of input is over the entire reach.
TN - (0.25)
                       300
                                500
                               T755
                                          0.42 mg-N/1
   Note that wx in  Equation  IV-91  is the  500 Ib/day shown in Table IV-30.  By
   reapplying these two  basic  equations for each reach the user can work downstream
   through the four reaches.   Also note that the total nitrogen concentration has
   decreased slightly through  reach 3, even though more TN has been added.  This is
   because the incoming  flow has served to lower the concentration by dilution.
                          •—  END OF  EXAMPLE  IV-14	'
4.6  TOTAL COLIFORM BACTERIA

4.6.1  Introduction
     Total coHform bacteria are considered  an  indicator of the presence of pathogenic
organisms, and as such relate to the  potential  for  public health proolems.  Allowable
levels of total  coliform bacteria In  rivers  vary  from  state to state and according to
the water use description characterizing  the particular river segment.  For example,
in Montana (Montana State Dept.   of Health and  Environmental Sciences,  1973) the raw
                                        -395-

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water  supply may not have more than an average of 50 MPN/100 ml* total  conforms 1f
It  1s  to  be used as a potable water supply following simple disinfection.  In water
suitable  for bathing, swimming and recreation, as well as growth and marginal propa-
gation of salmonld fishes, an average of 1,000 MPN/100 ml 1s allowable.
     Concentrations of total conforms vary with the season of the year.  Often
the heaviest loadings occur during the summer months, but this Impact 1s somewhat
offset due to the more rapid die-off at higher temperatures and more Intense solar
radiation.  In the Willamette River (Figure IV-37), for example, the highest counts
of  1971-72 were actually observed from November through May (EPA, 1974).
     Treated municipal sewage comprises a major source of conform pollution.
Urban  stormwater runoff can also be significant, especially through combined sewer
outflows. Rural storm water runoff transports significant fecal contamination from
livestock pastures, poultry and pig feeding pens, and feedlots.  Wildlife both within
refuges and In the wilds can contribute as well.  For guidance in the interpretation
of  preliminary coll form analyses. Table IV-31 can be used.

4.6.2  Mass Balance for Total Conforms
     The mass balance equations applicable to total col 1 form organisms are exactly
analogous to Equations IV-18, IV-21, and IV-23A and IV-23B, since first order decay
is  used for both. For purposes of hand computations, the following decay coefficient
Is  acceptable:

                           ktc - 1.0 + 0.02 (T-20)                          (IV-92)

where
        ktc  •  decay coefficient for total conforms, I/day
        T    »  water temperature, °C.
Those  equations with the widest applicability are listed below.  For a point source
of  conforms:
                         TC  *  TC   exp
                                Q
(IV-93)
*MPN means  "Most  Probable  Number".  Conform organisms are not counted Individually.
 but their  densities are statistically determined and the results stated as MPN/100
 ml.
                                         -396-

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                          SEASONAL  RIVER PROFILES
                                WILLAMETTE RIVER
                                Total  Coliform*
                                                        LEGEND:

1
0
o
w
&
•»
E
t.
O
"o
O
"5
100,000

10,000
i nno
1 ,WWW
100
10
1
w u n. i w vv* i . i 7 ' &
_. 	 .,._ 	 . •• %>
	 	 	 	 	 is%
\ .1 y\ /V/1 OREGON
A/\/ / 	 \ / STANDARD?
\A 1 ^~*^ ^ A
^1 /^ \
~ V '

1 1 1 I 1 1 1 I I ]
                         0   20  40  60  80  IOO  120 140  160  180 200
                                      River   Miles
                __  100,000 p
                E
                o
                2   10,000
E
o
                     1,000
                       100
                        10
                                   NOV. TO MAY
                                   '1972
                             OREGON  \
                             STANDARD -^
                         0   20  4O  60  80 100 120  140  160 180 20O
I                                       River   Miles

FIGURE IV-37   TOTAL COLIFORM PROFILES FOR THE  WILLAMETTE RIVER  (EPA, 1974)
                                 TABLE IV-3I

                      TOTAL COLIFORM ANALYSIS  (EPA, 1976)
               If the Calculated
               Concentration  is:
                               Probability of
                             a Coliform Problem
              Less than 100/100 ml
              Less than 1,000/100 ml
              More than 1,000/100 ml
              More than 10,000/100 ml
                               Improbable
                               Possible
                               Probable
                               Highly Probable
                                     -397-

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For both point and distributed  sources  of  conforms:


                                                       -Q2)                  (IV-94)


     For a change in coHform concentration due to a point  source modification:
                                  TCr   t   L     T
-------
I           x    »  10 mi les
j           ku  •  1.0/day at 20*C
j   First the computations will be performed assuming  no  distributed  flow.  Equation
:   IV-95A is then applicable.  Computing the expondent j   x  (at  a  flow distance
•   of 10 miles):
!                  (1.0) (10) (5280)
I           Jtcx -  (24) (3600) (1)  " °'611
   so

            -TC
                   •   exp  (-.611) • 0.54
   or
I
                        0.54 £
              (1.0)  (500)
 Etc  "  (24)  (3600)  (0.0057)
                »  2.02
   Then
                         2.02
iTC      /SOON2'02   . „
rrr;  =  (m)     ' °-39
   or

          iTC    «  0.39 JTC0

I  For ATCQ • 1,000 MPN/100 nml, ATC « -390 MPN/100 ml.
|  Note that this decrease 1s 150 MPN/100 ml less than If no distributed flow
j  existed.
j       To determine the absolute total conform level, simply add to the original
•  level the resulting change caused by the waste loading modification.
                             END OF EXAMPLE IV-15
                                         -399-
j   For example if ATCQ - -1,000 MPN/100 ml then ATC «  -540 MPN/100 ml  (negative        j
j   ATC  indicates that the colifonm level  has decreased  from  what  it previously        j

   was)>                                                                              i
        Now suppose the distributed flow of 300 cfs is included  in the computa-
   tion.  Then:                                                                       !
             f
                        ^               2                                            1
           A    •  Q /U« ' 500/1 - 500 ft*                                            !
            °       °                                                                 I
                      300              ?                                              !
           AQ   •  Tb75280J" • °-0057 ft /sec                                          I
                                                                                      j
                                                                                      i
                                                                                      I

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4.7  CONSERVATIVE CONSTITUENTS

4.7.1  Introduction
     Conservative constituents are those which are not  reactive and  remain  either  1n
solution or 1n suspension.  They are advected  through the water column  at the  velocity
of the river with no loss of mass.  The analysis of nutrients,  already  discussed 1n
this report, was performed assuming they acted conservatively.   Other substances,
such as salinity, can also be considered as conservative.  Chapter 3 contains  Informa-
tion on salinity 1n Irrigation return flow for many rivers with salinity problems.

4.7.2  Mass Balance for Conservative Constituents
     Two simple mass balance equations are sufficient for analyzing  conservative
constituents.  The first relates the Instream  concentration due to a point  source
loading:
                            S -                                             dV-96)
where
        S   -  resulting pollutant concentration, mg/1
        S   «  upstream concentration, mg/1
        Q   «  upstream flow rate, cfs
        0   »  point source flow rate, cfs
        U   •  loading rate of pollutants, Ib/day.
When a distributed flow 1s present along some length of the river, then the distribu-
tion of the conservative pollutant Is given  by:

                                 S Q
                             S - -2-2. * —21—                              (IV-97)
                                  Q     5.38 Q

where
        w   »  distributed loading rate,  Ib/day/mi
        x   »  distance downstream,  miles
        S   «  initial concentration (at  x » 0),  mg/1.
Srt in Equation IV-97 is identical  with S  in  Equation IV-96.
                                         -400-

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	  EXAMPLE  IV-16  	

                 Calculating  Salinity Distribution in a River

      Salinity problems  are receiving Increased attention In the western  United
 States, particularly relating to the economic Issues in the Colorado  River  Basin
 and international  compacts with Mexico.  In the Colorado River high  salinity
 .levels  in  the  lower  reaches adversely affect nearly twelve  million people and
 approximately one million acres of fertile irrigated farmland  (Bessler and Maletic,
 1975).   The  salinity now averages approximately 865 mg/1  at Imperial  Dam and  is
 projected  to be  1,160 mg/1 or more by the  year 2000, unless firm  control actions
 are taken.
      Consider the river shown in Figure IV-38,  Predict the salinity  distribution
 based on the inflows and withdrawals shown.   Assume the data are  averaged over a
 period  of  a  year. These data, along with the salinity concentrations  at different
 river mileposts  are  shown in Table IV-32.
      To calculate S  (salinity at milepoint 100)  use Equation IV-96:
         <-  m  0.500 +  (2xl06) (1.55/8.34)
           •  186 mg/1
 At milepost  199.9, Equation IV-97 is appropriate and S is  given  by:
         ,.  „  (186) (2000)     (4xl06) (1.55/8.34)
                507JC5000
           •  223 mg/1
              Q = 3000cfs            Q=5000cf,          Qs2500cfs
     Q«500cft!
           Q = l500cfi           *               Q=3000cft
           W=2x!06|b/doy         Q,,ooOcf,      W = 8xlo6|b/doy
             100      200      300     400     500      600      700   750
                                 RIVER MILES
                                                                                    i
     FIGURE  IV-38      SALINITY DISTRIBUTION IN  A HYPOTHETICAL RIVER     I
                                                                                    •
                                       -401-

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                                    TABLE IV-32
                   SALINITY DISTRIBUTION IN A HYPOTHETICAL RIVER
Reach
Number
1

2

3

4

5

6

7

8

9

10

River
Mile
Point
0
99.9
100
199.9
200
279.9
280
359.9
360
449.9
450
499.9
500
524.9
525
599.9
600
649.9
650
750
Salinity
Added*
(Ibs/day)
0
0 ,
2x1 0*
4x1 05
0
0 a
-1.2xl06
0
o ft
25x10°
0
0 ,
8 106
0 6
-7.9x10°
0 ..
-4.7x10°
0
0 ft
20x1 0°



L
0


L


0


L

L

L


0
Salinity
Cumulative
(Ibs/day)
0
0 c
2x1 0*
6x10°
6x1 of
6x1 05 ,
4.8x10°
4.8x10?
4.8x10°
29.8x10°
29.8x10°.
29.8x10°
37.8X106;
37.8xlOb
29.9x10?.
29.9x10°
25.2x10°
25.2x10°
25.2x10°
45.2x10°
Q
Cumulative
(cfs)
500
500
2000
5000
5000
5000
4000
4000
4000
9000
9000
9000
12000
12000
9500
9500
8000
8000
8000
10000
Salinity
Concentration
(mg/1 )
0
0
186
223
223
223
223
223
223
615
615
615
585
585
585
585
585
585
585
840
      *'L'  indicates  a  localized or point source at the milepoint shown in
        the  same  row.
        'D'  indicates  a  diffuse or non-point source ending at the milepoint
        shown  in  the same row and beginning at the milepoint in the above row.
       At milepoint 280, 1,000 cfs of flow leaves the mainstem (perhaps for irrigation •
  purposes).  The concentration of salinity in this flow is the same as that in the
  mainstem.  So the mass rate of withdrawal is:                                       !

             W - '^^ (223 x 1000)                                                   j
               « -1.2 x 106 Ib/day                                                    j
       A negative sign is used to signify a withdrawal. Completing the remainder      j
  of the table is solely a matter of reapplying these basic concepts.                 ;

 	 END OF EXAMPLE IV-16
4.8  SEDIMENTATION

4.8.1  Introduction
     One of the more difficult classes of hydraulic  engineering  problems  associated
with rivers involves the erosion, transportation,  and deposition of  sediment.  Sedi-
                                         -402-

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mentation is important economically,  particularly relating  to.filling  of  reservoirs
and harbors, and to maintaining channel  navigability and  stability.  Table  !V-2,
located in Section 4.1, documents some suspended solids problems  encountered  in eight
major U.S. waterways.
     The sediment load carried in a river can be divided  Into two components:  the
bed material load and  the wash load.   The bed material  load is  composed of  those
solid particles represented in the bed.   The transport  of this  material  Is  accomp-
lished both along the  bed (bed load)  and suspended within the water  (suspended  load).
Although there is no sharp demarcation delineating bed  load from  suspended  load, many
researchers have developed individual  expressions for each  transport component.  The
total bed material load is the sum of  the bed load and  the  suspended load.  Other
researchers have developed a unified  theory from which  the  total  bed material  load
can be predicted from  a single expression.
     The wash load is  usually produced through land erosion, rather  than  channel
scour.  Wash load is composed of grain sizes finer than found  1n  the bed  material.
It readily remains in  suspension and  1s washed out of the river without  being depos-
ited.  A definite relationship between the hydraulic properties of a river  and the
wash load capacity apparently does not exist, making it difficult to advance  an
analytical method for  washload prediction (Graf, 1971).  Not all  the credible mater-
ial entering a stream  1s transported  as wash load, but  a  large  portion may  become
part of the bed material and be transported as bed material load.
     Figure IV-39 provides a graphical Illustration of the  difference  between wash
load and bed material  load.  For a particular flow condition 1n a particular  river,
the river has the capacity to transport a certain quantity  of  sediment (q ) which
generally decreases as particle size  Increases.  At some  large  particle size  the
river cannot exert enough force to transport particles  of that  size  or larger.  This
situation would occur  at some point to the right of point 0 on  curve COO.  This  same
river might be supplied with sediment at a rate AOB, which  is  unrelated to  transport
capacity.
     To the left of point 0 the river 1s transporting all the  material of that size
range being supplied to 1t.  Sediment having diameters less than  d*  are classified  as
wash load, because the amount being transported Is supply limited, and not  transport
limited.  To the right of point 0, supply exceeds transport capacity.   The  amount
given by the curve 00 1s transported, and the difference in OB and 00  Is deposited  in
the stream bed.  The methods to be presented in the following  sections are  generally
concerned with predicting curve 00 (I.e.  the bed material  load), although  Section
4.8.2 does provide a brief description of how to estimate long-term  sediment  supply
rates.
     As a guide in evaluating whether a river 1s carrying a significant quantity
of suspended sediment, Table IV-33 can be consulted.  100 rug/1  is the  delinea-
                                         -403-

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                             FOR A PARTICULAR
                             FLOW CONDITION IN
                             A PARTICULAR STREAM
o
>
l
<
o
2
to
ID
Q
 M
cr
                                                        tu
                                                        i
             d  SIZE OF SEDIMENT PARTICLE

FIGURE  IV-39  DIVISION BETWEEN  WASH LOAD  AND BED MATERIAL
               LOAD (FROM:   COLORADO STATE UNIVERSITY,  1979)
                         TABLE IV-33
       RELATIONSHIP OF  TOTAL SUSPENDED SEDIMENT CONCENTRATION
              TO PROBLEM  POTENTIAL  (AFTER EPA, 1976)
         If Calculated
       Concentration is:
                                        Probability of
                                         a Problem
       Less  than 10 mg/1
       Less  than 100 mg/1
       More  than 100 mg/1
                                          Improbable
                                          Potential
                                          Probable
                             -404-

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tlon between a potential and probable problem.   In a table previously Introduced
(Table IV-1), a reference level of 80 mg/1 was set for protection of aquatic  life.

4.8.2  Long-Term Sediment Loading from Runoff
     The procedures outlined in Chapter 3 wi11 permit an assessment of the sediment
loading to a river on a  long-term basis.  When using those procedures care should be
taken to incorporate the entire drainage area of the watershed.  As an estimate, the
loading can be assumed conservative (i.e. all sediment that comes into the river will
be washed out of the river over an extended  time period).  Under that assumption the
procedure outlined in Section 4.7 can be utilized for an estimate of average yearly
suspended so-lids concentrations at locations  throughout the river system.  This
result should be interpreted as an indicator  of  the  impact of the runoff on sediment
loads within a river and not as actual suspended solids concentrations.  Not all of
the incoming sediment will be transported as  suspended load since a large fraction
can be transported as bed load.  The transport process is generally of an intermittent
nature with higher concentrations occurring  during periods of high flow.
     Care should be taken not to apply the conservative assumption at points on
a river where that assumption is clearly violated, such as at reservoirs which
can be efficient sediment traps.  An example  for the computation of sediment  loading
to rivers has been considered in Chapter 3.

4.8.3  Bed Material Load
     As previously mentioned, the estimation  of  bed material transport poses  a
difficult problem, and  is an area where there is no consensus regarding the best
predictive relationship  to use.  Numerous bed material load relationships (Task
Committee on Preparation of Sedimentation Manual, 1971) have been developed over the
past century, some requiring considerably more input data than others.  In this
report the DuBoys relationship (Task Committee on Preparation of Sedimentation
Manual, 1971) will be used in part because of its simplicity.  The relationship,
which is restricted to uniform flow in alluvial  channels, 1s:
                                                                             (IV-98)
where
        gK  »  bed  load, Ib/sec/ft of width of river
                                                      T
        4/   «  coefficient depending on grain size, ftj/lb/sec
        T0  "  vRH S> bed shear stress«
        Y   «  specific weight or water,  Ib/ft
        R.,  «  river hydraulic radius, ft

                                         -405-

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        S   »  slope of stream, ft/ft
                                          2
        TC  «  critical shear stress, Ib/ft .
The values of 4> and r  can be expressed as  functions of the median size  (by
weight) of the bed sediment (^Q).  These relationships are expressed graphically
1n Figure IV-40.  To aid In determining d5Q Table  IV-34 is presented to  show the
size range of sediment and each associated  class name.  If the class name  of the
predominant sediment type comprising a stream  bed  1s known, then the sediment  size
(in mm) can be estimated.
                                                             200
                       MEDIAN SIZE OF BED SEDIMENT, d«o
                                      (MM)
FIGURE IV-40
* AND TC  FOR DuBOYS RELATIONSHIP  AS FUNCTIONS OF  MEDIAN
SIZE  OF  BED SEDIMENT  (TASK COMMITTEE  ON PREPARATION c=
SEDIMENTATION  MANUAL,  1971)
     Once d5g is estimated, then 4* and T  can easily  be evaluated, leaving
only T  to compute.   A summary of hydraulic rad11  (the ratio of cross-sectional
area to wetted perimeter)  for different channel  geometries is shown in Figure 1V-41.
For very wide, shallow channels, the hydraulic radius approximately equals the depth
of flow.  Many river cross-sections can be approximated by a parabolic section.   To
calculate "c" in the relationship for hydraulic  radius of a parabolic section, refer
to Table IV-35.
     If the  bed slope  1s unknown it can be estimated  by using a topographic  map
and finding  contour  lines  approximately five hundred  feet above and below tne
point on the river where the measurement is to be  made.  Dividing this elevation
difference by the horizontal distance over which the  difference is measured, produces
the slope.
                                        -406-

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                   TABLE  IV-34

SEDIMENT GRADE SCALE (TASK COMMITTEE ON PREPARATION
          OF SEDIMENTATION MANUAL, 1971)
Class Nane
very large DOulce-'
uarge ro'jlae-s
*^6C i jf" -C u ' 06 '" S
i" <3 • ~ C ^ 1 C6 '" :
-arse c scales
S"a'. ' ccocles
,'ery coarje crave'.
Coarse gravel
"ecnur cra.e'
r-ne gra.e'
;ery '">e grave1
ver> coarse sana
Coarse sand
Meavji! sand
rmd sand
Very *i>ie sand
Coarse silt
Vec'ur silt
Fire S' 1 t
Very fine Silt
Coa-se :'ay
Medium clay
Fine clay
Very fine day
= .:.
Mi 1 1 imeters
4096-2048
2048-102i
•024-512
i'2-25£
246-123
126-64
64-32
32-16
16-8
5-4
4-2
2-1 2.000-1.000
1-1/2 1.000-0.500
1 '2-1/4 0.500-0.250
',4-1,8 0.250-0.125
••'3-1/16 0.125-0.062
1 16-1/32 0.062-0.031
1.32-1/64 C. 031-0. 016
' 64-1.. 123 0.016-0.003
',128-1/256 0.008-0.004
: 256-' 5:2 3 004-0. 0020
1/512-1/024 0. 0020-0. 0010
1/1024-1/2048 0.0010-0.0005
i -22.48-1/4096 0. 0005-0. OCC24
Rdn(|p A-.-c....ai* Sieve Mesn
.,.ۥ' "ngs Per !ncn
^nned States
Microns IncneS fyler Standard
160-5C
8C-4C
•• 
-------
                                    TABLE  IV-35
                COMPUTING D/T FOR DETERMINING THE HYDRAULIC  RADIUS  OF
                        A PARABOLIC SECTION  (FROM KING,  1954)
*
D
T
.0
.1
.2
.3
.4
.5
.6
.7
.8
.9
*?•
.00
.667
.650
.607
.554
.500
.451
.408
.370
.338
.311
c
.01
.667
.646
.602
.546
.495
.446
.404
.367
.335
.308
.02
.666
.643
.597
.543
.490
.442
.400
.364
.333
.306
.03
.665
.639
.592
.537
.485
.437
.396
.360
.330
.303
.04
.664
.635
.586
.532
.480
.433
.392
.357
.327
.301
.05
.662
.631
.581
.526
.475
.428
.388
.354
.324
.298
.06
.660
.626
.575
.521
.470
.424
.385
.351
.321
.296
.07
.658
.622
.570
.516
.465
.420
.381
.348
.319
.294
.08
.656
.617
.564
.510
.460
.416
.377
.344
.316
.291
.09
.653
.612
.559
.505
.455
.412
.374
.341
.313
.289
     Adequate methods that are within the scope of this report  and  which  would
provide a straightforward estimation of suspended sediment discharge presently
do not exist.  Most relationships require a known reference level  concentration
at some depth within the river to predict the concentration at  another depth (Morris
and Wiggert, 1972).  To determine the suspended sediment load,  then, a summation of
contributions at each depth must be made.  Since these formulas apply to  one grain
size this procedure should be repeated for all grain sizes present.  Einstein (Graf,
1971) has developed a method for computing suspended sediment discharge that does not
require knowledge of a reference concentration, but it is an advanced approach.  For
this report the contribution of the suspended load will be estimated from the bed
material load by the relationship given in Table IV-36.  The relationship in Table
IV-36 is valid for graded channels (by graded is meant that the slope is  stable over
time, being neither steepened nor flattened by flow or other influence).   Once  the
width to depth ratio for the stream in question is determined,  the suspended load can
then be approximated after first computing the bed material load,  and then using
Table IV-36.
      Once the suspended load discharge is estimated the average concentrations
 at a section can be computed by:

                                        1.6 x 104                           (!V-99a)

                                         -408-

-------
              CHANNEL SUDPE
                HYDRAULIC RADIUS
                      2X? D
                                                         . x - D/b,  z  - e/D
                                         1 + 2 x   'l + *2
              Trapezoidal
                  T	:>J
~7F
  D
              Rectangular
                                                       bD
                                                      b + 20
              Triangular
                                                    zO
                                                            z  » e/D
              Parabolic
                                                      „        (for c, see
                                                     c°        Table  IV-35)
FIGURE  IV-41      HYDRAULIC RADII  FOR DIFFERENT CHANNEL SHAPES  (FROM KING,  1954)

                                    TABLE  IV-36
           RELATIONSHIP BETWEEN WIDTH TO DEPTH RATIO OF A GRADED STREAM AND
              THE SUSPENDED AND  BED LOAD DISCHARGE (AFTER  FENWICK,  1969)

                       Suspended       Bed  Load % of     Width-
                    Load 5 of Total     Total Bed         Depth
                   Bed Material  Load  Material Load       Ratio
                        85-100
                        65-85
                        30-65
               0-15
               15-35
               35-70
  7
7-25
 25
                                        -409-

-------
or
                                   9ss         4
                             C   . -ii 1.6 x 10*                           (IV-99b)
                              ss    q
where
        C__  •  average suspended solids concentration, mg/1
        GSS  »  suspended solids discharge, Ib/sec
        Q    -  flow rate, cfs
        g..  •  suspended solids discharge per unit width, Ib/sec/ft
        q    «  flow rate per unit width, cfs/ft.
     The procedures discussed In this section can be summarized as follows:

        1.   Determine the bed load discharge gb (Ib/sec/ft) using Equation IV-98.
             The required Input data are channel slope, hydraulic radius {see Figure
             IV-41), and the median sediment size, dcQ.  Once d™ has been estimated
             the unknown parameters r  and 4> can be found from Figure IV-40.
        2.   Multiply gb by the river width to find the total bed load discharge.
        3.   Determine tne width/depth ratio.
        4.   Use Table IV-36 to determine the suspended load.
        5.   To determine the suspended sediment concentration use Equation IV-99.
        6.   Compare the suspended sediment concentration against the data in Table
             IV-33 to find out 1f a problem potentially exists.
        7.   The total bed material load Is sum of the total bed load (step 2) and
             the total suspended load (step 4).
     The user may be primarily concerned with the total bed material load rather than
either bed load or suspended load Individually.  Total bed material load can be
directly calculated using a number of predictive formulas.  The method of Yang (1976)
based on unit stream power is presented here. Yang's method has been verified for the
following parameter ranges:
        Median bed size:      from 0.16 mm to 1.0 mm
        Channel depth:        from 0.2 ft to 49.9 ft
        Water temperature:    from 0°C to 29.4°C
        Stream velocity:      front 1.23 fps to 7.82 fps
        Flow rate:            from 2.7 cfs to 470,000 cfs
        Slope:                from 0.0000428 to 0.00188
        Total sediment con-
        centration (excluding
        wash load):           from 2.8 ppm to 2,440 ppm.
     The Input data are the same as for the DuBoy's method, with the addition of
water temperature.  The predictive formula, however, 1s considerably more complicated.
                                         -410-

-------
so the method has been programmed on  a hand  held  calculator and  the program  1s
Included.  The predictive expression  1s:
                                       tail")             U
            log Ct • 5.435 - 0.286 log ^ - 0.457 log -f-

                   + (1.799 - 0.409 log £ - 0.314 log ^)  log  (£ - ^)
where
        C    »  total  sediment concentration  1n  parts  per million  by weight
        D    •  median  sieve diameter
        S    •  water surface slope or energy  slope
        U^   »  shear velocity
        U    «  average water velocity
        U    «  critical average water velocity  at  Incipient motion
        v    «  kinematic viscosity
        w    »  terminal fall  velocity.
The term  cr can be calculated as:
          w

                                         °-66 when 1.2 < ^  <  70
                                                                            (IV-100)
                              )  - 0.06

and

                              ^-  2.05  when 70 <. ^                     HV-102)

     Figure IV-42 shows the required  user  Instructions  to execute  the  program
on a TI-59.  Figure IV-43 contains  the program listing  and a  sample Input/output.
This program was written by Colorado  State University (1979).
 	  EXAMPLE IV-17  	

                         Estimation of Bed Material  Load

        Table IY-37 shows characteristics of the Colorado River at Taylor's Ferry,
   California, and of the Nlobrara River near Cody,  Nebraska.  Suppose one desires  to
   calculate the bed load for the Colorado River at  this location for flow ranges of
   8-35 cfs/ft.  The following data will be used:

           d50  *  0.33 mm
           V    -  62.4 lb/ft3, at 60°F
           S    -  0.000217 ft/ft
                                         -411-

-------
TITLE.
.PAGE.
.OF.
PROGRAMMED	DATE.
Partitioning (Op 1T) I <• 6. Q 6. Ql Ubmy Module	
                       Pnntar  Optional Card« 1
                                PROGRAM DESCRIPTION
 Program:  Yang's Sediment Transport  Equation
                                  USER INSTRUCTIONS
STEP! PROCEDURE
1
2
3
4
S
6
7

Enter kinematic viscosity, v(-^-)
Enter slope SQ (ft/ft)
Enter median sediment diameter, d$ (ft)
Enter flow velocity, U (-j~ )
Enter flow depth, Y (ft)
Compute sediment concentration (ppm)
To Input new data, repeat steps 1
through 6.
ENTER
V
*0
ds
U
Y



PRESS
A
B
C
0
E
2nd







A'










DISPLAY
V
so
«.
U
Y
Ct


FIGURE IV-42    USER  INSTRUCTIONS  FOR YANG'S SEDIMENT TRANSPORT  EQUATION.
  Using  Figure  IV-40 one finds:
         4-    -  64
         TC   «  0.019
  All  that remains is the computation of the hydraulic radius. Since the width
  Is much greater than the depth, assume Ru * D:
                                         n
         R   .  /"« ft at q • 8 cfs/ft
          H    \ 12 ft at q - 35 cfs/ft.
  Using  Equation IV-98 1t is found that the bed'load  1s:
             .   ^0.12 Ib/sec/ft at q - 8cfs/ft
          b    \ 1.5 Ib/sec/ft at q « 35 cfs/ft.
  The  actual  bed material load observed at Taylor's  Ferry has been compared with the
  OuBoys prediction for a range of flow rates (Task  Committee on Preparation of
  Sedimentation Manual, 1971).  This relationship  is  shown  in Figure IV-44 (The
                                       -412-

-------
Proerta
000
001
002
003
004
005
006
007
003
009
0 1 0
Oil
012
0 1 3
014
015
0 1 6
91-
013
01.9
020
021
022
023
024
025
026
' J 

031
052
033
034
055
036
057
053
059
060
061
062
063
064
065
066
067
063
069
070
071
072
073
074
075
076
077
073
079
030
031
032
n$3
03*
035
036
037
033
039
090
091
092
093
094
095
096
097
093
099
100

34
73
06
65
43
06
34
53
43
02
34
42
00
92
76
11
*^
06
22
52
92
76
12
42
01
32
76
13
42
02
92
76
14
*2
03
•a-?
76
15
*2
04
92
76
16
71
77
53
53
03
02


rx

6
X
RCL
06

i.
RCL
02

STD
00
RTN
LBL
A
STD
06
!NV
EE
RTN
LBL
B
STD
01
RTN
LBL
C
STD
02
RTH
LBL
D
STD
03
RTH
LBL
E
STD
0*
RTN
LBL
ft'
SER
GE
C
(
3
2
.

101
102
103
10*
105
106
107
103
109
110
111
112
113
114
115
116
117
113
119
12f>
121
122
123
1 2*
125
126
127
123
129
1 30
131
132
133
13*
135
136
137
133
139
1*0
1*1
1*2
143
14-1
1*5
1*6
147
143
1 *9
150

02
65
*3
04
65
43
01
34
34
42
03
65
*3
02
55
43
06
54
42
07
32
07
00
32
77
39
53
53
02
92
05
55
53
43
07
2*
75
93
00
fir.
54
54
35
93
06
06
54
*2
03
61

2
X
RCL
04
X
RCL
01
j
rx
STD
05
X
RCL
02
•f
RCL
06
>
STD
07
X4* T
7
0
V«* * ^
GE
11
*
•'
2
.
5
-
<
RCL
07
LDG
-
.
0
if,
;
>
f
.
6
6
>
STD
03
GT2

151
152
153
134
153
156
137
158
15?
160
161
162
163
164
165
166
167
163
169
170
171
172
173
17*
175
176
177
173
179
ISO
131
132
133
134
135
136
137
133
139
190
191
192
193
19*
193
196
197
1*5
19 i
200

70
76
39
02
93
00
05
*2
08
76
70
53
52
05
93
0*
02.
05
75
93
'•'•i
03
06
65
52
*3
00
65
42
02
cr
*3
06
V •
•ii-
— ^i
09
75
93
0*
05
07
65
^ w
43
05
55
43
00
54

Pr!D
LBL
fl
^
.
fi
5
STD
03
LBL
Pfili
(
<
5
.
4
3
5
-
.
2
3
6
X
f
RCL
00
f.
RCL
02
-
PCL
06
>
LGG
STC
09
-
.
4
c;
^
X
V
RCL
0 5
r
RCL
;"i ;"*,
i
  FIGURE  IV-U3
PROGRAM LISTING AND SAMPLE  INPUT/OUTPUT  FOR
YANG'S SEDIMENT TRANSPORT EQUATION
                                -413-

-------
       fregraa Listing  (continued):                         Stmplt Input:

                                                            v  • .0000111
                                                            SQ » .0017
                                                            d$ • .000623
                                                            U  • 2.89
                                                            Y  » 0.51
201
202
203
204
205
206
20"
203
^Q'S
210
211
212
213
214
215
216
217
213
21?
220
•^ •*. -~.
• • *
223
224
225
'^ •"* to
^ £
23
42
10
54
35
53
53
01
93
07
09
09
75
93
04
00
09
65
-3
09
'r -
* . •!
03
01
04
65
43
LOG
STD
10
>
•*•
<
<
1
.
7
o
•S
.
t
4
0
c.
X
RCL
09
"
9
2
1
•T
X
FCL
223
229
230
231
232
M! m- »'
23 A
235
236
237
-i : i
2:9
«i~'J
2^1
2-i£
2 4 3
"' * "*
H5
246
r'l
"r""'?
• -T
250
251
2*2
253
254
10
54
6-
53
43
03
65
43
0 1
55
43
00
75
43
OS
65
43
01
?j,
23
•• **
e <
JT

X
(
RCL
03
X
RCL
01
+
RCL
00
-
RCL
03
X
RCL
01
j
LCG
'
}
INV
LOG
flDV
FRT
RTN
                                                                 2117.066395
                              FIGURE  IV-43    (CONTINUED)
j   DuBoys  curve  1n  Figure  IV-44 does not quite match the calculations 1n this  example
'   because slightly different data were used). Observe that the DuBoys relationship
•   over-predicts  the bed material load for nearly all flow ranges.   This pattern  1s
!   repeated for  the Nlobrara River (Figure IV-45).  This suggests  that the bed
{   material load estimated by the DuBoys relationship will 1n general exceed the
I   actual  bed  material load.  This 1s further substantiated by other work (Stall  et^
|   a1.,  1958).  The more accurate predictions of bed material load occur under high
j   flow  conditions, which  1s generally when the prediction of bed  material load  1s
j   most  Important.
:        To estimate the suspended load  contribution first calculate the width-
   depth  ratio:
           U/D  -  / 88 at q - 8 i
                   I 29 at q « 35
cfs/ft
 cfs/ft.
                                        -414-

-------
                         TABLE IV-37

     CHARACTERISTICS OF THE COLORADO AND NIOBRARA RIVERS
(TASK COMMITTEE ON PREPARATION OF SEDIMENTATION MANUAL,  1971)
Data
Depth range, ft
Range in q, in cubic feet per
second per foot of width
Mean width, in feet
Slope, in feet per foot
Minimum value
Maximum value
Value used in calculations
Water temperature, in degrees
Fahrenheit
Minimum value
Maximum value
Value used in calculations
Geometric mean*sediment size,
in mill imeters
d-,, in mill imeters
d,^, in mil 1 imeters
d,,.* in mil 1 imeters
dgo> in millimeters
Mean size, d . in millimeters
m
*The geometric mean of a set of values
geometric mean of the values 1, 2, 3,
Compare with arithmetic mean of 2.5.
Stream
Colorado Niobrara
River River
(Taylor's Ferry) (Cody, Neb.)
4-12 0.7-1.3
8-35 1.7-5
350 110

0.000147 0.00116
0.000333 0.00126
0.000217 0.00129

48 33
81 86
60 60
0.320 0.283
0.287 0.233
0.330 0.277
0.378 0.335
0.530 0.530
0.396 0.342
xn 1s! n xj n. Thus the
and 4 is (1x2x3x4)1/4 - 2.213.
                           -415-

-------
                            COLORADO RIVER
                            AT TAYLORS FERRY
  FIGURE
8 0 80-
-v 0.60-
£ 040-
UJ
g 0.20-
S n in
eo 0.08—
o 006-
^ 0.04-
UJ
? 002-
o
Lul

Duboyr/
/
e

x^
e e
% e
*— Observed

                           2  4 6 810  20 406080100
                           WATER DISCHARGE (cfs/ft.)
                                                    I
                                                    i
SEDIMENT DISCHARGE AS A FUNCTION OF WATER DISCHARGE  j
FOR THE COLORADO RIVER AT  TAYLOR'S FERRY  (TASK       j
COMMITTEE ON PREPARATION OF
SEDIMENTATION MANUAL, 1971)                         !
                              NIOBRARA RIVER
j  FIGURE IV-U5
                                          4 6 810
            WATER DISCHARGE (cfs/ft)

SEDIMENT DISCHARGE AS A FUNCTION OF HATER DISCHARGE
FOR THE NIOBRARA RIVER AT CODY, NEBRASKA (TASK
COMMITTEE ON PREPARATION OF SEDIMENTATION
MANUAL, 1971)
                                 -416-

-------
I   In both cases W/D > 25.  Referring to Table IV-36, the suspended load should
|   be between 30 and 65 percent of the bed material load.  Assume 1t 1s on the
|   lower end of the scale, about 401.  Then the suspended load 1s:
j               m  C 0.08 Ib/sec/ft at q « 8 cfs/ft
'            ss    \ 1.0 Ib/sec/ft at q • 35 cfs/ft

i   or
i           C   m  /160 mg/l at q « 8 cfs/ft
!            ss    \440 mg/l at q - 35 cfs/ft
I   from Equation IV-99.  These concentrations Indicate that suspended sediment
I   concentrations are excessively high throughout the range of flows normally
i
|   encountered at Taylor's Ferry.  Data on suspended sediment concentrations have
j   been gathered at Taylor's Ferry (U.S. Bureau of Reclamation, 1958).  The averages
j   of 30 measurements taken there are as follows:
           Q    -  7350 cfs (or q « 21 cfs/ft)
!           Cee  -  132 mg/l
I
I           Observed range of suspended sediment concentration:  40-277  mg/l.
I        The method of Yang predicts total  concentrations of 40 to 80 mg/l, which is
|   within but toward the lower end of the observated data.  The method  of DuBoy's
|   predicts concentration between 160 and 440 mg/l which is toward,  and beyond,  the
j   upper end of observation.  These results illustrate the possible  variability  of
   predictions between different approaches, and are not necessarily atypical.
I	END OF EXAMPLE IV-17	

4.9  TOXIC SUBSTANCES

4.9.1  Methods of Entry of Toxic Pollutants into Rivers
     Although Chapter 3 discussed both point and nonpoint sources of pollutants,
the major pollutant source categories are summarized in Table IV-38 to indicate
how these scenarios differentially govern a pollutant's fate.  For simplicity,
fate is analyzed in terms of volatilization and sorption since these processes
are Important for a wide number of toxic organic chemicals.   These processes
govern whether a pollutant remains in the water column and whether the pollutant
is transported as solute or sorbate.  If the effects of these processes are known,
even If only qualitatively, then the Influence of processes such as photolysis and
biodegradation can be better predicted.   For example, 1f a pollutant is sorbed to
suspended and bedded sediments, 1t is more protected from photolytic reactions than
when 1t 1s dissolved 1n the water column.
     A common mode of pollutant entry is by a continuous discharge, either from
a municipal or industrial source.  As mixing of the effluent and river water occurs,
                                         -417-

-------
                             TABLE IV-38
     METHODS OF INTRODUCTION OF TOXIC ORGANIC COMPOUNDS INTO RIVERS,
             AND FATE IN TERMS OF VOLATILIZATION AND SORPTION
        Pathway
           Fate
Continuous input
Cessation of continuous
input
  solute transported and volatilized
  sorbate transported with suspended solids
  and with bed load
  sorbed to immobile sediments
  buried by sorption and net deposition

  desorbed from immobile sediments
  solute transported and volatilized
  resorbed to suspended sediments
  contaminated sediments resuspended
  portion remains buried
Washoff from land
application
  transport of a major portion of pollutant
  may be governed by first large storm event
  transported as solute and sorbate
  settles and accumulates on bed
  buried
  subsequently resuspended
Accidental releases
(e.g. spills)
Leaching
- If s.g.  >1, pollutant settles on streambed
- Volatilization may be unimportant
  --reentrained back into stream and sorbed
    on suspended solids
  —pollutant can be slowly transported along
    bottom
  --diffused into bedded sediments
- If s.g.  <1, pollutant tends to remain on
  surface  and be transported at speed of
  surface  current
  --volatilization can be important
  --gradually dissolved and sorbed
  --dispersion attenuates peak concentrations
  —wind speed and direction influential

- slow movement (years) of solute from dump
  or disposal site to stream
- continues for years after cleanup of
  dump
                                  -418-

-------
partitioning begins.   The  sorbate  is  transported with the suspended sediments, and
can interact with the bed  load  and immobile  bedded  sediments.  Depending on the rate
of exchange of the sorbate with the bedded sediments and on the net sediment deposition
rate, some of the sorbate  can gradually  become  buried in the bedded sediments.
      If a continuous input ceases, the water column initially  tends to clean  Itself
of the pollutant as uncontaminated upstream water replaces  contaminated river water
downstream  from the former source of pollution.  However,  pollutant from the  contami-
nated bottom sediments can desorb back Into the water  column  at  low concentrations
and the river bed becomes an Internal source of pollutant.   The  desorption period can
last  a long period of time, depending on the amount of  pollutant  contained in the
bottom sediments.  Section 4.9.3.4 discusses this phenomenon  in  detail.
      Periodic nonpoint sources, such as washoff after  an agricultural  application, is
another pathway of pollutant entry Into rivers.  The mass  of  pollutant transported
tends to be governed by the timing of the first storm  event following  application
together with the degradation and volatilization processes  operative during the
Interim period.
      Accidental releases of pollutants, even through infrequent  events, can be
important.  Exceptionally high  concentrations of pollutants can  result from spills
and the total mass supplied almost Instantaneously can  be  the  equivalent of a con-
tinuous release lasting for many days.  For example, 1n 1973  a chloroform spill  on
the Mississippi River resulted  1n about 800,000 kg (1,750,000 Ibs) of  chloroform
being released over a period of several hours (Thibodeaux,  1977).  Based on the
background  concentration of chloroform in the river (5  ppb),  the release was  equiv-
alent to a  continuous supply of chloroform released at  background rates for a period
of 300 days.
      Many chemicals 1n their pure or nearly pure form  have  specific gravities sig-
nificantly  different from unity. Because of this, and  their often limited solubility
in water, it is a mistake to believe that all spilled  pollutants  travel witn  the
speed of the river, have Infinite dissolution capability,  and  disperse accordingly.
High  density pollutants can sink to the river bed and  become  slowly reentrained back
Into  the water column while simultaneously diffusing and sorbing  into  the bedded
sediments.  Depending on the rate of dissolution of the spilled  pollutant, as well as
the significance of the sorptlon and diffusion processes,  the spilled  pollutant may
remain 1n the riverine system for either an extended or brief period of time.
      In contrast to high density pollutants, pollutants with  specific  gravities
less  than unity tend to at least partially remain on or near the water's surface
while undergoing dissolution.  For these pollutants, volatilization and photolysis
can be extremely Important.  As the pollutant 1s dissolved  in  the water coljmn and
moves downstream, dispersion becomes Important 1n attenuating  the peak concentration.
      Pollutants which leach  from a surface or subsurface disposal site may eventually
                                         -419-

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reach a river.  Although the mass Input rate may be low,  the source can be continuous
and last for years, even after cleanup of the site.
     The sequence of Instream events following the Initiation and  then the cessation
of point sources of toxicants further Illustrates the role that sorptlon plays  1n
governing fate of sorbates.  Figure IV-46 Illustrates the two situations. Figure
!V-46a shows the pollutant distributions below a point source at two distinct times
(t^ and t2 where t2 > t^) following Initiation of the point source.
As the toxicant Is discharged the water column concentration (the  sum of the dissolved
and sorbed phases) abruptly Increases at the mixing location.  As  the pollutant
travels downstream, the sorbate tends to partially desorb onto the formerly uncon-
tamlnated bottom sediments.  Additionally there may be a  net exchange between the
bedded sediments and water column sediments, even If there 1s no net deposition.  As
a result of these processes, the water column concentration tends  to decrease  1n the
downstream direction.  It may take a period of time greater than t, for the
effects of the discharge to reach a distance D*.  Depending on the distance, and on
the rate of accumulation of the toxicant In the bottom sediments,  as well as on other
factors, the time required for the water column concentration to be noticeably
elevated at D* could greatly exceed the travel time of the river over the distance.
     After the discharge of the toxicant has continued for a period of time, the net
exchange with the bedded sediment may diminish, so that the toxicant concentration
becomes constant over some distance both In the water column and 1n the sediments.
This situation 1s Illustrated by the solid curve 1n Figure IV-466.  Suppose at  this
time the Input of the pollutant ceases.  The water column concentration just below
the point source tends to abruptly approach zero.  As this happens, desorptlon  of the
toxicant from the bedded sediment can occur, tending to replenish  pollutant levels 1n
the water column, but to a lower level.  Gradually, the pollutant  can be desorbed
from the bedded sediments at a given location so that the bottom sediments are
naturally cleansed, from the upstream to the downstream direction.  This process can
take many years and low levels of pollutant 1n the water  column can be detected
throughout this period.  More discussion of this phenomenon Is provided later  1n
Section 4.9.3 and Example IV-18.  Host of the pathways for river contamination  pre-
sented 1n Table IV-38 have been programmed on microcomputers (Hills et. aj_., 1985).

 4.9.2   Vertical Distribution of  Sorbate within  Rivers
      Even though most of  the analytical tools presented  later  1n  Section  4.9.3
 assume  that,  for  simplicity, suspended  solIds concentrations are  uniformly distributed
 throughout the water column, 1n  reality this  1s  not  true.   The  vertical  distribution
 of  solids depends  both  on  particle  and  river  characteristics.   Heavier  particles
 (those  with  the greater settling velocities)  are transported closer  to  the  stream
 bottom  while the  lighter  particles  are  more  uniformly  distributed.   This  observation
 1s  significant  because  pollutants  which sorb  to the  particles  also exhibit  a non-

                                         -420-

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          I
                                           Concentration at  time  t)
                                           after discharge begins

                                           Concentration at  time  t2  t,
                                           after discharge begins
             SI RT
           POLLUTANT
             INPUT
                ANT
FIGURE   IV-46
                               DISTANCE DOWNSTREAM
                                                               D*
                                            Key:
2
<5
»-
POLLUT
j



/
k

r BED^ — ^x.
/ ^ WATER COLUMN ^y^x^
I/ \
1
DISTANCE DOWNSTREAM

-------
                               INCREASED SETTLING
                               VELOCITY
                   0.001
                           RELATIVE  SEDIMENT CONCENTRATION S/Sa

            FIGURE IV-47    VERTICAL EQUILIBRIUM DISTRIBUTION  OF
                              SUSPENDED SOLIDS  IN A  RIVER
     Figure IV-47 shows  the  vertical distribution of suspended solids  1n  an  equilibrium
condition.  The parameter  shown  In the figure 1s defined:
where
                                           V
                                          •Tff
        V   •  settling  velocity of suspended solids
                                                             (IV-103)
         s
        x
        U*
        9
        R
von (Carman's  constant  (~0.4)
shear velocity  -  (g  RH S)0*5,
         H
                                            ft/sec
               acceleration due to gravity, 32.2 ft/sec
               hydraulic  radius of river, ft
        S   •  slope, d1mens1onless.
Very small  values of z  represent clay-sized particles, while larger values  represent
first silt, and then sand.  Figure IV-47 Illustrates that clay particles  tend  to be
uniformly distributed vertically (50 percent 1n the top half of the water column).
About 75 percent of silt  and over 95 percent of the sand particles  (typically)  reside
In the bottom half of the water column.  This suggests that 1n rivers  where  the
suspended sediments are silt and sand, the sorbed pollutant distribution  will  be
                                        -422-

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vertically skewed.  If the suspended material  1s predominantly clay the sorbed
pollutant distribution will  be uniform.  Since pollutants tend to sorb to sand to a
lesser degree than to silt and clay, the vertical  distribution of sorbed pollutant
will not be as skewed as the suspended sediment distribution.
     Figures IV-48 through IV-49 show the fraction of pollutant present as solute
(C/Ct) versus relative depth for families of z values and ICSa values.  Sa 1s
the suspended sediment concentration a small distance above the bottom.  For K Sa
values less than 0.1, the sorbate concentration 1s generally negligible compared  to
the solute concentration regardless of the depth or the nature of the suspended
material.  For larger K Sa values, the sorbate level can be Important, depending
of the nature of the suspended material. For extremely large K Sa values, the  sorbate
concentration will greatly exceed the solute concentration, at least near the  river
bed.
     Based on the hydraulic  characteristics of the river, characteristics of the
material being transported 1n suspension, and  the partition coefficient of the
pollutant, predictions can be made of the pollutant's distribution 1n the water
column.  To use Figures IV-48 and IV-49 requires knowledge of  Sa, the suspended
solids concentration at a distance n - a above the bottom (where typically a « 0.05,
or 5 percent of the river's  depth).  The equilibrium expression for suspended  sedi-
ments, which is found 1n numerous sediment transport texts (e.g. Graf, 1971) can  be
rearranged to express Sa as:
where
        n  -  relative depth above bottom.
To use this equation the suspended solids concentration must be known at one depth In
the water column.  Typically, a depth averaged suspended solids concentration might
be readily available.  Under these circumstances Sa can be estimated as:
                              Sa •—\  , ' x a  '                           (IV-105)
                                              dn
where
        S  •  depth average suspended sediment concentration.
The denominator of Equation IV-105 can be integrated numerically by one of many
available solution techniques (e.g. see Carnahan et^ jj_., 1969).  For the case
                                         -423-

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    0.9-



    0.8-



    0.7- •



  X 0.6 —
  *-
  a.


  o °5"



  > 0.4- •



  < 0.3--

  uj

  * 0.2--



    0.1- •
   0.05-
                           S, • 10.
      0.001            0.01              01              1.0



         RELATIVE  POLLUTANT  CONCENTRATION.  7°-
                                                   ^T
FIGURE IV-^8
                 VERTICAL DISTRIBUTION  OF RELATIVE  SOLUTE

                 CONCENTRATION,  KpSA =  10,
z
&


$

5
    0.9-



    0,8-



    07.



    0.6-



    0.5-



    0.4-



    0.3-



    0.2



    0.1-1
   O.OS
           KpSa*100
      0.001              0-01              0.10

               RELATIVE POLLUTANT CONCENTRATION  C/CT



FIGURE  IV-49    VERTICAL DISTRIBUTION OF  RELATIVE  SOLUTE

                 CONCENTRATION,  KpSA  = 100.
                         -424-

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when  a  -  0.05 the  relationship between Sa and S 1s given below:

                                2 «   0  » Sa « S
                                2 - 0.2—»-Sa • 1.8 S
                                z « 0.6—»-Sa * 4.4 S
                                z - l.C—^-Sa - 8.2 S                      (IV-106)
                                z « 2.0—»-Sa - 17 S
                                z • 5.C—»-Sa ' 20 S

Based on a knowledge of S, Sa can be estimated from Equation IV-106,  and in turn can
be used In Figures IV-48 and IV-49.
     Typically there 1s a segregation of particle sizes found in suspension compared
with these found 1n the bed load, and In the Immobile bed materials.   Based on these
differences, the following can be hypothesized:
        Xs > Xbl > X1m
where
        X    *  sorbed pollutant concentration on suspended materials, mass
                pollutant/mass sediment
        Xbl  *  S01"'*6^ pollutant concentration on bed load, mass pollutant/
                mass sediment
        X,   -  sorbed pollutant concentration on Immovable sediment, mass
                pollutant/mass sediment.
Investigations carried out by Miles (1976) appear to support this relationship.
Miles collected Insecticide residues on stream sediments and In the water column.
Results of the DOT analysis of B1g Creek, Norfolk County, Ontario, 1973 (DOT was
banned In 1970) are as follows:

                     Concentration of DOT on Sediments
                   (mass of pollutants/mass of sediments)
                    Suspended sediments   110 ppb • X
                    Bed load               76 ppb - X^
                    Immovable bed          26 ppb • X.
Miles (1976) also found that DOT transported In the dissolved phase ranged from
10 to 92 percent of the total transported In the water column.  This finding 1s
consistent with the results 1n Table 11-14 which shows that the percent of pollutant
transported In the dissolved phase can be high even for pollutants such as DDT as
long as the suspended solids concentration 1s not extremely high.
     Contaminant data collected In bedded sediments can be very Illuminating.
Although in a screening approach 1t Is not anticipated the user will go to the
field to collect sediment core samples, some data might be available.  Depending
                                         -425-

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on the quantity of data available the following types  of Information might  be
determlnable:
        •    The spatial  extent of contaminated sediments,  and  pollutant  concentra-
             tions In the sediments
        •    The depth of contaminated sediment
        •    The quantity of toxicant contained In the sediment
        •    A time history of pollution levels to determine  whether they are
             Increasing or decreasing
        •    The probable sources of the pollutant, based on  the location and
             quantity of contaminated sediments.
Although extensive sampling Is required to accurately  determine all of the  above
Items, such programs have been successfully accomplished.  For  example, an  extensive
sediment sampling program was conducted 1n the Hudson  River In  New York to  determine
the sources of PCBs In the contaminated sediments, and the degree of contamination
(Turk, 1979).

4.9.3  Transport and Transformation Expressions for Toxicants 1n Rivers
     The tools presented in this section can be used to predict instream  concentra-
tions of toxicants for a variety of different situations.  Specifically,  the following
scenarios are addressed:
        t    Mixing zone analysis
        •    Continuous point source discharges
        •    Continuous nonpoint source discharges
        •    Oesorption from bedded sediments
        •    Spills and Instantaneous release of soluble chemicals, and
        •    Spills of high density chemicals which sink to the river  bed.
     In contrast to many conventional organic pollutants which  degrade into innocuous
substances, many toxicants are transformed to other chemicals which can be as  harmful
or more harmful than the original.  Consequently, when toxicants are continuously
discharged into a river, in addition to predicting the concentration profile,  it  is
useful to also determine:
        •    The pollutant's advection rate past a specified  location
        •    The pollutant's volatilization rate over a specified reach
        •    The pollutant's rate of transformation to other  species over a specified
             reach.
The toxicant's fate is thus segregated Into the processes of  advection, volatilization,
and transformation.
     In the following three sections on mixing zones, point sources, and  nonpoint
sources, the user will find there are different methods of approaching the problems.
One way to simplify the analysis is to first assume toxicants act conservatively.
                                        -426-

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The user can then perform a first level analysis to find out whether criteria are
violated.   If they are not, then a detailed analysis Is really not required if the
objective is to determine criteria compliance.  If violations are predicted, a more
detailed analysis of these "hot spots" can be performed by considering the various
processes affecting the toxicant In the river.  This approach requires more work, but
by judiciously applying the tools available, the analyses can be expedited.

4.9.3.1  Mixing Zone Expressions
     Section IV-4.1.9 presented earlier delineated one- and two-dimensional mixing
zone expressions for conventional pollutants.  The one-dimensional expressions need
to be extended in order to differentiate between solute and sorbate.  To do this, the
following expressions for pollutant concentration and the suspended solids concentra-
tions are needed:
                                                                           (IV-107)
                                  Cut Qu
                             to
                                            wt
                                                                           (IV-108)
where
        V Cut
             wt
                    concentration of suspended solids and concentration
                    of sum of solute and sorbate in the river above the  location
                    of mixing, respectively
                    concentration of suspended solids and concentration
                    of sum of solute and sorbate in the wastewater, respectively
                    concentration of suspended solids and concentration  of sum of
                    solute and sorbate in the river following mixing,  respectively
The dissolved phase concentration, C, of the pollutant at the completion of mixing  is
given by:
        S, C
            to
                                C -
                                        to
                                                                           (IV-1C9)
where C.   and S are found from the two previous expressions.
The concentration of the solute following mixing depends on characteristics of
the waste source, the river's flow rate, and the suspended solids concentration
in the river and waste source.  The solute concentration might also change after
mixing with a tributary of very high suspended solids concentration (high S },
even if 1t contains no additional  pollutant (C
                                              wt
                                                   0).
     Equation IV-108 1s particularly useful  because it predicts the total  instream
                                         -427-

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concentration of toxicant following Initial mixing.  This Is often the critical test
In establishing whether or not water quality standards are violated by a point
source.
     In cases where Initial mixing Is Incomplete (that Is the waste 1s Initially
diluted with a fraction of the total river flow), the two-dimensional mixing equation
shown earlier as Equation IV-4w1ll more accurately predict C.Q.  Then Equation
IV-109 can be used to find the solute concentration.
     When there are numerous discharges of the same toxicant,  analysis becomes
more complicated.  The most straightforward method of handling this situation
1s to sequentially apply Equation IV-108 to the series of discharges to find the
concentration as a function of distance downstream.  If the solute concentration is
needed, then sequential application of Equations IV-108 and IV-109 1s required.
     The analysis of multiple point sources can be simplified  in one of two ways.
One, the sources can be transformed to an equivalent nonpoint  source by assuming that
the toxicant input 1s uniformly distributed between the series of point sources. This
approach is discussed in Section 4.9.3.3.  Two, a series of closely grouped point
sources can be handled as an equivalent point source.  The equivalent point source
has a flow rate equal to the sum of the flow rates from the individual plants, or:
                                     Qw •  2-   Qw1                          (iv-no)

where
        Q ,  »  flow rate from ith treatment plant
        n    -  number of treatment plants being grouped.
     The total pollutant load can be expressed  in one of two ways.  If the concentra-
tions in the wastewater are known then the total loading is:
                                   Cw Q» '     Cw1
where

If the mass emission rates are known instead then:
C .   «  concentration of toxicant in effluent of 1th plant.
                                      "^    1-1
where
        M.  «  mass emission rate of toxicant from 1th plant is Ibs/day.
The conversion factor 5.38 converts mass emission rate in  Ibs/day to flow units
1n cfs  and concentration units  1n mg/1 (ppm).
     The grouping procedure described above has been applied by the U.S. Environmental
                                         -428-

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Protection Agency (1981) to a case study in Indiana to evaluate the economic impact
of toxicant standards.  Numbers of point sources were grouped together using a
procedure called cluster analysis.  The cluster analysis added the loadings of major
and minor industrial dischargers within a ten-mile radius of each other.   Ten clusters
were identified and few violations occurred within them once the best available
technology was attained.
     For  certain applications  the object of using  a mixing zone equation is to
directly  find  the maximum  allowable concentration  in  the discharge so that the
receiving water criteria are not violated.  Under  these circumstances Equation
IV-108 can be  rewritten as:

                                 C   (Q.  + Q   -  C   Q
                                     (Quc
where
         (C fL,   "  maximum allowable concentration of the toxicant
          Wt nlaX
                     in the waste discharge so that the water quality criterion
                     is met under critical conditions
         C.        «  water quality criterion for the toxicant
         Quc       »  critical river flow rate (e.g., 7Q10).
Equation  IV-113b  is applicable when the concentration of the toxicant is zero upstream
of the discharge  point.

4.9.3.2   Point Source Discharges
    For  point sources of toxicants, the pollutant  interactions depicted in Figure
IV-50 are simulated.  While transformation of toxicants is general ly more complex
than this, in many instances these interactions are sufficient to  analyze the in-
stream processes  affecting not only point source discharges but also nonpoint source
discharges, and instantaneous releases of soluble  pollutants.  Figure IV-50 reveals
that:
         •   The  solute only is assumed to volatilize.
         •   First order transformation processes  degrade only the solute.
         •   Adsorption and desorption are assumed to occur at rates much faster than
             other processes.
         •   No interactions with the bottom sediments occur (this is analyzed
             in later sections).
                                         -429-

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             I//H///////////II///UIIII/IIIIIIIIIIIII1IIIIIIIIIIHIIIIIIIIIIIIIIIIII1
             FIGURE  IV-50    INSTREAM  TRANSFORMATION  PROCESSES
                               ANALYZED  FOR TOXICANTS,
Based on these interactions,  the  concentration  profile below a point source of
toxicant is expressible  as:
                 .
where
        C    *  concentration of dissolved phase of the toxicant  at  a  distance
                x below the point source
        CQ   «  concentration of the dissolved phase of the toxicant at  x  «
                0 (after the point source discharge has mixed  with the river  water)
        D    •  water depth
      £k^   •  individual first order decay rates which are transforming
                the toxicant (other than volatilization)
        P    »  partial pressure of the toxicant In the atmosphere above the  river.
        The remaining variables have previously been defined.
Typically the partial pressure 1s zero, so that Equation  IV-114 simplifies  to:
                         C - CQ exp
                                      "k
(IV-115)
                                        -430-

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The initial dissolved phase concentration 1s given by:

                                            Ctn                            (IV-116)
where
        C   was defined by Equation IV-108.
The total pollutant concentration, C ,  at any location 1s:

                                    Ct  - C (1 + KpS)                       (IV-117)

The sorbed phase concentration expressed as  mass per unit  volume of  water 1s:



and the sorbed phase concentration expressed as mass per unit  mass of sediment  is:

                                         X - KpC                           (IV-119)

     The most direct application of Equation IV-114 cr IV-115,  plus  Equations
IV-117 through IV-119 is to find the Instream concentration  as  a function of distance
below the point  source.  There are, however, other uses of  the expressions. Consider
Equation IV-115, for example.   The ratio C/C  can be directly  calculated  as a
function of distance.  Thus the fractional dissolved phase concentration  can be
calculated without ever knowing the initial  concentration  C  .   This  approach has
the advantage of requiring less data.  Similarly, the fractional concentration  can be
calculated for any specified distance,  such  as the end of  a  reach.   Or, the distance
x can be found so that the fractional  concentration is some  specified number, which
may relate to an acceptable level of toxicant.  The length of  river  subjected to
unacceptable levels can then be found.
     The user might additionally want to know the distribution  of pollutant fluxes in
terms of advection (M^), volatilization (M ), and transformation (1^). Expressions
for these are presented for the case of P «  0.  These formulae  allow the  user to  pre-
dict the fluxes associated with the point source discharge where volatilization is
not altered by a background concentration In the atmosphere.  Under  these conditions:

                                     M - M,  + M  + M.                       (IV-120)
                                          d     V    t

Equation IV-120 states that the rate of entry of the toxicant  into the river  (M)
equals the rate of advecticn of that toxicant past some location x  , plus the
                                        -431-

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rate of volatilization across the water surface between  the  discharge  location  and
some other specified location plus the rate of transformation  of  the toxicant to
other substances within the water column between the same two  locations.   By knowing
expressions for each of M , H ,  and I"L the user knows the major processes
controlling the toxicant's fate  within any reach of river.
     The mass flux advected past a location x$ 1s given  by:

                                           Cs                               (IV-121)

where the concentration C$ 1s evaluated at x • x$.  The volatilization  mass  flux 1s
given by:
Mv ' Ac "v C0
              u (i + K s)
                                                     /   k; + £k     \
                                                     f - U  (1 *  Kpl) *sj
(IV-122)
where
        AC  -  cross-sectional area of river
        All other terms have previously been defined.
In some cases the user might have an estimate of the average dissolved phase concen-
tration, C, within the reach under consideration. Under these circumstances the
volatilization flux Is simply:

                                       M, ' At k  r                        (IV-123)
where
               surface area of the reach under Investigation.
The transformation mass flux Is expressible as:
                              U  (1 +  K  S)
                                             1-exp
                                                                            (IV-124)
 Since the  sum of Equations  IV-121, IV-122, and IV-124 equals the mass emission rate
 of  the  toxicant, Equation IV-120 can be used to double check the fluxes calculated.

 4.9.3.3 Nonpolnt Source Discharge
     This  section parallels the previous section on point source discharges by
 presenting expressions for  the steady-state concentration profile, and for mass
 fluxes.  In  addition to applying this methodology to a nonpolnt source, another and
 possibly more useful application 1s to express a series of point sources as an
                                         -432-

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equivalent nonpolnt source.  The equivalent nonpolnt source discharge rate Is simply
the sum of the discharge rates of the pollutant from all the point sources.  This
approach 1s not as accurate as analyzing each point source Individually but 1s much
faster depending on the number of point sources.  For example, suppose a river
segment has ten separate point sources located within 50 miles of each other.  The
most rigorous analysis Mould consist of considering each point source Individually,
where mixing zone and point source equations are applied sequentially ten times each.
This obviously 1s a great deal of work for a hand calculation approach.  By consid-
ering these point sources as a single equivalent nonpolnt source, a single equation
application 1s sufficient to analyze the problem.  Example IV-5 shown earlier in the
BOO section Illustrates this procedure.
     The solute concentration  in  a  river  resulting  from  a  steady  nonpoint  source of
toxicant is:
                                   /       \ /n  a. »w \  L,
                                                                           (IV-125  )
where

k2

k3
1 + KS
P m
A m
C
« k, + k1 + '
2 v '
             -  total concentration of toxicant in nonpoint source
        'tn
        Qf   *  river flow rate at end of nonpoint source
        Q    «  river flow rate at beginning of nonpoint source
        x.   •  length of ncnpoint source.
Equations IV-117 through IV-119 can be used to find Ct, C ,  and X,  respectively.
     In a manner similar to point source discharges. Equation IV-120 which expresses
the mass balance between toxicant inflow rate to the river and loss rate by advection,
and transformation, is valid.  The appropriate expressions are (when P » 0):
1   (Q0+mx)C  +  (Qp-Hnx) Ck S    at x - x$

   solute           sorbate
transport         transport
                                                                            (IV-126)
                                         -433-

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for the advcctlve flux.  For the volatilization flux:
For the transformation flux:

ftt  "   -Ik,
               £ *S +  Zk1AC  (C0 * M  i  **
                                \     *3/  m  icj-kj
As a first cut analysis, the user might want to assume that the toxicants act
conservatively.  If criteria are not violated under these circumstances,  then
criteria will not be violated if decay or transformation processes are included.

4.9.3.4  Desorption of Toxicant from a River Bed
     Because many toxicants are transported as sorbate rather than as solute,  a
significant fraction of the pollutant which enters a riverine system can  ultimately
be deposited  in  the bedded  sediments.   If the toxicant  is resistant to degradation
processes  it  can remain 1n  the sediments for extended periods of time.  During this
time,  the  toxicant can  slowly be desorbed back  into the water column or scoured into
suspension.
     Figure  IV-46 shown earlier  Illustrated an  idealization of the process of
desorption of  a  toxicant from bedded sediments. The process can be described as
follows.   Supposed the  average concentration of the pollutant  in the bedded sediment
is X   when the analysis bealns (called  t « 0).  The concentration X, at any later
time is estimated from mass balance considerations as:

                                    o  •  for x  * ¥nr
                                                  8 P                          (IV-129)
                                       .  otherwise
where
        XQ  •  concentration of pollutant 1n bed at some time t « 0
        M$  •  mass of contaminated sediment per unit area of river bed,  g/cm2
        U   »  stream velocity, cm/sec
        6   •  equivalent depth of water In sediment M   cm
        K
         p  »  partition coefficient.
Equation IV-129 reveals that desorption can be Interpreted as a frontal  phenom-
enon where desorption Is completed at one location before progressing downstream.
Based  on this interpretation, an effective removal velocity of the front  ^s:

                                      U   «  O-                              (IV-130)
                                         -434-

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 The  time T   required  to desorb  the toxicant over  any  specified distance  is:
 where
         x,  «   length of contaminated river segment.
 During  the  period of desorption the  average concentration  in the water column is:

                                     Xn6
                                     -2-  for x>  Uet                           (IV-132)
                                     P
                                     0    ,  otherwise                          (IV-133)

     To  use Equations IV-129 through IV-133, estimates for X   M , and 6 are
required.   If both the mass of contaminated sediment per unit area of river bed
(M.) and the mass of toxicant in the sediments are known, then X  can be deter-
mined.   Conversely, if both X  and the total mass of toxicant in the sediments
are known, then M^ can be calculated.
     In  lieu of having data on M  and 6,  these quantities can be estimated based
on the depth of contaminated sediments  by using  Table IV-39.   In addition to the
depth, the percent solids by weight must  be estimated.   This  parameter generally
increases with depths and can be chosen as 50 percent,  unless better data are avai-
lable.  The data in Table IV-39 were derived from the following two equations:

                              M            °C
                              Ms   '  ..  /   ..	Tn7TF\                     (IV-134)
and
                                                                             (IV-135)
where
                                                 2
        MS  «  mass of contaminated sediment, g/m
        6   «  equivalent water depth, mm
        S   »  specific gravity of solids
        D   «  depth of contamination, mm.
In cases where the depth of contamination exceeds 100 mm the equations can be
used in lieu of Table IV-39.
     The Hudson River in New York State provides an illustration of an extreme
                                         -435-

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                                    TABLE IV-39
                MASS OF CONTAMINATED SEDIMENTS AND EQUIVALENT WATER
                   DEPTH AS A FUNCTION OF DEPTH OF CONTAMINATION
Depth (mm)
1


5


10


20


50


100


Percent Solids by Weight
20
50
80
20
50
80
20
50
80
20
50
80
20
50
80
20
50
80
Ms (g/cm2)
0.02
0.06
0.11
0.11
0.30
0.55
0.23
0.60
1.1
0.45
1.2
2.2
1.1
3.0
5.5
2.3
6.0
11.0
6(1.)
0.9
0.6
0.3
4.5
3.0
1.4
9.1
6.0
2.7
18.
12.
5.5
45.
30.
14.
91.
60.
27.
case of PCB contamination (Turk, 1980).  Between 1951 and 1977 PCSs were discharged
from point sources near Fort Edward and Hudson Falls, about 80 km (50 mi) above
Albany, New York.  Figure IV-51 shows the general vicinity.
     During this time period the mass emission rate of PCBs decreased from 15 kg/day
(33 Ibs/day) to  less than 1 g/day (0.002 Ibs/day).  PCB concentration in the bottom
materials range from about 200 ng/g near Fort Edward to about 4 ng/g near Waterford,
about 70 km (43 mi) downstream.  In 1975 the New York State Department of Environmental
Conservation began a study to determine the source of contamination.  At that time
they estimated that the total mass of PCBs in the bottom sediments was 225,000 kg
(500,000 Ibs).
     It has been found that PCBs are being naturally desorbed from the river bed
under moderate and low flow conditions. The estimated transport rates are:
        At Glen Falls     «  0.0 kg/day (above discharge)
        At Schuylersville «  4.0 kg/day
        At Stillwater     -  5.0 kg/day
        At Waterford      «  4.0 kg/day (70 km downstream).
It  is  interesting to note that these transport rates are approximately 30 percent as
                                         -436-

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                                        Glens
                                                Hudson
                                                Falls
N
                     0    $   10   IS KILOMETERS
                FIGURE  IV-51   LOCATION MAP  OF HUDSON  RIVER,  NEW  YORK,
high as the original  point source mass  emission  rates.  At  a desorption rate of about
4 kg/day, the river between Glen Falls  and  Waterford would  be rid of PCBs  in about
150 years.
     Turk (1980) found that flood events transport  large  quantities of PCBs, although
this transport mechanism is only operative  periodically.  Turk  estimated that due to
the combined removal rates of PCBs during high  flow periods (by scour) and during low
flow periods (by desorption), the residence time of PCBs  above  Waterford would be
about one century.
                                  EXAMPLE IV-18
   For discharges of 600 m /sec or less,  it has been found  that  the Hudson River bed
   provides 4 kg/day of PC8s to the water column at  locations  between  Schuylersvi1le
   and Waterford, New York.  Determine the PCB concentration  in  the water column at
   the following two flow rates:
                                         -437-

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           a.  600 iir/sec
           b.   50 nr/sec.
   Compare these concentrations to the freshwater criterion of 0.001 jig/1  promulgated
   in the "Red Book".
        Since the mass emission rate and river flow rate are known,  Equation  IV-11
   can be rearranged to yield the total Instream concentration:
           C» '
              , 1.5 x 600 V   80  /  .  160 «« - 16 00
                         /I00-80>             Jo on
                     1.5 "
   where                                                                               J
           M   •  mass loading, kg/day
           C   «  concentration of pollutant, ppm
                              3                                                        i
           Q   «  flow rate, m /sec.                                                   ;
I   For the problem at hand:                                                            I
|           M  « 4 kg/day                                                               j
j           Q  • 50 and 600 m3/sec.                                                     j
                3
j   For Q » 600 fir/sec:                                                                 j

i           CT - -soxm  ' °-08 x 10~3 ppm                                            i
|              « 0.08 ng/1, or 80 times the Red Book criterion.                          |
|   For Q « 50 nr/sec:                                                                  |

I           CT " 86.44x 50 " °'9 x 10"3 ppm                                             j
I              « O.g Kg/U or gOO times the criterion.                                  I
       As  a  second part  to  the  problem estimate  the  time required to remove the PCBs
   in the  sediment by desorption (ignoring  scour),  assuming the desorptlon rate of 4    ;
I   kg/day  is  not  known.   Base  the  calculations on Table 1V-39 or Equations 1V-130 and   \
j   IV-131.   Use  the following  data:                                                     ]
I           Depth  of contaminated sediment • 600 mm                                      j
|           River  velocity »  1  fps                                                       I
j           Partition  coefficient :   103 to  104                                          j
j   Because the depth  of  contamination  exceeds  the maximum value tabulated in Table      i
•   IV-39,  Equations  IV-134 and  IV-135  are used Instead.  Assuming S  - 1.5 and P « 80:  '

i                                                                                       i
i           Hs	,   ,6°° ,nA..M * M 9/0.7
                                         -438-

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   The effective  transport  velocity  1s:
          ue" erriS*m  -25 x  10    u    for  "p
'   and
          Ue ' 6TTTO-5 - -25 x 10-3 U   for Kp - 103

I   The  time  required  for desorption over the 70 km (43 mi) reach is:
j
|         T  -  JVlO^°x  l  Sec - 290 year for Kp - 104
I
   and

          T « 29 years for K  - 10

|   Probably  the  biggest unknown  in this problem is K .  Based on a range of
             34                               ^
|   K  from 10  to  10  , the time  of desorption ranges from 29 to 290 years,
j   within  the  range predicted from observed desorption rates.
L..
                              END OF EXAMPLE IV-18 	
4.9.3.5  Instantaneous Releases of Low Density Toxicants
     Many toxicants have specific gravities less than  or  equal  to  unity.   Should  a
toxicant less dense than water be spilled in its pure  form,  the toxicant  can  ride
atop the water body for a period of time, while (perhaps)  being rapidly volatilized
and photolyzed as it becomes entrained and dissolved  in  the  river.
     Analysis of releases of low density pollutants Is complicated and, 1n many
cases, beyond the scope of hand calculation analyses.  Often spills of toxicants
occur over a part of the river, so the resultant movement  Is three-dimensional
because the toxicant spreads laterally, longitudinally,  and  vertically due to
turbulence and advectlon.  Buoyant spreading and mixing  can  further complicate
the dispersal process.
     Toxicant spills can occur 1n numerous ways.  In  one  Instance  the toxicant
may be discharged directly onto the surface of the river,  and depending on the
rate of mixing with ambient water a significant portion  could volatilize  directly
from the pure phase.  On the other hand submerged spills  may result in the chemical
becoming mixed with river water before 1t reaches the  water's surface.  Under these
circumstances volatilization fluxes will not be as great.
     When a chemical is spilled In pure form, the time required for the chemical
                                         -439-

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     It Is worthwhile to calculate the volume of water required  for  a  mass  M of
spilled chemical to be diluted to Us solubility Unit.  This  can  provide a rough
Idea as to whether mixing 1s likely to be "Instantaneous"  or not.  Suppose  that  a
mass M of spilled chemical  has a solubility C .   The volume of water needed to be
mixed with the pure chemical so that the solubility 11m1t  1s achieved  1s:
                                    V0 - M * 10                              (IV-138)

where
        M   »  mass of sp11 1 , kg
        C   •  solubility, mg/1
         5                       3
        V   -  volume of water, m
         o
     The concentration profile resulting from an Instantaneous spill  (and assuming
concentrations at or below the solubility limit are rapidly attained)  1s  expressed
by:
where
        C   •  dissolved phase concentration
              k1 + r-k,
                   V
         M    «  total mass  released
         The  remaining  variables have been previously defined.
 In most  Instances the  user would like to predict the maximum concentrations remaining
 1n the river for different elapsed times following the spill, given by the peaks In
 Figure IV-53.  Under  such conditions, and assuming P • 0, Equation IV-139 simplifies
 to:

                                           exp (-kl)                         {IV-140)
     The various components of the mass balance at time t  follow (for P • 0).
        Mass of dissolved pollutants  MQ (t • t$):

                         M0 (t • t$) ' M
                                         -442-

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    25
    20
  CD
  a.
  a
  o>
   '10
    \
h   \
          \25Miles
                \
                 \
                    XTSMiles
1 ,
\
""*"-• -^ .125 Miles
1 ,A~;-
200 Miles
"A;—
250 Miles
TV
                  50           100           150
                         Hours from Beginning ol Spill
                                                   200
250
      FIGURE  IV-53    HYPOTHETICAL DISTRIBUTION  OF TOXICANT  AT VARIOUS
                       LOCATIONS  FOLLOWING  A SPILL
        Mass  of  sorbed pollutants  M  (t « t ):
                             KpS MD exp (-kfits)
        Mass  of  pollutant which was volatilized My  (t  «  t$)
                   Mv (t - ts) - ^v  [1.exp(-kets)]
                                                                    (IV-142)
                                                                         (IV-143)
        Mass  of  pollutant which has decayed MQk (t  •  t$):
                        Dk
                                    -  [l  -  exp(-kets)J            (IV-144)
Equations IV-140 through  IV-144 allow the user to assess  the  fate of the pollutant
for any desired time t$ following the spill.
     A direct  extension of the instantaneous pollutant  release  in a plane is the
volumetric  release, where the pollutant is effectively  released within some Initial
                                       -443-

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^L  [e
2V0  L
volume of water.  For this case, the dissolved phase concentration Is:


                       | erf  t^^-}  -erf  (*4^M|    (exp(-k t))      (IV-145)
                             \v40t /         \v4Dt /I    \          /
where
        L    •  length of zone of Initial contamination
        erf  «  the error function
        All other variables have been previously defined.
The location of the maximum concentration for any time t$ after release 1s
approximately given by:

                                 x - Ut$ + L/2                             (IV-146)

4.9.3.6  Spill Analysis of High Density Toxicants
     Spills of hazardous chemicals have been of concern for quite a number of years,
and  Interest will increase as the quantity and variety of toxicants transported
increase.  In past years the primary emphasis has been on analysis and containment of
oil  spills.  This has probably been for a number of reasons:
        •    Large quantities of oil are transported, and are therefore subject
             to more frequent spills.
        •    The environmental consequences of an oil spill can be severe and
             visually offensive.
        •    Oil floats, so oil spills are easy to detect and monitor.
     In contrast to oil, many hazardous chemicals have specific gravities greater
than one,  so that in their pure form, they tend to sink in water.  Table IV-40 lists
some such  chemicals.  Chlorine, although it may be transported under pressure as a
liquid, is a gas under atmospheric conditions. Even so, if a  liquid chlorine barge
were involved in an accident on a river some of the chlorine could become dissolved
in the water since the solubility of chlorine in water 1s 50,000 mg/1, although most
would probably gasify and form  a toxic cloud.
     The chemicals  shown  in Table  IV-40 are generally either  slightly soluble
(10  to 10,000 ppm) or soluble (10,000 to 1,000,000 ppm).  In  any case the solubility
levels generally exceed or greatly exceed proposed water quality criteria. Thus  if a
mass of chemical were spilled into a river, H 1s to be expected that concentrations
near the chemical's solubility  limit could be detected In the  immediate vicinity of
the  spill.  As  the chemical  is dissolved and travels downstream, it could eventually
become mixed over the channel cross-section and expose all organisms  living within
the  water  column (and perhaps those  living in the bedded  sediments  as well) to its
effects.   With  increasing distance the concentrations of  the  toxicant will decrease
to reflect the  additional mixing afforded by the flow of  the  entire  river, plus
                       -444-

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                      TABLE IV-40
WATER-SOLUBLE, HIGH DENSITY (p>l),  IMMISCIBLE CHEMICALS
Species
Acetic acid
Acetic anhydride
Acetophenone
Aniline
Benzaldehyde
Benzyl alcohol
Bromine
Carbon disulfide
Carbon tetrachloride
Chlorine (liquid)b
Chloroform
Chloroptnalene
Oichloroethane
Ethyl bromide
Cthylene bromide
Furfural
Glycerol
Hydrogen peroxide
Mercury0
Naphthalene
Nitrobenzene
Phenol
Phenylhydrazine
Phosphorus trichloride
Trichloroethane
N-Propyltro.Tide
Ouinol ine
Tetrachlcroethane
water"
• In air. water, and its
b Under pressure.
C Mercury *n
Solubility
In water Interfaclal Tension
(mg/1) Air Water
50.000 68.030.
500.000
5.550
34.000 44.0
1.000 40.04 15.5120.
46.000 39.02Q. <-7522.!
41.700 41.520.
2.200 - *8-362Q.
500 - 4520.
50.000
5.000 27.142Q. 32.82(f
40.742Q.
9.000 23.435.
10.600 - 31.220.
4.300 - 36.5420.
83.100 43.520.
63.418.
50.000
.0005 470 3752Q.
30 28.8J27.
1900 «3.92Q.
67.000 40.92Q.
-
50.000
10 22^,.
2.500
60.000 45.020.
3.000 36.322 5.
N.A. 73.05)g. N.A.
Te-.perature is *C.

reference.

(dynes/en)*
Vapor
2>.B20.
32.720.
39-820.
42-V
-
;. 39-020.
41.520.
-
26.952Q.
18-42(T
-
-
-
24.1520.
38.3720.
43.520.
7'-lll.2'
28.e127.
43.920.
40.020.
46.12Q.
29.120.
-
19.6520.
-
-
72



                         -445-

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 dispersion, degradation, and volatilization processes.
      A  technique  1s presented here to estimate the concentration which can exist in
 the  water  column  and the duration of the elevated levels following a spill.  In
 particular tools  are presented to predict:
         •    The  concentration of toxicant In the water column at the downstream
             end  of the spll 1
         •    The  concentration of the toxicant after 1t has become completely
             mixed with the  entire river
         •    The  time required to dissolve the spilled toxicant
         •    The  amount of toxicant remaining sorbed to the bottom sediments and in
             the  pore water  following dissolution.
It 1s, of course,  more accurate but  more costly to measure concentrations directly
rather than predicting them.   However,  since  the toxicant 1s "somewhere"  on the river
bottom, and might  not be Immobile, detecting  the location of the toxicant will  take
time.  By estimating the dissolution time of  the spill, 1t can be determined if it  1s
feasible to even set up and carry out a sampling program.
     The tools delineated above are useful  not only to analyze spills which have
occurred, but also for answering hypothetical  questions which relate to the consequence
of spills based on river traffic, sizes of containers, kinds of toxicants being
transported,  and characteristics of the rivers.  Based on this Information the user
can evaluate possible "spill  scenarios" to predict Impacts before they occur.  Such
Information would be useful to formulate post-spill  responses.  In situations where a
spill of a toxicant would produce extreme consequences, provisions could be made to
mitigate the consequences before they occur.

4.9.3.6.1  Description of Spill Process
     Spills which contaminate rivers can be the result of a variety of accidents:
leaking barges, broken pipelines, highway accidents, and clandestine dumping.
The scope here 1s limited to those situations where the toxicant has been deposited
on the bottom of the river.  This situation Is most likely to result from an accident
on or under the water's surface.  Figure IV-54 conceptualizes what night happen when
a barge carrying a high density pollutant ruptures.
     Depending on the volume of contaminant,  the size of the hole, among other
factors, the toxicant might  Issue from the barge as a continuous jet.  However,
because the volumetric flow  rate of the jet 1s probably small, and perhaps even
Intermittent, the toxicant probably breaks up Into drops of various sizes as it
falls through the water column.  Some of the finest drops might never reach the
stream bed, but rather be transported in suspension within the water column, and
gradually  dissolve.  The majority of the toxicant may settle on the river bed and
form drops, globs, or pools  (using the terminology of Thibodeaux, 1979).  The drop
                                          -446-

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                     Water column
                     velocity profile
River bottom.
 sand dune-
 crest and valleys,    -»-
                                                                        Large drops
5feU«fe#'ww^//»i;V/^/^x/vJ/^/W>^^
^eiope of zone of contamination'
                                       Droplet    Droplet-glob     Pool
                                        zone         zone        zone

       FIGURE  IV-54    ILLUSTRATION OF HYPOTHETICAL SPILL INCIDENT
                         (FROM THIBODEAUX,  1979),

size depends on the intrafacial  tension and density differences between the toxicant
and the water (Hu and Klntner, 1955).  Pools tend to form  in  the valleys of sand
waves, and occur when large drops or globs coalese.  Thibodeaux (1980)  provides
techniques to estimate the residence time  of drops, globs, and  pools.   For the
simplified analyses here the spill  Is assijmed to be 1n  the shape of a  continuous
pool.
4.9.3.6.2  Fate of Pollutant Following Settling
     Once the toxicant has settled on the  river bed Its fate  1s governed by numerous
processes.  Depending on the texture of the bottom materials  (e.g. sands, cobbles,
boulders), the density of the toxicant, and Its Interfacial tension,  the toxicant
could settle in deep depressions, and dissolution would be slowed.
     Many pollutants have large partition  coefficients  so  that  sorption to bottom
sediments is significant.  The characteristics of the sediments affect  the partition
coefficient, but in many cases sorption can compete with dissolution  as a major
process controlling the pollutant's fate.   Although transformation processes other
than sorption and dissolution are operative the moment  the toxicant enters the water,
they are not considered here.
     In September 1974 an electrical transformer being  loaded onto a barge fell
Into the Duwamish Waterway in the State of Washington (Thibodeaux, 1980).  250
gallons of Aroclor 1242, a PCB mixture of specific gravity 1.4, were spilled into the
river.  Divers observed that pools of free PCB on the bottom moved back and fortn
with the tide.  Pools of PCBs were removed from the bottom using suction dredges, and
a second stage operation involved a high solids dredge.  Probably due to its low
solubility (0.2 ppb) and high sorption characteristics, much  of the PCB was recovered
(from 210 to 240 gallons).
                                -447-

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4.9.3.6.3  Predictive Tools
     It 1s hypothesized that a toxicant  spill  contaminates  an area of width W
and length L$, where the length 1s measured  1n the  flow direction.  The toxicant
which reaches the river bed 1s assumed to be highly concentrated, and Its dissolution
1s controlled by a thin layer Immediately above where molecular diffusion limits the
vertical flux of the pollutant. Above this layer the toxicant 1s  rapidly entrained
Into the river.  There are several expressions available  to determine the thickness
of the diffusion layer (e.g. Novotny, 1969 and Mills,  1976). The expression developed
by Mills will be used here, because the required Information 1s easier to attain
while the two approaches appear to give comparable  results. The expression  Is:

                                  11.6 • 1.49 v Rh  '/6
                                                 2 -                      (IV-147)
                                            Un
where
         6.   •  thickness of diffusive sublayer
         v    -  dynamic viscosity of water
         Rh   «  hydraulic radius of the river
         U    »  river velocity
         n    •  Manning's coefficient.
Just downstream from the spill zone, but before complete mixing with the river,
the concentration of the toxicant 1n the water column 1s:
                                                        C                  (IV-148)
                          L     o          \  «dH U  /   S
where
                          C  • (C -C ) exp
                          LL   uo V exp
         C     -   background concentration of chemical
         C     •   solubility of chemical In water
         0     »   diffusion coefficient of chemical In water
         H     •   water depth
         U     -   river velocity.
 The concentration  at the location of complete mixing Is:

                                                     .  -*}                  (IV-149)
                               ~WM    "L  *     "0 \"   W /
 where
         W$   -  spill width
         W    -  river width.
                                         -448-

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The time T. required to dissolve the chemical  Is:

                                Td ' T-J-TJ&7--                               (IV-150)

where
        MQ  •  total amount of pollutant which is dissolved («n amount  less
               than or equal to the amount spllled).
     As the spilled toxicant dissolves In the flowing river water,  it concur-
rently diffuses Into the Immobile bedded sediments,  where a portion  1s  sorbed
onto the sediments. Consequently, some residual  toxicant  will  remain in the  bottom
sediments following the initial  dissolution phase.  The residual  will then  slowly
diffuse and desorb back out into the river, although diffusion deeper into  the
sediments can also occur because of the concentration gradient.  The time  required
for the residual  toxicant to naturally desorb and diffuse back into  the water column
can greatly exceed the original  period of dissolution.
     The quantity of toxicant which resides In the sediments following  the  initial
dissolution period can be predicted as follows.   It  is assumed that  the dissolution
and downward diffusion/sorption proceed independently until all the  spilled  toxicant
has been removed.  The time t can be found such  that this statement  is  true.  From a
practical standpoint, the user can simply determine  the time required for  complete
dissolution, and  then find the total  mass which  would have diffused/sorbed  into  the
bottom sediments  during this period. Since this  approach  accounts for more  toxicant
than was originally present, the time period should  be decreased  by  the fractional
amount of toxicant created.  If the amount of excess toxicant  is  no  more than IS
percent of the total amount spilled, then a time adjustment is not  required.
     Based on the processes of sorption and diffusion the vertical  profile  of
dissolved chemical in the river bed at time t following the appearance  of  the
toxicant on the bottom Is given by:

                                   __» . i -_*  /   * _\
                                                                            (IV-151)
(v4Tt)
where
        C   •  concentration of dissolved chemical  1n the pore water,  in  units
               of mass of dissolved chemical  per unit volume of pore water
        Cfa  •  background concentration of chemical  in pore water
        C$  »  solubility of chemical  In water
        z   •  vertical  distance, measured downward  from the sediment-water  interface

        D   «  o
         P      e
                                        -449-

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        0   »  effective molcular diffusion coefficient
        p   «  density of sediments
        K   »  partition coefficient
        n   -  porosity of porous medium.
     From Equation IV-151, the total mass of pollutant found In the sediments
at time t 1s:
                                     /(C * Cs)
                                                                          (IV-152a)

                                                                          (IV-152b)
                                       w J \     'I

where
        A   «  spill area
        C$  »  concentration of pollutant sorbed to sediments,  per unit  volume
               of pore water.
Ce can be related to C by:
                                               / i  _ v
                                                                            (IV-153)

Combining Equations IV-151, IV-152 and IV-153 the total  mass 1n the sediment
1s:
                                     /          * _ V         -
                                                                            (IV-154)
                           °'563C   l  *  pk
.	EXAMPLE IV-19	

        The following Is an excerpt from Chemical  Engineering Volume 80,  September 3,
j   1973. as reported In Thlbodeaux (1979).
I             "Approximately 1.75 x 10  Ibs of chloroform were released
|           from a barge that sank near Baton Rouge. Louisiana, and the
           chemical  began flowing down the Mississippi  River toward the
           Gulf of Mexico.  Although state health officials did not push
           the panic button, noting that they did not anticipate too much
           trouble from the accident, the U.S. Coast Guard warned downriver
           communities to keep a close surveillance on  their water supply
           systems, particularly 1f Intakes were close  to the river bottom
           (chloroform Is heavier than water)."
   Based on the low flow conditions and the time history of the chloroform ccncentra-
                                         -450-

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   tion  much  of  the  chloroform  (of  specific  gravity  1.5) was  Initially deposited  on
   the  river  bed.  Determine  the fate of  the  chloroform during  the  first  few days
   following  the spill.   The following processes  are considered:
           t     Dissolution  Into the main  body  of the water
           t     Diffusion and  sorptlon Into  the bottom sediments
           t     Volatilization  Into the  atmosphere
           t     Sorptlon  to  suspended sediments.
        Since chloroform  1s  highly  volatile  and does not have  a strong tendency
   to sorb  to solids,  volatilization Is  an important process  controlling  Us  fate,
   while sorption  Is not. The  following  analysis  substantiates this  statement.
        The data pertinent to  the spill  are  (Thibodeaux, 1979; Neely e± ^aK, 1976):
           River flow  rate - 7590 m3/sec (268,000 cfs)
           Width of  river »  1220 m  » 4000  ft
           River velocity *  56.3 cm/sec  «  1.85  ft/sec
           Water depth »  11  m « 36.3 ft
           Diffusion coefficient of chloroform  in water « 1x10   cm /sec
           Length  of spill zone « 180 m  «  590 ft
           Background  chloroform concentration  *  5 ppb.
        Using a  Manning's n  of  0.03, the diffusion  layer thickness is:
)   The  average  concentration  of chloroform  in the water just below the spill zone
I   during  the period of dissolution  is:

j          C.  = (5 x 10-3  - 8200)  expf	-1- x 10"5  x  180	]  + 820Q
!           L                         \2.8 x 1C'2 x 11.  x  56.3/
I
             « 850 ppb
•   In order to  estimate the time required to dissolve  the chloroform the average
;   width  of the spill  zone is  reauired. The width is estimated to be 256 ft (78 m)
j   (Thibodeaux, 1981).
I       Based on  these data the dissolution ti.ne is:
I
j           T   ,  	0.9 x 1.75 x  106	,n  .
!           Td    5~38~T~.8TO x 1.85  x 156 x  36.2   2° dayS
I

,   The  factor 0.9 is used  in  the above expression because about  10 percent of
j   the  spill dissolved before  ever reaching the bottom (Neely _et^ _a_l_., 1976).
I       The amount of  chloroform which diffused and sorbed  into  the  sediments
                                         -4E1-

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  during this time period (20 days) will be estimated.  The porosity of the sandy
  bottom is approximately 0.35, and the partition coefficient is assumed to be 1.0.
  This is a realistic value based on KQw « 93 (see Table II-5).  The total mass
  contained in the sediments after 20 days is:
               •  .35 (,80 x 78) (M.K x 1 x $) K^£$^^

               x  ID'2-3 x (5-4.437)  =6000  kg

6000 kg is less than 2 percent of the total  mass which reaches the bottom
(715,000 kg).  Based on this result, it is not likely that the dissolution period
is markedly affected by diffusion of the chloroform into the bottom sediments.
Because of the vertical concentration gradient that has been established in the
sediment profile, some of the chloroform will temporarily continue to diffuse
downward after the dissolution period.   Hence concentrations in the water column
due to desorption ;f the chloroform and upward diffusion back into the water
column are not likely to be high compared to those observed djr'ng the initial
dissolution period.
     Following the chloroform spill, chloroform concentrations we measured
at several locations in the Mississippi River below the spill.  Figure IV-55a
shows the time history of the chloroform concentration at a location 16.3 miles
below the spill for the first 60 hours following the spill.  A more compressed
time scale is shown in Figure IV-55b and illustrates how the concentrations varied
for 20 days following the spill.  The peak concentration passes very rapidly (on
the order of 1 day) and the maximum observed concentration is aoout 365 ppb.  At
this location, the chloroform is approximately well-mixed with the river at this
point (Neely et_ aj_., 1976).
     Based on Figure IV-55b the total amount of chloroform passing the location
can be estimated  as follows:

        Mass  » /CQdt  »  Q f Cdt
                •/CQdt - Q/"
j   The right-most  integral  is  six.ply the  area  under  the  concentration-time  curve  in
•   Figure IV-55b.   Without  showing  the  calculations,  the total  -nass  of  chloroform
   (above background)  which passes  the  location  16.3 miles  below  trie so'll  is  about
;   300,000 kg.   Since  the  total  amount  of chloroform spilled  was  about  300,OCO kg,
I   more than half  of the chloroform was unaccounted  for.  It  is unlikely,  as earlier
I   calculations  showed, that diffusion  and sorptlon  into the  bottom  seaiment
I   significant.   Volatilizal'on  could be  important  and will be  c^ scussed  shc
                                         -452-

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          350
          300
       o
       a  250
       c
       o
       £  200
       4)
       U
       §
       O
        n 150
       -J
       .O
       O
          100
           50
                   •Actual Data
                        10
  20         30         40
        Elapsed Time. Hours
50
60
              FIGURE IV-55A
CHLOROFORM CONCENTRATION  IN  WATER COLUMN
FOR  FIRST  60 HOURS FOLLOWING A SPILL
16,3 MILES UPSTREAM,
        The  observed results shown 1n Figure IV-55a  are  compared against those
   predicted  in  this example.  A concentration of 850  ppb was predicted just below
   the  spill  site;  the maximum shown in Figure IV-55a is 365 ppb.  It is expected,
   for  several reasons, that the concentrations 16.3 miles below the spill site will
   be less than  at  the spill site.  First it is probable that additional dilution
   occurred  as the  chloroform was transported to the sampling site.  An estimate of
   the dilution  can be attained by multiplying  the  river width by the spill  width,
   or:
           4000
                  15
    ne ^ell-mixed concentration  becomes:
                > 60 ppb
|   Comparing this to Figure  i'/-55a,  1t  Is noted that this value approximates the
I   average concentration  following an elapsed time of about 20 hours, but misses  the
j   peak during the first  20  hours.   There may be a numoer of factors responsible  for
                                        -453-

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                 400
               I300
               5
               &
               M
               I
               .1 200
               n
               "E
               E
               5
               I
100
      FIGURE IV-55B
                                                '  r ' i  •  i
                                                •  Field data
                        • ••
       CHLOROFORM  CONCENTRATION  IN THE
       MISSISSIPPI  RIVER  AT A LOCATION  15.3
       MILES  BELOW THE AUGUST 19,  1973  SPILL.
this behavior, and one o* the most  Important will be examined  here.  During tne
spill  of chloroform, It was estimated that about 10 percent, or 80,000 kg were
transported  downstream directly without ever reaching the river bottom.  The
travel  time  to the sampling site 1s:

        TTO ' » »«"•
Figure IV-55a shows that this coincides with the arrival  of the peak at mile
16.3.   The peak concentration can be estimated using Equation  IY-140 presented
earlier.  The diffusion coefficient 1s approximately 210 m /sec (McQulvey
et^ aj_., 1976) for the lower Mississippi River.  The predicted  peak In concentration
at mile 16.3 1s:
                 80000 x 10'
             2  x 4000 x 36.3 x (.3048)2 \V210'3600-13
                                                        520 ppb
                                     -454-

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This concentration is  somewhat  higher  than  the maximum 365 ppb observed, but        j
this is to be expected since  Equation  IV-140 assumes the mass is input instantan-   I
eously, while in reality  about  8  hours elapsed.  Further if the concentration due   |
to the dissolved portion  of the spill  1s  calculated at 20 hours, a concentration    j
of 15 ppb 1s obtained. This  illustrates  that the mass due to initial dissolution   j
has almost passed the  sampling  location,  and the remaining contribution to the
elevated concentrations measured  1s  due largely to dissolution of chloroform which
has settled on the river  bottom.   It appears that there are two basic phenomena     j
which account for the  measured  concentration-time profile:  an initial period of    I
dissolution of chloroform (less than 1 day) before it settles to the bottom, and a  |
subsequent period (10  to  15 days)  of dissolution of settled chloroform.             j
     The absence of an adequate mass balance between the amount of chloroform       j
which entered the river as a  result  of the  spill and the amount which passed a
location 16.3 mi below the spill  has not  been addressed.  Volatilization losses
could be one reason for the imbalance.                                             .
     Equation IV-123 can  be used  to  estimate the volatilization losses.  Since the  J
chloroform was  initially  deposited on  the bottom of the river, during a portion of  I
the travel distance it was not  in contact with the atmosphere, and so volati 1 ization |
could not occur.  The  approximate travel  time for vertical mixing to occur is       j
(Fischer et aj.- • 1979> :                                                            i


         "•V                                                                !
where                                                                              I
        H   »  water depth                                                         |
        e   «  vertical diffusivity.                                                |
Choosing an e  value of 50 cnr/sec,  based on Fischer £t^ _ah (1979) and a            j
depth of 11 m, the travel time  required to  effect vertical mixing is:               j

         t  . 0-4 (HOP)2   hr  .  2  7 hrs                                             '
         1     50-3600      nr    '•' nrs                                             j

Based on a velocity of 1.85 ft/sec,  the travel distance Is about 3.3 miles.         I
Hence the pollutant is in contact with the  atmosphere for about 13 miles.           |
     Since only the dissolved phase  of chloroform volatilizes, the fraction         j
of the total chloroform as solute will be estimated using Equation IV-109:          '
The partition coefficient K  was estimated  as  1.0.  The  sediment concentra-
tion is about 400 ppm.   Hence:
                 1 + 1 x JOO + 10-


                                      -455-

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I   Thus, essentially all the chloroform is dissolved and is available  for volatiliza-   I
j   tlon.                                                                               |
j        Henry's Law constant for chloroform can be found based on the  data in          j
•   Table II-5:                                                                         j
           Vapor pressure « 150 Torr
j           Solubility in water » 8200 ppm
I           Molecular weight « 118.                                                     (
|   Henry's Law constant is:                                                            I
1           ISO x  118   . 3    ]Q_3  atm-rn3                                               '|
j           760 x  8200             mole
   From Table 11-15 a  typical  volatilization rate 1s about  17 cm/hr.
j        The average chloroform concentrations for the 13 miles above the data          ;
I   collection point are:                                                               I
j           200 ppb for 1 day                                                           I
|            40 ppb for the next 9 days                                                 |
j            10 ppb for the next 9 days.                                                 j
   The total  amount of chloroform volatilized Is (using Equation IV-109):              j
j           Z kv  C1 Ac At                                                              j
           - 0.17 x 24 x 1200 x 21 x 103(200 +  40  x  9 + 10 x 9 -5 x  19)x 103         j
j           • 5.8 x 107  - 58000 kg                                                    j
j   Hence, all of the unaccounted for chloroform (about 480,000 kg) could not have      |
j   volatilized within  13 miles.                                                        j
        Over  50 percent of the chloroform still  remains unaccounted for.  It Is        j
.   possible that other transformation processes were operative.  The environmental      •
I   fate of chloroform  In terms of photolysis, hydrolysis, oxidation, and biological
I   degradation was reviewed In Callahan e£ _aK, 1979.  It was concluded that these      !
I   processes are of minor Importance compared to volatilization and so are probably     j
|   not significant here.                                                               I
j        It 1s possible that the samples of chloroform shown in Figure  IV-55b were not   |
j   cross-sectional averages.  The chloroform concentration could have  been weighted     j
>   toward the stream bottom or toward one side.  A dye study performed by McQulvey      j
!   (1976) on the lower Mississippi River showed that 50 miles were required before
j   complete mixing was attained, while the sampling was conducted 16.3 miles below
I   the spill. Even though chloroform does not sorb strongly, there is  a possibility     '
|   that the suspended solids and bed load concentration near the bottom of the river   I
j   were high enough to cause substantial sorptlon.  Based on the evidence there Is  a   j
j   distinct possibility that some of the "missing" chloroform was actually advected     j
;   past the sampling locations without being detected.                                 j
 I	OF £XAMPLE Iv.19
                                         -456-

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 4.10   METALS

 4.10.1   Introduction

 4.10.1.1   Background
      In  addition  to organic  chemicals, metals comprise a second major category of
 toxic  contaminants which  are discharged  Into rivers.  Metals differ from toxic
 organics  1n a  number  of ways,  and these  differences  influence the approach used to
 predict  their  fate.   One  difference  is that metals are naturally occurring elements
 and their  fate can be detailed  individually since the number of different elements is
 relatively  small.  In contrast, an individualized approach is not always feasible for
 the thousands  of  organic  toxicants.  However, basic  properties of many organic
 chemicals  have been tabulated  or are derivable which can be used to  predict their
 fate.
     Two,  organic chemicals  are occasionally spilled into rivers because many of the
 chemicals  are  transported  in large volumes.  Metals, on the other hand, most often
 enter  rivers frcn continuous sources.  Consequently, methods to handle spills, wnile
 being  an  integral part of  the  screening  procedures presented for organic toxicants in
 the previous section, are  not  emphasized here.
     Three, metals are naturally occurring and are cycled througnout the environment
 by biogeochemical processes.   Consequently it is not appropriate to arbitrarily
 ignore background concentrations of metals, an approach reasonable for synthetic
 organic  toxicants.  Background  sources of metals can produce concentrations which, in
 certain  instances, approacn water quality standards.
     Four,  the fate of many metals is predominantly  controlled by transport processes
 since  they  generally  do not degrade, volatilize, or  photolyze as do many organic
 toxicants  (altnougn there  are  exceptions).  However, metals do speciate into many
 different  forms in tne aquatic  environment, and the  species may differ in toxicity
 and behavior.

 4.10.1.2   Organization
     Screening  metMccs presented in Section 4.10.3 can be used to predict the fate of
 metals.   These tools  assume that metals  are distributee between two basic phases:
 dissolved  and  adsorbed.   Linear partitioning is used to represent equilibrium adsorp-
 tion and thus  to  quantitatively relate the two phases.
     In  Section 4.10.4, a  detailed analysis of the speciation of arsenic, cadmium,
 chromium, copper, lead, mercury, nickel, silver, and zinc (As, Cd, Cr, Cu, Pb, Hg,
 Ni, Ag,  and Zn, respectively)  is presented.  The major processes affecting speciation
are delineated, and the equilibrium moael MiNEQL is  used  to  predict  the speciaticn of
    above solutes  for 14 cifferent  rivers and an acidified  lake m tne United States.
                                         -457-

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Simulated metal concentrations vary from background to well  above the 1984 U.S. EPA
water quality criteria.
     While the tools presented in Section 4.10.3 can be used independently of metal
species distribution predicted by MINEQL, the two approaches can be coupled together
to estimate species concentrations at different locations throughout a river.  The
steps required to accomplish this are described at the end of Section 4.10.4.
     Because of the potential importance of background contributions of metals,
methods are presented in Section 4.10.2 to address this problem. Since background
sources can be significant, this contribution should not be arbitrarily dismissed.
     Numerous case studies of metals in rivers In the eastern and western United
States are also reviewed.  The reviews may help the user to understand how metals
respond to different aquatic conditions and to establish concentration ranges which
have been documented in past studies.
     Finally, in Section 4.10.5, guidance is provided for a limited field sampling
program and river/stream reconnaissance.  A primary reason for suggesting a low-level
data collection program is a concession to the difficulty of predicting metal concen-
trations in rivers.  Although users are not required to perform a field study before
doing the screening analyses, in some instances they may decide a limited field study
is appropriate.
     The data requirements for the screening methods are summarized in Table IV-80 of
Section 4.1C.5.  Because degradation or removal rates are not required for the
screening analyses, the data requirements are somewhat more modest than for organic
toxicants.  The more important data are flow rates, loading rates, background levels,
and partition coefficients. Section 4.10.5 provides more discussion on the relative
Importance of the data requirements.  A summary of the screening methods for metals
Is sho«n 1n Figure IV-56.  An application and summary of the methods has recently been
published (Mills and Mok, 1985).  Also, many of the algorithms presented in Section
4.10 have been programmed for microcomputers (Mills, et_ £l_., 1985).

4.10.2  Water Quality Criteria, Background Concentrations, and Case Studies

4.10.2.1  Witer Quality Criteria
     Table IV-41 summarizes the most current U.S. EPA criteria (Federal Register
July 2?, 1985 »nd November 28, 1980) for the protection of freshwater aquatic life
for arsenic, cadmium, chromium, copper, lead, mercury, nickel, silver, and zinc.  The
1984 criteria pertain to arsenic, cadmium, chromium, copper, lead, and mercury.  The
1980 criteria pertain to nickel, silver, and zinc.  Many of the criteria depend on
water hardness. Examples are shewn in the table for hardnesses of 50, 100, and 200
mg/1 as CaCOj.  At the bottom of the table, expressions relating hardness to trie
water quality criteria are shown.  Note that the water quality criteria are expressed
a-s total dissolved netal.

                                         -453-

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                  Review Case Studfts
                  (Section 4.10.2.3)
                                               Decide if United  field
                                            Reconnaissance and/or Sampling
                                               Program 1s Appropriate
                                                  (Section 4.10.S)
            Identify and Quantify Background
            Contributions (Section 4.10.2.2)
               and Primary Anthropogenic
                  Sources (Chapter 3)
            and Suwarue Data Needed for Analysts
                     (Table iv-73)
                    c
Start
    Consider More detailed
    Study or Implementation
      of Renedlal Action
                                 Oocu*ent Problen Areas
                                       Apply Screening Methods  (Section 4.10.3)
                                       e Dilution  Only

                                       e Dilution  Plus Scour of Sediments

                                       e Dilution  Plus Deposition of Sediments

                                       e Presence  of Lakes

                                       e Desorptlon From Bedded Sediments
                                                                      Determine Concentrations of
                                                                     Metals Over Time and Distance
                                                                           (Section 4.10.3)
                                                                      Are As.  Cd. Cr, Co,  Hg, N1
                                                                            Pb, Ag, or In
                                                                            Being Analyied
                                                                       Review General Description
                                                                       of Fate (Section 4.10.4.1)
                                                                          Review Appropriate
                                                                         Metal  Fate Discussion
                                                                          (Section 4.1C.4.2)
                                                                       Estimate Metal Speclatlon
                                                                          (Section 4.10.4.3)
                                            Superpose Adsorption Isotherm
                                                 Estimate Levels of
                                                 Most  To»lc Soecies
FIGURE  IV-56     SUMMARY  OF  SCREENING  PROCEDURES  FOR  METALS   IN  RIVERS
                                                     -459-

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                                     TABLE  IV-41
               WATER QUALITY CRITERIA FOR  SELECTED  PRIORITY METALS FOR
                        PROTECTION OF FRESHWATER  AQUATIC  LIFE
                          (1980 and 1985 U.S.  EPA Criteria)
Total Dissolved Metal8
4 day Average Concentration
  Not to Be Exceeded More
 Than Once Every 3 Years'* »c
1 hour Average  Concentration
  Not  to  Be  Exceeded  More
 Than  Once Every  3  Yearsb«c
Arsenic
  (trlvalent Inorganic)
Cadmium
Chromium (hexavalent)
Chromium (trlvalent)
Copper
Lead
Me rcu ry
Nickel

Silver

Z1nc
           190

      0.66, 1.1,  2C
            11
      120,  210,  370C
       6.5, 12,  2ic
      1.3,  3.2,  7.7C
          0.012
      56, 96,  160C
    (30 day average)
            47
    (30 day average)
            360

       1.8,  3.9,  8.6C
             16
      980,  1700,  3100C
        9.2,  18,  34C
        34,  83,  200C
            2.4
      1100,  1800, 3100C
   (Instantaneous maximum)
       1.2,  4.1,  13C
   (Instantaneous maximum)
       180,  320,  570C
   (Instantaneous maximum)
'The total dissolved metal  1s  defined  to  be  "add  soluble".  No approved methods are
 presently available.  The  total  recoverable method  1s  recommended.
bThe water quality criteria (  g/1)  are related  to  water hardness (mg/1 as CaCOj) as:
 Arsenic:  independent of  hardness
 r.Hm-i  ,m .  e*P (0.7852 (In (hardness)) -3.49),  4-day average
 caamium    gxp ( M28 (ln  (hardness)) -3.828),  1-hour  average
 Chromium (VI):  Independent of  hardness
 rh..««< - /TIM .  exP (0.819  (In (hardness)) +  1.56), maximum, 4-day average
 Chromium (nij    Mp (Q>819  (1|) (hardncss)) <.  3.688), 1-hour average
 r  «... .  exP (0.8548 (In  (hardness)) -1.465),  4-day average
 Lopper    exp (0.9422 (In  (hardness)) -1.464),  1-hour  average
 ,   H m  exp (1.266 (In (hardness)) -4.661), 4-day average
  ™     exp (1.266 (In (hardness)) -1.416), 1-hour  average
 Mercury:  Independent of  hardness
 Nirk»i «  exP (O-76 0° (hardness)) +1.06), 30-day  average
   c       exp (0.76 (In (hardness)) +4.02), maximum at any time
 Silver * exp (1.72 (In (hardness)) -6.52),  maximum  at  any time
 Z1nc » exp (0.83 (In (hardness)) +1.95), maximum  at any time
cThe three water quality criteria are  examples  for total hardness levels of 50, 100,
 and 200 mg/1 as CaCOa.
                                        -460-

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4.10.2.2   Background  Levels of Metals

4.10.2.2.1  Introduction
     In contrast to most organic toxicants which are not initially present In the
environment, metals occur naturally and cycle by blogeochemical processes throughout
the environment.  Consequently, of the metals that may be present In a stream or
river, a small fraction, a moderate fraction, or nearly all might be from natural
sources.
     When  trace metal concentrations in streams are analyzed to see whether water
quality standards are violated, and whether wasteload allocation schemes are required,
a knowledge of background sources should be included as a part of the analysis.
Background sources can be defined to include both natural sources and sources produced
by man which are transported across watershed boundaries (e.g. dry deposition of
metal-enriched ash). Background sources can also be thought of as sources which are
not readily controllable, and thus contributions from these sources are likely to be
present regardless of the remedial action chosen.
     In this section, coverage of background sources is limited to weathering from
rocks and  riparian soils.  Typical values of metal concentrations are provided.
However, metals are not uniformly distributed throughout the environment but can be
locally enrlchea in natural deposits. Should a river intersect a mineral deposit, the
levels of metals in the stream from this source can be high.  Contributions of
background sources can be quantified by sampling upstream of the locations of major
anthropogenic Influence.
4.10.2.2.2  Stream Contributions From Rocks and Soils
     Tables IV-42 and IV-43 summarize data which show typical  concentrations of
metals  and Inorganics in soils and rocks.  The soil  samples from New Jersey and New
York in Table IV-42 are generally similar to average concentrations in the earth's
crust.   However, deviations can occur locally, so these numbers should be used with
caution.  Soil Conservation Service soil surveys might provide data on levels of
metals  1n local  soils. Chapter 3 also provides additional data.
     Concentrations of metals 1n streams from the background sources can be estimated
from the following formula:
                               Cb » X-S-10'3                                (IV-155)
where
     X  •  metals concentration in soils, M-g/g
     S  •  background Instream suspended solids concentration, mg/1
     £.  «  total, metal concentration 1n the stream due to the soil  and rock particles
      b
           in suspension and may include a dissolved component,  ng/1.
As an example, suppose a stream has a background suspended solids level  of 40 mg/1.
Based on a typical  :inc concentration of 80 *g/g in soils,

                                         -461-

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                                     TABLE IV-42
                  TYPICAL CONCENTRATIONS OF JCTALS IN SEVERAL SOILS
                              AND  IN THE EARTH'S CRUST
                                   (Values 1n jig/g)
Metal
Ag
As
Cd
Cr
Cu
Hg
N1
Pb
Zn
Soils In
New Jersey*
—
—
--
9.3
40.5
--
11.9
86.8
96.3
Soils 1n Upstate
New York6
—
—
0.2
—
21.6
—
--
7.9
79.9
Average 1n
Earth's Crustc
0.5
5.0
0.15
10. -100.
4. -55.
0.005. -1.0
80.
15.
50.
         "Kubota et aK (1974).
         ^Hber and Hunter (1979).
         °Weast (1977).
        Cb • 40-80-10"3 « 3 ng/1 of zinc
This 1s less than 10 percent of the U.S. EPA criteria level of 47 ng/1  (Table IV-41),
However, for some of the other metals (e.g. copper), typical contributions from
background sources can approach the 30-day criteria.
     For a number of the metals (Cr, Cu, N1 , Pb, and Zn), background levels of about
1 ng/'l  are common.  For Ag, Cd, and Hg, background levels are probably  closer to 0.1
    ,  or even less.
4.10.2.3  Case Studies of Metals In Rivers
4.10.2.3.1  Introduction
     This section provides a sampling of case studies of metals 1n rivers.   Case
studies help to reveal  Important master variables which control the fate of metals
                                         -462-

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                               TABLE IV-43

         AVERAGE CONCENTRATION OF METALS IN VARIOUS TYPES OF ROCK
                         AND DEEP OCEAN SEDIMENTS
                             (Values in jig/g)
Plutonic
Granitic

Chromium
Manganese
Iron
Cobalt
Nickel
Copper
Zinc

Chromium
Manganese
Iron
Cobalt
Nickel
Copper
Zinc
Ultramafic
1.6 xlO3
1.62xl03
9.4xl04
150
Z.OxlO3
10
50

Shale
90
950
4.72xl04
19
68
45
95
Basaltic
170
1.5 xlO3
8.65xl04
48
130
87
105
Sedimentary Rock
Sandstone
35
100
9.8xl03
0.3
2.0
1
16
Plagioclase
22
540
2.64xl04
7
15
30
60

Carbonate
11
l.lxlO3
3.8xl03
0.1
20
4
20
Orthoclase
4.1
370
1.42xl04
1.0
4.5
10
39
Deep Ocean
Carbonate
11
l.OxlO3
9.0xl03
7
30
30
35
Syenite
30
850
3.67x10*
1
4
5
132
Sediments
Clay
90
6.7xl03
6.5xl04
74
225
250
165
From:  Rubin, 1976.
                                  -463-

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Since there are potentially many processes which Influence the behavior of metals  In
aquatic systems (see Section 4.10.4.1), elimination of processes  of secondary  Im-
portance Is beneficial  In screening analyses.
     Some of the questions which users are likely to pose during  a  fate analysis
are:
        •    Is downstream transport of metals Important?  That 1s, do metals  move
             downstream 1n the water column significant distances below their  points
             of entry or are they rapidly deposited and/or adsorbed 1n the bedded
             sediments  so that water column concentrations are rapidly depleted?
        •    Are the metals In the water column present In adsorbed or dissolved
             form?  Dissolved species are likely to be more toxic and can be trans-
             ported further than the particulate form of the metal.
        •    What Is the relationship between water column concentrations and  con-
             centrations In the bedded sediments?  Metal concentrations In bedded
             sediments  are often found to far exceed those 1n the water column.
        •    What metals are typically present 1n rivers 1n the highest concentrations?
        •    What is the effect of a reservoir (or large backwater  region) on  the
             metal concentrations further downstream?
        •    Is metal desorption from bottom sediments likely to occur as a result of
             decreased  water column concentrations?  Desorption Is a natural cleansing
             mechanism, but may also take a significant period of time (e.g. 1 to  5
             years for several stream miles).  During the period of desorption,  a
             low level  of metal is maintained in the water column.
     A review of case studies often provides insights Into resolving these questions,
and others which arise during the course of a study.  Methods to address each of
these questions are presented in Section 4.10.3, and general qualitative answers to
these questions are provided  i-i Section 4.10.3.3.
     Before discussing Individual case studies, the U.S. Geological Survey's NASQAN
network is briefly mentioned.  Through the USGS's National Stream Quality Accounting
Network (NASQAN), water quality samples are collected at approximately 345 stations
throughout the  United States  (3r1ggs and Ficke, 1977).  Among the quality parameters
measured are arsenic, cadmium, chromium, copper, lead, mercury, selenium, and zinc.
The data contained in Briggs  and Ficke  (1977) are summarized in Tables IV-44 and
IV-45.
     Note that  the upper  limits of  the measured concentrations for cadmium, ::irani urn,
copper, lead, and zinc are, at times, close to U.S. EPA criteria for  Instantaneous
maximum levels  (see Table  IV-41).   The upper levels measured for mercury occasionally
exceed the suggested criteria of 4.1 ng/1  (instantaneous maximum).  These results
suggest that cadrrium, chromlun, copper, lead, zinc, and mercury often  require careful
investigation on  a 3ite-by-site basis.
                                         -464-

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                                                     TABLE  1V-44

     RANGES OF CONCENTRATIONS  OF DISSOLVED MINOR  ELEMENTS MEASURED AT NASQAN  STATIONS DURING THE  1975 WATER YEAR,
                           SUMMARIZED BY WATER RESOURCES  REGIONS  (Briggs  and  Ficke,  1977)a
Range of Concentrations (/
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                                                        TABLE  1V-45

        HANWS OF  T01AL  CONCFNTRAT10NS OF  MINOR FLEMENTS MEASURED AT NASQAN STATIONS DURING THE  1975  WATER  YEAR,
                            SUMMARIZED BY  WATER RESOURCES REGIONS (Briygs  and  Ficke, 1977)a
Range of Concentrations (fg/1)
Region
Nunber and N.une
01 New England
02 Mid-Atlantic
03 South Atlantic-Gulf
04 Great Lakes
OS Ohio
06 Tennessee
07 Upper Mississippi
08 Lower Mississippi
09 Souris-Red-Rainy
10 Missouri Basin
11 Arkansas-White-Re
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4.10.2.3.2  Case Studies
     The following case studies illustrate a range of metal  concentrations  which  are
present in rivers and streams in the United States.  The case studies  are summarized
in Table IV-46.  A number of different source types are represented.

4.10.2.3.2.1  Flint River. Michigan
     The Flint River study in Michigan (Delos et _al., 1983)  provides  a detailed
account of the fate of zinc, cadmium, and copper in the river. Results of the study
are used in Section 4.10.3 to compare against predictions made by the  analytical
screening procedures in this document.
     During the Flint River study, zinc, cadmium,  and copper were analyzed  in a  60 km
(37 mile) stretcn of the river.  Data were collected in August 1981,  December 1981,
and March 1982.  The watershed is both agricultural and urban.  Two wastewater
treatment plants provide the main sources of metals within the study  reach  (in
addition to the flux of metal across the upstream boundary).
     Table IV-47 summarizes the reported average metal  concentrations  and average
suspended solids levels.  The metal  concentrations shown in  the table  are the range
of averages at the locations sampled (typically 5  to 9 stations in  the 60 km  reach).
Zinc and cadmium levels are generally below the criteria levels of  47  ng/1  and 2.0
Kg/1, respectively, and copper is near its criterion level.
     In most cases, the levels of metals in the water column do not decrease  substanti-
ally with distance downstream.  Figure IV-57 illustrates the total  and dissolved
copper levels during the August 1981 survey.  Wastewater discharges are present  at km
41 and km 71.  Only minor sources are present between these  locations.

4.10.2.3.2.2  Chattanooga Creek, Tennessee
     Chattanooga Creek is tributary to tne Tennessee River and is 42  km (20 miles) in
length.  The basin is significantly industrialized and contains 13 permitted  indus-
trial sources, as well as agricultural and domestic discharges.  Past  studies indi-
cate that the creek is degraded by both conventional ana toxic pollutants.   The
September 1980 study of Milligan et_ a_l_. (1981) report tnat the creek  is contaminated
with organic and inorganic toxicants.  Their findings related to metals are summarized
here.
     Figure IV-58 shows the 12 sampling locations  selected in tne lower 15 km of the
creek.  The priority metals detected in the water column and in the sediments are
summarized in Table IV-48.  The metal concentrations are generally indicative of
contaminated conditions.  Mercury levels in the water column (0.3 to  0.9 ug/1) are
above the 1984 U.S. EPA criteria for the protection of aquatic life (0.2 ^g/1 for
chronic toxicity).  Chromium and zinc levels are near their criteria  limits.   Levels
in the water column appear to be fairly constant ove<- distance.  As noted b>  M-ni

                                         -467-

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      Table IV-46
SUMMARY OF CASE STUDIES
Location
Flint River, MI
Chattanooga Creek, TN
North Fork Holston
River, VA
Slate River, CO
Saddle River. NJ
Cayuga Watershed, NY
*
Acute criteria exceeded.
Source of Metal
wastewater
Industrial
chloralkall
plant
mine drainage
urban
rural
Metals
Zn, Cd, Cu
Cr, Hg, Zn, As,
tig
As, Cd, Cr, Cu,
Pb, N1, Ag, Zn
Pb, Zn, Cu, Ml.
Pb, Cd, Zn, Cu
Concentrations EPA Chronic Downstream
Measured In Criteria Transport
Water? Bed? Exceeded? Important?
Yes No No Yes
Yes Yes Hg, Zn Yes
Yes Yes Hg Yes
Yes* No As,* Cd,* Cu* Yes
No Yes -- not documented
Yes No No not documented
           -463-

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                                 TABLE  IV-47



SUMMARY OF METAL AND SUSPENDED SOLIDS CONCENTRATIONS  IN  FLINT  RIVER,  MICHIGAN
Suspended
Study Period Solids (Bg/l)
August 1981
December 1981
(Run 1)
December 1981
(Run 2)
Harch 1982
4.
a.
6.
16.
-13.
-15.
-22.
-24.

Zinc (Mg/l)
Total Particulate
8
5
6
7
.-24. 6. -20.
.-14. 2. -11.
.-30. 2. -22.
.-17. 4. -8.
Cad*lui (pg/1)
Dissolved
4. -12.
4. -14.
2. -8.
4. -6.
Total
0.05-0.16
0.05-0.15
0.02-0.13
0.02-0.06
Parttculate
0.04-0.1
0.02-0.08
0.01-0.08
0.01-0.02
Dissolved
0.02-0.12
0.00-0.15
0.00-0.08
0.00-0.02
Copper (jig/1)
Total
2.5-8.
2. -5.
2. -15.
2.2-5.2
Particulate
1.-4.
1.-2.
1.-7.
0.5-1.5
Dissolved
2. -4.
2. -4.
1.-3.
2. -2. 5
                                       -•I'D?-

-------
                                                 KEY
w -
1 8 "
ec*
«::
0 -
i
10 -
1 8 -
f
DISSOLVED COR
0 M * «
l 1 l 1
_ MEAN. PLUS OR MINUS
4 ONE STANDARD
1 DEVIATION

FLOW DIRECTION
II ^i
H it,
1 1 i { ' }
) 5 15 25 35 45 55 65 75
RIVER KILOMETERS
(»)TOTAL COPPER. /ig/l
FLOW DIRECTION
TT I IT "IT
M I I t f I J i
II 1}
                         15      25      35      45
                                   RIVER KILOMETERS
                              (b)DISSOLVED COPPER, pg/l
55
65
75
  FIGURE IV-57    MEASURED TOTAL AND DISSOLVED COPPER CONCENTRATIONS
                   IN  FLINT RIVER. MICHIGAN,  DURING AUGUST 1981  SURVEY,


et_ aK (1981), the levels of metals 1n the sediments  are from 2 to 50 times  nigner
than levels measured In the Tennessee River sediments, irfHch suggest that  tre source
of metal  contamination In Chattanooga Creek 1s local.

4.10.2.3.2.3   North Fork Holston  River. Virginia
     Wastes from an inactive chloralkall plant closed in 1972 and located  on the
North Fork Holston River continue to contaminate both the  water column and bottom
                                       -470-

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                                                      M-t
                                -8S-1
                                                  NUMBER OF
                                                  POIXUMNT3 OCTfCTEO N \MKTCR
                                                        30-4
                                                  SS» - SAMPUNC STO
                                                  8CAU
                                                  0
 FIGURE  IV-5S
EXTENT OP  PRIORITY POLLUTANT CONTAMINATION  IN CHATTANOOGA
CREEK WATERS.
seainents of the river (Turner  and  Lindberg,  1978).  The river is a fast-flowing
mountain stream with a coarse,  rocky  substrate in rrany areas, but with silt ano clay
substrates in backwater regions.
     Two large settling ponds at the  plant site drain into the river and provide  the
source of contamination.  Upstream  of tne ponds the levels of mercury are low.   Below
the plant, tne levels increase  significantly, as shown in Table IV-49.  upstream  of
the plant, the mercury in the water column averages O.C08Mg/l, while downstream, the
average is 0.15 ng/1, a 20-fold Increase.  Approximately a third of the mercury below
the discharge 1s 1n dissolved form.
     Plots of total  mercury  in  the  water column versus distance below the waste
discharge were developed by  Turner  and Lindberg for low and high flow rates.  They
are shewn in Figure IV-59.   They plotted predicted levels of mercury versus distance,
assuming that the mercury behaves conservatively 1n the water column.  At high  flow,
the mercury appears  to be conservative while  at low flow rates, seme loss of mercury
                                        -471-

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                                 TABLE IV-48



INORGANIC PRIORITY POLLUTANTS DETECTED IN CHATTANOOGA CREEK, SEPTEMBER  1980
Station Number and Chattanooga Creek Mile
1
dMpouftd 9.1
ChrootuB. total
Mercury, total 0.3
Zinc, total 19.
2
6.6
0.3
31.
3
Pond
(6.3)
0.3
29.
4
5.2
142.
0.3
22.
5 6
UruiMMd
Tributary
(4.5) (4.5)
Water Colum
0.8 0.9
55. 140.
7A
(4.15)
Sables (i
0.5
24.
78
(4.15)
>g/l)
0.4
23.
8 9
Dobbs
Brook
(2.2) 2.1
0.9 0.9
52. 30.
10
0.6
0.4
38.
11
UnnaMd
Tributary
(0.3)
0.5
40.
12
0.1
0.3
43.
                                   Sediment Simple* (iig/g)
Arsenic, total
leryllliM. total
CtdaluB. total
ChroBtuB. total
Copper, total
Lead, total
Mercury, total
Nickel, total
SelenluM. total
Stiver, total
Zinc, total
0.2
0.295
..
21.
2.4
7.04
0.85
10.3
-
-
25.
4.1
0.56
.
20.
8.6
26.
0.98
23.
-
-
45.
3.0
0.48
.
33.
6.7
21.
0.49
12.
-
-
29.
13
0.5
1.7
98.
140.
66.
240.
18.
-
1.0
230.
13.0
0.6
1.7
110.
27.4
37.
64.4
7.0
-
0.6
83.0
8.5
0.7
-
76.
11.7
38.
3.5
11.0
2.5
-
62.
2.0
0.7
-
24.0
7.4
10.
0.01
10.
-
-
37.
2.4
0.7
-
37.
8.2
16.
0.9
11.
-
-
46.
2.
0.5
1.2
35.
32.9
232.
1.8
16.
-
0.6
234.
4.
0.5
0.4
59.
28.6
106.
2.3
21.
-
0.4
154.
1.7
0.3
1.9
25.0
33.0
140.
0.24
13.0
-
1.7
380.
1.2
0.4
4.0
12.0
48.0
250.
1.8
20.1
-
1.6
1.100.
1.2
0.8
2.4
26.0
33.0
150.
0.88
14.5
.
1.7
340.
                                         -472-

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                                       TABLE IV-49
          MERCURY CONCENTRATIONS IN WATER. SUSPENDED HATTER,  AND BED SEDIMENTS
             IMMEDIATELY UPSTREAM AND DOWNSTREAM OF FORMER CHLORALKALI  PLANT
                               ON NORTH FORK HOLSTON RIVER
         Statistic
                            Water Column
Total Ha    Dissolved Hq
  Suspended        Bottom
Particulate Hg   Sediment Hga
    Utg/g)

Mean
Standard Deviation
Number Samples

Mean
Standard Deviation
Number Samples
*S1lt-clay fraction

0.008
0.004
10.

0.15
0.05
11.
only.

0.001
—
9.

0.05
0.02
11.

Upstream
0.41
0.17
7.
Downstream
7.6
3.8
10.


0.13
0.03
7.

19.3
1.2
3.

from the water column 1s evident.  In both cases, however, mercury Is transported far
downstream (120 km) 1n significant concentrations.
     Further down the river, at km 155 (not shown 1n the figure), 1s a large Impound-
ment - Cherokee Lake.  Much of the suspended sediments settle In this lake and take
the adsorbed mercury with tnem.  Mercury In the surflclal sediments ranges from about
0.47 ng/g to 2.4 »$/g.  These levels are expected based on the levels of mercury
found In the suspended matter 1n the North Fork Holston River (Table IV-49).

4.10.2.3.2.4  Slate River. Colorado

     Slate River, Colorado, 1s one of a number of rivers and creeks (see Table IV-50)
Investigated 1n a cooperative effort by U.S. EPA's Environmental Monitoring Systems
Laboratory, Las Vegas, Nevada.  The purpose of the Investigations was to study
degradation and recovery of biological communities 1n streams where the toxic metal
concentrations exceed the U.S. EPA's 1930 recommended acute criteria for aquatic
life.  The Slate River study Is summarized here as an example (Janlk et. al_., 1982).
     Figure IV-60 shows the station locations on the Slate River and Its tributary.
Coal Creek, where drainage from the Keystone Mine enters the creek.  Locations
                                         -473-

-------
 ^006-
   0.02-

                                              OJ6-

                                              aw-j
                                              aw H
                                              0.02-
       -20     20      60     100
                RIVER KILOMETERS
                 (•)HIGH FLOW
                    140
     1   i    '    \    •   r
-20     20      60     100
         RIVER  KILOMETERS
           (b) LOW FLOW
                                                               140
     REFERENCE;
FIGURE IV-59
 TURNER AND LINDBERG, 1978.
COMPARISON  OF OBSERVED  AND PREDICTED MERCURY CONCENTRATION
CALCULATED  FROM A  DILUTION MODEL FOR THE MORTH FORK
HOLSTON RIVER,
sampled on  the Slate River Include a control station (034), two  stations 1n the
Impact zone downstream of Coal Creek (035, 036) and two stations 1n the recovery zone
(037, 038).
     Table  IV-51 shows average concentrations at each station and the water quality
criteria.   The criteria are exceeded for arsenic, cadmium, copper, silver, and zinc.
There 1s generally some decrease 1n the level of total metals from the Impact zone to
the recovery zone, although statistical  tests reported by Janlk. et_ aj_., Indicate
that analytical variation or field replicate variation may be an Important reason for
the difference.  Even so, water quality criteria are exceeded In the recovery zone as
well as 1n  the Impact zone.
     Janlk  et_ aj_.  (1962) also Indicate that a large percentage (generally 75 to 100
percent) of the metals are transported In the dissolved fraction. While suspended
solid levels are not reported, these results do. In a general sense, appear to be
contradictory to the findings of other Investigations.
                                        -474.

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                                     TABLE IV-50

              STREAMS  SELECTED FOR I960 U.S. EPA FIELD SURVEYS AND METALS
              ANTICIPATED TO BE PRESENT IN EXCESS OF U.S. EPA RECOMMENDED
                                AQUATIC LIFE CRITERIA
         Major Pollution Source

         	Stream
           Metal(s)
         Prickly Pear Creek, Montana
         Silver Bow Creek, Montana
         Slate River,  Colorado
         Tar  Creek,  Oklahoma
         Red  River,  New Mexico
Copper, Z1nc, Cadmium
Copper, Cadmium, Zinc
Copper, Z1nc, Silver, Cadmium
Zinc, Cadmium, Silver, Lead
Copper, Cadmium
         Industrial

         Leon Creek,  Texas
         Little  M1$s1ss1newa River,  Indiana
Chromium, Nickel
Lead, Chromium
         Pub!1c-0wned Treatment  works(POTW)

         Bird  Creek,  Oklahoma
         Cedar Creek, Georgia
         Maple Creek, South  Carolina
         Irwln Creek, North  Carolina
         Blackstone River, Massachusetts
         Mill  River,  Ohio
         Cayadutta  Creek, New  York
         White River, Indiana
         References:   Janlk  et j»K  (1982).
Arsenic, Selenium
Chromium, Silver
Chromium
Chromium, Zinc, Nickel, Lead
Cadmium, Lead
Nickel
Chromium, Cadmium
Copper
4.10.2.3.2.5  Saddle River. New Jersey

     The Saddle River near Lodi, New Jersey was Investigated to determine the Impact

of urbanization on the levels of heavy metals 1n the bottom sediments of the river
(Wllber and Hunter, 1979).  The study area encompasses a distance of about 13 (cm (8

ml).  The lower 8 km (5 ml) are dominated by nonpoint sources of runoff from the city

of Lod1.  Industries and municipalities do not discharge directly into this section

of the river. Further upstream, however, two wastewater treatment plants discharge
their effluent.

     The average heavy metal concentrations In the sediments of the river are srown
In Table IV-52.  Ninety-six sediment samples from 18 cores were taken.  The priority

metals analyzed are lead, zinc, copper, nickel, chromium, and cadmium.  The tabula-

tions Indicate a general enrichment of each of the priority metals in the lower
                                         -.175-

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                        KHJOMfTEM
              REFERENCE:  JANIK ET AL.< 1982
FIGURE  IV-60    STATION LOCATIONS ON  COAL  CREEK  AND SLATE  RIVER, COLORADO,
urbanized Saddle River.  Average enrichment  factors  (concentrations 1n the lower
river divided by concentrations 1n the upper river)  are  6.7 for  Pb, 3.5 for Zn, 3.1
for copper. 2.8 for nickel, 5.1 for chromium, and  5.2  for  cadmium.  The results
appear to Indicate that the urban nonpolnt sources have  Increased concentrations  of
metals 1n the river's sediments.
     The heavy metal concentrations were subdivided  by bedded sediment particle size.
The results are shown 1n Table IV-53 for sizes ranging from coarse sand to clay.
Generally the concentrations Increase with decreasing  particle size.  However, on a
total mass basis, most of the metals are associated  with the larger particles because
the silt-clay fraction comprises only 1 percent of the solids by weight.

4.10.2.3.2.6  Cavuga Lake Basin. New York
     The water of 12 streams tributary to Cayuga Lake, New York  were sampled for
the priority metals lead, cadmium, zinc, and copper  (Kubota et_a_1_., 1974).  A number
of the streams flow predominantly through rural countryside and  others flow through
the City of Ithaca.  Sample collection focused on  periods  of high and low streamflow
from March through August 1970.
                                         -476-

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                                TABLE  IV-51

     COMPARISON OF MEAN TOTAL CONCENTRATIONS  OF  SELECTED METALS  (pg/1)
     IN THE SLATE RIVER VERSUS  U.S. EPA  CALCULATED^CUTE WATER QUALITY
                         CRITERIA FOR  AQUATIC LIFE
Stations
Control
034
Hardness (mg/1) 55.
Total Arsenic (Detection Limit
Actual (X) 658.9
1980 Criterion 440.
Total Cadmium (Detection Limit
Actual (X) ND*
1980 Criterion 2.
Total Chromium (Detection Limit
Actual (X) 9.2
1980 Criterion** 21.
Total Copper (Detection Limit •
Actual (X) 11.0
1980 Criterion 13.
Impact
035
61.
« 110.0)
1069.7
440.
« 7.5)
13.2
2.
• 5.0)
9.8
21.
11.0)
38.8
14.
Total Lead (Detection Limit • 120.0)
Actual (X) ND ND
1980 Criterion 83.
Total- Nickel (Detection Limit *
Actual (X) 46.5
1980 Criterion 1174.
Total Silver (Detection Limit «
Actual (X) 12.4
1980 Criterion 1.
Total Z1nc (Detection L1*1t • 9
Actual (X) 55.8
1980 Criterion 196.
95.
9.0)
95.4
1270.
12.0)
17.7
2.
.0)
1068.3
214.
036
68.

936. S
440.

10.2
2.

7.7
21.

24.0
15.
ND
107.

72.9
1374.

ND
2.

1005.2
233.
Recovery
037 038
71.

776.6
440.

8.1
2.

7.6
21.

16.6
16.
ND
113.

43.8
1418.

ND
2.

744.5
241.
75.

617.6
440.

9.6
2.

12.4
21.

15.6
17.
ND
122.

45.2
1465.

NO
2.

430.4
254.
 ND » Nondetectable.
**
  Criteria are for hexavalent chromium.
                                    4 ^7
                                   --»/ 7-

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                                     TABLE IV-52
              METAL CONCENTRATIONS IN BOTTOM SEDIMENTS OF SADDLE RIVER,
                          NEU JERSEY. AND IN ADJACENT SOILS
Metal Concentration (pg/g)
River
Mile
Pb
Zn
Cu
N1
Upper
16.6
8.2
38.6
12.6
84.2
66.4
28.9 6
20.5 6
.5
.4

Cr
Cd
Mn
Fe
Saddle River
6
3
.5
.6
0.4
0.4
197.4
111.0
8439
5956
Lower Saddle River
5.6
1.3
0.5
163.5
152.4
200.0
247.6
275.1
269.8
60.3 17
61.5 15
104.8 22
.5
.2
.3
24
17
34
.6
.8
.9
1.7
1.6
2.9
200.2
185.2
164.0
12872
11092
14565
   N/A
86.8
96.3
    Adjacent Soils 1n Watershed
40.5    11.9     9.3     not Measured    145.0   12300
  Data of Hllber and Hunter (1979).
     Table IV-54 suMMarlzes the levels of dissolved and participate lead 1n the Mater
coluwi.  The concentrations of soluble lead 1n the rural streams do not differ
appreciably fro* concentrations 1n the stream flowing through urbanized areas.
Participate and dissolved levels of cadxiuM, zinc, and copper also do not reflect an
Impact fro« urbanization (Tables IV-55 and IV-56). The observed levels of trace
elemnts 1n these streams appear to reflect predominantly natural background sources.
4.10.2.3.2.7  Additional Studies
     Numerous other studies of Metals in rivers can be found throughout the litera-
ture.  Of the various priority Metals, Mercury appears to be the most widely studied.
So** of the regaining literature on Metals 1n rivers 1s briefly suMMarized here.
     Mercury distribution 1n the Ottawa River, Canada, has been studied and  reported
by a nuMber of researchers, Including Ranaraoorthy and Rust, 1976;  Kudo «t.al_.,  1977;
                                         -478-

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                                      TABLE IV-53
                  AVERAGE HEAVY METAL CONCENTRATIONS BY PARTICLE SIZE
                     FOR SEDIMENTS X>F THE SADDLE RIVER, NEW JERSEY
                                         (ug/g)
Particle Size (M)
420-1000
(coarse sand)


250-420
(medium sand)


125-250
(fine sand)


63-125
(very fine sand)


5.8-63
(siU)


0.15-5.8
(fine to coarse clay)


0.01-0.15
(very fine clay)


NO * Noruletectibi*
River Mile
16.6
8.2
5.6
0.5
16.6
8.2
5.6
0.5
16.6
8.2
5.6
0.5
16.6
8.2
5.6
0.5
16.6
8.2
5.6
0.5
16.6
8.2
5.6
0.5
16.6
8.2
5.6
0.5

Pb
15
9
310
482
23
13
16
90
45
18
11
91
126
349
113
173
360
1127
259
582
860
3073
816
1940
1894
13372
1476
2747

Zn
22
42
388
413
30
28
63
119
48
34
35
135
125
440
155
251
420
3298
389
661
917
3365
1320
2348
2159
21279
4715
4680

Cu
11
7
206
252
11
8
10
44
14
12
6
29
81
3180
31
44
735
1222
151
258
1017
12221
417
1042
2272
84302
1145
1364

N1
4
4
20
28
4
4
6
12
4
5
4
11
14
169
11
21
60
202
23
46
72
559
99
189
ND
2907
488
444

Cr
5
3
29
46
5
3
S
15
6
5
4
12
18
34
15
27
41
127
33
143
201
321
126
563
530
1337
610
852

Cd
ND*
0.2
2.0
4.0
ND
0.3
0.5
1.0
0.1
0.5
0.3
0.9
1.4
3.4
1.3
1.3
5.2
14.5
7.9
6.9
7.2
27.9
30.6
26.9
37.9
290.7
120.0
34.0

Kudo e_t_a]_., 197^; and In tne Proceedings of the International Conference on  Transport
of Persistent Chemicals In Aquatic Ecosystems, 1974.  Much of the research an mercury
In rivers deals wlcn adsorption and desorptlon between the bedded sediments and  the
water column.
     Jenne (1972) summarizes concentrations of mercury in rivers throughout the
United States. •Tne U.S. Geological Survey provides a collation of papers on

                                         -479-

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                                     TABLE IV-54
          LEAD CONCENTRATIONS IN STREAMS TRIBUTARY TO CAYUGA LAKE, NEW YORK



Sample Source
Primarily rural
Canoga
Great Gully
Little Creek
Sheldrake
Taughannock
Salmon
Inlet
Buttermilk
Urbanized
Trunansburgc
Six Mile
Cascadllla
Fall Creek
Soluble
No. Samples
With
Detectable
Amounts

4/8
6/8
4/7
5/8
5/8
5/9
8/9
3/8

4/8
6/9
5/9
7/9
M9/1


Meanb

1.17
0.62
0.57
0.42
0.74
2.99
0.66
0.40

1.11
0.73
0.50
0.93



Maximum

2.67
1.33
1.00
0.67
1.00
16.1
1.33
0.67

1.67
1.33
1.00
2.67
Participate
No. Samples
With
Detectable
Amounts

5/8
8/8
6/7
7/8
8/8
8/9
8/9
6/8

7/8
8/9
9/9
7/9
Fraction,


Mean

1.37
1.38
0.66
1.39
1.57
0.91
1.89
1.45

3.94
3.14
3.88
2.91
W/l


Maximum

2.06
6.17
1.85
2.62
4.01
2.62
6.17
3.09

7.41
8.23
6.99
8.33
 Source:  Kubota et aU, 1974.
 'Samples with detectable  amounts/total number of  samples.
  Means  are given for  detectable  amounts.
 cSampl1ng site located below sewage  treatment plant.
mercury (1970) and lead (1976) In the environment.  The U.S. Geological Survey (1970)
also has summarized data on selected trace elements (arsenic, cadmium, hexavalent
chromium, lead, zinc, and mercury) 1n surface waters 1n the United States.
     Finally, the U.S. Environmental Protection Agency has published a series of
documents that review the environmental effects of pollutants. Among the pollutants
reviewed are chromium (Towill et.a]_., 1978), lead (Bell et_ al_.. 1978), and cadmium
(Mammons et.al_., 1978).

4.10.3  Analytical Models for Fate Prediction of Metals 1n Rivers

4.10.3.1  Introduction
     Figure  IV-61 Illustrates a number of Important processes which Influence the
fate of metals 1n rivers.  Consider an example where effluent from the pond  1n the
                                         -480-

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                                      TABLE IV-55
             SUMMARY OF CADMIUM,  ZINC, AND COPPER IN PARTICULATE3 CARRIED
                          BY TRIBUTARY STREAMS OF CAYUGA LAKE
Cadmium, ng/1


Stream
Primarily rural
Canoga
Great Gully
Little Creek
Sheldrake
Taughannock
Salmon
inlet
Buttermilk
Urbanized
Trumansburg
Six Mile
Cascadllla
Fall Creek
No. Samples
With
Detectable
Amounts

5/8
6/8
1/7
7/8
7/8
6/9
4/9
5/8

5/8
4/9
6/9
5/9


Meanb

0.09
0.06
iO.05
0.09
0.11
0.10
0.13
0.10

0.09
0.21
0.10
0.44
Z1nc, j/g/1
No. Samples
With
Detectable
Amounts

8/8
8/8
6/7
8/8
8/8
9/9
8/9
7/8

8/8
8/8
8/8
8/9


Mean

6.40
10.28
2.91
5.48
6.95
3.94
10.71
8.96

9.45
10.05
14.67
14.29
Copper, Acg/1
No. Samples
WltJ)
Detectable
Amount

8/8
8/8
7/7
8/8
8/8
9/9
9/9
8/8

8/8
9/9
9/9
9/9


Mean

1.69
1.35
1.72
1.11
1.46
1.37
3.37
1.64

1.30
5.92
2.43
2.89
Source:   Kubota  et _§]..,  1974.
Samples  with  detectable amounts/total  number  of  samples.
 Means are  given for  detectable  amounts.
cSamp!1ng site located below  sewage  treatment  plant.
figure overflows Into the river.  The main objective of predictive analyses for
metals 1s normally to find their concentration distributions with distance, and
possibly with time (I.e., to find Cj. C2, Cj, and C4 as depicted 1n the figure).
Once metals enter a river, they begin to adsorb to particles suspended 1n the water
column and to particles 1n the river bed.  Eventually, the bed can become contami-
nated with metals at depths below the sediment-water Interface ranging rrom a few
millimeters to many centimeters.  If the flow rate 1n the river were to Increase
enough, the shear force exerted by the moving water on the bed would be sufficient
to scour metal-contaminated solids back Into the water column.  In zones where
velocity 1s significantly diminished, as In a reservoir, the metal-contaminated
sediments can settle out of the water column, and establish a metal-contaminated
                                         .081-

-------
                                      TABLE IV-56
                   SUMMARY OF SOLUBLE CADMIUM, ZINC. AND COPPER IN
                           TRIBUTARY STREAMS OF CAYUGA LAKE
Stream
Cadmium,
No. Samples
with
Detectable
Amounts*
M9/1
Meanb
Zinc,
No. Samples
with
Detectable
Amounts
M9/1
Mean
Copper, i.
No. Samples
with
Detectable
Amounts
ig/1
Mean
 Primarily rural
   Canoga             6/8        0.25
   Great Gully        5/8        0.07
   Little Creek       3/7        0.20
   Sheldrake          6/8        0.10
   Taughannock        4/8        0.28
   Salmon             8/9        0.10
   Inlet              6/9        0.28
   Buttermilk         7/8        1.10

 Urbanized
   Trumansburg        6/8        0.07
   Six H11e           6/9        0.25
   Cascadllla         2/9        0.29
   Fall Creek         7/9        0.17
8/8
8/8
7/7
8/8
8/8
9/9
9/9
8/8
8/8
9/9
9/9
9/9
7.97
1.88
2.24
1.61
1.17
2.27
2.71
0.83
3.20
1.57
1.40
3.51
8/8
8/8
7/7
8/8
8/8
9/9
9/9
8/8
8/8
8/9
9/9
8/9
0.79
0.40
0.32
0.53
0.53
0.51
0.39
0.54
0.77
0.88
1.70
0.75
 Source:  Kubota £t a].., 1974.

 ^Samples with detectable  amounts/total number of samples.

  Means are given for detectable  amounts.

 cSampl1ng site located below sewage treatment plant.
layer on the bottom.  In the thin layer of contaminated sediments along the bottom,
metal concentrations can be hundreds to thousands of times higher on a unit-volume
basis than In water column.
     Tributaries provide dilution water which can rather abruptly decrease metal
concentrations.  Also partitioning between the dissolved and sorted phases can be
shifted If the suspended solid concentrations or other water quality parameters are
altered.

     Suppose that the pond overflow 1n Figure IV-61 Is eliminated after a period of
discharge of many years.  During the period of the discharge the bottom sediment on
the river has probaoly accumulated metals.  Once the metal concentrations 1n the
water column are lowered due to elimination of the pond overflow, the metal in the
bed tends to desorb back Into the water column, a process which may continue (depend-
                                         .482-

-------
FIGURE  IV-61    PHYSICAL PROCESSES INFLUENCING THE FATE OF  METALS IN  RIVERS
Ing on the rate of  desorptlon) for years.  Thus, the recovery period of the  meta)-
contamlnated river  may  take considerably longer than anticipated from the  point
source elimination.
     The tools presented  In this  section can be used to address the cases  described
above and are Hotted to  steady-state analyses, with the exception of the  method
which predicts adsorption and desorptlon of metals on bottom sediments.  The methods
treat metals as pollutants with two phases:  an adsorbed phase and a dissolved phase.
Each approach 1s summarized below.
        •    Dilution Approach.   The change In metal concentration 1n a river 1s
             assumed due  to loading from point and nonpoint sources, and dilution
             with background water.
        e    Dilution Plus Scour  or Deposition of Metal-Contaminated Sediments.
             Exchange of  metal-contaminated sediments between the water column and
             river  bed  can alter  the concentration 1n the water column.
                                        -433-

-------
        •     Influence of Small Lakes.  Small lakes or backwater regions are often
              present on river systems, and potentially could be a sink of adsorbed
             Mtals which settle along with suspended solIds In these quiescent
              reglons.
        e     Desorptlon from (or Adsorption to) Bedded Sediments. Dissolved metal In
             the water column can be adsorbed to bedded sediments If a nonequ111br1um
             condition exists between the bed and the water column.  Similarly,
             desorptlon of part1culate metal from bedded sediments may occur 1f metal
              concentrations are reduced 1n the water column (for example, by waste
              load allocation).
        e     Concentration Factors In Bedded Sediments.  Concentrations of metals 1n
             many bedded sediments are often significantly higher than levels 1n the
             water column.
     While some of the equations presented 1n the following sections may appear
complicated, the equations are no more sophisticated than the more familiar BOD-DO
analyses presented earlier 1n the chapter.  Even the data requirements are generally
less comprehensive than for dissolved oxygen analyses.  However, since the methods
are less familiar, they may require some study before they are fully understood.

4.10.3.2  Dilution Approach
     Using the dilution approach, total metal concentration (partlculate plus dis-
solved) 1s simulated as a conservative pollutant.  The dissolved component Is estimated
from the total concentration using linear partitioning:

                                  C •	^	                              (IV-.156)
                                       1 * KpS-10"6
where
        C   •  dissolved phase metal  concentration,  »g/l
        Cj  »  total metal  concentration,  ng/1
        S   •  suspended solids concentration,  mg/1
        Kp  *  partition coefficient, cm /gm (or I/kg).
Partition coefficients are summarized later In Section 4.10.4.1.
     Under the appropriate conditions the dilution approach appears to be useful  for
predicting metal concentrations throughout a river.   Before the method 1s discussed,
the major assumptions  Inherent In the procedure are  reviewed.  Decay or other loss
processes (e.g.* volatilization) are  not considered.  For metals this Is generally a
good assumption for the range of environmental  conditions likely to be encountered 1n
rivers.  Even though the species distribution can change with distance (1n response
to a pH change, for example), total metal  typically  Is not degraded.  A second
Important assumption made In the dilution approach Is that the metal  1n the water
column does not Interact with the river bed, either  1n the part1!culate form or 1n the

                                         -484-

-------
 dissolved  form.   This situation 1s generally true when:
         •     The  suspended solids In the river remain fairly constant with distance.
              If scour or deposition 1s significant theft a net Influx or loss of
              sol Ids and Mtals may occur.
         e     The  sources of metals to the river are fairly constant over time.  If
              major changes 1n the discharge of metals occur, this can create a
              driving force for adsorption to (or desorptlon from) the bed, which then
              acts as an fnternal source or sink.
 Field data of suspended solids can be reviewed to determine whether significant
 losses or  gains of solids occur within the study reach.  Alternatively, a predictive
 method,  such  as Figure IV-62, can be used.  Based on the mean Mver velocity, the
 figure shows  when deposition, transport, and erosion of solid particles 1s likely to
 occur.   Note  that the velocity when erosion occurs 1s significantly higher than the
 sedimentation velocity, except for particle sizes larger than sand (which are not of
 concern  for metals adsorption).  This means that as the stream velocity first drops
 below the  velocity required to erode a certain size particle, the particle 1s not
 deposited, but continues to be transported unless the velocity further decreases
 below the sedimentation velocity.
     As  the figure shows, sedimentation of clays and small  silts Is not likely to
 occur In free flowing rivers, but can occur 1n relatively small  reservoirs on the
 river with detention times exceeding a few days.  Under such conditions the net
 velocity can  be on the order of 0.1 cm/sec, or less, and the effects of settling of
 parti culates may be Important.
     While sedimentation of clays and small silts 1s not likely  In most free flowing
 rivers,  scour of these same sized particles Is more probable.  Clay 1s likely to be
 scoured  at velocities near 3 fps (100 cm/sec), and silts between 1 and 3 fps (30 to
 100 cm/sec), depending on their size. Consequently, during high  flow conditions when
 the water 1s moving rapidly, bottom scour of silts and clays, and perhaps of sand 1s
 possible.  If the scoured  sediments are contaminated with metals then the total
 metal being transported will Increase over distance (assuming for the moment that
 further  dilution 1s negligible).  Based on Figure IV-62, a fairly large envelope of
 stream velocities exists such that the clay and silt fractions of solids (those which
 adsorb most of the metals) are transported In suspension with the stream water.
     Dilution models are useful for both point and nonpolnt sources.   While dilution
models have been presented elsewhere 1n this document they are summarized here for
ease of  reference.  For point sources, the concentration In a stream following
mixing,  Cyf 1s:


                                      ^u  u *   *  *
                                             *
                                           u    w
                                         -185-

-------
                XXX)
                BOO -
                300 -
                200 -

                WO -
                 50 -
                 30 -
                 20 -
                  10 -
                  5-
                  3 -
                  2 -
                   1 -

                 0.5-
                 0.3-
                 0.2-
                 0.1
           SEDIMENTATION
I  I  I I
  MOM
  c»eio

i	
!5
                                 Note:
                                 30cm/MC
                                                      888 | ggg
                    CLAY    SILT         SAND


                                PARTICLE DIAMETER, mm
 FIGURE  W-62    RELATIONSHIP BETWEEN  STREAM VELOCITY,  PARTICLE SIZE, AND
                  THE  REGIMES  OF SEDIMENT EROSION,  TRANSPORT,  AND
                  DEPOSITION  (FROM GRAF, 1971),
            «  concentration  of total metal  In the river above  the point source,
where
        Qy   -flow rate 1n the river above the point source.  m /$ or cfs

        CJM  »  concentration of total metal 1n the point source, ng/1

        QI,   "flew rate of tne point source,  n /s or cfs.
According to the dilution model, the petal's concentration does not change with

distance downstream unless there are additional Inflows as loadings of metals.

     When CTu 1$ negligible, Equation IV-157a can be rewritten  as:
                                                                           (IV-157b)
wnere
              dilution attained  after mixing.
                                       -486-

-------
      The nonpolnt source representation can be written In one of two forms:
or
                                          * 'Tb                       
-------
j	, — -.,	—EXAMPLE IV-20	'	1
i                                                                                       i
j        Tht Flint Rlvtr study dtscrlbtd tarlltr (Section 4.10.2.3,2.1) provldts an     j
«   opportunity to test tht dilution approach undtr a varltty of hydrologlc conditions. :
[   To Implement tht dilution approach, tht data required art rlvtr and wasttwattr
|   flow rates, and associated metal concentrations.  Tht data used art summarized In   '
I   Table IV-ST.  Two wasttwattr treatment plants art tht largest sources of metals 1n  I
j   tht study reach.  Together with tht upstream contributions from the river, these    j
}   three sources art assumed to comprise tht total metal Input to tht system (the      j
I   minor sources shown In Tablt IV-57 art neglected).                                  j
        Tht Flint Hestewattr Trtatmtnt Plant discharges at km 70.7, which 1$ about 1,2 >
!   km below tht boundary at Mill Street.  After mixing, tht levels of total zinc,
I   cadmium, and copper 1n the river are:
i                                                                                       I
I        Zinc;                                                                           :
I                                                                                       i
!                      x% . 2.66 x 7.7 * 1.68 x SS ,
j                       ^         2.66 * 1.68

!        Cadmium.'

                       . 2.66 x  0.067  + 1.68 x 0.16 .
                                                     0.10
                                 2.66 +  1.68
'                                                                                       *
!      Copper;

                        2.66  r 2.9 » 1.68x8.3 . 5
-------
                                      TABLE  IV-57                                      ,
                   BOUNDARY  CONDITIONS AND  POINT  SOURCES  TO  FLINT RIVER                 j
                                   FOR AUGUST 4-7,  1981                                 j

                                                Discharge Concentration                J
                           Discharge                      Total    Total     Total
           Source            Flow     Suspended Sol Ids    Zinc    Cadmium   Copper     f
                             («3s)     (mg//)  (kg/d)    (ng/t)
!     Upstream Boundary       2.66      13.5   3100.       7.7     0.067      2.9      !
|     M1U Road (km 71.9)                                                              I
*                                                                                      i
I     Flint WWTP              1.68       4.1    600.      55.      0.16       8.3      t
j     (km 70.7)                                                                        j
i     Flint Fly Ash           0.04      39.5    150.      63.      1.32      80.       j
'     Ponds (km 70.0)                                                                  '
I                                                                                      I
;     Brent Run               0.15       5.9     77.       3.8     0.11       3.8      ;
I     (km 41.6)                                                                        {
!     Ragnone WWTP            0.69      58.7   3500.      84.      0.54      28.5      !
|     (km 41.1)                                                                        |
!     P1ne Run                0.06       7.0     33.7      5.0     0.04       3.8      j
      (km 29.7)                                                                        j
;      Silver Creek            0.085      6.8     50.0      5.0     0.04       3.8      j
!      (km 25.2)                                                                        !
I                                                                                       I
|      	                                                                     I
      Modified from:  Delos et ,jl. (1983)                                              j
•                                                                                       •
I                                                                                       I
.                                                                                       >
I        Copper;                                                                        j
i                                                                                       i
I                    c   , 5.0 x 4.34..+.CL69.X.23..5. . 3., ^,                          j
                      T        4.34*0.69
t                                                                                       •
}   Neglecting  the  minor sources  below the  Ragnone  WWTP, the  profiles  of  total           !
I   zinc,  cadmium,  and  copper are  shown in  figure IV-63.  Also  shown 1n the  figure  are   {
j   observed data  (mean and  one  standard deviation)  and  predictions  from  the MICHRIV     I
j   model  as reported by Oelos «t_ al_.  (1983).  M1CHKIV  is  a computer model wnich         j
j   analyzes metals in  greater detail  than  th> screening procedures, and  therefore       I
:   requires more data.
        Tne dilution model  generally  predicts values witnin  25 to 50  percent of
1   the means of tne ooserved va'-jes,  and also within 25 :.> M  percent of the MICHRIV    '

                                         -489-

-------
                                                MfAN4STAMOAM>
                                                MVMTIOM OF OMXA
                           "i«r—;
                           H
                                               Hff>t OMfCTlON
                      ott»
                                     MVffl MLOMCTM*

                                   (hi TOTAL COFMft «*/!
                                                   ttu     it
                  an
                   «M
                  •M
                                              now oMtcnoN
                                     WVfN KUOMfTfM
         FIGURE  IV-63
COMPARISON  OF PREDICTED  AND OBSERVED
TOTAL METAL CONCENTRATIONS IN  FLINT  RIVER,
MICHIGAN  (AUGUST  1981).  (AVERAGE FLOW -
2,66 M3/SEC (94 CFS) AT  KM 71,9)
                                                                                 I
nodtl predictions.  Figure IV-64 shows that the dilution model  also 1s applicable
under other flow  regimes In the Flint River:  December when the flow rate was
about 26.4 m3/sec (930 cfs), and Harch when the flow rate was 93.4 m3/sec (3300cfs),
For both the December and March surveys,  there do not appear to be significant
differences between predictions from  the  dilution model  and from the MICHRIY model.
                                                       I
                                     -490-

-------
n«
O


ni
i
no
o
                i"
                                 MfOMLZMC.OCCCMKIt MM
                                                                                        MTOTAl 21NC. MMCM MM
• •
* •
i * "
' •-
1

	 L , *•
. , t-n
1 • f • 1 • •
I ..
!••
t •
1 4
flOWOWECnON
\ I
* H
1 1 1 1 • • f
                                      MVfM KHOMCIEW
                                  (wrouL copftn. OKXMKH MI
                                                                                        to)1OTAl COfffM. MANCH
       «v
(

1 1
•
1
1

1

now on
i

ECTK3N
. T
1
    --- DILUTION MOOU
    - MICtMVMOOCL
    §  UCAHCCMMMND
    T  MVIMION Of DMA
                                      MVEM MLOMTTim

                                 MITOTAl CAOMMJM.
     MMEM H&OMETBI*

HlTOIAL CAOMUM. MANCN Wt>
                          FIGURE  IV-6^1    TOTAL ZINC,  COPPER, AND CADMIUM IN  THE FLINT  RIVER
                                                                 -491-

-------
     While dilution modeling can produce quite acceptable results under a variety of
conditions, the user should have access to tools which can be used when processes 1n
addition to dilution are Important.  The following section addresses some of these
situations.

4.10.3.3  Settling and Resuspenslon of Adsorbed Metals 1n Rivers
     This section begins with a brief discussion of the recently completed MICHRIV
model (Oelos ej^al_., 1983).  This model's framework Is shown 1n Figure IV-65.  The
most Interesting feature of the model 1s that 1t attempts to handle the exchange of
contaminants between the water column and the bed. Resuspenslon and deposition of
contaminated sediments redistributes adsorbed contaminants to and from the bed.
Also, diffusion can be a driving force for dissolved phase Interaction between the
sediment and water column.  For purposes of Illustration, the MICHRIV model 1s
simplified here, but the essence of the model (exchange of metal between the water
column and bed) 1s retained.
     The model 1s simplified based on these two assumptions:
        e    K , • K.2 » 0; that 1s, there Is no degradation or decay of metals,
                            and
        e    K . « X 2; that 1s, the partition coefficient 1n the bedded sediments
                        and 1n the water column are the si
The first assumption Is quite reasonable since most metals do not decay or otherwise
degrade (an exception Is elemental mercury which can volatilize).
     Regarding the second assumption, there Is reason to suspect that the sol Ids
partition coefficients for suspended and bedded sediments can differ since the
characteristics of solids In the bed can differ from those suspended 1n the water
column.  However, because of the range of uncertainty Inherent 1n partition coeffic-
ient prediction, there 1s no reason to consider differences between K . and K ~ for
these screening analyses.
     Using these two assumptions, the model formulations from Oelos et.al_. (1983) are
simplified as follows.  The simplification procedure 1s shown 1n detail so the user
can clearly see how the two assumptions are used.  The final results of these simpli-
fications are shown later as Equations IV-172 through IV-175, and show how the metal
concentrations  In the water column and bed are related.
     From Oelos «t_al_. tn* relationship between the total concentration of metal 1n
the water column  (CT1) and 1n the bed  (CT2) 1s:
                     fa -- **
                           <"rs + »d> V + Ktfd2 * Kd2 fd2 H2
                                         -492-

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                         LOtDU*,)
            WMItft
           ACTIVf    Hj
           SEDMENT
          FIGURE  IV-65
                                                                 TOANMOHT
                                                                 ASSUMED ZEflO
                   FRAMEWORK FOR  RIVER  MODEL  MICHRIV (REDRAWN
                   FROM DELOS ET  AL,> 1983)
where
*pl* *p2

fdl, fd2
 rs
                     P4rt1culate fraction of metal  1n water column and 1n bed,
                     respectively
                     dissolved fraction of metal  1n water column and 1n bed,
                     respectively
                     settling velocity, w/day
                     resuspenslon velocity, m/day
                     diffusion coefficient, in/day
                     decay rate In sediment, I/day
                     depth of active sediment,  m
                     solids concentration fn water  column and 1n bed. respectively,
From Equation  IV-160:
14£
'dl
                  CT2
dl CT1
        Cfd2  *s  fpl
                                           dl3
dl
                                    KLfd2
                                                    Kd2fd2

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since





        ——• M  • (w
        *2 "$   vwr$





Now
so
or
                                       4	                        (IV-161)
                                      f  .-i!k-                       (IV-162)
                                               *2  p2



«nd
                                   •     1  +
                                   "2    X
                                                   . K   f                  (IV-163)
                                                      PZ  aZ
or



                                            f
      • IL.                       (IV-164)


d2"2
                                          f   -    V
SlMllarly





                                              ' K , f^                       (IV-165)
                                          dl
                                        -494-

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Substituting Equations  1V-164 and IV-166 Into Equation IV-161 produces:
                              Cdl   "s "l Kp2 * *l- * K
-------
                  rl   <"rs +
Using the assumptions made before (K . « K 2 and Kdl •

s1npl1f1es to:
                                                « 0), r/r  « 1. Thus
                         ^.Vp^.ipir    ^   i.
                          Hj     mj Hj    Hj  L $   «!   J
    To summarize, under the simplifications made here, the MICHRIV model equations

become:
                             exp
                                 .ia/.   a,  U
                                  H!  \ $   •!  rs/u
                                                                (IV-172)
                               1 + K
                                   pl-1
                                                                (IV-173)
                               Cd2 * Cdl
                                                               (IV-163b)
 or
 and
                                 d2
                                    . cT1
                                      '*
                                                                (IV-174a)
                                                                (IV-1746)
                                                                (IV-175)
                                                                (IV-176)
                                 -496-

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 where
         Xl»*2  "  MSS of  pollutant  adsorbed  per  mass  of  sediment  In  the water  column
                   and  1n the  bed,  respectively, ng/g
         PS      •  density  of  solids  1n  sediment*  gm/cm (e.g.  for  sand  2.54 gm/cm)
         n       •  porosity of sediment  (volume fraction occupied by Mater).
 The  most notable results obtained  In the above analyses are that the  dissolved  metal
 concentration in the water column  and 1n the  bedded sediments  are  the same (Equation
 IV-169b), and so are the participate metal  concentrations, expressed  per unit weight
 of sediment  (Equation  IV-174t>).  However, on a unit volume basis, the  total metal
concentration  In the sediment  far exceeds the concentration 1n the water column
 (Equation IV-175).
     Typically,  first order decay rates  are positive numbers, which Indicate that
pollutants decrease In concentration with distance.  However, the kj term 1n Equation
 IV-171b can either be positive or negative.   For example, If significant scour of
partlculate metal from the bottom 1s occurring, then KT < 0 and the total metal
concentration can Increase downstream.
     While 1t  Is possible  that metal concentrations can Increase In the water column
due to scour  (e.g., see Figure IV-64 which shows total zinc and copper 1n the Flint
River during March 1982),  at  steady-state cundttlons this should not  happen when the
only source of loading 1s  a single source located at x « 0.  Rather than use Equation
IV-172 to simulate the effects of scour  on water column concentration, one of two
other alternatives has been selected.  One approach 1s to retain the unsteady-state
nature of the transient scour situation.  While this Introduces more complexity, 1t
shows that elevated metal  concentrations In the water column caused by scour are
due to a previous discharge or hydrologic condition when metals had contaminated the
bed,  and not due to the current steady discharge conditions.
     The two unsteady equations relating the  total metal concentrations 1n the bed
and In the water column are (using the previous notation):


              fll . *s fol ^   *rs fp2 ^2   KL fdl CTI   *L f d?
and

                  0C_,    L*  t   r     t*   f  r      v  t   f     Y  t   r
                    ~T 1    W_ ' _,^ **T1   "•• * ' ^«V*T*5    "t  * ^1 ^»T1   *S  ' A*) ^T'i
              +  u —-=•*   5  pi  Tl +  rs  P2"2  _  T.  dl "1 + JL  d2 "2    (JV-178)
                                         -497-

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     While these equations can be solved exactly and used  to predict  the  total  Instream
Mtal concentration due to a scour condition,  they are  not practical  for  screening
analyses.  The primary emphasis here 1s to predict longitudinal  pollutant distribution
when scour 1s Mich nore Important than deposition or diffusion.   The  approach  Is  to
spedfy (rather than calculate) the concentration In the bed and to assume 1t  remains
constant over the period of analysis.  Thus the screening  tools  which are presented  on
the following pages are fundamentally different from the previous MICHRIV equations,
such as Equation IV-172.  Table IV-58 summarizes the screening equations  and defines
the variables used 1n each equation.
                                        H! u
                                                     C_(0)                    dV-179)
where
        C2i     •  concentration of total  metal  1n the bedded  sediments ,ng/l  (a  direct
                   measurement of this value 1s  preferable)
        Cf}(0)  •  concentration of total  metal  In the water column  at an  upstream
                   boundary , ng/1 .
While Equation IV-179 represents steady-state conditions,  1t 1s  valid only as  long  as
the sediments being scoured have a total  metal concentration of  C.j. Once the
contaminated sediments have been scoured,  then the Instream  metal  concentration  1s
expected to return to 0^(0).  The period of validity, T,  of the equation  can  be
approximated by:
                                          H2
                                      T--*-                                  (IV-180)
                                          "rs
where
        Hg   •  depth of contaminated sediment,  m
        wr$  •  resuspenslon velocity, m/day
Typically, Equation IV-179 1s expected to be used during high  flow conditions,
perhaps for a seasonal analysis.  For an application of this type, the period  of
validity of the equation should be on the order  of one to two  months.   Using repre-
sentative data (H? « 5 cm and wr$ • 2 x 10   m/day) for an example,
       T -       ""«   - 250 days.
                 ^
             5 x
           2 x 10~Vday
For tne example conditions, Equation IV-179 1s applicable  for seasonal  analysis.
     When settling of solids Is Insignificant, the resuspenslon  velocity,  w    can !>e
estimated as:
                                        uH, ASS
                                         -498-

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                                                                    TABLE IV-58
                                    SUmARY OF  SCREENING PROCEDURES FOR METALS IN  RIVERS AND LAKES
Caution
                     Use
         Data Requirements
 IV-157*
                                                                        Dilution Analysis
This equation tt used to calculate the
concentration tt total Mtal In • river
•ftor • point source discharge mixes
with river  water.
                                                         CT.

                                                         ^u
         flow rite In river •boy*
         point sourc*
         ftoM rite of point source
         concentration of total
         Mtal In point source
         concentration of total
         Mtal In river above the
         point source
                       faueents
This equation Is anst applicable when exchange of
suspended solids and Mtals with bad Is negligible.
See Figure IV-*7:  HAM wan Mater velocity Is In
•transportation* regime, this condition Is approxt-
•ately true.   Also, the equation can be used as a
first approximation regardless of exchange with bed.
1V-156       Once the  total concentration versus
             distance  Is found from Equation I
             the aaaunt dissolved can be calculate*
             using this equation.
S      • suspended solids concen-
         tration
Kp     • partition coefficient
C.     • totel Mtal concentration
                                                                                    This equation Is used to find total dissolved octal at
                                                                                    locations In a river once total netal concentration
                                                                                    at  these sane locations has been calculated.
                                                       Dilution and Scour of Metal-Contaminated StdVatnts
IV-179       This equation Is used to predict the
             total netal concentration In a rlvar
             when •etal-contanlMted sedtoents are
             resuspended Into the water colon*.
                                            "21
                                                         H,
                                                         u
                                                          rs
       • concentration of total
         Mtal  In bedded sedt-
         Mnts
       « concentration of total
         Mtal  In the water
         column at an upstream
         boundary
       • water  depth
       • strew velocity
       • fraction of Mtal 1n bed
         which  Is In partIcolate
         fora H)
       • resuspenston velocity
         (see Equation IV-181)
The equation does not keep track of  the depth of contam-
inated sedtottnts.  It assuaes this depth Is not exceeded
during the period of scour.  Equation IV-180 can be used
to estlMte the period of validity of the equation.
Figure IV-66 Illustrates the Importance of scour.
                                                                         -499-

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                                                                   TABLE  IV-58  (continued)
Coiiatlon
           Bate *.eoMlre»enti
                        Consents
                                                  Dilution and Scour of Metal-Contaminated Sedlaents (continued)
IV-itt       This equation Is iiMd to calculate the
             teU) o»tal concentration In • rltnw
             when awtal-contoBlMted sedlawjnts are
             resuspendod Into tin water colum.
             Tbtt tt M alternate for* of Equation
             IV-17t.  See COM«OtS.
AS