WATER POLLUTION CONTROL RESEARCH SERIES • 11134 FKL 17/71
Storm Water Pollution
from
Urban Land Activity
U.S. DEPARTMENT OF THE INTERIOR • FEDERAL WATER QUALITY ADMINISTRATION
-------
WATER POLLUTION CONTROL RESEARCH SERIES
The Water Pollution Control Research Reports describe the results and progress
in the control and abatement of pollution of our Nation's Waters. They provide
a central source of information on the research, development and demonstration
activities of the Federal Water Quality Administration, Department of the
Interior, through in-house research and grants and contracts with the Federal,
State, and local agencies, research institutions, and industrial organizations.
Triplicate tear-out abstract cards are placed inside the back cover to facili-
tate information retrieval. Space is provided on the card for the user's
accession number and for additional key words. The abstracts utilize the
WRSIC system.
Water Pollution Control Research Reports will be distributed to requesters as
supplies permit. Requests should be sent to the Project Reports System, Office
of Research and Development, Department of the Interior, Federal Water Quality
Administration, Washington, D. C., 20242.
Previously issued reports on the Storm and Combined Sewer Pollution Control
Program:
WP-20-11 Problems of Combined Sewer Facilities and Overflows, 1967.
WP-20-15 Water Pollution Aspects of Urban Runoff.
WP-20-16 Strainer/Filter Treatment of Combined Sewer Overflows.
WP-20-17 Dissolved Air Flotation Treatment of Combined Sewer Overflows.
WP-20-18 Improved Sealants for Infiltration Control.
WF-20-21 Selected Urban Storm Water Runoff Abstracts.
WP-20-22 Polymers for Sewer Flow Control.
ORD-4 j* Combined Sewer Separation Using Pressure Sewers.
• '
DAST-4 ' Crazed Resin Filtration of Combined Sewer Overflows.
DAST-5 Rotary Vibratory Fine Screening of Combined Sewer Overflows.
DAST-6 Storm Water Problems and Control in Sanitary Sewers,
Oakland and Berkeley, California.
DAST-9 Sewer Infiltration Reduction by Zone Pumping.
DAST-13 Design of a Combined Sewer Fluidic Regulator.
DAST-25 Rapid-Flow Filter for Sewer Overflows.
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Storm Water Pollution
from
Urban Land Activity
Development of Analytical Procedures
for Predicting Storm Water Pollution from Urban Areas
by Use of Selectively Defined Urban Characteristics
Federal Water Quality Administration
Department Of The Interior
jj^Bm
by
Economic Systems Corporation
1025 Connecticut Avenue, N. W.
Washington, D. C. 20036
A Subsidiary of Avco Corporation
Program No. 11034 FKL
Contract No. 14-12-187
JULY, 1970
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FWQA Review Notice
This report has been reviewed by the Federal Water
Quality Administration and approved for publication.
Approval does not signify that the contents necessarily
reflect the views and policies of the Federal "Water
Quality Administration, nor does mention of trade
names or commercial products constitute endorsement
or recommendation for use.
U. S. GOVERNMENT PRINTING OFFICE
WASHINGTON : 1970
For sale by the Superintendent of Documents, U. S. Government Printing Office
Washington, D. C. 20402
11
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ABSTRACT
An investigation of the pollution concentrations and loads from storm
water runoff in an urban area was conducted in Tulsa, Oklahoma- The
scope of the project included: a field assessment of the storm water
pollution by obtaining samples of the water resulting from precipitation
and surface runoff from selected test areas within the metropolitan area;
development of an analytical procedure for correlation of storm water
pollution with selectively defined variables of land uses, environmental
conditions, drainage characteristics, and precipitation; and development
of a plan for implementing remedial measures necessary to abate or
control sources of pollution in an urban area.
Storm water runoff samples were collected from 15 "discrete" test
areas in the Tulsa metropolitan area for laboratory analysis in terms
of quality standards for BOD, COD, TOC, organic Kjeldahl nitrogen,
soluble orthophosphate, chloride, pH, solids, total coliform, fecal
coliform, and fecal streptococcus pollutants.
Selected land use parameters, environmental conditions, drainage and
precipitation data, along with storm water pollution factors, provided
input data for functional relationships to enable assessment of pollution
from storm water runoff.
Recommendations were made for a plan of action for preventing and
controlling storm water pollution from urban areas.
This report was submitted in fulfillment of Contract 14-12-187, between
the Federal Water Quality Administration and the AVCO Economic
Systems Corporation.
.KEY WORDS: STORM WATER POLLUTION, URBAN RUNOFF, LAND
USE INDICATORS
111
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CONTENTS
Section Title Page
Abstract iii
Figures vii
Tables xi
1 Findings, Conclusions, and Recommendations 1
2 Introduction 13
3 Description of the Urban Area 15
4 Description of Test Areas 25
5 Characterization of Land Use 39
6 Environmental Conditions 49
7 Sampling Instruments and Methods Used 59
8 Results of Storm Water Pollution Analysis 73
9 Storm Water Pollution Estimates 99
10 Analytical Procedure for Storm Water
Pollution Assessment 123
11 Acknowledgments 157
12 References 159
13 Publications 163
14 Glossary and Abbreviations 165
15 Appendices 169
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FIGURES
Figure TitLe Page
1 Aerial View of Central Business District, Tulsa,
Oklahoma 15
2 Natural Features Map 19
3 Water Resources Map 20
4 General Soils Map 21
5 Locations of the Fifteen Test Areas, Tulsa,
Oklahoma 26
6 Schematic Diagram of Storm Water Sequential Sam-
pling Equipment 60
7 Wiring Diagram and Parts List of Pump Unit 61
8 Inclined Sequential Sample Container 62
9 Detail Plans of Inclined Sequential Sample Container 63
10 Sampling Equipment 64
11 Pressure Recorder, Overflow Jug, and Inclined
Sequential Container 64
12 Top of Sampling Probe 65
13 Sampling Probe Float and Pressure Box 65
14 Equipment Enclosure and Sampling Probe at Sampling
Site No. 3 66
15 Service Truck, Enclosure, and Sampling Probe at
Sampling Site No. 10 66
16 Bar Graph of Average BOD, TOC, and COD Concen-
trations 82
vn
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FIGURES- - Continued
Figure Title Page
17 Bar Graph of Average Nutrient Concentrations 88
18 Bar Graph of Average Solids Concentrations 93
19 Cumulative Frequency Distribution of 465 Rainfall
Events at Tulsa International Airport 101
20 Rainfall-Runoff Relationships for Site Number 7 104
21 Rainfall of November 15, 1968 (Test Area No. 10) 106
22 Rainfall of November 15, 1968 (Test Area No. 15) 107
23 Dispersed Pollution Flow Chart 126
A-l Test Area No. 1--Southern Memorial Industrial
District 172
A-2 Test Area No. 2--Southroads-Southland Shopping
Center Area 173
A-3 Test Area No. 3--Sungate and Woodland View Area 174
A-4 Test Area No. 4--Sheridan Industrial District 175
A-5 Test Area No. 5--Woodward Park Area 176
A-6 Test Area No. 6--Latimer Industrial District 177
A-7 Test Area No. 7--Methodist Manor 178
A-8 Test Area No. 8--Strip-Pit Collection Basin 179
A-9 Test Area No. 9--Sunny Slope Addition 180
A-10 Test Area No. 10--South Central Business District 181
A-ll Test Area No. 11--Greenwood Drainage Shed 182
A-12 Test Area No. 12--Airport East 183
viii
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FIGURES--Continued
Figure Title Page
A-13 Test Area No. 13--Bolewood Acres 184
A-14 Test Area No. 14--Southern Hills Country Club 185
A-15 Test Area No. 15--Alt Ade Ma Place 186
B-l Indiscriminate Roadside Dumping of Trash and
Rubble 192
B-Z Scattering of Waste Construction Material and Poor
Maintenance of Drainage Channel 192
B-3 Unimproved and Poorly Maintained Open Drainage
Channel 193
B-4 Indiscriminate Dumping into Open Drainage Channel 193
B-5 Indiscriminate Dumping into Open Drainage Channel
(Grass Trimmings) 194
B-6 Poorly Maintained Drainage Structure--Buildup of
Decaying Organic Matter Resulting in Flow Stoppage 194
B-7 Vast Area of Disturbed Land with Ground Cover Re-
moved and Open Storage of Material During
Construction Activities 195
B-8 Dirty Streets--Subdivision Development 195
B-9 Land Filling with Construction Material Waste
Adjacent to Open Drainage Channel 196
B-10 Residential Parcel Deficiencies--Uncovered Garbage
Cans and Piles of Rubble 196
C-l Land Activity File Form 201
F-l Map of Test Area No. 1 224
F-2 Map of Test Area No. 2 225
ix
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FIGURES- - Continued
Figure Title Page
F-3 Map of Test Area No. 3 226
F-4 Map of Test Area No. 4 227
F-5 Map of Test Area No. 5 228
F-6 Map of Test Area No. 6 229
F-7 Map of Test Area No. 7 230
F-8 Map of Test Area No. 8 231
F-9 Map of Test Area No. 9 232
F-10 Map of Test Area No. 10 233
F-ll Map of Test Area No. 11 234
F-12 Map of Test Area No. 12 235
F-13 Map of Test Area No. 13 236
F-14 Map of Test Area No. 14 237
F-15 Map of Test Area No. 15 238
1-1 City of Tulsa Street Cleaning Districts 248
J-l Sewage Treatment Facilities, Tulsa, Oklahoma 258
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TABLES
Table Title Page
1 Summary of the Analytical Results 1
2 Selection of Best Multiple Regression Equations
for Precipitation Variables 3
3 Selection of Best Regression Equations from
Analysis of Land Surface Characteristics of
Combined Land Use Test Areas 4
4 Selection of Best Regression Equations from
Analysis of Land Surface Characteristics of
Residential Test Areas 5
5 Selection of Best Regression Equations from
Analysis of Land Surface Characteristics of
Commercial and Industrial Test Areas 6
6 Calculated Average Yearly Loads 7
7 Average Daily Loads per Mile of Street 8
8 Various Population Estimates 1°
9 Suitability of Soil Associations for Alternative
Uses 22
10 Population and Land Use by Watershed 23
11 Test Drainage Basins and Sampling Sites 32
12 General Description of the Test Areas 33
13 Features of the Test Areas 37
14 Land Use Activities in Acres by Major Use
Groups Within the Fifteen Test Areas 43
15 Percentage of Land Devoted to Major Use
Groups in the Fifteen Test Areas 44
xi
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TABLES- - Continued
Table Title Page
16 Population Characteristics of the Fifteen Test
Areas 45
17 Drainage Characteristics of the Test Areas 46
18 Street Characteristics Within the Fifteen Test
Areas 47
19 Number of Housing and Parcel Deficiencies With-
in the Fifteen Test Areas 55
20 Calculation Procedure for the Environmental Index
(El) of the Test Areas 56
21 Environmental Conditions of the Fifteen Test
Areas 57
22 Number of Reliable Observations of Each Parameter
from Each Test Area 71
23 Number of Samples Collected from Each Test Area
by Event Number 72
24 Chemical Characteristics of Urban Storm Water Run-
off (Other Studies) 74
25 Bacterial Characteristics of Urban Storm Water Run-
off (Other Studies) 75
26 Bacterial Densities in Urban Storm Water Samples
from 15 Test Areas, Tulsa, Oklahoma 76
27 Bacterial Densities in Urban Storm Water Samples
from Cincinnati Study 76
28 Geometric Means for Bacterial Density in Urban
Storm Water 77
29 Mean Ratios and Standard Deviations of Bacterial Pollu-
tion Parameters 78
xii
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TABLES- - Continued
Table Title Page
30 Average and Range for BOD, COD, and TOC
in Urban Storm Water Runoff 81
31 Selected Mean Ratios and Standard Deviations of
Organic Pollution Parameters 83
32 Selected Mean Ratios and Standard Deviation of
Organic and Solids Pollution Parameters 84
33 Average and Range for Nutrient Concentrations 87
34 Mean and Standard Deviation of Ratio of Organic
Kjeldahl Nitrogen to Soluble Orthophosphate 87
35 Average Values for Solids 92
36 Mean Ratios and Standard Deviations of Various
Solids Components 94
37 Average Values for pH, Cl, and Specific Conductance 96
38 Precipitation Means and Extremes 100
39 Calculated Average Runoff for Bird Creek Water-
shed Above the Sperry Gage 102
40 Average Monthly BOD Loads 108
41 Average Monthly COD Loads 109
42 Average Monthly Organic Kjeldahl Nitrogen
Loads 110
43 Average Monthly Soluble Orthophosphate Loads 111
44 Average Monthly Total Solids Loads 112
45 Average Daily Loads per Mile of Street 113
46 Estimated Daily Load of Pollutants Entering
the Area Receiving Streams 115
xiii
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TABLES- - Continued
Table Title Page
47 Comparison of Average Pollution Loads and
Loads for April 116
48 Sources of Flow Contribution Within the Bird
Creek Watershed 118
49 Average Daily Volumes Comparing Arkansas River
Flow at Tulsa with the Sewage Effluent of the South
Side Plant and with Storm Water Runoff from
Metropolitan Tulsa H9
50 Comparison of Sewage Flow with Total Flow for
Bird Creek and the Arkansas River 120
51 Receiving Stream Water Quality Data 122
52 Pollutional Load Criteria 127
53 Correlation Matrix--Land Use Activities 129
54 Correlation Matrix--Selected Environmental and
Land Use Factors 130
55 Correlation Coefficients--Parameter Concentra-
tions vs. Selected Land Use Variables 131
56 Correlation Coefficients--Parameter Concentra-
tions vs. Selected Percentage Land Use Variables 132
57 Rotated Factor Matrix Obtained by Factor Analysis
of Selected Drainage Characteristics 136
58 Variables and Associated Eigenvector Values Used
to Compute the Index Values for the Study Sites 138
59 Index Values for Study Sites from Principal
Components 139
60 Study Site Environmental Rankings 140
xiv
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TABLES- - Continued
Table Title page
61 Study Site Rankings in Relation to Drainage
Characteristics 141
62 Correlation Coefficients for In BOD vs. Rising
Limb Precipitation Variables 146
63 Summary of Occurrence and Frequency of Signifi-
cant Variables Determined by Regression Analysis
of Land Surface Characteristics 149
64 Mixed-Use Regression Equations for Sample
Calculations 150
A-l Summary of Zoning Classifications 187
H-l Format of Data Cards 242
1-1 City of Tulsa Street Sweeping Districts 249
1-2 Monthly Street Cleaning Operations for Fiscal Year
1967-1968 251
1-3 Monthly Street Cleaning Operations for Fiscal Year
1968-1969 252
1-4 Storm Sewer Cleaning and Maintenance for Fiscal
Year 1967-1968 and Fiscal Year 1968-1969 254
J-l Characteristics of Tulsa1 s Four Sewage Treatment
Plants 259
J-2 Monthly Average Daily Flows 1967 260
J-3 Monthly Average Daily Flows 1968 261
J-4 Average Pollution Parameter Concentrations from
City of Tulsa1 s Sewage Treatment Plants 262
J-5 Quality of Effluent from Tulsa1 s Municipal Sewage
Treatment Plants 263
xv
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TABLES- - Continued
Table Title Page
J-6 Efficiency of Removal of Tulsa's Municipal Sewage
Treatment Plants 264
J-7 Estimated Average Daily Loads to Receiving
Streams from the City of Tulsa's Four Sewage Treat-
ment Plants 265
K-l Dependent and Independent Variables Used in Re-
gression Analysis 268
K-2 Regression Equations--Pollution Parameter
Concentrations vs. Precipitation Variables 270
K-3 Multiple Regression Equations--In BOD Concen-
trations vs. Rising Limb Precipitation Variables 274
K-4 Selection of Best Univariate Land Use Regression
Equations for All Test Areas 275
K-5 Regression Equations for Common Predictor
Variables 277
K-6 Regression Equations for Residential Areas 280
K-7 Regression Equations for Commercial and Industrial
Areas 284
L-l Monthly Precipitation for Six Rain Gages, Tulsa,
Oklahoma 290
L-2 Average Frequency of Rainfall Events, Tulsa,
Oklahoma 293
L-3 Average Monthly Rainfall Amount Occurring Within
Specific Rainfall Intervals 294
M-l Analytical Results of Baseline Samples 297
M-2 Analytical Results of Storm Water Runoff Samples 298
xvi
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SECTION 1
FINDINGS, CONCLUSIONS, AND RECOMMENDATIONS
Findings
1. Analytical Results - The data presented in Table 1 summarizes the
assessment of pollution parameters measured on 15 urban watersheds.
TABLE 1
SUMMARY OF THE ANALYTICAL RESULTS
Parameter Mean of the Range of the Test
Test Areas Area Means
Bacterial (number/100 ml)a
Total coliform 87,000 5,000-400,000
Fecal coliform 4ZO 10- 18,000
Fecal streptococcus 6,000 700- 30,000
Organic (mg/1)
BOD 11.8 8- 18
COD 85.5 42-138
TOG 31. 8 15- 48
Nutrients (mg/1)
Organic Kjeldahl nitrogen 0.85 0.36-1.48
Soluble orthophosphate 1.15 0.54-3.49
Solids, (mg/1).
Total 545 199-2242
Suspended 367 84-2052
Dissolved 178 89-400
Other Parameters
pH7.4 6.8-8.4
Chloride (mg/1) 11.5 2- 46
Specific conductance 108 36-220
(mi c r omho s / cm)
Geometric mean.
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2. Functional Relationships - Regression analysis was used to deter-
mine predictor models for estimating urban pollutant concentrations.
Inputs for this phase of the study consisted of the analytical results
from the test areas and tabulated groups of independent variables de-
scribing both the precipitation regimen and land surface characteristics
of each test area. The best regression equations determined in these
analyses are shown in Tables 2 through 5.
Table 2 shows a listing of the best multiple regression equations devel-
oped using the precipitation variables and the associated sample results.
These equations are suitable for estimating the pollution concentrations
from characteristics which describe individual precipitation events.
The equations developed in the analysis of land surface characteristics
can be used to estimate the average concentrations of pollutants in the
storm runoff from urban areas. Table 3 presents the best equations
developed with data from combined land uses. Table 4 contains equa-
tions derived using data from Test Areas No. 3, 5, 7, 8, 9, 13, and
15--the "residential" test sites. The equations from Test Areas No. 1,
2, 4, 6, 10, and ll--the commercial and industrial sites--are presen-
ted in Table 5.
3. Estimates of Pollution Loadings - The estimated average annual
storm water pollution loads for each of the test areas were obtained by
multiplying the average pollutant concentrations by the estimated
annual volumes of runoff. This calculated load for each site is depicted
in pounds per acre per year in Table 6 and in pounds per day per mile
of street in Table 7. Both tables can aid in comparing the pollution
generating capacities of each site.
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TABLE 2
SELECTION OF BEST MULTIPLE REGRESSION EQUATIONS FOR PRECIPITATION VARIABLES
Regression Equation
Correlation
(R)
F-Value5 Equation
Number
Total Coliform (Thousands/100 ml)
In Y! = 5. 2598 - 0. 0853 (ZL) - 0. 9638 (Z2) - 0. 8297 (Z5)
Fecal Coliform (Number/100 ml)
In Y2 = 1. 5072 - 0. 0039 (Z4) - 0. 6503 (Z5) + 12. 3412 (Z?)
Fecal Streptococcus (Thousands/100 ml)
In YS = 2. 7615 - 0. 3901 (Zi) + 1. 1460 (Z2) - 0. 0039 (Z4)
BOD (mg/1)
In Y4 = 2. 7531 + 0. 0086 (Z:) - 0. 6484 (Z2) - 0. 3674 (Z5)
COD (mg/1)
In Y5 = 4. 5757 - 0. 0246 (Z^ - 0. 2001 (Z2) - 0. 0900 (Z3)
Total Solids (mg/1)
In Yg = 5. 7304 - 0. 0144 (Zj) +• 0. 057-2 (Z2) + 0. 3004 (Z3)
0. 232
0. 324
0. 416
0. 274
0. 215
0. 103
7. 27**
13. 88**
30. 21**
11.
5. 78**
1.45
K-9
K-20
K-28
K-39
K-47
K-57
Legend for dependent and independent variables
Y^ = Pollution parameter concentration
Zj = Time since, start (hrs. )
Z2 = Antecedent amount (in.)
Z3 = Antecedent average intensity (in. /hr. )
Z4 = Time since antecedent event (hr. )
Z5 = Amount of antecedent event (in. )
Z-j = Average intensity of antecedent event (in. /hr. )
The 99 percent significance level is indicated by two asterisks (**)
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TABLE 3
SELECTION OF BEST REGRESSION EQUATIONS FROM
ANALYSIS OF LAND SURFACE CHARACTERISTICS
OF COMBINED LAND USE TEST AREAS
Regression Equation
F-Value'
Equation
Number
Total Coliform (Thousands/100 ml)
MI = 430 - 363 (X^0
Fecal Coliform (Thousands/100 ml)
M2 = -11. 7 + 6. 92 (Xj) + 6. 25
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TABLE 4
SELECTION OF BEST REGRESSION EQUATIONS FROM
ANALYSIS OF LAND SURFACE CHARACTERISTICS
OF RESIDENTIAL TEST AREAS3-
•Regression Equation
F-Value
Equation
Number
17.75**
0. 26
Total Coliform (Thousands/100 ml)
M! = 521 - 427 (Xx)
Fecal Coliform (Thousands/100 ml)
M2 = 0. 884 + 0. 806 (Xj) - 0. 396 (X20) + 0. 543 (D,)
Fecal Streptococcus (Thousands/100 ml)
In M3 = 2. 4741 - 1. 216 (Xx) - 0. 115 (X17) t 2. 076 (X20) 0. 42
BOD (mg/1)
M4= 21.7 - 0.05 (X22)
COD (mg/1)
M5 = 69 - 74. 71 (Xi) -K 3. 68 (X21) + 0. 0105 (D2)
Organic Kjeldahl Nitrogen (mg/1)
M7 = Z. 01 - 1.00 (X20)
Soluble Orthophosphate (mg/1)
M8 = 0. 66 - 0. 0011 (X21) + 0. 0645 (X29)
Total Solids (mg/1)
M9 = -139 - 15.4 (X20) + 16. 0 (X22) + 2. 57 (D4)
Suspended Solids (mg/1)
M12= 791 - 31.2 (XX) - 288 (X20) + 1. 32 (X21)
2.89
16. 55**
7.73*
4. 01
1.41
2. 17
K-131
K-145
K-150
K-156
K-164
K-169
K-179
K-187
K-190
aTest Areas No. 3, 5, 7, 8, 9, 13, and 15.
''Legend for dependent and independent variables:
MI = Arithmetic mean (by events) of parameter concentration (geometric mean by events
for bacterial parameters)
D2 = Length of main stream (ft.)
D4 = Fall of drainage area (ft.)
Dg = Form factor (dimensionJ.es s)
Xj = Environmental Index (dimensionless)
Xj7 = Residential density -(people/res, acre)
X20 = Covered sewer/total length (ratio)
X21 = Arterial streets (%)
X22 = Other streets (%)
X29 = Unused space (%)
cLevels of significance:
* 95 percent level
** 99 percent level
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TABLE 5
SELECTION OF BEST REGRESSION EQUATIONS FROM
ANALYSIS OF LAND SURFACE CHARACTERISTICS
OF COMMERCIAL AND INDUSTRIAL TEST AREASa
Regression Equation F-Valuec Equation
Numbe r
Total Coliform (Thousands/100 ml)
Mj = 372 - 329 (X^ 25.66** K-193
Fecal Coliform (Thousands/100 ml)
M2 = 5. 64 + 5. 25 (X20) 10. 58* K-203
Fecal Streptococcus (Thousands/100 ml)
M3 = 37. 29 - 6519 (X14) 19.65* K-210
BOD (mg/1)
M4 = 8. 3 - 0. 709 (Xj) + 1. 10
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TABLE 6
CALCULATED AVERAGE YEARLY LOADS
Pollution Load: Ibs. /acre /year
Test
Area
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Acres
686
272
550
938
507
368
197
211
64
206
815
223
212
263
74
BOD
30
27
14
44
33
21
15
33
20
48
35
25
25
12
25
COD
250
150
110
320
250
160
90
250
230
470
290
140
150
60
90
Organic
Kjeldahl
Nitrogen
2.5
3. 3
2.6
3. 0
1. 3
1, 1
1. 5
1. 5
1. 3
3.6
1. 7
1. 2
2.4
1. 1
0.8
Soluble
Orthophosphate
8.
2.
3.
3.
1.
1.
1.
2.
2.
3.
2.
1.
2.
1.
1.
0
9
3
3
6
5
3
5
0
1
1
7
0
1
7
Total
Solids
5100
920
1200
1900
490
600
790
840
830
1900
1400
630
780
660
570
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TABLE 7
AVERAGE DAILY LOADS PER MILE OF STREET
Average Load: Ibs. /day/mile
Test
Area
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Total
Street
Miles
11.
7.
14.
28.
16.
12.
6.
6.
3.
12.
49.
3.
5.
2.
2.
46
41
87
40
32
24
84
97
11
99
05
39
58
07
06
BOD
4.
2.
1.
3.
2.
1.
1.
2.
1.
2.
1.
4.
2.
4.
2.
85
54
41
98
80
70
20
72
12
10
60
53
58
26
47
COD
4i.
15.
11.
29-
21.
12.
7.
20.
13.
20.
13.
25.
15.
20.
8.
10
12
46
29
43
73
20
89
09
44
29
47
16
54
67
Total
Solids
838
92
120
175
43
49
63
69
47
82
66
113
81
23
56
Organic
Kjeldahl
Nitrogen
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
41
32
26
28
11
09
12
12
07
16
08
22
25
37
07
of street
Soluble
Or th opho sphat e
1.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
30
29
34
30
13
13
10 -
21
11
13
15
30
20
38
17
8
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Conclusions
1. The largest portion of the pollutants from the urban test areas
which were studied resulted from (1) washout of materials which
were deposited on the j.mp_ervious areas and (2) the erosion of
drainage channels caused by the high volumes of runoff generated
on the impervious portions of the test areas.
2. The season of the year with the greatest^j-mgu^^f^unoff also
p^odu£fiR the 1argesjLa.mgunts of pollutants. For example, during
the period of record used in the hydrological portion of the study
(1964-1968), the months of March, April, and May produced only
28 percent of the annual average precipitation. In this same period,
however, about half of the annual runoff occurred. Therefore, even
though pollutant concentrations in urban watersheds might have been
higher during events occurring in other seasons, the larger runoff
coefficient during these three months, with its stimulated effects
on yield, would produce the greater amount of pollutants,
3. The functional relationships developed in this study between storm
water pollution parameters and variables grouped in either the
precipitation regimen or the land surface characteristics classifi-
cation can be used to obtain a first order estimate of the average
pollutant concentrations in urban watersheds at other geographical
locations. These techniques provide an applicable procedure for
looking at the impact of urban storm water pollutional loads to the
receiving streams and for planning storm water pollutional control
strategy for water quality management.
4. Principal component analysis can be used to rank the watersheds
of an urban area after pollutional loads and other base measurements
have been measured on a reference drainage basin within the area.
In place of sampling, information and data obtained from maps,
local municipalities, and local health departments can be used to
compare the pollutional generating capacity of urban watersheds.
5. The land surface characteristics which have the strongest para-
metric relationships with storm water pollutant concentrations
are the environmental conditions, the geomorphic characteristics
which affect drainage, and the degree of development. The last-
mentioned characteristic is evidenced by the amount of streets,
the type of streets, the amount of main covered storm sewer, and
the ratio of covered storm sewer to total length.
-------
6. Land surface characteristics which influence the drainage of a
watershed affect the amounts of pollution produced per unit area
to a larger degree than the recorded environmental deficiencies
or the types of land activity. For example, Test Area No. 9 had
a bad environment as determined by the number of total deficiencies,
and ranked the highest of all sites in the number of total coliform.
The drainage characteristics of the area were poor, however, and
relatively small yields of pollutional material were washed from
the watershed in storm runoff.
7. A good prediction variable for the bacterial pollution parameters
was found to be the Environmental Index, which reflects the general
sanitary conditions of the sites. This index can be calculated by
the procedure explained in Section 6 of this report. An alternate
approach for calculation of an environmental index is through
principal component analysis as presented in Section 10.
8. The regression equations developed with the precipitation variables
and all associated samples indicated the existence of several
meaningful relationships. Pollutant concentrations, for example,
decreased with both the time since the start of the current precipita-
tion event and the time since the antecedent event. The bacterial and
total solids concentrations increased with the average intensity of the
current precipitation event.
9. The analysis of the precipitation variables and BOD values taken
during the rising limb of the runoff hydrograph indicated that the
BOD concentrations decreased with increasing flow. The amounts
of BOD contained in the flow increased with runoff rates because
the time rate of flow increased at a greater rate than the BOD con-
centration decreased.
10. Examination of the analytical results indicates that there is a de-
crease in the amount of pollution produced per unit area of
commercial and industrial use if the daily number of people who
visit the area is high. The frequency and degree of maintenance
operations increase with the number of daily visitors entering
an area, whereas maintenance functions are not performed at
the same frequency or degree if the number of daily visitors is
low.
11. The study results indicate that, in the residential sector, the
amount of pollution produced per unit area increases with the
population density and/or the number of developed parcels.
10
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12. Considering calculations using the results of this study and data
from Tulsa's sewage treatment plants, it is reasonable to con-
clude that, with the continued urbanization of the area in conjunction
with the demands for increased efficiencies in waste treatment
facilities, storm water runoff in Tulsa will eventually become
the prime source of pollution in the area receiving streams.
Recommendations
The recommendations presented below are based on the findings of the
study which are applicable to all urban areas with separate storm
drainage systems. Remedial measures and research of the nature
proposed herein would reduce storm water pollution from urban areas.
Specific recommendations and controlling storm water pollution in
Tulsa are presented in Appendix N.
1. Three approaches to the abatement and control of dispersed
pollution loads appear to be the most promising. These are: (1)
a reduction in total runoff, (2) a reduction in the rates of runoff,
and (3) environmental policy. It is therefore recommended that
structural measures be implemented to effect control within
the first two areas. Examples of the type of control measures
which might be used are:
• devices or schemes that would eliminate or deplete runoff
in the urban area.
• the use of impoundments or catch basins to attenuate flows
and thus reduce the rate of runoff.
• implementation of upstream retention programs for open
spaces within the urban complex.
In the third area, it is recommended that environmental controls
on storm water pollution be invoked through the enactment of:
• regulations and enf or cement procedures to control urban
litter and general sanitary conditions of public and private
areas.
• performance standards in subdivision regulations for builders
and contractors during periods of land development. These
standards would deal with such measures as would (1)
11
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minimize periods of exposing bare soil, (2) enhance house-
keeping activities during and after construction, and (3)
strengthen specifications for drainage practices followed
during construction periods.
• open storage and drainage regulations for commercial and
industrial areas.
• improved street cleaning and drainage channel maintenance
practices with the primary intent of storm water pollution
control rather than aesthetics or flood control.
2. In investigations such as this which rely on precipitation as the
prime mover or cause of events that are to be studied, the time
span of the project should be adjusted to compensate for the irreg-
ularity in the occurrence of study events.
3. The influential role exerted by the physical characteristics of
watersheds on the future runoff regimen in a developing urban
area must be recognized by the municipal agencies charged with
planning and public works.
4. It is recommended that an investigation should be initiated to
determine the correlation between the results of this study and
measurements of pollution parameters in storm runoff from areas
both in the "natural" state and those with a developed agriculture.
Knowledge of the pollutants derived from these types of land uses
is necessary for the complete assessment of storm water pollution
within the metropolitan fringe areas and at the rural interface.
12
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SECTION 2
INTRODUCTION
This has been an investigation of urban area storm water pollution, or
more precisely, an assessment of pollution in storm, water as it relates
to land activity. The central purpose of this effort was to design a
method of analysis which would enable the city planner and engineer to
assess the quality as well as quantity of storm water, and to do so by
looking at land activity, selected environmental factors, and precipita-
tion.
Although major concern in recent years regarding pollution from storm
water runoff has been with problems of combined sewage systems, storm
water pollution is also a real and urgent problem in areas having
separate storm and sanitary systems. Considerable quantitative data
regarding the pollution from combined and separate sewers are available
(1-4); there have also been several recent studies (5-8) into methods
of control. Most of the proposed measures incorporate some type of
structural system or physical treatment, such as retention, treatment,
and coordinated discharge.
The control techniques discussed in this report are mainly the applica-
tion of planning and management directed toward the control of pollution
from land use practices rather than extensive structural facilities to
treat or dispose of contaminant storm water effluents. Planning and
management control techniques will be beneficial, notwithstanding the
need for physical treatment to reduce the pollution load by making
possible iribre economical treatment and/or better water quality. In
other words, water quality management and physical pollution control
measures are not necessarily mutually exclusive, but additive.
This report deals with an assessment of the sources of pollution from
various land activities to provide possible means for control of storm
water pollution by improved urban planning and land use regulation.
Given the relationship of man's activities to storm water drainage,
civic actions can be undertaken to reduce pollutional loads. If urban
planning and proper regulation of land activity can reduce the overall
costs associated with the achievement of an acceptable quality of the
environment in the urban area, such activities should be considered
the first order of business and an adjunct to any construction of physical
systems for collection, disposal, or treatment.
13
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In an engineering sense, the process was to relate land use, land
condition, and hydrological input to a pollutional output for homogen-
ous areas. The predicted area load thus is aggregated to provide an
estimate of pollution. The process is similar to the determination of
runoff from urban areas.
14
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SECTION 3
DESCRIPTION OF THE URBAN AREA
Tulsa, Oklahoma is a relatively young city, incorporated in 1907, the
same year that Oklahoma became the nation's forty-sixth state.
Tulsa1 s population that year was approximately 12, 000. The city grew
very rapidly until 1930. In the following 10 years, growth was retarded
by the depression, and Tulsa recorded only a 0. 6% change in population.
From 1940 until today Tulsa has grown rapidly to a population of over
400,000 people.
Cattle raising constituted the predominant industry of the area until
the major oil discoveries at Red Fork in 1901, 1902, and 1904 and at
Glenpool in 1905. Since that time, Tulsa has become known as one of
the nation's leading centers for oil technology and the principal trade
and distribution center for northeastern Oklahoma.
An aerial view of the central business district as it looks today is
shown in Figure 1. Included in the view is the Arkansas River as it
approaches the city from the west and turns to the southeast.
FIGURE 1.
Aerial view of central business district,
Tulsa, Oklahoma
15
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Population
The population of Tulsa County in 1969 was 424, 000. This compares
with 346, 000 in I960 and 252, 000 in 1950. An increase of about
172, 000 people, or 68 percent, occurred in this 19-year period. The
rate of growth for the 9-year period from I960 to 1968 was approxi-
mately 22 percent. Various population estimates for Tulsa County,
City of Tulsa, SMSA, and Tulsa Urban are presented in Table 8:
TABLE 8
VARIOUS POPULATION ESTIMATES3"
Planning Unit
SMSA
Tulsa Urban
Tulsa County
City of Tulsa
Area in
Square
Miles
3819
n. a.
572
172 •
Population
500,700
401,400
424, 000
335,000
aSource: Tulsa Metropolitan Area Population
Estimates 1969, Tulsa Metropolitan Area
Planning Commission, June, 1969.
Topographic Characteristics
The highest elevation in the Tulsa region is 1, 017 feet above sea
level and the lowest is 550 feet above sea level. The latter lies in
the flood plains of the Arjkansas River. The eastern portion of the,
county has hill elevations of 800 and 850 feet above sea level with
valley bottoms at 600 and 650 foot elevations. In general, a north-
south line formed by the Osage- Tulsa County line and extending south
along the Arkansas River separates the western area of more rugged
topography from the more gently undulating land to the east.
16
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Geology
Tulsa County, located in the northeastern part of the State of Oklahoma,
contains an area of approximately 572 square miles. The county is
situated between the High Plains to the west and the Ozarks uplift to the
east. Specifically, Tulsa County is comprised of Prairie Plains and
the Sandstone Hills. The rocks are principally sandstone and shale of
the Pensylvanian age. Some limestone occurs in the northern part of
the county. Surface geological features of the Tulsa area result from
two factors, (1) structural subsurface layers of a northeast-southwest
orientation and (2) the erosion of the original surface of the earth by
wind and water, followed by the uplifting and tilting of the surface,
followed again by erosion forces. Hence, the surface of Tulsa County
is generally rough with east-facing ranges of sandstone hills separated
by flats or valleys underlaid by shale. Because of the differences in
hardness of rock and because of the tilting of these rocky areas to the
extent of 30 to 50 feet per mile, cuestas have been formed by erosion
processes. These cuestas present their high slopes to the east and
gentle slopes to the west. Escarpments are modified locally by greater
erosion along streams that lead into or across them. Hence, many
escarpments may be served by the streams.
Climate
Tulsa is located in a zone with a continental type of climate. Sudden
wide changes in temperature characteristic of this climatic pattern
occur with the rapid passage of frontal air masses through the area.
The record mean monthly temperatures range from 37. 4° F in
January to 82. 5° F in July. This area has an average growing season
of 221 days and is frost-free normally from March 25 to November 1.
The annual record mean precipitation of 37. 25 inches is well distributed
throughout the year. The season of maximum rainfall is spring, when
much precipitation occurs through thunder storm activity. The high
levels of soil moisture and the high precipitation intensities produced
by the thunderstorms help to increase the percentage of runoff during
this season.
The percent of possible sunshine varies from 49 percent in January to
72 percent in July. The average annual values show Tulsa with 125
clear days, 110 partly cloudy days, and 130 cloudy days.
17
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General Drainage Characteristics
Drainage of Tulsa County is into the Arkansas River, which crosses
the county generally from the northwest to the southeast. The northern
part of the City of Tulsa and the north portion of Tulsa County drain
into the Verdigris River, which in turn drains into the Arkansas River
at Muskogee, Oklahoma. Immediately west of the City of Tulsa, the
valley of the Arkansas River is deeply incised with a flood plain less
than two miles wide. Major .drainage basins and their natural features
are shown in Figure 2 . Figures 3 and 4 give respectively the water
resources and general soil types of the Tulsa area. Table 9 contains
the legend for the soils map, as well as selected land use ratings.
There are eight principal drainage basins in urban Tulsa, emptying
into the Arkansas and Verdigris Rivers as follows:
Arkansas River Verdigris River
Central Flatrock
Berryhill Coal
Black Boy Mingo
Joe
Cherry
Central Basin can be divided into a number of sub-basins. Nearly all
of Central Basin is fully developed, and portions are in the original
townsite. Located along the Arkansas River are numerous drainage
outfall sites ranging in size from &" pipe to 24' x 12' arches.
The population and land use activities for six of the principal drainage
basins are shown in Table 10.
18
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FIGURE 2
NATURAL FEATURES
MAJOR WATERSHED LIMIT
MINOR WATERSHED LIMIT
RAIN GAUGE STATIONS
& NUMBERS
tulso metropoliton area planning commission
19
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FIGURE 3
WATER RESOURCES
SURFACE WATER
UNDERGROUND WATER
STREAMS AND CREEKS (FLOWING)
HV'.."I CYCLIC FLOOD PLAINS
(AVG. CYCLE 3 YRS.)
20
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flOURE 4
GENERAL SOILS
21
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TABLE 9
SUITABILITY OF SOIL ASSOCIATIONS FOR ALTERNATIVE USES3
Symbol
of Map
Mapping Units
Name
Residences With
Commun. Indiv.
Service Service
Use Ratings
Recreation Corn.
and and
Parks Ind.
Agriculture
Crop- Pasture
Land
Deep, gently sloping loamy
soils on prairie uplands. Good Fair Good Good
Deep, nearly level loamy
soils with clayey subsoils
on prairie uplands. Fair Poor Fair Fair
Deep, gently sloping to
strongly sloping sandy
soils with loamy subsoils
on wooded uplands.
Shallow to deep, gently
to strongly sloping, loamy
and clayey soils over sand-
stone and shale on prairie
uplands.
Shallow to deep, gently to
strongly sloping, loamy and
clayey soils over lime-
stone and shale on prairie
uplands.
Deep, nearly level loamy
and clayey soils on high
bottomlands that flood
rarely.
Deep, nearly level, loamy
and clayey soils on low
bottomlands that flood
occasionally.
Shallow to deep, gently to
strongly sloping loamy and
clayey soils over sand-
stone and shale on wooded
uplands. Fair Good Good Poor
Arkansas River and Very Very Very Very Very
riverwash. Poor Poor Poor Poor Poor
Good Exc.
Good Good
Good Good Exc. Poor Poor Good
Fair Good Good Poor Poor Fair
Fair Poor Fair Fair Poor Fair
Fair Fair
Poor Poor
Fair Fair Exc. Exc.
Good Poor Good Exc.
Poor
Fair
Very
Poor
aSource: Industrial Development
1969. p. 66.
Plan 1990. Tulsa Metropolitan Area Planning Commission, January,
22
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TABLE 10
POPULATION AND LAND USE BY WATERSHED3"
Water-
shed
Central
Mingo
Land Use Activity
Population
95,800
84, 500
Flatrock 72, 700
Joe
Coal
Cherry
aSource
50,000
38,800
23,500
of the above
Residential
Acres
5,000
9,400
10,900
4,300
3,000
2, 800
Industrial
Acres
380
5,700
440
220
1,040
850
Commercial
Acres
290
370
210
150
670
800
information was Water and Sewage Plan
Institutional0
Acres
1,100
1,330
1,000
900
1,050
600
1990,
Tulsa Metropolitan Area Planning Commission, March, 1969.
Institutional means land that is occupied by educational or govern-
mental establishments, churches, or cemeteries.
23
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SECTION 4
DESCRIPTION OF TEST AREAS
This section discusses the test areas. Fifteen test areas were selec-
ted; in each, sampling sites were identified as indicated in Figure 5.
Table 11 shows the address of each sampling site, the type of drainage
channel, and the type of drainage structure at each site. A general
description and summary of features of the test areas are contained
in Tables 12 and 13.
Methodology of Test Area Selection
Since one of the main objectives of this research was to relate pollu-
tion to land activity, it was necessary to select drainage areas with a
single predominant land activity. This was accomplished in several
of the areas chosen, but not in all areas. Selection of discrete (homo-
geneous land activity) areas was limited by a number of additional
considerations. The most important of these factors were:
1. Size of area large enough to produce a measurable
sample of a certain type land use.
2. Lack of known point sources of pollution in the
drainage area.
3. Security of the sampling instruments from
vandalism.
4. Accessibility of the sampling site.
The sites selected were determined to meet the above criteria and to
provide a typical cross section of the different types of land activity.
Below are the steps followed in the delineation and selection of the test
areas:
1. The storm drains were transcribed from the City
Engineer's Storm Drain Atlas onto a 1" = 600' Land
Use Base Map of the TMAPC.
25
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FIGURE 5
LOCATION OF THE FIFTEEN TEST
AREAS TULSA, OKLAHOMA =1
Illll C:ty Limit
niim
IIIIIIIIIIII: Illffllllllllllllllllllll
26
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2. The land use and zoning within each candidate
test area were checked by use of the TMAPC's
zoning maps.
3. Each test area was reconnoitered for actual
conditions not shown on the maps.
4. Each test area was observed during periods of
storm water runoff to better define the boundaries
of the watershed.
During the early phases of the project, several of the initially selected
test areas had to be dropped and new ones added. The main reason for
these changes was vandalism of the sampling instruments.
The selected test areas with their drainage boundaries and major drain-
age conduits are illustrated in Appendix A.
Characteristics of Test Areas
Each of the fifteen test areas is described and pertinent characteristics
discussed in this section.
Southern Memorial Industrial District (Test Area No. 1) - This test
area is located approximately 7. 5 miles southeast of downtown Tulsa.
The size of the drainage area is approximately 686 acres. It is
primarily a relatively new industrial district.
At present, and during the course of this investigation, this area was
under development. It is predominantly zoned U-4A (Light Industrial
District) and, therefore, includes warehousing, industrial sales, and
light manufacturing. Some tracts with residential area are located in
the lower reaches of the drainage shed.
The industrial buildings are somewhat uniform in nature and have small
amounts of space for outside storage. The area is uncluttered and
well-kept except for one concrete batch plant located on the bank of an
unimproved open channel at the lower end of the catchment.
Southr pads-Southland Shopping Center Area (Test Area No. 2) -
This 273 acre test area is situated 6 miles southeast of downtown Tulsa.
Located on it is the largest shopping center in urban Tulsa. Accompany-
ing the shopping center are large paved parking areas. The shopping
27
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center is similar to those found in most cities and is composed of
retail shops and general merchandise stores. It is well-kept and the
parking lots are cleaned daily.
The arterial streets adjacent to the shopping center are heavily
traveled. Drainage is from east to west with the shopping center
located on the south and a residential area on the north. The only
noticeable sources of pollution are: oil, grease, and dirt from
automobiles in the parking areas; litter in the parking area and streets;
and vegetation and pet manures in the residential section.
Sungate and Woodland View Area (Test Area No. 3) - This test area
can be classified as an upper middle class residential neighborhood.
The development is about 5 or 6 years old, and has few vacant lots.
The houses of brick masonery range from 1800 to 3000 sq. ft. in
floor area.
Runoff from streets passes through the inlet structures into concrete
storm sewers that subsequently empty into an open channel which
drains the area. This channel is grass-covered and well-kept. Some
scattered shade trees are present in the watershed.
Sheridan Industrial District (Test Area No. 4) - This test area encom-
passes industrial, commercial, and residential uses. Industrial
usage ranges from light to moderate types and includes a concrete
batch plant; a cement block plant; repair shops and pipe storage facili-
ties for the Oklahoma Natural Gas Company; oil field supply firms
with accompanying outside storage; and a trucking company. A large
Sears Roebuck shopping center, part of the Tulsa State Fairgrounds,
grocery stores, gas stations, and drive-in restaurants comprise the
commercial uses. The residential areas consist of single family
housing. Structures are from 15 to 20 years old and most are well-
kept. The main streets through the area are heavily traveled.
Woodward Park Area (Test Area No. 5) - The centroid of this residen-
tial test area is located approximately 20 miles south of downtown
Tulsa. It is in the old section of Tulsa. This watershed is fully
developed and most of the homes are large. Good grass cover exists on
all yards, and the area is thickly covered with large trees.
The drainage of this watershed is from the northeast to the southwest
and empties directly into the Arkansas River. The storm drainage
line passes through a park near the center of the watershed. All of
the drainage basin is sewered by covered channel. The outlet
28
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structure is a 7 ft. x 10 ft. arch, located on the Arkansas River, At
the upper part of the watershed, the size of pipe is 24 in. This in-
creases to 10Z in. before it empties into the 7 ft. x 10 ft. arch about
a quarter of a mile from the river.
Latimer Industrial District (Test Area No. 6) - This test area is
located 2. 0 miles north of downtown Tulsa. It is a mixture of
industrial and residential activity. Industrial operations include a
Dowell Chemical Company facility, a trucking company, a steel
fabrication company, and several auto salvage yards. Associated
with the industrial operations are large areas of open storage. The
houses in the residential portion are old and not well-kept. The area
is drained by a covered channel which starts in the upper reaches as
a 36 in. concrete pipe and ends as a 4 ft. x 8 ft. box culvert.
Methodist Manor (Test Area No. 7) - This test area is entirely residen-
tial. The homes are ten to fifteen years old and they average 1200 to
1600 sq. ft. in floor area. The entire watershed is drained by an
enclosed conduit which has a semielliptical main line.
The sampling site for this drainage shed is located where the semi-
elliptical pipe opens into an unimproved natural channel. At this
location, water stands and is backed up for a distance in the pipe. This
situation causes suspended particles and trash to settle out in the mouth
of the drainage structure, thereby altering the hydraulic capacity of
the channel. During periods of no runoff, the sludge in the bottom of
the pipe can become septic, adding to the pollutional load when runoff
occurs.
Strip-Pit Collection Basin (Test Area No. 8) - The storm drainage
from this test area dumps into an abandoned strip-pit and normally
does not reach a receiving stream as surface flow. The strip-pit has
an overflow (30 in. round concrete pipe) but, except during an excessively
heavy runoff event, no overflow from the pit occurs.
Land use in the drainage basin is primarily residential. Most of the
streets in the residential area are not guttered. Some industrial
activities are located, however, in the upper portions of the basin.
At the sampling site for this area, the same condition exists as for
Test Area No. 7. The flow is restricted and back-up occurs for a
distance in the pipe.
29
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Sunny Slope Addition (Test Area No. 9) - This test area is located
north of downtown Tulsa and is in the Model Cities Area of Tulsa. It
is in a portion of the city that can be classified as the lower socio-
economic class. The environmental conditions in this watershed are
bad. There are large and numerous accumulations of rubbish. The
yards are poorly kept. Structures are dilapidated and near the "Urban
Renewal" stage.
The watershed is small (approximately 64 acres) and well defined. It
is drained by a 48 in. concrete pipe.
Southern Central Business District (Test Area No. 10) - This test
area, is composed of a mixture of commercial and residential land
activities. The upper portion of the drainage basin consists of
office-retail multiple store buildings. Included in the area are several
parking lots. In the central part of the watershed is an expressway
clearance project. Numerous buildings and houses have been torn
down or have been in some stage of demolition during the project. The
approximate area encompassed by this clearance work is 20 acres.
Along the lower reaches and below the expressway project is located an
old residential area.
Greenwood Drainage Shed (Test Area No. 11) - This is the second
largest drainage basin investigated in the study. Most of the area is
in residential use but there are some commercial land activities. Ex-
tensive holdings are devoted to railroads in the upper portion of the
area.
The watershed is directly north of the downtown area and is in the
heart of Tulsa1 s Model Cities area. At least one third of the housing
can be considered in a poor or dilapidated condition. Located in the
test area are urban renewal projects where buildings are being
demolished and the land cleared.
Airport East (Test Area No. 12) - This test area is composed mostly
of open land or runways. The only land activity of major interest is in
a portion of the southwest corner containing support buildings and pads
for aircraft maintenance and repair activities. This relatively small
amount of activity could conceivably produce a significant amount of
"exotic" pollution in the natural drainage stream.
Bolewood Acres (Test Area No. 13) - This test area is residential
and is composed primarily of large tracts on which big, expensive
homes have been built. Each home averages 4 to 5 bedrooms and
30
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3 bathrooms. Almost every home in the lower portion of the water-
shed has a private swimming pool. Approximately 50 homes in the
lower half of the watershed are not connected to a sanitary sewer
and have individual septic systems. The homes in the upper portion
of the test area are connected to a sanitary sewer.
The drainage channel which runs down through the middle of the water-
shed is a 54 in. conduit. This opens into an unimproved natural channel
in the lower quarter of the basin. As the drainage leaves the watershed,
the flow is divided, and one half enters a 66 in. semielliptical conduit.
The sampling site for the watershed was at the mouth of the 66 in.
semielliptical conduit. This is approximately two blocks south of the
divided flow.
Southern Hills Country Club (Test Area No. 14) - The Southern Hills
Country Club is located approximately 5. 5 miles south of downtown
Tulsa. The test watershed encompasses portions of the club's golf
course and some residential tracts that line the perimeter of the golf
course. These residential tracts with their large, expensive houses
are in the upper reaches of the catchment area.
The watershed drains to the northwest. Upon joining flow from adja-
cent areas, the drainage flows to the Arkansas River, which is about
1. 5 miles west of the site.
Several ponds which serve as embellishments to the golf course have
been constructed on the drainage channel through the area. Only during
storm events producing considerable runoff do these ponds overflow.
These small ponds act as "treatment" lagoons and provide some de-
gree of disposal for storm water runoff generated on the site.
Alt Ade Ma Place (Test Area No. 15) - Alt Ade Ma Place is the second
smallest drainage area investigated on this project. This test site is
one of the postwar residential areas in Tulsa and consists of small
frame and brick houses. The normal tract size is approximately 0. 2
acres and the average density is 4. 96 people per acre. The area is
located on the flat alluvial plain of the Arkansas River. The outfall
line for storm drainage consists of a 48 in. round concrete conduit.
31
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TABLE 11
TEST DRAINAGE BASINS AND SAMPLING SITES
Site
No.
Name of Test
Basin
Address of
Sampling Site
Approach to
Sampling Site
Structure at
Sampling Site
1 S; Memorial Ind. Dist.
2 Southroads-Southland
3 Sungate & Woodland View
4 Sheridcin Industrial Dist.
5 Woodland Park
6 Latimer Ind. Dist.
7 Methodist Manor
8 Strip Pit
9 Sunny Slope
10 Central Business Dist.
11 Greenwood
12 Airport East
13 Bolewood Acres
14 Country Club
15 Alt Ade Ma Place
9000 E. 40th Place
3900 S. Toledo
5500 S. Sheridan
6100 E. llth Street
2600 S. Riverside
1800 N. Victor
4100 E. 31st Street
2100 N. Quebec
900 E. 27th North
1400 S. Riverside
500 Woodrow Street
3100 N. Mingo
4600 S. Wheeling
6100 S. Lewis
4300 S. Riverside
Open Channel (Unimproved)
10 x 8 Semielliptical
Open Channel (Concrete)
Open Channel (Unimproved)
102" Concrete Pipe
8x4 Box
5x6 Semielliptical
4x6 Semielliptical
48" Concrete Pipe
66" Concrete Pipe
12 x 10 Semielliptical
Open Channel (Unimproved)
5x6 Semielliptical
Open Channel (Unimproved)
48" Corrugated Pipe
10 x 6 Double Box
Manhole into Semielliptical
8x4 Double Box
10 x 10 Double Box
7x10 Arch
8x4 Box
Mouth of Semielliptical
Mouth of Semielliptical
Mouth of Pipe
10 x 10 Box
Mouth of Semielliptical
10 x 6 Box
Mouth of Semielliptical
4x4 Box
48" Concrete Outfall
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TABLE 12
GENERAL DESCRIPTION OF THE TEST AREAS
Test General
Area Land Use
No. Classification
Specific
Zoning
Classification
Socioeconomic
Class
Remarks
Industrial
Commercial
Residential
Pred. U-4A
Small amount
U-3A
Pred. U-3E
Some U-1C,
U-2B, U-3A
Pred. U-1C
Small amount
U-1B, U-3DH
Light industrial, warehousing, industrial
sales--new industrial development con-
taining little outside storage--large
portion still in construction stage--water
quality should reflect cement company
waste in lower reaches of watershed.
Some upper middle Shopping center with large paved parking
class residential areas--includes drainage .from large
grassy slope (portion of Pan American
Research Laboratories property).
Upper middle
class
Relatively new additions with little tree
cover and well-kept lawns--area swim-
ming pool probably drains into storm
sewer--some commercial activity on
major streets.
-------
TABLE 12-- Continued
Test General
Area Land Use
No. Classification
Specific
Zoning
Clas sif ication
Socioeconomic
Class
Remarks
Industrial
and
Residential
U-4B
U-1C
Go
Residential
Pred. U-1C
Residential
portion: lower
middle class
Upper middle
class--some
lower upper class
--some lower
middle class in
upper reaches
Light to moderate industrial with approxi-
mately 1/3 residential--far upper reaches
drain portion of Tulsa State Fairgrounds--
industrial area is approximately 1/2 old
development and 1/2 new development or
open land zoned for industrial use--con-
siderable amount of outside storage of
industrial products--railway service to
most of area for shipping.
Large old homes — great amount of tree
cover--some small old housing in upper
reaches of water shed--includes some
commercial activity on major streets,
drainage from Woodward Park, Tulsa
Garden Center, and overflow from Swan
Lake.
Industrial
U-4B
Old industrial area with considerable amount
of outside storage--water quality should
reflect waste from trucking firm--lower
middle class residences make up the upper
and eastern reaches of the watershed.
-------
TABLE 12— Continued
Test General
Area Land Use
No. Cla s s if i cation
Specific
Zoning
Classification
Socioeconomic
Class
Remarks
oo
Residential
8 Residential
Residential
10 Commercial-
Office and
Residential
U-1C
U-1C
Pred. U-1C
Traces of
U-4B
3/4 U-3.DH
and remain-
der in U-2A
and U-2B
Upper middle
class
Lower middle
class
Lower class
Some lower
middle class
Postwar addition of mostly three bed-
room frame and brick houses with
medium-sized trees--well-kept area.
Postwar addition of mostly two bedroom
frame and brick houses with medium-
sized tree cover.
Old houses of various sizes, many near-
ing delapidation--ill-kept area residentially
with some commercial activity on major
thoroughfares.
Upper portion of watershed is commercial-
office including multi- story buildings —
middle areas of watershed are largely open
areas with considerable tree cover--these
areas have been cleared by the Tulsa urban
renewal authority for eventual redevelop-
ment--some urban renewal work is still
underway in the area--lower areas of the
watershed are old residential neighborhoods
containing various size houses with great
amount of tree cover.
-------
TABLE 12--Continued
Test General
Area Land Use
No. Classification
Specific
Zoning
Classification
Socioeconomic
Class
Remarks
oo
11 Residential U-1C
and
Commercial
12 Industrial U-4A
and
Commercial
13 Residential U-1A
Lower middle
class
Lower upper
class
14 Recreational
15 Residential U-1C
Lower middle
class
This drainage basin is in the heart of
Tulsa's model city area—mostly small
old frame houses with great amount of
tree cover--some commercial activity
on major streets.
Runways and supporting buildings with
some light industry--considerable open
grassy area.
Non-sewered, newly laid concrete pipe
into unimproved open channel--large lots
with a number of swimming pools--well-
kept lawns.
Southern Hills Country Club--most of
drainage basin includes golf course.
Postwar addition of small 2-3 bedroom
frame and brick houses with substantial
coverage of medium sized trees.
-------
TABLE 13
FEATURES OF THE TEST AREAS
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Physiography
Prairie Plains
Prairie Plains
Prairie Plains
Prairie Plains
Flood and
Prairie Plains
Prairie Plains
Prairie Plains
Prairie Plains
Prairie Plains
Flood Plains
Prairie Plains
Prairie Plains
Flood and
Prairie Plains
Prairie Plains
Flood Plains
Geology
Shale Group
Shale Group
Shale Group
Shale Group
Shale Group
& Alluvial
Basins and
Terraces
Shale Group
Shale Group
Shale Group
Shale Group
Alluvial
Basins &
Terraces
Shale Group
Shale Group
Alluvial
Basins &
Terraces
Shale Group
Alluvial
Basins &
Terraces
Land
Slope
0-5%
0-5%
0-5%
0-5% and
Small Amount
of 6-10%
0-5% and
Small Amount
of 6-10%
0-5% and
Small Amount
of 6-10%
0-5%
0-5%
0-5%
0-5% and
Small Amount
of 6-10%
0-5% and
Small Amount
of 6-20%
0-5%
0-5% and
Small Amount
of 6-20%
0-5% and
Small Amount
of 6-20%
0-5%
Type
Vegetation
Cover
Prairie Grassland
Prairie Grassland
Prairie Grassland
Prairie Grassland
Small Amount of
Alluvial Forest
Prairie Grassland
Prairie Grassland
Prairie Grassland
Prairie Grassland
& Alluvial Forest
Alluvial Forest
fe Upland Woods
Prairie Grassland
Prairie Grassland
Alluvial Forests
& Prairie Grass-
land
Alluvial Forests
fe Upland Woods
Alluvial Forests
Major
Drainage
Basin
Mingo
Joe
Joe
Mingo
Central
Flatrock
Joe
Flatrock
Flatrock
Central
Flatrock
Mingo
Central
Joe
Central
37
-------
SECTION 5
CHARACTERIZATION OF LAND USE
Land use activity within each of the 15 drainage areas was determined
by utilizing the Land Activity File of the Tulsa Metropolitan Area
Planning Commission (TMAPC). A description of the procedure used
to characterize each test area will be given in this section.
The first step in the procedure was to establish the ridge lines of each
drainage basin. This was accomplished by the use of U. S. G. S. quad-
rangle maps (7.5 minute series) and the City of Tulsa Storm Drain
Atlas (1" = 100'). The storm drain pipe network was transposed to
base maps (1" = 600') developed by the TMAPC for a better definition
of the storm, drain system for the test areas.
The second step was to define the drainage areas in such a way that a
computer program could be written to retrieve the land use data from
the file. This was accomplished by outlining each drainage basin on
Land Use Base Maps (1" = 200') of the TMAPC and by utilizing the
appropriate parcel identification overlays. These overlays contain
the census tract, planning block, and planning parcel numbers. The
planning block was the level chosen to define each basin. Appendix F
shows the watershed perimeters and the storm drain system within the
watershed for each of the study areas. After each drainage basin had
been defined by census tract and planning blocks, a program was
written to sum various land use activities within each basin.
Data from the Land Activity File can be retrieved by using several
different controls. The controls are codes that are attached to each
parcel of land. The different codes assigned to each parcel are:
Commercial Statistical Area Code
Industrial Planning District Code
Predominant Use Group Code
Zoning Classification Code
Establishment Activity Code
Establishment Use Group Code
TMAPC normally retrieves land use data once a year for planning needs.
39
-------
The commission retrieves land use data using the Establishment Use
Group Code as its control. The TMAPC also makes a land use retrieval
by study analysis units, using the Zoning Classification Code as the
control.
Land activity retrieval for this project was accomplished by using the
Establishment Use Group Code as the control for summing the various
land activities. The alphanumeric use group code as set up by the
TMAPC is a three digit (1--) numeric code. The first digit of the code
represents a general land use classification. The second and third
digits represent more specific land use activities within the particular
general classes.
The code is an attempt to sort the various land activities into classifi-
cations which are economically or socially compatible. Present
restrictions limit the TMAPC1 s utilization of the code for land use
retrieval to the first two digits of the three digit code. All land activity
data for this study was grouped into the following classifications by the
present retrieval process.
The two digit Land Use Group Code is as follows:
1--Housing (Residential)
100-single family housing
120-two family housing
130-multi-family housing
140-mobile home housing
150-group living
170-not classified
2--Commercial
210-retail and personal service
220-intensive and extensive commercial
recreation
230-business service
270-vacant commercial structure
3--Industrial
310-low or limited nuisance activity
320-wholesale, warehouse, and trucking
activities
340-substantial nuisance activity
350-hazardous or noxious activity (includes
extractive industries)
40
-------
360-non-manufacturing activity
370-vacant industrial structure
4- -Institutional
410-educational
420-health and welfare
430-cultural or social center
440 - gove rnmental
450-philanthropic and non-profit organization
460-church or cemetery
470-military
5--Transporation, Communication, Utility,
and Right-of-Way
510 - transportation
5 20 - communication
530-utility
540-rights-of-way and/or utility easements
550-other utilities, communications, and
sanitary services
6--Open Space and Recreation
610-open space
620-recreation outdoor land
630-recreation outdoor water
640-recreation indoor public facility
7- -Agriculture
710-cropland
720-grazing and improved pasture
730-timberland
740-special farms
8--Unused Space and Accessory Buildings
810-water area
830-marginal land
840-vacant urban land
850-disposal areas
860-accessory buildings
The computer output from the retrieval based on TMAPC's Establish-
ment Use Group Code gives the following reliable information:
Residential Land Activity
Household units
41
-------
Acres
Density (household units/residential area)
Commercial Land Activity
Acres
Total number of establishments
Number of parcels
Industrial Land Activity
Acres
Floor area
Public, Quasi-Public, Utilities, Open Space,
and Agriculture
Acres
The summation of the above land use activities should give the total
area within each drainage shed minus the amount of land devoted to
roads and streets. Only the land devoted to large expressway systems
has parcel numbers assigned.
The totals of the land activities within each test area had to be adjusted
to account for the streets and for the divisions caused by the true ridge
lines. The total amount of land devoted to streets was determined by
measuring the length and width of the streets as shown on the 1" = 600'
base maps of the TMAPC. Portions of the large tracts divided by
ridge lines were either added or deleted by measuring the portion
of land in question on TMAPC's 1" = 200' Land Use Base Maps.
The adjusted Land Use Activities by major groups are summarized
in Tables 14 and 15. The population, drainage, and street characteristics
are shown in Table 16, Table 17, and Table 18, respectively.
42
-------
TABLE 14
LAND USE ACTIVITIES IN ACRES BY MAJOR USE GROUPS
WITHIN THE FIFTEEN TEST AREAS, TULSA, OKLAHOMA
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Acres
Res.
29
84
311
234
268
120
128
109
30
33
367
0
160
71
52
Com.
50
62
5
179
10
12
3
13
7
32
16
0
0
0
0
Ind.
325
1
0
172
1
129
0
10
0
0
41
3
0
0
0
Inst.
1
0
23
53
33
2
18
3
0
4
15
0
6
0
1
Trans.
10
4
0
28
15
9
0
7
0
1
3
103a
0
0
0
Open
Space
0
68
19
8
50
0
0
0
0
0
107b
0
172
0
Unused
Space
170
2
88
50
30
11
1
9
3
32
28
0
5
0
5
Arterial
Streets
48
15
13
55
20
8
3
30
7
39
48
0
11
12
0
Other
Streets
53
41
92
159
80
77
44
30
17
65
292
0
31
8
16
Total
686
277
550
938
507
368
197
211
64
206
815
213
212
263
74
103 Acres of airport runways and supporting paved areas.
107 Acres of grassland adjacent to runways.
-------
TABLE 15
PERCENTAGE OF LAND DEVOTED TO MAJOR USE GROUPS
IN THE FIFTEEN TEST AREAS, TULSA, OKLAHOMA
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Percent
Res.
4.23
30.32
56.54
24.94
52.85
32.60
64.97
51.66
46.86
16.02
44. 99
0. 00
75.46
26.99
70.25
Com.
7.28
22.38
0.91
19-08
1.97
3.26
1.52
6. 16
10.93
15.53
1.96
0.00
0. 00
0. 00
0. 00
Ind.
47.35
0. 36
0.00
18.34
0. 20
35. 05
0. 00
4. 74
0.00
0.00
5.03
1.41
0. 00
0. 00
0. 00
Inst.
0. 15
0. 00
4. 18
5.65
6. 51
0. 54
9. 14
1.42
0.00
1. 94
1. 84
0. 00
2.83
0. 00
0.00
Trans.
1.46
1.44
0. 00
2. 98
2.96
2.45
0. 00
3. 32
0. 00
0.49
0. 37
48.36
0. 00
0.00
0. 00
Open
Space
0.00
24.55
3.46
0.85
9.86
0. 00
0. 00
0. 00
0.00
0.00
0.61
50. 23
0. 00
65.39
0.00
Unused
Space
24. 77
0. 72
16. 00
5. 33
5.92
2. 99
0.51
4. 27
4.69
15. 53
3. 44
0. 00
2. 36
0. 00
6.76
Arterial
Streets
6. 99
5.42
2. 36
5.86
3. 94
2. 17
1. 52
14. 22
10. 93
18. 93
5.88
0. 00
5. 19
4. 56
0. 00
Other
Streets
7.72
14.80
16.73
16. 95
15. 78
20. 92
22. 33
14. 22
26.55
31.55
35. 80
0. 00
14.62
3. 04
21.62
-------
TABLE 16
POPULATION CHARACTERISTICS OF THE FIFTEEN TEST AREAS
Ul
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Total
Living
Units
100
369
1147
1122
1765
501
616
715
267
425
3396
0
168
77
282
Population
350
1100
3925
3625
4525
1200
2275
2400
875
885
2800
0
500
250
830
Population
Estimator
People /Unit
3. 50
3. 00
3.42
3.23
2.56
2.37
3. 70
3.35
3. 26
2. 08
2. 30
0. 00
3. 01
3.01
2. 95
Residential
Area
Acres
29
84
311
234
268
120
128
109
30
33
367
0
160
71
52
Residential Total Average
Density Area Density
People /Res. Acre Acres People/Acre
12. 07
13.09
12.62
15.49
16.88
10. 00
17.77
22. 02
29. 17
26. 82
21. 25
0. 00
3. 13
3. 52
15. 96
686
272
550
938
507
368
197
211
64
206
815
223
212
263
74
0.51
4, 04
7. 13
3.86
8. 93
3. 26
11.55
11. 37
13. 67
4. 30
9. 57
0. 00
2. 36
0. 95
11. 22
-------
TABLE 17
DRAINAGE CHARACTERISTICS OF THE TEST AREAS3
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
A
686
272
550
938
507
368
197
211
64
206
815
223
212
263
74
L
9050
4230
6890
9260
11200
2170
4500
4800
2600
6350
9000
5710
7840
6400
2700
Lc
6000
2040
3000
4800
4800
3600
2100
1800
1380
3300
4200
2400
2600
3480
1600
H
113
92
186
126
140
91
85
95
60
140
162
58
140
171
30
Sc
0. Oil
0. Oil
0. 009
0. 010
0. 013
0. 009
0. 013
0. 013
0. Oil
0. 032
0. 007
0. 007
0. 015
0. 014
0. 012
SL
3. 19
3.48
3.82
2.89
3.29
2. 19
2.89
1.67
1.55
2. 26
1.83
0.75
4.60
4.25
0.78
C
30
55
27
51
30
24
32
37
31
74
41
46
23
11
38
FF
0. 83
2.85
2. 66
1.77
0. 96
1. 24
1. 94
2. 84
1. 47
0.82
2.01
1.68
1. 37
0. 95
1. 26
GxlO2
1. 07
0. 95
1.41
1. 00
2. 16
0. 55
1. 52
2. 99
3.61
4.69
2. 24
4. 53
2. 54
2. 24
3. 21
Rn
. 034
. 033
. 054
. 029
. 071
. 012
. 044
. 050
. 056
. 106
. 041
. 034
. 117
. 095
. 025
Legend:
A = Area, acres.
L = Length of the main stream, feet.
LC = Length of the main stream from the
sampling site to the point nearest
area centroid, feet.
H = Fall of the watershed, feet.
Sc = Average main channel slope, feet
per foot.
S^ = Average land slope, percent.
C = Impervious cover, percent.
FF = Form factor = 43, 560 A/ (Lc) ,
dimensionless.
G = Geometry number (G)
= ' ' ' ' , dimensionless.
(43, 560) (A) (Si)
Rn = Relief number -
. dimensionless.
-------
TABLE 18
STREET CHARACTERISTICS WITHIN THE FIFTEEN TEST AREAS
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Total Area
of Streets
and
Easements3"
Acres
101
56
105
2.14
100
85
47
60
24
104
. 340
0
42
20
16
Estimated
Area
of
Pavement
Acres
65
32
56
124
56
46
24
39
10
104
179
0
24
14
10
Arterial
Streets
Acres Miles
48
15
13
55
20
8
3
30
7
39
48
0
11
12
0
3.43
1.21
1.07
4. 52
1.63
0.62
0.26
2.48
0.60
3.21
4.00
0.00
0.88
1. 14
0.00
Other
Streets
Acres
53
41
92
159
80
77
44
30
17
65
292
0
31
8
16
Milesc
8.03
6.20
13.80
23.88
14.69
11.62
6. 58
4.49
2.51
9.78
46.66
3. 39
4.70
0. 93
1.64
Ratio of Streets to Total Area
Acres/Acre
Arterial
0.070
0.055
0.024
0.059
0.039
0.022
0.015
0.014
0.011
0.019
0.059
0.000
0.052
0.046
0.000
Other
0.077
0. 151
0. 167
0. 169
0. 158
0.209
0. 223
0. 142
0.266
0.316
0.358
0.000
0.146
0.030
0. 216
Miles/Acre
Arterial
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0050
0044
0019
0048
0032
0017
0013
0012
0009
0016
0049
0000
0042
0043
0000
Other
0.012
0.023
0.025
0.025
0.029
0.032
0.033
0.021
0.039
0.047
0.057
0.015
0.022
0.004
0.022
, Calculated from land use retrieval information.
Calculated by measurements taken from land activity maps.
cEstimated by assuming an average street width of 55 feet (this includes pavement
and easements).
-------
SECTION 6
ENVIRONMENTAL CONDITIONS
In 1968 the Tulsa City-County Health Department conducted a Commu-
nity Block Survey in Tulsa. The purpose of the survey was to delineate
the general environmental conditions of the Tulsa area. An analysis of
the data resulting from this survey provides a method of locating environ-
mental conditions of communicable disease within a specific community.
Also, with this data and additional census block data, a community can
be stratified into socioeconomic areas.
The environmental factors included in the survey were land use, exterior
housing quality, water supply, human waste disposal, refuse storage,
rubble accumulations, junked cars, dilapidated sheds, vacant lot sani-
tation, poor drainage areas, vector harborage, and the presence of
livestock, poultry, and dogs.
Definitions of Environmental Factors
Environmental conditions or factors have different meanings to various
groups and agencies. For example, the TMAPC has many business and
commercial categories which it classifies into several use groups. The
health agencies, on the other hand, normally make only two classifi-
cations for business and commercial activities: food and non-food.
For the most part, the survey followed the procedures set forth in the
manual "Community Block Survey and Socioeconomic Stratification"
(9) published by the Public Health Service. Below are the definitions
of the data items collected by the survey.
Land Uses - This factor is divided into nine classifications which are
standard in Public Health Service procedures. These classifications are:
Residential
Business and Commercial
a) Food
b) Non-food
Industrial
a) Food processing
b) Non-food manufacturing
Transportation Services
Public, Cultural, Educational, and
Related Uses
49
-------
Parks and Recreational
Utilities
Agriculture
Miscellaneous
The business and commercial classification and the industrial classifi-
cation have each been divided into two subclassifications, because food
using and processing establishments produce organic wastes. These
wastes usually present a greater public health problem than waste
materials from other types of firms.
Exterior Housing Quality - This factor is divided into three categories:
good (sound), fair (deteriorating), and poor (dilapidated). The deteriora-
tion of the exterior of residential structures is classified and used as a
basic factor in stratifying a community into socioeconomic frames. The
condition of housing is also a basic environmental sanitation factor.
A residential structure should have at least 150 square feet of floor space.
The window space should equal at least 10 percent of the floor area. A
house is classified as sound if it is free from decay and structurally safe.
The exterior walls are level and plumb. The surface of a good structure
is composed of an acceptable material as judged by recognized building
code standards.
Human Waste Disposal - When untreated human waste is exposed to the
elements, to a water source, to animals, or to insects, a human waste
disposal deficiency exists. Examples of exposed human waste are out-
door privies, improperly operated septic tanks, cesspools, and
frostproof toilets.
Refuse Storage - Refuse is solid waste including garbage and rubbish.
Garbage consists of all putrescible material except body wastes. Rubbish
is non-putrescible waste and includes debris, tin cans, bottles, paper,
grass cuttings, paper boxes, short pieces of lumber scraps or other
building materials, and tree limbs not over 3 feet in length. No piece
classified as rubbish weights over 50 Ibs.
Suitable refuse storage exists on a premise if all refuse (garbage and
rubbish) is stored in a container which meets the requirements of local
ordinances and authorities.
Rubble Accumulations - Solid waste which is larger and heavier than
rubbish is classified as rubble. Examples of rubble are: large brush-
wood, large and/or long cardboard boxes, large and/or heavy yard
trimmings, discarded fence posts, bed springs, large furniture, and
50
-------
water heaters. Improper rubble storage exists when any rubble is on
a premise.
Junked Cars - An abandoned automobile is a special category of rubble.
A junked car is improperly stored if it is outside a conforming structure
anywhere in a residential area or in a business or commercial area
not zoned for this type of storage.
Dilapidated Sheds - Outbuildings that have deteriorated past their intend-
ed usefulness or original purpose are considered to be dilapidated sheds.
Their structures are decayed and not weatherproof. A shed of this type
is a fire hazard and a rodent harborage. It also detracts from the
appearance of the premises and the neighborhood.
Vacant Lot Sanitation - A vacant lot in an urban community is an undevel-
oped lot which has an area the size of other lots which are developed in
the neighborhood. If there is no indication of a standard size, a street
frontage of 100 linear feet per vacant lot is used to estimate the number
of vacant lots in a block. A weeded vacant lot is one that has pollinating
weeds or brush and weeds over 12 inches high. No sanitary deficiencies
must be present. A lot with these conditions is classified as a fair or
moderate vacant lot. A vacant lot which has any refuse, trash, rubble,
or carrion on its premises is classified as a poor vacant lot.
Drainage - The area is rated as to the existence and form of its drainage
net. Poor drainage exists when the surface has depressions which
hold water for three or more days following a rain. The channels are
classed as either open channels or enclosed conduits, such as storm
sewers. Open channels are further classified as to type of lining, such
as concrete or earthen.
Presence of Livestock, Poultry,and Dogs - The type and number of
livestock, the number of poultry, and the number of dogs observed in
the area survey are recorded. Dogs are further classified as controlled
or stray. The "controlled" classification is assigned to dogs which are
kept in an enclosure.
jiurvey Procedures - The procedure followed in gathering the data was
a block by block "windshield" survey. All housing conditions and
environmental deficiencies were recorded and then coded on TMAPC's
Land Use Maps. These data items were evaluated and summarized by
block and census tracts.
The block summaries were recorded on computer cards and stored.
This information was thus available for other studies and was used to
51
-------
categorize the 15 test areas in this project.
The environmental conditions or variables within the test areas were
determined by summing the block totals for the particular drainage
basins. Table 19 presents these totals for each of the 15 test areas.
Normal socioeconomic stratification by the Public Health Service is
accomplished by evaluating and utilizing slow-to-change factors such
as the housing conditions, housing prices, family incomes, and
education level of adults within the community of interest (9). The
degree of deterioration of the exterior surfaces of residential structures
is a consistent, reliable indicator of the socioeconomic status--the
higher the density, the lower the indicated socioeconomic status.
The procedure followed in stratifying a community into socioeconomic
levels involves the determination and weighting of three or more
"indicators. " The indicators used are: (1) housing condition, (2)
housing price, (3) crowding, (4) family income, and (5) education level.
This procedure is not valid for large areas. Large areas have to be
subdivided to enable the groupings of existing housing and other
environmental conditions into uniform classes. Also, a more complete
evaluation of socioeconomic areas should involve physical health
standards and a knowledge of the culture of the local people.
Environmental Index
Since the above procedure is not applicable to large areas and could
not be extended for use in commercial or industrial areas, a method
was devised by the author of this study for determining the general
environmental conditions of the fifteen test areas. An Environmental
Index (El) was calculated for each area, as follows:
Environmental Index (El) = f (housing condition, vacant lot
condition, parcel deficiencies) (6-1)
Assuming that the parcel deficiencies should be weighted
more heavily than the housing conditions and that the housing
conditions should be weighted more heavily than the vacant
lot conditions:
El = 2A + B -f 3C (6-2)
52
-------
Where: . Total Housing Structures
G + 2F + 3P
Note: G = no. of good houses
F = no. of fair houses
P = no. of poor houses
•n_Total Vacant Lots
G + 2F + 3P
Note: G = no. of good vacant lots
F = no. of fair vacant lots
P = no. of poor vacant lots
,-._Total Structures - Total Deficiencies
Total Structures
Note: Total deficiences include the
sum total of refuse, burners,
rubble, lumber, old autos,
poor sheds, livestock, poultry,
and privies.
The above three factors (A, B, and C) are a measure of the general
housing condition, the vacant lot condition, and the parcel deficiencies,
respectively. Factors A and B vary from a low of 0. 33 to a high of
1. 00. Factor C varies from a negative number to 1. 00. The smaller
numbers indicate poor environmental conditions.
Applying the above formula will result in an Environmental Index that
varies from a negative number to a maximum of 1. 00. A value of 1. 00
denotes an area of all good houses, all good vacant lots, and no parcel
deficiencies.
Not included in the above index are several other factors that, if used,
would result in a better measure of the "general environmental condi-
tion of an area. " Such items are: air pollution sources; density of
population and structures; point sources of water pollution; parks;
noise level; and traffic volume. If these data items were available and
each could be expressed as a weighted numerical coefficient, a better
El could be developed. Factor analysis was used in an attempt to
refine the El; results are discussed in Section 10.
53
-------
Applying the above formula to the data of Table 19. an El for each of
the test areas was calculated. Table 20 presents these calculations
with the resulting El. Table 21 gives a percentage breakdown of the
various categories shown on Table 19.
54
-------
TABLE 19
NUMBER OF HOUSING AND PARCEL DEFICIENCIES WITHIN
THE FIFTEEN TEST AREAS
Test
Area
No.
Housing
Condition
Total
No. Good Fair Poor
Total
Units
Bus. Struct.
Food Other
Vacant Lots
Total
No. Good Fair Poor
Deficiencies
Bur- Rub- Lum- Old Poor
Refuse ners ble ber Autos Sheds
-------
TABLE 20
CALCULATION PROCEDURE FOR THE
ENVIRONMENTAL INDEX (El) OF THE TEST AREAS
en
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
1
Total
Housing
242
369
1147
1200
1413
476
599
674
247
267
3130
0
168
77
265
Housing3"
2
1G+2F
+3P
244
369
1147
1201
1415
705
599
676
358
319
6872
0
168
77
256
A^
0.99
1.00
1.00
1.00
1.00
0.68
1. 00
1. 00
0.70
0.84
0.46
1. 00
1. 00
1.00
Vacant Lotsa
4 5
Total Vac. 1G+2F
lots +3P
308
0
85
6
16
18
7
7
23
174
197
0
8
1
3
308
0
102
6
16
29
7
7
43
180
350
0
8
1
3
6
B
1. 00
1.00
0.83
1. 00
1. 00
0.62
1. 00
1. 00
0. 53
0. 97
0. 56
n. a.
1. 00
1. 00
1. 00
Parcel Deficiencies
7 89
Total Total 7-8
Structures Def.
367
418
1155
1466
1466
530
601
687
259
484
3364
0
170
77
269
1
3
1
423
29
277
27
259
307
35
4501
0
10
0
77
366
415
1154
1043
1437
253
574
428
-48
449
-1137
0
160
77
192
10
C
1. 00
0.99
1. 00
0.71
0. 98
0.48
0. 96
0.62
-0. 19
0. 93
-0. 34
n. a.
0.94
1. 00
0. 71
El
11
2A+B+3C
6
1. 00
0. 99
0. 97
0. 86
0.99
0. 57
0. 98
0. 81
0. 23
0. 91
0. 08
1. 00d
0. 97
1. 00
0.86
aG=Good F=Fair P=Poor
bA=Housing Index (HI)
jNot applicable
Test area no. 12 was assumed to have an El of 1. 00
-------
TABLE 21
ENVIRONMENTAL CONDITIONS OF THE FIFTEEN TEST AREAS
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Housing
Percent
Good Fair Poor
99. 2 0. 8 0. 0
100.0 0.0 0.0
100. 0 0.0 0.0
100. 0 0. 0 0.0
99.9 0.1 0.0
60.3 31.3 8.4
100.0 0.0 0.0
99.7 0.3 0.0
60.7 32.5 6.8
83.1 14.2 0.7
21.0 38.5 40.5
0.0 0.0 0.0
100.0 0.0 0.0
100.0 0.0 0.0
100. 0 0. 0 0. 0
HIa
.99
1. 00
1. 00
1. 00
1. 00
.68
1. 00
1. 00
. 70
.84
•46H
d
n. a.
1.00
1. 00
1. 00
Refuse
0. 000
0. 000
0. 000
0. 308
0. 027
0. 329
0. 051
0. 920
1. 700
0. 114
2. 370
0. 000
0. 028
0. 000
0. 460
Parcel Deficiencies
Average Deficiencies Per Acre
Burners Rubble Lumber Old Autos Poor Totalb EIC
Sheds
0.000 0.000 0.000 0.000 0.000 0.001 1.00
0.000 0.000 0.000 0.000 0.000 0.011 0.99
0.000 0.000 0.000 0.000 0.000 0.033 0.97
0.095 0.035 0.005 0.007 0.000 0.450 0.86
0.016 0.012 0.004 0.002 0.000 0.057 0.99
0. 274 0. 060 0. 027 0. 030 0. 008 0. 778 0. 57
0.051 0.035 0.000 0.000 0.000 0.137 0.98
0.204 0.052 0.019 0.028 0.004 1.230 0.81
1.480 0.810 0.265 0.109 0.390 4.960 0.23
0.053 0.005 0.000 0.000 0.000 0.199 0.91
2.290 0.420 0.140 0.170 0.115 5.660 0.08
0.000 0.000 0.000 0.000 0.000 0.000 1.00e
0.009 0.005 0.005 0.000 0.000 0.047 0.97
0.000 0.000 0.000 0.000 0.000 0.000 1.00
0.392 0.135 0.013 0.013 0.013 1.040 0.86
aHousing index (HI)
Total deficiencies per acre including fair and poor
Environmental index (El)
Not applicable
eTest area no. 12 was assumed to have an El of 1. 00
vacant lots.
-------
SECTION 7
SAMPLING INSTRUMENTS AND METHODS USED
The collection of storm water runoff samples required the use of
several different types of instruments and methods. The methods and
instruments used are described in the following:
Sampling Equipment
Standard procedures for manual sampling (grab sampling) were used
when baseline samples or storm water runoff samples were collected.
The bacteriological samples were collected in sterile plastic bags. The
samples for chemical analysis were collected in one-half gallon plastic
jugs.
A stationary, automatic-sampling method was used when a time series
of samples was desired. The sampling apparatus used was unique. It
was fabricated locally from commercially available components. The
assembled device consisted of a peristaltic tube pump, inclined sequen-
tial sample container, voltage inverter, 12-volt battery, sampling
probe, pressure diaphragm box, and pressure recorder. All of the
components except the sampling probe and pressure box were enclosed
in a semi-portable shelter which was secured against pilferage.
Shown schematically in Figure 6 is the mechanical arrangement of parts.
The wiring diagram and parts list are shown in Figure 7. Figures 8 and
9 consist of detailed drawings of the inclined sequential sample container.
Various views of the sampling equipment and installations are shown in
Figures 10 through 15.
The inclined sequential sample container and overflow jug are connected
to a peristaltic tube pump with "Tygon" tubing and a polyethylene quick
disconnect. The inlet side of the tube pump is connected to a length of
polyethylene tube which is inside a lightweight aluminum conduit. The
aluminum conduit is also the float arm which activates the switch
mechanism.
The switch-float mechanism consists of a polyethylene foam float
connected to a length of aluminum conduit which is hinged at the top
of the storm drainage structure. Attached to the aluminum conduit
arm is a small micro-switch which is activated by a small metal arm
59
-------
FIGURE 6
SCHEMATIC DIAGRAM OF STORM WATER SEQUENTIAL SAMPLING EQUIPMENT
COLE-FARMER MASTERFLEX
TUBE-PUMP
INCLINED
SEQUENTIAL
SAMPLER
TYGON
SAMPLING TUBE
VOLTAGE
REGULATOR
SWITCH
ALUMINUM CONDUIT
SWITCH
ADJUSTMENT
POLYPROPYLENE PICK-UP TUBE
POLYETHYLENE FLOAT
— PRESSURE
LINE
L— FOXBORO WATER PRESSURE
RECORDER
VOLTAGE INVERTER
12 VOLT
MARINE TYPE
BATTERY
CUTAWAY OF TYPICAL DRAIN
STRUCTURE
-------
•
R2
K) **>S-I
n „,
0
ARMATURE
FIELD
REF.
DESIGN
II
Bl
MTI
SI
Kl
Rl
R2
CRI
CRZ-CR9
QUAN.
8
PARTS LIST
PART NUMBER
' DESCRIPTION
Ttrfldo Power lrt¥«rl«r,l2VDC Input- 120 VAC Output, Allied No 2lf4499
I2VDC flotttry
Cde-Ponw Maiterften Tub* Pump, Model No. 7O1S
Cherry Electric Spot, ISA At I25/23OV AC, Switch
PR7DY PuMer Brumfitld, RtloylZVOC
470 OHM 10% Ruiitor
200 OHM lOOWott Rheostat, Ohmitt No. 0452
IN/53 Diede
IN 2069 Otode
REF.
DESIGN
01
02
Jl
PI
J2
P2
QUAN.
,
1
1
t
I
1
1
I
1
PART NUMBER
DESCRIPTION
2N2I56 Tronsiitor
2N2560 Tromittor
Two Prong AC Rtceptoclt - Port of 11
Two Prong AC Plug
S- 240606, 6 Pin Connector, Cinch Jonei
P-406 DB, 6 Pin Plug, (PortofMPO
CU-726 Bud Cho»it
870 Terminal Strip, H.H. Smith
905 Dial Plot* , Woldon
FIGURE 7
WIRING DIAGRAM AND
PARTS LIST OF PUMP UNIT
-------
FIGURE 8
INCLINED SEQUENTIAL SAMPLE CONTAINER
IN)
•'/V MARINE PLYBOARD (Not*: Top, Bottom, and
1 ' , ,. ,,
W'lD.
W i.o.
t i I I/ 1
I-O— -O— — O— — O— — O—
1 ' 1 1 1 1
r 1—
1
-?-
TOP VIEW
1
_<
M
ALUMINUM ANGLE
INLET
1
4
'_s
7
1
1*
1
1
1
1
1
1
l_
1
1
1
1
1
!
i
i
i
i
i
t
i
i
t ,
\
Ji
M
M
x-r
!/
//
i1'
i
k
u
JS
i
%
1
1
^ i
pH
-f ' '
' \ t
t u
1
1
t
1
1
1
ll
/
rt"^
LJ L
* * - *
7
^
AI
i
n
H
f
U
OUTLET END VIEW
-------
FIGURE 9
DETAIL PLANS OF INCLINED SEQUENTIAL SAMPLE CONTAINER
OJ
minum ongl« '/» « V. '/•"• 16"
© MIDDLE SHELF VIEW
« " e
f ' *
* . 1
9 I 8
I1
o
I:
•Si
8
8
I
I S J
t S
&
ft/
a
d
O
-------
I'KIM'CMTV Uf U.S. CO*
rwcji
u.a. nerr. nr
FIGURE 10.
Sampling equipment- -from left to right:
overflow jug, inclined sequential sample
container pump and control unit, and
12VDC marine battery
FIGURE 11.
Bottom of enclosure showing pressure
recorder, overflow jug, and inclined
sequential sample container
64
-------
FIGURE 12.
Top of sampling probe
showing hinge box fastened
to top of drainage structure
with "on" switch and switch
arm
FIGURE 13. Sampling probe float and pressure
box
65
-------
FIGURE 14. Equipment enclosure and sampling
probe located at sampling site for
Test Area No. 3.
FIGURE 15.
Service truck, enclosure,
and sampling probe at
sampling site for Test Area
No. 10.
66
-------
extending down from the hinge.
As the storm water flow lifts the float, the micro switch activates the
relay, the pump turns on, and the sampling starts. With this arrange-
ment, it was possible to collect separate bacteriological samples
and have each sample composited over a predetermined time period.
Five such "sampling stations" were fabricated and used on the project.
The principle of operation of the inclined sequential sample container
is very simple. As the water is lifted by the peristaltic pump and
enters the inlet side of the container, the sampler composites an amount
of water into the first bottle, which is a 60 ml sample bottle, until it is
full. The water then travels up the inclined tube to the next bottle,
which is a 2000 ml chemical collection bottle, and water is composited
until it too is full. This sequence of filling the polyethylene bottles
is repeated until all the bottles in the sequential sample container are
filled. Once this container is full, the water is then composited in an
air vented 5 gallon capacity overflow bottle.
It is possible to collect a series of separate bacteriological and chemi-
cal samples each composited over a given time period according to
flow rate and bottle size. The only mixing that occurs involves the
amount of water displaced in the air vent tube as the sample moves up
the incline due to the pressure differential between bottles. The pres-
sure differential is a function of the slope of the inclined tube and can
be kept small by selecting an air vent tube of small inside diameter.
Below is a breakdown of the unit cost of the stationary automatic
sampling station used on the project.
Item Cost
12VDC Marine battery $ 25. 00
Voltage inverter 47. 00
Tube pump 83. 00
Pump motor control voltage regulator, relay, and switch 30. 00
Inclined sequential container 26. 00
Tubing, float, float arm, float arm hinge, and wire 15. 00
Enclosure, chain, lock 30. 00
Pressure recorder 213. 00
Pressure diaphragm box 65. 00
Pressure line and connectors 4. 00
Labor: Assembly time of components--15 hours at
$10. 00/hour (includes overhead) 150. 00
67
-------
Installation time in field at sampling sites--4
hours at $10. 00/hour (includes renting of
necessary equipment for installation) 40. 00
Total unit cost of sampling station $728. 00
The number of drainage sheds investigated made it imperative that
more than five drainage areas be sampled during each runoff period.
Therefore, three portable automatic sampling systems were utilized.
Pumps and sample containers in these systems were housed in small
plyboard boxes which were placed at the sampling sites after the
rainfall events started.
Runoff Sampling Methods and Procedures
The 15 drainage sheds were originally divided into three groups of 5
test areas. Each group was located within the same general area to
expedite sample collection. Samples were collected at each site during
each quarter of the "water year" or annual cycle of rainfall. The
planned sampling schedule was not rigorously followed throughout the
entire project because of the lack of rainfall and runoff during the dry
months.
The five sampling stations and instruments were placed at sites in
Group A in September, and samples were collected at these sites during
September and October 1969. In November the sampling stations were
moved to sites in Group B; they were subsequently moved to Group C in
January. In April 1969, it was concluded that the 5 semi-stationary
automatic sampling stations should remain at these sites for the re-
mainder of the project.
To obtain composite samples at the other ten sites, 3 portable plyboard
instrument enclosures were fabricated to house the sampling gear. The
instruments were normally placed out after the start of the rainfall to
operate at the beginning of the runoff period. The composite time could
be adjusted to have a period of "pump-on time" and a period of "pump-
off time". The sample containers in the three portable enclosures
could be changed to obtain a set of time series composite samples during
runoff periods.
Bacteriological samples were collected in sterile plastic bags. The
sampling sequence for the bacteriological samples was: one sample
when the pump was placed in operation, another sample when the
68
-------
11
composite jug was changed, and the third sample when the pump and
enclosure were retrieved from the site.
During the course of the project, "grab" samples were collected when
more samples were needed from a particular drainage shed. "Baseline
samples were also collected by the "grab" sampling procedure. Vandals
hampered the operation of the project. Several of the semi-stationary
sampling stations were broken open and some of the equipment
damaged. This caused important data losses on some of the watersheds.
The biggest problem was obtaining stage readings and velocity measure-
ments of the runoff flows. Originally, pressure recorders used on the
project were calibrated for 120 inches of water at full scale.
The initial hydrograph records produced at the sites utilized only a
fraction of the chart scale. Therefore, it was necessary to recalibrate
the pressure recorders to obtain more sensitive readings. In February,
the pressure recorders were recalibrated to obtain 60 inches of water
at full scale.
Since only five recorders and pressure diaphragm boxes were purchased
for the project, it was necessary to relocate these instruments during
the project period. Stream flow hydrographs were only obtained from
several of the test areas investigated.
Laboratory Methods and Procedures
After the storm water runoff samples were obtained at the field samp-
ling sites, they were transported to the laboratory for analysis. The
samples were stored and analyzed in accordance with Standard Methods
for the Examination of Water and Waste Water, Twelfth Edition (10).
The first action was to divide the samples into two portions and to "fix"
and store one portion for future analysis. The second portion was used
for BOD and bacteria analysis. Bacteriological samples were examined
for total coliform, fecal coliform, and fecal streptococcus by the mem-
brane filter (MF) technique with the use of M-Endo, MFC, and KF
Streptococcus media, respectively.
Analyses for Total Organic Carbon (TOG) were performed by the Civil
Engineering Department, University of Arkansas. Preceding the ship-
ment of these samples to the University of Arkansas, the samples were
"fixed" with sulfuric acid for preservation. The shipment, normally
by bus, was accomplished on the day of collection. Analysis was
69
-------
performed with, the use of a Beckman TOC Analyzer (Model 915).
Listed below are the various pollution parameters measured on each
sample.
Bacteriological
Total Coliform (T. Col. )
Fecal Coliform (F. Col. )
Fecal Streptococcus (F. Strep. )
Organic
Biochemical Oxygen Demand (BOD)
Chemical Oxygen Demand (COD)
Total Organic Carbon (TOC)
Nutritional
Organic Kjeldahl Nitrogen (N)
Soluble Orthophosphate (PO4)
Solids
Total Solids (TS)
Suspended Solids (SS)
Dissolved Solids (DS)
Volatile Suspended Solids (VSS)
Volatile Dissolved Solids (VDS)
Other
pH
Chloride (Cl)
Specific Conductance
The number of reliable measurements of each parameter for each test
area is shown in Table 22. Many more observations were made than are
shown in the table, but a number were discarded as unreliable due to
poor analytical results. Table 23 shows the number of samples
collected from each test area by event number and date.
70
-------
TABLE 22
NUMBER OF RELIABLE OBSERVATIONS OF EACH PARAMETER
FROM EACH TEST AREAa
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Total
a
Parameter
Y!
32
20
36
42
45
15
38
13
16
33
25
29
13
17
14
388
Legend:
Y2
16
15
27
44
50
14
28
11
15
33
22
27
15
18
22
357
Y3
33
25
44
45
49
15
49
13
16
30
25
29
23
18
22
436
Y4
30
26
39
44
47
15
37
13
13
32
26
28
28
18
21
417
Symbol
Yl
Y3
Y4
YS
Y6
Y5 Y6 Y? Y8
17 14 17 17
16 11 16 16
31 28 31 31
44 34 29 29
49 36 38 34
15 13 15 15
26 22 26 26
13 13 13 13
15 11 15 15
31 23 26 26
26 20 26 26
28 23 28 28
19 17 19 19
18 17 18 18
14 12 14 14
362 294 331 327
Parameter
Total coliform
Fecal coliform
Fecal streptococcus
BOD
COD
TOG
Y9
30
26
39
39
43
15
41
13
15
30
26
28
28
15
18
406
Y^ Organic Kjeldahl nitrogen
Y8
Soluble orthop'hosphate
Symbol
Y10
30
26
39
39
43
15
41
13
15
30
26
28
28
15
20
YH
29
25
39
39
41
15
39
13
15
30
26
28
28
15
20
408 402
Symbol
•y
Q
YIO
Y1Z
Yl3
Y14
Yl5
Y16
Yl2 Y13 Y14
30 30 36
26 24 26
39 42 48
39 39 44
43 40 49
15 15 15
41 41 49
13 13 13
15 15 15
30 29 31
26 26 26
28 28 28
28 28 28
15 14 18
17 16 21
405 396 447
Parameter
Total solids
Dissolved solids
Volatile dissolved
Suspended solids
Volatile suspended
pH
Chloride
Y15
30
26
48
36
32
15
43
13
15
24
26
28
28
11
14
389
solids
solids
Y16
17
16
31
25
31
15
26
13
15
24
26
28
19
11
6
303
Specific conductance
-------
TABLE 23
NUMBER OF SAMPLES COLLECTED FROM EACH
TEST AREA BY EVENT NUMBER
Event
No.
Date
Test Area No.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Total
1
2
3
4
5
6
7
8
9
10
11
12
*a
13
*!..
14
15
16
17
18
19
20
21
*
22
23
24
25
26
27
•£
28
29
30
Sept. 23
Oct. 5
Oct. 9
Oct. 16
Nov. 2
Nov. 10
Nov. 15
Nov. 26
Dec. 18
Dec. 27
Jan. 15
Jan. 29
Feb. 11
Feb. 20
Mar. 12
Mar. 23
Apr. 13
Apr. 16
Apr. 26
May 6
May 15
May 24
June 8
June 11
June 12
June 13
June 14
June 17
June 23
June 24
July 30
July 31
Aug. 14
Aug. 15
6
6
7
1
3
1
2
2
1
1
1
1
1
1
1
1
2
2
3
7
3
1
3
2
1
1
1
2
1
2
6
4
7
1
4
1
2
3
2
2
1
3
2
1
3
3
1
1
3
2
5
3
4
7
5
3
6
1
1
1
3
2
1
1
1
1
1
1
2
7
7
7
6
8
1
1
3
3
1
1
1
4
2
1
1
1
1
2
2
1
1
1
3
1
1
1
2
6
6
6
2
3
4
1
3
3
3
2
1
1
1
1
1
4
1
3
1
1
1
2
2
1
1
3
1
1
1
2
1
1
1
2
1
1
3
1
1
2
2
1
7
2
5
1
3
1
2
3
1
3
3
3
4
1
1
1
3
3
4
1
1
3
1
1
1
3
2
7
4
1
3
1
1
2
2
1
1
3
1
1
1
1
2
3
6
2 7
1
7 7
8 2
1
1
3
3
6
1
3 1 1
1 1 1
1 1
2 1 2
12
12
22
29
17
12
31
14
13
26
13
11
8
22
11
18
12
14
6
21
15
3
5
9
9
6
5
21
13
10
9
19
21
24
Baseline samples are indicated by asterisks.
72
-------
SECTION 8
RESULTS OF STORM WATER POLLUTION ANALYSIS
This section presents the results of the analytical observations of the
various pollution parameters measured throughout the testing period.
These results are presented in tabular form in five pollution classifica-
tions: Bacterial, Organic, Nutrient, Solids, and Other Parameters.
The data are tabulated as average values of the separate precipitation
events and not as averages of the individual samples collected. This
was done to more effectively compare the individual event characteris-
tics. Since continuous sampling at each site for each event was not
practicable, the averaging of the sequential samples for the sites which
were continuously monitored was felt to yield more representative
comparisons between these sites and those where only grab samples
were obtained. Reference is made to Table 23 in Section 6 for the
number of samples collected for each event from each test area.
Chemical and bacterial characteristics found in other studies of urban
storm water runoff are shown in Tables 24 and 25. These values may
be compared with the pollution levels found in this project.
Bacterial
The three bacteriological parameters measured on this project were
total coliform, fecal coliform, and fecal streptococcus. All samples
were examined by the membrane filter (MF) technique.
Table 26 shows the results of a cumulative frequency distribution of the
three bacteriological parameters. This distribution was derived from
data from all fifteen test areas.
These values may be compared with data from urban stormwater runoff
as reported in the Cincinnati study (1). The frequency distribution
reported in the Cincinnati investigation is shown in Table 27. It should
be noted that the 90% and 50% values for the cumulative frequency dis-
tributions found in this study are in all cases lower than the corresponding
values from the Cincinnati report.
The geometric means of the three bacteriological parameters measured
from each test area are shown in Table 28, Table 29 presents the mean
ratios and standard deviations of the bacterial pollution parameters. The
overall geometric means of the bacterial parameters from all fifteen
73
-------
TABLE 24
CHEMICAL CHARACTERISTICS OF URBAN STORM WATER RUNOFF
(OTHER STUDIES)
Location
and
Date
Cincinnati
7/62-9/63
Detroit
1949
Ann Arbor
1965
Oxney, Eng.
1954
Moscow, USSR
1936
Parameter (m
BOD COD Orgai
Range Mean Range Mean Range
2-84 19 20-610 99 0.2-4.8
96-234 147
a/1)
lie N Soluble PO^ SS
Mean Range Mean ' Mean
1.7 0.07-4.3 0.8 210
Max. 62 28 Max. 4.0 1.0 Max. 3.4 0.8 2,080
Max. 100
186-285
Leningrad, USSR 36
1948-50
Seattle
1959-1960
Stockholm
1945-1948
Pretoria,
S. Africa
Residential
Business
10 Max. 9-
Max. 80 17 Max. 3, 100 188
30 29
34 28
0
5. 4
3. 5
-------
TABLE 25
BACTERIAL CHARACTERISTICS OF URBAN STORM WATER RUNOFF
(OTHER STUDIES)
Location
and
Date
Cincinnati
7/62-4/63
Cincinnati
1/62-1/64
Seattle
1959-1960
Pretoria
S. Africa
Source
Street
Gutters
Spring
Summer
Autumn
Winter
Business
District
Spring
Summe r
Autumn
Winter
Residential
Business
Bacteria (Number/
Total Fecal
Coliform Coliform
58,000
1,400
90, 000
Z90, 000
1, 600
22, 000
172, 000
190, 000
46, 000
16, 000
240, 000
230, 000
10,900
230
6,400
47,000
50
2, 500
13,000
40, 000
4, 300
100 ml )
Fecal
Streptococcus
20,500
3, 100
150, 000
140, 000
2, 200
13, 000
51, 000
56, 000
28, 000
Remarks
(Median values)
(Median values)
(Median values)
MPN/100 ml
MPN/100 ml
-------
TABLE 26
BACTERIAL DENSITIES IN URBAN STORM WATER
SAMPLES FROM 15 TEST AREAS, TULSA, OKLAHOMA
Bacterial .
Parameter
Total Coliform
Fecal Coliform
Fecal Streptococcus
No.
of
Samples
389
358
304
Numbers
Percent of
90%
2, 100
2
2
Exceeded in Designated
Samples (number /1 00 ml )
50% 10%
57,000
30
5,000
1, 140,000
30,000
167,000
TABLE 27
BACTERIAL DENSITIES IN URBAN STORM WATER
SAMPLES FROM CINCINNATI STUDY
Numbers Exceeded in Designated
Bacterial Percent of Samples (number/100 ml )
Parameter 90% 50% 10%
Total Coliform 2, 900 58,000 460,000
Fecal Coliform 500 10, 900 76,000
Fecal Streptococcus 4,900 20,500 110,000
76
-------
TABLE 28
GEOMETRIC MEANS FOR BACTERIAL DENSITY (THOUSANDS/100 ml) IN
URBAN STORM WATER FROM 15 TEST AREAS IN TULSA, OKLAHOMA3
DATES: SEPTEMBER 1968 TO SEPTEMBER 1969
Test
Area
No.
No. of
Events
Total
Min.
Coliform
Geometric
Mean Max.
No. of
Events
Fecal
Min.
Coliform
Geometric
Mean Max.
No. of
Events
Fecal
Min.
Streptococcus
Geometric
Mean
Max.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
14
11
13
13
11
10
14
9
11
11
11
12
6
4
6
0. 0
0.7
0. 0
0. 0
0. 0
4.0
0.0
0. 0
26. 0
2.0
14.0
0.0
0. 0
0. 0
20. 0
71
43
100
25
150
140
3Z
240
400
130
370
56
28
5
220
2,000
800
20,000
500, 000
21,500
5,500
3,500
3, 300
7,500
3,800
5,800
2, 500
1,700
1,425
1,450
11
8
10
8
12
9
13
8
10
11
10
11
9
5
8
0.00
0.00
0. 00
0. 00
0. 00
0. 00
0.00
0. 00
0. 00
0. 00
0. 00
0. 00
0. 00
0. 00
0. 00
0. 94
1. 90
3. 30
0. 77
1. 50
18. 00
0. 12
0.45
0. 29
0.30
0. 62
0.01
0. 18
0. 37
0. 35
70
170
175
30
185
470
80
420
265
45
290
20
110
95
135
13
11
15
13
12
10
16
9
11
10
11
12
9
5
8
0. 00
0. 00
0. 00
0. 00
0. 00
0. 00
0.00
0. 00
0. 00
0. 00
0. 00
0. 00
0.00
0. 00
0. 00
4. 20
0.78
15. 00
12. 00
3. 80
24. 00
2. 30
5. 80
7. 60
30. 00
6.80
0. 70
5.70
21. 00
14.00
775
440
380
450
370
650
775
1,400
1, 100
840
3,450
550
430
100
280
''Geometric means were calculated using the arithmetic means of each event sampled.
-------
oo
TABLE 29
MEAN RATIOS AND STANDARD DEVIATIONS OF
BACTERIAL POLLUTION PARAMETERS
FROM 15 TEST AREAS, TULSA, OKLAHOMA
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Classification
Light Industrial
Commercial -Retail
Residential
Med. Ind. -Residential
Residential
Medium Industrial
Residential
Residential
Residential
Commercial (Office)
Residential -Com. Mix
Open Land -Runways
Residential
Recreation (Golf)
Residential
F. Col.
Ratio
0.075
0. 165
0.093
0.005
0.054
0. 104
0.035
0. 145
0. 117
0.034
0.035
0.024
0. 162
0.005
0.013
/T. Col.
Std. Dev.
0. 115
0.272
0.210
0.021
0. 168
0. 166
0. 132
0.213
0.260
0.071
0.083
0.092
0.345
0.017
0.025
F. Col.
Ratio
0.428
0.228
0. 507
0.237
0.213
0.683
0.376
0.785
0.893
0.081
0.246
0. 102
o. 169
0. 341
0.840
/F. Str.
Std. Dev.
0. 520
0.349
0.806
0.684
0.377
1. 126
1.020
1.444
2.411
0. 177
0.455
0. 232
0.257
0.986
1.057
-------
test areas were:
Bacterial Parameter Geometric Mean
Total Coliform 87,000/100 ml
Fecal Coliform 470/100 ml
Fecal Streptococcus 6, 000/100 ml
These values were considerably in excess of the State of Oklahoma
water quality criteria for recreational areas for body contact sports:
In all areas designed as recreational areas for body contact
aquatic sports, including swimming and skiing, bacteria of
the coliform group shall not exceed 1, 000/100 ml as a monthly
average * value (either MPN or MF count) during the recre-
ational season; nor exceed this number in more than 20% of
samples examined during any one month; nor exceed 2,400/100
ml (MPN or MF count) on any day except during periods of
storm water runoff. Provided, however, that the fecal coliform
shall not exceed a geometric mean of 200/100 ml, nor shall
more than 10% of total samples during any 30 -day period exceed
400/100 ml. (11)
In all 15 test areas, the geometric means for total coliform were far
above the 1000/100 ml designated by the water quality criteria; this
value was exceeded in more than 90% of all samples taken. It should
be kept in mind, however, that the geometric means reported in this
study are exclusively from periods of storm water runoff, and should
not be interpreted on the same basis as values obtained on samples
taken during other periods as well. In reference to fecal coliform,
Test Areas 7, 12, and 13 exhibited geometric means falling within
the 200/100 ml maximum set by the criteria. Although considerably
more than 10% of the fecal coliform samples exceeded 400/100 ml,
such samples were not in the majority.
For the fifteen test areas, the fecal coliform value was, on the average,
3% of the total coliform value. The average fecal coliform to fecal
streptococcus ratio varied from a low of 0. 081 (Test Area No. 10) to a
high of 0. 893 (Test Area No. 9).
These low ratios indicate the source of the bacterial pollution to be
warm-blooded animals other than man (12). An initial suspicion at the
start of the project was that Test Areas No. 13 would record a high fecal
Logarithmic average based on a minimum of five samples per
30 days.
79
-------
coliform to fecal streptococcus ratio, since this drainage basin was
unsewered and utilized septic systems for liquid waste disposal. After
checking with the authorities at the Tulsa City-County Health Depart-
ment, it was learned that the septic systems in this area function
properly, and very few complaints had been reported in regard to the
"pooling" of septic systems.
Test Area No. 9 had the highest total coliform geometric mean (400, 000
/100 ml). The lowest total'coliform geometric mean (5, 000/100 ml) was
recorded from Test Area No. 14, which is a country club golf course.
This low geometric mean may be due to the small number of sample
analyses from this drainage area. The one characteristic of this water-
shed which distinguishes it from the other test areas is that there are
two small recreation ponds on the drainage channel; these ponds capture
almost all of the runoff water. The only time that the drainage channel
flows is after or during a precipitation event of high intensity or large
amount. Such an event normally occurs during the spring of the year.
Because of this characteristic, the samples actually collected were from
the overflow of impounded water rather than actual runoff water.
No clear-cut relationships were found between the bacterial parameters
and land use activities. Some correlation with the environmental con-
ditions of the test areas, on the other hand, is evident as seen in Table
54 in section 10. It appears that the test areas with the worst environ-
mental condition produce the greatest numbers of bacteria in storm
runoff.
Organic
The three parameters measured on this project to determine the amount
of organic pollution were 5-day, 20°C, biochemical oxygen demand
(BOD), chemical oxygen demand (COD), and total organic carbon (TOC).
Table 30 summarizes the analytical results. These averages and ranges
are based on .the averages for each rainfall event sampled. Figure 16
illustrates the average values of all three parameters. Tables 31 and
32 present respectively the mean ratios of the organic pollution para-
meters and selected organic to solids ratios.
In general, all three organic parameters were moderate and not ex-
tremely high. The COD values appear to have the most significant
variation between the test areas. The organic pollution parameter
ratios (BOD/COD and TOC/COD) and certain individual observations
indicate that some organic material of storm water runoff does not
show up in the standard COD test. The organic material may, therefore,
include straight-chain aliphatic components, aromatic hydrocarbons, and
80
-------
00
TABLE 30
AVERAGE AND RANGE FOR BOD, COD, AND TOG IN URBAN STORM WATER
RUNOFF FROM 15 TEST AREAS IN TULSA, OKLAHOMA
DATES: SEPTEMBER 1968 TO SEPTEMBER 1969
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Min.
3
2
2
4
3
6
2
3
4
4
4
6
4
6
1
BOD (mg/1)
Avg.
13
8
8
14
18
12
8
15
10
11
14
8
15
11
12
Max.
23
16
21
29
38
18
17
25
15
27
23
16
39
23
24
COD
Min.
54
21
20
14
37
39
12
50
40
36
80
21
13
22
18
(mg/1)
Avg.
110
45
65
103
138
90
48
115
117
107
116
45
88
53
42
Max.
215
94
162
232
261
133
69
405
263
240
167
^ 69
220
74
62
Min.
17
12
14
22
11
12
0
5
13
0
17
6
17
18
11
TOG (mg/1)
Avg.
43
22
22
42
48
34
15
37
35
28
33
20
35
29
34
Max.
71
36
31
74
85
42
20
82
61
80
49
40
66
36
75
-------
00
150
125
en
in
Z
O
5 100
Z
s
z
0
u
§
u
•a
— .
"
Q
50
AVERAGE
N>
0
y
O
J
OS
pi
0
0
!1
:•:
X
v
X
X
v
i
I
1
1
V
i
-r
:•
:•
;:;
:-'
;
-
;
':
i;
^
1
|
:j:
X;
V
X
X
1
I
S:
i;i
X
•:•
x
1
7.
•"•
\
'.
:
•\
•?
I
j
"x
v
X
5
f^n
j:
X
i
• 1
•:
:•
";
;•;
X
•:•
:::
•:•
•;•
x
rt
il
7-7
X
5
;j;
:':
'.•'.
;!;
:-'
:::
•'•
x
X
1
V
V
J
10
] 1
12
13
15
TEST AREA NUMBER
FIGURE 16 BAR GRAPH OF BOD, TOC & COD AVERAGE
CONCENTRATIONS VS. TEST AREA NUMBER
-------
TABLE 31
SELECTED MEAN RATIOS AND STANDARD
DEVIATIONS OF ORGANIC POLLUTION
PARAMETERS FROM 15 TEST AREAS
TULSA, OKLAHOMA
00
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
BOD/ COD
Ratio Std. Dev.
0. 129
0, 220
0. 134
0. 176
0. 163
0. 149
0. 150
0. 162
0. 120
0. 105
0. 119
0. 208
0. 127
0. 263
0. 342
0. 062
0.248
0. 069
0. 192
0. 106
0.095
0. 099
0. 083
0. 039
0. 043
0.051
0.071
0. 068
0. 230
0. 213
BOD/ TOG
Ratio Std, Dev.
0. 289
0. 415
0. 304
0. 368
0. 357
0.434
0. 379
0.462
0.403
0.396
0.375
0.529
0.389
0.391
0. 577
0. 164
0.416
0. 138
0. 162
0. 152
0. 239
0. 205
0. 180
0. 257
0. 217
0. 165
0. 301
0. 238
0. 246
0. 331
TOG/ COD
Ratio Std. Dev.
0.447
0.636
0.465
0.445
0.396
0.445
0.289
0. 379
^ 0.373
0. 349
0. 334
0.495
0. 525
0. 591
0. 847
0. 158
0. 400
0. 283
0. 331
0.223
0. 237
0. 158
0. 140
0. 136
0. 327
0.088
0. 228
0.514
0. 215
0. 591
-------
00
TABLE 32
SELECTED MEAN RATIOS AND STANDARD DEVIATIONS OF
ORGANIC AND SOLIDS POLLUTION PARAMETERS FROM'
15 TEST AREAS, TULSA, OKLAHOMA
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
COD/ YDS
Ratio Std. Dev.
0.885
0.911
1.024
1.992
4. 938
2.221
1. 192
1. 154
1. 268
2.450
2. 512
1. 201
1. 858
1.031
0. 892
0.700
0.553
0.738
2.249
8.476
2.516
1.278
0.344
0.596
2. 959
2. 287
0. 816
1. 532
0. 547
0.479
TOC/VDS
Ratio Std. Dev.
0.463
0. 662
0.489
0. 757
1. 962
0. 541
0.494
0.431
0.412
0.892
0. 927
0. 634
0.699
0. 600
0.850
0.286
0.433
0. 363
0.=416
2. 967
0.321
0.613
0. 195
0.211
0. 787
1. 120
0.442
0. 518
0. 336
0. 626
COD/DS
Ratio Std. Dev.
0. 653
0.448
0.488
0. 502
1.602
0.699
0.521
0.692
0.734
1. 086
0. 764
0.509
0.817
0. 330
0. 574
0. 528
0. 198
0. 397
0.342
1. 341
0. 396
0.408
0.542
0. 328
1.255
0.490
0. 301
0.591
0. 207
0. 197
TOC/DS
Ratio Std. Dev.
0.274
0. 280
0. 176
0. 193
0. 603
0. 227
0. 198
0.238
0.222
0.467
0. 215
0. 249
0. 294
0. 155
0.488
0. 165
0. 141
0. 066
0. 115
0. 608
0. 104
0. 148
0. 124
0. 105
0. 706
0. 122
0. 159
0. 193
0. 046
0. 319
-------
pyridine. These components are not oxidized to any appreciable extent
in the COD test.
The average BOD concentrations from the fifteen test areas ranged
from a low of 8 mg/1 (Test Areas No. 2, 3, 7, and 12) to a high of
18 mg/1 (Test Area No. 5). Test Areas No. 5 and 13 recorded the
highest maximum single observations of 38 mg/1 and 39 mg/1, respec-
tively. Both of these test areas are classified as residential areas with
medium to heavy tree cover.
With the exception of Test Area No. 10, all of the high average values
occurred from test areas with moderate to heavy tree cover. Also, all
of these areas had one other common factor: the condition of drainage
channels offered many opportunities for the leaves and grass trimmings
to become trapped in depressions, thus allowing a chance for this
vegetation to decompose. This condition could explain the higher
average BOD values.
/
The fact the fifteen test areas did not show extreme variations tends to
indicate that the possible relationship between BOD values and land use
is not present.
It is interesting to note that all of these average concentrations are
approximately 50% of that reported for good secondary sewage treatment
plants. Additional comparative data and calculations are presented in
Section 9.
The BOD/COD ratio varied from 0. 105 (Test Area No. 10) to 0. 342
(Test Area No. 15). The average ratio from all fifteen sites was 0. 171.
The high ratio from Test Area No. 15 may be due to the small number
of events sampled. Also, Test Area No. 14 is not typical, since the
samples collected were not from runoff, but from overflow water from
the ponds on the drainage basin.
The average BOD/TOC ratio from the fifteen test areas was 0. 405. The
range of values was from 0. 289 (Test Area No. 1) to 0. 577 (Test
Area No. 15).
In general, these ratios are not useful for characterization of the test
areas. There is considerable variation between the test areas, and each
drainage basin has a high standard deviation.
Table 32 presents several selected mean ratios of organic to solids
pollution parameters. The only interesting findings in this group of
ratios were the high calculated ratios from Test Area No. 5. No logical
85
-------
explanation can be found for such high values except that this test area
is a fairly old residential neighborhood with steep slopes and a large
amount of tree cover.
Examining the standard deviations of the ratios indicates that consider-
able variation is .present from sample to sample, and no one site has a
constant relationship.
Total organic carbon (TOC) was measured in conjunction with BOD
and COD to further characterize the test areas. It was hoped that a
constant 'relationship could be found between samples. The TOC/COD
ratio varied from 0. 289 (Test Area No. 7) to 0. 847 (Test Area No. 15).
The average of all fifteen test areas was 0. 468.
The average values of the fifteen test areas show no positive groupings;
the test areas with the three highest values are each classified differently.
In several instances the TOC concentrations were higher than the COD
concentrations, indicating that the standard COD test did not detect
some organic compounds. At present, this finding cannot be readily
explained.
Nutrients
Organic Kjeldahl nitrogen and soluble orthophosphate were the nutrients
measured in the study. The averages and ranges of values of these two
components are given in Table 33. Figure 17 illustrates the average
concentrations for both parameters. The means and standard deviations
of the nitrogen to phosphorus ratios are shown in Table 34. The values
that were obtained varied between land uses and sites.
With knowledge of the present land use and an examination of the data
shown in Appendix M for some of the sites, several possibilities as to
the sources of nutritional pollution can be advanced. Other sites exhibit
such variation as to season, concentration, and so on, that logical
deductions as to cause cannot be made unless more complete land use
information is available.
The organic Kjeldahl nitrogen measured in the runoff could have been
obtained from several sources. The entrainment of organic matter by
surface flows, and the eluviation of decay products from organic matter
are probably responsible for a large portion of the nitrogen load. Deriv-
atives from commercial fertilizers are potential high pollution sources
in the event that precipitation events occur at high intensities after
these fertilizers have been applied on the land surface. Ammonia and
86
-------
TABLE 33
AVERAGE AND RANGE FOR NUTRIENT CONCENTRATIONS
IN STORM WATER RUNOFF FROM 15 TEST AREAS
DATES: SEPTEMBER 1968 TO SEPTEMBER 1969
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Organic
Kjeldahl
Nitrogen
Min.
0. 06
0. 17
0. 24
0.00
0. 00
0. 16
0. 01
0. 00
0. 14
0. 06
0. 13
0.01
0. 15
0. 13
0. 15
(mg/1)
Avg.
1. 11
0. 95
1.48
0. 97
0. 72
0. 65
0.80
0.69
0.67
0.83
0.66
0. 39
1.46
0. 96
0. 36
Max.
2.95
3.61
3. 28
3.03
1.80
1. 50
1.60
2.52
1.30
2.40
1.82
1. 26
5.32
2.40
0. 98
Total
Soluble
Or thopho sphat e
Min.
1. 20
0. 24
0. 10
0. 36
0.53
0.58
0. 28
0.00
0.48
0. 30
0. 60
0. 20
0. 10
0. 09
0. 35
(mg/1)
Avg.
3.49
0.86
1.92
1. 05
0.87
0.86
0. 67
1. 15
1.02
0. 70
1. 11
' 0. 54
1. 18
0. 99
0.81
Max.
15. 10
1. 50
3. 70
3. 00
1. 53
1. 40
1.43
2. 60
1.92
1. 50
1. 88
1.68
1. 97
2. 25
1. 17
TABLE 34
MEAN AND STANDARD DEVIATION OF RATIO
OF ORGANIC KJELDAHL NITROGEN TO
SOLUBLE ORTHOPHOSPHATE
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
N/PO4
Ratio
1. 929
4. 080
2.676
4. 008
2. 950
2. 193
4.425
1.867
2. 201
3. 191
2.446
4. 210
5.800
2. 086
2. 591
Std. Dev.
1.455
3.013
1.606
3.813
2.995
1.502
3.491
1.670
1.813
2.436
2.833
5.435
5. 175
0. 696
4.513
87
-------
1.50
1.25
z
g
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10
11
1?
1 j
FIGURE 17
TEST AREA NUMBER
BAR GRAPH OF AVERAGE NUTRIENT CONCENTRATION VS.
TEST AREA NUMBER
-------
organic nitrogen are also washed from the air at rates of 2 to 6 pounds
per year (13).
A valid apportionment of the measured nutrients to these sources is not
possible, and only inferences can be made. In the spring, Test Areas
2, 3, and 13 exhibit increased levels of organic nitrogen which can be
attributed to fertilization of lawns within these high-income residential
areas. Other sites have high values during the fall, winter, and spring
which could be assigned to organic decay. A decrease in organic nitro-
gen is seen during the growing season due to the rapid assimilation of any
free nitrogen by growing vegetation.
The flows from Site 7 were considered to be primarily from the imper-
vious portion of the drainage area. Using the average value of the
nitrogen as the multiplier, an estimate of the nitrogen load from the
site was obtained by a procedure described in Section 9 of this report.
When the estimated load was apportioned to the calculated imperviousness
of the site, a value of 7. 0 pounds per acre per year was obtained. Tabu-
lation of the annual loads from the impervious'portion of other test areas
showed that Sites 2, 4, 5, 6, 8, 9, 10, and 11 exhibited annual values
which fell within a range of 4. 9 to 7. 3 pounds per acre. These loads
could be assigned to both washout from the air and to organic nitrogen
sources deposited on the impervious portion of the watersheds.
Of the remaining sites, only Test Areas 3 and 13 are justifiable when
the nitrogen loads are assigned just to the impermeable portion of the
sites. The higher average nitrogen values of these two sites can be
attributed to the apparent washout from heavy yard fertilizations in the
spring. The high value for Test Area 14 can be attributed to the decay
products of organic matter present within the channels and lakes of the
drainage way during the two fall events that were sampled. Site 1 was
in a state of flux with construction taking place at the site during much of
the test period. Erosion took place at these construction sites, and the
organic matter which was eroded probably contributed to the high average
nitrogen value. Sites 12 and 15 were both flat and had low average values.
Drainage from the paved parking aprons and runways in Test Area 12
runs into grassed channels, and ample opportunities exist for seepage and
for assimilation of the entrained nitrogen by plants. Site 15 has old
streets and curbings. Puddling along the curbing is commonplace, and
drainage amounts from the area are low.
The varying amounts of orthophosphate found in the analysis of the
study sites can likewise be assigned to various sources. The frequency
of street sweepings; the amount, type, and location of organic material
and its decay products; the application of commercial fertilizer; the
89
-------
season; the number of sampled events; and the drainage characteristics
can either singularly or in combination influence the washout of
orthophosphate from the test sites.
The presence of a concrete plant upstream, from the sampling point was
the prime cause of the high level of orthophosphate in Test Area 1.
This plant affected these levels either through the eluviation of limestone
containing soluble phosphates from the plant site or through the furnish-
ing of highly basic calcium hydroxide solutions which stripped the
phosphates from suspended clays in the storm runoff.
The prairie soils in this area are high in soluble phosphates, and the
breakup of land at the construction sites enabled soils to be eroded. Site
4 contained some concrete plants also, but the resultant influence of
high total solids and high pH on the level of orthophosphate was not as
striking as that exhibited by Test Area 1.
Sites 3 and 13 exhibited high average orthophosphate levels which re-
sulted from the heavy lawn fertilizations in the spring. The high maximum
levels which are shown for 8 and 14 are caused by organic decay products.
Test Area 12 had low orthophosphate levels due to low runoff volumes and
the lack of decidous vegetation.
If the amounts of orthophosphate are apportioned just to the impermeable
portions of the site as was done previously for organic Kjeldahl nitrogen,
Test Area 10, located in the central business district, has 4. 34 pounds,
the lowest annual amount per impermeable acre. This value appears
reasonable in that most of the runoff-producing portion of the streets
is swept each night, and there is relatively little organic matter from
vegetal sources in the drainage ways of the area. Site 2 was also low
in pounds per impermeable area, but since it contained a higher percen-
tage of residential area with its characteristic vegetation, the yield was
greater than from Site 1. Site 7 also exhibited a low yield of orthophos-
phate per impermeable acre. This was thought to result from the low
percentage of covered storm sewers and from the low contribution of
surface flow from the pervious areas. The remaining areas had larger
yields of orthophosphate per impervious area; this finding was attributed
to the larger amounts of tree cover in these older developed areas.
Solids
The five solids constituents measured on this project were total solids
(TS), suspended solids (SS), volatile suspended solids (VSS), dissolved
solids ( DS), and volatile dissolved solids (VDS). The arithmetic averages
90
-------
of these constituents are summarized in Table 35. These averages are
based on the average of each event sampled from the fifteen areas.
Figure 18 illustrates the average values for total solids, suspended
solids, and dissolved solids. Selected ratios were calculated to provide
further insight into the character of urban runoff pollution from different
types of land activity. These mean ratios and standard deviations are
shown in Table 36.
Total solids is the sum of the suspended solids and dissolved solids
fractions; it is closely related to the topography and soil conditions of the
various test areas. It should be noted that,due to the sampling techniques,
total solids is not a measure of all solids found in urban storm runoff. All
solids would be the sum of total solids and the floating and large particles
not picked up by the sampler used on this project. These "other solids"
include such materials as tree limbs, leaves, paper, plastics, etc. Such
materials are not only objectionable as to aesthetics, but indirectly add
to the bacterial, organic, and nutrient storm water loads. For example,
during late fall large amounts of leaves reach the storm drainage system
and become trapped in depressions within the- system. Between the rain-
fall that carries the leaves to the system and the next precipitation event,
the leaves have time to decay and disintegrate, thus adding additional
organic and nutrient contaminants to the runoff water.
The average values for the solids show considerable variation. The
lowest average value for total solids (199 mg/1) was found from Test
Area No. 12. Test Area No. 1 had the highest average value (2242 mg/1).
The value for this site was eight to nine times greater than the average
for the other test areas. This extremely high concentration can be
explained by exposed open land. Shortly after the start of the project,
construction began on a large apartment house complex. The land was
stripped of its ground cover, cuts were made for streets, and water and
sewer line trenches were dug. Construction continued throughout the
project. Therefore, this test area is representative of a drainage basin
that is under development.
The second highest average value (680 mg/1) for total solids was recorded
from Test Area No. 3. This test area is a new fully developed middle-
class subdivision. A large portion of the main drainage channel is open
and unimproved, with unstable banks.
The percentage of suspended solids varied from a low of 38% (Test Area
No. 12) to a high of 82% (Test Area No. 1). The remaining test areas
had percentages from 40% to 60%. The suspended solids concentrations
were ten to twenty times higher than the concentrations reported for
Tulsa's sewage treatment plants. The low value from Test Area No. 12
91
-------
TABLE 35
AVERAGE VALUES FOR SOLIDS
FROM 15 TEST AREAS IN TULSA, OKLAHOMA
DATES: SEPTEMBER 1968 TO SEPTEMBER 1969
t\>
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Classification
Light Industrial
Com. -Retail
Residential
Med. Ind. -Res.
Residential
Med. Industrial
Residential
Residential
Residential
Commercial -Off ice
Res. -Com. Mix
Open Land -Run ways
Residential
Recreation (Golf)
Residential
No.
of
Storms
14
10
16
15
13
10
18
8
11
11
11
11
10
5
8
No.
of
Samples
36
23
48
46
50
15
60
13
16
34
26
27
30
18
22
Average Solids (mg/1)
Total
2242
275
680
616
271
346
413
382
417
431
575
199
469
592
273
Suspended
Total Volatile
2052 296
169 48
280 53
340 83
136 54
195 55
84 28
240 96
260 70
300 61
401 95
89 24
332 85
445 206
183 122
Dissolved
Total
190
106
400
276
135
151
328
141
157
132
174
110
137
147
89
Volatile
111
70
317
87
76
66
124
75
98
71
83
59
73
53
56
-------
700 -
600 -
500 -
OJ
<
lil
>
300 -
200 -
100 -
2242
2052
-
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ft
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TOTAL SOLIDS
SUSPENDED SOLIDS
DISSOLVED SOLIDS
-
••'•
;
f
; ;i
[T
n*
:1- '
H
R
r
§
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10
11
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13
14
If,
TEST AREA NUMBER
FIGURE 18
BAR GRAPH OF AVERAGE SOLIDS CONCENTRATIONS VS.
TEST AREA NUMBERS
-------
TABLE 36
MEAN RATIOS AND STANDARD DEVIATIONS OF
VARIOUS SOLIDS COMPONENTS
FROM 15 TEST AREAS, TULSA, OKLAHOMA
Test
Area No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
SS/TS
Mean Std. Dev.
0.819
0.505
0.528
0.483
0.454
0.514
0.404
0.524
0.533
0.530
0.639
0.379
0.612
0.594
0.427
0. 208
0.234
0.221
0.194
0. 166
0.197
0.242
0. 157
0.221
0.273
0. 169
0.224
0.261
0. 188
0.245
VDS/DS
Mean Std. Dev,
0.521
0.538
0.508
0.326
0. 518
0.423
0.514
0.484
0.620
0.514
0.433
0.499
0.498
0.382
0.594
0. 154
0.254
0.233
0. 156
0.216
0. 130
0.212
0. 118
0. 129
0. 224
0.243
0.209
0.195
0.252
0.220
vss/ss
Mean Std. Dev.
0.228
0.399
0.315
0.272
0.467
0.393
0.495
0.314
0.311
0.326
0.302
0.412
0.287
0.348
0.526
0. 172
0.292
0. 188
0.212
0.248
0.230
0.298
0. 164
0.200
0. 212
0. 169
0. 324
0. 184
0.346
0.231
DS/Cond.
Mean Std. Dev.
1.688
1.450
1.420
1.653
1.578
1.381
1.251
1.508
1.696
1.469
1.583
1.678
1.591
1. 191
2. 543
0.888
0.902
0.725
0.912
1.000
0.475
0.546
0.415
0.646
0.513
0.593
1.001
0.685
0.349
1.342
-------
is due to the fact that the runoff comes from airport runways and is
channeled to the main drainage channel by well-kept drainage ditches
along the runways. Also, the main sources of suspended solids in fully
developed residential and commercial areas are the streets, in that they
collect the dust, dirt, and clay droppings from automobiles. It is
interesting to note that Test Area No. 12 also had one of the four highest
volatile suspended solids to total suspended solids ratios.
Generally, the volatile suspended solids followed the same pattern as
suspended solids, and formed 20-50 percent of the total suspended solids.
It should be remembered that high values of volatile matter in storm
water may not necessarily be decomposable organic material. The
relatively low BOD values found on this project support this, as does
the fact that clay will lose considerable weight on ignition.
The average total dissolved solids ranged from a low of 89 mg/1 (Test
Area No. 15) to a high of 400 mg/1 (Test Area 3). The overall
mean of the test areas was 178 mg/1. The volatile portion of the
dissolved solids averaged 49% for the 15 test areas. The range of values
was from 33% (Test Area No. 4) to 62% (Test Area No. 9).
Other Parameters
In addition to the bacterial, organic, nutrient, and solids pollution
parameters measured on this project, the pH, chloride, and specific
conductance were measured. Table 37 presents a summary of these
results.
The average pH from the fifteen test areas varied from a high of 8, 4 (Test
Area No. 1) to a low of 6. 8 (Test Area No. 15). All of these average
values are within the water quality criteria assigned by the State of
Oklahoma for the Arkansas River and Verdigris River. The criteria
call for the pH to be between 6. 5 and 8.5, and all values below 6. 5 and
above 8. 5 must not be due to a waste discharge. The only observations
of pH values that were higher than these limits were found from Test
Area No. 1, which can be classified as a light industrial area. This
test area recorded a maximum pH of 12. 2 on October 16, 1968. The
particular sample having this maximum pH value was the third in a series
of seven 30-minute composite samples, and was collected approximately
5. 4 hours after the rainfall event started. All the samples collected from
this test area had consistently high pH values. The only sources of land
contaminants that could be found within this drainage area were piles of
cement, waste concrete, and other waste associated with a concrete batch
plant operation. The batch plant is located on the bank of the unimproved
95
-------
TABLE 37
AVERAGE VALUES FOR pH, Cl, AND SPECIFIC CONDUCTANCE
FROM 15 TEST AREAS IN TULSA, OKLAHOMA
DATES: SEPTEMBER 1968 TO SEPTEMBER 1969
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Classification
Light Industrial
Com. -Retail
Residential
Med. Ind. - Res.
Residential
Med. Industrial
Residential
Residential
Residential
Commercial -Off ice
Res. -Com. Mix
Open Land -Runways
Residential
Recreation (Golf)
Residential
No.
of
Storms
14
10
16
15
13
10
18
8
11
11
11
11
10
5
8
No.
of
Samples
36
23
48
46
50
15
60
13
16
34
26
27
30
18
22
PH
8.4
7.3
7.3
7.5
7.1
7.5
7.4
7.4
7.4
7.4
7.4
7.2
7.3
7. 1
6.8
Cl
(mg/1)
11
10
13
10
8
9
46
10
5
10
6
4
15
13
2
Specific
Conductance
(micromhos/cm)
120
78
110
154
89
105
220
101
100
104
113
64
105
114
36
-------
open channel that drains the lower portion of this watershed.
The only test area that approached the lower limit of the State of
Oklahoma's pH criteria was Test Area No. 15. The average pH
value from this area was 6. 8 and the lowest observed value was 6. 4.
The pH of the runoff from Site 15 can be attributed to contributions from
several factors. The soils of the watershed were developed under
forest-like conditions found along the terraces adjoining the Arkansas
River bottoms before Tulsa developed. These conditions produced soils
which were slightly acidic. This area is located in a fairly old residen-
tial neighborhood, and tree cover and other vegetation levels are
approaching the levels once found in the primitive state. The decomposi-
tion of vegetation both on the ground surface and in covered storm sewers
of the area contributes to lower pH values in the runoff water.
Average concentrations of chloride (Cl) from the fifteen test areas varied
from 2 mg/1 (Test Area No. 15) to 46 mg/1 (Test Area No. 7). None of
these values are excessive considering the average concentrations found
in the two receiving streams in Urban Tulsa. The 50% value for chloride
measured in the Arkansas River at Sand Springs, Oklahoma is 970 mg/1
( 11 ). The average concentration found in Bird Creek is 126 mg/1 ( 14).
The only samples collected which were expected to show a possible
increase in concentrations were those of February 20, 1969. These
samples were collected from runoff originating from melting snow. The
runoff samples were from the street source areas only, since the snow
had not started melting on the roofs and yard areas. The results of
these observations were very low (less than 15 mg/1).
Due to the scarcity of snow and ice events in this area, very limited
amounts of salt are applied to the streets for snow and ice control. The
main material used in Tulsa for snow and ice control is sand (see
Appendix I ). Due to such limited use, the natural concentrations found
in the receiving streams, and the concentrations found from the fifteen
test areas, the chloride (Cl) load reaching the receiving streams does
not present a problem in the Tulsa area.
The average specific conductance from the fifteen test areas varied from
a low of 36 micromhos/cm to a high of 220 micromhos/cm. The mean
ratios of dissolved solids to specific conductance varied from 1. 19 (Test
Area No. 14) to 2. 54 (Test Area No. 15).
The overall average of the means of the test areas was 1. 579- None of
the average values of the fifteen test areas deviated significantly from
this mean, with the exception of Test Area No. 15. This finding tends
97
-------
to indicate that the dissolved substances in the runoff water from this
test area are higher in organic compounds than in inorganic ions.
Additional support for this conclusion is the relatively high volatile
dissolved solids to total dissolved solids ratio of 0. 594. This ratio,
as compared with the other fifteen test areas, was second highest.
Phenols determinations were made on samples collected on June 17,
1969 from Test Areas No. 2, 5, 6, 10, and 11. The results of these
determinations are shown below:
Test Area No. jig/1
2 14
5 18
6 10
10 35
11 18
The above five values are within the range (1-30 jig/1) as reported in
the Detroit-Ann Arbor study ( 3 ). It should be noted, however, that
Test Area No. 10 recorded the highest concentration (35 jig/1). This
test area is a downtown central business district having a high percen-
tage of streets and heavy traffic volumes.
Since phenols are subject to rapid biochemical and chemical oxidation,
they must be preserved and stored at cold temperatures if not analyzed
within 4 hours after collection. Due to this requirement and to the
sampling procedures used on this project, additional determinations
were not made.
98
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SECTION 9
STORM WATER POLLUTION ESTIMATES
In the preceding section, the data presented have been based on factual
analytical observations. It should be noted that the pollution loadings
calculated and presented in this section are estimates. These loading
estimates (BOD, COD, organic Kjeldahl nitrogen, soluble orthophos-
phate, and total solids) are presented by month for each test area.
Additional quality and quantity data are given for the two receiving
streams (Arkansas River and Bird Creek) in the Tulsa urban area.
Information concerning the pollution loadings from Tulsa's four treat-
ment plants can be found in Appendix J.
Precipitation and Runoff
Storm water pollution is the end product of many processes which occur
in a drainage basin. The linkage between these processes is runoff,
which itself is the product of a complex interaction of factors brought
about by precipitation events. Therefore, the precipitation-runoff
regimen of an area must be investigated as a first step in determining
storm water pollution problems. Table 38 lists some of the pertinent
precipitation data for the Tulsa area.
The limited length of the study and the relatively small number of
precipitation events available for sampling during the study period neces-
sitated an analysis of precipitation events and patterns over a longer
time span in order that meaningful surface runoff relationships could
be developed. The five year period from 1964 to 1968 was used for this
purpose. Tables L-l, L-2, and L-3 (Appendix L) and Figure 19 were
developed from the hourly precipitation amounts recorded by the weather
bureau at the Tulsa International Airport.
The precipitation regimen of the Tulsa area is portrayed in the informa-
tion shown in these figures. The months with the most frequent events
and the largest amounts of rainfall are April and May. From June
through October, the major portion of the rainfall occurs in short,
high intensity showers resulting from local convective storms. In the
period from November to March, the convective activity lessens, and
most of the rainfall events occur in conjunction with frontal storms.
This type of rainfall is characterized by low intensity, uniformly dis-
tributed precipitation. The cumulative frequency distribution curve
99
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TABLE 38
PRECIPITATION MEANS AND EXTREMES3"
Month
J
F
- M
A
M
J
J
A
S
O
N
D
Precipitation (in. )
Average
Monthly
1.68
1.59
2.72
4. 10
5. 16
4.58
3. 27
3. 19
3. 58
3.21
2.33
1. 84
Maximum
Monthly
6.65
3. 95
6. 14
9. 23
18.00
11. 17
10.88
7.47
10.50
16. 51
7.57
4.29
Minimum
Monthly
Tb
0.40
0.25
0. 51
1. 33
0.53
0.03
0. 21
T
T
0.01
0. 16
Maximum in
24 hours
2.25
1.77
2.66
4. 58
7. 30
5.01
7.54
4. 16
6.39
5.46
2.77
3. 19
Source: U. S. Department of Commerce Environmental Science
Service Administration, Local Climatological Data, 1968 Annual
Summary for Tulsa, Oklahoma. Asheville, N. C. : National
Weather Records Center.
T= Trace--An amount too small to measure.
shows that only about 8. 5 percent of the storm events produce rainfall
amounts greater than one inch. Under this precipitation regimen,
runoff from natural areas should be low.
This assumption was checked through the computation of average monthly
runoff values for the Bird Creek watershed above the USGS gage near
Sperry, Oklahoma. More than ninety nine percent of the watershed area
is in a natural state. The average monthly flows for the watershed are
given in Table 3 9.
These figures reflect the information given in Appendix L describing
the precipitation regimen. The months with higher event frequencies
and with substantial percentages of the events in the higher amount
intervals (see Table L-2) have larger runoff values than other months.
100
-------
100
20
RAINFALL IN INCHES
FIGURE 19 CUMULATIVE FREQUENCY DISTRIBUTION OF 465 RAINFALL EVENTS WHICH
OCCURRED FROM 1-64 TO 12-68 AT TULSA INTERNATIONAL AIRPORT.
-------
TABLE 39
CALCULATED AVERAGE RUNOFF FOR BIRD CREEK
WATERSHED ABOVE THE SPERRY GAGEa
Month
Runoff in
inches/acre
January
February
March
April
May
June
July
August
September
October
November
December
0. 0870
0. 0826
0.4757
0. 9633
0.4415
0. 2860
0.4177
0. 0931
0.4221
0. 0571
0. 2110
0. 1373
Total
3. 6744
aPeriod 1964-1968
Due to the nearness of Tulsa to the gage at Sperry, it was deemed
appropriate to transpose the runoff figures obtained from the gaged
watershed for use in calculating the runoff volume from the pervious
portions of the 15 test areas. Using these figures, the annual runoff
from a natural site in the Tulsa area is seen to be approxtnaately.
tgn jT^rrpTvt^vMjTg avpragp ^rmrial rainfall for the period of record.
Studies on areas in a natural state have shown that these sites have
places which contribute more frequently to runoff than others (15).
Such places, unlike the paved portions of urban areas, vary their
contributions to runoff in particular precipitation events. This varia-
tion is caused by the differences in soil moisture content, soil water
storage capacity, infiltration capacity, and other factors for different
regions in the watershed. Both between and during precipitation
events, such variations cause fluctuations in the size of the watershed
area contributing to runoff.
These circumstances cast doubt on the applicability of the procedure
of assigning to each pervious acre an equal chance of contributing to
102
-------
runoff. At present, however, no techniques exist for a rapid analysis
to determine the location, size, or sequential contribution of these
part-time pervious tracts within a natural watershed. The monthly
runoff volumes for the pervious areas within the test areas were thus
estimated by multiplying the number of acres of pervious land within
the site by the values given above for the Bird Creek basin.
The runoff volume from the sites is, therefore, composed of runoff
from both naturally occurring and man-made impervious areas. The
effects of these impervious areas on rates and volumes of runoff from
pervious natural watersheds have been shown in other studies ( 16 ).
The occurrence of flow events in the test areas at times when adjacent
rain gages showed little or no rainfall for the same period, also indi-
cated the dominating influence of man-made imperviousness on the
runoff regimens of the urbanized study sites in Tulsa. In Figure
20, the measured amounts of runoff from Test Area 7 were plotted
against the amount of precipitation obtained for the storm event. If
the entire area was impermeable and there was no infiltration, evapora-
tion, interception loss, or depression storage, then the points should
fall along the line labelled Aj7A=l.
The size of the impervious area contributing to runoff within the site was
then calculated. Since the roofs of most buildings in Test Area No. 7
are not guttered, and most residential driveways drain onto lawns or
permeable areas rather than into storm sewers, the area of land
covered by these two physical structures was multiplied by a runoff
coefficient of 0. 5. This result was then summed with the area occupied
by paved streets and by other large paved areas within the watershed.
The resulting A^/A ratio for the site was 0. 218. This ratio line is
plotted in Figure 20 and represents the flow that would come from man-
made impervious areas if there were no losses. It can be seen that the
points lie fairly close to this line. It is of interest that, for the larger
events, the points cluster below the line rather than above it. This
indicates that the runoff samples from Test Area No. 7 were from areas
of man-made imperviousness. Since the watershed outlet lay at a point
midslope up a hill along an ephemeral drainage channel with the drain-
age area lying along the crest and upper slopes of the hill, the lack of
runoff from the pervious areas is understandable.
The slope of the line of best fit through the data points was 0. 158. The
difference between the line of best fit and the Ai/A=0. 218 line was
assumed to be a measure of the losses from the impermeable areas
through evaporation, infiltration, and depression storage. The ratio of
the lesser slope to the other was 0. 727. This value was then used as
103
-------
5
tf
£
o
1.0 1.5 2.0
RAINFALL IN INCHES
fWU«20 RAINFAU-RUNOFF RELATIONSHIPS FOR SITE NUMBER 7,
104
-------
the runoff coefficient for all the impervious areas within the different
study sites.
The amount of impervious area for the other sites was derived by the
same procedure as that used for Test Area No. 7. The resulting
figure was multiplied by 0. 727 and by the monthly rainfall amount to
arrive at an estimate of flow from the impervious area. This value
was added to the estimated flow from the pervious portion of the
watershed to obtain the total volume of the average monthly flow from
each site. These estimates were used to calculate the information
shown in Tables 40 through 44.
Estimates of Pollution Loads from the Study Sites
The necessity of traveling from site to site during any one rainfall
event to collect samples and to inspect the operation of the sampling
equipment precluded attempts to obtain continuous samples over the
entire period of any single event. The capacity and rate of fill of the
sequential sampling container was such that quality measurements for
distinct periods of runoff could not be made once the sampled runoff
began filling the overflow units. Measurements of flows at low stages
during the short runoff periods were considered unreliable. No site
was felt to have reliable data taken continuously over an entire runoff
event for an actual load computation. Figures 21 and 22 show the
distribution of BOD results at two sites for a storm which occurred in
November 1968. Sampling ended at both test areas before the runoff
ceased.
Precipitation at each site could be expected to vary due to differences
in rainfall patterns over the city. For this reason, the records of
precipitation for the Weather Bureau Station at the Tulsa International
Airport were used as the base data for all test areas. The runoff from
the test areas was calculated in relation to this precipitation pattern
and was used to estimate the amounts of various pollutants washed
annually from each site. This value was obtained by multiplying the
average concentration of the parameter in question by the monthly flows.
The monthly total loads per site are given in Tables 40 through 44. A
more representative figure would have been obtained on the basis of the
impervious area within each site. Further differentiation was not
attempted, however, since the samples taken were not from source
points within the sites. Table 45 gives the average daily loads per
mile of street for each test area.
The breakdown and listing of pollution loads does allow a comparison to
be made between different land uses. Some of these comparisons are
105
-------
1.0
300
o
O
200
O
z
O
o.
O
2 100
a
o
O
O
Z
O
70
60
50
30
20
10
TEST AREA NO. 10
206 ACRES
TOTAL RAINFALLS.? IN.
RUNOFF=8t%
TOTAL ACCUMULATED LOAD
360 IBS. BOD
1.75 IBS/ACRE
\
DISCHARGE
\
BOD CONC
FIGURE 21
TIME-HOURS
RAINFALL OF NOVEMBER 15, 1968
-------
O
§ 100
O O
-J Z
Q
<
O
50
RAINFALL in/h
u
.2
.4
.6
1 1
1
70
60
50
O
O
30
20
10
TEST AREA NO. 15
74 ACRES
J] /
i
t
i
i
Z
«
«
TOTAL RAINFALL=0.85 in.
RUNOFF=40%
TOTAL ACCUMULATED LOAD
142 Ibi. BOD
1.92 Ibs/acre
BOD CONCENTRATION
123 4
TIME-HOURS
FIGURE 22 RAINFALL OF NOVEMBER 15, 1968
-------
TABLE 40
AVERAGE MONTHLY BOD LOADS FROM THE FIFTEEN TEST AREAS
Test Area
No. Acres
1
2
3
4
5 5
00 6
7
8
9
10
11
12
13
14
15
686
272
550
938
507
368
197
211
64
206
815
223
212
263
74
Jan.
1.49
1.42
0.67
2.32
1.59
0.91
0.74
1.64
0.97
2.63
1.66
1.32
1. 17
0.53
1.24
Feb.
0.85
0.80
0.38
1.31
0.92
0.57
0.43
0.94
0.56
1.48
1.03
0.75
0.68
0.32
0.72
Mar.
2.31
1.81
1.23
3.04
2. 84
1.83
1.28
2.61
1.66
3.01
2.65
1.74
2.25
1.29
2.04
Apr.
4.55
3.63
2.38
6.08
5.51
3.55
2.51
5. 13
3.22
6.11
5.23
3.47
4.35
2.46
4.00
Average BOD Load (Ibs. /acre)
May June July Aug. Sept.
3.40
2.97
1.65
4. 91
3.86
2.44
1.78
3.78
2.31
5.29
4.01
2.81
2.95
1.52
2.91
3.28
3.04
1.50
4.98
3.57
2.23
1.66
3.63
2. 17
5.55
3,93
2.84
2.67
1.27
2.77
2.42
2.29
1.07
3.77
2.56
1. 58
1.20
2.66
1.58
4.30
2.93
2. 15
1.89
0.85
2.03
2.46
2.45
1.05
3.97
2.52
1.55
1.19
2.71
1.58
4.63
3.02
2.27
1.83
0.76
2.04
3.06
2.76
1.44
4. 54
3.39
2. 13
1.57
3.39
2.05
4.99
3.64
2.59
2.57
1.27
2. 59
Oct.
1.43
1.42
0.6.1
2.30
1.46
0.90
0.69
1.57
0.92
2.67
1.75
1.31
1.07
0.44
1.19
Nov.
2. 65
2.53
1. 18
4. 12
2.81
1.74
1. 31
2.91
1.73
4.69
3.20
2.36
2.07
0. 94
2.22
Dec.
1.70
1.62
0.75
2.64
1.80
1. 12
0.84
1.87
1. 11
3.00
2.05
1. 51
1.33
0.60
1.42
Total
29.61
26.73
13.91
43.99
32.84
20.61
15.21
32.84
19.84
48.35
35.24
25. 13
24.83
12.24
25. 16
-------
TABLE 41
AVERAGE MONTHLY COD LOADS FROM THE FIFTEEN TEST AREAS
Test
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Area
Acres
686
272
550
938
507
368
197
211
64
206
815
223
212
263
74
Jan.
12.6
8.0
5.4
17.0
12.2
7.4
4. 5
12.6
11.4
25.6
14.9
7.4
6.9
2.6
4.4
Feb.
7.2
4.5
3. 1
9.7
7.0
4.3
2.6
7.2
6.6
14.4
8.5
4.2
4.0
1. 5
2.5
Mar.
19.6
10.2
10.0
22.4
21.8
13.8
7.7
20.0
19.3
29.3
21.9
9.8
13.2
6.2
7. 1
Apr.
38. 5
20.4
19.4
44.7
42.3
26.6
15. 1
39.3
37.6
59.4
43.3
19.5
25. 5
11.8
14.0
Average COD Load (Ibs,
May June July Aug.
28.8
16.7
13.4
36.1
29.6
18.3
10.7
29.0
27.0
51.4
33.2
15.8
17.3
7.3
10. 2
27.8
17. 1
12.2
36.6
27.4
13.4
10.0
27.8
25.4
54.0
32.6
16.0
15.7
6. 1
9.7
20. 5
12.9
8.7
27.8
19.6
11.9
7.2
20.4
18.4
41.8
24. 3
12.1
11. 1
4. 1
7. 1
20. 9
13. 8
8.5
29.3
19.4
11.6
7. 1
20.7
10. 5
45. 1
25. 1
12.8
10.7
3.7
7. 1
/acre)
Sept.
25.9
15.5
11.7
33.4
26.0
16.0
9.4
26.0
24.0
48.5
30. 1
14.6
15. 1
6,1
9. 1
Oct.
12. 1
8.0
5.0
16.9
11.3
6.7
4. 1
12.0
10.7
26.0
14. 5
7.4
6.2
2. 1
4. 1
Nov.
22.4
14.2
9.6
30.4
21.5
13.0
7.9
22.4
20.2
45.7
26.5
13.3
12.2
4. 5
7.8
Dec.
14.4
9. 1
6.1
19.4
13.8
8.4
5. 1
14. 3
13.0
29.2
17.0
8.5
7.8
2.9
5.0
Total
250.6
150.4
113. 1
323.6
251.8
154.6
91.3
251.8
232. 1
470.4
291.9
141.3
145.6
59.0
88. 1
-------
TABLE 42
AVERAGE MONTHLY ORGANIC KJELDAHL NITROGEN LOADS FROM THE FIFTEEN TEST AREAS
Test Area
No. Acres
1
2
3
4
5
6
7
8
9
10
11
1Z
13
14
15
686
272
550
938
507
368
197
Zll
64
206
815
223
212
263
74
Jan.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
127
168
123
160
063
053
074
076
065
198
085
064
114
046
037
Feb.
0.073
0.095
0.071
0.091
0.037
0.031
0.043
0.043
0.038
0. 112
0.048
0.037
0.066
0.027
0.021
Mar.
0. 198
0. 215
0.228
0. 211
0. 114
0.099
0. 129
0. 120
0. 110
0.227
0. 125
0.085
0.219
0. 113
0.061
Average Organic Kjeldahl Nitrogen Load (Ibs
Apr. May June July Aug. Sept.
0.389
0. 573
0.441
0.421
0.221
o. 192
0.251
0.236
0.216
0.461
0.247
0. 169
0.423
0.215
0. 120
0.290
0. 353
0. 304
0. 340
0. 154
0. 132
0. 178
0. 174
0. 155
0.399
0. 189
0. 137
0.288
0. 133
0.087
0.280
0.360
0.278
0. 345
0. 143
0. 121
0. 166
0. 167
0. 146
0.419
0. 185
0. 139
0.260
0. Ill
0.083
0. 207
0. Z72
0. 209
0.261
0. 102
0.086
0. 120
0. 123
0. 106
0. 324
0. 138
0. 105
0. 184
0.074
0.061
0.211
0.291
0. 224
0.276
0. 101
0.084
0. 119
0. 124
0. 106
0.350
0. 143
0. Ill
0. 178
0.066
0.061
0. 261
0. 328
0. 253
0. 314
0. 136
0. 115
0. 157
0. 156
0. 140
0. 376
0. 172
0. 126
0.250
0.111
0.078
. /acre)
Oct.
0. 122
0. 168
0. 129
0. 159
0.059
0.049
0.069
0.072
0.061
0. 202
0.082
0.064
0. 104
0.039
0.036
Nov.
0.226
0. 300
0. 218
0.286
0. 112
0.094
0. 131
0. 134
0. 116
0. 354
0. 151
0. 115
0.202
0.081
0.066
Dec.
0. 145
0. 192
0. 140
0. 183
0.072
0.060
0.084
0.086
0.074
0.226
0.097
0.074
0. 130
0.053
0.043
Total
2. 529
3.316
2. 618
3.048
1. 314
1. 116
1. 521
1. 511
1. 332
3.649
1.661
1.225
2.416
1.069
0. 755
-------
TABLE 43
AVERAGE MONTHLY SOLUBLE ORTHOPHOSPHATE LOADS FROM THE FIFTEEN TEST AREAS
Test
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Area
Acres
686
272
550
938
507
368
197
211
64
206
815
223
212
263
74
Jan.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
400
152
160
174
077
070
062
126
099
167
107
089
092
048
084
Feb.
0.229
0.086
0.092
0.098
0.044
0.041
0.036
0.072
0.057
0.094
0.061
0.051
0.053
0.028
0.048
Mar.
0.622
0. 195
0.295
0.228
0. 137
0. 131
0. 108
0.200
0. 168
0. 192
0. 166
0. 117
0. 177
0. 116
0. 138
Average Soluble Orthophosphate Load (Ibs.
Apr. May June July Aug. Sept.
1. 223
0. 390
0. 572
0.456
0.267
0.255
0.210
0.393
0. 330
0.389
0.327
0. 234
0.342
0.221
0.270
0.912
0.320
0.395
0. 368
0. 187
0. 175
0. 149
0.290
0.236
0. 336
0.244
0. 189
0.232
0. 137
0. 197
0.881
0. 326
0. 361
0. 373
0. 172
0. 159
0. 139
0. 278
0. 222
0.353
0. 236
0. 192
0.210
0. 115
0. 187
0.649
0.246
0.257
0.283
0. 124
0. 113
0. 100
0.204
0. 161
0.273
0. 174
0. 145
0. 149
0.076
0. 137
0.663
0.263
0. 252
0.298
0. 122
0.111
0. 100
0.207
0. 161
0.295
0. 177
0. 153
0. 144
0.068
0. 138
0. 821
0.297
0.345
0. 340
0. 164
0. 153
0. 132
0.260
0.209
0. 317
0.220
0. 175
0. 202
0. 114
0. 175
/acre)
Oct.
0. 384
0. 152
0. 146
0. 172
0.071
0.064
0.058
0. 120
0.093
0. 170
0. 103
0.089
0.084
0.040
0.080
Nov.
0.711
0.272
0.282
0. 309
0. 135
0. 124
0. 110
0.224
0. 176
0.299
0. 190
0. 159
0. 163
0.084
0. 150
Dec.
0.456
0. 174
0. 181
0. 198
0.087
0.080
0.071
0. 143
0. 113
o. 191
0. 122
0. 102
0. 105
0.054
0.096
Total
7.950
2.873
3.340
3.299
1. 587
1.477
1.274
2. 518
2.025
3.077
2. 128
1.696
1. 953
1. 103
1.699
-------
to
TABLE 44
AVERAGE MONTHLY TOTAL SOLIDS LOADS FROM THE FIFTEEN TEST AREAS
Test Area
No. Acres
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
686
272
550
938
507
368
197
211
64
206
815
223
212
263
74
Jan.
257
49
57
102
30
28
38
42
41
103
74
33
37
29
28
Feb.
147
28
33
58
14
16
22
24
23
58
42
19
21
17
16
Mar.
399
62
105
134
43
53
67
67
69
118
109
43
70
70
46
Apr.
786
125
203
267
83
102
130
130
134
240
215
86
136
132
91
Average Total
May June
586
102
140
216
58
70
92
96
96
207
165
70
92
82
66
566
104
128
218
53
64
86
92
91
218
161
71
83
68
63
Solids Load (Ibs. /acre)
July Aug. Sept. Oct.
417
79
91
166
37
46
62
68
66
168
120
54
59
46
46
426
84
89
175
38
45
61
69
66
182
124
57
57
41
46
527
95
122
200
51
61
81
86
85
195
149
64
80
68
59
247
49
52
101
22
26
36
40
38
105
72
33
33
24
27
Nov.
457
87
100
182
36
50
68
74
72
184
132
59
65
50
50
Dec.
293
56
64
116
27
32
43
48
46
118
84
38
42
32
32
Total
5107
918
1183
1936
494
594
785
836
827
1895
1447
625
776
659
572
-------
TABLE 45
AVERAGE DAILY LOADS'PER MILE OF STREET
FROM THE 15 TEST AREAS
Test
Area Total
Total
Street
No. Acres Miles
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
686
272
550
938
507
368
197
211
64
206
815
223
212
263
74
Mean 372
^Adjusted
b. ,.,
11
7
14
28
16
12
6
6
3
12
49
3
5
2
2
12
value
1 _ -. .
.46
.41
.87
.40
.32
.24
.84
.97
. 11
.99
.05
.39b
.58
.07
.06
. 18
based
Total
Street
Acres
101
56
105
214
100
85
47
60
24
104
340
103b
42
20
16
94
Average Load (Ibs
BOD
4.85
2.54
1.41
3.98
2. 80
1.70
1.20
2. 72
1. 12
2. 10
1.60
4.53
2.58
4.26
2.47
2.66
on width of streets
COD
41, 1
15. 1
11.5
29'. 3
21.4
12, 7
7.2
20.9
13-. 1
20.4
13.3
25.5
15.2
20.5
8.7
18.4
T. Solids
838
92
120
175
43
49
63
69
47
82
66
113
81
23
56
128
. /day/mile of street)
Organic
Kjeldahl Soluble
Nitrogen
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
41
32
26
28
11
09
12
12
07
16
08
22
25
37
07
20
Orthophosphate
1.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
30
29
34
30
13
13
10
21
11
13
15
30
20
38
17
28
and easements.
Miles and acres of airport runways.
-------
shown in Section 10.
Computation of Estimated Average Daily Storm Water Pollution Loads
to Area Receiving Streams
An estimate of the average daily storm water pollution load can be ob-
tained by multiplying the reported 1675 miles of streets in Tulsa
(1100 miles paved) by the arithmetic mean of the 15 test areas shown
in Table 45. This approach is plausible since the average load per
mile of street per test area is based on the expected precipitation (based
on 5-year record) and the average of the pollution parameter concentra-
tions. Since the impervious areas (primarily streets) are the important
source areas for storm water runoff pollution, it is also logical to re-
late the pollution loads to the length of streets. This methodology is
intended only as a first-order, rapid estimating procedure rather than
a complete analysis. The results using this procedure are shown in
Table 46 along with comparisons utilizing data available from Tulsa1 s
sewage treatment plants. In Table 47 the estimated average daily load
is compared with the estimated average daily values for April--the
month with the highest runoff value.
Considering the estimates presented in Tables 46 and 47, it is reason-
able to speculate that with the continued urbanization of the Tulsa area
in conjunction with the demands for increased efficiencies in waste treat-
ment facilities, storm water runoff in the Tulsa area may well become
the prime source of stream pollution within the next decade.
Of greater importance are not the estimated average daily loads, but the
"shocl^" loads resulting from urban storm water runoff. There are, for
example, an average of 52 rainfall events over 0. 1 inch in Tulsa each
year (See Table L.-2 in Appendix L). If each event produced the same
amount of pollution and occurred periodically at the end of equal incre-
ments of time, then approximately every 7 days a BOD load of 31, 185
pounds (7 x 4, 455) would be introduced into the area receiving streams
in addition to the daily load of 10, 370 pounds imposed by Tulsa1 s treat-
ment facilities.
Such a storm water pollution load would reach the receiving stream in
less than 24 hours. This consideration points out the fact that any
treatment facility being utilized for storm water pollution alone would
be in operation approximately 52 days per year. The average hydraulic
load imposed on the storm water treatment facilities in the Tulsa area
during or after the storm event would be approximately 310 million
gallons. Since the average BOD concentrations are low, treatment
114
-------
TABLE 46
ESTIMATED DAILY LOAD OF POLLUTANTS
ENTERING THE AREA RECEIVING STREAMS
Parameter
BOD
COD
Suspended Solids
Organic Kjeldahl
Nitrogen
Soluble Orthophosphate
Average
Daily Storm Water
Pollution Load
in pounds
4,455
30, 803
107, 200b
355
469
1968 Average Daily
Load from Sewage
Treatment Facilities3
in pounds
19,370
67, 180
18,400
760
*•
11, 020
Total
Load
23, 825
97,983
125, 600
1, 115
11,489
Percentage
Contribution
Storm Water
Total Load
20
31
85
31
4
of
to
From Appendix J.
"Storm water suspended solids was estimated to be 50 percent of total solids,
-------
TABLE 47
COMPARISON OF AVERAGE POLLUTION LOADS AND LOADS FOR APRIL
Parameter
BOD
COD
Suspended Solidsa
Organic Kjeldahl
Nitrogen
Soluble Orthophosphate
Average Daily
in pounds
Annual Basis
4,455
30, 803
107,200
355
469
Load
April Basis
7,219
54,760
199,360
529
749
Ratio of
April to
Annual
1.62
1. 78
1. 86
1.49
1.50
lStorm water suspended solids was estimated to be 50 percent of total solids.
-------
practices may not be feasible.
Storm. Flow Amounts from Urban Tulsa
Estimates of the storm flows to Bird Creek and the Arkansas River,
the major receiving streams in the metropolitan area, were obtained
by the following procedure. The total number of acres classified under
each category of land use in the land activity file of the TMAPC was
determined for the two watersheds. These figures were multiplied by
0. 25 to obtain an estimate of the impervious area within each drainage
basin. The value of 0, 25 appears reasonable since no actual figures
for the areas of paved streets, driveways, parking lots, and roofs are
maintained in the land use file. For example, if a standard four lane
undivided highway with curbing (52 ft.) is constructed around a section
of 640 acres, the highway by itself would "waterproof" approximately
3 percent of the section.
Using the figures of impervious acreage obtained above, the average
monthly runoffs from the pervious and impervious sections of Tulsa in
the Arkansas River and Bird Creek watersheds were obtained by the
procedure described in the precipitation and runoff section of this re-
port. These results are shown in Tables 48 and 49-
The dilution ratios given for the average monthly flows in the tables
referred to above become meaningless when examined in conjunction
with flow duration analysis as shown in Table 50. Only 33 percent of
the time are the flows of Bird Creek greater than the estimated daily
sewage flow in 1970. The estimated sewage flow in 1990 will be 58 mgd,
and the Bird Creek watershed will produce flows greater than the
sewage volume only 24 percent of the time. The construction of reser-
voirs in the upper Bird watershed and the resulting regulation of flow
will decrease the number of days in which sewage flows will exceed
the daily discharge from the drainage basin. With complete regulation
of flows in the upper watershed and with no evaporation or seepage losses
from the reservoirs, 282 mgd would be available for dilution of the
sewage effluent. Realistically this will not be possible, however, and
the amount actually available for dilution will be much less.
It can be expected that increases in urbanization of the watershed will
continue to multiply the amounts of flow generated in storm runoff events.
With more complete development, shock loads of pollution will be added
in larger amounts and with greater frequency to the lower reaches of
Bird Creek. When the costs for alternatives to prevent or treat storm
117
-------
TABLE 48
SOURCES OF FLOW CONTRIBUTION WITHIN THE
BIRD CREEK WATERSHED (DAILY AVERAGE)
(1) (2) (3)
Average Daily Sewage Flow From Estimated
Volume From 1045 Metropolitan Area Storm Water Volume Dilution
Square Miles of to Bird Creek at From 92 Square Miles Ratio
Month Natural Watershed3- 1970 Rateb of Urban Land (1) /[(Z) + (3)]
(mgd) (mgd) (mgd)
00
Jan.
Feb.
Mar.
April
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
87
54
280
503
259
173
245
54
255
33
128
80
34
34
34
34
34
34
34
34
34
34
34
34
30
19
45
93
68
68
49
50
63
29
55
34
1.4
1.0
3.5
4.6
2.5
1.7
3.0
0.6
2.6
0.5
1.4
1.2
aBased on years 1964-1968.
"The estimated 1970 sewage rate for the Tulsa metropolitan area is 59. 9 mgd. This
flow was apportioned to the percentage of the total urban area in the Bird Creek basin.
-------
TABLE 49
AVERAGE DAILY VOLUMES COMPARING ARKANSAS RIVER
FLOW AT TULSA WITH THE SEWAGE EFFLUENT
AT THE SOUTH SIDE PLANT AND WITH STORM
WATER RUNOFF FROM METROPOLITAN TULSA
Month
Jan.
Feb.
Mar.
April
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
(1)
Average Daily
Flow of Arkansas
River at Tulsaa
(mgd)
1249
960
1455
2512
2934
5550
4265
2473
4454
1944
3411
1805
(2)
Sewage Flow From
South Side Plant at
1970 Rateb
(mgd)
26
26
26
26
26
26
26
26
26
26
26
26
(3)
Storm Water Flow
67 Square Miles
of Urban Area
(mgd)
15
10
27
55
37
35
24
23
33
14
27
17
Dilution
Ratio
(1)/[(Z) + (3)]
20.5
26.7
27.5
31.0
45.8
91.0
85.3
50.5
75.5
48.6
64.4
42.0
aBased on years 1964-1968.
°The estimated 1970 sewage rate for the Tulsa metropolitan area is 59. 9 mgd. The
flow was apportioned to the total urban area in the Arkansas River basin.
-------
TABLE 50
COMPARISON OF SEWAGE FLOW WITH TOTAL
FLOW FOR BIRD CREEK AND THE ARKANSAS RIVERa
Percent of Time
Discharge is Equalled
or Exceeded
5
10
20
30
40
50
60
70
80
90
Daily Sewage Flows
from Metropolitan
Area to Appropriate
Basin at 1970 Rate.
Daily Volume
of Bird Creek
Near Sperry
in Million Gallons
509. 0
196. 0
74. 0
41.0
23. 0
13.0
6.2
2.8
1.2
0.4
34
Daily Volume of
Arkansas River
at Tulsa in
Million Gallons
8,476
5,379
2,804
1,858
1,490
1,255
951
766
522
306
26
*Based on years 1964-1968.
79. 5 percent of the Bird Creek watershed is located above the Sperry gage
-------
water pollution are considered, it may be necessary to continue using
Bird Creek as the storm sewer for a large portion of Tulsa.
The storm water effluent to the Arkansas River from Tulsa causes no
problems under present conditions. In the future, the continued urbani-
zation of this area will cause increases in both storm and sewage flow
to the river. Pollutional loads from sewage can be expected to decrease
with the advent of new technology and with the enforcement of stricter
quality standards. This factor should offset the increased loads brought
down by storm runoff. The operation of Keystone Reservoir could be
planned to minimize intolerable situations produced by the storm flows
and their associated pollution. In the case that the River Lakes plan
is implemented, the problems associated with storm water pollution
will require immediate attention. For example, a 4 inch rainfall in a
twenty-four hour period would produce from Test Area No. 10 alone
a minimum volume of at least 17 MG of storm runoff containing an
average of 8 tons of BOD and 75 tons of COD. Storms of this type
have a two year return period for Tulsa and its environs.
Table 51 gives the average water quality of the two receiving streams in
the Tulsa area. These values can be used as the base from which dilu-
tion concentrations can be calculated in storm runoff events.
When considered in the true context, the values of the pollution multi-
pliers used in this section were based on a limited amount of information.
The limitations emerge since the analysis was performed on a minute
fraction of the flow volume taken over an infinitesimal portion of the time
span in which the flow was occurring. Whether the samples were a
representative mix of the multitudinous factors which contributed to the
flow and pollution is unknown. It is speculation also as to whether the
combined effects of these factors are reproduced with predictable
certainty, or whether each event is unique in nature. At present, when
compared with the ranges of the pollution parameters found in the effluents
of the municipal treatment plants, the levels of pollution from storm
water runoff found in the study samples are in themselves no cause for
alarm.
The problem which arises is the magnitude of the total pollutional
loads which issue from an urban area. The estimates of pollution given
in this section are therefore presented as valid indicators of the pollu-
tional loads which are generated annually on each of the study sites.
The rapid development of a metropolitan area such as Tulsa, and the
unceasing aggregations of the pollutional loads into the drainage ways
of the area will continue the decline of a valuable portion of the regional
121
-------
TABLE 5 1
RECEIVING STREAM WATER QUALTIY DATA
Stream
and
Location
Arkansas
at 51st St.
Bridge
Bird Creek
at Avant
Oklahoma
D. O.
mg/1
9.4
7.5
BOD
mg/1
4
4
COD
mg/1
40
17
Organic
Kjeldahl
Nitrogen
mg/1
0. 31
0.38
Ortho-
phosphate
mg/1
0.80
0. 23
Cl
mg/1
239
41
PH
8. 3
7.7
aSource: U. S. Dept. of HEW, FWPCA, Preliminary Studies Arkansas
River and Tributaries, Tulsa to Muskogee,
Oklahoma, February,
1966.
environment. The degraded conditions which are emerging in conjunc-
tion with this type of pollution defy an economical solution with present
technology.
122
-------
SECTION 10
ANALYTICAL PROCEDURE FOR STORM WATER
POLLUTION ASSESSMENT
Introduction
The methodology used in investigating and establishing the relationships
of the pollution parameter concentrations to the various explanatory
variables included the standard statistical techniques of correlation
analysis, factor analysis, and multiple linear regression. All analyses
were performed utilizing an IBM 360-40 computer with a core capacity
of 128K. The reference document for the statistical programs and
subroutines is IBM's Application Program Manual titled "System/360
Scientific Subroutine Package (360A-CM-03X) Version III Programmer's
Manual (H20-0205-3), " No new or special programs were written for
analyzing the data or establishing the relationships. Of course, the
developed relationships presented later in this section can very easily
be programmed for use with any computer.
Prior to developing the relationships, preliminary investigations were
performed using correlation analysis and factor analysis. These tech-
niques were used to select the explanatory or prediction variables that
possibly would establish the best relationships with the pollutant con-
centrations.
Preceding the detailed description of the methodology used in the study
is a recapitulation of factors which affect the storm water pollution regi-
men. Included is a discussion of the reasons for the investigation approach
which was utilized by the study group.
General Considerations
The primary objective of the study was to develop functional relation-
ships between various land use classifications and the amounts of
pollution in urban storm water runoff. Land use classifications, along
with land condition and precipitation, are used as input functions to
generate pollutional loads and concentrations. Professional planners
generally use such categories as residential land, commercial land,
industrial land, open space, unused space, and so on. Each classifi-
cation may be subdivided further, as, for example: single family
123
-------
residential, multifamily residential, retail commercial, office
commercial, light industrial, and heavy industrial. Variables usually
associated with these categories include: assessed valuation of the
structures, population density, socioeconomic class, and employment
density. For most purposes, the general classifications, the classifi-
cation subdivisions, and the economic variables provide more than
ample descriptions of specific areas. Other characteristics important
in describing an urban area for the purpose of storm water runoff and
pollution are: type of streets, type and condition of drainage conduits,
topographic conditions, and so on. The primary source areas within
a drainage shed are the paved sections, including streets, parking lots,
roofs, and other impervious surfaces. As pointed out in the Chicago
Study (4), the significant sources of storm water pollution can gen-
erally be restricted to the impervious portion of the drainage area.
Therefore, it is important to use variables which either directly or
indirectly relate to the impervious ness. Some possible choices might
be the actual length and area of the streets. In commercial and
industrial areas, possible elements might be the number of establish-
ments, worker density, retail sales, and production figures. Informa-
tion on these prime variables is not available in many cases, and
secondary ones have to be used as measures of the imperviousness of
drainage basins.
Before a pollution load is obtained, precipitation of some form is neces-
sary. Variables associated with precipitation are the duration, amount,
and intensity of individual precipitation events. The pattern and distri-
bution of the event's occurrence act in conjunction with the antecedent
moisture conditions within the particular drainage basin to cause varia-
tions in the rates, patterns, and volumes of runoff, and in the concentra-
tion level of the pollution parameters entrained in the runoff flows.
As the precipitation reaches the ground, it comes in contact with either
a pervious or an impervious area. In an urban site, examples of
impervious areas are streets, parking lots, and roofs, whereas exam-
ples of pervious areas are the bare or vegetally covered soils located
within the urban basin. Generalizations of land use characteristics
have been developed in terms of runoff and have been employed by
engineers for many years to determine runoff (e. g. , the rational
formula written as Q=CiA gives peak discharge when "C" represents a
function of land use, "i" is the precipitation intensity, and "A" categorizes
the drainage area). The precipitation which is unable to infiltrate the
surface now transverses the surface until deposited into a channel which
conveys it from the area. In this process, the runoff water entrains
pollutional material from sources on the surface or within the channel.
124
-------
Certain variables in the channel conditions affect the quality of the
flow. For example, if a channel is open and unimproved, potholes and
vegetation will catch organic material as the flow recedes, and hold it
until the next flow flushes the decomposed or decomposing material
farther down the channel. Laterals entering the main channel exert
an influence on the amount of pollution entrained. Significant differen-
ces have been noticed between the storm water flow to the main channel
via covered laterals attached to street inlets and via open ditches
paralleling the streets.
Initially, one must consider the temporal condition of the watershed.
The general sanitary conditions of the individual parcels influence the
environment of the entire drainage basin. Some of the parcel indica-
tors are the housing or establishment condition, the number of uncovered
garbage cans, piles of rubbish and rubble, autos and animals maintained,
the presence of privies, and the amount of litter in the streets which
bound the parcel.
It is important to note that an area classified as residential or com-
mercial in one section of an urban community is not the same environ-
mentally as another area so classified. For example, in a new middle
to upper class subdivision, the general environmental conditions are
normally good to excellent. The yards are well-kept with no litter or
piles of rubble. Furthermore, most individuals in these areas keep
clean the portion of the street fronting their own property. A different
section of the same community may have the same zoning and be
classified the same, but may have entirely different environmental
conditions due to the presence of the environmental deficiencies listed
above.
Figure 23 presents a dispersed pollution flow chart. This chart details
some of the groups of variables influencing the pollutional load as well
as the runoff and flow reaching a receiving stream. It is linkages such
as those partially illustrated in the table which complicate the predic-
tion of the pollutional loads from an area. No one variable can
be singled out which seems to influence the particular pollutant loads
to the same degree for each event.
The sets of input variables selected to be investigated were: precipi-
tation (current and antecedent events); environment (general sanitary
conditions); and the geomorphological characteristics of the watershed
(basin area, length of channel, relief, and land slope).
125
-------
to
PRE CIPITATION
1. Rainfall duration
2. Rainfall amount
3. Average intensity
PEOPLE ACTIVITIES
1. Traffic volume
2. Construction
3. New development
4. Recreation events
ENVIR ONMENT AL
1. Condition of structure
2. Condition of parcel
3. Deficiencies
4. Type & condition of
drainage channel
5. Maintenance & street
cleaning
1.
2.
3.
4.
LAST RAINFALL,
Length of time since
last event
Average intensity
Total amount
Duration
PHYSIOGRAPHIC
1. Length of main stream
2. Basin shape
3. Average stream slope
4. Average land slope
5. Impervious ness
6. Ground cover
LAND USE
1. Residential
2. Commercial
3. Industrial
4. Open space
5. Unused space
6. Street area
— ^
/
POLLUTION
PARAMETER
CONCENTRATION
FIGURE 23 DISPERSED POLLUTION FLOW CHART
-------
TABLE 52
POLLUTIONAL LOAD CRITERIA
Pollution
Category
Measurable
Parameter
Possible
Sources
Bacterial
Total coliform
Fecal coliform
Fecal streptococcus
Humans
Land mammals
Birds
Organic
BOD
COD
TOG
Organic matter
Leaves
Grass clippings
Humans and other animals
Oil and grease
Nutritional
Nitrogen
Phosphates
Fertilizers
Leaching from minerals
Decomposition of organic
matter
Solids
Suspended solids
Clay
Silica
Organic matter
Dissolved solids
Carbonates
Chlorides
Sulfates
Phosphates
Nitrates of calcium
Organic matter
Erosion of cleared land
Dust and dirt from streets
Unimproved drainage
channels
Erosion of cleared land
Leaching from minerals
Soluble dust and dirt
from streets
127
-------
The output variables descriptive of pollution are the various bacterial,
organic, nutrient, and solids parameter concentrations and their associ-
ated loadings. Table 52 illustrates pollution categories, the measur-
able parameters,and the possible sources of the pollutants. This chart
is not intended to present all of the possible sources, but only to indi-
cate some of the most common ones. The investigation technique re-
quires relating inputs to outputs from the homogeneous sections
within the basins, and aggregating the results to obtain a value repre-
sentative of the total drainage area.
Correlation Analysis
The values of the correlation coefficient (R) determined by standard
correlation analysis were used to examine the degree (or intensity) of
association among the study variables. Whereas the simple correla-
tion coefficient always lies between -1 and +1, the multiple correlation
coefficients range between 0 and 1. If the value of the coefficient is 0,
the variation between the variables is unexplained. The results of the
correlation analysis are shown in Tables 53 through 56.
The coefficients were tested against the null hypothesis that there was
no correlation between the variables. This hypothesis is rejected for
values greater than the 5 percent critical point.
Correlation matrices between independent variables are shown in
Tables 53 and 54. Table 53 shows the associations between land
use activities on the fifteen sites. As would be expected, the total
area is correlated with the variables depicting the areas of various
land use activities. It is felt that possibly the classifications of land
use held by the TMAPC should be redefined. The land use categories
should include only the area devoted to specific types of use. For
example, a forty acre industrial site would not be listed just as a forty
acre industrial parcel, but would be further delineated to include the
street, open space, and transportation area, as well as the area de-
voted strictly to industrial activity.
The residential area is highly correlated with the street area and
institutional area. This is understandable in that house sites are usually
required to front on a street along at least one side of a parcel. There-
fore, an increase in housing also produces an increase in street area.
In like manner, discrete amounts of institutional area (school sites)
are required at predictable intervals in the growth of residential areas.
128
-------
TABLE 53
CORRELATION MATRIX
LAND USE ACTIVITIES3"
Total Street Residential
Symbol Area Area Area
(1) (2) (3)
(1) 1.0000 0.8162** 0.6682**
(2) 1. 0000 0. 6707**
(3) 1.0000
(4)
(5)
(6)
(7)
(8)
(9)
Commercial Industrial
Area Area
(4) (5)
0. 6327* 0.
0.4113 0.
0. 1556 -0.
1.0000 0.
1.
6125*
2825
0616
5229*
0000
^
Institutional
Area
(6)
0.
0.
0.
0.
0.
1.
6874**
4992
6862**
6313*
1551
0000
Transportation Open
Area Space
(7) (8)
0.
0.
-0.
0.
0.
0.
1.
0280
1350
2471
0600
0248
0032
0000
-0.
-0.
-0.
-0.
-0.
-0.
-0.
1.
0571
2352
0410
0634
2080
1005
1515
0000
Unused
Space
(9)
0.
0.
0.
0.
0.
0.
-0.
-0.
1.
6115*
3262
1390
2939
7799**
1344
1077
2180
0000
aData input was the area of land use activities in acres in January 1969, for all 15 test areas.
Levels of significance:
* 95 percent level
**99 percent level
-------
TABLE 54
CORRELATION MATRIX
SELECTED ENVIRONMENTAL AND LAND USE FACTORS a'b
oo
Symbol
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
El HI %
Poor
Housing
(1) (2) (3)
1.000 0.926** -0.831**
1.000 -0.882**
1.000
Refuse
Def. /Acre
(4)
-0. 944**
-0. 810**
0. 826**
1.000
Total Def.
Def. /Acre
(5)
-0. 962**
-0. 833**
0. 806**
0. 981**
1.000
%
Com.
Use
(6)
-0.007
0. 009
-0. 136
-0. 009
-0.007
1.000
%
Ind.
Use
(7)
-0.039
-0. 129
0.035
-0.094
-0. 106
0. Ill
1.000
%
Res.
Use
(8)
-0. 118
0.032
0.051
0. 179
0. 167
-0.374
-0.464
1.000
%
Arterial
Streets
<9)
-0. 187
-0. 198
0.017
0.258
0.211
0.510
-0.042
-0. 196
1.000
Res. Density
Peo. /Res, Acre
{10)
-0. 517*
-0. 426
0. 272
0.571*
0. 560*
0.406
-0. 129
0. 182
0. 648**
1.000
Levels of significance:
* 95 percent level
** 99 percent level
Data taken from all 15 test areas
-------
TABLE 55
CORRELATION COEFFICIENTS
ARITHMETIC MEAN OF PARAMETER CONCENTRATIONS VS.
LAND USE VARIABLES3"
Pollution
Parameter
Name
Total coliform
Fecal coliform*
Fecal streptococcus
BOD
COD
Organic Kjeldahl nitrogen
Soluble orthophosphate
Total solids
Suspended solids
Specific conductance
El
Symbol
M
M?
M3
M4
M5
MY
M8
Mg
M12
M16
These correlation coefficients
Independent Variables*3
Arterial Streetsc Other Streets^ Residential
(Acres/Acre) (Miles/Acre) Density
(Peo. /Res. Acre)
"V "V
xl A13
-0.
-0.
-0.
-0.
-0.
0.
0.
0.
0.
0.
856**
192
058
121
426
330
118
116
102
031
are based on
-0.
-0.
-0.
0.
0.
0.
0.
0.
0.
0.
264
076
157
373
304
553*
508
555*
554*
242
15 observations (All
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
X16
634*
095
28.8
102
373
139
228
214
237
046
x17
0.
-0.
0.
0.
0.
0.
0.
0.
0.
0.
691**
155
137
121
533*
236
068
060
075
147
Main Covered
Storm Sewere (mi)
X19
0.
0.
-o.
0.
0.
0.
0.
0.
0.
0.
303
100
030
479
550*
022
029
044
002
269
1 5 test areas).
* 95 percent level
** 99 percent level
Arterial Streets--Ratio of area of arterial streets to total area of the drainage shed.
Other Streets--all streets except arterial streets.
All covered interceptor storm sewer greater than 24 inches in diameter.
Geometric mean by events.
-------
TABLE 56
CORRELATION COEFFICIENTS3-- b
ARITHMETIC MEAN OF PARAMETER CONCENTRATIONS VS.
SELECTED PERCENTAGE LAND USE VARIABLES
Pollution
Parameter
Name
Total coliform
Fecal coliform0
Fecal streptococcus0
BOD
COD
Organic Kjeldahl nitrogen
Soluble orthophosphate
Total solids
Suspended solids
Specific conductance
Symbol
M
M2
M3
M4
M5
M7
M8
Mq
Mj2
•^16
Other
Streets
X2°2
0.370
-0.050
-0.072
-0.281
-0. 044
-0. 548*
0.455
0.401
0.384
-0. 182
Residential
Land
X2°3
0. 244
-0.070
-0. 137
0. 218
0. 037
0. 164
0. 229
0.379
0.424
0. 087
Commercial
Land
X24
-0.061
-0.075
0.043
0. 124
0. 160
0.079
0.017
0.041
0.055
0. 061
Industrial
Land
X25
-0. 126
0.514*
0.094
0. 198
0. 279
0.083
0. 660*
0. 728**
0. 736**
0. 152
Open
Space
X2°6
-0. 350
-0.095
0. 192
-0. 128
-0.331
0. 137
-0. 100
-0.049
-0.021
-0.044
Unused
Space
X29
0. 060
-0.073
0. 199
0. 137
0.383
0.332
0. 788**
0. 733**
0. 708**
0.028
These correlation coefficients are based on 15 observations (All 15 test areas).
"Levels of significance:
* 95 percent level
** 99 percent level
cGeometric mean by events
-------
A significant amount of correlation exists between the commercial area
and both the industrial and institutional areas. Although these relation-
ships are expected when analysis is performed at the regional or
metropolitan level, they were unexpected at the level of analysis in this
study.
The correlation between industrial area and unused space can be ex-
plained partially by the usual associations of land uses. In areas with
mixed uses and areas zoned for industrial use, vacant land waiting
for development is classified as unused space. Its location is usually
such that it is not economical to utilize it during the interim period
for a higher order use, such as recreational land or even agricultural
land.
Table 54 shows the relationships between selected environmental and
land use variables. As would be expected, the environmental variables
are highly correlated with each other. Residential density exhibits
a significant correlation with three of the five environmental variables
used. This relationship leads to the conclusion that higher population
densities increase the probability of a poor environment.
The significant relationship between the arterial streets and residential
density can be interpreted in view of classic zoning procedures. Ar-
terial streets are usually strip zoned for commercial use. Parcels
with multifamily or apartment units are ordinarily used as buffers be-
tween commercial areas and the areas which are restricted exclusively
to single family dwellings.
Tables 55 and 56 show the correlation coefficients of the arithmetic
averages (geometric averages for bacterial parameters) of the pollution
parameter concentrations (by event) correlated against several land
use and environmental variables. The tables are based on 15 observa-
tions (15 test areas) and include all of the land use classifications
investigated on this project. Since each of the 15 watersheds considered
is "homogeneous" as to land use, the only correlation coefficients that
have meaning are the ones formed between variables common for all
test areas. The common variables are: Environmental Index (X,);
unused space (Xog); other streets (X,/ and ^22^' arterial streets (Xjg);
and main covered storm sewer (^2Q^'
From the tables it can be seen that the two solids categories and the
total coliform category had the most significant correlations. The
variables which correlated with total coliform indicate that these all
describe the general environmental factor of an area. This factor and
133
-------
its effects on the numbers of total coliform can be explained by the El,
residential density, and the length of other streets. The last category
is also an indicator of residential density, in that there is a direct
increase of street area with each increase in the number of residential
dwellings.
The highest correlation coefficients formed with the solids categories
are for the percentage of open space and industrial area and for the
variable depicting arterial streets. Since this coefficient was developed
with information from all test areas, the exceptionally high solids
data from Test Area 1 may introduce a bias with respect to the variables
depicting percentage of unused space and industrial area. The corre-
lation with the amount of arterial streets can be interpreted in view
of the fact that arterial streets are indicators of the degree of develop-
ment. The imperviousness added by arterial streets correspondingly
increases the amount and velocity of runoff, which act together to ex-
pand the solids load, either by scouring of channel banks or by greater
flow entrainment of particles on the channel bed.
The COD concentration is significantly correlated with the residential
density and the length of main covered storm sewer. Residential
density may influence the COD value either through home maintenance
functions performed for a large automobile population or through
the observed study relationship that the high population density test
areas were in older, residential sections which had greater amounts
of vegetal cover. The decay products from this vegetal material may
cause the higher COD loading. In the same manner, the greater the
length of storm sewer within an area, the more probable the oppor-
tunity for decay of organic matter in the damp confines of the sewer.
The significant correlations of the variables for the percentage of
industrial and unused area with soluble orthophosphate may be also
biased by the high results from Test Area No. 1. The other significant
correlations shown in the table are unexplainable at present.
Factor and Principal Component Analysis
A large number of variables can influence the types and amounts of
pollutional loads flushed from an urban area during storms. In the
initial stage of the study, variables thought to exert considerable in-
fluence on pollution were selected for measurement in hopes that, as
the study progressed, the primary determinants of urban pollution
could be identified.
134
-------
These variables were grouped into one of two major classifications.
One classification was composed of variables which pertained to the
precipitation regimen. This regimen produces the driving force which
extrudes the pollution from its source and geographically redistributes
it in a manner which has been deemed unsuitable for man's environ-
ment. The other classification pertained to characteristics of the land
surface, and included factors, both naturally occurring and those caused
by man, which could react with precipitation to produce an undesirable
pollutional condition at a point downstream or downslope from the area
at which the characteristic is located. The models developed with data
sets from the two classifications were deterministic since the hydro-
logical and demographical categories were specified.
The multivariate methods of factor and principal component analysis
were used to examine the variables in the land surface classification.
Both methods have been used previously in various fields of study.
Factor analysis has been used in geology (17), hydrology (18), and water
quality (19). Principal component analysis has been applied to problems
in econometrics (20) and water resources (21). Factor analysis was used
to determine the degree of grouping and importance of the groups when
a number of different variables were lumped together. This form of
analysis served as an aid in selecting variables for regression studies
in that it delineated the variables which accounted for the most variance
within the factors. The principal components method was used to
determine index numbers from data on groups of land based variables for
each test area. These index numbers were then compared with the
measured pollution loads obtained by sampling.
The computer program given in Version III of IBM's SSP/360 was used
to perform factor analysis on the selected variables. An intermediate
step in the program was the computation of eigenvalues and eigenvectors
from the correlation matrix of the variables which were studied together.
The 36 variables measured for this portion of the study could loosely
be grouped into classifications which pertained either to drainage,
environment, land use, or public utility decisions (i. e. , covered storm
sewers). Factor analysis was performed on each of the four groups. The
results for the analysis of the drainage characteristics are shown in
Table 57.
The rotated factor matrix contains three factors which together explain
87. 77% of the variance exhibited by the seven variables.
135
-------
TABLE 57
ROTATED FACTOR MATRIX OBTAINED BY FACTOR ANALYSIS
OF SELECTED DRAINAGE CHARACTERISTICS
OF THE TEST AREAS
Variable
Factor 1
Area 0.
Length of main channel 0.
Length of main channel
to centroid of area 0.
Fall of watershed 0.
Average main channel
slope -0.
Average land slope 0.
Impervious cover 0.
Explained covariance (%)
Cumulative covariance (%)
9549
8339
8866
5163
1857
1806
1621
39.33
39.33
Loadings
Factor 2
-0. 1562
0. 0970
-0.0181
0. 1098
0. 9057
-0. 0516
0.7974
21.50
60.83
Factor 3
0. 0263
0. 3558
0.2117
0. 7489
0. 2758
0. 9145
-0.4904
26.94
87.77
136
-------
The first factor, which explains 39. 33% of the variation, is dominated
by the variable of watershed area. Two other variables influence the
factor at slightly lower levels. These variables are the total length of
channel, which is a measure of the drainage density of the watershed,
and the length of the main channel to the point nearest the centroid of
the basin, which is an indicator of the catchment shape. The second
factor, explaining 21. 50% of the variance, is ordered by the variable
of channel slope with contributions from the variable of area impervious -
ness. The third factor, which accounts for 26. 94% of the variation, is
controlled by the land slope variable. An important secondary influence
is exerted by the variable of watershed relief.
The loadings of the factors can be interpreted when several drainage
basins are examined. The sites with large values for the first factor can
be expected to produce larger volumes of runoff than the sites with lower
values. The second factor is a measure of relief and urban development.
The sites with larger values can be expected to produce greater velocities
of flow and higher percentage increases in peak flow than the sites with
lower values. High values for the third factor indicate greater relief
or ruggedness of the site, and, therefore/ greater erosional capability.
After examination of the grouped factor runs, 22 variables from the four
major classifications were selected, and factor analysis was performed.
Eight factors which together explained 95 percent of the variation were
computed. The variables within the factor that exhibited the most influ-
ence on the factor were used in regression analysis; the results are shown
in Table 58.
The eigenvectors or principal components from this run were used to com-
pute an index value for each site. The variables and the values of the first
two eigenvectors are shown in Table 58. The first eigenvector exhibits
high factor loadings on the variables affecting the environment. The
second shows the most important loadings on the first four drainage
characteristics and the public utility decision variable, which measures
miles of main covered storm sewer on the watershed. The values for
the 22 variables used in the analysis were standardized. The standardized
values for each site were multiplied by the corresponding numerical
coefficient in the eigenvector and summed to obtain an index value for the
site. The index numbers for each site are shown in Table 59.
The index values for the components were ranked and compared with
ranks obtained from pollutional measures made for the test areas. The
137
-------
TABLE 58
VARIABLES AND ASSOCIATED EIGENVECTOR VALUES USED
TO COMPUTE THE INDEX VALUES FOR THE STUDY SITES
1st Principal
Variable Component
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
Refuse
Burners
Rubble
Lumber
Old autos
Poor sheds
Main covered storm sewer
Covered sewer/total length
Arterial streets
Other streets
Residential land
Commercial land
Area
Length of main stream
Length of main stream
to point nearest centroid
of area
Fall of watershed
Average main channel slope
Average land slope
Impervious cover
Institutional land and
open space
Unused space and trans -
portational land
Industrial land
0.36127
0. 35496
0.36271
0.35921
0.35347
0.32949
0. 13460
0. 18760
0.08249
0. 19831
0.08092
0.07502
-0.01697
-0. 11978
-0. 11322
-0. 11776
-0.08598
-0.23110
0.03932
-0. 16610
-0.06838
-0.04273
2nd Principal
Component
0. 10051
0. 11619
-0.02609
-0.00353
0. 13199
-0.05824
0.40421
0. 13939
0.05688
-0.07006
-0.09034
0. 18551
0.46560
0.36973
0.42643
0.31144
0.06116
0. 15944
0.02437
-0.01390
-0.04938
0.23796
138
-------
TABLE 59
INDEX VALUES FOR STUDY SITES
FROM PRINCIPAL COMPONENTS
Test
Area No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Index No. from 1st
Principal Component
-2.034
-0.835
-1. 583
-0.517
-1. 600
+0.599
-0.657
+0. 541
+6.474
-0.360
+4.993
-0. 635
-1. 613
-2.881
+0.996
Index No. from 2nd
Principal Component
+2.497
-0. 506
+0. 504
+3. 626
+1. 660
+0. 288
-1,645
-1.041
-1. 958
-0.009
+3. 604
-2.439
-0. 573
-0.469
-3.015
139
-------
TABLE 60
STUDY SITE ENVIRONMENTAL RANKINGS*
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Index No. from
1st Principal
Component
2
6
5
9
4
12
7
11
15
10
14
8
3
1
13
EIb
1-3
4-5
7-8
10-11
4-5
13
6
12
14
9
15
1-3
7-8
1-3
10-11
BOD Load
(Ib. /acre/year)
10
9
2
14
11
5
3
12
4
15
13
7
6
1
8
Rankings
COD Load
(Ib. /acre/year)
10
7
4
14
11
8
3
12
9
15
13
5
6
1
2
Based On:
Total Coliform
Geometric Mean
(number/ 100 ml )
7
5
8
2
11
10
4
13
15
9
14
6
3
1
12
Fecal Coliform
Geometric Mean
(number/ 100 ml )
11
13
14
10
12
15
2
8
4
5
9
1
3
7
6
Fecal Strep.
Geometric Mean
(number /1 00 ml )
5
2
12
10
4
14
3
7
9
15
8
1
6
13
11
Sites ranked in order from best (rank = 1) to poorest (rank=15).
Multiple entries indicate that several sites have equal El values.
-------
TABLE 61
STUDY SITE RANKINGS IN RELATION TO
DRAINAGE CHARACTERISTICS21
Test
Area
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Index No. from
2nd Principal
Component
13
7
11
15
12
10
4
5
3
9
14
2
6
8
1
Rankings Based On
COD Load
(Ib. /acre/year)
10
7
4
14
11,
8
3
12
9
15
13
5
6
1
2
•
Total Solids Load
(Ib. /acre/year)
15
10
11
14
1
3
7
9
8
13
12
4
6
5
2
aSites ranked from best (rank=l) to poorest (rank=15).
-------
rankings from the first principal component were compared with
rankings of BOD, COD, total coliform, fecal coliform, fecal strepto-
coccus, and a calculated El described in Section 6 of this report. The
results are shown in Table 60. This method appears to have promise
as a means of classifying an area as to bacterial output. The same
procedure was used for drainage characteristics; results are given in
Table 61. The sites with larger values for the index computed from the
second eigenvector should produce greater loads of total solids and,
possibly, COD per acre than other sites with lower indexes.
This method lends itself to survey techniques once pollutional loads
have been measured in a base watershed within an area. Information
from map's, municipal authorities, and local health departments is
applied in place of sampling to compare urban drainage basins. The
procedure can be used to compute and compare pollutional loads be-
tween the base sites and the sites already developed. Planners can
utilize the method to determine what the pollutional loads will be from
future developments under different land uses. However, additional
work is needed to determine whether these variables adequately
describe the test areas, or whether others are required. This can be
regarded as continuing example of the expanding quantitative aspects
of the planning process.
Regression Analysis
This type of analysis was performed to construct models for predicting
or estimating the pollution parameter concentrations. Both univariate
and multivariate regression methods were used. Since multiple re-
gression is but an extension of the methodology for univariate analysis,
the defining equation will be for the former type.
The equation for the multiple linear regression model is:
Y=b0 + biXj + b2X2 + --- + bkXk + u (10-1)
where Y is the dependent variable, Xj (i=l to k) represents an explana-
tory variable, b; (i=l to k) represents a regression coefficient, and u
is an unexplained residual term. There are n of these equations.
In this case, the Y's are the pollution parameter concentrations.
Specific symbols used to represent these concentrations for individual
observations are designated Y^'s, while Mj's represent the arithmetic
14Z
-------
z
averages (by events) of all observations from each test area.
The Xj's are the independent variables which for this study depict
precipitation, land use, environment (land parcel sanitary conditions),
and drainage characteristics.
Factor analysis was used to indicate the independent variables most
suitable for univariate regression analysis. The symbols and units
for the dependent and independent variables used in this analysis are
listed in Table K-l in Appendix K. Neither all the pollution parameters
measured in the study nor all the independent variables were used in
this analysis. From the independent variables in Table K-l, the most
promising groupings of variables for multiple regression analysis were
selected by the additional use of factor analysis. No regression analysis
was performed with all the study variables grouped together.
The correlation coefficient (R) and the coefficient of multiple determina-
tion (R ) are possible criteria for the selection of the most reliable
equations. However, a high R value (close to unity) can often be mis-
leading. This is particularly true when only a small number of obser-
vations are used, because the increase in the number of variables may
have more of an influence on the accompanying increase in R than the
related explanation contributed by the variables. Since the equations
developed from this study include a maximum of only 15 test areas
(this corresponds to a maximum of 15 observations), large R^ values
may not be the best criteria for selection.
The F-value, which is the ratio of the regression mean square to the
residual mean square, is not necessarily a measure of the equation's
usefulness as a predictor. A significant F-value means only that the
regression coefficients explain more of the variations in the data than
would be expected by chance a specified percentage of time under
similar conditions. The level of significance selected for regression
analysis in the study was 95 percent.
It should also be noted that the use of the F-test requires that the
residuals be normally distributed. This distribution cannot be arbi-
trarily assumed to exist for hydrologic data or data on the concentra-
tion levels of the pollution parameters. Regression analysis, however,
can be used regardless of whether the data set is from a normal
di s t r ibution.
o
Geometric averages for bacterial parameters.
143
-------
The regression analysis was performed separately on each of the two
classifications mentioned previously in the discussion of factor analysis.
Utilization of the equations developed in the analysis of the precipitation
data would enable pollution loads to be predicted on an event basis. The
use of equations derived from land use data would enable planners to
evaluate the average pollutional loads that could be expected from a
site with certain land surface characteristics.
Precipitation Regimen - As has been discussed, the variables depicting
the precipitation regimen are among the most important in analyzing
the pollutional characteristics of an urban area. Two groups of inde-
pendent variables were developed to examine the influence of precipi-
tation. These were (1) those concerning data taken during the current
event and (2) data items from the antecedent event. The two categories
had the following associated variables:
Current Event Antecedent Event
Time since start Time since antecedent event
Antecedent amount Amount of antecedent event
Average intensity Duration of antecedent event
Average intensity of antecedent
event
It was reasonably assumed that the various pollution parameter con-
centrations (and thus pollution loads) at a particular time during a
precipitation event are functions of one or more of the variables in-
cluded in the above classifications. Data for these variables were
calculated for each sample. The values are shown in Table M-Z of
Appendix M.
The procedures used in these calculations were:
• Time since start (Zj)--The length of time in hours from the
start of rainfall to the starting time of a composite sample
or the time of a grab sample.
• Antecedent amount (Z2)--The total accumulated amount of
precipitation in inches that had occurred from the beginning
of rainfall to the sample collection time.
• Average intensity ^3) --The average intensity in inches per
hour. This value was obtained by dividing the accumulated
amount by the time since start. It should be noted that this
144
-------
value, as well as the antecedent amount for samples collected
after a rainfall has ended, remains the same for all samples
collected after the stop of the rainfall.
• Time since antecedent event (Z4)--The time in hours that had
elapsed from the end of the previous precipitation event over
0. 10 in. to the starting time of the current event or the event
being sampled. This value does not change for the individual
samples collected during the current event.
• Amount of antecedent event (Z5)--The total amount of the ante-
cedent event in inches.
• Duration of antecedent event (Z/)--The duration of the antece-
dent event in hours.
• Average intensity of the antecedent event (Z^^-The average
intensity of the antecedent event in inches per hour.
All the above precipitation variables except Z^ were investigated by
scatter gram plotting, univariate linear regression, and multiple
linear regression. The dependent variables were concentrations of the
pollution parameters. The results of the univariate and multivariate
regression analysis are shown in Table K-2 in Appendix K.
As can be seen from an examination of the table, there is at least one
significant univariate equation that could be used to predict the pollu-
tant concentration of each of the parameters. Significant multiple
regression equations are also available to use with each of the param-
eters, with the exception of total solids. The deficit in this category
is understandable since total solids is primarily dependent on the
velocity of flow. The only factor of the six remotely related to the
velocity of flow is Z-$ (the antecedent average intensity), and its effect
on the significance level of the multiple equation in which it appears is
noticeable.
The examination of the precipitation variables was extended further to
include an analysis of the BOD concentration measured on the rising
limb of the runoff hydrograph for each test area. The BOD observa-
tions were transformed to natural logarithms, and multiple linear
regression was run against both the current and antecedent precipi-
tation variables. It was hoped that the analysis would further charac-
terize the test areas by grouping them by similar equations. Table 62
shows the correlation coefficients which were obtained in this analysis.
145
-------
TABLE 62
CORRELATION COEFFICIENTS
In BOD VS. RISING LIMB PRECIPITATION VARIABLES3-
Test
Area
No.
1
2
3
4
5
6
7
8
9
10C
11
12
13
14
15
Current Precipitation Variables
b
1 2 3 JL £ J
-0. 594*
-0. 560*
-0.269
-0. 511**
0. 470*
-0.595
-0.496
0. 384
-0. 915**
0. 725*
0.386
-0.405
-0. 760*
0. 552*
-0.356
-0. 642*
-0. 711**
-0. 350
-0. 653**
-0. 166
-0. 753*
-0. 652*
-0. 150
-0. 535
-0.433
0.518
-0. 860**
0. 699*
0. 200
-0. 636**
-0.031
-0. 363
-0.009
-0. 666**
-0.431
-0. 142
-0. 244
-0.454
0. 262
-0.771*
0.285
-0.407
-0.637
-0. 508*
-0.438*
0.651
0. 788*
0. 356
0.713**
0. 650*
0.753
0.684
0.475
0. 930**
0. 833**
0.770
0. 893**
0.848
0. 566
0. 678*
Antecedent Precipitation Variables
Z4 Z5 Z7 Z4'Z5'Z7
-0. 663*
-0. 053
-0. 142
0. 202
-0. 056
-0. 776**
-0. 206
0.592
-0.697*
0. 145
0.434
-0. 138
-0. 207
0. 047
-0. 186
-0. 067
0. 034
0. 199
0.218
0. 676*
-0.040
0.286
0.395
-0. 662*
0.064
-0.397
0.727*
0. 108
0. 576*
0. 303
0. 398*
-0. 169
-0. 550**
0. 812**
0.433
0.061
0. 199
-0. 553
0.299
-0. 212
0. 257
-0. 612**
0.750
0.603
0.430
0.320
0. 829**
0. 906*
0.566
0. 958*
0. 857*
0.743
0.441
0.457
0. 916**
0. 759**
Legend:
Zj = Time Since Start of Rainfall (hr. ) Z^ = Time Since Antecedent Event (hr. )
Z2 = Cumulative Amount of Precipitation Z^ = Amount of Antecedent Event {in. )
(in. ) Zy = Average Intensity of Antecedent
Z3 = Avg. Intensity Preceding Sample Event (in. /hr. )
Collection (in. /hr. )
Correlation coefficients for multiple regression equations using all three listed independent
variables.
cAntecedent selections were skipped because of singular matrix.
-------
The time since start of rainfall (Z^) and the cumulative amount of
precipitation (Z2), which are both current precipitation variables,
are the most influential factors on the BOD concentrations.
Table K-3 shows the multiple regression equations developed from, the
current precipitation variables. The equations exhibit considerable
variation between the test areas. The most consistent variable
(as to sign) among the test areas was Z^ • This variable is directly
related to the flow at the time of sample collection. The predominating
negative coefficient indicates that a decrease in concentrations shown
in the equations is more than offset by the greater volumes of runoff
occurring between the start of runoff and the peak flow.
Land Surface Characteristics - These characteristics as defined have
included 3 categories of variables: (1) land use, (2) environment,
and (3) drainage. Land uses depict various land activities, such as
residential, commercial, industrial, recreational, and institutional.
The environmental variables are indicators of the general sanitary
conditions of a parcel of land and include such factors as state of
housing, refuse deficiencies, piles of rubble, and so on. Drainage
variables are geomorphic factors which aid in defining the drainage
characteristics of the watershed. The data items considered for this
analysis were determined as follows:
1. The test area parameter concentrations were calculated by
first averaging all sequential samples taken during any
one precipitation event and then averaging these results
with the grab sample results from other events which were
sampled. The mean value so obtained was considered to
be the representative concentration that would be found in
storm runoff from the test site. All of the dependent
variable input consisted of arithmetic averages except for
the bacterial parameters, which were calculated in terms
of geometric means. The averages were denoted as M^'s.
2. The land surface characteristics which were the independent
variables in the analysis were calculated from the data pre-
sented in Sections 5 and 6. The X^'s in the equations specify
the land use and environmental characteristics, while the
D^'s represent the drainage characteristics.
A complete listing of the symbols and units for each of the dependent
and independent variables considered for study is shown in Appendix H.
Factor analysis was used to eliminate those variables which were
147
-------
either similar to others in effect or which could be replaced by other
variables which explained more of the variations.
Regression analysis was performed using four sets of input data. The
data sets utilized were:
1--A11 15 test areas taken together
2--A11 test areas except 1, 12, and 14
3--Residential Test Areas No. 3, 5, 7, 8, 9, 13, and 15
4--Commercial and Industrial Test Areas No. 1, 2, 4, 6,
10, and 11
In data set 2, Test Areas No. 1, 12, and 14 were omitted because these
watersheds were considered non-typical for the urban area. Test Area
No. 1, which was undergoing development, recorded extremely high
solids and phosphate averages. Test Area No. 14 was eliminated be-
cause of the small impoundments located along the drainage channel.
The influence of the airport runways and adjoining open land of Test
Area No. 12 was also considered to be minor, since only small amounts
of land are usually devoted to this use in the typical urban area.
In data set 4, the regression equations for solids and soluble orthophos-
phate may be misleading due to the inclusion of Test Area No. 1. As
mentioned, this test area was undergoing development, and the high
solids and phosphate values obtained may be nonrepresentative of
developed industrial areas.
Univariate and multiple regression analyses were performed. The
equations were evaluated by correlation coefficients and F-values.
The selections of the best results are shown in Tables K-4 through
K-7 in Appendix K.
The results of the univariate analysis with the land use variables of all
15 test areas are shown in Table K-4. Significant equations were ob-
tained for prediction of COD, organic Kjeldahl nitrogen, soluble
orthophosphate, total solids, and total coliform.
Tables K-5, K-6, and K-7 present a selection of regression equations
developed from data sets 2, 3, and 4, respectively. Data set 2, which
includes data from both the residential and the commercial and indus-
trial land use groups, was analyzed by univariate and multiple regres-
sion. The results are shown in Table K-5. The most interesting
finding was the importance that can be attached to the significant
influence of both the natural drainage characteristics as depicted by the
D^'s and the man-made drainage characteristic ^-20 (ra^io of the
148
-------
TABLE 63
SUMMARY OF OCCURRENCE AND FREQUENCY OF SIGNIFICANT51 VARIABLES DETERMINED BY
REGRESSION ANALYSIS OF LAND SURFACE CHARACTERISTICS
Dependent
Variables
Total coliform 6
Fecal coliform 1
Fecal strep.
BOD
COD 2
TOC 1
Organic Kjeldahl
nitrogen 1
Soluble ortho-
phosphate
Total solids
Suspended solids
Independent Variables
X13 X14 X16 X17 X19 X20 X21 X22 X24 X25 X29 Dl D2 D3 D4 D6 D9
132 1 1
2 1
1
1
112 2
1 1
1 131 13
1 1 1
1 1211
1 1 2
^•Significance > 95 percent level
-------
TABLE 64
MIXED-USE REGRESSION EQUATIONS FOR SAMPLE CALCULATIONSa
Regression Equation
Correlation
(R)
F-Valuec
Equation
Number
Total Coliform (Thousands/100 ml)
M! = 565 - 4ZO (Xx) - 49. 3 (X2Q) - 6. 70 (D9)
COD (mg/1)
M5 = 71 - 45, 4 (Xi) + 2. 61 (X21) + 0. 0062 (D2)
Organic Kjeldahl Nitrogen (mg/1)
M? = 0, 23 - 0 (X1?) - 0. 029 (X20) + 0. 256 (D6)
Total Solids (mg/1)
M9 = 130 + 8. 99 (X20) + 2. 59 (X22) + 2. 06 (D4)
0. 885
0.839
0.887
0.690
9. 81**
2.42
K-97
K-109
K-121
K-129
Equations developed using all test areas except 1, 12, and 14.
Legend for dependent and independent variables:
M- = Arithmetic mean (by events) of parameter concentration (geometric mean
by events for total coliform)
D2 = Length of main stream (ft. )
D4 = Fall of drainage area (ft. )
D£ = Average land slope (%)
Dg = Form factor (dimensionless)
Xi = Environmental Index (dimensionless)
Xj7 = Residential density (people/res, acre)
X20 = Covered sewer/total length (ratio)
X2j = Arterial streets (%)
X22 = Other streets (%)
cLevels of significance:
* 95 percent level
** 99 percent level
-------
covered sewer to the total length of storm sewer) on the pollution
parameters. There is at least one significant equation in each of the
following categories: total coliform, fecal coliform, BOD, COD,
organic Kjeldahl nitrogen, soluble orthophosphate, and total solids.
Tables K-6 and K-7 show the results from, the separate analysis of the
residential and the commercial and industrial land use areas. Signifi-
cant regression equations for the residential test areas were found
for only the total coliform and COD categories. In the analysis of the
commercial uses, significant equations were developed in the total
coliform, fecal coliform, fecal streptococcus, TOC, organic Kjeldahl
nitrogen, total solids, and suspended solids categories.
The variables and frequency of their occurrence in the 39 significant
regression equations found in the analysis are shown in Table 63 .
Most of the data concerning the 18 independent variables in this table
can be obtained either from maps or from files of the planning and action
agencies of the subject municipality. The calculation of the Environ-
mental Index may require the assistance of the local public health
agency if data on a past environmental survey is not available for use.
This group of equations or a selection of equations from this group
can be used to obtain a first order estimate of the storm water pollu-
tion loads in an urban area other than Tulsa if the precipitation regimen
is similar.
The use of these equations is illustrated in Table 64. Calculations with
these equations using the minimum and maximum values of the Tulsa
test areas are presented. This is done to show the predictable
range of pollutant concentrations obtained within the test data. Also
included are examples showing the use of data from individual test
areas.
Sample Calculations
1. Total Coliform
The multiple regression equation for total coliform (mixed
use) is:
M1=565-420 (Xx) -49. 3 (X20) -6. 70 (D9)
For an area with good environment (Xi=EI=l. 00), this
equation reduces to:
151
-------
49. 3 (X2o) -6. 70 (D9)
The ranges of values for X20 and Dg are:
Symbol Min. Max. Item
X2Q 0. 61 3. 78 Covered sewer /total length
Dg 0. 82 2. 85 Form factor
At maximum values for X2g and Dg, the calculated MI is nega-
tive:
Mi = 145-49. 3 (3. 78) -6. 70 (2. 85} = -60
Consequently, this regression equation is not suited to the pre-
diction of total coliform concentrations near the maximum
values for X2o an
-------
For EI=0 (bad environment):
M5=71 + 2. 61 (X21) + 0. 0062 (D2)
The ranges of values for X-,, and D2 are:
Symbol Min. Max. Item
X21 0 18. 93 % Arterial streets
D2 2170 11, 200 Length of main stream (ft.)
For EI=1. 00:
The minimum COD would be:
M5=26 + 0. 0062 (2170) = 39 (minimum from test sites
studied: 42)
For EI=0:
The maximum COD would be:
M5=71 + 2. 61 (18. 93) + 0. 0062 (11200) = 190 (maximum
from test sites studied: 138)
For Site 12:
M5= 71 -45. 4 (1) + 2. 61 (3. 94) + 0. 0062 (5710) = 61 (actual
value: 45)
For Site 5, a residential test area:
M5= 71 -45. 4 (0. 99) + 2. 61 (3. 94) +0. 0062 (11200) = 106
(actual value: 138)
One can conclude that this equation can be a somewhat useful
predictor, even near the limits of some of the independent
variables.
3. Organic Kjeldahl Nitrogen
The regression equation (mixed use) is:
153
-------
M?=0. 23-0 (X1?) -0. 029 (X20) + 0. 256 (D&) (Independent of
X17)
The ranges of values for X2Q and D£ are:
Symbol Min. Max. Item
X2Q 0- 61 3. 78 Covered sewer/total length
E>6 0. 75 4. 60 % Land slope (At DQ=0, the
land slope would be at a minimum)
For I>6=0, the equation would be:
M? = 0. 23-0. 029 (X20)
The minimum value from this equation (at X2Q=3. 78) would be:
M7=0. 23-0. 029 (3. 78) = 0. 12
If there were no covered sewers (X2Q = 0), on the other hand,
the nitrogen concentration would depend only upon the land
slope:
M7=0. 23 + 0. 256 (D0)
For a 4. 6% land slope (maximum of test areas studied):
M7=0. 23 + 0. 256 (4. 6) = 1. 41
For Test Area 6:
M7=0. 23-0. 029 (3. 78) + 0. 256 (2. 19) =0.68 ( actual value : 0. 65)
For Test Area 13:
M?=0. 23-0. 029 (0. 55) + 0. 256 (4. 60) = 1.39 (actual value: 1. 46)
For mixed land use, this regression equation was one of the most
accurate ones obtained.
4. Total Solids
The best multiple regression equation for total solids (mixed
154
-------
use) is:
Mg=130 + 8. 99 (X2Q) + 2. 59 (X22) + 2. 06 (D4)
The ranges of va,lues for the independent variables are:
Symbol Min. Max. Item
X2Q 0. 00 3. 78 Covered sewer/total length
X22 0. 00 35. 80 % Other streets
04 30 186 Fall of drainage area (ft. )
Using these limits, the corresponding minimum value for
total solids would be:
Mg=130 + 8. 99 (0. 61) + 2. 59 (0. 00) + 2. 06 (30) = 197 mg/1
(minimum of test areas studied = 199)
The maximum would be:
M9=130 + 8. 99 (3. 78) + 2. 59 (35. 80) + 2. 06 (186) = 640 mg/1
(maximum of test areas studied = 2242)
For Test Area 1:
M9=130 + 8. 99 (0. 61) + 2. 59 (7. 72) + 2. 06 (113) = 388 mg/1
(actual value: 2242 mg/1)
For Test Area 12:
M9=130 + 8. 99 (0. 00) + 2. 59 (0. 00) + 2. 06 (58) = 249 mg/1
(actual value: 199 mg/1)
For extreme cases, therefore, this regression equation is of
only limited usefulness.
It is obvious that these models, as well as most multiple regression
equations, have definite boundary limits for the input independent
variables. In addition, it cannot be overemphasized that extrapolation of
the statistically fitted function beyond the range of values of the pre-
dictor variables may lead to erroneous results for the dependent para-
meter. If one strictly follows statistical results, regression equations
with the largest coefficients of multiple correlation should be used as
the "best" equations. However, due to the errors inherent in sampling,
analysis, and data handling, the equations (models) which give the best
155
-------
explanations are preferred. Thus, statistical results are used as much
as possible within the limitations of rational judgments.
The utilization and demonstration of a few of the test equations in this
section have shown that the equations will not be suitable for predicting
pollutant concentrations in all cases. As found in the example for total
coliform, the values of variables and the mix of variable values in the
equations, even though within the range of numbers found in Tulsa, will
not give reliable answers in certain combinations. Judicious caution
must be exercised in the intrepretation of equation results. When obviously
wrong results are obtained with the best equations, it is recommended that
other equations from Appendix K be utilized and the results compared with
those obtained using the best equations.
156
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SECTION 11
ACKNOWLEDGMENTS
AVCO Economic Systems Corporation is deeply indebted to the following
organizations for the services they rendered to the ESC Environmental
Systems Tulsa Project Office in carrying out this study for the Federal
Water Quality Administration. Without their cooperation and assistance,
the study would not have been possible.
Public Agencies
Tulsa Metropolitan Area Planning Commission
Tulsa City-County Health Department
City of Tulsa Street Department
City of Tulsa Engineer's Office
City of Tulsa Water and Sewerage Department
Acknowledgment with grateful appreciation is made to Professor George
W. Reid and his experimentation at the University of Oklahoma for the
helpful conceptual inputs to this research effort.
Acknowledgment is made to members of the AVCO Economic Systems
Corporation staff as follows:
Washington Office
Paul R. Walters Project Director
Tulsa Project Office
Jerry G. Cleveland Principal Investigator
Ralph H. Ramsey Project Engineer
Gary L. Miessler Analytical Chemist
Robert J. Gilbert Lab Technician
Gary D. Woodruff Engineering Aide
Charles A. Johnston Engineering Aide
Norma Z. Whitworth Typist
157
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SECTION 12
REFERENCES
Text References
1. Weibel, S. R. , Anderson, R. J., and Woodward, R. L., "Urban
Land Runoff as a Factor in Stream Pollution. " Journal Water
Pollution Control Federation, Vol. 36, No. 7 (July, 1964), p. 914.
2. Benzie, W. J. , and Courchaine, R. J. , "Discharges From.
Separate Storm Sewers and Combined Sewers. " Journal Water
Pollution Control Federation, Vol. 38, No. 3 (March, 1966),
p. 410.
3. Burm, R. J. , Krawczyk, D. R. , and Harlow, G. L. , "Chemical
and Physical Comparison of Combined and Separate Sewer
Discharges. " Journal Water Pollution Control Federation,
Vol. 40, No. 1 (January, 1968), p. 112.
4. American Public Works Association, "Water Pollution Aspects
of Urban Runoff. " FWPCA Publication No. WP-20-15, U. S.
Department of the Interior, January, 1969.
5. Evans, F. L. , III, Geldreich, E. E. , Weibel, S. R. , and
Robeck, G. G., "Treatment of Urban Storm Water Runoff. "
Paper presented at the 39th Annual Meeting of the Water Pollution
Control Federation in Kansas City, Missouri, September 25-30,
1966.
6. Simpson, George D. , and Curtis, Lament W. , "Treatment of
Combined Sewer Overflows and Surface Waters at Cleveland,
Ohio. " Paper presented at the 41st Annual Conference of the
Water Pollution Control Federation, Chicago, Illinois, September
23, 1968.
7. Hittman Associates, A System Study, Design, and Evaluationjpf^
the Local Storage, Treatment, and Reuse of Storm Water.
Columbia, Maryland, August, 1968.
8. Federal Water Pollution Control Administration, U. S. Depart-
ment of the Interior, "Seminar on Storm and Combined Sewer
Overflows. " Edison Water Quality Laboratory, Edison, New
Jersey, November 4, 5, 1969.
159
-------
REFERENCES- - Continued
9. Waldrop, Reuel H. , "Community Block Survey and Socioeconomic
Stratification. " U. S. Department of Health, Education and
Welfare, Public Health Service, Bureau of Disease Prevention
and Environmental Control, Atlanta, Georgia.
10. American Public Health Association, Standard Methods for the
Examination of Water and Wastewater. 12th Ed., New York, 1965.
11. Oklahoma Water Resources Board, Water Quality Standards for
the State of Oklahoma 1968. Oklahoma City, Oklahoma, 1968.
12. Geldreich, E. E., Best, L. C., Keener, B. A., and Van Donsel,
O. J., "The Bacteriological Aspects of Storm Water Pollution."
Prepublication Copy, U. S. Department of Health, Education, and
Welfare, National Center for Urban and Industrial Health,
Cincinnati, Ohio, 1968.
13. Allison, F. E., "Nitrogen and Soil Fertility. " Soil, the 1957
Yearbook of Agriculture, U. S. Government Printing Office,
Washington, D. C., 1957.
14. Federal Water Pollution Control Administration, Preliminary
Studies Arkansas River and Tributaries, Tulsa to Muskogee,
Oklahoma, U. S. Department of Health, Education, and Welfare,
Arkansas-Red River Basins Comprehensive Project, Ada,
Oklahoma, February, 1966.
15. Betson, R. P., and Marius, J. B., "Source Areas of Storm
Runoff." Water Resources Research, Vol. 5, No/3 (June, 1969).
16. Espey, W. H., Morgan, C. W. , and Masch, F. D., A Study of
Some Effects of Urbanization on Storm Runoff from a Small Water-
shed. Technical Report No. HYD 07-6501 CRWR-2, Hydraulic
Engineering Laboratory, The University of Texas, Austin, Texas,
1965.
17. Imbrie, J., Factor and Vector Analysis Programs for Analyzing
Geologic Data, Office of Naval Research, Geography Branch
Technical Report 6, ONR Task No. 389-135, 1963.
160
-------
REFERENCES- - Continued
18. Tennessee Valley Authority, "Design of a Hydrologic Condition
Survey Using Factor Analysis. " Tennessee Valley Authority
Division Water Control Planning Research Paper No. 5, 1965.
19. Dawdy, D. R., and Feth, J. H. , "Applications of Factor Analysis
in Study of Chemistry of Ground Water Quality, Mojave River Valley,
California. " Water Resources Research, Vol. 3, No. 2 (Second
Quarter, 1967).
20. Tintner, G. , Econometrics. John Wiley and Sons, Inc., New
York, 1952.
21. Saunders, R. J., "Forecasting Water Demand An Inter- and
Intra-Community Study. " West Virginia University Business and
Economic Studies, Vol. 11, No. 2 (February, 1969).
22. Powell, MelD., Winter, William C., and Bodwitch, William P. ,
"Community Action Guidebook for Soil Erosion and Sediment
Control. " National Association of Counties Research Foundation,
Washington, D. C. , 1970.
General References
Environmental Science Service Administration, Local Climatological
Data, 1968 Annual Summary for Tulsa, Oklahoma. U. S. Department
of Commerce, 1963.
International Business Machines Corporation, "System/360 Scientific
Subroutine Package (360A-CM-03X) Version III Programmer's Manual
H20-0205-3." White Plains, New York, 1968.
Tulsa Metropolitan Area Planning Commission, Industrial Development
Plan 1990. January, 1966.
Tulsa Metropolitan Area Planning Commission, Tulsa Metropolitan
Area Population Estimates 1969. June, 1969.
Tulsa Metropolitan Area Planning Commission, Water and Sewage Plan
1990. March, 1969.
Wheeler and Associates, Report on Sewage Collection and Treatment
Facilities for Tulsa, Oklahoma. Tulsa, Oklahoma, 1957.
161
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SECTION 13
PUBLICATIONS
Cleveland, Jerry G. , and Ramsey, Ralph H. , "Storm Water Pollution
from Urban Land Activity. " Proceedings, Storm and Combined Sewer
Seminar, Federal Water Quality Administration, Great Lakes Region,
Chicago, Illinois, June 23, 1970.
Cleveland, Jerry G. , Reid, George W. , and Walters, Paul R., "Storm
Water Pollution from Urban Land Activity. " Meeting Preprint 1033,
ASCE Annual and Environmental Meeting, Chicago, Illinois, October 13
17, 1969.
163
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SECTION 14
GLOSSARY AND ABBREVIATIONS
Glossary
Antecedent Precipitation Index (API) - An indicator of the amount of
water (in inches) present in the soil at any given time. The calculation
of the API is based on the assumption that, during time periods of no
precipitation, the soil moisture decreases logarithmically with time.
Baseline Sample - A sample collected during dry-weather flow (i. e. ,
it does not consist of runoff from a specific precipitation event).
Covered Sewer /Total Length - The ratio of the total length of covered
storm sewer (conduits <24 in. diameter omitted) to the total length of
the main channel (L or
Dependent Variables - The dependent variables in this study are the
chemical and bacterial pollution parameters measured in the laboratory.
Environmental Index (El) - An indicator of environmental quality derived
and explained in Section 6.
Form Factor (FF) - An indicator of the drainage characteristics of a
watershed defined in Table 17, Section 5.
Independent Variables - The independent variables in this study are the
precipitation, drainage, land use, and environmental characteristics
which were related to the dependent variables by correlation analysis
and regression analysis.
Pollution Parameters - The chemical and bacterial quantities measured
in the laboratory to indicate pollution levels.
Precipitation - Includes all forms- -such as rain, snow, sleet, etc.
Precipitation Event - A continuous fall of precipitation having a water
equivalent greater than or equal to 0. 10 in.
165
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Abbreviations
A
Ant.
API
BOD
Bus.
C
Cl
COD
Col.
Com.
Commun.
Cond.
Def.
Dist.
DS
El
Exc.
F.
FF
FY
G
Area
Antecedent
Antecedent precipitation index
Biochemical oxygen demand (5-day, 20° C)
Business
Percent impervious cover
Chloride
Chemical oxygen demand
Coliform
Commercial
Community
Specific conductance (micromhos/cm )
Deficient, deficiency
District
Dissolved solids
Environmental Index
Excellent
Fecal
Form factor
Fiscal year
Geometry number
166
-------
H Fall of watershed
HI Housing Index
Ind. Industrial
Indiv. Individual
Inst. Institutional
L Length of main stream
Lc Length of main stream to centroid of test area
Med. Medium
Mem. Memorial
MF Membrane filter
MG Million gallons
mg Milligrams
mgd Million gallons per day
MPN Most probable number
N Organic Kjeldahl nitrogen (does not include ammonia)
n. d. No data
P Phosphorus
Peo. People
pH Negative logarithm of hydrogen ion concentration
PHS Public Health Service
Prec. Precipitation
Pred. Predominantly
167
-------
Quan.
R
Ref.
Res.
°1
SMSA
SS
Std. Dev.
Strep.
Struct.
Sus.
T.
TMAPC
TOC
Trans.
TS
U.S.D.A.
U.S.G.S.
Vac.
VDS
VSS
Quantity
Correlation coefficient
Relief number
Reference
Residential
Average main channel slope
Average land slope
Standard Metropolitan Statistical Area
Suspended solids
Standard deviation
Streptococcus
Structure
Suspended
Total
Tulsa Metropolitan Area Planning Commission
Total organic carbon
Transportational
Total solids
United States Department of Agriculture
United States Geological Survey
Vacant
Volatile dissolved solids
Volatile suspended solids
168
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SECTION 15
APPENDICES
Appendix Title Page
A Urban Storm Water Runoff Test Areas 171
B Sources of Storm Water Pollution 191
C Tulsa Metropolitan Planning Data and Information
System: Land Activity File 197
D Administrative and Legal Control of Water Pollu-
in the State of Oklahoma and the City of Tulsa 203
E State of Oklahoma Instream Water Quality Criteria
for the Arkansas and Verdigris Rivers and Their
Interstate Tributaries 217
F City of Tulsa Storm Drain System Including Test
Area Boundaries 223
G Federal Water Quality Administration Storet II
Sampling Station Code Numbers 239
H Format of Data Cards Used for Computer Analysis 241
I Street Cleaning Operations in Tulsa 247
J City of Tulsa's Municipal Sewage Treatment Plant
Effluent Data 257
K Regression Equations 267
L Monthly Precipitation Data for Six Rain Gages
in the Urban Tulsa Area 289
M Analytical Results 295
N General Plan for the City of Tulsa to Control
Storm Water Pollution 313
169
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APPENDIX A
URBAN STORM WATER RUNOFF TEST AREAS
The following pages include pictorial descriptions of the fifteen test
areas selected for sampling and analysis. The residential test areas
(3, 5, 7, 8, 9, 13, and 15) are typical of broad categories of various
types of single-family living. Although all are zoned U-1C Restricted
Residence District, there are many differences among the test areas
as to streets, tree and ground cover, age of addition, and general
environmental conditions. Whereas Test Area 2 is typical of
neighborhood shopping districts in large metropolitan areas, Test
Area 10 is an example of a central business district. The industrial
areas (1, 4, 6) are typical of developing light, medium, and heavy
industrial areas. Test Area No. 11 consists mainly of very low-
income residential areas, but has strip commercial activity on the
arterial streets. Test Area No. 14 is a golf course typical of all
urban areas.
Table A-l presents a summary of the zoning classifications.
171
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TEST AREA NO. 1
SOUTHERN MEMORIAL INDUSTRIAL DISTRICT
FIGURE A-l. Memorial Drive south of 41st Street looking
east
TRIBUTARY TO: Mingo Creek
ZONING: U-4A Light Industrial District
This subdrainage basin is located in the upper Mingo
Basin. It is a relatively new light industrial district
with large amounts of undeveloped and developing
land. During the testing period large amounts of land
were disturbed due to the construction of a large apart-
ment house complex. Arterial streets in the area are
not curbed and guttered. Storm water runoff is mainly
into unimproved drainage channels.
FINDINGS:
Average Concentration Average Yearly Load
BOD:
COD:
Total Solids:
13 mg/1
110 mg/1
2242 mg/1
30 Ibs./acre
25 1 Ibs./acre
5107 Ibs./acre
172
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TEST AREA NO. 2
SOUTHROADS-SOUTHLAND SHOPPING CENTER AREA
FIGURE A-2. Looking northeast from, southeast corner of 41st
Street and Yale Avenue
TRIBUTARY TO: Joe Creek
ZONING: Predominantly U-3E General Commercial District
This drainage shed is a relatively new typical suburban
commercial and retail shopping center. It is characterized
by large parking lots and heavily traveled arterial streets.
The estimated average daily traffic on 41st Street is 25,000
vehicles per day. The parking areas and the arterial streets
are cleaned daily. All of the storm water runoff in this area
is routed to covered conduits via streets and inlet structures.
FINDINGS:
Average Concentration Average Yearly Load
BOD: 8 mg/1 27 Ibs./acre
COD: 45 mg/1 150 Ibs./acre
Total Solids: 275 mg/1 918 Ibs./acre
173
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TEST AREA NO. 3
SUNGATE AND WOODLAND VIEW AREA
FIGURE A-3. 6700 block on East 55th Street looking east--
Sungate Addition
TIRBUTARY TO: Joe Creek
ZONING: U-1C Restricted Residence District
This test area is a typical new single-family residential
subdivision. No houses in this area are over 5 years old.
All streets are curbed and guttered. The drainage is into
an open channel that runs through the center of the addition.
Two schools and a community swimming pool are also
located within this drainage shed.
FINDINGS:
Average Concentration Average Yearly Load
BOD:
COD:
Total Solids:
8 mg/1
65 mg/1
680 mg/1
14 Ibs. /acre
113 Ibs./acre
1183 Ibs./acre
174
-------
TEST AREA NO. 4
SHERIDAN INDUSTRIAL DISTRICT
FIGURE A-4. Atop Tulsa City-County Health Department
looking south over Tulsa County Fairgrounds
TRIBUTARY TO: Mingo Creek
ZONING: Predominantly U-4B Heavy Industrial District with
small amount of U-1C Restricted Residence District
This test area is characterized by heavily traveled arterial
streets, portions of the Tulsa County Fairgrounds, a large
Sears Shopping Center, a concrete building material plant,
several trucking firms, and large amounts of open storage.
The drainage is into an open channel which runs through the
properties of several industrial firms.
FINDINGS:
Average Concentration Average Yearly Load
BOD:
COD:
Total Solids:
14 mg/1
103 mg/1
616 mg/1
44 Ibs./acre
3Z4 Ibs. /acre
1936 Ibs./acre
175
-------
TEST AREA NO. 5
WOODWARD PARK AREA
FIGURE A-5. Riverside Drive looking east up 26th Street
TRIBUTARY TO: Arkansas River
ZONING: Predominantly U-1C Restricted Residence District
This test area is located adjacent to the Arkansas River in
a fairly old section of Tulsa. It has steep slopes and large
amounts of tree cover. All of the streets are curbed and
guttered. The drainage is into a large closed conduit.
Located within the test area is a park.
FINDINGS:
Average Concentration Average Yearly Load
BOD:
COD:
Total Solids:
18 mg/1
138 mg/1
271 mg/1
33 Ibs./acre
252 Ibs./acre
494 Ibs./acre
176
-------
TEST AREA NO. 6
LATIMER INDUSTRIAL DISTRICT
FIGURE A-6. St. Louis Avenue looking north
TRIBUTARY TO: Flat Rock Creek
ZONING: U-4B Heavy Industrial and U-1C Restricted
Residence District
This test area is a mixture of industrial firms and fair to
poor residential housing. The watershed is characterized by
several auto wrecking firms and trucking companies. The
drainage is into a closed conduit.
FINDINGS:
BOD:
COD:
Total Solids:
Average Concentration Average Yearly Load
12 mg/1
90 mg/1
346 mg/1
21 Ibs. /acre
155 Ibs. /acre
594 Ibs. /acre
177
-------
TEST AREA NO. 7
METHODIST MANOR
FIGURE A-7. 27th Street and Quebec Avenue
TRIBUTARY TO: Joe Creek
ZONING: U-1C Restricted Residence District
This test area is a post-World War II housing addition.
Almost all homes are frame or frame and brick. The
yards in the area are -well-kept. Drainage is from street
to inlet structures to covered drainage channel.
FINDINGS:
Average Concentration Average Yearly Load
BOD:
COD:
Total Solids:
8 mg/1
48 mg/1
413 mg/1
15 Ibs./acre
91 Ibs./acre
785 Ibs./acre
178
-------
TEST AREA NO. 8
STRIP-PIT COLLECTION BASIN
FIGURE A-8. Virgin and Jamestown
TRIBUTARY TO: Coal Creek
ZONING: U-1C Restricted Residence District
This test area is a lower middle class postwar addition of
mostly two-bedroom frame and brick houses with medium-
sized tree cover. Many streets are not curbed and guttered.
FINDINGS:
Average Concentration Average Yearly Load
BOD:
COD:
Total Solids:
15 mg/1
115 mg/1
382 mg/1
33 Ibs./acre
252 Ibs./acre
836 Ibs./acre
179
-------
TEST AREA NO. 9
SUNNY SLOPE ADDITION
'- '
A-
FIGURE A-9. Typical backyard in test watershed
TRIBUTARY TO: Flat Rock Creek
ZONING: U-1C Restricted Residence District
This test area is mostly composed of fairly old houses of
various sizes, many nearing delapidation. All of the area
is ill-kept and can be characterized by many general sanitary
deficiencies, such as uncovered garbage cans, rubble, and
old autos.
FINDINGS:
Average Concentration Average Yearly Load
BOD:
COD:
Total Solids:
10 mg/1
117 mg/1
417 mg/1
20 Ibs./acre
232 Ibs./acre
827 Ibs./acre
180
-------
TEST AREA NO. 10
SOUTH CENTRAL BUSINESS DISTRICT
FIGURE A-10.
View of parking lots and office buildings in the
upper portions of the watershed
TRIBUTARY TO: Arkansas River
ZONING: Predominantly U-3DH Restricted Commercial
District, some U-ZA Multiple Dwelling District,
some U-2B Restricted Apartment District
The upper portion of the watershed is commercial-office in
nature and includes multistory buildings. The middle areas
of the watershed are largely open areas with considerable
tree cover; these areas have been cleared by the Tulsa Urban
Renewal Authority for eventual redevelopment. Some urban
renewal work is still underway in the area.
FINDINGS:
Average Concentration Average Yearly Load
BOD:
COD:
Total Solids:
11 mg/1
107 mg/1
431 mg/1
48 Ibs./acre
470 Ibs./acre
1895Ibs./acre
181
-------
TEST AREA NO. 11
GREENWOOD DRAINAGE SHED
FIGURE A-11. Intersection of Kingston and South 18th Street
TRIBUTARY TO: Dirty Butter Creek
ZONING: U-1C Restricted Residence District
U-2A Multiple Dwelling District
U-3E General Commercial District
This test area, containing mostly small frame houses, is in
the heart of Tulsa's Model City Area. The streets in the area
are deteriorating, and many are not curbed and guttered.
There is strip commercial activity on the arterial streets in
the area.
FINDINGS:
Average Concentration Average Yearly Load
BOD:
COD:
Total Solids:
14 mg/1
116 mg/1
575 mg/1
35 Ibs./acre
292 Ibs./acre
1447 Ibs./acre
182
-------
TEST AREA NO. 12
AIRPORT EAST
FIGURE A-12. Gilcrease Freeway looking northeast
TRIBUTARY TO: Mingo Creek
ZONING: U-4A Light Industrial District
This test area includes a portion of the Tulsa International
Airport runways and supporting buildings of North American
Rockwell Corporation. The drainage shed has a great amount
of open grassy area. The runoff is into an unimproved open
channel.
FINDINGS:
Average Concentration Average Yearly Load
BOD:
COD:
Total Solids:
8 mg/1
45 mg/1
199 mg/1
25 Ibs./acre
141 Ibs./acre
625 Ibs./acre
183
-------
TEST AREA NO. 13
BOLEWOOD ACRES
FIGURE A-13. Intersection of East 43rd Street and Oak Road
TRIBUTARY TO: Joe Creek
ZONING: U-1A Restricted Residence District
This test area is mostly a non-sewered upper-class
residential area. It is characterized by large lot size,
expensive homes, and a large amount of tree cover.
Almost all homes have private swimming pools and
individual septic systems. Most streets are not curbed
and guttered. The drainage is via roadway drainage
ditches.
FINDINGS:
Average Concentration Average Yearly Load
BOD:
COD:
Total Solids:
15 mg/1
88 mg/1
469 mg/1
25 Ibs./acre
146 Ibs./acre
776 Ibs./acre
184
-------
TEST AREA NO. 14
SOUTHERN HILLS COUNTRY CLUB
FIGURE A-14. View of water hazard on the golf course
TRIBUTARY TO: Joe Creek
ZONING: Recreational
This drainage shed includes a golf course. It is
characterized by tree cover, well-kept grass cover, and
two small recreational ponds. The ponds capture most of
the runoff water. The only time storm water runoff escapes
from this watershed is during heavy rains--mostly in the
spring of the year. The samples collected from this area
were actually overflow from the ponds and not storm water
runoff samples.
FINDINGS:
Average Concentration Average Yearly Load
BOD:
COD:
Total Solids:
11 mg/1
53 mg/1
592 mg/1
12 Ibs. /acre
59 Ibs. /acre
659 Ibs. /acre
185
-------
TEST AREA NO. 15
ALT ADE MA PLACE
FIGURE A-15. 45th Street and Riverside Drive looking east
TRIBUTARY TO: Arkansas River
ZONING: U-1C Restricted Residence District
This residential area is a post-World War II addition of
small 2-3 bedroom frame and brick houses. The area is
covered with a great amount of medium sized trees. All
streets are curbed and guttered.
FINDINGS:
Average Concentration Average Yearly Load
BOD:
COD:
Total Solids:
12 mg/1
42 mg/1
273 mg/1
25 Ibs./acre
88 Ibs./acre
572 Ibs./acre
186
-------
TABLE A-l
•
SUMMARY OF ZONING CLASSIFICATIONS3
District
U-RE
Restricted
Residence
District
U-1A
Restricted
Residence
District
U-1B
Restricted
Residence
District
U-1C
Restricted
Residence
District
U-2A
Multiple
Dwelling
District
Permitted_ Use s jind Requirements
Single family residences; lot width. 1ZO ft. ; lot
area 25, 000 sq. ft. ; front yards 50 ft. ; side
yards ZO ft. ; rear yards 25% of lot depth. (Board
of Adjustment may approve schools, churches,
and police and fire stations, subject to conditions.)
Single family residences; lot width 100 ft. ; lot
area 13, 500 sq. ft. ; front yards 35 ft. ; side
yards 15 ft. ; rear yards 20% of lot depth. (Schools,
churches, etc., in U-RE.)
Single family residences; lot width 75 ft. ; lot
area 9, 000 sq. ft. ; front yards 30 ft. ; side yards
a total of 15 ft. ; neither less than 5 ft. ; rear yards
20% of lot depth. (Schools, churches, etc. , by
Board of Adjustment.)
Single family residences; lot width 60 ft. ; lot area
7, 000 sq. ft. ; front yards 25 ft. ; side yards 5 ft. ;
rear yards 20% of lot depth. (Duplexes on not less
than 10,000 sq. ft. lot with Zoning Board of
Adjustment approval.)
Mixture of single family, duplex, multifamily,
townhouse, and institutional dwelling units. Many
detailed requirements including a multifamily lot
area of 2, 400 sq. ft. per dwelling unit.
The contents of this summary are limited and are intended to
serve only as a guide. The full text of the Zoning Ordinance
is in Title 42, Revised Ordinance, City of Tulsa, 1964.
187
-------
TABLE A-I — Continued
District
U-2B
Restricted
Apartment
District
U-2C
General
Apartment
District
U-3A
Parking
District
U-3B
Professional
Office
District
U-3BH
Professional
Office
District
Permitted Uses and Requirements
Same as U-2A except for several detailed
requirements of multifamily lot area, lot width,
and lot area per dwelling unit.
Same as U-2A and U-2B except for several detailed
requirements. Multifamily lot area per dwelling
unit is 1, 000 sq. ft.
Parking of motor vehicles; single family residences.
(Sign and structure limitations. )
Funeral homes, offices of lawyers, architects,
dentists, doctors, engineers, etc. Buildings are
limited to one story or 30 ft. in height and 20%
coverage of the lot. If adjacent to a U-1A through
U-2C district, 10 ft. side yard is required. Signs
limited to 16 sq. ft.
All U-3A and U-3B uses inclusive, plus all
administrative offices of private, public, semi-
public, eleemosynary, civic, religious, etc. ,
organizations, but excluding uses where merchan-
dise is shown or for sale on the premises. Total
floor area must not exceed 50% of the lot area.
Whenever a U-3BH district adjoins a U-1A through
U-2A district, a setback to height ratio of 2:1 shall
be in effect. When it adjoins other use districts or
street rights-of-way, a ratio of 1:1 shall be in
effect.
U-3C
Personal
Service
District
Automobile service stations, ice docks, automatic
vending machines for ice, milk, ice cream, or
dairy products. Buildings are limited to one story
in height and 30% coverage of the lot. If adjacent
to residential zoning, a 10 ft. side yard is required.
Also: Motels on tracts of 2-1/2 acres or more and
at least 200 ft. frontage; front yard of 50 ft. ; side
and rear yards of 10 ft. when adjacent to residential
188
-------
TABLE A-I — Continued
District
U-3D
Restricted
Commercial
District
U-3DH
Restricted
Commercial
District
U-3E
General
Commercial
District
U-3F
Heavy
Commercial
District
U-4A
Light
Industrial
District
Permitted Uses and Requirements
zoning. Dining rooms and coffee shops as accessory
uses in conjunction with a motel.
All retail commercial uses (except those listed
under U-3E and U-3F below). Note: Taverns,
which were formerly allowed only in U-3E, are
now included in this district, subject to the
requirements of Ordinance No. 9952. Buildings
limited to one story or 30 ft. in height and 50%
coverage of the lot. Buildings must be set back
10 ft. from a residential district.
U-3A through U-3D uses plus: All retail commer-
cial uses except those listed in U-3E and U-3F below.
Total floor or floors area must not equal more than
50% of the total lot area. When such a district
adjoins a U-RE through U-2C district, the setback
from such districts shall be 2 ft. for every 1 ft. in
height of such building or structure. When adjoin-
ing a public street, the setback from such right-of-
way line will be a distance of 1 ft. for each 1 ft. of
building or structure height.
All retail commercial uses and U-1A through U-2C
residential uses, plus: Bowling alleys, pool halls,
dance halls, taverns. Also: all general commercial
uses (except those listed uncjer U-3F below). No
height or lot coverage restrictions.
All general commercial uses plus: bakeries, lumber
yards, ice cream and dairy products manufacturing,
scientific research laboratories, race tracks, miniature
auto tracks, outdoor theatres, drive-in eating places.
No height or lot coverage restrictions.
Light industrial or manufacturing uses. Residential
uses prohibited. Buildings must be set back 150 ft.
from residential districts unless a public street lies
between such districts, in which case buildings shall
189
-------
TABLE A-1 - - Continued
District Permitted Uses and Requirements
be set back 50 ft. Detailed specific provisions as to
building height and off-street parking.
U-4B Heavy industrial uses. Residential use prohibited.
Heavy Building setback lines equivalent to U-4A above; no
Industrial height restriction; specific detailed provisions for
District . off-street parking.
U-5 Any lawful use, except that residential uses are
Unrestricted prohibited. Building setback requirements
District equivalent to U-4A above; no height restriction;
specific detailed provisions for off-street parking.
190
-------
APPENDIX B
SOURCES OF STORM WATER POLLUTION
This appendix describes with pictures several sources of storm water
pollution. The pictures were taken in various areas of the City
of Tulsa, Oklahoma. Each one of these sources can be corrected by
better public works practices and by enforcing existing or new local
ordinances pertaining to general sanitary conditions.
191
-------
FIGURE B-l.
Indiscriminate roadside dumping of trash
and rubble
FIGURE B-2.
Scattering of waste construction material
and poor maintenance of drainage channel
192
-------
FIGURE B-3.
Unimproved and poorly maintained open
drainage channel
FIGURE B-4.
Indiscriminate dumping into open
drainage channel
193
-------
FIGURE B-5.
Indiscriminate dumping into open drain-
age channel (grass trimmings)
FIGURE B-6.
Poorly maintained drainage structure-
buildup of decaying organic matter re-
sulting in flow stoppage
194
-------
FIGURE B-7.
Vast area of disturbed land with ground
cover removed and open storage of
material during construction activities
FIGURE B- 8. Dirty streets--subdivision development
195
-------
FIGURE B-9. Land filling with construction material
waste adjacent to open drainage channel
FIGURE B-10.
Residential parcel deficiencies--uncovered
garbage cans and piles of rubble
196
-------
APPENDIX C
TULSA METROPOLITAN PLANNING DATA AND
INFORMATION SYSTEM:
LAND ACTIVITY FILE
The Tulsa Metropolitan Area Planning Commission's (TMAPC)
"metropolitan data bank concept" originated from the need for improved
methods of recording urban data to be used by governmental agencies.
With the capabilities of the new computers, it is possible to economi-
cally store, maintain, manipulate, and retrieve considerable amounts
of data. The folio-wing is a short description of TMAPC's data bank
and operating procedure.
TMAPC has developed three distinct data processing systems in the
last ten years. The first, called "A Program for Automatic Tabulation
of Basic Data for the Tulsa Metropolitan Area, " was initiated in 1958.
The second system, established in 1965, was the "Tulsa Metropolitan
Data Center System, " a product of the Metropolitan Data Center Pro-
ject. The third system, initiated in 1966 and presently in use, is the
"Metropolitan Planning Data and Information System: Land Activity
File."
The operation of the first two data processing systems will not be
discussed here; only the current "Land Activity File" will be considered.
Land Activity File Qpe ration
The TMAPC's Land Activity File Operation is based on electronic data
processing equipment which employs magnetic tape for the storage and
processing of current data needed in urban planning activities. Follow-
ing is a summary of the operation of the Land Activity File in terms of
data file storage, file development, and file usage.
Data File Storage - The Land Activity File presently consists of three
large reels of magnetic tape containing land use data. These data
represent approximately 150,000 parcel records covering an area of
about 577 square miles.
Equipment and Records - At present, the TMAPC utilizes the data
processing equipment of the City of Tulsa. Tulsa has an IBM 360
Computer which requires magnetic tapes for data file storage.
197
-------
Magnetic tape drives do not have the direct-file access capabilities of
disk storage drives, but are extremely flexible in that they have very
few data storage requirements or file layout restrictions.
A printed documentary record of the data file contents, called the
Master File Card Reference System, is maintained. The card refer-
ence system consists of approximately 150, 000 preprinted cards
grouped by township section and range, census tract, planning block,
and planning parcel. These reference cards allow for easy handling as
well as quick access to the file contents.
Having the reference file on punch cards instead of on a tabulated
listing provides up-to-date reference without the need to reprint the
entire data set every year. The entire file is reprinted only when a
substantial change in the format occurs, as when new items are collected,
old items deleted, or data files combined.
Data File Design - Data items are grouped in a logical organization
called the "Parcel Record Format, " shown on the following two pages,
to accomodate processing of the data by the computer. This grouping
makes possible the systematic collection and recording of physical,
social, and economic data about each parcel. The parcel number code
is used as the common file reference code which serves to properly
identify and locate land activity. The data file is organized in ascend-
ing sequential parcel number order, and categorizes planning data of
every parcel into three basic information levels: (1) parcel information,
(2) building and/or open space information, and (3) establishment in-
formation.
Parcel information includes the location, characteristics, use data, and
zoning data associated with a specific parcel. Examples of this infor-
mation level are the building condition and gross floor area. Each
parcel record includes a numeric file identification code for individual
and multiple buildings and/or open space uses (open parking lots or
tennis courts). Establishment characteristics, such as floor space
utilized and the establishment activity code, are recorded at the
establishment information level. Each parcel record provides for
multiple establishments within a building or open space classification.
A numeric file identification code is assigned to each establishment.
Establishment characteristics are recorded separately for every
establishment in the file. Multifamily housing units are summarized
for each structure. All parcel records entered into the data file
require a parcel identification number, building location number, and
establishment location number.
198
-------
TMAPC LAND ACTIVITY FILE
PARCEL RECORD FORMAT
I. Parcel Information
A. Parcel location information
Parcel identification number
Grid coordinates
Parcel address
B. Political jurisdictions
County
Incorporated unit code
C. Planning/statistical areas
Community statistical area code
Planning statistical area number
Industrial planning district code
Commercial area code
Community renewal project number
Transportation sub-zone number
Postal zone number
Street control section number
Land use map number
II. Parcel Characteristics
A. Size
Parcel area
Average parcel width
Average parcel depth
Parcel frontage
B. Tax and economic factors
Assessed land value
Assessed improvements value
Assessed total value
Parcel sale data
Parcel sale price
Homestead exemption
C. Other Characteristics
Area building practice
Area environmental status ownership
199
-------
TMAPC LAND ACTIVITY FILE
PARCEL RECORD FORMAT--Continued
III. Parcel Use Data
Free off-street parking spaces
Comprehensive plan use code
Predominant use group code
IV. Zoning Data
Zoning classification code
V. Building Information
A. General building data
Building location number
Building condition
Year building built
Type of building construction
B. Building Floor Data
Number of floors
Gross building floor area
Ground building floor area
VI. Establishment Information
Establishment location code
Floor level
Establishment name code
Establishment floor space utilized
Paid off-street parking spaces
Establishment attributable parcel area
Number of employees
Number of housing units
Data File Format - The "Land Activity File Form," Figure C-l, con-
tains 47 separate classifications: 31 parcel items, 7 building items,
and 9 establishment items. These data are contained within three
80-column cards numbered 1, 2, and 3. Cards 1 and 2 contain only
parcel data items. The number 3 card includes both building information
and establishment information. The card control number appears in
column 80 of each card on the form. Card control number 3 appears
five times on the activity form. Therefore, a single form accommo-
dates a total of five separate buildings and establishments or any
200
-------
PARCEL IDENTIFICATION
NUMBER
8
1
CENSUS
TRACT
2315
PLANN
BLOCK
6 7 8
PLANN
PARCEL
9
10
11
LAND ACTIVITY FILE FORM
SIGNATURE
tmapc, DEC.. 1966
FORM NO; LA 1
TRANS
DATE
o
12
12
YEAR
13 14
GRID
LATITUDE
15 16 17 18 19
ASSESSED
LAND
VALUE
13 14 15 16 17 18
BLDG
LOC
NO
12
13
BLDG
IOC
NO
12
13
BLDG
LOC
NO
!2
BL
LC
N
1
12
13
DG
C
0
13
BLDG
LOC
NO
12
13
8
CD
14
§
8
CD
14
z
o
00
14
O
CJ
9
14
z
q
8
14
YEAR
BLDG
BUILT
15 16 17
YEAR
BLDG
BUILT
15 16 17
YEAR
BLDG
BUILT
15 16 17
TEAR
BIDG
BUILT
15 16 17
YEAR
BLDG
BUILT
15 16 17
19
COORDINATES
20
21
LONGITUDE
22 23 24 25 26
ASSESSED
IMPROVEMENT
VALUE
20 21
TYPE
BLDG
CONSTR
18 19
20
TYPE
BLOG
CONSTR
18 19
20
TYPE
BLDG
CONSTR
18 19
20
TYPE
BLDG
CONSTR
18 19
20
TYPE
BLDG
CONSTR
18 19
20
o
z
21
22 23 24 25
1
22
O O
u.
21
o
z
21
d
z
21
i
21
22
1
22
o
22
'&
8
22
PARCEL ADDRESS
BUILDING
NUMBER
27 28 29 30 31
9E
a
32
ASSESSED
TOTAL
VA1UE
26 27 28 29 30 31 32
GROSS
BUILDING
FLOOR AREA
23 24 25 26 27 28 29 30
GROSS
BUILDING
FLOOR AREA
23 24 25 26 27 28 29 30
GROSS
BUILD NG
FLOOR AREA
23 24 25 26 27 28 29 30
GROSS
BUILDING
FLOOR AREA
23 24 25 26 27 28 29 30
GROSS
BUILDING
FLOOR AREA
23 24 25 26 27 28 29 30
STREET
NAME
33
34
35 36 37
AREA
BLDG.
PRACT.
33
34
35
%
38
AREA
ENVIR
STATUS
36 37 38
GROUND
BUILDING
FLOOR AREA
31 32 33
34
35 36 37 38
GROUND
BUILDING
FLOOR AREA
31 32 33
34S35 36 37 38
GROUND
BUILDING
FLOOR AREA
31 32 33
34
35 36 37 38
GROUND
BUILDING
FLOOR AREA
31 32 33
34
35 36 37 38
GROUND
BUILDING
FLOOR AREA
31 32 33
34
35 36 37 38
P
c
39
.ANN
TAT.
REA
NO.
40 41
COM.
STAT.
AREA
CODE
42 43
IND.
PLAN.
DIST.
CODE
44 45
PARCEL
SALE DATE
MONTH
39
40
ESTB
LOC
NO.
39
40
ESTB.
LOC.
NO
39
40
ESTB
LOC
NO
39
40
ESTB.
LOC
NO
39
40
ESTB
LOC
NO.
39
40
DAY
41 42
YEAR
43 44
COMM'L
AREA
CODE
46
45 46
47 48
COM.
REN
PROJ.
NO.
49 50
PARCEL
SALE
PRICE
47 48 49 50
ESTABLISHMENT
ACTIVITY CODE
ACTIVITY
CODE
41 42 43 44
USEGRP.
CODE
45 46
47
ESTABLISHMENT
ACTIVITY CODE
ACTIVITY
CODE
41 42 43 44
USEGRP.
CODE
45 46
47
ESTABLISHMENT
ACTIVITY CODE
ACTIVITY
CODE
41 42 43 44
USEGRP.
CODE
45 46
47
ESTABLISHMENT
ACTVITY CODE
ACTIVITY
CODE
41 42 43 44
USEGRP.
CODE
45 46
47
ESTABLISHMENT
ACTIVITY CODE
ACTIVITY
CODE
41 42 43 44
USEGRP.
CODE
45 46
47
i
48
a
48
a
48
is
48
i
48
TRANSP
SUBZONE
NO
51
52 53 54
HOME.
EXEM.
51
52
POSTAL
ZONE
NO.
55 56
FREE
OFF ST.
PARKING
SPACES
53 54 55
ESTABLISHMENT
NAME
CODE
49 50 51
52 53 54
ESTABLISHMENT
NAME
CODE
49 50 51
52 53 54
ESTABLISHMENT
NAME
CODE
49 50 51
52 53 54
ESTABLISHMENT
NAME
CODE
49 50 51
52 53 54
ESTABLISHMENT
NAME
CODE
49 50 51
52 53 54
57
58
PRED
USE
GROUP
CODE
59
60 61
STREET
CONTROL
SECTION
NO.
62
63 64 65
PARCEL
AREA
56
57
58 59
60 61 62
ESTABLISHMENT
FLOOR
SPACE UTILIZED
55 56
57
58 59
60
ESTABLISHMENT
FLOOR
SPACE UTILIZED
55 56
57
58 59
60
ESTABLISHMENT
FLOOR
SPACE UTILIZED
55 56
57
58 59
60
ESTABLISHMENT
FLOOR
SPACE UTLIZED
55 56
57
.58 59
60
ESTABLISHMENT
FLOOR
SPACE UTILIZED
55 56
57
58 59
60
63
PAID
OFF STREET
PARKING
SPACES
61 62
63
PAID
OFF STREET
PARKING
SPACES
61 62
63
PAID
OFF STREET
PARKING
SPACES
61 62
63
PAID
OFF-STREET
PARKING
SPACES
61 62
63
PAID
OFF STREET
PARKING
SPACES
61 62
63
66 67 68
AVERAGE
PARCEL
WIDTH
~f
64 65
66 67
68
69
MAP NO.
z
*
70
71
AVERAGE
PARCEL
DEPTH
69 70 71
ESTABLISHMENT
ATTRIBUTABLE
PARCEL AREA
64 65
66 67 68
69 70 71
ESTABLISHMENT
ATTRIBUTABLE
PARCEL AREA
64 65
66 67 68
69 70 71
ESTABLISHMENT
ATTRBUTABLE
PARCEL AREA
64 65
66 67 68
69 70 71
ESTABLISHMENT
ATTRIBUTABLE
PARCEL AREA
64 65
66 67 68
69 70 71
ESTABLISHMENT
ATTRIBUTABLE
PARCEL AREA
64 65
4
66 67 68
69 70 71
SEC
72 73
C
ONE
LASS.
CODE
74 75 76
PARCEL
FRONTAGE
72 73 74 75
NO
EMPS
72 73 74 75
NO
EMPS
72 73 74 75
NO
EMPS
72 73 74 75
NO
EMPS
72 73 74 75
NO.
EMPS
72 73 74 75
OWNSHP
76j
COMP.
PLAN
USE
CODE
77
78
INC.
UNIT
CODE
77
78
NO
HOUSING
UNITS
76 77
78
NO
HOUSING
UNITS
76 77
78
NO
HOUS NG
UNITS
76 77
78
NO.
HOUSING
UNITS
76 77
78
NO
HOUS NG
UNITS
76 77
78
K
79
c/iu,
Is
79
79
LOuJ
79
ps
"^
79
tfluj
I
79
Is
79
i
o
OL
3
1
80
o
z
0
(T
CJ
2
80
i
o
cr
3
80
i
Q
tt
3
80
o
Q
a
3
80
o
z
a
cc
5
3
80
b
z
o
ce
o
3
80
t~
Z
> -n
Qo
n
-n ^
m
5
-------
combination of buildings and establishments totaling five.
The first 11 columns of every card are for the parcel identification
number, which serves as the common reference number for related
information concerning each parcel. Column 79 of each card is used
for the file transaction code data field.
Every record in the file contains 160 card columns of information
characterizing each parcel and its location, political jurisdiction,
planning/statistical areas, size, tax and economic factors, parcel use
data, zoning data, and other characteristics. Thirty-eight columns
describe each building and its location, general building data, and
building floor data. Forty columns describe each establishment, its
location, and establishment characteristics.
202
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APPENDIX D
ADMINISTRATIVE AND LEGAL, CONTROL
OF
WATER POLLUTION
IN THE
STATE OF OKLAHOMA
AND
THE CITY OF TULSA
The following pages include a brief description of the structure of
pollution control in the State of Oklahoma and pertinent provisions of
Tulsa's ordinances which were assembled and analyzed in the course
of this study. It should be noted that almost all of the City of Tulsa's
ordinances indirectly regulate or control storm water pollution. The
enforcing power is also spread over several different city departments.
State of Oklahoma
The Oklahoma Legislature enacted House Bill 905 in 1968, creating the
Department of Pollution Control. This department is administered by
a Pollution Control Coordinating Board composed of the heads of five
state agencies, each of which has statutory authority. The five
agencies are the State Water Resources Board, State Corporation
Commission, State Department of Health, State Department of Agri-
culture, and State Department of Wildlife Conservation.
The Department of Pollution Control is responsible for establishing a
coordinated water pollution control program, utilizing the existing
resources and facilities in the five state agencies having water pollution
control responsibilities and authority under existing statutes.
The powers and duties of the board are:
1. To coordinate and eliminate duplication of effort by the State
agencies having statutory authority in water pollution control.
2. To request member agencies to investigate suspected or
potential pollution and to file a report on such investigations
with the Pollution Control Coordinating Board.
203
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3. To conduct studies, investigation, research, and demonstra-
tions for the prevention and control of pollution.
4. To assume jurisdiction in a pollution problem if the agency
having statutory jurisdiction fails to meet its responsibility
in regard to that problem.
5. To establish, amend, or repeal standards for quality of the
waters of the state.
6. To hold hearings, issue notices, and issue subpoenas for the
attendance of witnesses and for the production of documents
in the enforcement and administration of the Water Pollution
Control Act.
Each agency has its own area of responsibility in Water Pollution
Control. Below is a brief resume of these responsibilities.
State Department of Agriculture -Responsible for enforcing
pesticide applicator laws to prevent water pollution by pesticides.
Commercial applicators are required to be licensed, bonded, and
responsible for any damages caused by their operations. Owners
of livestock feed yards are licensed and are required to provide
such facilities and to take such action as may be necessary to
avoid any water pollution which might result from their operations.
State Corporation Commission -Makes and enforces rules
governing the handling, storage, and disposition of mineral brines,
waste, oil, and other deleterious substances related to the drilling,
development, production, refining, and processing of oil and gas
products.
State Department of Health -Responsible for the prevention,
control, and abatement of water pollution associated with discharge
and nuisance problems. The State Department of Health is also
responsible for reservoir sanitation and the sanitation and health-
fulness of public water supplies and public bathing places.
State Water Resources Board -Responsible for pollution control
as it applies to industry with the exception of waste water discharges
from, the oil and gas industry. All other industries are subject to
the rules and regulations of the Water Resources Board regarding
pollution control.
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State Department of Wildlife Conservation -Charged with the
conservation of all wildlife resources in the state. Any time that
lime, sawdust, salt water, crude oil (oil pollution must first be
reported to the Corporation Commission), explosives, drugs,
or other deleterious substances pollute water to the extent that
wildlife suffers, the State Department of Wildlife Conservation
acts to correct the problem.
City of Tulsa
The City of Tulsa has many local ordinances that indirectly regulate
or control storm water pollution. These ordinances are administered
by several different city departments, each department having its own
area of responsibility. Below are all the ordinances that were found
in the Charter and Revised Ordinances of the City of Tulsa, Oklahoma,
which, although primarily designed for other reasons, indirectly
reduce or control storm, water pollution.
Charter of the City of Tulsa and Amendments Thereto
Article II. Powers of the City
Section 5. HEALTH
(5) The City of Tulsa is hereby given full power and authority
to take such steps to improve and preserve the purity of the water
in Arkansas River, above the city of Tulsa, as it may think nec-
essary; provided, that the power in this section shall not be
construed to give said corporation any jurisdiction or control over
said river beyond the corporate limits of said city, except for the
purpose of protecting or improving the water shed, i. e. , and
water supply of both Arkansas River and the smaller streams or
tributaries; provided further, that the said corporation shall have
the right to condemn land, buildings and outhouses or closets
when it may deem the same necessary for the protection and
preservation of the purity of the water in said river, and shall
have power to control the same.
The City of Tulsa shall also have power to require any persons or
corporations owning or operating manufacturing enterprises within
• or without the city which shall discharge refuse matter into
Arkansas River or its tributaries, to make other provisions for
such refuse matter or so purify the same as that the public health
will be fully protected.
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Title 11 - Engineering Department
Chapter 9. Construction on or over Easements
Section 121. CONSTRUCTION PERMITTED OVER STORM
SEWER EASEMENTS
(121) The construction of buildings, and/or structures over,
upon, and in easements of land for storm sewer purposes, inuring
to the benefit of the City of Tulsa and inuring to the benefit of the
"public" shall hereafter be permitted within the City of Tulsa
over, upon and in said easement lands. (Ord. No. 10913)
Section 122. PERMIT REQUIRED
Any person desiring to construct a building and/or structure
over, upon, or in a storm sewer easement, or a portion thereof,
shall obtain, prior thereto, a permit from the office of the City
Engineer of the City of Tulsa, Oklahoma, therefore, the issuance
of which shall be the condition precedent to such construction.
(Ord. No. 10913)
Section 123. AGREEMENT REQUIRED
Any person desiring to construct a building or structure upon
a storm sewer easement inuring to the benefit of the City of Tulsa
and located within the City limits of the City of Tulsa, Oklahoma,
shall execute an agreement with the City of Tulsa subject to
approval thereof by the City Engineer, setting forth such terms,
conditions and provisions as may be prescribed by the City
Engineer to whom authority is hereby delegated to execute said
agreement in behalf of the City of Tulsa. Such agreement shall
be in writing and shall restrict the use of said storm sewer ease-
ment substantially in accordance with the restrictions and
conditions as herein below set forth, and said agreement shall,
upon execution, be recorded in the office of the County Clerk of
the County in which that property is located, recording cost to be
paid by the property owner. (Ord. No. 109.13)
Title 17 - Health Regulations
Chapter 18
Section 415. UNSANITARY CONDITIONS.
It shall be unlawful and a public nuisance for any person to
suffer, permit, or have upon their premises, whether owned or
occupied by them either one or more of the following unsanitary
206
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fly-producing or mosquito-producing, disease-causing conditions,
any of which is hereby declared to be a nuisance, to-wit:
(a) Manure which is not securely protected from flies and
mosquitoes.
(b) Garbage which is not securely protected from flies and
mosquitoes.
(c) Vegetable waste, grass sod, moulded grass, trash, litter,
rags, or refuse of any kind, nature, description or composition
in which flies or mosquitoes may breed or multiply.
(d) Standing water, either in low places or vessels. Provided
that all low places, pits, depressions, sloughs, ditches, sags,
or basins in which water naturally collects from rain or
natural drainage or overflow or backwater shall be drained in
such a manner that such water shall fall in the water channels
into which such places naturally drain, provided that water
may be kept in clean vessels for the purpose of watering fowls
or animals on conditions that the same is emptied each day
and cleaned thoroughly of all accumulation each day.
It shall be the duty of the Director of Health to prevent and
abate all nuisances as described in this chapter in the manner
prescribed by law.
Title 27 - Penal Code
Chapter 6. Public Property
Section 91. PROTECTION OF PUBLIC PROPERTY
It is hereby declared to be unlawful and an offense for any
person in the City of Tulsa, Oklahoma, to do any of the following
things, upon any public street, highway, avenue, alley, public
place or upon any property belonging to the City of Tulsa, regard-
less of the purpose for which such property was dedicated, acquired
or purchased, without the consent of the Board of Commissioners
of said city, to-wit:
(f) To dump boxes, trash, litter, paper, refuse matter in
cans, garbage, or any other articles in any substantial
quantities upon any of the public property of said City.
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Chapter 24. Streets and Sidewalks
Section 286. STAGNANT WATER
All owners or occupants of any grounds within the City are
forbidden to suffer stagnant water to stand or remain on any of
the said premises; all such stagnant water is hereby declared to
be a public nuisance and the owners, lessees, or occupants of
"such grounds are required, whenever the Board of Commissioners
shall deem it necessary, to cause said grounds to be leveled or to
be drained so that stagnant water be allowed to flow naturally and
freely from said place. (Ord. No. 499)
Section 353. CLEANING
It shall be unlawful for any person to omit or refuse to clean
off the sidewalk and gutter in front of the premises of such person
or the alley in the rear of such premises when notified to do so by
the officers of the City of Tulsa. (Ord. No. 55)
Section 354. TRASH
It shall be unlawful for any person to deposit, throw, place,
or scatter or cause to be placed on any street, alley, sidewalk,
gutter, or other public place within the City of Tulsa any filth,
refuse, garbage, ashes, rubbish, grass, weeds, paper, or any
animal or vegetable matter. (Ord. No. 499)
Section 356. OPEN GRATING
It shall be unlawful and an offense for any person to permit
to be open or leave open any cellar door, manhole, or grating of
any kind in or upon any street, sidewalk or alley of the City.
Section 357. DRAINAGE
No person shall permit any water, slops, or other liquids to
drain into any street or alley or onto any sidewalk within the City.
Provided, that the natural drainage of rainwater shall not be pro-
hibited by the provisions of this section when the same is from
natural elevations, in reasonable quantities as would naturally
occur and which do not carry filth or other accumulations from
off the private property into or onto said streets or alleys. (Ord.
No. 499)
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Title 40 - Waterworks and Sewage
Chapter 4. Spavinaw Water District
Section 62. HEALTH RULES
Whereas, the Commissioner of Health of the State of
Oklahoma, has, for the preservation of the public health, pro-
mulgated, adopted, and put in force and effect in said Spavinaw
Water District, the following Rules and Regulations, to-wit:
(e) Refuse Matters Not to be Discharged in Spavinaw Reser-
voir. No human excrement shall be deposited or discharged into
the Spavinaw Reservoir or into any watercourse, as hereinbefore
defined in paragraph (b); and no cesspool, privy, or other recep-
tacle for the deposit of human excrement shall be located,
constructed, or maintained within said Spavinaw Water District,
unless such cesspool, privy or other receptacle be so constructed
that no portion of its contents can escape or be washed into such
waters, and shall not be located closer than 660 feet to water's
edge.
(f) Same. No human excrement, or contents of any privy,
cesspool, sewer, or other receptacle for the reception or storage
of human excrement shall be deposited or discharged within said
Spavinaw Water District or upon or into the ground at a place from
which any such excrement, composit, or contents or particles
thereof, may flow or be washed or carried into the Spavinaw
Reservoir, or into any watercourse as hereinabove defined in
paragraph (b).
(g) Same. No house slops, sink waste, water which has been
used for washing or cooking, or other polluted water shall be
discharged into the said Spavinaw Reservoir, or into any water-
course with said Spavinaw Water District; and no house slops,
sink waste, water which has been used for washing or cooking, or
other polluted water shall be discharged into or upon any ground
in said Spavinaw Water District within 660 feet of the high water
line of said Spavinaw Reservoir, or of any watercourse as here-
inabove described in paragraph (b).
(h) Same. No garbage, manure, or putrescible matter
whatsoever shall be put into the said Spavinaw Reservoir, or into
any watercourse as hereinabove described in paragraph (b); and
no garbage, manure, or putrescible matter whatsoever shall be
put upon the ground in said Spavinaw Water District within 660
209
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feet of the high water line of said Spavinaw Reservoir or of the
high water line of any watercourse, as hereinabove defined in
paragraph (b); or within any such greater distance as may from
time to time be established either by the State Health Department
or by the City of Tulsa.
(i) Same. No stable, pigsty, henhouse, barnyard, hog yard,
hitching or standing place for horses, cattle, or other animals,
or other place where animal manure is deposited or accumulated,
shall be located, constructed, or maintained in said Spavinaw
Water District, any part of which is within 660 feet of the high
water line of any watercourse, as hereinabove defined in para-
graph (b).
(j) Same. No refuse, industrial wastes, or other waste
products or polluting liquids, or other substance of a nature
poisonous or injurious, either to human beings or animals, or
of such nature as would impart an objectionable taste or odor to
any water into which it might be discharged, and no putrescible
matter whatsoever shall be discharged directly into or at any
place from which it may flow or be washed or carried into said
Spavinaw Rese.fvoir or into any watercourse, as hereinabove
defined in paragraph (b).
(k) Approval State Department of Health; When. No system
of sewers or other works for the collection, conveyance, disposal
or purification of domestic or manufacturing sewage, wastes, or
drainage, or any other putrescible matters whatsoever shall,
except in accordance with plans first approved in writing by the
State Department of Health, be constructed or maintained at any
place within the Spavinaw Water District so called. No private
or separate sewer shall be constructed or maintained in said
Spavinaw Water District having an outlet upon or in the ground
within 660 feet of the high water line of said Spavinaw Reservoir
or of the high water line of any watercourse, as hereinabove
defined in paragraph (b).
Title 40 - Waterwork and Sewage
Chapter 5. Requirements for Use of Sanitary Sewage System
Section 104. PROHIBITED CONNECTIONS
No roof, foundation drain, or surface water drainage pipe
shall be connected so as to discharge water into a public sewer
or house sewer. No structure shall be constructed and no condi-
210
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tion created which will cause or permit the discharge of surface
drainage of any type into any house or public sewer line. No
septic tank shall be connected with the sanitary sewer system.
No dam or obstruction shall be placed in any sanitary sewer
except with the permission of the Superintendent.
Section 105. SWIMMING POOLS - PONDS
It shall be unlawful for any person to connect any swimming
pool, wading pool, fish pond, or similar reservoir to the sewer
system unless first granted permission by the Superintendent.
Any person desiring to make such a connection shall make a
written application to the Superintendent and if such application
is approved, shall, before being issued said permit, execute a
written agreement to the City stipulating that, (1) the reservoir
shall not be drained except during the hours designated by the
Superintendent; (2) the outlet orifice shall be a restricted diameter
of a size to be designated by the Superintendent; (3) the owner
shall hold the City harmles.s from liability for any damage result-
ing from such a connection; (4) and that the permit so issued is
of a temporary nature and may be discontinued at any time the
Superintendent deems it advisable for the safety and health of
other users of said sanitary sewer line that the connection shall
be discontinued.
Section 106. SEPARATE SANITARY SEWERS - EACH
PREMISE
Each premise shall have a separate sanitary sewer connec-
tion, provided that where, after the public sewer has been
constructed, the adjacent property has been platted, replatted,
or the several buildings thereto relocated in such a manner that
one or more are separated from the public sewer, then the
Superintendent may require an extension of the main or lateral
of the public sanitary sewer system so that the said public sewer
could serve directly any building that has been separated from the
existing public sewer; provided further such other requirements
are met as to size of pipe, construction, and use as the Superin-
tendent may deem necessary and that easements be granted to
the public covering the location of the extended public sewers
across intervening lots or tracts of ground.
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Section 107. UNLAWFUL DISCHARGE
It shall be unlawful for any person to discharge, place, throw,
or deposit or so place as to be carried in any public sewer or house
sewer or works of the City of Tulsa, or into any sewer connected
therewith, any of the following substances:
(a) General Restrictions: Grease, unground garbage, hair,
feathers, hide, blood, paunch, dead animals, sand, cinders, ashes,
stone dust, lime sludge, plastics, wood, mud, or any other solids
likely to cause obstruction of flow in any such sewers or works;
gas, tar, residues from petroleum storage, refining or process
fuel, or lubricating oil, gasoline, naptha, or explosives or inflam -
mable liquids or substances; cyanides, or cyanogen compounds,
capable of liberating hydrocyanic gas on acidification; mineral
acids, waste acid pickling or plating liquids, from pickling or
plating of iron, steel, brass, copper, chromium, nickel, zinc,
lead, or any other dissolved or solid substance which will endanger
health or safety, interfere with the flow of sewers, attach or
corrode sewers or sewage treatment structures or otherwise
interfere with the operation of the sewers or works of the City of
Tulsa.
(b) Specific Restrictions:
(1) Acidity or alkalinity must be neutralized so that the average
daily pH will be in the range of pH 6. 0 to pH 8.0, with a
maximum temporary variation of pH 6 to pH 10.
(2) Must not contain more than ten parts per million of the
following gases: hydrogen sulfide, sulphur dioxide, nitrous
oxide, or any of the halogens.
(3) Must not contain any explosive substance.
(4) Must not contain any inflammable substance with a flash
point lower than 187° F.
(5) Must not contain grease or oil or other substances that
will solidify or become viscous at temperatures between 32°
to 150° F.
(6) Must have a temperature with the range of 32° to 150° F.
212
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(7) Must not contain soluble substances or concentrations
that would increase the viscosity to greater than 1. 1 specific
viscosity.
Title 51 - Building Code
Chapter 12. Safeguards During Construction
Section 1213. STORAGE OF MATERIAL
1213. 1 Within Building
Materials or equipment needed in a building operation, if
stored within the building, shall be so placed that they will not
load any part of the construction in excess of the design load, nor
interfere with the safe prosecution of the work.
1213.2 Outside Building
(a) Materials and equipment shall not be stored in a street,
alley, sidewalk, or any other public space except by special per-
mission of the municipality.
/
(b) In whatever manner building material may be stored or
equipment set up in a street, a safe walkway not less than 4 feet
wide, unobstructed for its full length and adequately lighted at all
times shall be maintained for use of the public.
1213. 3 Covering Material
Materials stored within the building or within 10 feet of the
building which require covering shall be protected by noncombusti-
ble material.
Section 1214. DISPOSAL OF WASTE
Waste material and rubbish shall not be stored nor allowed to
accumulate within the building or in the immediate vicinity, but
shall be removed from the premises as rapidly as practicable.
No material shall be disposed of by burning on the premises or in
the immediate vicinity without permission from the municipality.
Dry material or rubbish shall be wetted down, if necessary, to lay
dust or prevent being blown about.
Chapter 18. Use of Streets and Alleys During Construction
Section 1808. MORTAR, CEMENT - PREPARING
Lime, cement, or other mortar and concrete may be prepared
upon any street within the space designated in this code, to be used
213
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or occupied for building purposes. If such mortar or concrete is
prepared or deposited upon the roadway, sidewalk, or parkage, it
shall be upon a light bed of tongued and grooved boards, placed
upon two-inch bearers or sleepers, leaving an air space below,
and shall be properly protected so as to prevent any splashing or
dripping on the parkage, roadway, or sidewalk. It shall be unlawful
for any person to prepare or deposit concrete or mortar of any
description, or any similar mixture upon the unprotected surface
of any pavement, parkage, or sidewalk.
Section 1809. EMERGENCY PRECAUTIONS
The Building Inspector shall be empowered hereby to use his
discretion in enforcing additional measures not specifically
required by this code, to safeguard the public and all property
interests against injury, loss, or damage as the occasion may
arise when streets, sidewalks, or alleys are used for the storage
and handling of materials or any other purpose connected with any
building operation in the corporate limits of the City of Tulsa.
(Ord. No. 5374)
Title 56. Plumbing Code
Chapter 12. Drainage System
Section 152. BUILDING SEWER
(d) Sanitary and Storm Sewers. Where separate systems of
sanitary drainage and storm drainage are installed in the same
property, the sanitary and storm building sewers or drains may
be laid side by side in one trench.
Chapter 14. Storm Drains
Section 177. GENERAL
(a) Drainage Required. Roofs, paved areas, yards, swimm-
ing pools, courts and courtyards, the drainage of which discharge
onto public property, shall be drained into a storm sewer system
where such a system is available. Permit applicants must first
check with the office of the City Engineer.
(b) Prohibited Drainage. Storm water shall not be drained
into any sanitary sewer system.
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Chapter 15. Septic Systems
Section 186. PERMIT REQUIRED
Before any person shall construct, repair, or install any
septic tank system within the corporate limits of the City of Tulsa,
within five miles of the City Corporate limits, or outside of the
City of Tulsa wherever the plumbing system is connected directly
or indirectly with the Water Works System of the City of Tulsa, he
shall obtain a permit therefor from the Plumbing Inspector, and
the refusal, failure, or neglect to obtain such a permit before
commencing such construction or installation shall be unlawful,
and each day thereafter in which such work shall be done, shall be
unlawful and a separate offense.
215
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APPENDIX E
STATE OF OKLAHOMA
INSTREAM WATER QUALITY CRITERIA
FOR THE
ARKANSAS AND VERDIGRIS RIVERS
AND
THEIR INTERSTATE TRIBUTARIES
All storm water runoff from Urban Tulsa flows either directly or
indirectly into the Arkansas River or the Verdigris River. Therefore,
it is important to include in this study the State of Oklahoma's water
quality criteria for both major receiving streams. These criteria are
essentially identical for the two rivers, with the exception that the
Verdigris River and its interstate tributaries provide more favorable
public and private water supplies, but are not designated for the
production of hydroelectric power. The water quality standards for
the Arkansas River and interstate tributaries are quoted below (11):
The water quality criteria for the Arkansas River and interstate
tributaries, are based on the present and potential uses, and on
existing quality data. The proposed criteria shall serve as
guidelines to control pollution and to maintain the best quality
which will result in an equitable balance of social and economic
benefits to the State. It is realized that the criteria cannot be
considered as permanently fixed. Future changes in cultural
activities, the development of additional quality data, enhance-
ment of existing quality by further removals of dissolved solids,
and improvements in waste treatment technology may necessitate
revisions of the criteria. The proposed criteria are applicable at
all times and at all flows, except as otherwise indicated.
I. Arkansas River and Interstate Tributaries
A. Water Uses
The Arkansas River and Interstate Tributaries above the
Kaw Reservoir Dam are used, or may be used for fish
and wildlife propagation, agriculture, hydroelectric
power, aesthetics, public water supplies, industrial
supplies, and to receive treated wastes. Inflows from
the Salt Fork Arkansas River and the Cimarron River
result in a high degree of mineralization and a quality
217
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less than desirable for public water supplies and similar
uses requiring water of higher quality. However, due to
the shortage of waters in the area of more suitable
quality, it is expected that off-channel storage will be
developed for diverting flows of suitable quality for
domestic use. Less than desirable quality through the
Tulsa area has discouraged general development for
higher quality uses. The mineral quality improves below
Keystone Dam to the Arkansas State Line. Further
improvements in quality through flow regulation and
control of natural and manmade pollutants should result
in a quality suitable for a wider range of beneficial uses.
B. General Criteria
All tributary streams and all waste effluents shall be in
such condition that when discharged to the Arkansas
Rivers and Interstate Tributaries, they shall not create
conditions which will adversely affect public health, or
use of the water for beneficial purposes.
C. Specific Criteria
1. Mineral Quality-Historic data on stream flow and
mineral quality has been published in reports entitled,
"Chemical Character of Surface Water of Oklahoma, "
water years 1947 through 1964, and "Water Quality
Records in Oklahoma, " for the 1964 water year.
Statistical summaries of these records. . .will serve
as interim guidelines for control of water quality.
It is recognized that the present water quality of the
Arkansas River and Interstate Tributaries, particular-
ly the Salt Fork Arkansas and Cimarron Rivers, is
less than desirable with significant contributions of
minerals from natural as well as manmade sources.
These criteria have the objective of enhancement of
4 water quality by preventing further degradation at
this time with the intent of improving the quality as
the plans for removing the major natural salt sources
are implemented and manmade pollution is further
controlled. Quality management objectives, insofar
as is practical, will be directed toward securing a
water of higher quality.
218
-------
2. Bacteria
In evaluating biological quality of waters and the use
and value of such waters for beneficial purposes,
consideration will be given by the appropriate
regulatory authority to the results of a sanitary
survey covering the drainage areas and stream
reaches that may effect such biological quality.
Waste discharges into waters used or capable of
being used for domestic water supplies or body
contact aquatic sports including skiing and swim-
ming, shall receive disinfection or equivalent treat-
ment as necessary for compliance with the following
requirements.
a. At the point of intake for treatment of waters
used as public water supplies, bacteria of the
coliform group shall not exceed 5, 000/100 ml
as monthly average5 value (either MPN or MF
count); nor exceed this number in more than 20%
of the samples examined during any month; nor
exceed 20, 000/100 ml in more than 5% of such
samples.
b- In all areas designed as recreational areas for
body contact aquatic sports, including swimming
and skiing, bacteria of the coliform group shall
not exceed 1, 000/100 ml as a monthly average
value (either MPN or MF count) during the
recreational season; nor exceed this number in
more than 20% of samples examined during any
one month; nor exceed 2,400/100 ml (MPN or
MF count) on any day except during periods of
storm water runoff. Provided, however, that
Bacteriological criteria is tentative pending release of recommenda-
tions by the National Technical Task Committee on bacterial para-
meters for public water supply, recreation and irrigation and
subsequent approval by appropriate state and federal water pollution
control agencies.
Logarithmic average based on a minimum of five samples per 30 days.
219
-------
the fecal coliform shall not exceed a geometirc
mean of 200/100 ml, nor shall more than 10% of
total samples during any 30-day period exceed
400/100 ml.
c. Bacterial concentrations of other than natural
origin will be maintained below levels detrimental
to beneficial uses.
3. Oil and Grease - Essentially free of floating or
emulsified oil or grease.
4. Solids - Free of floating debris, bottom deposits,
scum, foam, and other materials of a persistent
nature from other than natural sources.
5. Turbidity - Turbidity of other than natural origin
shall not cause a substantial visible contrast with
the natural appearance of the water or be detrimental
to beneficial uses.
6. Color - Color producing substances of a persistent
nature from other than natural sources shall be
limited to concentrations which will not be detrimen-
tal to beneficial uses.
7. Temperature - Differential changes in temperature
from other than natural sources shall be limited to
a maximum of 5° F provided the maximum tempera-
ture due to manmade causes shall not exceed 70° F
in trout streams, 75° F in small-mouth bass streams,
or 93° F in warm water streams.
8. Taste and Odor Producing Substances - Taste and
odor producing substances shall be limited to con-
centrations that will not interfere with the production
of potable water by modern treatment methods or
impart off color or unpalatable flavor to the flesh of
fish, or result in offensive odors in the vicinity of
the water, or otherwise interfere with beneficial uses.
9. Dissolved Oxygen - The dissolved oxygen concentra-
tion shall not be less than 4 mg/1, except that this
limitation of 4 mg/1 will not be applicable in the
220
-------
immediate vicinity of the point of waste discharge
when the stream flow is less than 200% of the waste
flow. In addition, the relationship of dissolved
oxygen, biochemical oxygen demand and chemical
oxygen demand of waste releases, and the flow
characteristics of the stream shall not create con-
ditions down-stream that are detrimental to beneficial
uses.
10. Toxic Substances - Toxic Substances shall not be
present in such quantities as to cause the waters to
be toxic to human, animal, plant, or aquatic life.
For aquatic life, using bioassey techniques, the toxic
limit shall not exceed one-tenth of the 48-hour median
tolerance limit, except that other limiting concen-
trations may be used in specific cases when justified
on the basis of available evidence and approved by
the regulatory authority.
11. Radioactivity - The average concentration of the
radionuclide (or radionuclides) in water at points of
release from the control of the user shall not exceed
the limits prescribed for such releases in the
applicable portion of the current set of Radiation
Protection Regulations, as promulgated by the
Oklahoma State Board of Health or subsequent
revisions thereof. A reasonable effort shall be made
to identify each radionuclide, and to determine its
concentrations, which is present in the effluent.
12. pH - The pH shall be between 6. 5 and 8.5. pH values
below 6. 5 and above 8. 5 must not be due to waste
discharge.
13. Other Substances - The control of other substances
not heretofore mentioned will be guided by the U. S.
Public Health Service Drinking Water Standards of
Wherever reference is made to a current standard and to a "sub-
sequent revision thereof, " it is implied that such revisions will be
officially approved by appropriate state and federal agencies prior
to becoming official state or federal criteria respectively.
221
-------
1962, or latest revision thereof, and accumulated
scientific data on limits above which injury to use
occurs. Pollutional substances will be maintained
below maximum permissible concentrations for public
water supplies, recreation requirements, agricultural
needs, and other beneficial uses.
II. Tributaries to the Arkansas River
The quality of tributary streams shall be controlled so that the
quality of the Arkansas River and Interstate Tributaries will
not be lowered beyond the criteria set forth above. In addition,
adequate control shall be maintained to prohibit the development
of public health hazards or nuisance conditions in such tribu-
taries and maintain the highest current beneficial use of the
waters pending a determination of best usage and the establish-
ment of specific criteria.
222
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APPENDIX F.
CITY OF TULSA
STORM DRAIN SYSTEM
INCLUDING
TEST AREA BOUNDARIES
The following plates were made by overlaying the City of Tulsa's
Storm Drain System on TMAPC's 1:600 Land Use Maps. The Storm
Drain System overlays were drawn to this scale utilizing the City of
Tulsa's Official 1:200 Storm Drain Atlas and maps. The purpose of
this task was twofold. First, the project's test area boundaries had
to be defined to better understand the drainage patterns and to outline
the drainage area for a land use retrieval within the test areas.
Second, the maps will provide TMAPC with working maps to define
subdrainage storm, water runoff sheds for planning and management
purposes.
LEGEND FOR FIGURES F-l THROUGH F-15
Symbol Item
• Natural drainage boundaries
iiiiniii Boundaries used in data retrieval for the test areas
-~ ^x Open drainage
——— Covered drainage conduit
A(2)
o
Sampling site location
Rain gage location
223
-------
FIGURE F-l
TEST AREA NO. 1
224
-------
FIGURE F-2
TEST AREA NO. 2
N
225
-------
FIGURE F-3
TEST AREA NO. 3
226
-------
FIGURE F-4
TEST AREA NO. 4
227
-------
FIGURE f-5
TEST AREA NO. 5
i
t3
. \-\ Xi[inniii
ZZ8
-------
21"
FIGURE F-6
TEST AREA NO. 6
2Z9
-------
FIGURE F-7
TEST AREA NO. 7
\ \' l
\\-r-
230
-------
FIGURE F-8
TEST AREA NO. 8
N
231
-------
FIGURE F-9
TEST AREA NO. 9
232
-------
FIGURE F-10
TEST AREA NO. 10
Z33
-------
FIGURE F-11
TEST AREA NO. 11
234
-------
FIGURE F-12
TEST AREA NO. 12
N
235
-------
I
N
236
-------
N
FIGURE F-14
TEST AREA NO. 14
Z37
-------
FIGURE F-15
TEST AREA NO. 15
238
-------
APPENDIX G
FEDERAL WATER QUALITY ADMINISTRATION
STORET II SAMPLING STATION CODE NUMBERS
All storm water quality data collected on this project were coded,
transferred to the Federal Water Quality Administration Storet II
Water Quality Data Sheets (Form No. GPO 902-791), and sent to
the Robert S. Kerr Water Research Center, Ada, Oklahoma for
storage in the Storet System. The code numbers assigned to the
sampling stations are shown below:
Project Storet II
Station Station
Number Code
1 360625009552300
2 360624009555200
3 ." 360508009554100
4 360851009554300
5 360733009559600
6 361030009558220
7 360708009555100
8 361102009556020
9 361252009558430
10 360828009600030
11 361109009559070
12 361152009552070
13 360515009557530
14 360428009557290
15 360552009559050
239
-------
APPENDIX H
FORMAT OF DATA CARDS
USED
FOR COMPUTER ANALYSIS
This appendix gives the format of the data cards used for recording
and storing all of the storm water quality data and other pertinent
information collected and calculated on this project. These cards
served as input data to many statistical computer programs used to
analyze and evaluate the characteristics of storm water pollution.
All statistical analyses were performed utilizing an IBM 360 computer
and the System/360 Scientific Subroutine Package--(360A-CM-03X)
Version III. The reference document for these programs is IBM
Application Program Manual No. H20-0205-3.
241
-------
TABLE H-l
FORMAT OF DATA CARDS
Card
Symbol Item Unit Columns No.
Yj Total coliform thousands/100 ml 1-6
Y2 Fecal coliform number/100 ml 7-12
Yg Fecal streptococcus thousands/100 ml 13-18
Y4 BOD mg/1 19.24
Y5 COD mg/1 25-30
Y6 TOG mg/1 31-36
Y7 Organic Kjeldahl mg/1 37-42
nitrogen
Yg Total soluble mg/1 43-48
o rthopho sphate
Blank 49-63
Date 64-69
Event no. 70-71
Time 72-75
Test area no. 76-77
Composite or grab sample 78
Sample no. 79
Card no. 80 1
Yg Total solids mg/1 1-6
Dissolved solids mg/1 7-12
Volatile dissolved mg/1 13-18
solids
Suspended solids mg/1 19-24
Volatile suspended mg/1 25-30
solids
Yj4 pH dimensionless 31-36
Y15 Chloride mg/1 37-42
Yj£ Specific conductance micromhos/cm 43-48
Blank 49-63
Date 64-69
Event no. 70-71
Time 72-75
Test area no. 76-77
Composite or grab sample 78
Sample no. 79
Card no. 80 2
242
-------
TABLE H-l--Continued
Symbol
Zl
Z2
Z3
Z4
Z5
Z6
Z7
Z8
Item
Time since start
Antecedent amount
Antecedent average
intensity
Time since antecedent event
Amount of antecedent event
Duration of antecedent
event
Avg. intensity of
antecedent event
Antecedent prec. index
(API)
Blank
Date
Event no.
Time
Test area no.
Composite or grab sample
Sample no.
Card no.
Unit
hr.
in.
in. /hr.
hr.
in.
hr.
in. /hr.
in.
Care
Columns No.
1- 6
7-12
13-18
19-24
25-30
31-36
37-42
43-48
49-63
64-69
70-71
72-75
76-77
78
79
80 3
Environmental Index dimensionless 1- 6
(El)
Housing Index (HI) dimensionless 7-12
Good housing % 13-18
X4 Fair housing % 19-24
Poor housing % 25-30
Refuse no. def. /acre 31-36
X7 Burners no. def. /acre 37-42
Rubble no. def. /acre 43-48
Lumber no. def. /acre 49-54
Old autos no. def. /acre 55-60
Poor sheds no. def./acre 61-66
Total deficiencies no. def. /acre 67-72
Blank 73-75
Test area no. 76-77
Blank 78-79
Card no. 80
243
-------
TABLE H-l--Continued
Symbol
XT -i
j. J
X, ,
14
X
Y15
X16
J. \J
X-i 7
1 i
Xjg
X19
X20
Xo,
Zl
•*»•*> o
LL
•**-1 *5
Z3
X0 .
24
X25
£*.J
X0/
x26
27
X28
X29
X21
X22
X23
X?4
wTX
X17
Xi8
xl
Item
Arterial streets
Arterial streets
Other streets
Other streets
Residential density
Residential density
Main covered storm
sewer
Covered sewer/
total length
Arterial streets
Other streets
Residential land
Commercial land
Blank
Test area no.
Blank
Card no.
Industrial land
Institutional land
Transportational land
Open space
Unused space
Arterial streets
Other streets
Residential land
Commercial land
Residential density
Residential density
Environmental Index
(El)
Blank
Test area no.
Blank
Card no.
Unit
acres/acre
miles /acre
acres/acre
miles/acre
people /res. acre
people /acre
miles
ratio
%
%
%
%
%
%
%
%
%
%
%
%
%
people/res, acre
people /acre
dimen s ionle s s
Card
Columns No.
1- 6
7-12
13-18
19-24
25-30
31-36
37-42
43-48
49-54
55-60
61-66
67-72
73-75
76-77
78-79
80 5
1- 6
7-12
13-18
19-24
25-30
31-36
37-42
43-48
49-54
55-60
61-66
67-72
73-75
76-77
78-79
80 6
244
-------
TABLE H-l--Continued
Symbol
M,
1
M3
M.
Mt
5
M?
M8
DID
Item
Unit
Card
Columns No.
All Items: Arith. Mean by Events
Total coliforma
Fecal coliforma
Fecal streptococcusa
BOD
COD
TOG
Organic Kjeldahl
nitrogen
Total soluble
orthophosphate
Blank
Relief number
Blank
Test area no.
Blank
Card no.
thousands/ 100 ml
thousands/ 100 ml
thousands/ 100 ml
mg/1
mg/1
mg/1
mg/1
mg/1
dimen s ionle s s
1- 6
7-12
13-18
19-24
25-30
31-36
37-42
43-48
49-66
67-72
73-75
76-77
78-79
80 7
All Items: Arith. Mean by Events
M9
M10
M12
M14
M15
M16
Total solids
Dissolved solids
mg/1
mg/1
Volatile dissolved solids mg/1
Suspended solids
Volatile suspended
solids
PH
Chloride
Specific conductance
Blank
Test area no.
Blank
Card no.
mg/1
mg/1
dimen s ionle s s
mg/1
micromhos/cm
1- 6
7-12
13-18
19-24
25-30
31-36
37-42
43-48
49-75
76-77
78-79
80 8
aGeometric mean by events
245
-------
TABLE H-l--Continued
Symbol
Dl
J.
Item
Total area
Unit
acres
Length of main stream feet
03 Length to center of area feet
D4
D5
D6
D7
X30
X31
x
25
D8
D9
Ll
L
L3
L4
L5
L6
L7
L9
L10
Fall of drainage area
Average main
channel slope
Average land slope
Impervious cover
Open space +
institutional land
Open space 4-
transportational land
Industrial land
Geometry number (G)
Form factor (FF)
Blank
Test area no.
Blank
Card no.
BOD loading
COD loading
Total solids loading
Organic Kjeldahl
nitrogen loading
Soluble orthophos-
phate loading
BOD loading
COD loading
Total solids loading
Organic Kjeldahl
nitrogen loading
Soluble orthophos-
phate loading
Blank
Test area no.
Card no.
feet
feet/foot
%
07
(yi
%
O/
dimen s ionle s s
dimensionless
Ib. /day/mile of
street
Ib. /day /mile of
street
Ib. /day /mile of
street
Ib. /day /mile of
street
Ib. /day/mile of
street
Ib. /acre/year
Ib. /acre/year
Ib. /acre/year
Ib. /acre/year
Ib. /acre/year
Card
Columns No.
1- 6
7-12
13-18
19-24
25-30
31-36
37-42
43-48
49-54
55-60
61-66
67-72
73-75
76-77
78-79
80 9
1- 6
7-12
13-18
19-24
25-30
31-36
37-42
43-48
49-54
55-60
61-75
76-77
78-80 10
246
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APPENDIX I
STREET CLEANING OPERATIONS
IN TULSA
Large portions of the typical urban area are devoted to street and ex-
pressway systems. Since urban storm water runoff reaches the drainage
system and thus the receiving streams via the road system, no report
on storm water pollution would be complete without investigating and
analyzing the street cleaning operations. The following pages describe
the city street cleaning and drainage maintenance operations. Also
included are data showing the volumes of street refuse collected and
the various cost functions which have been assigned concerning the
street cleaning operations in Tulsa.
Street Cleaning
In any investigation of urban storm water pollution, consideration has
to be given to the litter accumulated in the streets. As pointed out in
the 1969 Federal Water Pollution Control Administration publication,
"Water Pollution Aspects of Urban Runoff, " the actual amount of litter
on the street at any one time is largely dependent upon the frequency
and effectiveness of the street cleaning operations. Also, the report
indicates that the amount and nature of street litter is found to vary with
land use, population, traffic flow, and other indigenous factors.
In Tulsa, the street cleaning is conducted by the Street Maintenance
Department. Within this department, there are five main divisions: (1)
street cleaning, (2) storm sewers, (3) paved streets, (4) unpaved streets,
and (5) demolition and forestry. All divisions of this department are of
significance to this study.
Street Cleaning Section - The city is divided into eight street cleaning
districts, which vary in size according to the number of streets in each
area. The district characteristics arid locations are shown in Figure 1-1
and Table 1-1. The downtown area (District No. 1) is swept and flushed
nightly except Saturdays. Arterial streets are swept and flushed a
minimum of once weekly, more often if required. Residential streets
are swept approximately six times per year. There are approximately
1, 071 miles of paved, and 576 miles of unpaved, streets and alleys in
Tulsa. By the city's definition, an unpaved street (or alley) is any dirt,
247
-------
FIGURE 1-1
CITY OF TULSA
STREET CLEANING DISTRICTS
DENOTES DISTRICTS WHERE NO
SCHEDULED STREET CLEANING
6 DONE.
Z48
-------
TABLE I-1
CITY OF TULSA
STREET SWEEPING DISTRICTS
District
Number
1
2
3.
4
5
6
7
8
9
10
11
12
13
District
Name
Downtown
Northwest
North Central
Northeast
Far Northeast
Far East
East No. 2
East No. 1
Southeast No. 1
Southeast No. 2
Southwest
Far South
Far Southeast
No. of
Curb
Blocks3-
3200
3744
1322
2820
n. d.
n. d.
3736
3978
3628
3384
n. d.
n. d.
n. d.
Sweeping
Frequency
Each night except
Saturday
10 weeks
5-6 weeks
8 weeks
Not scheduled
Not scheduled
10 weeks
11 weeks
9 weeks
10 weeks
Not scheduled
Not scheduled
Not scheduled
n. d. =no data.
rock, oiled, or asphalted street having no concrete base, curbs, or
gutters. An average of 3, 700 curb miles of streets is cleaned per
month. Since curb miles represent both sides of a street, the preceding
figure is reduced to 1850 miles of streets per month. The average
monthly cleaning is 80% for downtown streets and 20% for residential
areas because the downtown area is swept nightly, and arterial
streets weekly.
The Street Cleaning Section is divided into two 30-man shifts (day and
night). A sweeping crew normally consists of one sweeper operator,
one flusher operator, one dump truck operator, and two laborers.
During the past year, the city started replacing its old sweepers with
new machines having added features. Incorporated in the new models
are dirt and trash hoppers capable of unloading into trucks or other
containers. This new type of machine will cut down the operation cost
of the street cleaning department.
249
-------
This section also removes debris, underbrush, and trees from the
open channels. With its appropriate equipment, the section performs
the major portion of cleaning all streets of debris after storms. There
are approximately 500 miles of open drainage channels in Tulsa at
the present time.
Although this section's major function is maintenance of unpaved
streets, considerable time and effort are spent on indirectly controlling
storm water pollution through cleaning and maintenance of the open
drainage ditches. Since all of the cost of this section is combined, no
effort was made to determine the cost for cleaning and maintenance of
open drainage.
Forestry and Demolition - This section's responsibilities are weed
control and removal of debris, trees, and underbrush from city proper-
ty. A new function of this department is the demolition of dilapidated
structures condemned by the Health Department and City Commission.
This new function will clear areas of unwanted dilapidated structures,
thereby indirectly helping to control urban storm water pollution.
Snow and Ice Control - The city uses both salt and sand for snow and
ice control. Salt is used mainly in the downtown areas and on arterial
streets. Sand is used primarily at intersections in outlying areas. Due
to Tulsa1 s geographical location, these practices are utilized infrequent-
The amount of salt used during the winter months of 1968-1969 in Tulsa
was approximately 90, 000 pounds. This compares with approximately
530,000 pounds used during the winter months of 1967-1968. The much
larger amount used during 1967-1968 was due to the unusually heavy
amount (11. 8 in. ) of snow received in March 1968. Based on thirty
years of records at the Tulsa International Airport, the yearly mean
snowfall is 9. 4 inches. The amount of salt applied to the streets and
the amount of snow recorded during the past two fiscal years are
shown below:
Year Snow (in. ) Salt Applied (Ib. )
FY 1967-68 17.0 530,000
FY 1968-69 8.0 90,000
250
-------
TABLE 1-2
MONTHLY STREET CLEANING OPERATIONS FOR FISCAL YEAR 1967-1968
Components of Street
Month
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
Total
Dirt
498
411
57
381
108
129
369
576
366
474
567
405
4341
Trash
2925
3840
2041
3135
2304
885
2184
1986
2085
2367
3582
2838
30, 192
Limb
120
321
168
168
111
174
87
69
606
384
447
393
3048
Litter In Cubic Yards
Leaves
and
Grass
0
15
30
1035
2142
1458
108
72
72
90
33
3
5058
Othera
231
129
234
258
375
237
285
408
87
432
252
204
3132
Total
3774
4716
2550
4977
5040
2883
3033
3111
3216
3747
4881
3843
45,771
Water
Used By
Flushers
MG
3.7
5.0
4.0
5. 2
2.9
1.7
2.8
2.5
3. 0
4.3
4.2
3.7
43.0
Number
Of Curb
Blocks
Cleaned
53, 000
53,000
45, 000
53, 000
39,000
33, 000
36, 000
38,000
35, 000
39,000
53,000
48,000
525,000
Estimated
Average
cu. yd. /block
0.071
0.089
0. 057
0. 094
0. 129
0. 087
0. 084
0. 082
0. 092
0. 096
0. 092
0.080
aThis category includes sand, gravel, rock, and other street litter not included in the other
categories.
-------
TABLE 1-3
MONTHLY STREET CLEANING OPERATIONS FOR FISCAL YEAR 1968-1969
Ui
to
Components of Street
Month
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
Total
Dirt
810
303
174
66
105
60
39
375
471
306
156
303
3168
Trash
3234
2946
3189
4083
1473
1107
3531
1797
2736
3288
2199
2034
31,617
Limb
378
363
288
273
225
222
183
51
78
174
216
330
2781
Litter In Cubic Yards
Leaves
and
Grass
0
0
0
414
1428
2283
510
102
129
99
0
6
4971
Other3-
168
255
1143
264
264
3
390
324
258
411
186
222
3888
Total
4590
3867
4794
5100
3495
3675
4653
2649
3672
4278
2757
2895
46,425
Water
Used By
Flu she rs
MG
3.9
4.2
3.0
3.6
2.0
0.9
2.6
2.9
3. 2
4.3
3.9
4.7
39. 2
Number
Of Curb
Blocks
Cleaned
50,000
46,000
45,000
49,000
23,000
31,000
51,000
46,000
48,000
57,000
48,000
46,000
494, 000
Estimated
Average
cu. yd. /block
0.092
0. 084
0. 106
0. 104
0. 152
0. 118
0. 091
0. 058
0. 076
0.075
0.057
0.063
aThis category includes sand, gravel, rock, and other street litter not included in the other
categories.
-------
A study of the Street Department's monthly and annual reports pro-
vided information on the amounts and components of street litter
collected in Tulsa.
Tables 1-2 and 1-3 show the monthly volumes, components, and number
of curb blocks cleaned in Tulsa for FY 1967-68 and FY 1968-69.
The reported yearly average volumes of street litter collected in the
residential and commercial areas are:
Residential areas 16 to 18 cu. yd. /sq. mi.
Commercial areas 14 to 16 cu. yd. /sq. mi.
The average yearly weights per square mile are:
Residential areas 4 tons/sq. mi.
Commercial areas 4. 5 tons/sq. mi.
The greater tonnage and lower volume collected in the commercial
areas are attributed to a larger collection of rock and sand on major
thoroughfares and in the downtown area. This could result from the
greater effort devoted to sanding operations in the downtown area
during snow or ice storms.
The average yearly cost for cleaning the streets in Tulsa is approxi-
mately $447, 000. 00. This average is based on the expenditures for
FY 1967-68 and FY 1968-69. The cost includes wages, material,
and equipment. It does not include cost incurred for administration
or overhead. Various yearly cost functions are:
(1) $ 1. 38 per capita
(Z) $420. 00 per mile of paved street
(3) $ 0. 88 per curb block cleaned
(4) $ 98. 00 per cubic yard of street litter collected
Storm Sewer Section - The storm sewer division maintains approxi-
mately 330 miles of storm sewer which varies in size from 12 inch
diameter pipes to 15 foot semielliptical sections. The average length
of storm sewer lines cleaned per year is 12, 000 feet (2. 27 miles).
This division is also responsible for cleaning approximately 22, 000
catch basins. The catch basins, all located in the older sections of
the city, are cleaned on an "as needed" basis. The average number
cleaned per year is 2, 100. The volume of dirt and trash removed
253
-------
TABLE 1-4
STORM SEWER CLEANING AND MAINTENANCE FOR
FISCAL YEAR 1967-1968 AND FISCAL YEAR 1968-1969
Oi
Month
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
Total
Catch
Basins
Cleaned
194
268
117
159
227
131
168
221
364
267
112
72
2, 300
FY 1967-68
Storm Sewer
Cleaned
(Feet)
20
220
675
640
815
775
845
877
1,060
962
895
945
8,729
Cubic Yards
of
Dirt and
Trash
30
87
6
9
24
21
12
24
24
84
30
18
369
Month
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
Total
Catch
Basins
Cleaned
98
63
113
83
101
163
245
292
155
182
220
118
1,833
FY 1968-69
Storm Sewer
Cleaned
(Feet)
795
785
1, 191
223
1, 118
1,075
1, 085
1,290
1,205
1, 144
1,405
1,475
12,791
Cubic Yards
of
Dirt and
Trash
0
9
9
0
0
81
45
42
3
18
24
12
243
-------
from the catch basins in FY 1968-69 was 243 cubic yards. The older
catch basins are being replaced with a design that is "self-cleaning. "
The new type has a direct connection to the storm sewer line and has
no holding capacity for solids or runoff water. Catch basins are not
included in the street design of Tulsa's newer developments.
Although the main function of this section is to keep storm sewers,
manholes, and catch basins free of accumulated debris, this section
also installs stud-outs to drain low areas. During and after heavy
rains, pumping operations are carried on in low areas and dead-end
sewers.
The total man-hours worked by this division in FY 1967-68 and
FY 1968-69 were 7, 582 and 6, 944, respectively. The cleaning and
maintenance activities for these two fiscal years are shown in Table
1-4. The total cost of operation (including wages, material, and
equipment) was approximately $21, 000. 00 in FY 1967-68 and $22, 000
in FY 1968-69. The yearly cost functions are:
(1) $ 0. 07 per capita
(2) $10. 24 per catch basin cleaned
(3) $63. 42 per cubic yard of catch basin solids
removed
The above cost functions are somewhat in error becaus^ there was
no way of breaking down the wages and equipment for the various work
items of the section. Therefore, the cost per catch basin cleaned
and the cost per cubic yard of catch basin solids are extremely high
because the other work items (storm sewer cleaning, installation of
stud-outs, and pumping of low areas) are included in these figures.
Paved Street Section - The major functions of this section are: repairs
on paved streets, minor repairs on structures, replacement of paving
cuts, and drainage channel relocation. Inspection of the Street Depart-
ment's monthly reports indicates that on occasion this section performs
some street cleaning. Since the amount of street litter picked up is very
small, no cost estimates were made.
Unpaved Street Section - This section's main function is to keep all un-
paved streets and alleys open for traffic. The major portion of this
work is accomplished through grading, ditching, and filling the bad
places with crushed rock. There are approximately 575 miles of un-
paved streets and alleys in the city.
255
-------
APPENDIX J
CITY OF TULSA'S
MUNICIPAL SEWAGE TREATMENT PLANT
EFFLUENT DATA
The information in this appendix was compiled to provide the pollution
loadings to the receiving streams from the four treatment plants
serving Tulsa. These data were then compared with the storm water
pollution loadings from the urban area; results of such comparisons
are given in Section 9.
The locations and general characteristics of the treatment plants are
shown in Figure J-l and Table J-l. Tables J-2 and J-3 give the month-
ly average daily flows for the years 1967 and 1968, along with the
associated total flows to the Arkansas River and Bird Creek.
Average pollutant concentrations for BOD, COD, suspended solids,
organic Kjeldahl nitrogen, and soluble orthophosphate have been
listed in Table J-4. There is, as one might expect, considerable
variation in these concentrations, as shown in the cumulative frequency
distributions for BOD and suspended solids in Table J-5. These
frequency distributions are related to the efficiencies illustrated in
Table J-6.
Finally, Table J-7 contains the estimated average pollution loadings
calculated from the data already given. For comparison of these
results with the quality of storm, water runoff, reference should be
made to Table 46 in Section 9.
257
-------
FIGURE j.i
SEWAGE TREATMENT FACILITIES
TULSA, OKLAHOMA
LEGEND
I FLAT ROCK
1 COAL CREEK
3 NORTH SIDE
SOUTH SIDE
258
-------
TABLE J-l
CHARACTERISTICS OF TULSA'S
FOUR SEWAGE TREATMENT PLANTS
Treatment Population
Plant Served Capacity
North Side
South Side
Type of Removal
Flat Rock 57, 100 4 mgd Primary and secondary--
secondary treatment
accomplished by contact
stabilization
Coal Creek 52, 950 4 mgd
57, 100 11 mgd
Primary and secondary--
secondary treatment
accomplished by trickling filter
processes
Primary and secondary--
secondary treatment
accomplished by trickling filter
processes
156,590 21 mgd Primary
259
-------
TABLE J-2
MONTHLY AVERAGE DAILY FLOWSa
1967
Month
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Average
Flat Rock
4.5
4.5
4.5
5.0
5.2
5.3
5.4
5. 1
5.4
4.8
5.4
5.1
5.0
Average
Coal Creek
2.3
2.2
2.4
3.0
3.5
3.4
3.6
3.1
3.2
2.9
3.2
3.0
3.0
Daily Flow
North Side
5.9
6.3
6. 1
7.2
8.2
8.7
7.4
8.2
7.9
7.4
8.4
7. 5
7.4
(mgd)
Subtotal13
12.7
13.0
13.0
15.2
16.9
17.4
16.4
16.4
16.5
15. 1
17.0
15.6
15.4
South Sidec
13.0
13. 1
13.4
14.0
15. 1
15.9
16.6
15. 1
14. 3
13.7
14.8
14. 1
14.4
Totald
25.7
26. 1
26.4
29.2
32.0
33.3
33.0
31. 5
30. 8
28.8
31.8
29. 7
29.8
aBased on unpublished data from the Tulsa Water and Sewer Department
bTotal to Bird Creek
cTotal to Arkansas River
dTotal from City of Tulsa
-------
TABLE J-3
MONTHLY AVERAGE DAILY FLOWS*
1968
Month
Jan.
Feb.
Mar.
Apr.
May
June
to
0s July
Aug.
Sept.
Oct.
Nov.
Dec.
Average
Flat Rock
5.8
6.2
5.6
7.2
7.0
6.5
5.5
5.5
5.2
5.2
5.8
5.4
5.9
Average
Coal Creek
3. 1
4.0
4.7
5.6
4.0
3.9
3.2
3.0
3.0
3.0
3.4
3.6
3.5
Daily Flow
North Side
6.9
6.0
6.6
8.0
7. 1
7.2
7.7
8.2
7.3
8.3
7.9
7.8
7.4
(mgd)
Subtotal5
15.8
16.2
16.9
20.8
18. 1
17.6
16.4
16.7
15.5
16.5
17. 1
16.8
16.8
South Side0
14. 1
17.0
17. 7
16. 1
16.8
14.8
15.2
15.0
14.3
13. 3
11. 5
10.4
14. 7
Totald
29.9
33.2
34.6
36.9
34.9
32.4
31.6
31.7
29.8
29.8
28.5
27.2
31.5
aBased on unpublished data from the Tulsa Water and Sewer Department
bTotal to Bird Creek
cTotal to Arkansas River
dTotal from City of Tulsa
-------
TABLE J-4
AVERAGE POLLUTION PARAMETER CONCENTRATIONS
FROM CITY OF TULSA'S SEWAGE TREATMENT PLANTS
Treatment
Plant
Flat Rock
Coal Creek
tsj North Side
ro
South Side
BODa
55
34
16
120
aAverage monthly values for
Department) .
Source: U. S. Department
COD'
272
265
72
340
Average Concentration
Suspended
1 Solidsa
93
42
21
92
(mg/1)
Organic
Kjeldahlb
Nitrogen
2.0
4.3
3.9
2.4
1968 (Unpublished data, City of Tulsa, Water
of HEW, PHS, Preliminary Studies Arkansas
Soluble
O rthopho sphate
45
40
58
33
and Sewer
River and
Tributaries--Tulsa to Muskogee, Oklahoma, February, 1966.
-------
TABLE J-5
QUALITY OF EFFLUENT FROM TULSA'S
MUNICIPAL SEWAGE TREATMENT PLANTS2
Period of Time
%
Biochemical Oxygen
10
20
30
40
50
60
70
80
90
Suspended Solids
10
20
30
40
50
60
70
80
90
Probable Concentration
Flat Rock
Demand
28
35
42
51
66
77
86
98
113
76
90
100
109
116
128
138
151
178
Coal Creek
21
29
35
39
44
50
60
70
83
24
31
37
43
48
53
60
67
75
aSource: Wheeler and Associates, Report
North Side
10
12
16
17
18
19
20
22
23
10
16
18
21
24
27
30
33
38
on Sewage Collection
(mg/1)
Composite
11
13
18
23
32
41
53
74
93
17
23
29
35
47
65
87
111
138
and Treatment
South Side
126
138
151
158
165
174
181
191
202
/ r\
69
81
88
93
99
106
111
117
125
Facilities for Tulsa, Oklahoma, 1967, p. 65.
-------
TABLE J-6
EFFICIENCY OF REMOVAL OF TULSA'S
MUNICIPAL SEWAGE TREATMENT PLANTS21
Period of Time
%
Biochemical Oxygen
90
80
70
60
50
40
30
20
10
Suspended Solids
90
80
70
60
50
40
30
20
10
Probable Percentage
Flat Rock
Demand
18
32
47
58
60
65
71
75
79
16
22
30
37
41
46
52
57
62
Coal Creek
61
65
68
73
75
78
80
82
86
63
68
72
75
77
80
82
84
87
aSource: Wheeler and Associates, Report on
North Side
87
88
89
90
90
91
91
92
93
86
88
89
90
90
91
92
93
94
Removal
Composite
45
60
68
70
79
84
87
89
91
28
45
59
69
78
83
86
89
91
South Side
12
20
23
25
28
30
33
37
41
38
47
53
56
58
61
63
65
68
Sewage Collection and Treatment
Facilities for Tulsa, Oklahoma, 1967, p. 64.
-------
TABLE J-7
ESTIMATED AVERAGE DAILY LOADS TO RECEIVING STREAMS
FROM THE CITY OF TULSA'S FOUR SEWAGE TREATMENT PLANTS
Treatment Receiving
Plant Stream
Flat Rock Bird Creek
Coal Creek Bird Creek
North Side Bird Creek
Subtotal Bird Creek
South Side Arkansas River
Total
BOD
2, 700
980
990
4, 670
14, 700
19, 370
Average Daily Load (Ibs. /day)
Organic
Suspended Kjeldahl Soluble
COD Solids Nitrogen Orthophosphate
13,400
7,650
4, 450
25, 500
41, 680
67, 180
4, 600
1, 200
1, 300
7, 100
11, 300
18,400
100
130
240
470
290
760
2, 220
1, 170
3, 580
6,970
4, 050
11,020
-------
APPENDIX K
REGRESSION EQUATIONS
This appendix contains a selection of 263 of the univariate and multi-
variate regression equations developed during the course of the study.
The legend for the dependent and independent variables is given in
Table K-l. The equations themselves, along with their corresponding
correlation coefficients and F-values, are tabulated in Tables K-2
through K-7.
Tables K-2 and K-3 are both concerned with precipitation variables.
In Table K-2 are shown equations developed using data for all test
samples taken from all 15 test areas. Multiple regression equations
listed in Table K-3, on the other hand, were derived using BOD data
for only the samples which were collected on the rising limb of the
runoff hydrograph. Correlation coefficients for a number of additional
regression equations of this type are shown in Table 62 in Section 10.
Whereas Tables K-2 and K-3 deal with pollution parameter concentra-
tions at particular times during individual precipitation events, the last
four tables in this appendix are concerned with relating average pollut-
ant concentrations in storm water runoff to environmental, drainage,
and land use characteristics. The best univariate land use equations
for all test areas are shown in Table K-4. Table K-5 illustrates a
selection of the best univariate and multiple regression equations for
predictor variables common to both commercial and residential areas
(Test Areas No. 1, 12, and 14 have been omitted). Tables K-6 and
K-7 give, respectively, regression equations for residential test areas
and for commercial and industrial test areas.
For more complete explanations of the data presented in this appendix,
and for a description of the statistical methods used, reference should
be made to Section 10 of this report.
267
-------
TABLE K-l
DEPENDENT AND INDEPENDENT VARIABLES
USED IN REGRESSION ANALYSIS
Symbol
Item
Unit
D3
D4
D6
Dg
Ml
M3
M4
M5
M6
M7
M8
Mg
M10
M12
xl
X13
x14
X15
X16
X17
X18
X
X
X
X
19
20
21
22
X24
X25
X29
Total area
Length of main stream
Length to center of area
Fall of drainage area
Average land slope
Form factor
Total coliform geometric meana
Fecal coliform geometric mean
Fecal streptococcus geometric mean
Meanb BOD
Mean COD
Mean TOG
Mean organic Kjeldahl nitrogen
Mean soluble orthophosphate
Mean total solids
Mean dissolved solids
Mean suspended solids
Mean specific conductance
Environmental Index (El)
Arterial streets
Arterial streets
Other streets
Other streets
Residential density
Residential density
Main covered storm sewer
Covered sewer/total length0
Arterial streets
Other streets
Commercial land
Industrial land
Unused space
acres
feet
feet
feet
%
dimensionle s s
thousands/100 ml
thousands/100 ml
thousands/100 ml
mg/1
mg/1
mg/1
mg/1
mg/1
mg/1
mg/1
mg/1
micromhos/cm
dimensionless
acres/acre
miles/acre
acres/acre
miles/acre
people/res, acre
people/acre
miles
ratio
268
-------
TABLE K-l--Continued
Symbol Item Unit
YI Total coliform thousands/100 ml
Y£ Fecal coliform number/100 ml
Yj Fecal streptococcus thousands/100 ml
Y4 BOD mg/1
Y5 COD mg/1
Y9 Total solids mg/1
Zj Time since start hours
Z£ Antecedent amount inches
Z^ Antecedent average intensity inches/hour
Z4 Time since antecedent event hours
Zc Amount of antecedent event inches
Zy Average intensity of antecedent event inches/hour
aFor bacterial parameters, the geometric means are calculated
from the arithmetic averages of each event.
Arithmetic mean by events.
°See Glossary (Section 14) for a definition of the covered sewer/
total length ratio.
269
-------
TABLE K-2
REGRESSION EQUATIONS
POLLUTIONAL PARAMETER CONCENTRATIONS VS. PRECIPITATION VARIABLES
-j
o
Regression Equation3-
Correlation
(R) F-Valueb
Equation
Numbe r
Total Coliform (Thousands/ 100 ml)
In
In
In
In
In
In
In
In
In
In
Fecal
In
In
In
In
In
In
In
YI
Y!
YI
Y!
Yl
Yl
Yl
Yl
Yl
Yl
= 4.
= 4.
= 3.
= 4.
= 4.
= 3.
= 4.
= 4.
= 5.
= 3.
5125 -
4209 -
6591 +
0465 -
2364 -
3093 +
5157 -
7559 -
2598 -
8498 -
0
1
0
0
0
2
0
0
0
0
. 1667
.0553
.7748
.0011
.6697
.8925
.0921
. 1017
.0853
(Zi)
(Z2)
(Z3)
(Z4)
(Z5)
(Z7)
(Zj) - 0. 7517 (Z2) +0.6174 (Z3)
(Zj) - 0.6506 (Z2) - 0.00063 (Z^
(Zx) - 0.9638 (Z2) - 0.8297 (Z5)
.00039 (Z4) - 0.7950 (Z5) +3.2111 (Z?)
Coliform (Number/ 100
Y2
Y2
Y2
Y2
Y2
Y2
2
= 3.
- i
•*• •
= 1.
= 3.
= 2.
= -0
= 2.
0496 -
4867 +
7006 +
6669 -
2287 -
.0170 -
4327 -
0
1
2
0
0
.2022
. 1215
.3628
.0064
. 1047
ml)
(Zj)
(Z2)
(Z3)
(Z4)
(Z5)
f 13, 6623 (Z?)
0
.4498
(Zj) + 2.8966 (Z2) - 0.2350 (Z3)
-0.
-0.
0.
-0.
-0.
0.
0.
0.
0.
0.
-0.
0.
0.
-0.
-0.
0.
0.
167
151
056
078
122
135
185
186
232
200
093
076
086
208
009
295
183
11.
9.
1.
2.
5.
7.
4.
4.
7.
5.
3.
2.
2.
16.
0.
33.
4.
13**
08**
22
35
82*
15**
C C 5'^ j'j
62**
27**
33**
12
05
62
07**
03
95**
08**
K-l
K-2
K-3
K-4
K-5
K-6
K-7
K-8
K-9
K-10
K-ll
K-12
K-13
K-14
K-15
K-16
K-17
-------
TABLE K-2--Continued
Correlation
Regression Equation
lnY2
lnY2
In Y2
= 3.
= 1.
= 1.
2934
9157
5072
- 0.
- 0.
- 0.
2840 (Zj)
4689 (Zj)
0039 (Z4)
+ 2.
+ 3.
- 0.
2461 (Z,)
1576 (Z2)
6503 (Z,)
- 0.0053 (Z4)
+ 0.6380 (Z5)
+ 12. 3412 (Z7)
0.
0.
0.
(R)
244
189
324
F- Value
7.44**
4. 38**
13. 88**
Equation
Numbe r
K-18
K-19
K-20
Fecal Streptococcus (Thousands/100 ml)
In Y
In Y
In Y
In Y
In Y
In Y
In Y
In Y
In Y
In Y
= 2. 4938 - 0. 3757 (Zj)
= 1. 1485 - 0.4251 (Z2)
= 0.4574 + 2.3032 (Z3)
= 2.0997 - 0.0053 (Z4)
= 0.7375 + 0.2506 (Zg)
= 0.2525 + 3.7180 (Z7)
= 2.2075 - 0.5109 (Zj) -I- 1.5954 (Z2) - 0.3832 (Z3)
= 2.7615 - 0.3901 (Zi) + 1.1460 (Z2) - 0.0039 (Z4)
= 1. 6878 - 0. 5137 (Zi) + 1.7319 (Z2) + 0.5837 (Z5)
= 1. 6891 - 0.0051 (Z4) + 0.2647 (Z5) + 1. 1073 (Z?)
BOD (mg/1)
In Y4 = 2. 3731 - 0. 1264 (Z1)
In Y4 = 2.4774 - 0.5125 (Z2)
In Y = 2. 3156 - 0. 7452 (Z )
In Y4 - 2.2466 - 0.0003 (Z4)
In Y4 = 2.3351 - 0.2453 (Zg)
In Y4 = 2.2143 - 0.2045 (27)
In YA = 2. 6679 - 0.0408
0.318
0.051
0. 149
0.321
0.039
0. 147
0.352
0.416
0.362
0.327
48. 88**
1. 14
9.91**
49.91**
0.65
9. 57**
20.40**
30.21**
21. 75**
17.28**
K-21
K-22
K-23
K-24
K-25
K-26
K-27
K-28
K-29
K-30
- 0.2790 (Z,) - 0.8185 (Z,)
& J
0. 126
0.210
0. 149
0.060
0. 123
0.027
0.251
6.76**
19. 13**
9. 42**
1.51
6.36*
0.30
9.25**
K-31
K-32
K-33
K-34
K-35
K-36
K-.37
-------
TABLE K-2--Continued
fO
Regression Equation
In
In
In
Y =
Y4 =
Y4 =
2.
2.
2.
5293
7531
4310
+ 0.
•f 0.
- 0.
0018
0086
(Zx) - 0.5139 (Z2) - 0.00026 (Z4)
(Zi) - 0. 6484 (Z2) - 0. 3674 (Z5)
00033 (Z4) - 0. 2348 (Z5) - 0. 1692 (Z?)
Correlation
(R)
0.
0.
0.
216
274
138
F- Value
6.
11.
2.
75**
21**
67**
Equation
Number
K-38
K-39
K-40
COD (mg/1)
In
In
In
In
In
In
In
In
In
In
Y5 =
Y5 =
Y5 =
Y5 =
— *
Y5 =
Y5 =
Y5 =
Y5 =
Y5 =
Total Solids
In
In
In
In
In
In
In
Y_
Q ~"
Y9 =
Yg =
Y9 =
v -
I. Q —
Y__
Q ~~
Q —
4.
4.
4.
4.
4.
4.
4.
4.
4.
4.
5031
5138
3440
3600
2975
3649
5757
5559
5339
3750
- 0.
- 0.
- 0.
- 0.
4- 0.
- 0.
- 0.
- 0.
- 0.
- 0.
0391
3046
0434
0001
0618
1789
0246
0201
0218
(Zl)
(Z2)
(Z3)
(Z4)
(Z5)
(Z7)
(Zi) - 0.2001 (Z2) - 0.0900 (Z3)
(Zi) - 0.2247 (Zz) - 0.00001 (Z4)
(Zi) - 0.2101 (Z7) + 0.0292 (Z5)
00017 (Z4) + 0.0798 (Z5) - 0. 3015 (Z?)
-0.
-0.
-0.
-0.
0.
-0.
0.
0.
0.
0.
176
199
015
034
050
037
215
213
214
086
11.
14.
0.
0.
0.
0.
5.
5.
5.
0.
57**
91**
08
41
90
50
78**
69**
75**
89
K-41
K-42
K-43
K-44
K-45
K-46
K-47
K-48
K-49
K-50
(mg/1)
5.
5.
5.
5.
5.
5.
5.
8313
7428
6876
7769
7514
6994
7304
- 0.
+ 0.
+ o.
- 0.
+ 0.
+ 0.
- 0.
0168
0275
3788
0001
0119
3333
0144
(Zl)
(Z2)
(Z3)
(Z4)
(Zc)
~J
(Zj) + 0.0572 (Z2) + 0. 3004 (Z3)
-0.
0.
0.
-0.
0.
0.
0.
057
014
097
020
007
052
103
1.
0.
3.
0.
0.
1.
1.
33
07
85*
16
02
11
45
K-51
K-52
K-53
K-54
K-55
K-56
K-57
-------
TABLE K-2--Continued
Regression Equation
In YQ
In Y9
In Y
= 5.7961
= 5.7663
= 5.7052
- 0.0282 (Zj)
- 0.0295 (Zj)
- 0.00002 (Z
+ 0. 1355 (Z2) 4- 0.00002 (Z4)
+ 0. 1535 (Z2) -f 0.0453 (Z5)
) - 0.0019 (Z,) + 0. 3269 (Z7)
• 3 f
Correlation
(R)
0.079
0.083
0.052
F- Value
0.85
0. 94
0. 37
Equation
Numbe r
K-58
K-59
K-60
aSee Table K-1 for a listing of the dependent and independent variables,
bL,evels of significance: * 95 percent level
** 99 percent level
-j
00
-------
TABLE K-3
MULTIPLE REGRESSION EQUATIONS
In BOD CONCENTRATION21 VS. RISING LIMB PRECIPITATION VARIABLES
to
Test
Area
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Regression Equation
In Y4
In Y4
In Y4
In Y4
In Y4
In Y4
In Y4
In Y4
In Y
In Y4
In Y4
In Y4
In Y4
In Y4
In Y4
= 2.584 +0.
= 3. 148 - 0.
= 2. 139 - 0.
= 3.760 - 0.
= 2. 864 + 0.
= 2. 898 - 0.
= 1.793 +0.
= 2.641 + 0.
= 2.699 - 0.
= -6.922 + 2
= -0.236 + 0
- 2. 117 + 0.
= 3.831 - 0.
= 2.072 + 0.
= 3. 686 - 0.
080 (Zx)
185" (Z^
018 (Z^
189 (Zi)
147 (Z$
008 (Zt)
166 (Zx)
032 (Zj)
086 (Zj)
.096 (Zj)
.306 (Zj)
037 (Zj)
291 (Zi)
141 (Zj)
098 (Zx)
- 1
+ 0
- 0
+ 0
- 0
- 0
- 2
- 0
- 0
-
-
- 0
+ 0
- 0
- 0
.395 (Z2)
. 154 (Z2)
.402 (Z2)
.529 (Z2)
.490 (Z2)
.513 (Z2)
.177 (Z2)
.022 (Z2)
.357 (Z2)
8.644 (Z2)
1.394 (Z2)
.878 (Z2)
.258 (Z2)
. 130 (Z2)
.627 (Z2)
+ 1.35 (Z3)
- 5.71 (Z3)
-0. 17 (Z3)
- 6. 53 (Z3)
+ 0. 10 (Z3)
- 0. 10 (Z3)
+ 2.25 (Z3)
- 1.19 (Z3)
+ 1.02 (Z3)
+ 31.58 (Z3)
+ 9.39 (Z3)
+ 1.40 (Z3)
- 2.88 (Z3)
- 0.45 (Z3)
- 2.09 (Z3)
Correlation
\R) F- Value0
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
651
788
356
713
650
754
684
475
930
833
770
893
848
566
678
1.
5.
1.
11.
4.
2.
2.
0.
12.
3.
3.
21.
4.
2.
4.
96
46*
06
72**
14*
63
35
39
82**
78
41
08**
26
20
81*
Equation
Number
K-61
K-62
K-63
K-64
K-65
K-66
K-67
K-68
K-69
K-70
K-71
K-72
K-73
K-74
K-75
1BOD in mg/1.
'See Table K-1 for a listing o£ the dependent and independent variables.
'Levels of significance:
* 95 percent level
** 99 percent level
-------
TABLE K-4
SELECTION OF BEST UNIVARIATE
LAND USE REGRESSION EQUATIONS FOR ALL TEST AREAS
Regression Equation'
Correlation
(R)
Equation
F-Valueb Number
Total Coliform (Thousands/ 100 ml)
Mj = 430 - 363
Mx = -23 + 5802 (X16)
M! = -16 + 10.2 (X17)
Fecal Coliform (Thousands/ 100 ml)
M2 = 0.75 + 0. 158 (X25)
Fecal Streptococcus (Thousands/ 100 ml)
M3 = 7.2 + 112 (X16)
BOD (mg/1)
= 10.0 + 1.41 (X19)
COD (mg/1)
M5 = 55 + 2.08 (X1?)
M5 = 63 + 17.2 (X19)
-0.856
0.627
0.691
0. 514
0.288
0.479
0. 533
0. 550
35.76** K-76
8.45* K-77
11.90** K-78
4.66
1. 18
3.88
K-79
K-80
K-81
5.15* K-82
5.63* K-83
-------
TABLE K-4--Continued
tv)
-J
Regression Equation
Organic Kjeldahl Nitrogen (mg/1)
M? = 0.60 + 7.76 (X13)
M7 = 1. 18 - 0.016 (X22)
Soluble Orthophosphate (mg/1)
Mg = 0.64 4- 15.8 (X13)
Mg = 1.77 - 0.03 (X22)
Mg = 0.90 4-0.03 (X25)
Mg = 0.62 + 0.08 (X2 )
Total Solids (mg/1)
M9 = 165 + 11, 750 (X13)
M9 = 915 - 18.0 (X22)
Mg = 363 4- 24.4 (X25)
Mg = 212-1-50.2 (X29)
Suspended Solids (mg/1)
M12 = -3 + 11,430 (X13)
M12 = 187 4-24.0 (X25)
M12 = 54 4-47.3 (X2
-------
TABLE K-5
REGRESSION EQUATIONS FOR COMMON PREDICTOR VARIABLES5
Regression Equation*3
Correlation Equation
(R) F-Valuec Number
-J
-J
Total Coliform (Thousands/100 ml)
M! = 565 - 420 (Xj) - 49.3 (X2Q) - 6.70 (Dg)
Fecal Coliform (Thousands/100 ml)
M2 = -11.7 + 6. 92 (Xj) + 6.25 (X2Q) - 0.396 (D9)
Fecal Streptococcus (Thousands/100 ml)
M3 = 9. 30 + 6. 23 (Xj) + 4. 28 (X2Q) - 5. 58 (D?)
BOD (mg/1)
M4 = 8.2 + 0.00065 (D,)
M4 = 8.0 + 0.00138 (D3)
M4 = 10.6 + 582 (X14)
M4 - 10.0 + 1.35 (X19)
M4 = 7. 3 - 0.724 (Xj) + 0. 679 (X2Q) + 0.00073 (D2)
0.885
0.900
0.585
0.590
0.520
0.306
0.421
0.627
9.67** K-97
11.33**
1.39
K-98
K-99
5.35** K-100
3.70 K-101
1.03 K-102
2.15 K-103
1.73 K-104
-------
TABLE K-5--Continued
oo
Regression Equation
COD (mg/1)
M5 = 56 + 0.0056 (D2)
M = 50 -f 0.0136 (D3)
M5 = 70 + 3.03 (X21)
M5 = 67 + 14.6 (X19)
M5 = 71 - 45.4 (Xx) +2.61 (X21) + 0.00619 (D2)
TOC (mg/1)
M6 = 23.9 + 0.00135 (D2)
M6 = 21.3 + 0.00363 (D3)
M6 = 36.6 - 9.29 (D9)
M6 = 26. 5 + 3. 56 (X19)
M6 = 53. 5 - 19. 5 (Xx) - 0. 757 (X22) + 0.00157 (D2)
Organic Kjeldahl Nitrogen (mg/1)
M7 = 0. 30 + 0.0049 (D4)
M? = 0. 16 + 0.266 (D6)
M? = 0.52 + 0.429 (Xx)
M = 0.65 + 79.8 (X14)
M = 1. 19 - 0.045 (X18)
M? = 0.96 - 0.379 (X2Q)
M? = 0.23 - 0.00 (X1?) - 0.029 (X20) + 0.256 (D6)
Correlation
(R)
0. 506
0. 511
0. 526
0.455
0.839
0.428
0.475
-0.413
0. 386
0.648
0.668
0.882
0.406
0.413
-0.534
-0. 562
0.887
F- Value
3.44
3.54
3.83
2.61
6. 32*
2.24
2.92
2.06
1.75
1.93
8.05*
34. 87**
1.97
2.06
3.99
4.60
9.81**
Equation
Number
K-105
K-106
K-107
K-108
K-109
K-110
K-lll
K-112
K-113
K-114
K-115
K-116
K-117
K-118
K-119
K-120
K-121
-------
TABLE K-5--Continued
INJ
O
NO
Regression Equation
Soluble Orthophosphate (mg/1)
Mg = 0.53 + 0.0043 (D4)
Mg = 0.82 + 0.402 (D9)
Mg = 1.28 - 1.24 (X15)
M8 = 0.59 - 0.00 (X17) - 0.027 (X2Q) + 0.0042 (D4)
Total Solids (mg/1)
M9 = 318 + 0.303 (Dj)
M9 = 199 + 2.05 (D4)
M9 = 332 + 62.8 (X19)
M9 = 130 + 8. 99 (X2Q) + 2. 59 (X22) + 2. 06 (D4)
Suspended Solids (mg/1)
M12 =24+4. 69 (X20) + 4. 38 (X22) + 1. 08 (D4)
Correlation
(R)
0.579
0.501
-0.265
0.584
0.626
0.671
0.464
0.690
0.629
F- Value
5.05*
3.36
0.75
1,38
6.45*
8.20*
2.74
2.42
1.74
Equation
Number
K-122
K-123
K-124
K-125
K-126
K-127
K-128
K-129
K-130
aTest Areas 1, 12, and 14 omitted.
See Table K-l for a listing of the dependent and independent variables.
cLevels of significance: * 95 percent level
** 99 percent level
-------
TABLE K-6
REGRESSION EQUATIONS FOR RESIDENTIAL AREAS'
to
oo
o
Regression Equation
Correlation
(R)
Total Coliform (Thousands/ 100 ml)
Mx = 521 - 427 (Xi)
MJ = -62 + 14 (X1?)
M! = -192 + 320 (X20
M, = -106 + 15 (X22)
In
M
M
J^^i
i^i.
Fecal
In
M
M
M
M
M
M
M
i
J,
1
1
= 303 -
= 268 -
290 (Xj) +6.21 (X1?)
286 (Xi) + 3.99 (X17) + 61.8
= 3. 7475 - 0. 738 (X,) + 0. 054 (X17)
= 269 -
Coliform
309 (Xj) - 137 (X2Q) +0.580
(Thousands/ 100 ml)
+ 0.638 (X20)
(D9)
= -0. 175 + 1.276 (X,)
2
2
7
Lt
2
7
= 1.333
= 1.866
= 2.413
= -1.69
= 0.274
= 0.884
- 0.027 (X1?)
-0.877(X20)
- 0.081 (X22)
16 + 1.626 (Xj) + 0. 115 (X17)
+ 1.07 (Xj) - 0. 245 (X2Q)
+ 0.806 (X,) - 0.396 (X7n) +
- 2.097 (X20)
0.543 (Dq)
-0.
o;
0.
0.
0.
0.
0.
0.
0.
-0.
-0.
-0.
0.
0.
0.
883
828
798
514
918
920
778
915
300
184
248
328
360
304
452
F- Value c
17.
10.
8.
1.
10.
5.
1.
5.
0.
0.
0.
0.
0.
0.
0.
75**
70*
79*
80
67*
49
54
16
49
18
33
60
15
20
26
Equation
Number
K-
K-
K-
K-
K-
K-
K-
K-
K-
K-
K-
K-
K-
K-
K-
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
-------
TABLE K-6--Continued
oo
Regression
Equation
Correlation
(R)
F- Value
Equation
Number
Fecal Streptococcus (Thousands/ 100 ml)
M = 8.492 - 0.903 (Xj)
M3 = 8.837 - 0.065 (X12)
M3 = 5.739 + 1.790 (X20)
M = 6.08 + 0.088 (X22)
In M7 = 2.4741 - 1.216 (X,) -
3 1
M3 = 3.80 + 1.30 (X!) + 2.
M3 = 2. 34 .+ 0. 645 (XL) +2
BOD (mg/1)
M4 = 9.8 + 3.0 (Xx)
M4 = 13.9 - 0. 1 (X17)
M4 =17.0-4.2 (X20)
M4 = 21.7 - 0.5 (X22)
. 0. 115 (X1?) -f 2.076 (X2Q)
56 (X20)
. 18 (X20) + 1.36 (D9)
M4 = 9. 1 - 2. 79 (Xi) + 0. 182 (X?n) + 0. 00091 (D?)
In M4 = 4. 7221 - 0.879 (XL) i
- 0.091 (X22)
M4 = 21.4 + 3.66 (X20) - 0
COD (mg/1)
M5 = 126 - 46 (Xi)
M = 62 + 1.6 (X17)
M5 = 87 + 0.2 (X20)
- 0.25T(X2Q) - 0. 195 (X21)
. 700 (X22)
-0.050
-0. 106
0. 120
0.084
0.545
0. 130
0.237
0.215
-0. 198
-0.359
-0.605
0.621
0.674
0.635
-0.336
0.334
0.002
0.01
0.06
0.07
0.04
0.42
0.03
0.06
0. 24
0.20
0. 74
2.89
0.63
0.42
1.35
0.63
0.63
0.00
K-146
K-147
K-148
K-149
K-150
K-151
K-152
K-153
K-154
K-155
K-156
K-157
K-158
K-159
K-160
K-161
K-162
-------
TABLE K-6--Continued
Regression Equation
Correlation
(R)
F-Value
Equation
Number
ro
oo
ro
M5 = 126 - 2. 1 (X22)
M5 = 69 - 74.71 (X!) + 3.68 (X21) +0.0105 (D2)
M5 = 295 - 111 (XO +0.963 (X2i) - 6.40 (X22)
In M5 = 4.3850 - 1.956 (Xt) - 0.002 (X21) - 0. 118 (X22)
- 0.023 (X29)
Organic Kjeldahl Nitrogen (mg/1)
M7 = 0.44 + 0.54 (Xj)
M? = 1.48 - 0.04 (X1?)
M? = 2.01 - 1.00 (X2Q)
My = 1.69 - 0.04 (X22)
M? = 2. 13 + 0.0152 (X17) - 1. 34 (X2Q)
In M? = 1.3895 + 0.046 (X1?) - 2. 145 (X20)
M? =0.02 - 0.0072 (X1?) + 0. 200 (X20) + 0. 286 (D6)
Soluble Orthophosphate (mg/1)
Mg = 0.97 +0. 14 (Xx)
M8 = 1.32 - 0.01 (X1?)
Mg = 1.60 - 0.45 (X2Q)
Mg = 1.73 - 0.03 (X22)
M = -1.01 - 0.039 (X17) + 1. 56 (X2Q) + 0.0095 (D4)
Mg =0.66 - 0.0011 (X21) + 0.0645 (X29)
In M8 = -0.3482 + 0.0075 (X21) +0.051 (X29)
-0.260
0.971
0.759
0.844
0.36
16.55*
1.36
1.24
K-163
K-164
K-165
K-166
0.348
0.670
0.779
0.476
0.787
0.797
0.889
0.69
4.07
7.73*
1.47
3.26
3.47
3.78
K-167
K-168
K-169
K-170
K-171
K-172
K-173
0.094
0.276
0.364
0.391
0.803
0.817
0.804
0.04
0.41
0.76
0.90
1.82
4.01
3.64
K-174
K-175
K-176
K-177
K-178
K-179
K-180
-------
TABLE K-6- -Continued
oo
U)
Regression Equation
Total Solids (mg/1)
M = 384 + 37 (Xj)
M9 = 224 - 1.6 (X )
M9 = 577 - 144 (X2Q)
M9 = 498 - 4.4 (X22)
M9 =-481 - 326 (X2Q) +
In M = 6.0338 - 0.904 (X
M9 = -139 - 15.4 (X2Q)
Dissolved Solids (mg/1)
5.50 (X21) + 14.2 (X22)
) +0.022 (X21) +0.045 (X22)
+ 16.0 (X22) + 2.57 (D4)
MIQ = 150 -1- 71. 8 (X^ + 14. 9 (X20) - 5. 11 (X21)
In M10 = 5. 0566 + 0. 244 (:
Suspended Solids (mg/1)
M12 = 791 - 312 (Xt) -
In M12 = 8.0193 - 1. 589 (:
M12 = 267 - 81 (X2Q) +
Xj) - 0.028 (X2Q) - 0.013 (X21)
288 (X2Q) + 1.32 (X21)
Xj) - 1.381 (X2(J) +0.012 (X21)
0.88 (X22) + 0.23 (D4)
Correlation
(R)
0.073
-0. 107
-0. 344
-0. 148
0.435
0. 507
0.765
0.334
0.231
0.828
0.764
0.385
F- Value
0.03
0.06
0.67
0. 11
0.23
0.34
1.41
0. 13
0.06
2. 17
1.40
0. 17
Equation
Number
K-181
K-182
K-183
K-184
K-185
K-186
K-187
K-188
K-189
K-190
K-191
K-192
f"Test Areas No. 3, 5, 7, 8, 9, 13, and 15.
See Table K-l for a listing of the dependent and independent variables.
f^
Levels of significance: * 95 percent level
** 99 percent level
-------
TABLE K-7
REGRESSION EQUATIONS FOR COMMERCIAL AND INDUSTRIAL AREAS*
00
Regression
Total Coliform (Thousands/ 100
MX
Ml
Ml
Ml
M
Ml
In Mi
= 372 - 329 (Xj)
= 126 + 1128 (X14)
= 69 + 34 (X2Q)
= 250 - 10 (X24)
= 154-3 (X29)
= 119 - 384 (Xx) - 19.5
= 370 - 304 (XL) - 1.47
= 5. 9923 - 1.240 (Xi) -
Equation"
ml)
(X19) - 13. 4 (D)
(X24)
- 0.050 (X?A\
Correlation
(R)
-0.930
0.015
0.308
-0.711
-0.206
0.951
0.933
0.852
F- Value0
25.66**
0.00
0.42
4.08
0. 18
9.46
10.06*
3.96
Equation
Numbe r
K-193
K-194
K-195
K-196
K-197
K-198
K-199
K-200
Fecal Coliform (Thousands/ 100 ml)
M2 = 6.63 - 3.91 (XL)
M2 = 13. 13 - 2511 (Xu)
M2 = -5. 64 + 5.25 (X2Q)
M = 7.86 - 0.35 (X,4)
M2 = 5.93 - 0.25 (X2g)
M2 = -8. 61 + 7. 52 (Xj) + 5. 65 (X20) - 1. 66 (D9)
M2 = 8. 92 - 1. 12 (Xj) - 0. 574 (X21)
lnM2 = 1.2828 + 0.478
- 0. 183 (X21)
-0.200
-0.584
0.852
-0.438
-0.332
0.897
0.497
0.718
0. 17
2.07
10.58*
0.95
0.49
4. 10
0.49
1.60
K-201
K-202
K-203
K-204
K-205
K-206
K-207
K-208
-------
TABLE K-7--Continued
00
Ul
Regression Equation
Correlation
(R)
F- Value
Equation
Numbe r
Fecal Streptococcus (Thousands/ 100 ml)
M
M3
M3
M3
M3
M3
M3
In M,
= 13.37 - 0.55 (X,)
= 37. Z9 - 6516 (X14)
- 7.24 + 3.20 (X2Q)
= 15. 16 - 0. 19 (X24)
= 12.06 + 0. 10 (X29)
= 36. 40 - 8. 78 (Xx) - 1290 (X14) - 8. 94 (Do)
= 8.75 - 6. 17 (Xj) - 0. 522 (X21)
= 2.2404-- 1. 396 (X,) + 0. 108 (X71)
-0.017
-0.912
0.312
-0..141
0.083
0.660
0.552
0. 503
0.00
19.65*
0.43
0.08
0.03
0.77
0.66
0.51
K-209
K-210
K-211
K-212
K-213
K-214
K-215
K-216
BOD (mg/1)
M4 = 14.3 - 3. 1 (Xj)
M4 = 10.5 +393 (X14)
M, = 11.3 + 0.38 (X__)
M4 =
M4 =
M . =
Ml =
13.8 - 0. 15 (X24)
11. 5 + 0.05 (X2g)
8. 3 - 0.709 (Xj) H
13.2 - 0. 130
1.
+ 0.202J
) + 0.00028 (D )
J.VJ-4 — J.-l.ij - \J . 1JU \S*.~.) T U . t,U£. ^y^.-j-.J
In M = 2. 5773 - 0.013 fx24) + 0.0020 (X25)
COD (mg/1)
0.489
0.280
0. 191
0. 578
0.223
0.830
0.599
0.626
1.26
0. 34
0. 15
2.01
0.21
2.22
0.84
0.97*
K-217
K-218
K-219
K-220
K-221
K-222
K-223
K-224
M5 = 117 - 29 (Xj)
M5 = 94 + 247 (X14)
-0.400
0.015
0. 76
0.00
K-225
K-226
-------
TABLE K-7--Continued
Regression Equation
M
M
M
M
M
In M
5
5
5
5
= 96 -
= 116
= 83 +
= 152
= 116
0
-
1
1
*
91 (X2Q)
. 80 (X24)
39 (X?q)
- 52.2 (Xj)
-
1
= 4.7686
.78 (X24
- 0.024
+ 1.72 (X21) - 21. 7 (D9)
) + 0.0108 (X25)
(X24) + 0.0011 (X25)
Correlation
(R)
-0.
-0.
0.
0.
0.
0.
040
598
501
862
598
609
F- Value
0.
2.
1.
2.
0.
0.
01
23
34
89
84
61
Equation
Number
K-227
K-228
K-229
K-230
K-231
K-232
TOG (mg/1)
M6 = 3. 8 + 4. 76 (Xj) + 2. 10 (Xlq) + 0.0055 (D3)
oo
^ Organic Kjeldahl Nitrogen (mg/1)
M? = 0. 57 + 0.41 (Xj)
M? = 0. 65 + 56 (X14)
M7 = 1.08 - 0. 12 (X20)
M7 = 0.73 +0.01 (X24)
My = 0.76 + 0.01 (X2Q)
M7 = 0.79 + 0.277 (Xj) - 0.0742 (X2Q
•»*• ... f\ -"» r- r» n i r\ ** A f\ t -*r \ f\ f\ rt /•* / •*.?-
= . . j - . 2Q)
In M? = -0. 2588 + 0. 340 (Xj) - 0. 089 (X2(J)
= 0.31 - 0.0810 (X!) - 0.0507 (X2Q) + 0.265 (D6)
M?
Soluble Orthophosphate (mg/1)
Mg = 0.74 + 0.83
M8 = 0. 17 + 315 (Xu)
0. 970
0.805
0.505
-0.772
0. 542
0.579
0.889
0.909
0.958
0.279
0.483
15.74*
7.38
1.37
5.89
1.66
2.02
5.65
7. 17
11.24*
0.34
1.22
K-233
K-234
K-235
K-236
K-237
K-238
K-239
K-240
K-241
K-242
K-243
-------
TABLE K-7--Continued
to
00
Regression Equation
Mg = 2.14 - 0.44 (X2Q)
Mg = 1.75 - 0.04 (X24)
Mg = 0.57 +0.09 (X29)
Mg = 2.74 - 1.20 (Xj) + 0. 118 (X2g) - 0.0131 (D4)
Mg = 1. 35 + 0. 0252 (X25) + 0. 0622 (X2?)
In Mg = -0.3833 + 0.0151 (X25) + 0.0272 (X29)
Total Solids (mg/1)
M9 = 306 + 600 (X1)
M = -72 + 206, 154 (X )
Mg = 1348 - 335 (X2(J)
M9 = 1024 - 24 (X24)
M9 = 162 + 67 (X29)
Mg = 1426 - 715 (Xj) + 83.0 (X2
-------
TABLE K-7--Continued
Suspended
M12 =
™12 =
M12 =
In M12 =
Regression Equation
Solids (mg/1)
-3 + 65.9 (X )
1392 - 746 (XTj) + 83. 1 (X29) - 8. 37 (D4)
-93 + 36.1 (X2Q) + 68.7 (X2:< 99 percent level
-------
APPENDIX L
MONTHLY PRECIPITATION DATA FOR SIX RAIN GAGES
IN THE URBAN TULSA AREA
The following table gives the monthly precipitation data for six rain
gages located in Tulsa for the years 1964 through 1969. Gages No.
1-5 are maintained by the City of Tulsa Engineering Department.
Gage No. 6 is the official Environmental Science Services Administra-
tion gage located at the Tulsa International Airport. The data from
these six gages were used for the calculations of expected storm water
runoff volumes.
Locations of the rain gages are illustrated in Figure 2 in Section 3.
289
-------
TABLE L-l
MONTHLY PRECIPITATION FOR SIX RAIN GAGES
TULSA, OKLAHOMA3"
1964
Month
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Total
1
0.40
1.05
2.85
4.70
3.95
3.60
0.25
3.90
1.35
1.05
4.65
1.00
28.75
2
0.45
1.00
2.55
5.40
4.25
3.90
0.30
3.55
1.10
1.00
5.15
1.05
29.70
3
0.40
1.20
2.60
4.05
3.90
4.35
1.45
4. 15
1.85
1.00
4.65
1.05
30.65
Gage
Number
4
0.
1.
2.
5.
3.
6.
0.
3.
1.
0.
5.
1.
32.
50
20
35
20
85
55
30
90
15
80
05
15
00
5
0.50
1.85
2.45
4.30
3.75
3.60
1.05
4.00
1.75
1.05
4.70
1.05
30.05
6
0.63
2.17
3.96
5.87
4.77
5.79
1.80
6.14
3.33
1.24
6.90
1.67
44.27
6*
0.
2.
3.
5.
4.
5.
1.
6.
3.
1.
6.
1.
42.
^
54
13
82
72
64
50
75
02
17
24
73
56
82
Average0
0.
1.
2.
4.
4.
4.
0.
4.
1.
1.
5.
1.
32.
46
40
77
89
06
58
85
25
73
03
15
16
33
1965
Month
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
1
1. 15
0.75
0.55
1.80
4.85
2. 15
4.55
2.55
4.30
0.25
0.00
2.80
2
0.75
0.85
0.60
1.75
3.85
2.30
2.30
3.15
1.70
0.25
0.00
2.75
3
0.70
0.90
0.55
1.35
4.70
2. 10
3.95
2.10
3. 15
0.45
0.00
3.05
Gage
Number
4
1.
0.
0.
2.
3.
1.
4.
1.
4.
0.
0.
2.
15
85
50
00
95
30
55
60
00
00
00
95
5
0.85
0.85
0.60
1.85
3.90
1.75
2.95
4.40
2.60
0. 15
0.00
2.80
6
1.56
1.45
0.73
3.00
3.91
3.76
3.39
3.72
4.59
0.26
0.00
4.29
Average
6*
1.
1.
0.
2.
3.
3.
3.
3.
4.
0.
0.
4.
51
31
62
85
76
68
28
64
54
24
00
24
1.
1.
1.
2.
4.
2.
4.
2.
3.
0.
0.
3.
02
09
07
77
16
21
43
91
38
27
00
10
Total 25.70 20.25 23.00 22.85 22.70 30.66 29.67
26.41
290
-------
TABLE L-l--Continued
1966
Month
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Total
Month
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Gage Number
0
1
0
3
0
2
2
3
3
0
0
2
21
1
.50
.50
.50
.95
.40
. 10
.45
.40
.45
.90
.25
.40
.80
2
0.45
1.95
0.95
3.80
0. 95
2.65
2. 15
2.70
3.60
0.70
0.30
2.00
22.20
3
1. 50
2.05
0.70
3.55
0.50
1.85
4.00
3.20
3.15
1.35
0.35
2. 10
23.30
4
0.35
1.50
0.75
2.70
1.85
1.90
2.35
2.25
1.55
0.35
0.30
1.90
17.75
1967
5
0.55
2.00
0.80
2.65
0.90
3.30
1.85
4.05
4.60
0.90
0.80
2.05
24.45
6
0.69
2. 35
0.86
4.84
1.86
2.56
2.00
4. 59
2.68
1.39
0.51
2.53
26.86
Average
6*
0.
2.
0.
4.
1.
2.
1.
4.
2.
1.
0.
2.
25.
53
19
86
70
83
56
98
45
54
26
44
46
80
Gage Number
1
0
1
5
5
4
4
0
5
3
0
0
1
.45
.50
.30
.30
.50
.90
.90
.80
.20
.85
.75
.60
2
1.40
0.30
1. 15
3.95
5.30
4.70
4.05
1.10
5.80
3.20
0.65
0.25
3
1.20
0.40
1.05
4.00
6.25
4.20
5.35
0.80
6.70
3.15
0.80
0.25
4
1.20
0.65
1.50
5. 15
5. 10
1.90
2.65
0.45
5.40
3.35
0.80
0.20
5
1.75
0.30
1.20
5.00
5.65
4. 10
4.90
0.85
3.95
3.35
0.85
0.40
6
1. 51
0.65
1.42
5.09
5.34
4.60
6.88
0.57
4.89
3.75
1.09
1. 12
0.
1.
0.
3.
1.
2.
2.
3.
3.
0.
0.
2.
22.
48
87
74
56
07
39
46
34
15
91
41
15
53
Average
6*
1.
0.
1.
4.
5.
4.
6.
0.
3.
3.
1.
0.
51
45
09
41
34
53
76
34
80
74
06
76
1.
0.
1.
4.
5.
4.
4.
0.
5.
3.
0.
0.
42
44
25
69
52
07
77
73
14
39
79
37
Total 35.05 31.85 34.15 28.35 32.30 36.91 33.79
32.58
291
-------
TABLE L-l--Continued
1968
Month
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Total
Month
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Total
Gage Number
1
3.25
0.70
3.40
4.15
2.90
4.50
0.95
2.45
2.05
2.30
5.90
1.80
34.35
2
3.05
0.80
3.25
3.25
2.90
6.00
0.90
2.50
2.15
2.05
5.10
1.40
33.35
3
2.95
0.65
2.60
3.75
2.40
5.55
1.55
3.10
2.20
2.00
4.50
1.60
32.85
4
3. 10
0.95
3.05
3.55
2.20
3.90
2.15
2.55
1.45
2.60
5.80
1.80
33.10
1969
5
3.75
1.00
3.95
5.20
2.70
6.95
1.45
3.40
1.35
1.90
4.25
1.90
37.80
6
3.
1.
3.
4.
3.
4.
1.
1.
2.
2.
5.
2.
35.
26
08
49
40
56
08
37
90
80
64
19
01
78
Average
6*
2.
0.
3.
4.
3.
4.
1.
1.
2.
2.
5.
1.
34.
89
97
30
33
46
08
32
80
75
64
00
91
54
Gage Number
1
1.50
1.65
2.90
1.75
2.00
5.95
0.75
2.80
0.95
5.60
0.35
1.25
27.45
2
1.30
1.60
2.80
1.90
1.50
4.90
0.55
2.20
1.20
4.65
0.30
1. 10
24.00
3
1.60
1.65
2.75
2.15
1.25
6.85
0.85
2.85
1.00
5.30
0.45
1.25
27.95
4
1.35
1.45
2.95
1.60
1.95
6.30
0.80
1.95
1.05
5.65
0.20
1.10
26.35
5
1. 80
1.40
3.25
2.30
1.15
4.25
0.85
2.65
1.00
5.15
0.65
1.15
25.60
6
1.
1.
3.
1.
1.
6.
1.
3.
1.
5.
0.
1.
29.
63
34
25
56
98
40
03
24
67
86
32
62
90
3.
0.
3.
4.
2.
5.
1.
2.
1.
2.
5.
1.
34.
18
85
26
04
76
16
39
63
99
25
09
74
34
Average
6*
1.
1.
3.
1.
1.
6.
0.
3.
1.
5.
0.
1.
27.
42
28
03
35
81
28
98
24
51
83
00
25
98
1.
1.
2.
1.
1.
5.
0.
2.
1.
5.
0.
1.
26.
50
51
95
84
61
76
80
62
12
36
33
18-
56
Rainfall amounts in inches.
Adjusted values for Gage No. 6 obtained by deleting events
less than 0.2 inches.
•^
"Arithmetic average of Gages 1-5 and 6*.
292
-------
TABLE L-2
AVERAGE FREQUENCY OF RAINFALL EVENTS, TULSA, 'OKLAHOMA1
a, b, c
Month
Jan.
Feb.
Mar.
Apr.
May
June
July
N Aug.
•^ Sept.
\jJ
Oct.
Nov.
Dec.
Total
0. 01
to
0. 10d
4.2
3.8
3.8
4.6
4.4
3.2
2.2
3.6
3.6
1.0
3.0
3.6
41,0
0. 11
to
0.20
0.6
1.2
0.8
1.6
1. 0
0.8
1.4
1.2
0.4
0.6
0. 2
0.4
10,2
0.21
to
0.40
0.2
1. 2
0.6
2.6
2. 2
0.8
1.0
1.8
0.8
0.6
1.0
1.4
14.2
0.41
to
0.60
0.6
0.4
0.4
0.8
1.0
1. 2
0.6
0.0
1.0
0. 4
1.4
0.4
8.2
Rainfall Interval (Inches)
0.61 0.81 1.01 1.21
to to to to
0.80 1.00 1.20 1.40
0. 2
0.0
0.4
0.8
0.6
0.8
0. 2
0.2
0.4
0.6
0.4
0.2
4.8
0.6
0. 2
0.4
0.8
0.6
0. 2
0. 2
0.6
0.6
0.4
0.4
0.0
5.0
0.0
0.0
0.2
0.4
0. 2
0.4
0.6
0. 2
0.6
0.0
0. 0
0.2
2.8
0. 0
0.0
0.4
0. 0
0. 0
0.6
0.2
0.4
0.0
0.4
0.4
0. 2
2.6
1.41
to
1.60
0. 2
0. 0
0.0
0.0
0.4
0.0
0. 0
0.2
0.2
0.0
0.0
0.6
1.0
1.61
to
1.80
0. 2
0. 0
0. 0
0.2
0.0
0.4
0. 0
0. 0
0. 0
0.0
0.0
0.2
1.0
1. 81
to
2. 00
0. 0
0.0
0.0
0.0
0. 0
0. 2
0. 0
0. 2
0. 2
0. 0
0.0
0.0
0.6
>2. 00
0. 0
0.0
0. 0
0. 2
0. 2
0. 0
0.4
0.2
0.2
0.0
0.2
0. 2
1.6
Total
6.8
6.8
7. 0
12. 0
10.6
8.6
6.8
8.6
8. 0
4.0
7. 0
6.8
93. 0
Number of events per month falling within rainfall interval.
Five-year record (1964-1968). Source: Local Climatological Data, Tulsa Internationa Airport, Tulsa, Oklahoma.
cThe precipitation was considered to represent only one event if not more than two hours without precipitation
clasped between individual hourly events.
^Trace amounts and amounts equal to or less than 0. 01 were treated as no rainfall.
-------
TABLE L-3
AVERAGE MONTHLY RAINFALL AMOUNT OCCURRING WITHIN SPECIFIC RAINFALL INTERVALS*
Month
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Total
0.01
to
0. 10
0.21
0. 19
0. 19
0.23
0.22
0. 16
0.11
0. 18
0. 18
0.05
0. 15
0. 18
2. 05
0. 11
to
0. 20
0. 09
0. 18
0. 12
0.24
0. 15
0. 12
0.21
0. 18
0. 06
0.09
0.03
0.06
1.53
0. 21
to
0.40
0.06
0.36
0. 18
0.78
0.66
0.24
0. 30
0.54
0.24
0. 18
0.30
0.42
4.26
0.41
to
0.60
0.30
0.20
0.20
0.40
0.50
0.60
0.30
0.00
0.50
0.20
0.7-
0.20
4. 10
0.61
to
0.80
0. 14
0.00
0.28
0.56
0:42
0.56
0. 14
0. 14
0.28
0.42
0.28
0. 14
3.36
Rainfall
0. 81
to
1.00
0. 54
0. 18
0.36
0.72
0. 54
0. 18
0. 18
0.54
0. 54
0. 36
0.36
0.00
4,50
Interval
1.01
to
1, 20
0.00
0. 00
0. 22
0.44
0. 22
0.44
0.66
0.22
0.66
0.22
0.66
0. 22
3.96
(Inches)
1.21
to
1.40
0.00
0.00
0. 52
0.00
0.00
0.78
0.26
0. 52
0.00
0. 52
0.52
0.26
3.38
1.41
to
1.60
0. 30
0,00
0.00
0.00
0.60
0.00
0.00
0.30
0.30
0.00
0.00
0.00
1.50
1.61
to
1.80
0.34
0.00
0. 00
0.34
0.00
0.68
0.00
0.00
0.00
0.00
0.00
0.34
1.70
1.81
to
2.00
0. 00
0. 00
0. 00
0.00
0.00
0.38
0.00
0.38
0.38
0.00
0. 00
0. 00
1. 14
>2. 00
0. 00
0.00
0. 00
0.54
0. 54
0.00
1.08
0.54
0. 54
0. 00
0. 54
0. 54
4. 32
Total
1.98
1. 11
2.07
4.25
3.85
4. 14
3.24
3.54
3.68
2.04
3. 54
2.26
35.80
aThe rainfall amount for each interval is based on the average number of events per interval (from Table L-2) times
the average amount of the rainfall interval. For example, there are,on the average, 0. 6 precipitation events
between 0. 41 and 0. 60 inches during January. The average amount of the interval is 0. 50 inches.
average rainfall amount per interval is 0. 6 x 0. 50 in. = 0. 30 in. , which is the value listed above.
Therefore, the
-------
APPENDIX M
ANALYTICAL RESULTS
Table M-l presents the analytical results obtained from samples
collected during dry-weather flow. It should be noted that Test
Areas 9, 14, and 15 did not have any dry-weather flows on the days
indicated. The other twelve test areas exhibited small amounts of
flow at the sample collection times. These samples may be con-
sidered representative of water seepage into the storm drain system.
Analytical results for samples taken during periods of storm water
runoff are shown in Table M-2. Also included are data for the pre-
cipitation variables for each sample collected.
LEGEND FOR TABLES M-l AND M-2
Abbreviation
T. COL.
F. COL.
F. STREP.
BOD
COD
TOG
N
PO4
TOTAL
DS
YDS
SS
VSS
PH
CL
COND
TIME SINCE START
Units
number /ml
number/ml
number /ml
mg/1
mg/1
mg/1
mg/1
mg/1
mg/1
mg/1
mg/1
mg/1
mg/1
none
mg/1
micromhos/cm
hr.
Item
Total coliform
Fecal coliform
Fecal streptococcus
Biochemical oxygen demand
(5-days, 20°C)
Chemical oxygen demand
Total organic carbon
Organic Kjeldahl nitrogen
Soluble orthophosphate
Total solids
Dissolved solids
Volatile dissolved solids
Suspended solids
Volatile suspended solids
pH
Chloride
Specific conductance
The length of time from the
beginning of rainfall to the
start of the sample composite
period
295
-------
Abbreviation Units
ANT. AMOUNT in.
ANT. AVERAGE in. /hr.
INTENSITY
TIME SINCE ANT. hr.
EVENT
AMOUNT OF ANT. in.
EVENT
DURATION OF ANT. hr.
EVENT
AVERAGE INTENSITY in. /hr.
ANT. EVENT
API in.
Item
The amount of rainfall accu-
mulated from the start of
rainfall to the start of the
sample period
The average intensity pre-
ceding sample collection
The time elapsed since the
last measurable precipi-
tation event
The total precipitation of the
antecedent event
The duration of the antece-
dent event
The average intensity of the
antecedent event
Antecedent precipitation
index
296
-------
TABLE M-l
ANALYTICAL RESULTS OF BASELINE SAMPLESa
TEST
AREA DATE
NO.
1 2-11
3-12
6-H
7-30
2 3-12
3 2-11
3-12
6-11
7-30
4 2-11
3-12
6-11
7-30
5 2-11
3-12
6 2-11
3-12
6-11
7-30
7 3-12
6-11
7-30
8 6-11
7-30
10 3-12
7-30
11 2-11
3-12
7-30
12 2-11
3-12
6-11
7-30
13 2-11
3-12
6-11
DAYS
SINCE
LAST
PREC.
EVENT
11
4
2
35
7
11
4
2
35
11
7
2
35
11
7
11
7
2
35
7
2
35
2
35
7
35
11
7
35
11
4
2
35
11
7
2
BACTERIOLOGICAL ORGANIC
(number /ml) (mg/1)
T. COL. F. COL. F. STREP. BOD COD TOG
20
0
0
50
125
0
0
10
0
0
35
500
200
100
170
500
680
800
350
240
830
650
250
5,900
0
1, 100
100
270
2,900
400
15
190
0
100
0
4,000
0
0
4
2
0
0
0
8
1
0
0
25
0
0
0
0
0
80
0
0
70
37
13
52
0
5
0
0
2
0
0
10
0
0
0
130
0
0
78
0
0
0
0
170
0
0
0
165
150
0
0
5
0
160
0
0
420
10
140
2,900
0
10
0
0
20
0
0
2,000
0
0
0
800
2
5
3
10
2
0
3
1-
3
3
4
1
3
1
2
2
6
1
6
2
2
36
5
17
0
10
0
0
20
0
0
2, 000
0
1
3
1
24
28
34
90
12
8
44
13
31
20
20
50
15
6
8
26
24
30
30
20
3
116
52
97
20
18
19
52
7
16
24
40
10
8
12
10
7
11
6
n. d.
4
10
8
6
n. d.
40
9
2
n. d.
5
7
10
17
0
n. d.
3
0
n. d.
16
n. d.
10
n. d.
14
14
n. d.
15
16
4
n. d.
6
5
1
NUTRIENT
(mg/1)
N P04
0.28
0.35
0.00
0.97
0.42
0. 14
0.28
0.00
0.24
0.28
0.35
0.00
0.22
0.49
0.20
0.00
0.49
0.03
2.53
0.28
0.01
0.85
0.00
0.53
0.28
0.39
0.14
0.91
0.86
0.28
0.28
0.00
0.49
0.00
0. 14
0.08
1.00
1.00
1. 02
0.60
0.40
0.05
0.00
0. 10
0.02
0.90
0.20
0.82
0.82
0.05
0. 10
0.72
0.30
1.50
4.40
0.60
0.55
0.90
1.06
0.62
0.30
0.60
1.88
0.60
2. 11
0. 18
0.00
0.32
0.68
0. 10
0.00
0.87
TOTAL
240
360
380
528
528
76
328
432
560
1068
856
1480
2128
440
228
520
500
364
668
904
868
968
636
568
268
1124
588
680
436
320
416
124
276
212
444
292
SOLIDS
(mg/1)
DS VDS
240
360
372
488
528
76
300
388
512
1060
852
1468
2108
420
228
520
500
344
648
880
820
924
632
544
260
500
568
480
424
320
408
108
276
212
440
260
60
128
240
136
160
24
300
168
252
200
200
384
844
60
120
100
148
204
240
208
292
320
208
268
132
160
88
12
240
40
140
20
214
40
88
76
SS VSS
0 60
0 128
8 240
40 136
0 160
0 24
0 300
44 168
48 252
8 200
4 200
12 384
20 844
20 60
0 120
0 0
0 0
20 20
20 16
24 12
48 44
44 22
4 4
24 24
8 0
624 96
20 12
200 72
12 12
0 0
8 0
16 16
0 0
0 0
4 0
32 32
OTHER
PH CL COND
7. 2 n. d. n. d.
8.5 38 328
8.6 25 255
9. 1 50 300
8.5 35 417
7.3 n. d. n. d.
8. 0 29 348
8.0 32 292
8.0 74 316
7.5 n. d. n. d.
8.0 37 682
8. 1 63 643
7. 9 77 675
7.2 n. d. n.d.
8.3 9 154
7.3 n. d n. d.
8.0 50 306
8.1 50 411
8. 1 65 387
8.6 118 537
7.9 112 511
7.5 110 512
7.6 33 238
7. 6 36 282
8.0 32 216
7.9 55 304
7. 1 n. d. n. d.
8. 0 43 420
7.9 15 218
7. 0 n. d. n. d.
8.0 41 358
7.4 11 140
7. 9 10 121
7.3 n.d. n.d.
8.6 25 223
7.5 24 226
> data
297
-------
TABLE M-2
ANALYTICAL RESULTS OF STORM WATER RUNOFF SAMPLES
TEST AREA NO. 1
DATE TIME
00
100568
100568
100568
100568
100568
100568
100968
100968
100968
100968
100968
100968
101668
101668
101668
101668
101668
101668
101668
22069
220«9
22069
J2364
32369
50669
5076
51Sb
60 lib
6126
6176
6236
6246
7316
73169
81469
81469
915
945
1015
1045
1115
1130
665
710
725
740
755
810
1855
1910
1525
1940
1955
2010
2025
1350
1355
16)0
!45
1350
2330
115
2015
2100
520
1200
2350
1225
60U
755
BIO
1025
BACTERIOLOGICAL
NUMBER/ML
T, COL. F.COL. F.
*•«*«•* «*•«
332 ••**
50 *•*•
20 •«••
ii «•••
50 ****
21 ••«•
ao *••*
35 *•«•
10 •**•
25 «•*•
45 ****
0 0
75 0
275 0
100 a
ao i
11430 2
4380 »»•«
4CO 0
20000 250
1000 350
3750 150
3500 700
till 50
5JO 150
2300 200
700 40
STREP. BUD
320 7
413 21
4'5 9
211 V
21 34
11 17
13 23
7 19
10 21
15 23
2 20
0 6
10 5
0 3
U i
360 22
127 16
O 5
7750 12
250 11
250 16
750 U
0 19
130 V
1100 11
100 26
ORGANIC
KG/1
COO TOO
132 64
44 35
36 87
62 27
02 27
180 64
54 35
114 44
64 17
213 5»
73 28
130 «*•
62 24
85 «••
184 *»•
NUTRIENT
N&/L
N P04
2.24
1.40
1.40
2.24
2.24
0.14
2.38
0.2D
O.U6
0.42
1.77 1
0.51
0.4t>
0.19
0.51
0.64
.90
.19
.10
.90
.90
.10
.80
.42
.02
.20
.10
.8d
.95
.00
1.10
1.83
TOTAL
948
3164
2172
1920
1672
2608
2792
2292
1300
1924
2084
992
664
640
1400
1400
164
1312
352
5oua
. 944
5812
1180
1796
848
200
1020
SOLIDS
HG/L
OS VOS
236 78
172 72
BO 40
40 28
48 28
40 20
140 60
272 96
460 220
111 140
160 92
168 108
180 72
32 12
192 72
160 88
100 60
100 60
140 52
144 «•«*
284 164
192 80
220 100
276 144
108 24
236 180
320 244
272 248
60 44
232 124
SS
312
2992
2092
1880
1624
1336
4908
2332
2332
1820
1140
1756
1904
960
472
480
1300
1300
24
1168
68
6376
4868
668
5704
994
1476
576
140
768
VSS PH
96 9.4
1100 10.4
292 8.9
304 8.6
224 a. 5
276 8.*
836 11.2
456 11.8
620 12.2
500 12.0
240 11.4
300 10.7
290 9. B
184 9.3
48 7.1
60 1.3
260 7. B
260 7.8
16 7.3
200 8.8
64 7.1
660 8.1
736 a. 2
120 7.7
576 8.2
148 7.5
200 8.9
104 8.2
36 7.8
166 7.2
TIME
OTMEfl SINCE
NS/L • SHUT
CL CONO (HRSI
14 2.4
8 2.7
a 2.9
71 3.2
71 3.4
71 3.7
14 4.9
38 5.2
7 5.4
14 5.7
14 5.9
17 6,2
14 b.4
14 18 6.8
10 17 6.9
0 16 9.5
4 9 12.8
4 9 16.8
11 14 1.5
5 129 3.3
21 168 2.3
5 68 1.3
5 96 1.6
I 129 4.5
4 92 1.3
8 120 1.1
4 63 3. B
4 83 5.7
4 77 5.8
9 163 ft.O
ANT.
AftUUNT
(IN.)
0.31
0.44
0.60
0.80
0.94
0.59
0.60
0.60
0.60
0.60
O.bO
0.34
0.35
0.35
0.35
0.35
0.35
0.35
0.53
0.54
O.60
1.41
2.25
0.03
0.22
O.Ctl
3.35
0.10
0.35
0.65
0.25
0.65
0.85
0.10
0.70
ANT
AVERA
INTENS
(1N./H
0.13
0.16
0.18
0.21
0.22
0.25
0.22
0.21
0.19
0.18
0.16
0.07
0.07
0.06
0.06
0.06
0.06
0.05
0.08
0.08
0.06
0.11
0.13
0.02
0.07
0.03
0.27
0.06
0.00
0.50
o.or
0.17
0.1S
0.12
0.09
TIME AMOUNT DURATION AVERAGE
SINCE OF ANT OF ANT. INTENSITY API
NT. EVENT EVENT EVENT ANT. EVENT
(HRS.J (IN.I (HRS.I IIN./HH.I
265.
265.
265.
265.
265.
265.
58.
i*.
5tt.
58.
56.
58.
163.
163.
163.
163.
163.
163.
163.
110.
110.
110.
742.
742.
53.
53.
169.
181.
80.
72.
156.
9.
25t>.
256.
336.
336.
1.05
1.05
1.05
1.05
1.05
1.05
1.00
1.00
1.00
1.00
1.00
1.00
0.70
11.70
0.70
0.70
0.70
O.TO
0.70
0.45
0.45
0.45
0.40
0.40
0.30
0.30
0.25
1.20
0.35
O.BO
0.35
0.65
0.20
0.20
U.B5
0.85
9.00
9.00
V.OO
9.00
9.00
9.00
4.50
4.50
4.50
4.50
4.50
4.50
2.50
2.50
2.50
2.50
2.50
2.5U
2.50
26.00
26.00
26.00
12.00
12.00
1.00
1.00
0.75
4.25
0.50
3.50
3.50
1.00
0.50
0.50
5.00
5.00
0.12
0.12
0.12
0.12
0.12
0.12
0.22
0.22
0.22
0.22
0.22
0.22
0,28
0.28
0.28
0.28
0.28
0.28
0.28
0,02
0.02
0.02
0.03
0.03
0.30
0.30
0.33
C.2U
0.70
0.26
0.10
0.65
0.40
0.40
0.17
0.17
0.85
0.89
0.85
0.85
0.85
0.85
1.30
1.30
1.30
1.30
1.30
1.30
1.10
1.10
1.10
1.10
1.10
1.10
1.10
0.40
0.40
0.40
0.40
0.40
0.45
0.45
0.60
1.05
1.10
2.80
l.ao
2.40
0.10
0.10
0.25
0.25
* HICHOMhCS/LN
•••» NU CATA
-------
TABLE M-2 — Continued
TEST AREA NO. 2
DO
UATE TIME
T.
100966 610
10096S 625
101669 1U10
10166 1825
10166 1^40
10166 1955
10166 2U1C
10166 2C25
10166 2140
22C6 1315
2206 1335
2206 1415
3236 100C
3236 HOC
3236 12CO
5076 15
50769 250
51569 2030
6U69 121',
6M69 1CC5
73169 545
73104 B1C
81469 740
81569 730
81569 S25
• MICRLMH_S/C«
***« NU L-'dfA
OAC7EMUIUGKAI UKuANlC NUTRIENT SOLIDS
NUM tR/ML MG/L MO/L HG/L
CIA. F CUL. F.$fH£P. d(ll> CUd TUC N Plj4 7U7A1. OS VOS SS VSS PH
111 40 7 ... .... ».. 176 6d 12 108 36 6.2
**• 2* 4 ... .... ... [52 69 3(> S4 8 8.1
««• 13 4 «* . ..«. *.. 96 28 »*»» 68 56 8.0
**. 43 5 .4 * *.*. *** i^j j£ ^4 4y 24 g^ j
*** 5 3 ... .... ... 154 no 10 44 20 8.1
*** 05**. .... ... 136 9i 30 38 19 7.9
... ******* 4 ** * ***« *.* J3g 34 46 54 4 7^ j
97 30 6 53 2 0.30 0.40 168 92 72 V6 2* 7.4
62 5 / 53 3 C.90 0.60 244 104 56 140 60 7.4
125 2 6 5J 1 C.^0 0.60 220 100 40 120 60 7.4
200 C 2 22 I 1.6B 1.00 280 40 20 240 60 7.4
100 0 2 24 1 1.41 1.J5 660 40 12 620 60 7.5
•>0 0 2 24 1 1.20 1.35 600 60 20 540 40 7,2
428C 160 12 52 2 2.84 O./O 120 92 2fl 28 0 7.4
42HO 40 11 20 1 0.70 O.UO 172 60 20 112 24 7.0
1500 105 C 8 OH 2 0.22 1.29 332 212 172 120 10» 7.4
BOIO 1700 0 7 46 1 0.74 0.80 560 164 JOS 396 64 7.3
250 20U 25C 6 27 . 0.60 0.25 216 2C4 176 12 12 7.3
600 40 100 12 94 * 3.61 1.50 152 100 6« 52 4 6.8
200 100 4400 2 36 * 0.28 0.90 12S 72 7Z 56 16 7.1
OTHER
MC/L
CL
71
71
71
10
7
7
7
7
7
7
4
5
6
2
2
2
6
4
4
3
5
5
2
2
*
CONP
91
116
122
67
59
69
95
67
74
92
56
76
116
48
44
IlHt
MNCb
STAKT
(HKSI
1 .9
2.2
2 .4
4.4
5.7
5.-,
6.2
6.4
0.7
6.3
6,6
T.3
13.0
14.0
15.0
2.3
4.
5.
0.
6.2
5.7
3.5
5.4
l.vf.
AMOUNT
I liM. 1
0.53
0.56
0.60
d.il
0.29
0.35
0.35
0.35
0.35
0.35
0.51
J.53
0.53
1.35
1.65
1,75
J.Cd
0.41
0.28
0.40
0.25
0.85
0.25
1.23
2. 52
AI»T.
AVERAGE
INTbNS t [r
1 IN./HK. )
0.25
0.25
0.06
0.07
0.1,6
0.06
0.06
O.C5
0.05
u.CB
O.Od
0.08
0.10
O.U
0.12
0.03
0.22
U.06
0.31
0. 14
0.04
0.35
0.47
TIMf
SINCE
INT. EVCiV
IHKS.J
1C).
10).
1C).
163.
163.
16).
163.
16).
163.
16).
772.
?72.
772.
)75.
375.
375.
53.
53.
5 74 .
71.
10.
259.
256.
336.
20.
20.
AHOUN7
OF- ANT
• ttftflT
1 .00
1.00
1.00
U.70
u.70
0.70
0. Id
0.70
o.ro
0.70
0.40
a. 40
0.40
u.ll
0.11
0.11
0.30
0.30
0.25
L.40
1.20
0.15
U.15
O.dl
0.25
OUHAI 1UN
OF AKit.
E VEfcf
4HRS.1
3. 75
3.75
3.75
2. 50
2.50
2.50
2)50
8.50
8.50
1.00
1.00
1.00
1.00
1.00
1*58
3.50
1.75
1.00
I.JO
4.50
C.75
0. /5
AVERAGE
INTENSITY
ANT. tVtft7
1 IN./HR.I
0.27
0.27
0,27
0.28
0.28
0.2«
0.28
0.26
0.28
0.05
0.05
0.05
0.11
0.11
0.11
0.30
0.30
0* 16
0.69
0.15
0.15
0.18
0.33
0.33
API
1 30
U30
1.30
1.10
I. 10
1. 10
1. 10
1. 10
1. 10
1. 10
0*40
0.40
0.40
0.40
0.40
U.40
0.45
0* 60
2.40
0. 10
U.JO
0.25
0.45
0,45
-------
TABLE M-2 — Continued
TEST AREA NO. 3
8ACTER1ULUCICAI
NUMBER/XL
T. CUL. F.COL. F.STKEP.
ORGANIC NJTK1ENT
HG/L Hti/L
COO 7OC N P04
SOi. I OS
HC/L
VOS
o
O
92368 2100
92368 2130
92368 2200
92369 2230
92368 2330
100968 550
100968 605
100968 620
100968 635
101668 1840
101668 1855
1016C8 1910
101668 1940
JOUtS 1555
22069 1330
22C69 1410
22069 1450
22069 1530
32369 1000
12369 1400
41369 1000
41369 1200
41069 2330
41769 130
50669 2345
50769 130
51569 2130
52469 2005
60869 2015
61369 2030
61369 2110
61369 2150
62369 2300
62469 1105
62469 20
62469 140
73169 445
73169 545
73169 645
91469 715
61469 800
50
30
10
30
10
50
53
25
50
0
25
70
70
360
160
480
360
10000
6000
7550
200
137500
2COOOO
132500
5500
4750
5750
6000
4000
1800
750
2000
700
**•»
****
0
0
0
0
i
i
0
0
4
32
53
33
»***
20
750
1700
1500
1750
50
500
1050
50
0
50
100
640
30
50
30
20
0
560
1665
1873
0
0
1
0
27
150
2
5
2
0
0
60
85
100
23
920
411
343
60
250
1000
750
1500
2750
3250
3250
3600
3800
1400
650
450
4
3
3
4
4
3
3
3
5
4
1
4
2
2
9
5
9
8
18
11
12
5
4
2
4
15
9
12
12
10
7
7
22
20
52
40
36
36
28
12
100
64
72
92
104
36
39
9
136
58
61
42
117
51
82
59
60
il
33
Id6
137
20
18
21
22
18
18
28
17
31
**»
32
2o
31
0
11
15
21
20
18
38
19
32
22
18
18
22
***
***
0.98
0.84
0.70
0.84
1.26
1.33
4.41
2.80
3.64
2.87
3.T8
3.78
0.45
0.20
0.17
l.UO
0.98
0.80
0.90
1.67
0.72
1.62
1.69
0.22
0.29
0.20
0.67
1.13
0.60
0.60
0.65
0.60
1.78
1.25
4.80
3.60
2.60
2.40
2.10
2.80
1.30
0.10
0.10
2.36
2.15
2.64
2.68
3.02
2.12
3.02
3.02
0.92
0.78
0.74
1.05
1.04
108
72
56
68
46
192
198
160
120
205
136
126
128
212
160
224
180
380
400
,396
180
556
312
452
2T2
264
1052
788
520
412
3760
296
952
424
552
312
168
B04
416
60
40
32
48
32
80
go
68
40
116
88
1i
96
92
80
112
120
90
80
232
140
160
160
136
80
144
180
72
164
164
236
240
240
120
172
272
120
BO
300
32
B
12
40
24
40
12
24
28
54
22
38
30
32
20
104
48
20
20
84
40
68
72
64
20
48
88
16
112
60
108
180
196
76
140
256
112
0
168
48
32
24
20
16
112
116
92
80
89
48
28
32
120
60
112
60
300
320
164
40
396
152
316
192
120
872
716
460
248
3524
56
712
304
360
40
48
724
116
24
28
8
16
4
64
56
48
24
16
26
2
2
20
12
16
12
60
80
64
20
56
48
120
56
36
136
136
60
136
260
24
172
64
96
20
16
32
32
7.2
7.2
7.2
7.2
7.2
7.1
1.2
7.2
7.2
8.0
8.0
7.9
7.9
7.9
7.4
7.4
7.3
7.1
7.3
7.2
7.2
7.2
7.2
7.2
6.7
6.8
7.0
8.2
7.3
7.1
7.1
7.0
7.3
7.3
7.2
7.1
7.2
7.2
7.1
7.0
7.0
15
15
15
15
19
71
71
Tl
Tl
7
7
7
7
7
7
6 I
5 1
7 1
7 1
3
3
14 1
T I
6 1
6
8 1
4 1
9 1
30 2
30 2
5 1
1
1
10 1
7 1
4
4
4
11 1
15 1
0.0
0.5
1 .C
1.5
2.9
1.3
1.6
1.8
2.1
4.4
4.7
4.9
5.4
5.7
5.8
15 6.5
7 7.2
il 7,4
!T 8.5
it 13.0
70 17.0
13 8.5
t2 10.5
19 1,8
)6 3.8
14 1.8
3 3.5
19 3.5
99 0.3
18 1.6
38 0.5
S9 0.3
77 0.9
)C 1.6
13 0.5
12 2.3
>« 1.6
1 3.2
>5 2.5
IT 3.5
b3 4.5
10 4.8
)2 5.6
OTHEK
PH
I.I
7.2
7.2
7.2
T.2
7.2
7.1
1.2
7.2
7.2
8.0
8.0
7.9
7.9
T.9
7.4
7.4
7.3
7.1
7.3
7.2
7.2
7.2
7.2
7.2
7.2
6.7
6.8
7.0
7.9
9.2
7.3
7.2
7.1
7.1
7.0
7.3
7.3
7.2
7.1
7.2
7.2
7.1
7.0
7.0
MG/L
TIME
SINCE
' iTA
RT
ANT.
AMOUNT
11N.I
CL CQNO (HRS1
1>
15
15
15
15
19
71
71
Tl
71
7
7
'
7
,
6 I
5 1
7 1
7 1
3
3
14 1
7 1
7 I
6 1
6
6 1
4 1
0
0
1
1
2
2
1
1
1
2
4
4
4
5
5
5
15 6
7 7
it 7
IT 8
it 13
70 17
13 8
tO 9
t2 10
19 1
»6 3
14 1
3 J
9 139 3
29 296 0
30 2
5 1
1
1
1
10 1
7 1
4
4
4
11 1
)6 1
38 0
12 1
>9 0
77 0
)C 1
13 0
JZ 2
>e i
1 3
k3 2
17 3
b3 4
10 4
15 192 5
.0
.5
.c
.5
.0
.5
.3
.6
• 8
.1
.4
.7
.9
.2
.4
.8
.5
.2
,8
.5
.0
.0
.5
.5
.5
.8
.8
.8
.5
.5
.9
.6
.5
,B
.3
.9
.6
.5
.3
.6
.2
.5
.5
.5
.8
.6
0.0
0.13
0.25
0.33
0.40
0.45
0.35
0.46
0.50
0.53
0.24
0.25
0.25
0.25
0.25
0.25
0.25
0.48
0.56
J.59
0.60
1.45
2.35
0.30
0.40
0.50
0.35
a. ia
0.04
J.26
0.10
0.22
0.25
0.31
0.3*
0.25
0.51
0.54
0.65
0.25
0.65
0.65
0.53
0.63
0.80
0.63
0.70
ANI.
AVEKAGt
INTENSITY
1 1N./HH. 1
0.0
0.26
0.25
0.22
C.20
0.18
0.26
0.29
0.28
0.25
0.05
0.05
0.05
0.05
0.05
0*04
0.04
0.07
0.08
0.08
0.07
0.11
0.14
0.04
0.04
0.05
0.19
0.24
0.02
0.07
0.03
o!24
C.16
0.62
0.19
0.83
0.57
C.34
1.30
0.11
C.36
0.20
0.21
0.18
0.18
0.13
O.U
TIME
SINCE
>NT. EVEN
IHRS.I
34.
34.
34.
34.
34.
34.
58.
*8.
58.
58.
163.
163.
163.
163.
163.
163 .
163.
110.
110.
110.
110.
742.
742.
467.
467.
467.
82.
82.
79.
79.
169.
121
12.
181.
lei.
40.
40.
40.
156.
9.
156.
156.
256.
256.
256.
336.
336.
AHOUN7
OF ANT
T EVENT
UN.I
0.25
0.25
0.25
0.25
0.25
0.25
I. 00
i.oo
1.00
1.00
0.70
0.70
0.70
0. 70
0.70
0. 70
0.70
0.45
0.45
0.45
0.45
0.40
0.40
3.00
3.00
3.00
0.50
0.50
0.25
0.25
0.25
o.'zo
0.20
1.20
1.20
o. in
0.10
0.10
0.35
0.65
0.35
0.35
0.20
0.20
0.20
0.85
0.83
DURATION AVERAGE
OF ANT. INTENSITY
EVENT
(HRS.I
0.75
o.rs
0.75
0.75
0.75
0.75
4.50
4.50
4.50
4.50
2.50
2.50
Z.50
2.50
2.50
2. 50
2.50
26.00
26.00
26.00
26.00
12.00
12.00
29.00
29.00
2V. 00
10.25
10.25
0.25
0.25
0.75
1. 50
1.50
1.50
4.25
4.25
1.00
1.00
1.00
3.50
1.00
3.50
3.50
0.50
0.50
0.50
5.00
9.00
ANT.
UN.
0
0
0
0
0
0
a
0
a
0
0
0
0
0
0
(
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
c
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
EVENT
/HR.I
.33
.33
.33
.33
.33
.33
.22
.22
.22
.22
.28
.28
.28
. 28
.28
.26
.28
.02
.02
.02
.02
.03
.03
.10
.10
.10
.05
.05
.00
.00
.33
.'u
.13
.28
.28
.10
.10
.10
.10
.65
.10
.10
.40
.40
.40
.17
.17
API
0.1S
a. 15
0.15
0.15
0.15
0.15
1.30
1.30
1.30
1.30
1.10
1.10
1.10
1.10
1.10
1.10
1.10
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.70
0.70
0.45
0.45
0.60
0.'60
0.60
1.09
1.05
1.7S
1.75
1.75
l.BO
2.40
1.80
1.60
0.10
0.10
0.10
0.25
0.25
• MCKGMI-CS/CN
•••• NO CATA
-------
TABLE M-2 — Continued
TEST AREA NO. 4
BACTERIOLOGICAL OHCAN1C
DATE TIHt NU«atK/ML MG/L
T. COL. F.COl. F.STREP. BCD COD TOC
NUTRIENT
HG/L
N PU4 TOTAL
SOLIDS
HG/L
VDS
TIME ANT. ANT. TIME AMOUNT DURATION AVERAGE
OTHER SINCE AMOUNT AVERAliE SINCE OF ANT OF ANT. INTENSITY API
HG/L • START I IN.) INTENSITY ANT. EVENT EVENT EVENT ANT. EVENT
PH CL CONO IHHSI (IN./HK.J (HSS.f (IN.I (HRS.I IIN./HR.I
110268 1445
110268 1515
110268 1545
110268 1615
110268 1(45
111068 1030
111068 1100
111068 1130
111568 130
111568 145
111568 215
1115(8 245
112668 1210
112668 1220
1126(8 1250
1126(8 1320
112668 1350
, 1126(8 1420
W 112668 1450
O 121868 1325
,_, 121868 I34U
121868 1355
i2iaea i4ic
121868 1429
122768 630
122768 «CC
122768 730
11569 600
11569 620
11569 640
11569 700
11569 720
11569 740
22069 2130
41369 500
41369 530
41369 630
50769 45
50769 225
51569 2105
60969 2045
61269 445
73169 530
8156V 755
81569 940
4400000
5000000
*******
*******
*******
160
600
440
3280
360C
3200
3880
2360
1840
1160
4080
3400
40
720
1480
120
aao
480
600
0
1700
20
280
400
720
160
640
440
125
750
3500
5000
8000
12000
7290
0
10000
2500
0
0
60
80
40
120
60
0
0
0
0
7
0
0
0
0
0
5
0
0
0
0
c
0
0
0
0
0
0
0
0
0
0
0
0
0
3
11
9
4
4
**«*
0
250
300
40
100
* HICRGMI-CS/CH
• *»• NO CATA
20
BO
40
0
40
70
120
130
30
ISO
8C
9Q
40
60
10
ao
310
0
100
70
5
30
25
90
10
10
20
35
65
15
27
80
140
200
280
10
lib
4500
250
2iOC
2300
16
8
10
9
29
16
11
16
16
13
10
27
31
38
32
9
10
7
3
5
13
4
5
29
27
25
19
18
17
4
25
25
25
21
8
IB
8
8
5
3
50
76
68
64
64
72
104
104
»2
V2
196
124
116
I ft,
132
160
IBt.
4b
86
296
192
180
144
176
212
112
60
76
36
240
236
220
92
48
14
120
52
39
61
66
**+
* + *
«*«
32
27
27
34
74
63
75
58
41
58
40
63
41
23
26
59
59
71
55
41
28
15
74
72
77
46
24
26
27
22
21
***
***
0.70
0.70
0.63
1.12
1.12
o.va
0.98
1.20
1.20
1.20
1.20
0.0
0.0
3.00
0.0
3.00
1.00
1.61
3.36
2.V4
2.80
3.22
1.40
0.12
0.0
0.38
0.18
0.19
0.25
0.70
0.70
0.70
1.55
1.55
1.00
1.00
0.55
0.55
0.55
0.55
4.00
2.00
1.00
1.00
1.00
1.00
0.30
3.80
2.80
2.40
1.30
0.60
0.80
0.96
0.64
0.36
0.46
0.77
402
299
280
265
654
164
220
983
594
411
384
640
820
408
520
420
420
440
1092
384
447
1244
1168
812
606
368
848
1050
740
1304
424
176
744
564
468
828
1052
236
224
222
187
568
134
162
733
326
134
124
280
172
160
200
168
180
200
218
238
250
518
654
462
348
320
328
492
400
928
208
148
96
196
284
356
124
66
68
90
64
190
78
80
140
60
26
32
80
52
40
100
80
80
80
88
14
46
114
94
72
118
132
64
120
88
180
48
20
40
. 76
244
120
80
166
75
58
78
86
30
58
250
268
277
260
360
648
148
320
252
240
240
847
146
197
726
514
350
258
48
520
560
340
376
216
176
648
360
184
472
928
18
3
6
8
4
6
0
4
28
20
24
200
440
128
232
132
108
80
130
58
33
114
94
112
54
8
192
156
92
176
76
17
156
44
32
80
88
7.2
7.3
7.6
7.4
7.3
7.4
.5
.1
.3
.4
.6
.5
.4
7.5
7.9
8.0
7.
7.
7.
7.
1.
7.
7.3
7.3
7.3
7.5
7.5
7.2
7.3
7.3
7.0
7.2
7.2
7.8
a. i
7.5
7.4
7.7
17
10
10
10
3
3
3
**«
*«*
***
***
«
*»* *
11 1
9 1
9 1
9 1
7 I
11 1
18 1
40 3
41 4
55 3
45 2
37 2
48 2
30 3
9 2
14 3
13 2
25 6
5 1
4 1
4
5
3
3
3
3.0
3.5
4.0
4.5
1.8
2.3
2.8
2.3
2.5
3.C
3.5
1.8
2.3
»• 4.3
10 1.4
57 1.7
57 1.9
13 2.2
SI 4.5
74 b.O
S4 5.5
14 0.0
D3 0.3
10 0.7
51 1.0
!8 1.3
14 1.7
Dl 14.5
!5 3.3
30 3.8
99 4.8
94 2.8
10 4.4
!4 1.8
94 3.3
95 2.0
76 3.5
71 3,9
n 5.7
0.81
C.81
0.81
0.81
0.15
0.20
0.25
0.20
0.25
0.39
0.56
0.12
0.14
0.15
0.17
0.19
0.21
0.22
0.24
0.24
0.73
0.75
0.75
O.C
0.03
0.07
0.10
0.12
0.13
0.65
0.20
0.23
0.26
0.15
0.37
0.30
0.55
0.45
C.48
1.33
2.55
0.2T
0.23
0.20
0.16
0.16
0.08
0,09
0.09
0.09
0.10
0.13
0.16
O.Ob
0.07
O.Ob
0.05
0.05
0.05
0.04
0.15
0.13
0.13
0.11
0.10
0.16
0.13
0.14
0.0
0.10
0.10
0.10
0.09
0.08
0.04
C.06
O.Ob
0.05
0.05
0.06
0.17
0.17
0.23
0.14
0.34
C.45
3S9.
39».
399.
398.
398,
175,
175.
175.
80.
UO.
80.
BO.
259.
259.
259.
259.
259.
259.
259.
511.
511.
511.
511.
511.
124.
124.
124.
457.
457.
457.
457.
457.
457.
772.
470.
470.
470.
53.
53.
574.
180.
69.
256.
20.
20.
0.35
0.35
0.35
0.35
0.35
0.30
0.30
0.30
0.50
0.50
0.50
0.50
0.25
0.25
O.J5
0.25
0.25
0.25
0.25
0.71
0.71
o.ri
0.71
0.71
0.14
0.14
0.14
1.10
1.10
1.10
1.10
1.10
1.10
0.40
2.75
2.75
2.75
0.30
0.30
0.25
1.25
0.55
0.15
0.25
0.25
4.30
4.30
4.30
4.30
4.30
2.75
2.75
2.75
6.00
6.00
6.00
6.00
8.50
8.50
8.50
8.50
8.50
8.50
B. 50
9.00
9.00
9.00
9.00
9.00
2.00
2.00
2.00
3.25
3.25
3.25
3.25
3.25
3.25
8. SO
27.00
27.00
27.00
1.00
1.00
1.56
2.75
12.00
1.00
0.75
0.75
0.08
0.08
o.oe
o.oe
o.oe
0.11
0.11
0.11
0.08
0.08
o.oe
0.08
0.03
0.03
0.03
0.03
0.03
0.03
0.03
O.OB
o.oe
o.oa
o.oe
o.oe
0.07
0.07
0.07
0.34
0.34
0.34
0.34
0.34
0.34
0.05
0.10
0.10
0.10
0.30
0.30
0.16
0.46
0.05
0.15
0.33
0.33
0.35
0.35
0.35
0.35
0.35
1.05
1.05
1.05
1.10
1.10
1.10
1.10
0.90
0.90
0.90
0.90
0.90
0.90
0.90
0.30
0.30
0.30
0.30
0.30
0.50
0.50
0.50
0.30
0.30
0.30
0.30
0.30
0.30
0.40
0.40
0.40
0.40
0.45
0.45
0.60
1.05
1.10
0.10
0.45
0.45
-------
TABLE M-2 — Continued
TEST AREA NO. 5
UAH TIME NUMBER/ML
t. CCL. F.COL. F.STREP,
UKbANIC
000 COO IOC
MWL
N PD4
SOLIDS
HC/L
OS VOS
TIMC ANT. INT. TIKE AMOUNT DURATION AVERAGE
OTHER SINCt AHUUNT AVERAit SINCE LF ANT UF ANT. INTENSITY API
MG/L • START I IN.I INTENSITY ANT. EVENT EVENT tVEM AMI. EVENT
PH CL CONO IHRSI UN./MR.I (HRS.I ([N.I ChRi.1 IIN./HR.I
to
O
to
1110(6 449
111068 1C19
111068 1049
111066 1115
111066 1149
11IC68 1215
111068 1249
111S(8 130
111968 145
111568 200
1119(8 215
111568 230
111568 2«5
1115(8 JOC
112666 16iO
1126(6 HOC
112668 1730
112668 iaoc
112668 1630
1126(8 IV JO
1126(8 1910
121868 1240
121868 1259
121668 1310
121868 1329
1218(8 1340
1218(8 1455
122768 230
1227(6 245
1227(8 300
122766 319
122768 330
1227(6 349
1227(8 4CO
1227(8 840
41769 150
41769 221)
41769 250
61369 2110
61369 2190
61369 2230
61769 1130
62469 949
73169 43C
81469 190
81469 250
81469 350
81469 845
81569 410
81969 1045
660
120
1280
4CC
480
5»C
120
404J
J660
J200
3/eC
3200
3840
280U
80
160
120
80
160
0
8U
2200
«0
C
40
0
0
3000
4020
3560
9120
3600
30oO
3440
3200
*******
*******
180
215000
225CO
40000
750
9250
40003
*******
*******
*******
100
65CO
50U
0
n
10
40
40
10
3U
7
0
7
74
47
21
1
0
5
0
0
0
0
5
50
5
0
0
0
0
0
0
0
0
0
0
0
0
209
29
0
250
250
50
1JOO
1850
0
400
JOO
1200
100
40
180
* MICBCHKG&/CN
•**• NJ CAfA
310
220
24U
170
180
210
160
50
30
40
50
90
40
50
100
90
JO
90
120
10
40
170
0
0
0
40
0
49
19
5
20
30
19
25
35
755
675
91
0
250
0
1500
0
0
1200
3700
850
60 U
1400
*****
18
38
40
39
20
32
20
42
4|
43
38
35
J2
33
40
36
40
36
36
32
31
34
28
24
23
21
9
13
5
5
3
3
2
7
2J
8
0
4
2
2
10
11
U
***
*•*
27
16
18
12
120
120
128
126
104
104
72
148
148
164
164
116
116
116
196
222
84
172
324
224
2SO
156
198
222
182
226
1(4
218
192
184
284
224
124
32
26
46
3)
31
110
7J
135
347
285
251
160
159
75
• •*
• *•
***
• **
• **
• **
• **
au
89
95
76
61
49
88
107
69
62
57
13)
103
91
81
82
70
30
2)
16
16
IT
11
38
48
21
24
11
11
10
30
26
28
**•
***
*«•
*••
***
**•
0.70
O.TO
0.56
0.96
0.63
0.63
0.42
1.20
1.20
1.20
1.20
0.60
0.60
0.60
• *•*•
2.40
2.40
1.40
1.40
0.0
0.42
0.98
0.70
3.64
0.91
0.84
0.0
0.02
0.01
0.0
0.30
C.68
1.33
1.30
1.15
0.51
0.33
0.64
1.99
1.95
.65
.69
.69
.65
.29
.40
.40
.40
.40
.30
.30
.30
*****
0.65
0.65
0.75
0.79
1.40
*****
*****
*****
1.10
0.50
0.60
0.98
0.53
0.50
0.72
0.59
0.68
1.29
0.90
0.83
0.71
0.46
1.01
76
72
106
170
166
222
170
250
304
216
304
224
198
198
236
128
140
456
352
240
228
172
276
636
344
192
40
92
224
284
168
380
224
534
482
360
212
272
336
216
36
34
66
136
92
164
118
115
178
172
162
160
108
116
112
80
48
40
200
160
100
108
72
112
136
296
94
112
20
80
140
204
144
84
132
284
138
208
160
188
132
152
****
42
36
26
102
40
31
72
80
66
72
52
64
32
40
a
16
120
80
60
6
40
40
116
54
36
64
20
48
66
152
116
0
80
214
104
192
80
132
104
104
40
40
34
74
38
92
135
126
44
142
64
90
42
124
112
80
100
256
192
140
120
100
130
140
380
250
80
20
12
84
ao
24
296
92
290
344
152
92
84
204
64
26
22
96
12
36
71
38
9
34
20
20
4
64
92
68
60
96
72
80
80
40
2
»***
•***
74
28
20
16
0
36
48
24
64
36
104
192
116
48
56
128
36
6.8
.8
.7
.6
.6
.1
.1
7.0
T.O
7.2
6.9
6.9
6.9
6.9
6.8
T.I
T.I
7.2
T.2
T.2
T.4
T.2
T.3
T.4
T.O
T.4
7.6
T.O
6.8
6.7
7.1
7.2
T.2
T.7
7.3
6.8
6.6
6.7
6.6
T.2
7.1
T.2
»*•
*•
*»
**
*•
*•
• *
• •
• *
• *
• *
•*
*
11
It
11
11
11
4
2
1
2
2
2
3
2
I
2
3
4
4
4
2
20
11
9
10
9
6
3
3
2.
.
.
.
.
*
.
.
.
.
»
5!
6.
6.
7.
127 7.
112 8.
126 0.
Ill 0.
108 1.
100 1.
100 1.
86 0.
65 1.
91 1.
92 1.
91 1.
49 2.
51 2.
• ** 6.
68 3.
62 4.
68 4.
99 1.
73 1.
70 2.
64 4.
99 0.
84 2.
128 0.
130 1.
126 2.
112 7.
74 0.
72 7.
0
5
0
5
0
5
C
0
3
5
6
C
3
5
3
3
8
3
a
3
7
t
2
4
7
8
C
3
5
8
0
3
9
6
1
6
2
a
5
3
6
5
1
1
1
0
4
0
0.13
0.16
0.2)
0.28
0.33
0.36
0.39
0.48
0.50
0.65
0.15
0.85
0.95
1.05
0.33
0.35
U.40
0.45
0.5C
U.55
0.58
0.15
0.16
0.19
0.21
0.22
0.24
3.53
0.59
0.65
0.66
0.70
0.73
0.75
d. 82
0.98
1.02
1.04
0.56
0.59
0.60
0.43
0.11
0.40
0.20
0.20
0.20
0.25
0.26
2.55
C.13
U.U
0.12
0.11
0.11
0.10
0.10
C.10
0.11
0.12
C.13
0.14
0.15
C.16
G.06
0.06
0.06
0.07
0.07
0.07
0.07
C.21
0.20
0.16
0.15
0.13
C.08
0.66
0.59
0.50
0.45
0.39
0.37
0.33
0.12
0.27
0.25
0.23
0.47
0.33
0.24
0.10
0.14
0.16
2.00
o.ia
0.10
0.04
0.65
0.36
221.
221.
221.
221.
221.
221.
221.
4.
4.
4.
4.
4.
4.
4.
2:9.
259.
259.
259.
259.
259.
259.
511.
ill.
511.
911.
511.
511.
144.
144.
144.
144.
144.
144.
144.
144.
67.
67.
67.
40.
40.
40.
72.
II].
880.
331.
331.
331.
331.
21.
21.
U.45
0.49
0.45
0.45
0.49
U.45
1}. 45
.60
.60
.60
.60
.60
.60
.60
0.25
0.25
0.25
0.25
0.25
U.25
0.25
0.71
0.71
0.71
0.71
0.71
0.71
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.50
0.50
0.50
0.30
0.30
0.30
1.35
0.65
0.20
0.75
0.75
0.75
0.75
0.25
0.25
5.00
5.00
5.00
5.00
5.UO
5.00
5.00
10.50
10.50
10.90
10.50
1C. 90
10.50
10.50
11.50
8. 50
8.50
8.50
8. 50
6.50
8.50
9.00
9.00
9.00
9.00
9.00
9.00
1.00
1.00
1.00
l.ou
1.00
1.00
1.00
1.00
13.90
13.50
13.50
1.29
1.25
1.25
3.25
1.15
1.25
4.75
4.75
4.75
4.75
5.00
5.00
0.09
0.09
0.09
0.09
0.09
0.09
0.09
0.19
0.15
0.15
0.15
0.15
0.15
0.15
0.03
0.03
0.03
0.03
0.03
0.03
0.03
O.OB
0.08
O.Od
O.Ob
o.oa
0.08
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.04
0.04
0.04
0.26
0.26
0.26
0.42
0.37
0.16
0.16
0.16
0.16
0.16
0.05
0.05
1.05
1.05
.05
.05
.05
.05
.09
• 10
.10
.10
.10
.11)
1.10
1.10
0.90
0.90
0.90
0.90
0.90
0.90
0.90
0.30
0.30
0.30
0.30
0.30
0.30
0.50
0.50
0.50
0.50
0.90
0.50
0.50
0.50
0.70
0.70
0.70
1.75
1.75
1.75
2.80
2.40
0.10
0.25
0.25
0.25
0.25
0.45
0.45
-------
TABLE M-2 — Continued
TEST AREA NO. 6
DATE
12969
22069
32369
32369
50769
40769
51569
61269
61769
61769
61769
62369
73169
B1569
01569
TIME
T
1CQC
1510
800
1500
230
530
2liO
330
B40
1040
1250
2300
740
540
740
UACTEHIULOGICAL
NUMUtR/HL
. CUL.
40
311
150
3200
20000
10000
17600
35000
36000
11000
10000
9500
4000
300
100
F.COL.
0
0
0
1
9
0
**•*
750
4700
1550
700
1750
200
90
60
F.UREP.
10
7
0
0
1000
450
100
650C
1250
1000
750
1250
500
5900
3000
ORGANIC
MG/L
BOD
8
6
5
6
16
14
15
11
15
17
21
14
9
13
1
CUD
133
90
80
68
64
4B
39
122
102
106
109
95
79
145
74
I IK
42
30
39
26
30
42
37
42
43
33
36
12
20
»*»
**»
NUTRIENT
HG/L
N
0.9B
0.1)0
1.13
1.40
1.12
0.98
O.IT
0.59
0.27
0.26
0.32
0.16
0.23
0.29
0.21
PU4
1.39
0.90
a.aa
0.88
0.80
0.80
0.74
0.87
o.ao
0.76
0.78
1.05
0.58
0.76
0.44
TOTAL
474
328
260
200
228
172
284
516
516
300
392
480
124
528
304
SOLIDS
HG/L
OS
154
160
80
100
168
152
192
192
160
168
284
200
56
88
112
VDS
68
60
28
40
60
64
100
64
100
80
184
104
B
24
52
ss
320
168
180
100
60
20
92
324
356
132
108
280
68
440
192
vss
38
48
80
60
40
8
40
92
136
40
36
40
68
52
72
07 HER
MC/L
PH
7.4
7.5
7.3
7.3
7.4
7.0
7.7
8.0
7.7
7.5
T.3
7.5
7.4
7.4
7.4
CL
5
6
5
5
12
12
13
10
8
11
13
1
7
5
3
*
CONC
101
147
94
118
144
149
138
95
94
135
139
91
73
84
62
HUE
SINCE
STAR 7
IHRSI
2.3
8.2
10.5
17.5
4.5
T.5
.8
.0
.4
.4
.6
i. a
5.7
1.9
3.S
ANT.
AMOUNT
UN.)
0.45
0.66
1.15
2.25
Q.3U
0.43
o.ao
o.ia
0.28
0.3V
0.45
0.65
0.75
0.7S
1.72
A«r.
AVERAGE
INTENSITY
t 1N./HR.I
C.20
0.08
0.11
0.13
0.08
0.06
0.21
0.18
0.20
0.11
0.08
0.36
0.13
0.39
0.44
TIME AMOUNT
SINCE Of ANT
ANT. EVENT EVENT
IHRS.I
331.
13S.
718.
718.
53.
53.
692.
69.
72.
72.
T2.
154.
980.
21.
21.
UN.)
0.45
0.65
0.25
0.25
0.30
0.30
1.05
0.60
1.35
1.35
1.35
0.45
0.20
0.25
0.25
DURA)1 UN
OF ANT.
EVENT
(MRS.)
4.75
6.50
11.00
11.00
1.00
1.00
4.25
12.00
3.25
3.25
3.25
4.50
1.25
5.00
5.00
AVERAGE
INTENSITY API
ANT. EVENT
I1N./HR.)
0.10
0.02
0.02
0.02
0.30
0.30
0.25
0.05
0.42
0.42
0.42
0.10
0.16
0.05
O.05
0.20
0.40
0.40
0.40
0.45
0.45
0.60
1.10
2.80
2. dO
2.80
1.80
0.10
0.45
0.45
* NICKQMhOS/CM
OO
o
OJ
•»•» NO
cm
-------
TABLE M-2 — Continued
TEST AREA NO. 7
DAU
92364
92368
92368
92368
92368
92368
100568
100568
100568
100568
100568
100568
100968
100968
100968
100968
100968
100968
.^ 101668
TIME
1950
2C2C
2C50
2120
2150
2220
1030
1100
1130
1200
1230
1300
625
640
655
710
725
740
1750
UACTtRlOLOGlCAL
NUMBER ML
T. COl. F.CU . F.
285
120
125
995
65
70
•«*«**«
37
23
11
21
10
13
O 110268 430 «««««*«
.K 110268 10CO ••«*»»«
110268 1030 •*»••••
22069 1230 175
22C69 1310 250
22069 1350 75
22069 1430 62
32369 (30 70
32369 103C 100
32369 LliO 260
41369 1035 120
41369 1135 40
41369 1235 40
41769 220 40
41769 250 20
41769 320 0
50769 25 15000
50769 215 6000
51369 2040 5320
60869 2030 50
61269 420 350CO
61769 1300 1250
62369 2120 15000
62369 2200 12000
62369 2240 12000
62369 2300 8250
81469 200 62CO
81469 SCO 1600
81469 400 100
• MlCRCMhGS/CH
• ••• NO DATA
«*«•
120
0
80
0
0
0
0
0
1
2
0
0
0
0
0
11
1
• **»
0
0
800
300
0
0
0
0
20
20
STREP.
60
70
40
70
240
90
13
17
15
14
21
1
151
175
145
113
140
123
1
0
0
0
20
2
0
0
0
0
0
c
20
51
43
107
115
151
1600
443
0
25
775C
1250
250
500
0
0
0
0
150
BOD
1
2
3
1
2
0
15
13
15
15
21
6
5
5
4
2
3
3
5
6
5
11
10
10
17
13
4
8
7
3
3
4
3
5
4
4
OHGANIC
MG/L
CPU
82
68
61
43
52
52
56
48
48
48
68
88
52
72
40
39
65
33
55
16
11
15
7
58
50
49
IOC
23
19
21
14
24
19
17
21
14
25
**»
26
26
10
2C
15
13
15
0
0
0
0
**•
*•*
**•
NUTKIENT
HG/L
N PC4
0.
0.
0.
0.
1.
1.
1.
1.
1.
1.
1.
1.
1.
2.
1.
0.
0.
0.
0.
c.
0.
0.
0.
i.
i.
i.
70
60
50
40
89
68
40
40
40
33
82
40
26
74
12
10
01
35
13
10
37
32
18
34
40
0.
0.
0.
0.
1.
1.
1.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
1.
1.
1.
0.
0.
0.
0.
60
70
80
80
21
14
2C
50
40
6C
«C
50
50
7C
50
50
53
21
44
34
46
59
9!
Be
92
9C
SOLIDS
MG/L
VDS
T1CE MI. M7. TINE AMOUNT DURATION AVERAGE
OTHER SINCE AMOUNT AVbRAliC SINCE OF ANT Of ANT. INTENSITY API
NG/L •
PH CL CONC
(HAS)
1.1
1.6
2.1
2.6
3.1
3.6
i.H
3.5
5.C
2.2
2.4
2.7
2.9
>.Z
3.4
3.8
4.1
1.5
2.0
2.5
5.5
6.2
6.8
7.5
12.5
13.5
14.5
e.tt.
9. a
10. *
4.6
5.1
5.6
2.4
4.2
1.4
3.C
1.6
5.8
0.1
o.a
1.4
l.b
0.0
1.0
2.C
0.62
0.77
0.87
0.93
C.9»
1.05
(1.70
0.90
0.95
1.00
1.03
1 .00
0.66
0.60
0.64
0.6>
0.65
0.65
0.23
0.26
0.20
0.20
0.20
0.43
a. 51
0.54
0.60
1.28
1.50
1.70
0.41
0.4U
0.50
0.90
0.90
0.90
0.10
0.35
0.28
0.58
0.26
0.40
0.28
0.30
0.80
1.15
0.0
0.10
0.15
< IK./HK. t
0.56
C.48
G.41
C.Jb
C.32
0.29
C.23
0.26
0.24
0.22
C.JO
0.18
0.25
0.25
C.24
C.22
0.20
0.19
0.06
0.06
0.13
0.10
O.CB
0.08
O.Od
0.08
O.OB
0.10
0.11
C.12
0.05
0.05
0.05
0.20
0.18
0.16
0.04
O.C8
0.20
0.19
0.16
0.07
2.80
0.38
0.57
0.64
0.0
a. 10
0.08
IHKS.I
27.
27.
27.
27.
27.
27.
247.
267.
267.
267.
267.
267*
103.
1C3.
1C3.
1CJ.
1C3.
1CJ.
163.
163.
398.
398.
348.
772.
772.
772.
772.
375.
375.
375.
470.
470.
470.
82.
82.
82.
53.
53.
574.
180.
69.
71.
154.
154.
154.
154.
336.
336.
336.
UN. I
0.15
0.15
0.15
0.15
0.15
0.15
1.70
1.70
1.70
1.70
1.70
1.70
1.00
1.00
1.00
i.oo
1.00
1.00
0.70
U.70
0.35
0.35
0.35
0.40
0.40
0.40
0,40
0.11
0.11
0.11
2.75
2.75
2.75
0.50
0.50
0.50
0.30
0.30
0.25
1.25
0.55
1.40
0.40
0.40
0.40
0.40
0.85
0.85
0.85
CVEM
IHKS.I
O.SO
0.50
0.50
C.50
o.*o
0.50
9.80
9. BO
9.80
9.80
9.80
9* fiO
3.80
3.80
3. DO
3.80
3.80
3.80
2.50
2.50
4.30
4.30
4.30
6.50
8.50
11.50
8.;o
1.00
1.00
1.00
27.00
27.00
27.00
10.00
10.00
ID. 00
1.00
1.00
1.60
2. HO
12.00
3.50
4.50
4.50
4.50
4.50
4. SO
4.50
4.50
ANT. EVENT
( IN./HR.)
0.30
0.30
0.30
0.30
0.30
0.30
0.17
0.17
0.17
0.17
0.17
0.17
0.27
0.27
0.27
0,27
0,27
0.27
0.28
0.28
0.08
0.08
0.08
0.05
0.05
0.05
0.05
0.11
0.11
0.11
0.10
0.10
0.10
0.05
0.05
0.05
0.30
0.30
0.16
0.46
0.05
0.40
0.09
0.09
0,09
0.09
o.ie
0.18
0.18
0.15
0.15
0.15
0.15
0.15
0.15
0.8!
0.85
0.85
0.85
0.89
0 «05
1.30
.30
.30
.30
.30
.30
.10
.10
0.35
0.35
0.35
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.70
0.70
0.70
0.45
0.45
0.60
.05
.10
.80
.80
.80
.80
.80
0.25
0.25
0.25
-------
TABLE M-2 — Continued
TEST AREA NO. 8
u>
o
Ul
GATE T IME
T.
12969 940
22069 1550
32369 735
50769 300
50769 500
51569 2220
51569 30
61269 305
61769 1020
61769 1300
61769 1390
62369 2245
7316V 750
81569 450
81569 720
• MCROHI-CS/Crt
»*** NO CAT A
BACTERIOLOGICAL
NUMBEH/ML
COL. F.COL.
2ao
37
100
10000
5715
14150
15100
33000
9000
1250
1500
8250
2800
600
0
0
0
3
0
0
**«#
****
0
4200
750
1950
950
800
60
17
F.STRtP.
ao
10
0
211
165
71
47
14000
1250
750
500
2750
0
2900
2000
ORGANIC
BCD
2!>
3
12
9
16
14
25
8
23
11
10
14
10
10
13
nu/L
COD
405
50
108
72
80
125
62
33
107
77
72
83
69
72
79
IOC
62
24
67
25
31
31
39
13
42
17
18
27
36
»* +
***
NUTRIENT
HG/L
N P04
1.40
0.0
2.52
1.19
1.6D
0.12
0.14
0.35
0.31
0.16
c.ur
0.12
0.91
0. IB
0.31
2.60
0.0
1.50
0.90
1.60
1.68
1.78
0.23
0.87
1.54
0.98
1.20
0.97
0.44
0.56
TOTAL
978
216
512
224
236
324
312
136
348
292
252
364
212
400
400
SOLIDS
OS
156
128
152
116
152
160
200
68
172
204
144
128
120
124
120
nur t-
VOS
38
72
72
56
60
76
108
28
124
124
48
76
48
60
64
SS
822
88
360
108
84
164
112
68
176
88
108
236
92
276
280
VSS
266
0
52
28
44
76
4
16
72
60
32
40
24
76
88
OTHER
PH
7.6
7.2
7.4
7.2
7.2
7.3
7.3
7.7
7.2
7.6
7.7
7.6
7.5
7.4
7.5
no/^.
Cl
12
2
6
12
18
12
21
2
7
13
9
12
10
2
3
TIME
SINCE
* START
COMB IHRSI
US 6.7
5C 7.8
109 9.6
12C 5.C
149 7.C
116 4.3
157 "6.5
52 2.1
117 5.3
108 8.C
til a.o
94 2.8
78 6.8
60 2.6
67 5.3
ANT.
AMOUNT
1 IN. 1
0.47
0.70
1.01
0.42
U.43
0.35
0,35
0.75
0.42
0.45
0.45
C* 83
1.03
0.35
1.36
ANT.
TIME
AMOUNT
AVERAGE SINCE OF ANT
UN./HH.t INKS.) UN.)
C.07
0.09
0.11
0.08
0.06
0.08
C.05
0.36
0.08
O.Ob
0.06
0.30
0.15
0.13
0.26
338.
148.
191.
53.
53.
182.
182.
68.
70.
70.
70.
153.
880.
17.
17.
0.45
0.23
0.08
0.30
0.30
0.35
0.35
0.61
1.41
1.41
1.41
0.45
O.OS
1.05
1.05
DURATION
OF ANT.
IHRS. )
7.00
13.00
6.00
1.00
1.00
2.00
2.00
13.00
4.00
4.00
4.00
6.00
1.00
4.00
4.00
AVERAGE
INTENSI TV
I1N./HR.)
0.06
0.02
0.01
0.30
0.30
0.18
0.18
0.05
0.35
0.35
0.35
0.08
0.08
0.26
0.26
API
0.20
0.40
0.40
0.45
0.45
0.60
0.60
1.10
2.80
2.80
2.80
1.80
0.10
0.45
0.45
-------
TABLE M-2 — Continued
TEST AREA NO. 9
tjO
0
DATE TIKE
T.
12969 1119
22069 1939
32369 840
90769 200
90769 410
91969 2119
61269 400
61769 910
61769 1109
61769 1210
62169 2320
T3149 72C
11469 400
11469 790
81969 930
11969 100
* NICROMHCS/CM
••»• NO CAT*
BACTERIOLOGICAL
NUMBER/NL
CUL. F.CUL. f.
960 0
361 0
260 0
10000 9
4000 0
17000 •*##
79000 1000
11000 1000
1000 1100
2790 2690
11290 0
9300 90
1600 440
600 140
1100 60
900 0
swp. 100
40 11
0 9
0 4
179 7
29 7
11000 19
9730 13
2290 12
11000 11
2000 It
1900 9
90 »*•
100 •••
3600 14
1300 1
ORGANIC
MC/L
COO TOC
189 61
120 36
64 22
40 23
40 23
134 43
90 30
119 94
73 21
113 13
99 26
241 «•*
269 ••»
131 •«•
6« **•
TIME ANT.
NUTRIENT SOLIDS OTHER SINCE AMOUNT
HG/L MG/L MC/L * START (IN.I
N f>04 70TAL OS VOS SS VSS PH Cl CDNO IHRSI
1.12 1.90 672 161 84 904 92 7. 4 10*9 . C.63
1.10 1.19 460 192 112 261 21 7. 162 . 0.61
1.19 1.25 210 140 10 140 40 7. 93 1 . 1.29
0,91 0.90 196 140 60 16 0 7. 123 . 0.33
0.9* 0.30 196 140 60 16 0 7. 123 . 0.43
0.48 0.10 TOO 164 92 936 161 T. 74 . 0.29
0.22 0.17 360 61 36 292 10 7. 76 . 0.33
0.3* 1.12 711 236 114 992 316 7. 76 . 0.40
0.03 1,02 320 204 116 116 60 7. 140 4. 0.49
0.42 1.92 304 112 61 192 41 7. 101 2. 0.63
0.22 0.41 132 14 61 41 34 T. 64 9. 0.73
0.33 0.69 976 272 201 304 10 7. 125 2. 0.20
0.72 0.80 732 214 232 441 164 T. Ill 6. 0.29
0.19 0.34 232 120 10 112 12 1. TO 1. 0.70
0.13 0.64 404 124 14 210 16 7. 92 4. 1.90
ANT.
AVERAGE
INTENSITY
IIN./HR.I
0.11
0.08
C.ll
0.08
0.07
0.24
0.17
0.18
0.11
0.09
0.31
0.14
0.09
0.04
0.39
0.44
TIME
SINCE
ANT. EVENT
IHRS.I
331.
133.
718.
33.
93.
15.
69.
72.
72.
72.
194.
860.
331.
331.
21.
21.
AMOUNT
at ANT
EVENT
(IN.I
0.49
0.69
0,29
0.30
0.30
0.29
0.60
1.39
1.39
1.39
0.49
0.20
0.79
0.79
0.29
0.29
DURATION
OF ANT.
EVENT
IHRS.I
4.79
6.90
11.00
1.00
1.00
5.29
12.00
3.25
3.29
3.23
4.90
1.29
4.75
4.75
9.00
5.00
AVERAGE
INTENSITY
ANT. EVENT
IIN./HR.I
0.10
0.10
0.02
0.30
0.30
0.05
0.09
0.42
0.42
0.42
0.10
0.16
0.16
0.14
0.09
0.09
API
0.20
0.40
0.40
0.45
0.49
0.60
1.10
2.10
2.10
2.10
1.60
0.10
0.25
0.29
0.45
0.45
-------
TABLE M-2 — Continued
TEST AREA NO. 10
HdCfERIOLOGICAL
uo
-0
CATE
111064
111566
1 11 5t8
111568
111568
I1156S
111568
1 11 5t B
121868
121 868
122768
122768
122766
122766
122768
41749
41769
41769
61269
61769
61769
42469
62469
62469
7M69
73169
7)169
91469
91469
81469
41569
61569
61569
TIME
7.
1005
130
145
200
215
230
245
300
1220
1235
20C
230
300
CIS
1100
130
230
330
SL5
920
1120
1015
1105
1145
645
725
805
250
530
900
600
640
1030
N
CUL.
480
440
720
3320
560
320
400
260
840
240
60
40
20
HO
40
285
570
270
38000
250
6750
4750
4250
£500
1500
650
1500
6000
1400
2600
200
600
300
UMBER/ nL
F.COL.
0
0
0
0
0
c
0
0
0
0
0
0
0
0
0
1
0
1
250
300
200
0
450
200
0
100
100
40
380
20
340
140
40
F. STREP.
130
7C
90
*Q
0
20
50
30
50
0
45
270
10
20
5
200
115
67
8250
0
1000
*******
*******
*******
4100
8400
130
100
0
0
1400
1000
200
ORGANIC
BUD
13
15
16
16
23
20
10
28
26
3
2
3
6
6
e
7
7
5
7
13
10
9
9
7
6
6
17
14
11
9
7
6
MG/L
CDU
140
140
140
140
144
144
194
286
29J
104
92
100
104
76
64
56
36
64
139
61
58
60
33
52
49
174
164
136
103
69
81
IOC
27
29
44
23
36
26
80
13
12
26
18
20
43
97
53
15
19
37
22
13
11
26
NUTRIENT
HO
N
1.12
1.12
1.12
1.12
1.12
2.40
*****
*****
2. 38
2.11
2.24
0.11
0.12
0.0
0.25
0.27
0.22
0.32
0.39
0.39
0.31
0.90
0.51
0.46
0.27
0.44
/L
P04
2.00
1.40
1.40
1.20
1.20
0.65
*****
*****
1.20
1.00
0.90
0.30
0.46
0.69
0.46
0.64
0.57
0.25
0.28
0.36
0.42
0.50
0.52
0.72
0.62
0.80
TOTAL
204
152
140
152
150
206
152
184
230
968
808
600
264
332
508
228
416
500
176
410
540
454
516
466
1180
1468
1376
SOLIDS
DS
88
110
104
108
116
26
122
100
142
64
48
100
224
120
140
1T6
140
244
64
184
156
280
324
256
88
84
128
MG/L
VOS
24
56
20
10
56
48
28
4
48
36
68
24
40
40
140
48
44
156
92
208
48
124
80
204
228
160
52
76
64
SS
2
116
42
44
34
52
180
30
84
88
904
760
700
40
212
368
52
276
256
112
226
384
174
192
212
1092
•1384
1248
VSS
44
16
12
16
80
0
10
10
104
88
80
12
32
56
32
188
164
68
20
44
88
96
88
128
92
228
PH
7.4
7.0
7.2
7.0
J^4
T.I
7.5
».3
T.3
7.3
7.3
1.5
T.6
T.a
7.4
7.5
7.5
T.3
7.4
7.4
7.1
7.1
T.3
7.5
7.5
T.4
OTHER
KG /I
CL
*••
**•
**•
13
2
2
3
9
3
3
3
10
3
5
8
li
15
6
14
19
21
21
21
2
Z
6
*
CONO
***
*•*
***
133
65
66
85
122
78
76
T6
104
61
94
94
129
149
63
105
65
163
172
166
56
92
90
TIME
SINCE
START
IHRi]
5.0
5.5
5.B
6.3
6. 5
0.3
0.6
0.3
0.8
6.5
9.3
3.3
4.3
5.3
2.6
2.1
4.1
1.3
3.1
3.8
4.8
5.4
6.1
1.1
3.8
7.3
2.3
2.9
8.8
ANT.
AHL1UNT
< IN.t
0.4b
0.65
0.75
0.95
1.05
0.12
0.14
0.55
0.60
o.ao
0.84
0.93
1.03
1.05
0.28
0.36
0.42
0.16
0.20
0.20
0.71
0.75
0.75
0.20
0.20
0.25
0.85
1.16
2.55
ANT.
AVERAGE
INTENSITY
1 IH./HR.I
0.10
0.12
0. 13
b.14
0.15
C. 16
0.40
C. 23
1.83
0.75
0.12
0.09
0.28
C.24
0.20
C.10
C.17
0.10
0.12
0.06
0.05
0.15
0.14
0.12
0.18
0.05
e.os
0.37
0.41
0.29
TIME
SINCE
INT. EVEN
(MRS.)
221.
•
14 .
14 .
14 .
14 .
144 .
M4.
144.
67.
67.
67.
69.
72.
72.
10.
10.
10.
880.
880.
860.
331,
331.
331.
21.
21.
21.
AMOUNT
OF ANT
r EVENT
UN.)
0.45
1.60
1.60
1.60
1.60
1.60
1 .60
0.60
0.60
0.12
0.12
0*12
0.12
0.12
0.50
0.50
0.50
0.60
1.35
1.35
0.65
0.65
0.65
0.20
0.20
0.20
0.75
0.75
0.75
0.25
0.25
0.25
OURATIUN
OF ANT.
EVENT
(BBS.)
5.00
10.50
10.50
10.50
10.50
10.50
1.00
1.00
1.00
1.00
1.00
1.00
1.00
13.50
13.50
13.50
12.00
3.25
3.25
1.75
1.75
1.75
1.25
1.25
1.25
4.75
4.75
4.75
5.00
5.00
5.00
AVERAGE
INTENSITY
ANT. EVEN
1 IM./HR.I
0.09
0.15
0.15
0.15
0.15
0.15
0.15
0.60
0.60
0.12
0.12
0.12
0.12
0.12
0.04
0.04
0.04
0.05
0.42
0.42
0.37
0.37
0.37
0.16
0.16
0.16
0.16
0.16
0.16
0.05
0.05
0.05
API
T
1.05
1.10
.10
.10
.10
.10
1 . 10
0.30
0. 30
0.50
0.50
0. 50
0.50
0.50
0.70
0.70
0.70
1.10
2.80
2.60
2.40
2.40
2.40
0.10
0. 10
0.10
0.25
0.25
0.25
0.45
0.45
0.45
* MiCRCHHCS/CH
• *** NO
DATA
-------
TABLE M-2 — Continued
TEST AREA NO. 11
DATE IIHt
I
12969 1C10
12169 110C
12969 1130
12«6« 120C
22069 1529
32369 815
32369 820
12369 1515
50769 190
50769 400
50769 700
91969 2030
91569 2100
91S69 2130
91S69 2200 *
61269 420
61769 «00
, 61764 1100
W 61769 1240
O 62369 2345
QO 73169 710
81469 345
(1469 445
61469 (45
81569 520
81569 150
* MICftCMI-CS/CM
»*•• NU CAT*
SACrERIOLUGICAL
NUHBER/ML
. COt. F.COL. F.
160 0
240 0
360 0
440 0
650 0
140 0
1750 0
150 0
120CO 4
6000 0
8000 0
23750 *«»*
21100 •••*
28100 **»»
58000 500
12000 0
200CO 0
4750 50
24000 2900
9000 400
1100 60
BOO 40
400 0
700 260
900 100
STREP.
10
0
0
10
0
0
0
0
50
40
5
125
65
5
11250
14000
3500
34500
3500
2 SO
450
100
100
2900
2300
BOO
23
13
15
12
12
12
6
12
10
7
15
21
18
16
13
12
24
22
22
26
16
ORGANIC
MGA
COD
144
144
136
103
100
140
64
68
80
80
80
102
82
89
89
129
202
162
138
85
106
2U
ITi
179
180
81
TINE ANT. ANT. TIKE AMOUNT DURATION AVERAGE
NUTRIENT SOLIDS OTHER SINCE AMOUNT AVERAGE SINCE UF ANT Of ANT. INTENSITY API
MG/l KG/I MC/L • START (IN.) INTENSITY ANT. EVENT EVENT EVENT ANT. EVENT
IOC N P04 TOTAL OS VOS SS VSS PH CL COND IHRSI IIN./HR.I IHRS.I (IN.) (HRS.I UN. /MR. I
44 1.66 1.60 568 138 38 430 86 7. 6 11* 2. 0.50 0.16 332. 0.45 4.75 0.10 0.20
13 2.10 1.70 672 114 14 556 144 7. 4 109 3. 0.55 0.17 332. 0.45 4.75 0.10 0.20
29 1.82 2.10 726 166 30 560 134 7. 5 109 3. 0.70 0.18 332. C.4S 4.75 0.10 0.20
50 1.40 1.90 5*7 HO 94 367 24 7. 5 101 4. 0.85 0.20 332. 0.45 4.75 0.10 0.20
L7 0.40 0.95 416 168 60 248 20 7. 10 19« e, 0.67 0.08 135. 0.65 6.50 0.10 0.40
36 2.24 l.aO 660 140 20 520 112 7. 3 66 10. 1.19 0.11 718. 0.25 11.00 0.02 0.40
27 1.05 1.10 398 128 32 230 100 7. 4 102 10. 1.20 0.11 718. 0.25 11.00 0.02 0.40
24 1.19 1.29 272 160 20 112 32 7. 7 152 17. 2.21 0.13 718. 0.25 11.00 0.02 0.40
25 1.87 0.60 320 208 40 112 52 7. 12 175 3. 0.26 0.07 53. 0.30 1.00 0.30 0.45
25 1.87 0.60 320 206 40 1U 52 7. 12 175 6.C 0.41 C.07 53. 0.30 1.00 0.30 0.45
25 1.87 0.60 320 208 40 112 52 7. 12 175 9.0 0.43 0.05 !3. 0.30 1.00 0.30 0.45
37 0.20 .24 772 276 156 49« 80 7. 169 2.5 0.78 0.31 6?2. 1.05 4.25 0.2$ 0,60
39 0.19 .06 516 204 164 312 56 7. 135 3.0 0.80 0.27 632. 1.05 4.25 0.25 0.60
28 0.23 0.88 464 180 lot 264 76 1. lit 3.5 C.60 0.23 612. I. OS 4.15 0.25 0.60
40 O.'l3 .12 1016 166 120 848 128 7. 78 1.8 0.26 0.14 69. 0.60 12.00 0.05 lilO
55 0.22 .63 680 232 46 448 216 7. Ill 1.6 0.35 0.20 72. 1.35 3.25 0.42 2,80
49 0.15 .58 980 292 64 726 176 7. 151 3. a 0.40 0.11 72. 1.35 3.25 0.42 2. 80
0.19 0.95 760 320 172 440 148 7. 153 5.4 0.45 0.08 72. 1.35 3.25 0.42 2.8C
2 0.34 1.93 608 180 88 426 44 7. 67 2.5 C.65 0.26 154. 0.45 4.50 0.10 1.6C
0.30 0.61 260 96 44 204 52 7. 65 5.2 C.75 0.14 880. 0.20 1.25 0.16 0.10
0.42 0.86 596 346 272 200 160 7. 113 2.C 0.20 0.10 331. 0.75 4.75 0.16 0.25
0.33 0.71 544 264 264 260 L72 7.0 114 3.0 0.20 0.07 331. 0.75 4.75 O.lfr 0.25
0.30 0.70 476 204 104 272 64 7.0 115 5.0 0.25 0.05 331. 0.75 4. 75 0.16 O.25
0.31 1.20 936 12 32 864 240 7.4 62 1.6 0.65 0.41 21. 0.25 5.00 0.05 0.45
0.17 0.76 496 112 48 384 100 7.5 52 4.1 1.81 0.44 21. 0.25 5.00 0.05 0.45
-------
TABLE M-2 —Continued
TEST AREA NO. 12
U)
0
vD
DATE
11569
11569
11569
11569
11569
1 1 569
11569
12969
12969
12969
12969
22069
22C6»
22069
32369
50769
50769
51569
51569
61269
6176S
61769
62369
73169
81469
81569
81569
TIHE
T
lejo
1850
1910
19 JO
1950
2C10
2020
910
940
1010
1040
1200
1245
1330
7J5
330
600
2245
2400
245
750
1345
2230
815
730
430
820
BACTERIOLOGICAL
NUMBER/ML
. COL.
0
0
40
120
40
40
40
0
0
80
0
875
15CO
625
150
10000
6000
11000
25000
250
0
4250
1300
50
1400
0
F.COL.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
5
0
****
0
0
50
200
0
0
0
0
F. STREP.
0
0
0
50
0
0
19
50
50
10
30
10
12
0
0
15
25
30
5500
0
250
0
250
0
0
150
250
ORGANIC
KG/I
800
12
11
9
8
8
a
9
7
a
7
23
13
11
B
9
6
7
t)
6
6
6
8
a
10
3
COD
92
40
38
36
56
76
28
37
40
33
29
107
53
46
64
28
24
50
41
21
34
21
45
47
67
47
TOC
28
17
14
12
I 1
12
23
24
27
31
62
41
18
22
24
11
26
13
5
21
1
**
•*
**
**
NUTRIENT
HG/L
N '
C.UO
0.60
0.60
0.60
0.0
0.0
0.0
0.42
0.42
0.21
0.14
1.33
1.19
1.26
0.98
1.12
0.63
0.15
0.04
0.02
0.0
0.01
0.13
0.16
0.12
0.33
0.12
P04
0.30
0.30
0.10
0.20
0.20
0 * 20
0.10
0.59
0.59
0.50
0,60
0.50
0.30
0.20
0.56
0.50
0.40
1.68
0.37
0.26
0.37
0.32
0.37
0.66
0.70
0.25
0.27
TOTAL
234
162
136
96
90
184
226
244
216
168
146
96
292
72
76
256
396
140
132
296
276
96
148
272
136
SOLIDS
HG/L
OS
89
86
70
48
58
100
84
88
100
80
100
72
112
56
68
196
52
116
268
148
88
124
104
VOS
36
42
32
18
22
32
29
42
42
32
44
32
52
16
20
36
36
116
120
124
80
104
44
84
ss
146
76
66
48
32
84
142
156
116
88
48
24
180
16
8
60
334
24
28
128
8
0
148
32
VSS
4
3
6
10
22
14
IB
14
28
16
36
12
52
8
4
20
64
24
20
20
8
0
100
0
OTHER
NG/L
PH
7.1
7.1
7.C
6. a
6.8
7.0
6.8
6.6
6.8
7.4
7.0
6.7
7.6
7.1
7.1
7.6
7.4
7.2
7.5
7.1
6.9
6.9
7.2
7.2
Ct
5
4
4
4
3
4
3
3
3
3
5
5
5
3
2
3
4
2
3
TIHE ANT.
SINCE AffUUNT
* START 1114. 1
cone IHHSI
79
83
70
53
60
62
64
52
62
61
60
110
93
ai
70
51
84
T5
32
53
84
29
55
68
119
32
0.5 C.OB
0.8 0.10
1.2 C.12
1.5 C. 1 3
1.8 0.14
2.2 0.15
2.3 0.16
6.2 0.43
6.1 0.47
7.2 0.51
7.7 0.55
4.( 0.70
4.8 0.70
5.5 C.70
9.3 0.66
5.5 0.43
8.0 0.43
4. » 0.35
1.8 0.68
2.8 0.28
8.8 0.45
2.5 0.82
7.3 1.03
2.5 0.60
2.5 0.32
6.3 1.99
ANT.
INTENSITY
IIH./HH.)
O.lb
o.u
0.1C
0*09
G.Od
0.07
C.07
0.07
C.07
0.07
0.09
0.18
C.15
0.13
0.07
0.08
0.05
0.07
0. 06
C.36
0.11
0.05
0.33
0.14
0.24
0.13
0.32
TIHE AMOUNT
SlftCE Of ANT
ANT. EVENT EVENT
INKS.)
450.
450.
450.
45fl!
450.
339.
338.
338.
338,
148.
14B.
148.
191.
53.
53.
182.
182 .
68.
70.
70»
10.
153.
680.
334.
17.
17.
I1N.I
1.24
1.24
1.24
1,24
1.24
0.45
0.45
0. 45
0.45
0.23
0.23
0.23
0.08
0.30
0.30
0.35
0.35
0.61
.41
.41
.41
.45
.08
.03
.05
.05
DURATION
OF ANT.
EVENT
(MRS.)
22.00
22.00
22.00
22.00
22,00
22.00
7.00
7.00
7. 0O
7.00
13.00
13.00
13.00
6.00
1.00
1.00
2.00
2.00
13.00
4.00
.00
.00
.00
.00
.00
.00
.00
AVERAGE
INTENSITY API
ANT. EVENT
IIN./HK.)
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.02
0.02
0.02
0.01
0.30
0.30
o.ie
0.18
0.05
0.35
0.35
0.35
0.08
0.08
0.17
0.26
0.26
0.30
0.30
0.30
0.30
0.30
0.20
0.20
0..20
0.20
0.40
0.40
0.40
0.40
0.45
0.45
0.60
0.60
1.10
2.80
2. 80
2. BO
i.eo
0.10
0.25
0.45
0.45
• KICROKHCS/CN
**** NU
CATA
-------
OO
I—'
o
DATE
100968
1009(8
1009«8
101668
101668
1016(6
110268
1102*8
4f369
41369
41369
41769
41769
41769
42669
42669
42669
42669
42669
61469
61469
TIME
640
655
710
1840
1855
1925
1245
1430
600
too
BOO
245
345
445
1900
1920
2COO
2020
745
845
42469 1040
73169 510
81569 650
81569 900
• MICROMKS/CM
*•** NO CAT4
BACTER10LOG1C
NUMBER/ML
T. CUL. F.CUL.
101 *»**
50 ••»•
33 ****
•**«***
*******
10
0
0
510
290
430
*******
*******
170CO
1500
100
300
160
00
0
0
0
9
4
0
100
200
200
1100
0
20
300
At.
F.SIREP.
200
220
181
7
3
0
1
1
460
120
7
0
11
87
103
323
0
0
0
1750
$00
2700
4300
[
UOO
6
6
4
14
9
1
7
22
10
0
0
0
34
32
13
43
43
43
34
35
34
5
4
4
7
7
7
5
1R&AN1C
MG/L
COD roc
16
12
12
172
132
104
264
280
248
2 OH
172
148
46
47
47
73
48
61
93
12
28
11
61
51
33
65
71
75
78
52
56
19
14
18
28
33
• **
***
NUTRIENT
MG/L
N P04
0.42
0.56
0.98
.50
.50
.41
.44
.37
.39
.90
.62
.20
0.38
0.29
0.2)
0.16
0.18
0,16
0.14
0.0
0.19
0.20
2.30
1.90
1.70
2.40
2.20
1.90
1.80
1.70
1.40
1.92
1.72
1.72
0.92
0.60
0.70
1.26
TABLE M-2 — Continu
TEST AREA NO. 13
SOI IDS 1
MG/L
TOTAL OS VOS SS VSS PH
248 72 16 176 64 7.2
256 32 16 224 BO 7.2
288 40 20 248 48 7.2
192
184
148
12k
352
302
324
320
344
488
440
300
768
744
922
212
472
328
2304
720
884
208
300
444
1240
52
86
64
98
112
172
312
320
340
120
120
ao
160
208
150
112
184
168
176
140
100
112
124
124
144
44
58
14
60
44
52
112
136
160
64
40
20
96
116
72
48
64
96
124
56
20
104
108
80
SO
140
98
84
28
240
130
12
0
4
368
320
220
608
536
372
120
288
160
2128
580
784
128
176
320
1096
0
6
18
30
22
4
0
0
80
48
168
164
108
60
88
56
208
116
716
80
40
52
92
7.6
7.5
7.2
7.0
T.I
8.0
8.0
B.I
7.0
T.O
7.1
T.O
6.9
6.9
6. a
6.8
T.2
T.2
T.J
T.2
7.0
7.3
ed
JTHER
MG/L
CL
71
71
71
J
7
T
T
T
10
28
28
2B
3
5
25
31
20
13
9
9
2
2
3
2
2
1
TIME
SINCE
• START
CQNO (HRSI
2.4
2.7
2i9
.2
.4
.7
.9
2*3
263
72
109
181
204
172
135
116
121
69
60
59
49
56
46
.2
.3
2.3
2.9
3.5
4.5
4. a
6.8
0.0
0.3
0.7
1.0
1.3
1.7
3.5
4.5
5.7
2.4
2. a
5.0
ANT.
AMOUNT
(IN.l
0.53
0.58
C.60
0.32
C.3i
0.35
0.35
0.35
0.80
1.10
0.12
0.14
C.16
0.90
0.90
0.0
0.01
0.05
O.U
0.15
0.15
1.10
1.19
0.32
0.41
C.85
1.90
ANT.
AVERAGE
INTENSITY
I1N./HR.I
0.22
0.21
0.21
0.08
C.Cfl
0.07
C.07
0.07
0.19
C.48
C.05
0.04
0.04
0.19
0.13
0.0
0.03
0.07
0.12
0.11
C.09
0.31
0.26
0.06
0.17
0.30
C. Jfl
TIHE AMOUNT
SINCE OF ANT
ANT. EVENT EVENT
IHRS.I IIN.I
80. 1.07
aa. 1.07
88. 1.07
176. 0.60
176. 0.60
176. 0.60
176. 0.60
176. 0.60
350. 0.35
350, 0.35
466. 2.65
466. 2.65
466. 2*65
82. 0.35
82. 0.35
S2. 0.35
119. 0.15
119. 0.15
119. 0.15
119. 0.15
111.
25.
25.
25.
6.
£00.
20.
20.
0.15
0.55
0.55
0.55
0.75
0.35
0.15
0.15
DURATION
OF ANT.
EVENT
IHRS.I
5.25
5.25
5.25
2.25
2.25
2.25
2.25
2.25
4.00
4,00
21.00
21.00
21.00
a. 50
8.50
8.50
l.»0
1.50
.59
.50
.50
.50
.50
.53
.00
.75
.50
.50
AVERAGE
INTENSITY API
ANT. EVENT
IIN./HR.)
0.20 1.30
0.20 1.30
0.20 1.30
0.27 1.10
0.27 1.10
0.27 1.10
0.27 1.10
0.27 1.10
0.09 0.35
0.09 0.35
0.13 0.4C
0.13 0.40
0.13 0.40
0.04 0.70
0.04 0.70
0.04 0.70
0.11 0.65
0.11 0.65
0.11 0.65
O.U 0.65
0.11
0.42
0.42
0.42
0.38
0.06
0.10
0.10
0.65
2.25
2.25
2.25
2.40
0.10
0.45
0.45
-------
TABLE M-2 — Continued
TEST AREA NO. 14
DATE TIME
1115(8 350
111568 405
111568 420
111568 435
11156D 450
111568 505
111568 520
122768 215
1227(8 23C
1227(8 245
122768 300
122768 315
1227«B 330
122768 345
122748 430
61469 710
62469 1050
81569 850
• NICROMHQS/CN
• *•• NO CATA
NUMBER/ML
T. CUL.
6000
7040
T200
6880
4000
6400
5000
40
80
40
80
120
40
60
80
»*»*»**
14250
0
F.COL.
27
14
0
27
0
0
0
0
0
0
0
0
0
0
0
700
950
0
F. STREP.
190
120
170
210
170
140
150
50
10
15
10
10
0
0
0
75C
250
1000
ORGANIC
MG/L
BOO
11
22
26
29
29
26
15
6
7
6
5
6
5
4
7
8
9
6
COO
36
56
56
48
40
36
48
68
68
84
84
80
80
64
52
74
51
22
IUC
31
37
49
41
36
33
23
29
47
43
41
36
19
24
2U
IB
***
NUTRIENT
MG/l
N
.68
.68
.66
.66
.96
.96
.40
2.80
2.80
2.80
2.80
2.50
2.50
2.50
0.82
0.36
0.13
P04
2.20
2.20
2.65
2.65
2.65
2.65
2.65
0.20
0 *20
0.0
0.0
0.0
0.20
0.10
2.25
0.87
0.27
TOTAL
424
640
816
814
646
450
384
608
752
776
188
413
916
1068
48
SOL 1 OS
MG/L
OS
400
278
290
272
1B2
160
192
198
262
256
86
206
128
212
28
vos
192
56
84
32
46
40
118
36
72
40
64
78
44
72
28
SS
24
526
542
464
290
192
410
490
120
102
207
7B8
856
20
VSS
10
88
100
152
36
30
178
72
78
72
**••
IS
92
828
20
OTHER
NB7L
PH
6.9
6.7
6.7
6.7
6.7
6.7
6.0
*•**
7.2
7.2
7.S
T.2
7.2
7.2
T.4
7.0
7.!
7.1
Cl
U
19
32
31
29
27
21
18
8
IT
1
TIKE
SINCE
• START
CONO
1»4
148
190
182
167
,157
149
88
163
J»
HRSl
3.6
4.1
4.3
4.6
4.8
5.1
5.3
0.3
0.5
0.8
1.0
1.3
r'.i
Z.9
5.H
4.8
ANT.
AMOUNT
UN.)
0.68
0.71
0.75
0.79
0.83
C.86
0.90
0.35
Q» 4Q
0.45
0.50
0.53
0.55
0.58
0.75
0.98
0.33
1.79
AVERAGE
INTENSITY
I1N./HR.)
a. la
C.17
C.17
0.17
C.17
0.17
0.17
1.17
C. 80
0.56
0.50
0.41
0.37
0.32
0.10
C.34
0.06
0.37
SINCE OF ANT
ANT. EVENT EVENT
(MRS.)
1C4.
1C4.
1C4.
1C4.
1C4.
104.
104.
144.
1 44 •
144.
144.
144.
144.
144.
144.
25.
6.
20.
1 IN.I
0.50
0.50
0.50
0.50
0.50
0.50
0.50
0.12
0* 12
0.12
0.12
0.12
0.12
0.12
0.12
0.55
0.75
0.15
Uf ANT.
EVENT
(HRS.I
6.30
6.30
6.30
6.30
6.30
6.30
6.30
1.00
1 . 30
1.00
1.00
1.00
1.00
1.00
1.00
1.50
2.00
1.50
INTENSITY API
AhT. EVEJVT
( 1N./HK. 1
J.OB
O.OB
o.oa
o.oa
o.oa
0.08
0.08
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.42
0.38
0.10
.10
.10
.10
.10
.10
.10
.10
0.50
0.50
0.50
0.50
0.50
a. 50
0.50
2.25
Z.40
0.45
-------
TABLE M-2 — Continued
TEST AREA NO. 15
DATE
110266
110268
110268
110268
1102(8
110268
110268
111068
111568
1115(8
111568
1115(6
111568
111568
111 568
1227C6
1227(8
61461
62461
73169
81569
81569
TIME
1230
1300
1330
1400
1500
1530
1015
130
145
200
215
230
245
230
sec
730
1030
500
705
910
UACTGHIULUCICAL
NUMBER/ML
T. COL. f.CUL. f. STREP.
80 40
1260
U40
2720
4400
5200
2720
2720
440
2160
*•*••••
14500
5000
200
200
fltf
40
60
40
60
220
20
20
100
27
47
7
0
0
300
1350
0
0
0
4V
0
20
20
0
0
150
150
100
140
150
110
140
0
0
900
900
2400
2500
2800
ORGANIC
HG/L
800 COO 70C
10
11
11
7
6
17
34
41
31
15
16
26
4
1
10
14
13
6
64
64
60
60
40
3k
44
la
62
54
71
40
24
28
36
38
35
61
68
11
18
23
»**
*••
NUTRIENT
HG/L
N P04
1.54
1.54
0. 70
0.70
0.56
0 56
0.56
0.16
0.15
0.22
0.31
0.20
4.30
4.30
2.50
2.50
1 40
0.60
0.10
0.71
0.1«
1.02
0.64
0.58
TOTAL
180
104
88
76
20*
142
**•*
86
7*
116
80
TOO
316
160
260
364
SOLIDS
MO/L
OS VDS
64 28
30
60
66
54
36
198
138
66
52
66
86
68
20
172
88
132
124
If
28
30
20
22
150
6
60
40
62
44
42
8
66
62
112
100
ss
116
60
44
22
24
28
16
4
20
22
110
12
680
22«
72
148
240
VSS
32
22
36
12
20
10
0
0
10
la
38
*•»*
624
96
24
84
104
OTHER
MO /I
PM CL
6.7 3
6.7 3
6.7 3
6.7 3
6.7 3
6.7 3
6.7 »»•
6.7 •••
6.4 •«•
4.6 •••
6.1 3
6.1 2
7.0 1
7.0 3
6.8 2
6.7 1
t.e i
TIME
SINCE
• START
COND IHRS)
••• 4.0
***
:::
•••
•*•
...
**•
49
30
90
41
41
29
4.7
5.C
5.5
6.C
7.C
0.8
1,8
2 > C
2.3
2.5
2.9
3*0
0.
1.
3.
5.
2.
3.
9.2
ANT.
AMOUNT
UN.)
J.70
0.10
0.13
C.15
0.18
1.03
0.08
c.ce
0.11
0.13
0.25
0.35
0.45
0. 55
0.25
0.75
1.05
0.30
0.40
0.13
1.13
ANT.
AVERAGE
INTENSITY
IIN./HR.I
C.18
0.20
C.11
0.17
0.16
0.15
0.15
0.10
0.05
0.06
0.11
0.14
0.16
0.18
C.50
0.58
0.32
0.09
0.17
0.30
0.37
TIME AMOUNT DURATION
SINCE Of MT Of AM.
ANT. EVENT EVENT EVENT
IHRS.I UN.) IhRS.)
390. 0.35 4.00
350.
350.
350.
390.
350.
350.
350.
1C4.
104.
104.
1C4.
104.
104.
1C4.
144.
144.
25.
6.
880.
20.
20.
V.?7 4.UW
0.35 4.00
0.35 4.00
0.35 4.00
0.35 4.00
0.35
0.35
0.50
0.50
0. 50
0.50
0.50
0. 50
0.12
0.12
0.55
0.75
0.35
0.15
0.15
.00
.00
.25
.25
• 25
.25
.25
.25
.25
.00
.00
.50
.00
.75
.50
.50
AVERAGE
1N7ENSITY API
ANT. tVCNT
I 1N./HR. 1
0.01 0.35
0.09
0.01
0.01
0.01
0.01
0.09
0.01
0.08
0.08
0 .08
0.08
0.08
o'.12
0.12
0.42
0.38
0.06
0.10
0.10
0.35
0.35
0.35
0.35
0.35
.09
.10
.10
• 10
.10
1.10
1.10
0.50
0.50
2.25
2.40
0.10
0.45
0.45
* HICRCNHCS/CH
»«»• NO
OA7A
-------
APPENDIX N
GENERAL PLAN FOR THE CITY OF TULSA
TO CONTROL STORM WATER POLLUTION
Introduction
From the onset of this project, it was visualized that, because of the
amounts of pollution found in urban surface drainage in the Tulsa
Metropolitan Area, remedial measures would relate to institutional
and regulative actions rather than extensive structural facilities.
It must be remembered that a single method of control or treatment
would usually not be sufficient to cope with all sources of storm water
pollution in an urban area. The varying surface characteristics,
including land use in an urban community, demand, under specific
circumstances, those methods which are the most feasible for each
specific subdrainage basin. The analysis must take into account the
sewer hydraulics, topography, land use, availability of construction
sites, rainfall and runoff characteristics, water quality standards for
the receiving waters, and many other factors.
In the Tulsa Metropolitan Area, the basic plan of action should
emphasize institutional and regulatory measures which are necessary
for a completely integrated storm water pollution control program. In
the future, it is quite possible that physical approaches may have to be
utilized at several points in the storm water system, to completely
alleviate the problem. The three basic physical methods are: (1) con-
trol--includes storm water system regulators, retention basins, etc.;
(2) treatment—includes microstraining, high rate filtration, chlorina-
tion, dissolved air flotation, etc. ; and (3) a combination of the two.
It is quite apparent that, as state standards relating to water pollution
are established, local governments will be responsible for upgrading or
maintaining the quality of interstate and intrastate waters. Local
jurisdictions will find it necessary to adopt local standards to control
all sources of pollution. In order to avoid the possibility of forfeiting
the right to control these sources of pollution, including storm water
pollution, local communities should begin to develop sound water
pollution control regulations to prevent all unnecessary contaminants
from entering their waterways.
Development of appropriate plans of action at an early date would
prevent further degradation of the receiving streams in the Tulsa area.
313
-------
Preventing and abating storm water pollution is a costly and complex
problem. The economic benefits to be gained are not readily apparent
and are often long range in nature. Strong prevention-type programs
are the most economical. Prevention as used in this context refers
to institutional and regulatory programs to reduce the amount of con--
taminants reaching the drainage channels and to utilize depletion methods
which reduce the amount of runoff.
The plan presented in this section is specifically related to the Tulsa
urban area. It may be adopted for use in other areas if demonstrated
feasible. The course of action is presented as a list of recommendations
for consideration by the various public agencies and policymakers.
Preceding these recommendations are several facts concerning storm
water pollution in Tulsa.
Storm Water Pollution Facts
1. The average daily BOD population equivalent (0. 17 Ibs. BOD/day/
person) of storm water runoff in Tulsa is over 26, 000.
2. The average daily storm water pollution percentage contributions
of total pollutional load (storm water runoff plus municipal effluents)
are:
Pollutional Percentage
Parameter
BOD 20
COD 30
Suspended solids 85
Organic Kjeldahl nitrogen 30
Soluble orthophosphate 4
It should be noted that, as improved sanitary treatment facilities
are provided in the Tulsa area, the primary source of pollutional
loads to the receiving streams will be storm water runoff.
3. Approximately 52 rainfall events occur per year, causing a storm
water BOD load to the receiving streams of 160% of the average
daily BOD sanitary treatment plant effluent loads. This "shock"
load normally occurs in less than a two hour period.
4. The continued urbanization of the Tulsa area will cause an increase
in the volume of storm water runoff with its associated pollutional
314
-------
loads into the Arkansas River and Bird Creek, the major receiving
streams in the area. Of the two, the greater problem exists on
Bird Creek. At present, only about a third of the daily flows within
the creek are greater than the volumes of effluent discharged from.
the metropolitan sewage treatment plants within the basin. By 1990,
the daily flows within the creek will be exceeded 76% of the time by
the daily volume of sewage effluent. The construction of a proposed
dam in the upper Bird watershed should increase the amount of
flow within the creek and provide a greater degree of dilution. Such
a dam, however, would not alleviate the problem caused by storm
water runoff.
With more complete urbanization in the Tulsa portion of the basin,
shock loads of pollution from storm events will be added in larger
amounts and with greater frequency to the lower reaches of Bird
Creek. Consequently, the environs in the lower reaches of Bird
Creek will probably continue to remain in a poor ecological state.
5. The storm water additions to the Arkansas River should cause no
problems in the foreseeable future as long as the river remains in
its present state and no extreme condition develops which drastically
increases the amounts of pollution entrained in storm flows. If,
however, the River Lakes plan is implemented, the problems of
storm water pollution will have to be examined more critically,
as illustrated in Section 9 of this report.
After the first of the three dams of the River Lakes plan is con-
structed, an extensive program of sampling and evaluation should
be initiated, and corrective actions taken to lessen the impact of
storm water pollution.
Recommended Actions
1. Several methods for determining the amounts of pollution generated
on urban watersheds are presented elsewhere in this report.
It is recommended that one of these methods be adopted.
This would allow planners to make comparisons as to the
runoff- and pollution-producing capabilities from storm
events during the transition from a natural to an urbanized
watershed. These comparisons could be made for various
plans of land use and schedules of development.
315
-------
2. The study established the influential role that an impervious area
within a watershed exerts on the runoff regimen. Complete listings
of impervious area for each parcel in the Land Use Activity File
are not available.
It is recommended that information on streets, drives,
parking areas, roofs, and other man-made imperviousness
be maintained for each parcel. This information would
not only be helpful in determining the amount of storm water
pollution which could be expected from the parcel, but would
aid in the determination of peak rates of flow for the design
of culverts and floodways required to pass the flows. This
information could be used by the street department to plan
sweeping schedules and to estimate the effort required in
snow removal or sanding operations. Other uses of this
data could include parking surveys, estimations of the
cost for area renewal*and evaluation of the trends of land
use.
3. In any new program of water pollution control, it is necessary
to have an organization to review the nature and extent of the pro-
blem and to establish the guidelines under which the program can
best be financed, administered, and implemented.
It is recommended that the elected officials of the City of
Tulsa appoint a Storm Water Pollution Control Advisory
Council. This advisory council should be made up of in-
dividuals from the Tulsa Metropolitan Area Planning Com-
mission, Indian Nations Council of Governments, City
Engineering Department, County Engineering Department,
Tulsa City-County Health Department, local U. S. Soil
Conservation Service, Corps of Engineers, City of Tulsa
Water and Sewer Department, State Water Pollution Control
Board, and Tulsa Home Builders Association.
4. One of the major water pollution problems of urban areas was
visually observed throughout the project period. This problem
is that of silt and debris which washes into the storm drainage
channels and streams when natural cover is stripped from the
ground in preparation for construction. These source areas
include housing subdivision developments, expressway construc-
tion, renewal projects, and many others.
For example, in new subdivision developments and urban renewal
areas, the ground cover is usually removed for the purpose of
316
-------
laying sewer and storm water lines, constructing streets, and
grading building sites. After the cover is removed, the topsoils
are exposed, offering the potential of erosion by storm water
runoff. If precipitation occurs during the time the soil is exposed,
the runoff erodes and carries the loose soil into the drainage
system, thus causing a high suspended solids concentration. The
effects of this pollution are: (1) clogging of inlets, (2) filling
of catch basins, (3) reduction of the capacity of the drainage
structures, and (4) blockage and thus retention of storm water
contaminants. This type of pollution should be regulated at its
source by establishing specific regulations for builders, con-
tractors, and developers. A model program would be one that
would require the builders and developers to refrain from clearing
the land until it was absolutely necessary for a particular phase
of construction.
It is recommended that regulations be adopted by the City and
County Commission which would prevent and control this type
of water pollution. For example, specific items of erosion
control should be incorporated into the TMAPC's subdivision
regulations and also should be included in expressway con-
tracts. Specific community action guidelines for soil
erosion and sediment control have been published by the
National Association of Counties Research Foundation ( 22).
The guidebook presents the legal authority, planning,
personnel, and financing aspects of soil erosion and sediment
control. The material included in the manual describes a
model approach which, with appropriate modifications, should
be used by the City of Tulsa and Tulsa County to control
the solids pollutional load to the receiving streams. Many
aspects of the guidebook could be used for developing a com-
plete storm water pollutional control program.
In addition, on-site inspections of development and construction
activities must be provided for assurance of compliance with the
approved plans. These inspections should be housed in the
Protective Inspections Office of the City of Tulsa and in the County
Engineering Office. Permanent sediment control measures should
be made a part of the general maintenance operations of the local
government. In Tulsa these measures should be programmed as
part of the Storm Sewer Section of the City Engineer's Office. In
the county, these inspections should be accomplished by the County
Engineering Office.
317
-------
5. Economical incorporation of storm water pollution control
measures, especially soil erosion and control measures, can only
be accomplished in newly developing drainage sheds where no
storm drainage structures have been built or in urban renewal
areas where existing systems can be replaced. In the Tulsa
Metropolitan Area, the most logical places to start on such
programs are within newly developing basins.
It is recommended that the Tulsa Metropolitan Area embark
upon a program of incorporating storm water depletion and
control methods in all newly developing drainage basins and
urban renewal areas. Also, as economic feasibility permits,
control measures should be included into the open space and
parks program. Storm water depletion and control concepts
should be incorporated in several planned projects in
the Tulsa area. These projects are: (1) the Flat Rock Creek
Flood Plain Open Space Project, (2) the lower Joe Creek
Flood Prevention Project, and (3) urban renewal projects in
the Model Cities and West Bank areas.
The Tulsa Urban Renewal Authority should include storm
water pollution control measures as part of all its projects.
In the future, all Federally assisted projects may require
this type of control. Possible areas of demonstration are:
(1) rooftop or underground storage of storm water with
reuse of the captured water for lawn irrigation or other
non-potable uses, (2) small reservoirs for upstream retention
and treatment in blue-green recreational areas, and (3)
underground holding tanks for roof and parking areas.
6. After the alternatives for urban development within a watershed
have been established, appropriate strategies for controlling and
depleting storm water to minimize the pollutant load should be
structured. The evaluation of a workable plan for storm water
pollution abatement prior to development is the most economical
and desirable approach for a community. Coordination between
the planning and action agencies of the municipality and between
private interests is desired during the early phases of planning.
It is recommended that practices, either as agency operating
procedures or ordinances, be adopted to establish the responsi-
bilities of the public agencies and the landowners within each
basin in order to effect the utmost cooperation. The most
important factor for consideration is that of cost. Some
318
-------
system for the apportionment of costs for easements, con-
struction, and maintenance of the watershed drainage system
must be developed in accordance with the production and rate
of runoff and pollutants from the individual parcels. For
example, property owners within a hillside development
could be assessed a charge based on the runoff from the
impervious portions of their lots, the runoff from roads and
streets which connect their properties to the regional net-
work of highways, and the sediment hazard during construction
and development of the subdivi sion. Some other items to be
considered in the establishment of ordinances and standard
operating procedures are: the land uses to be allowed within
the drainageway and the method of policing these uses; the
responsibility for the maintenance of the drainage channel,
channel banks, and flood plains; and the responsibility for a
continuing evaluation of drainage system development within
the site and the effect of this development on the regional
system.
7. Numerous source areas of storm water pollution were found to be
located on commercial and industrial land. Many types of con-
taminants come into contact with storm water as it flows across
land parcels where raw and waste materials are stored in the
open and are unprotected from the elements. Open drainage
channels frequently run across the property where these sources
are located, and in some situations the channel is used as a "sink"
for disposing solid and liquid waste materials. These findings
were supported by the analytical observations from several test
areas, complaints received by the City Engineer and Health
Department, and on-site inspections.
It is recommended that a Commercial and Industrial Storm
Water Pollution Control Ordinance be prepared by an advisory
council and adopted by the City and County Commissions. This
ordinance should include a strong enforcement section.
8. The impervious areas of an urban community are the greatest
sources of storm water pollution. The primary source areas are
the streets. Secondary sources are large parking areas, sidewalks,
and roofs. Abating the contaminants at these sources is essential
for any degree of storm water pollution control.
It is recommended that programs be developed to increase
the "cleanliness" of these source areas. The street cleaning
effort should be increased. Performance standards of
cleanliness should be developed, adopted, and enforced for
319
-------
commercial and industrial areas.
9. Depressions in the drainage channels, as well as on the land
parcels, hold runoff water, thus allowing time for organic
matter to decompose. Because of the flushing action of
runoff water, substantial amounts of pollution are added to the
receiving streams.
It is recommended that these depressions in the drainage
channels and conduits (both natural and enclosed) be elimi-
nated by a planned program of improvement.
A possible approach would be that Model Cities incorporate
a storm drainage system cleanup and maintenance project
in their program. The work crews should be recruited from
the Model City Area in order to provide summer jobs for
high school students in the area and to accomplish an even
greater need--that of public awareness.
10. Tulsa is creating a model approach to the flood-control and
parks programs. This approach involves the creation of parks
for public use in the flood-plain zone of the remaining natural
streams adjacent to the urban area. The plan is intended to
accomplish two things: (1) to prevent flood damage to the public
sector by not allowing residential and commercial development
in the flood-plain area, and (2) to preserve natural resources
and to create recreational areas.
It is recommended that upstream control techniques be
included as part of the overall plan. Procedures and tech-
niques utilized by agricultural interests to reduce erosion
and runoff from crop land can be adapted for use in the up-
stream areas. The capture and storage of storm water
for reuse is a concept for control of storm water pollution
that offers the most tangible benefits. Runoff is collected
and diverted to storage basins dispersed throughout the
urban area. Possible uses of the captured runoff are: (1)
specialized industrial uses, (2) crop and lawn irrigation,
(3) recreational lakes and ponds, (4) ground water recharge,
and (5) non-potable domestic uses. The benefits derived
from the use of storm water can be used to offset the cost
of the storage and collection system.
Upstream control techniques would not only deplete the
urban runoff but possibly would offer some degree of treatment
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before the water was released to the receiving streams. If
upstream control programs are not included in the overall
plan, the recreational areas located in the flood plains
downstream, could become contaminated with pollutants from
the urban areas upstream. Including storm water control
measures would increase the benefits of the multi-purpose
plan and demonstrate the program's feasibility, thereby
encouraging its use in other municipalities. It is further
recommended that concepts for depletion and/or treatment
of storm water be considered in approving new development
in the Mingo and Haikey Creek Watersheds.
11. General "housekeeping" practices on commercial and industrial
lands need to be improved. The open storage of solid and liquid
wastes on these properties constitutes an important source of
storm water pollution.
It is recommended that proper ordinances and regulations be
adopted to regulate potential sources of pollution caused by the
present general storage practices for waste material and/or
raw material.
12. Contractors and builders dispose of their waste materials and
rubbish in the nearest depression, which, more times than not,
is the nearest drainage channel. Some of this material becomes
entrained as either suspended or dissolved solids in storm flows.
It is recommended that drainage channels be kept clear of
building debris. This is especially important at inlets or out-
lets to closed drainage systems.
13. Possible storm water treatment techniques applicable to completely
developed urban areas which already have a substantial invest-
ment in a storm drainage system need to be investigated. Several
methods involving gas transfer processes show promise. One is
the direct transfer of high purity oxygen to the receiving streams
and/or small metropolitan reservoirs to improve the assimilative
capacity and quality of streams and impoundments. Alternate
methods would be induced aeration using surface mechanical
aerators and diffusion (bubble) aeration or natural stream aeration
through construction of static devices in the stream channel area.
It is recommended that consideration be given for conversion
of the Flat Rock Creek and Coal Creek sanitary sewage treat-
ment plants into storm, water treatment facilities after the
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facilities are phased out and the sanitary flow diverted
to the North Side Plant. The plants could be converted into
high rate plastic media trickling filters, high rate sand
filters, dissolved air flotation units, or rotating filter units
for treating the "first flush" of storm water runoff. After
completing this task, the units could treat the partial flow
for the remainder of the storm. In addition, either chlori-
nation or ozonization could be provided to enhance the
bacterial quality of the plant effluent.
14. Because the general public as well as the commercial and
industrial sectors cause urban pollution, it is imperative that
they become involved in the remedial processes for abating urban
storm water pollution.
It is recommended that an extensive public awareness program
be initiated to inform the public of the problems and corrective
measures necessary to abate the sources of urban storm
water pollution. This should be done on the local level since
this level is closest to the problem. Possible instigators of
such programs are the Tulsa Metropolitan Area Planning
Commission, the Tulsa City-County Health Department, the
City Street Department and the City Engineer's Office.
15. It is quite obvious that the cost involved in reducing or treating
storm water pollution from urban runoff will be very high in most
instances. Therefore, the most economical solution may be
techniques involving control and treatment before the contaminants
are discharged directly into receiving waters.
It is recommended that planners and engineers of separate
storm water systems minimize the number of outfalls within
the limits of feasibility and practicality in order to reduce
the number of points of control, should such action be
necessary. For example, there are approximately 100 points
with storm water outfalls along the east bank of the Arkansas
River from the Sand Springs Bridge southward to 56th
Street.
Proposed Storm Water Demonstration Projects
The storm and combined sewer pollution control branch of the Federal
Water Quality Administration has listed pertinent areas of interest for
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research and development. In line with these research needs, problems
relevant to interest areas o£ local municipal agencies are presented in
this section. It is felt that these problems are important in the Tulsa
area and that they are worthy of further consideration as demonstration
projects by the agencies listed.
A. Tulsa Urban Renewal Authority
West Bank Project
1. Capture storm water runoff in a reservoir system for:
a. possible reuse by DX, Texaco, or Public
Service Company.
b. possible treatment by one of the refineries.
2. Demonstrate parcel storm water control techniques
in commercial or apartment areas by:
a. rooftop storage.
b. holding tanks for roof and parking areas.
c. small open reservoirs for upstream control
in blue-green areas.
B. Park Department and City Engineer's Office
Flat Rock Multi-Purpose Park and Storm Water Project
1. Plan storm water retention concepts in conjunction
with parks and demonstrate two debris control methods:
a. intensified street cleaning, general sanitary
parcel cleanliness, and drainage channel main-
tenance.
b. capture of debris at reservoir site by use of units
which utilize micro straining, rotating filters,
cyclones, or dissolved air flotation.
2. Demonstrate use of new material and/or construction
methods of storm, drains in Sunny Slope Addition (this
addition has no storm drains), or demonstrate an off-
system storage concept.
3. Demonstrate storm water rooftop collection and storage
in public buildings such as fire stations, public schools,
or sewage treatment plants. Costs and feasibility of
utilizing the captured runoff for non-potable uses can be
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determined in conjunction with the storage and collection
concepts.
4. Demonstrate in-line aeration or chlorination systems
for use in existing storm sewers.
C. TMAPC
Subdivision Regulations and Zoning
1. Develop extensive storm water quantity and quality
regulations for builders, contractors, and land developers.
2. Put together demonstration project which evaluates the
effectiveness of the new regulations. Expertise of other
action agencies of the city can be utilized in this phase.
D. Tulsa City-County Health Department
1. Develop commercial and industrial land "housekeeping"
regulations and enforcement procedures for open storage
of raw, finished, and waste products.
2. Evaluate the effectiveness of existing urban storm water
catchments and impoundments.
In addition, the Federal Water Quality Administration is very interested
in other storm and combined sewer demonstration projects. Problems
associated with "marginal" pollution, such as uncontrolled dispersed
loads from urban storm water runoff, can only increase as the percent
of total discharged municipal and industrial waste loads increases.
These sources must be recognized now and planning initiated to improve
the system efficiencies in order to bring storm water flows under
control.
Areas of other needed demonstration projects that have applications in
the Tulsa urban area are:
1. Improved catch basin design.
2. Use of new sewer (both sanitary and storm) sealants.
3. Sewer flushing solids control.
4. Sequential screening of storm water.
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5. Completely integrated control and treatment systems in
moderate-sized urbanizing drainage basin.
6. Effects of street cleaning on quality of urban runoff.
7. Demonstration of "flow-thru" storm water treatment
facility.
8. Use of seepage basin for treating runoff from the expressway
system--especially at large interchanges.
9. Assessment of techniques of urban land use modifications and
their application to control of urban runoff.
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BIBLIOGRAPHIC: Avco Economic Systems Corporation,
Storm Water Pollution from Urban Land Activity,
FWQA Publication No. 11034FKL07/70, 1970.
ABSTRACT: An investigation of the pollution concentrations and loads from
storm water runoff in an urban area was conducted in Tulsa, Oklahoma.
The scope of the project included: a field assessment of the storm water
pollution by obtaining samples of the water resulting from precipitation
and surface runoff from selected test areas within the metropolitan area;
development of an analytical procedure for correlation of storm water
pollution with selectively defined variables of land uses, environmental
conditions, drainage characteristics, and precipitation; and development
of a plan for implementing remedial measures necessary to abate or con-
trol sources of pollution in an urban area.
Storm water runoff samples were collected from 15 "discrete" test areas
in the Tulsa metropolitan area for laboratory analysis in terms of quality
standards for BOD, COD, TOC, organic Kjeldahl nitrogen, soluble ortho-
phosphate, chloride, pH, solids, total coliform,, fecal coliform, and
fscal streptococcus pollutants.
Selected land use parameters, environmental conditions, drainage and pre-
cipitation data, along with storm water pollution factors provided input data
for functional relationships to enable assessment of pollution from storm
water runoff.
Recommendations were made for a plan of action for preventing and con-
trolling storm water pollution from urban areas.
I-
ACCESSION NO:
KEY WORDS:
Storm Water Polluti.
Urban Runoff
Land Use Indicators
1.
I
I
BIBLIOGRAPHIC: Avco Economic Systems Corporation,
Storm Water Pollution from Urban Land Activity,
FWQA Publication No. 11034FKL07/70, 1970.
ABSTRACT: An investigation of the pollution concentrations and loads from
storm water runoff in an urban area was conducted in Tulsa, Oklahoma.
The scope of the project included: a field assessment of the storm water
pollution by obtaining samples of the water resulting from precipitation
and surface runoff from selected test areas within the metropolitan area;
development of an analytical procedure for correlation of storm water
pollution with selectively defined variables of land uses, environmental
conditions, drainage characteristics, and precipitation; and development
of a plaa for implementing remedial measures necessary to abate or con-
trol sources of pollution in an urban area.
Storm water runoff samples were collected from 15 "discrete" test areas
in the Tulsa metropolitan area for laboratory analysis in terms of quality
standards for BOD, COD, TOC, organic Kjeldahl nitrogen, soluble ortho-
phosphate, chloride, pH, solids, total coliform, fecal coliform, and
fecal streptococcus pollutants.
Selected land use parameters, environmental conditions, drainage and pre-
cipitation data, along with storm water pollution factors provided input data
for functional relationships to enable assessment of pollution from storm
water runoff.
Recommendations were made for a plan of action for preventing and con-
trolling storm water pollution from urban areas.
ACCESSION NO:
KEY WORDS:
Storm Water Pollutic
Urban Runoff
Land Use Indicators
BIBLIOGRAPHIC: Avco Economic Systems Corporation,
Storm Water Pollution from Urban Land Activity.
FWQA Publication No. 11034FKL07/70. 1970.
ABSTRACT: An investigation of the pollution concentrations and loads from
storm water runoff in an urban area was conducted in Tulsa, Oklahoma.
The scope of the project included: a field assessment of the storm water
pollution by obtaining samples of the water resulting from precipitation
and surface runoff from selected test areas within the metropolitan area;
development of an analytical procedure for correlation of storm water
pollution with selectively defined variables of land uses, environmental
conditions, drainage characteristics, and precipitation; and development
of a plan for implementing remedial measures necessary to abate or con-
trol sources of pollution in an urban area.
ACCESSION NO:
KEY WORDS:
Storm Water Pollutio
Urban Runoff
Land Use Indicators
Storm water runoff samples were collected from 15 "discrete11 test areas
in the Tulsa metropolitan area for laboratory analysis in terms of quality
standards for BOD, COD, TOC, organic Kjeldahl nitrogen, soluble ortho-
phosphate, chloride, pH, solids, total coliform, fecal coliform, and
fecal streptococcus pollutants.
Selected land use parameters, environmental conditions, drainage and pre-
cipitation data, along with storm water pollution factors provided input data
for functional relationships to enable assessment of pollution from storm
water runoff.
Recommendations were made for a plan of action for preventing and con-
trolling storm water pollution from urban areas.
L_.
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