FINAL REPORT
                OF THE


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111
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NATIONWIDE URBAN RUNOFF PROGRAM
              OFFICE OF WATER
       U.S. ENVIRONMENTAL PROTECTION
            WASHINGTON, D.C. 20460

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            FINAL REPORT
               OF THE
   NATIONWIDE URBAN RUNOFF PROGRAM
          December 30, 1983
       Water Planning Division
 Office of Water Program Operations

           OFFICE OF WATER
U.S. ENVIRONMENTAL PROTECTION AGENCY
       WASHINGTON, D.C.  20460

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                         DISCLAIMER

This  report  has been  reviewed  by  the  U.S.  Environmental
Protection  Agency  and  approved  for  release.   Approval  to
publish  does  not  signify  that  the  contents  necessarily
reflect any  policies  or decisions of  the  U.S.  Environmental
Protection  Agency  or any  of  its  offices,  grantees,  con-
tractors , or subcontractors.

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                                  FOREWORD

The U.S.  Environmental  Protection Agency was  created because  of increasing
public and government concern about environmental quality.  The complexity of
our environment and  the  interplay among its components  require concentrated
and integrated approaches to pollution problems.

The possible  deleterious  water quality effects  of nonpoint sources  in gen-
eral, and urban runoff in particular, were  recognized by the Water Pollution
Control Act  Amendments of  1972.   Because  of uncertainties  about the true
significance  of  urban runoff  as  a  contributor to  receiving  water  quality
problems,  Congress made treatment of  separate  stormwater discharges ineligi-
ble  for Federal  funding when  it  enacted  the  Clean  Water  Act in  1977.   To
obtain information that  would help  resolve these uncertainties,  the Agency
established the Nationwide  Urban  Runoff Program (NURP)  in  1978.   This five-
year program was  designed to examine such issues as:

        The quality characteristics of urban runoff,  and similarities or
        differences at different urban locations;

        The extent to which urban  runoff is a significant contributor to
        water quality problems across the nation; and

     -  The performance  characteristics and  the  overall effectiveness
        and utility of management  practices for the control of pollutant
        loads from urban runoff.

The interim NURP  report,  published in March 1982, presented preliminary find-
ings of the program.  This  document  is  the  final report covering the overall
NURP  program.   Several  specialized  technical  reports  are published  under
separate cover.
                                iii/iv blank

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                                   PREFACE

The Nationwide Urban Runoff Program  (NURP) was  conducted  by the EPA and many
cooperating federal, state, regional,  and local agencies, distributed widely
across the  United  States.   The individual  project studies,  which  were con-
ducted over the  past five years, were  designed and overseen using a common
technical team from EPA headquarters.  This  approach  was taken  to assure a
desired level of commonality and consistency in the overall program,  while
allowing each individual project to  specially tailor its  effort  to focus on
local concerns.

The program has yielded a great deal  of information  which will be useful for
a broad spectrum of  planning activities for many years.   Furthermore, it has
fostered valuable  cooperative  relationships among  planning  and regulatory
agencies.   The most tangible products  of the  program are  this  report, the
reports of  various  grantees  (available under  separate  cover),  and several
technical reports  which focus  on specialized  aspects of the program, its
techniques,  and  its findings.   In addition,  a considerable  number of  indi-
vidual articles drawing on information  developed under the NURP program have
already appeared in the technical  literature and  address specific technical
or planning aspects of urban runoff.

At the time of publication of this Final Report, the main technical effort of
the NURP program is complete;  the  field studies and the  analysis of most of
the resultant data  are  complete enough  that the findings  reported herein can
be taken with confidence.   However,  there is still  some  work in progress to
make certain details of the  program  available  for future use.  The products
of this on-going work include:

        A summary database which is being compiled to make all  technical
        information  from  the 28 projects  available  for  review and use
        (DECEMBER 1985);

     -  A technical report which focuses  on the  program's studies and
        findings relative to detention and recharge devices   (MAY 1984);

        A technical  report on urban  runoff effects on  the water quality
        of rivers and streams (MARCH 1984); and

        A technical  report on the effectiveness of street sweeping as a
        potential "best management practice" for water pollution control
        (MAY 1984).

This  report  and the  supplementary  technical  documents  identified  above,
supersedes  the  earlier   NURP  publication,  "Preliminary  Results  of  the
Nationwide  Urban  Runoff Program," March  1982.   Information  presented  there
has been expanded, updated, and in some cases revised.
                                 v/vi blank

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                              ACKNOWLEDGEMENTS

The Nationwide Urban Runoff Program was unusual in  its  large scale,  covering
a broad  spectrum  of technical and planning  issues  at many  geographic  loca-
tions.  Because the program placed such emphasis on tailoring the results to
support the planning process, it involved many participants  - some from EPA,
some  from  other federal  agencies,  and many  from  state, regional, and  local
planning agencies  and other consultants.

The program  was  developed,  implemented,  and managed by the  Water  Planning
Division, Office of  Water,  at EPA Headquarters, Washington, D.C.   Principal
contributors were:   Dennis N. Athayde, Program Manager;  and Patrice M. Bubar,
Norman A. Whalen,  Stuart S.  Tuller,  and Phillip H. Graham,  all of whom served
as Project Officers.  Additional contributions  from EPA personnel came from
Rod E. Frederick  and Richard P.  Healy (Monitoring  and  Data  Support Division),
Richard Field  (Storm and  Combined Sewer  Section,  EPA Office  of  Research and
Development), and  many project staff in the  various  EPA  Regional Offices.

As described elsewhere, much  of  the  field work, water  quality analysis, and
data  analysis  was  performed  by  the  U.S. Geological  Survey  (USGS),  under  a
Memorandum of  Agreement with  EPA.   Both  District Offices  and National  Head-
quarters participated actively.   The contributions of  Messrs. Ernest Cobb and
David Lystrom are  especially acknowledged.

Members of  the project team  which  provided essential  strategic,  technical,
and management assistance to  the EPA Water  Planning Division through a con-
tract  with Woodward-Clyde  Consultants were:   Gail B.  Boyd,  David Gaboury,
Peter Mangarella,  and James D. Sartor (Woodward-Clyde  Consultants); Eugene D.
Driscoll (E. D. Driscoll and  Associates); Philip E. Shelley  (EGSG Washington
Analytical Services Center,  Inc.); John L.  Mancini  (Mancini  and  DiToro Con-
sultants);  Robert E.  Pitt  (private  consultant);  Alan Plummer  (Alan  Plummer
and  Associates);  and  James P.  Heaney  and  Wayne  C.  Huber   (University  of
Florida).

The   principal writers   of  this   report   were   Dennis  N.  Athayde   (EPA),
Philip E. Shelley    (EGSG  Washington  Analytical    Services   Center,   Inc.),
Eugene D. Driscoll  (E.  D. Driscoll   & Associates) ,  and  David  Gaboury  and
Gail B. Boyd (Woodward-Clyde Consultants).
                               vii/viii blank

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                              TABLE OF CONTENTS

Chapter                                                                  Page
             Foreword	     iii
             Preface  	       v
             Acknowledgements 	     vii
             Executive Summary (Bound Separately)
   1         INTRODUCTION 	     1-1
   2         BACKGROUND	     2-1
             Early Perceptions	     2-1
             Conclusions From Section 208 Efforts 	     2-2
             EPA's ORD Effort	     2-3
             Other Prior/Ongoing Efforts  	     2-4
             Discussion	     2-5
             The Nationwide Urban Runoff Program  	     2-6
   3     .    URBAN RUNOFF PERSPECTIVES  	     3-1
             Runoff Quantity  	     3-1
             Water Quality Concerns 	     3-3
             Water Quantity and Quality Control 	     3-3
             Problem Definition 	     3-5
   4         STORMWATER MANAGEMENT  	     4-1
             Introduction 	     4-1
             Stormwater Management Planning 	     4-1
             Financial and Institutional Considerations 	     4-6
             Relationship Between NURP and WQM Plans	    4-17
                                     IX

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                         TABLE OF CONTENTS  (Cont'd)

Chapter                                                                  Page
   5         METHODS OF ANALYSIS	     5-1
             Introduction  	     5-1
             Urban Runoff  Pollutant Characteristics  	     5-2
             Receiving Water Quality Effects   	     5-7
             Evaluation of Controls	    5-18
   6         CHARACTERISTICS OF URBAN RUNOFF   	     6-1
             Introduction  	     6-1
             Lognormality  	     6-2
             Standard Pollutants  	     6-9
             Priority Pollutants  	    6-44
             Runoff-Rainfall Relationships  	    6-57
             Pollutant Loads  	    6-60
   7         RECEIVING WATER QUALITY EFFECTS OF URBAN RUNOFF   ....     7-1
             Introduction	     7-1
             Rivers and Streams	     7-2
             Lakes	    7-21
             Estuaries and Embayments  	    7-23
             Groundwater Aquifers 	    7-24
   8         URBAN RUNOFF  CONTROLS  	     8-1
             Introduction  	     8-1
             Detention Devices   	     8-2
             Recharge Devices 	    8-14
             Street Sweeping  	    8-17
             Other Control Approaches  	    8-22
   9         CONCLUSIONS   	     9-1
             Introduction  	     9-1
             Urban Runoff  Characteristics  	     9-1
             Receiving Water Effects   	     9-6
             Control Effectiveness  	    9-12
             Issues	    9-15

             Data Appendix (Bound Separately)

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                               LIST OF FIGURES
Figure                                                                   Page
2-1          Locations of the 28 NURP Projects	     2-7
4-1          Typical Changes in Runoff Flows Resulting
             from Paved Surfaces	     4-2
4-2          Incomplete Water Quality Planning  	     4-6
4-3          Integrated Water Quality Planning  	     4-8
4-4          Preliminary Matrix for Section of a Control
             Approach (Combined Sewer Overflows)  	     4-8
4-5          Major Components of a Financial Institutional Data .  .  .     4-9
4-6          Institutional Assessment for Educational Program
             to Control Chemical Substances 	    4-14
4-7          Cost Analysis for Educational Program to Control
             Chemical, Herbicide, Fertilizer and Pesticide
             Runoff	    4-15
4-8          Ability to Pay Analysis for Educational Program to
             Control Chemical, Herbicide, Fertilizer and
             Pesticide Runoff 	    4-16
5-1          Lognormal Distribution Relationships   	     5-5
5-2          Idealized Representation of Urban Runoff
             Discharges Entering a Stream 	    5-14
6-1          Cumulative Probability Pdf of Total Cu at
             C01 116 and Claude Site	     6-5
6-2          Cumulative Probability Pdf of Total Cu
             at TNI SC Site	     6-6
6-3          Cumulative Probability Pdf of Total Cu at
             NH1 Pkg. Site	     6-8
6-4          Range of TSS EMC Medians (mg/1) by Project	    6-21
6-5          Range of BOD EMC Medians (mg/1) by Project	    6-21
6-6          Range of COD EMC Medians (mg/1) by Project	    6-22
6-7          Range of Total P EMC Medians (mg/1) by Project 	    6-22
6-8          Range of Soluble P EMC Medians (mg/1) by Project ....    6-23
6-9          Range of TKN EMC Medians (mg/1) by Project	    6-23
6-10         Range of NO   -N EMC Medians (mg/1) by Project	    6-24
                                     XI

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                          LIST OF FIGURES (Cont'd)

Figure                                                                   Page
6-11         Range of Total CU EMC Medians (yg/1) by Project  ....    6-24
6-12         Range of Total Pb EMC Medians (yg/1) by Project  ....    6-25
6-13         Range of Total Zn EMC Medians (yg/1) by Project  ....    6-25
6-14         Range of Normalized EMC Medians at Denver (CO1)  ....    6-27
6-15         Range of Normalized EMC Median at FL1 and DC1	    6-29
6-16         Range of Normalized EMC Medians at IL1	    6-30
6-17         Box Plots of Pollutant EMCs for Different
             Land Uses	    6-33
6-18         Site Median Total P EMC Probability Density
             Functions for Different Land Uses	    6-36
6-19         Relationship Between Percent Impervious Area
             and Median Runoff Coefficient  	    6-59
6-20         90 Percent Confidence Limits for Median
             Runoff Coefficients  	    6-61
7-1(a)       Regional Value of Average Annual Streamflow
             (cfs/sq mi)   	     7-4
7-1(b)       Regional Value of Average Storm Event
             Intensity  (inch/hr)  	•	     7-4
7-2          Regional Values for Surface Water Hardness 	     7-6
7-3          Geographic Regions Selected for Screening
             Analysis	     7-8
7-4          Probability Distributions of Pollutant
             Concentrations During Storm Runoff Periods 	    7-11
7-5          Recurrence Intervals for Pollutant Concentrations  .  . .    7-11
7-6          Exceedance Frequency for Stream Target
             Concentration  (Copper) 	    7-14
7-7          Exceedance Frequency for Stream Target
             Concentration  (Lead) 	    7-15
7-8          Exceedance Frequency for Stream Target
             Concentration  (Zinc) 	    7-16
7-9          Effect of Urban Runoff on Lake Phosphorus
             Concentrations 	    7-22
8-1          Regional Differences in Detention Basin
             Performance	     8-6
8-2          Average Stormwater Management  (Dry) Pond
             Construction Cost Estimates Vs. Volume of Storage  .  . .    8-12
8-3          Cost of Urban Runoff Control Using Wet
             Detention Basins  	    8-13

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                          LIST OF FIGURES  (Cont'd)
Figure
8-4
8-5

8-6
8-7
Long Term Average Performance of Recharge Devices
Page
8-16
Table
 2-1
 5-1
 6-1
 6-2
 6-3
 6-4
 6-5
 6-6
 6-7
 6-8
 6-9
 6-10
 6-11
 6-12
 6-13

 6-14
 6-15
 6-16
 6-17
Bivariate Plots of Median EMCs for Swept and
Unswept Conditions 	     8-20
Street Sweeping Performance   	     8-21
Effect of Street Sweeping on  Site Median EMC
Values	     8-23


                  LIST OF TABLES

                                                             Page
NURP Project Locations 	      2-7
Summary of Receiving Water Target Concentrations
Used in Screening Analysis -  Toxic Substances
(All Concentrations in Micrograms/Liter, yg/Jl)  	     5-12
Site Mean TSS EMCs (mg/Jl)	     6-10
Site Mean BOD EMCs (mg/Jl)  	     6-11
Site Mean COD EMCs (mg/Jl)  	     6-12
Site Mean Total P EMCs (yg/Jl)  	     6-13
Site Mean Soluble P EMCs  (yg/Jl)  	     6-14
Site Mean TKN EMCs (yg/Jl)  	     6-15
Site Mean Nitrite Plus Nitrate EMCs  (yg/Jl)	     6-16
Site Mean Total Copper EMCs  (yg/Jl)	     6-17
Site Mean Total Lead EMCs  (yg/Jl)	     6-18
Site Mean Total Zinc EMCs  (yg/X.)	     6-19
Project Category Summarized by Constituent  	     6-26
Median EMCs for All Sites by  Land Use Category  	     6-31
Number of Significant Linear  Correlations
By Constiuent	     6-38
Sign of Correlation Coefficients by  Sites   	     6-39
Correlation Coefficient Values by Site  	     6-40
Sites With Many Significant Correlations	     6-42
Water Quality Characteristics of Urban  Runoff   	     6-43
                                    Xlll

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                           LIST OF TABLES (Cont'd)

Table                                                      '              Page
 6-18        Fecal Coliform Concentrations in Urban Runoff  	    6-45
 6-19        Summary of Analytical Chemistry Findings From
             NURP Priority Pollutant Samples1 	    6-47
 6-20        Most Frequently Detected Priority Pollutants
             in NURP Urban Runoff Samples1	    6-51
 6-21        Summary of Water Quality Criteria Exceedances For
             Pollutants Detected in at Least 10 Percent of
             NURP Samples:  Percentage of Samples in Which
             Pollutant Concentrations Exceed Criteria1  	    6-53
 6-22        Infrequently Detected Organic Priority
             Pollutants in NURP Urban Runoff Samples1 	    6-55
 6-23        Runoff Coefficients for Land Use Sites	    6-58
 6-24        EMC Mean Values Used in Load Comparison	    6-60
 6-25     .   Annual Urban Runoff Loads KG/HA/Year 	    6-64
 7-1         Average Storm and Time Between Storms for
             Selected Locations in the United States  	     7-3
 7-2       "  Typical Regional Values  	     7-7
 7-3         Urban Runoff Quality Characteristics Used in
             Stream Impact Analysis (Concentrations in ug/1)   ....     7-9
 7-4         Regional Differences in Toxic Concentration
             Levels  (Concentrations in yg/1)  	    7-13
 8-1         Detention Basins Monitored by NURP Studies 	     8-3
 8-2         Observed Performance of Wet Detention Basins
             Reduction in Percent Overall Mass Load	     8-5
 8-3         Observed Performance of Wet Detention Basins
              (Percent Reduction in Pollutant Concentrations)   ....     8-8
 8-4         Performance Characteristics of a Dual-Purpose
             Detention Device 	    8-10
                                     xiv

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                                  CHAPTER 1
                                INTRODUCTION
Rain falling  on an urban  area results  in  both benefits and  problems.   The
benefits  range  from  watering vegetation  to  area cleansing.   Many of  the
problems  are  associated with  urban  runoff, that  portion of  rainfall  which
drains  from  the urban  surfaces  and  flows  via natural or man-made  drainage
systems into receiving waters.

The  historical  concern with  urban  runoff has  been  focused primarily  on
flooding.  Urban development has the  general effect of reducing pervious land
surface area and increasing the  impervious  area (such as  roof tops,  streets,
and sidewalks) where water cannot infiltrate.  In comparison with an undevel-
oped area  (for  a  given storm event) ,  an urban area will yield more runoff,
and it will occur more quickly.  Such increases in the rate of flow and total
volume often have a decided effect on  erosion  rates  and flooding.   It is not
surprising, therefore,  that at the local level the quantity  aspect continues
to be a principal concern.

In recent  years,  however,  concern with urban  runoff  as a contributor to re-
ceiving water quality  problems  has been expressed.   Section 62  of the Water
Quality Act of  1965  (P.L.  89-234)  authorized  the  Federal government to make
grants for the purpose of "assisting in  the development of  any project which
will demonstrate  a new or improved method  of  controlling the discharge into
any water  of untreated or  inadequately treated  sewage or  other  waste  from
sewerage  which  carry  storm  water or  both  storm  water and  sewage  or  other
waste  ..."   The  Federal  Water Pollution  Control  Act  Amendments  of  1972
(P.L. 92-500) signaled  a heightened national awareness of the degraded state
of the nation's surface waters and a  Congressional intent that national water
quality goals be pursued.   The scarcely two-year old Environmental Protection
Agency built upon its predecessors' activities by taking up the challenge and
implementing this far reaching legislation.

As a result of Section  208 of The Act,  State and local water quality manage-
ment  agencies were  designated to integrate  water  quality activities.   As
point source discharges were increasingly brought under control and funds for
the  construction  and  upgrading of  municipal   sewage  treatment plants  were
granted,  the awareness of  nonpoint  sources   (including urban  runoff)  as
potential  contributors  to  water quality degradation  was  heightened.  Uncer-
tainties associated with  the local nature  and extent of urban  runoff  water
quality  problems,  the effectiveness   of  possible  management  and  control
measures,  and their affordability in terms  of  benefits to be derived mounted
as water quality management plans were developed.  The unknowns were so great
and certain control cost  estimates were so  high that  the Clean Water Act of
1977  (P.L. 95-217)  deleted  Federal  funding  for  the  treatment of  separate
stormwater discharges.  The Congress stated that there was  simply not enough
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known about urban runoff loads, impacts, and controls to warrant making major
investments in physical control systems.

In 1978, EPA Headquarters reviewed the results of work on urban runoff by the
technical community and the various 208 Areawide Agencies and determined that-
additional, consistent data were needed.  The NURP program was implemented to
build upon pertinent  prior  work  and  to provide practical information and in-
sights to  guide  the planning process, including policy  and program develop-
ment  and  implementation.   The  NURP  program included  28 projects,  conducted
separately  at the  local  level,  but  centrally  reviewed,  coordinated,  and
guided.  While these  projects were separate  and distinct, most share certain
commonalities.  All were involved with one or more of the following elements:
characterizing pollutant  types,  loads, and effects  on  receiving  water qual-
ity;  determining  the need  for  control;  and evaluating  various  alternatives
for the control of stormwater pollution.  Their emphasis was on answering the
basic questions underlying  the NURP  program  and providing practical informa-
tion needed for planning.
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                                  CHAPTER 2
                                 BACKGROUND
EARLY PERCEPTIONS

As noted earlier, drainage is perhaps the single most important factor of the
urban hydrologic  cycle.   Nuisance flooding,  more than  anything  else, gives
Public  Works  directors  concern,  as  complaints  are  received from unhappy
motorists, residents, and business.  Drainage has typically been considered a
local responsibility, usually that of the City or County Public Works Depart-
ment.  Rarely does this responsibility go  to the State or Federal level, ex-
cept  in cases  of catastrophic  flooding involving  risk  to  human  life and
extensive property damage.

By  1964,  the U.S.  Public Health  Service  had begun  to be  concerned about
identified pollutants  in  urban runoff and  concluded that there  may be sig-
nificant water quality problems associated  with stormwater runoff.  In 1969,
the Urban Water Resources Research Committee of the American Society of Civil
Engineers  (directed  by M.  B.  McPherson  and sponsored by the  U.S. Geological
Survey)  recognized the  potential threat of pollution from urban runoff and
described.a research program  intended to obtain  needed  information to char-
acterize urban stormwater quality.

In the late 1960's, the Federal Water Quality Administration  (FWQA) conducted
a  study in an  area  of Tulsa,  Oklahoma  which  was  served by  separate storm
sewers.   This first  attempt at using  regression analysis on urban runoff in-
dicated that there was only a very poor correlation between stormwater runoff
quantity and water quality constituents  (except for  suspended solids).  Com-
paring the concentrations of  various  pollutants examined by this study  (sep-
arate storm sewers)  with previous  data on  combined  sewer overflows indicated
that storm runoff from areas having separate sewers had much lower values for
BOD, fecal coliform,  and most other pollutant concentrations.  The study con-
cluded  that the largest portion of  pollutants resulted  from (1) washoff of
material  from  impervious  surfaces and  (2)  the erosion  of drainage channels
(caused by high volumes of runoff  from the impervious surfaces).  Control of
urban runoff was recommended to reduce both runoff volume and rates.

Atlanta, Georgia  is  an example of  a  city that has both a combined sewer sys-
tem and a separate system.  In 1971,  EPA conducted a study which compared the
contribution of various sources of pollutants.   It  was concluded that, on an
annual basis,  64 percent of the BOD load came from separate storm sewers, and
19 percent  came  from  combined  sewers,  the balance  coming  from treatment
plants.

In  1971,  EPA  also conducted a study  in  Oakland and  Berkeley, California, to
assess the infiltration of stormwater into  sanitary  sewers.   While only four
                                      2-1

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percent of the  study  area had combined sewerage and the remaining 96 percent
separate, the study made  it clear that infiltration can cause a separate sys-
tem to function as though it were combined.

Studies in Sacramento, California, which has both combined and separate storm
sewers, indicated that  the stormwater was  comparable to the average strength
of domestic wastewater.   However, the concentrations for BOD were found to be
so unrealistically  high,  that  contamination of  the runoff by  raw sanitary
sewage was considered to  be a distinct possibility.

In  1973,  the  Council on Environmental Quality  published a  report titled,
"Total Urban  Pollutant Loads:  Sources and  Abatement  Strategies."   The pri-
mary  conclusion was  that much pollution  was  coming  from urban runoff and
that, unless it was taken care of, the goals of the Act would not be met.

CONCLUSIONS FROM SECTION  208 EFFORTS

EPA  guidance  for  conducting  the  early   208 planning  efforts  designated
17 topic  areas (including urban  runoff)   that  were to  be addressed  by all
Water Quality  Management agencies  in developing their 208-funded plans.  Al-
though all topic areas were to be covered, the degree of emphasis to place on
each was  left  to  the  individual agencies  to decide.  As a result, the amount
of the 208 efforts spent in the area of urban runoff varied greatly (but was
rarely a major portion).

Many of the  208 agencies began their studies with  the  assumption that urban
runoff  was  an important cause of  water  quality  problems.   Although  the
studies developed much information on runoff and .receiving waters, not enough
basic information was known to assess urban  runoff's role as a major cause of
problems.  This was partly because of interferences by other sources and com-
plex  relationships  within the receiving  waters.   It  was  also  due  to the
difficulties in deciding  what constitutes a  "problem."  In some cases, "prob-
lems" were  synonymous with  criteria violations; in others,  "problems" were
synonymous with an  impairment or denial of  beneficial  uses.   In many cases,
"problems"  were concluded to exist,  simply on the basis  of  the possible
presence  of certain  contaminants  in  urban runoff, based solely  on  values
taken from  literature regarding studies conducted  elsewhere.   The practical
implication of these differences (which were differences in viewpoints rather
than differences  in physical conditions,  in many cases) was that local agen-
cies were very reluctant  to commit  to  implementing urban  runoff controls in
the absence of a clear problem definition.

Furthermore, in the early years of  the 208 program, EPA's  guidance  on how to
address urban runoff was  vague.  As  a result, local agencies took a wait-and-
see attitude  on the stormwater portion of their  plans.  They  simply did not
know what EPA would eventually do on  the issue of stormwater control.

Another major  obstacle  to implementation  resulted from the uncertainties re-
garding  the effectiveness of controls.  Many  of the  measures  proposed for
controlling  urban runoff  are  either new  or  special applications of conven-
tional practices  developed for other purposes.  Little was known  about how
                                       2-2

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well  they  would  work in  urban runoff  applications.   Engineers,  planners,
public works  personnel,  and other decision  makers have  been understandably
reluctant to invest large amounts of time and money in controls which may not
perform as hoped.

Another obstacle  to  implementation of controls was  a  lack of  basic  data on
sources, transport mechanisms,  and  receiving water characteristics  (hydro-
logic  and  water quality  aspects).   Some of  the  more important  topic  areas
where knowledge was lacking are summarized below:

        Sources - Not enough was known about where pollutants originate.
        Major sources  certainly include vehicles, vegetation,  erosion,
        fertilizer and pesticide  application, litter, animals,  and air
        pollution.  However,  a better  understanding of  source contri-
        butions could enhance control opportunities.

     -  Washoff/transport mechanisms -  Not enough was  known  about how
        pollutants get from the sources to the receiving waters.  Models
        could be better used for simulating runoff in problem definition
        and control evaluation, if they more accurately  reflected wash-
        off and transport mechanisms.

        Impacts - It was difficult to go beyond speculation in assigning
        urban runoff its proper share of responsibility  for problems in
        cases  where   several  pollutant  sources  contribute.    In  cases
        where other sources create obvious problems,  it was difficult to
        determine the appropriate degree to which urban runoff should be
        controlled.

        Relative benefits - Planners had difficulty deciding whether the
        various benefits of controlling urban runoff quality justify the
        costs  involved.   There  was  considerable  controversy  over the
        present dry weather standards'  relationship  to  beneficial uses,
        given the time and space scales of storm events and their inter-
        mittent nature.  Many plans  failed to be  implemented because of
        uncertainties  regarding:    How  much  control  is  enough?   Who
        benefits?  Who should pay?  Who should decide?

        Controls - Both  cost  and effectiveness data on  full-scale con-
        trol programs were lacking.  Some of the  control  measures cited
        for  typical   208 plans were plausible  candidates,  but  their
        application for  the  purpose of  urban runoff pollution control
        had not been studied quantitatively.

EPA'S ORD EFFORT

During the past  15 years, EPA's Office  of Research and Development (ORD) has
conducted over 250 studies on the  characterization and  control of stormwater
discharges  and combined  sewer overflows, with particular  emphasis on the
latter  due  to their  greater pollution  potential.  Consistent  with  overall
Agency policies, ORD has  deemphasized  studies on  receiving water impacts and
effects  (although it  has  done some  such work) .  Rather,  ORD  has focussed
principally  on multi-purpose  analyses   and  controls,  because  it  is  nearly
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impossible  to  segregate benefits  and strategies of  urban stormwater runoff
pollution control  from drainage, flood, and  erosion  control.   Many signifi-
cant results have  been obtained by ORD's  effort,  which has dramatically in-
creased the technical  literature in the area.

Data from ORD  studies indicate the high variability  of pollutant concentra-
tions in urban runoff.   Based  on loading projections, it is safe to conclude
that urban stormwater  can contribute  significant pollutant loads to receiving
waters,  in  many  cases having  pollutant  concentrations  on  the  order  of
secondary treatment plant  effluent  for some  constituents.   Nonetheless,  in
its  efforts to  find  direct urban  runoff  generated  receiving  water impacts
(using the  conventional  dissolved  oxygen parameter as the indicator)  ORD has
been only partly successful.  However, this  was only one  study  and  was not
intended to  be the final word.   Nonetheless, based  on  the  size  of the load
coming from  urban  runoff,  a significant pollution potential  is there for at
least some  types of receiving  waters.  For example,  a small urban lake could
receive nutrient loads sufficient to increase  algal  productivity and accel-
erate the eutrophication process.   The  existence of  heavy metals and certain
organics  (mostly of petroleum origin)  in  urban runoff  have  also  been docu-
mented by the ORD program.

In addition to studying  urban  runoff  loads,  the ORD program has investigated
a  number  of management  and control  approaches.   This  effort  has  been very
successful,  and  many  innovative techniques  have  been  proposed  and tested.
The results of such research,  development, and demonstrations have been pre-
sented in  reports  which document  many  of these potential controls,  thereby
allowing the technology to be utilized in other programs and at other loca-
tions .  Included have  been  such  control measures as  on-site  (upstream) stor-
age; porous pavement;  the swirl concentrator, helical bend, tube settler, and
fine mesh  screens  for  grit and settleable solids removal;  street sweeping;
disinfection;  and  high rate filtration, dissolved air flotation,  and micro-
screening for suspended  solids and BOD  removal.  Most of these controls were
developed principally to deal with combined  sewer overflow problems.  How-
ever, some may also have application  in urban runoff control, once their ef-
fectiveness has  been conclusively demonstrated  and initial and operating cost
data are available to  allow the necessary trade-off studies to be made.

The ORD program's  reports  constitute  an invaluable source of data and infor-
mation that was  used to  design and guide the  development of the emerging NURP
program.  Also,  three  of the NURP projects were joint efforts with ORD  (i.e.,
West Roxbury, Massachusetts, Bellevue, Washington, and Lansing, Michigan).

OTHER PRIOR/ONGOING EFFORTS

The Clean Water  Act requires EPA to provide  Congress  with a needs assessment
every two  years  in the  six categories  of the  construction  grant funds pro-
gram.  In  1974,  the Needs   Survey  for Separate Storm  Sewer Discharges  (Cate-
gory VI) was done  by  each  state.  Using the goals of the Act as the criteria
to be met,  they  identified  a cost of  about $235 billion  (June 1973 dollars).
One  state  alone identified $80 billion in  needs  to  control  separate storm
sewer discharges.   In  1976,  the Needs Survey  was conducted by the Agency, and
it was found that  Category  VI  would require $66 billion  to meet the goals of
                                       2-4

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the Act.  This survey broke the goals into three categories or levels of pol-
lution abatement;  (1) aesthetics,  (2)  fish  and wildlife,  and  (3) recreation.
Costs to meet each category were determined.

As  noted previously, the  ASCE  defined  a  program in  1969 to  identify the
causes and  effects of urban stormwater pollution.   The recommendations were
not followed, so in 1974 at the Rindge, New Hampshire, Engineering Foundation
Conference  (jointly  sponsored  with  ASCE's Urban  Water  Resources  Research
Council), a  similar program was  again recommended.  A similar  scenario oc-
curred  at  the Easton,  Maryland, conference  of 1976  sponsored by  the same
group.

DISCUSSION

In the past  (ca  1890) ,  dilution was considered to be  the  appropriate way to
control  combined sewer overflows,  since the  primary  concern was  odor and
related nuisances.  Between 1890 and 1960 little concern was shown for storm-
water  pollution.   Stormwater  concerns were  primarily  related  to  drainage
problems.   As  time  progressed,  water quality began  to  be  considered, and
workers began to characterize problems in terms of concentrations of certain
pollutants and loads of these pollutants.   In the 1970's, problems were being
defined  in  terms of  pounds  of pollutants  needing to be  removed from over-
flows, in the interest of preventing pollution.

Past work, reported by  EPA and  published  in professional journals, tended to
focus  on determining (a)  the type  and amount of  pollutants  involved and/or
(b) methods to reduce the  loads.  However,  such reports and articles did not
consider either  the level of improvement attainable or the  need to improve
quality of the receiving water  body associated with the study.  A conclusion
common to all such  reports was  that not enough was known about stormwater to
adequately understand cause  and  effect  relationships.  Also  common to such
reports  were  recommendations for  further  study and more  data.   A tangible
result of the lack  of belief and uncertain  attitude in this area is the fact
that stormwater  controls  for water quality have  been implemented  in so few
places throughout  the nation.   Thus,  there has been a critical  need to ob-
jectively examine the situation.

Many  factors  led to  the  development  of NURP, one  being  a legally-mandated
necessity.  As implementation of  P.L.  92-500 moved into full swing, the lack
of progress in the area of urban runoff was becoming  apparent.   In 1974 EPA
lost a  court  case,  which led to  the  decision that  EPA should issue permits
for separate storm sewer discharges.  In 1976 EPA requested that the Areawide
Waste Management Planning  Program focus  on  the three  or  four most important
of the 17 items  required by  the regulations.   Many of the 208 Areawide Agen-
cies cited urban runoff as an important item.

Two years later, EPA  reviewed  ninety-three  208 Areawide Agencies' work plans
to assess their  basis for  having identified urban runoff  as  an element upon
which  they would focus.   Review of these projects'  methods and findings did
not provide  much to  further our understanding of the pollution  aspects of
urban  runoff.   If  one  reason  can  be  identified,  it  was  the  lack  of site-
specific data to define the local conditions.
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As mentioned  earlier,  the Rindge Conference  recommended a candidate program
for obtaining the data necessary to  provide  a good  understanding  of storm-
water pollution  (EFC/ASCE,  1974).   It is not  coincidental that the NURP pro-
gram is quite similar in design to those recommendations.

THE NATIONWIDE URBAN RUNOFF PROGRAM

Program Design

NURP was not  intended  to  be a research program, per se, and was not designed
as such.   Rather, the program -was  intended  to be a  support  function which
would  provide  information  and  methodologies  for  water quality  planning
efforts.  Therefore, wherever possible, the projects  selected were ones where
the work undertaken would complete  the urban  runoff elements of formal water
quality management plans  and the results  were likely  to  be  incorporated in
future plan updates and lead to implementation  of management recommendations.
Conduct of  the  program provided direction and  assistance  to  28 separate and
distinct  planning projects,  whose  locations  are shown  in  Figure  2-1  and
listed in Table 2-1, but  the  results  will  be  of value to many other planning
efforts.  NURP  also acted as  a clearinghouse  and, in that capacity, provided
a common communication link to and among the  28 projects.

The NURP  effort began with a careful  review of what  was  known  about urban
runoff mechanisms, problems,  and  controls,   and  then built upon  this base.
The twin  objectives of the  program were to  provide  credible  information on
which Federal, State, and local  decision makers could base future urban run-
off management decisions  and to  support both planning  and  implementation
efforts at the 28  project  locations.

An early step in implementing the NURP  program  involved identifying a limited
number of  locations where intensive data gathering and study  could be done.
Candidate locations were assessed relative to three basic  selection criteria:

     -  Meeting program objectives;

     -  Developing implementation plans for those areas; and

     -  Demonstrating  transferability,  so that  solutions  and knowledge
        gained  in  the  study area could be applied in other areas, with-
        out need for intensive, duplicative data gathering efforts.

The program design used for NURP included providing a full range of technical
and management assistance  to each project as  the needs  arose.  Several forums
for the communication of  experience and sharing of data were provided through
semi-annual meetings involving participants from all  projects.  The roles and
responsibilities of the various  State,  local, and regional agencies and par-
ticipating  Federal agencies  were  clearly  defined and communicated  at  the
outset.   These were  reviewed and  revised where  warranted as  the projects
progressed.
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Figure 2-1.  Locations of the 28 NURP Projects
      TABLE 2-1.  NURP PROJECT LOCATIONS
EPA
Region
I



II




III


IV




NURP
Code
MAI

MA2
NH1
NY1

NY2
NY3

DC1

MD1
FL1
NCI
SCI
TNI

Project Name/Location
Lake Quinsigamond
(Boston Area)
Upper Mystic (Boston Area)
Durham, New Hampshire
Long Island (Nassau and
Suffolk Counties)
Lake George
Irondequoit Bay (Rochester
Area)
WASHCOG (Washington, D.C.
Metropolitan Area)
Baltimore, Maryland
Tampa, Florida
Winston-Salem, North Carolina
Myrtle Beach, South Carolina
Knoxville, Tennessee

EPA
Region
V





VI

VII
VIII


IX


X

NURP
Code
IL1
IL2
Mil
MI2
MI3
WI1
AR1
TX1
KS1
C01
SD1
UT1
CA1

CA2
OR1
WAI
Project Name/Location
Champaign-Urbana, Illinois
Lake Ellyn (Chicago Area)
Lansing, Michigan
SEMCOG (Detroit Area)
Ann Arbor, Michigan
Milwaukee, Wisconsin
Little Rock, Arkansas
Austin, Texas
Kansas City
Denver, Colorado
Rapid City, South Dakota
Salt Lake City, Utah
Coyote Creek
(San Francisco Area)
Fresno, California
Springfield-Eugene, Oregon
Bellevue (Seattle Area)
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The 28 NURP projects  were managed by designated State, county,  city,  or re-
gional  governmental  associations.   The  U.S. Geological  Survey  (USGS)  was
involved with  EPA as  a cooperator,  through an  inter-agency  agreement,  on 11
of the  NURP projects.  The  Tennessee  Valley Authority was  also involved in
one project.

A major objective of  the  program was the acquisition of data.  Because these
data will  be  used for  several  years to characterize problems,  evaluate re-
ceiving water  impacts from urban runoff,  and evaluate  management practices,
consistent  methods of  data collection  had to  be developed  and rigorously
employed.

Project Selection

Projects were  selected from  among  the  93 Areawide  Agencies that  had  iden-
tified urban runoff as  one of  their significant problems.   The intention was
to build upon  what these  agencies  had  already  accomplished  in their earlier
programs.  Also,  projects  that  would be a  part  of  this  program were screened
to be  sure that  they represented  a broad range  of  certain characteristics
(e.g., hydrologic regimes, land  uses,  populations,  drainage  system types).
Actual  selection  of  projects  was  a  joint effort among  the  States,  local
governments,  and  Regional EPA  offices.   The  five  major  criteria used to
screen candidate  projects  were  as follows:

     1.  Problem  Identified.   Had  a  problem relative  to urban runoff
         actually been  identified?   Could  that  problem  be  directly
         related  to separate storm  sewer discharges?   What pollutant or
         pollutants were  thought to be  causing  the  problem?  Using the
         NURP  problem identification categories, what was the "problem"
         (i.e.,   denying   a  beneficial  use,  violating a  State  water
         quality  standard, or public concern)?

     2.  Type  of  Receiving Water.   The  effects of stormwater runoff on
         receiving water  quality were  the  NURP  program's  ultimate con-
         cern.    Because   flowing  streams,  tidal  rivers,   estuaries,
         oceans,  impoundments,  and  lakes  all have different hydrologic
         and  water quality responses,  the  types  of  receiving waters
         associated with  each  candidate project had to be  examined to
         ensure that  an appropriately representative mix was included in
         the overall  NURP  program.

     3.  Hydrologic Characteristics.   The  pattern of  rainfall  in  the
         study area  is perhaps  the  single  most  important  factor  in
         studying urban runoff  phenomena,  because  it provides the means
         of conveyance  of pollutants from  their source  to the receiving
         water.   For  this reason,  projects in  locations  having in dif-
         ferent hydrologic regimes  were chosen for the program.

     4.  Urban Characteristics.   Characteristics   such  as   population
         density, age  of community,  and  land  use  were  considered  as
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         possible  indicators  of  the  waste  loads  and  ultimately  the
         rainfall-runoff water quality relationship.  The type of sewer-
         age system was  another  factor considered  (e.g., whether  it is
         combined, separate, or  mixed; how severe  the  infiltration and
         inflow problems may  be) .   Such factors  have  different effects
         on the quantity and quality of  storm runoff,  and were balanced
         as well as possible in selecting projects.

     5.  Beneficial Use of Receiving Water.  Because this factor greatly
         affects the type of control measure  that would be appropriate,
         attempts  were  made   to  include   a  wide  range  in  selecting
    ,»    projects.
     •'A.
Although these were the primary criteria used to identify potential projects,
other  factors also  had  to be  considered   (e.g.,  the applicant  agencies'
willingness to participate, the State's  acceptance  of  the project,  the expe-
rience  of  the proposed project  teams).    Because the NURP program  used
planning grants  (not  research funds)  a  major consideration was  the antici-
pated working  relationships with local  public  agencies and  the  applicants'
ability to raise local matching funds.

Program Assistance

Technical expertise and  resources  available for urban  runoff planning varied
among  the  various projects  participating  • in NURP.  Therefore,  the program
strategy called  for providing a broad  spectrum of technical  assistance to
each project as needed and  for intercommunication of  experiences and sharing
of data in a timely manner.

Assistance was also provided to the applicants in developing their final work
plans.   This  was done  to  ensure  that  there  would  be consistency  among
methods, especially in the  collection  of data.  If there were to be differ-
ences in data  from city  to city, they must be  due  to  the characteristics of
each city and not a result of how the data were obtained.

Assistance with  instrumentation  was provided during the program  in the form
of information on available equipment,  installation,  calibration,  etc.  Be-
cause one of the  more  important  elements of a data  collection program is the
"goodness" or quality  of the  data themselves, questionable data  would be of
little use.  Accordingly, a quality assurance and quality control element was
required in the plans for each project.

Periodic visits were  made to each  project site to ensure that the partici-
pants were provided opportunities  to discuss any problems,  technical or ad-
ministrative.  The visiting team  typically included  an  EPA  Regional Office
representative,  an EPA  Headquarters  representative,  and one or  two  expe-
rienced consultants.  All  interested parties, including representatives from
State or local governments, were requested to attend those visits.

As the projects moved  farther  into their planned activities  and the time for
data analysis approached, each project was required to describe how they were
going to analyze their data.  No single method was recommended for each proj-
ect, because  it  was  believed that  a  broad  diversity of available methods
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would be suitable, if used  properly.   Guidance  on  proper use was provided as
a part  of  technical assistance through project visits  and special workshops
for this purpose.

Communication

It was  intended that  the  entire  group  of NURP participants function  as  a
single  team.   Accordingly,  a communication program  was developed.  National
meetings were  conducted semi-annually so  that  key personnel  from the indi-
vidual  projects  would have  an  opportunity to discuss  their experiences and
findings.

Reports were required of each project quarterly.   EPA Headquarters also pro-
vided composite  quarterly reports  summarizing the  status of each project and
discussing problems encountered and solutions found.
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                                  CHAPTER 3
                          URBAN RUNOFF PERSPECTIVES
In evaluating  the  impacts of urban  runoff,  one's perspective may  be influ-
enced  by one' s  concerns  and  priorities -  and  what  one  defines  to be  a
"problem".  Recognizing  this,  the following discussion covers  several  such
perspectives,  including  concerns over  runoff  quantity,  water  quality,  and
control possibilities.

RUNOFF QUANTITY

The following discussion covers a major cause and two major effects of runoff
problems  related  to  "quantity"   (i.e.,  increased urbanization  as  a cause;
flooding and erosion/sedimentation as effects).

Flooding Problems

As noted earlier,  drainage has  historically been the  principal local-level
concern  regarding urban  runoff.   Concerns over quantity can  be  divided into
two  basic  categories:    nuisance flooding   and  major  flooding.   Nuisance
flooding  (e.g., temporary  ponding of water on.streets,  road  closings, minor
basement flooding), although hardly  tolerable to  those immediately affected,
rarely affects an  entire urban  populance.  Nonetheless, the  concerns of the
(often vocal)  minority  of affected  citizens  commonly  reach  the point where
local action is taken to minimize the recurrence  of  such events.  Such miti-
gation activities  are usually  locally  determined,  funded,  and implemented
because both the affected  public  and government decision makers  perceive and
concur that such flooding constitutes a "problem".

Catastrophic flood events, on the other hand, have to be  thought about dif-
ferently for several reasons:

        They typically affect the majority of the  urban populace.

        Mitigation  measures  often   involve engineering  improvements
        extending well beyond local  jurisdictions.

        Mitigation measures  often cost more than  the  local community
        could  afford.  Historically,  the Federal government  has become
         involved,  in  major flood control efforts  through a  number of
        related programs.   In  such   cases, water  quantity  problems are
        relatively easy  to define  because  the  extent  of flooding is
        readily observable, the  degree  of damage is easily determined,
        and  the  benefits  of proposed   flood control  projects   can be
        estimated.   Thus,  decision   makers  face  a  relatively low  risk
        in prescribing courses  of action and justifying the  associated
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        costs  in  light  of  benefits.    As  will  be  discussed  later,
        decision making in the  case  of water quality concerns  is less
        straightforward.

Erosion and Sedimentation Problems

Erosion results  from rainfall  and  runoff when soil and  other particles are
removed from  the  land  surface  and  transported  into conveyance  systems and
water bodies.  Since land surface erosion  is  the principle source of stream
sediment, the  type of soil,  land cover,  and  hydrologic  conditions are major
factors in  determining . the  severity and extent of  sedimentation problems.
Although erosion  is a natural  process,  it is frequently  exacerbated by the
activities of man, in both urban and rural environments.

When addressing  the broad spectrum of  receiving  water problems  which result
from sedimentation,  it  is  convenient to  divide  cases into  two categories;
(1) those that respond to control  measures directed at  nuisance flood pre-
vention,  and  (2)  those  that  are  not  controlled by  such  measures.   When
natural loads are  discharged into receiving waters, the effects are primarily
physical  and  only  secondarily  chemical  (because  the mineral  constituents
which make up the  primary sediment load are relatively benign  in most cases).
Among the physical problems imposed upon  the receiving waters  are:

     -  Excess turbidity  reduces light  penetration, thereby interfering
        with sight feeding and photosynthesis;

     -  Particulate  matter clogs  gills  and  filter systems  in  aquatic
        organisms,  resulting,  for  example,  in retarded growth, systemic
        disfunction, or asphyxiation in extreme cases; and

     -  Benthal  deposition can  bury bottom  dwelling  organisms,  reduce
        habitat  for juveniles,  and interfere with egg  deposition and
        hatching.

Although sedimentation is storm-event related, its  resultant problems are not
exclusively either  "quantity"  problems  or water  "quality"  problems.  Being
hybrid problems,  sedimentation  control has  received a mixed  approach.   The
organizations  involved  range widely, from Federal agencies  (e.g.,  the Army
Corps  of  Engineers,  the Soil  Conservation Service)  to  local  drainage and
sedimentation  control  officials, frequently with involvement  from State and
county governmental  agencies.

Urbanization as a  Cause of Problems

Urbanization  accelerates erosion  through  alteration  of  the land surface.
Disturbing the land  cover, altering natural drainage patterns, and increasing
impervious  area  all increase  the  quantity and  rate  of  runoff,  thereby in-
creasing both  erosion and flooding potential.  Also,  the sedimentation pro-
ducts which result from urban activities are generally not  as benign as the
natural mineral  sediments which result  from soil erosion.  Atmospheric depo-
sition  (associated  with  industrial,   energy,  and agricultural  production
activities) and  added surface  particulates (resulting from  tire wear,  auto
                                     3-2

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exhaust, and road surface decomposition) fall in this latter category.  Their
effects on receiving waters tend to be more "chemical" than "physical".  They
may contain  toxic  substances and/or  other  compounds which can  have adverse
impacts  upon   receiving  water  quality   and  the   associated  ecological
communities.

WATER QUALITY CONCERNS

The notion that urban runoff  can  be a significant contributor to the impair-
ment or  degradation  of  the quality  of  receiving waters has  formed only re-
cently and is not universally shared.   It  is the totality of receiving water
characteristics  (e.g., flow  rate,  size or volume,  and  physical  and chemical
characteristics) that determines  its use,  although  some characteristics are
more important  than  others  (e.g.,  there must be present an appropriate rate
of flow and/or volume in the receiving water to support  the desired use).

In addressing the water quality needed  to  support  a designated use, one must
consider specific  requisite  characteristics.   For example,  in the  case of
swimming,  total dissolved solids  and dissolved oxygen levels  are  far less
important than  pathogenic organisms.   For  irrigation, the biochemical oxygen
demand of  the  water is  of  little concern to  the farmer, whereas  the total
dissolved  solids  level  is  of  immense  concern  (to minimize  salt  buildup).
Although high nutrient levels may be detrimental to the quality of impounded
waters  (by  hastening eutrophication processes), a  farmer  may welcome nutri-
ents in irrigation water.

It is  also important to note that  it is the  concentration,  rather than the
mere presence of  a water quality  constituent,  that affects  use.   The rela-
tionship between pollutant  concentration and resultant  impacts  on receiving
water  use  are  quite non-linear,  with  plateau  effects not  uncommon.   For
example, consider dissolved  oxygen and its effect upon  fin  fish.   Down to a
certain  level  below  saturation,  there  are virtually  no  important effects
(upon  a  given  species).   As  dissolved  oxygen levels fall  below this thres-
hold,  the  more  sensitive members  of the species  begin to be  affected.  As
levels continue to  fall,  the affected percentage  of  the population will in-
crease until a  level is reached at  which the entire population can no longer
survive.   Obviously,  any further reduction  of dissolved  oxygen level would
have no further effect upon the community, since it no longer exists.  It is
important to keep this plateau  effect in mind when considering the practical
impacts of  increased pollution  and the practical  value of remedial measures
to restore  beneficial uses,  since  limited  removal of  a polluting substance
may do nothing  to alleviate the problem.   In the example given above, if one
were to  somehow reduce  the input of oxygen demanding  substances  to the re-
ceiving water,  the result might be that the dissolved oxygen level of the re-
ceiving water would  rise from 1.0 mg/1  to  3  mg/1.   If the species of concern
were trout,  they  still  could not survive.   Even though polluting substances
were removed and money was spent, the desired benefit would not be achieved.

WATER QUANTITY AND QUALITY CONTROL

There  is no  question that excessive urban runoff  causes problems.   Remedial
costs  may  be high,  but the  benefits  are  obvious.   Currently, there  is  a
growing national awareness that, if steps are taken during the planning phase
                                     3-3

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of development,  excessive stormwater  discharges  can be prevented,  at least
from typical  events  (large  infrequent  storms will always present  a greater
threat).

Past And Current Work

During  the  past two  decades attention has  been focused on  reducing runoff
rates  and  volumes  and reducing  flood  damage.  During  the  early  1970's,  a
manual  of  practices  was  prepared under  grants  from the  Office  of Water
Research and  Technology sponsored by  the American Public Works Association
stressing detention (Poertner, 1974).  The University of Delaware also issued
a manual of practices on methods  to control rates and volumes of urban runoff
(Toubier and Westmacott, 1974).

Work done by the ASCE Urban  Water Resources  Research Council during the six-
ties stressed  the  concept of natural easements  for  drainage,  observing that
there were two drainage ways; major routes  for large events  and minor routes
for smaller more frequent events (Jones,  1968).  It was claimed  that money
could  be  saved by  using  natural channels,  swales,  etc.,  thus  reducing the
need for more expensive concrete  conveyances.

The idea of intentionally  using  natural runoff courses,  green belts, and the
like was new to  engineers  who had long been trying to control runoff through
more artificial  conveyances.   In 1970,  EPA's Office  of Research and Develop-
ment initiated work on a  development  known as the Woodlands project in Texas
near Houston.  Studies were  conducted to determine how  storm  flows could be
managed  and water  quality  could be  protected or  improved  by the  use  of.
natural  drainage ways,  detention  facilities,  porous pavements,  increased
infiltration rates, and a decrease in runoff rates (Characklis,  1979).

Federal Involvement

As part  of its  national  effort  to control  erosion  from agricultural lands,
the  Soil Conservation Service  (SCS)   (Department  of Agriculture)  provides
technical  assistance  in developing erosion  control plans.  During the past
decade  or  so,  the methods  they   have  developed  have been applied  much more
widely  than just to  agricultural  situations.   SCS has become increasingly
involved in erosion control  in urban areas and has produced a useful document
for assessing urban hydrology in  small watersheds  (SCS, 1975).

Other Federal  agencies  that  have an interest in urban runoff and its control
include the U.S. Geological Survey, the  Federal Highway Administration, the
Federal Housing  Administration,   the Tennessee Valley Authority,  and others
too numerous to mention.

State And Local  Involvement

Although  some  27 states  have adopted  floodplain  management  legislation  to
protect  property,  the  control  of  urban drainage has traditionally  been a
local  matter.  Some  states have  some form of erosion  control  laws in force;
however few states have runoff rate/quantity  legislation.  This  situation has
begun  to change  over the last decade,  and Maryland  is one  example where the
statewide legislation for  stormwater management is implemented at the county
level.
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The methods used tend to be preventive, wherein erosion is controlled by pre-
scribing  certain  proven  design  practices  and  conventions.   Many  local
agencies are developing control plans  along  these  lines,  so this report will
not cover this aspect of control.

PROBLEM DEFINITION

As  pointed out  earlier,  water quantity  problems  are  relatively easy  to
identify and describe.  Water quality problems, on the other hand, tend to be
more elusive because their definition  often  involves  some subjective consid-
erations,  including  experiential  aspects  and  expectations of  the populace.
They are  not immediately  obvious  and  are usually  less  dramatic  than,  for
example,  floods.   They also  tend  to  vary markedly  with locality  and geo-
graphic regions within the country.  For example, a northwestern resident may
want to upgrade stream quality  to  support  some highly-prized species of game
fish, while  a northeastern resident contemplating  the river  flowing  by the
local  factory might  be  grateful  to  see  any game  fish at  all.  Thus,  a
methodological approach  to the determination  of water quality  problems  is
essential  if one  is  to  consider the relative  role of  urban  runoff as a con-
tributor.  An important finding of the work conducted  during  this NURP pro-
gram has  been  to  learn  to avoid  the  following  simplistic logic  train:
(a) water quality problems are caused by pollutants, (b) there are pollutants
in urban runoff, therefore, (c)  urban runoff causes "problems".  The unspoken
implication is that  a  "problem" by definition requires action,  and any type
of "problem" warrants equally vigorous  action.  It  becomes clear that a more
fundamental and  more precise definition  of a water quality  "problem" from
urban runoff  is  necessary.   For this purpose,  the NURP has  adopted the fol-
lowing three-level definition:

        Impairment or denial of beneficial uses;

        Water quality criterion violation;  and

     -  Local public perception.

The first of these levels refers to cases of impairment or denial of a desig-
nated use.  An  example  would be a case where a determination  has been made
that some  specific beneficial use  should be  attained;  however, present water
quality characteristics are  such that  attainment of the  use  cannot be fully
realized.

The second  level  of  problem definition refers to violations  of a designated
water quality criterion.   An example would  be a case where  some  measure  or
measures of water  quality characteristics  have been  found to violate recom-
mended or  mandatory  levels  for  the receiving  water  classification.   Some  of
the  subtle distinctions between this  and  the preceding  problem definition
arise in the fact that receiving water classification may not be appropriate,
the beneficial use may not be impaired or  denied,  and the water quality cri-
teria associated with that  classification  may  or may  not  be  overly conserv-
ative or directly related to the desired use.

The third  level  of problem definition involves public  perception.   This may
be expressed in a number of ways,  such as telephone calls to public officials
                                     3-5

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complaining about  receiving water color, odor,  or  general aesthetic appear-
ance.  Public perception  of receiving  water body problems is highly variable
also.  Some people enjoy fishing for carp or gar,  children  will play in al-
most any creek, and so on.  This level of problem definition can also include
one concept of  anti-degradation.   Here the  thought  is that no polluting sub-
stances of any  kind in any quantity should be  discharged into the receiving
water regardless of its  natural  assimilative  capacity.   This concern has its
ultimate expression in the  "zero discharge" concept.   EPA's  concept of anti-
degradation, on the other  hand,  refers  to  degradation of use;  a subtle but
essential difference.

The  foregoing   levels  of problem  definition  provide an  essential framework
within which to discuss  water quality  problems  associated with urban runoff.
However, it  is  important to  understand  that when one is  dealing at a local
level all three elements  are  typically present.   Thus,  it is up to the local
decision makers, influenced by other levels of  support and concern, to care-
fully weigh  each,  prior  to making a final  decision  about the existence and
extent of  a  problem and  how  it  is to be defined.  It  follows that,  if this
step of problem definition  is done carelessly,   it will be difficult,  if not
impossible, to  plan an effective  control strategy  and  establish a means for
assessing its effectiveness.
                                     3-6

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                                  CHAPTER 4
                            STORMWATER MANAGEMENT
INTRODUCTION

This chapter is  included  for those who wish to  know more about how  to plan
and implement stormwater  management programs.   Most of  the  information con-
tained herein was developed  through several related programs  that  were pro-
ceeding in parallel with the NURP program.

     -  The Southeast Michigan  Council of Governments  (SEMCOG),  a  NURP
        grantee, was developing stormwater management procedures.

        The Midwest Research Institute  (MRI) was  collecting  cost infor-
        mation on control practices from selected NURP projects.

     -  A  related  EPA Water  Planning  Division  program, the  Financial
        Management Assistance  Program  (FMAP),  was  developing  financial
        and institutional planning procedures designed to be helpful in
        the implementation of stormwater management plans.

STORMWATER MANAGEMENT PLANNING1

Stormwater management planning  develops policies,  regulations,  and programs
for the control  of  runoff from the land.  Stormwater management planning is
normally directed toward either or  both of  two primary  goals:   the reduction
of  local  flooding  and/or the protection  of water  quality.  However, storm-
water management planning is also  generally used to insure that stormwater
programs   and   regulations  provide  multiple   benefits  to   the   affected
communities and do so in a way that does not create additional  problems.

Stormwater management planning need not involve  expensive technical studies.
Available data and maps, the experience of other  communities, and advice from
experts can be used to develop an effective planning program.  Detailed tech-
nical studies can then be  targeted  toward  specific  issues and  problems.  Ef-
fective  local  planning can  alleviate  the  need   for costly remedial public
works projects.
   The material in this section of the chapter is largely from Technical Bul-
   letin  No.  1:   Stormwater Management  Planning:   Cost-Saving Methods  for
   Program Development,  the  first of a  seven-part bulletin  series  on water
   quality management prepared  by the Southeast Michigan Council  of Govern-
   ments  and available  from  Information  Service,  SEMCOG,   8th Floor,  Book
   Building, Detroit, Michigan 48226.
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  The  Need

  Stormwater  runoff cannot be ignored in developing communities.  As  urban de-
  velopment  occurs,  the  volume  of  stormwater  and  its rate of  discharge  in-
  crease.  These increases are caused when pavement and structures  cover soils
  and  destroy vegetation which otherwise would slow  and absorb runoff.  Pollut-
  ants,   washed  from  the  land surface and carried by runoff into  lakes  and
  streams, may  add to existing water quality problems.

  Figure 4-1  illustrates  the effects of  paved  surfaces  on  stormwater  runoff
  volumes.  When natural ground cover  is present over the  entire site, normally
  less than  10  percent  of  the stormwater runs  off the  land into nearby creeks,
  rivers, and lakes.   When  paved surfaces cover 10 to 30 percent of  the site
  area,  approximately 20 percent of  the stormwater can be  expected  to run off.
  As paved surfaces increase, both the volume  and the  rate of runoff  increase.
  Furthermore,  paved  surfaces prevent natural infiltration  of stormwater into
  the  ground, and increased runoff volumes and rates increase soil  erosion and
  pollutant runoff.  Stormwater management planning  can be used to develop pro-
  grams  to reduce adverse  affects and  even to provide community benefits.
                 40%
                   EVAPO-
                   TRANSPIRATION
                                         38%
                                         4 EVAPO
                                           TRANSPIRATION
                        NATURAL
                        GROUND
                        COVER
       10%
     25%
     SHALLOW
     INFILTRATION
                                            20% RUNOFF
                                                 10-20%
                                                 PAVED
                                                 SURFACES
  DSP
  INFILTRATION
21%
SHALLOW ^    I DEEP
INFILTRATION    T INFILTRATION
           21%
                 25%
                 35%
                   EVAPO-
                   TRANSPIRATION
30% RUNOFF
                         35-50%
                         PAVED
                         SURFACES
                                         30%
                                          , EVAPO
                                           TRANSPIRATION
                                          55% RUNOFF
                                                75-100%
                                                PAVED
                                                SURFACES
       20%
       SHALLOW
       INFILTRATION
  DEEP
  INFILTRATION
15%
   10%
   SHALLOW
   INFILTRATION
5%
DEEP
INFILTRATION
    Source: J.T. Tourbier and R. Westmacott, Water Resources Protection Technology: A Handbook of Measures to Protect Water
         Resources in Land Development, p. 3.


    Figure 4-1.   Typical Changes in Runoff Flows Resulting from Paved Surfaces
                                           4-2

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Stormwater management can and should be directed  toward two goals:   the con-
trol of runoff flows (i.e., volumes and rates)  and  the  control of pollutants
in stormwater.  Control measures which emphasize the storage of runoff rather
than the  immediate conveyance  from the  site  and  from the community  often
provide benefits  which meet both  goals.   Stormwater storage  and conveyance
measures, however, affect the community in a variety of ways.  Through storm-
water management planning the effects of alternative policies,  programs, con-
trol measures, and financing schemes can be evaluated.

Stormwater management  planning  is  directed toward basic  policy questions,
such as:

        What should be done with runoff from the land?

     -  Is the temporary (detention) or permanent (retention) storage of
        stormwater runoff desirable?

     -  Under  the  circumstances,   should  retention  basins,  detention
        basins, natural  infiltration areas, or dished parking  lots be
        used to store runoff?

        What requirements should be placed on new developments?

     -  Do stormwater runoff problems in developed areas warrant special
        attention?

     -  Should communal retention or detention facilities be provided by
        the local jurisdiction?  If so, how can such areas be financed?

     -  Who should pay for retention and detention facilities on private
        property?

        Are the local  jurisdictions already  carrying  out programs (such
        as parkland  acquisition programs or wetlands  regulation) which
        affect stormwater  runoff?   Can programs  and/or  regulations be
        coordinated to achieve multiple purposes?

        Should enclosed  drains  or  natural channels  be used  to convey
        stormwater to and from storage areas?

        Can  routing and  storage be  provided   for  major storms (e.g.,
        100-year  frequency)  as well  as  minor  storms  (e.g.,  10-year
        frequency)?

        Who should be responsible for facility maintenance?

The specific questions to be addressed in a local government planning program
will vary among local  jurisdictions,  reflecting varying problems and commun-
ity objectives.   The answers to these questions may take the  form  of policy
statements, changes in regulations or engineering design standards,  technical
assistance materials  for  landowners  or consulting engineers,  revisions  to
existing programs, or a written plan document.
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Because  stonnwater management planning  for  quantity and  quality  control is
relatively new,  and because community stonnwater concerns  differ,  there are
no easy formulas for preparing stormwater management plans.

Stonnwater Runoff  as a Community Resource

Although,  stormwater management programs  are typically undertaken  to avoid
problems  (e.g.,  flooding,  pollution, lawsuits), effective  planning  can also
be used  to pursue potential community benefits.  When  effectively  managed,
stormwater can provide benefits such as:

     -  Recharge of groundwater supplies;

     -  Water quality enhancement;

     -  Recreational opportunities  (e.g., use of large retention areas
        for boating, fishing, or nature study);

     -  Replenishment  of wetlands  which serve as wildlife habitats,
        absorb   peak  floods,  and  naturally  break   down  certain
        pollutants;

     -  Maintenance of summertime lake levels and stream flows; and

     -  Enhancement of community  appearance  and image when facilities
        are attractively designed.

The Role of Local  Governments

In some  cases,  the institutional systems for stormwater management  may need
to be  complex,  largely because State, county,  and  local agencies'  policies,
regulations, and procedures may all affect  stormwater control within a par-
ticular development.  For example,  in Michigan, the following roles apply:

     -  County  drain commissioners  construct and manage  county drains
        and also review subdivision plans to  assure adequate drainage.

     -  County  highway departments  affect drainage  in  new developments
        by regulating connections to roadside drains and ditches.

        The  State  Department of  Natural Resources  regulates  wetlands,
        dam construction, and floodplain alterations.

        The  State  Water  Resource Commission  issues  permits for certain
        stormwater discharges  when  known water quality  problems can be
        linked  with  a particular  activity,  (e.g.,  certain  storm drains,
        animal  feeding operations,  industrial parking lots).

     -  Both the State Department of Public Health and county drain com-
        missioners regulate  drainage in proposed mobile home parks.

     -  County  agencies  and certain local  governments issue erosion and
        sediment control permits for certain  development sites.
                                     4-4

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Furthermore, there  has been  increasing emphasis  upon the  consideration  of
environmental factors  in  land use decisions.  Recent  amendments  to  the City
or Village  Zoning  Act and the Township  Rural Zoning Act have  clarified the
legal authority of  local  governments to complete  site plan reviews  for en-
vironmental management purposes."  Standards  for  the  review  of  land uses must
be included  in  local  ordinances  and take natural  resource  preservation into
account.  The Michigan Environmental Protection  Act  (MEPA)  (Act 127,  P.A.  of
1970) places a duty on all government agencies to prevent  or  minimize water
pollution and other environmental problems while carrying on regular activi-
ties.  Section 5(2) of MEPA addresses  the  actions of  local  officials in the
following terms:

     In any  ...  administrative, licensing or other proceedings, and in
     any judicial review  thereof, any  alleged pollution impairment or
     destruction of the air,  water  or other  natural  resources  or the
     public  trust therein,  shall  be determined, and  no conduct shall
     be authorized or  approved which  does,  or is  likely  to have such
     effect  so  long as there is a  feasible and  prudent alternative
     consistent with the reasonable requirements of the public health,
     safety and welfare.

Environmental aspects  of  stormwater runoff  may  be addressed by  local offi-
cials in response to MEPA.

None of  the above laws specifically  require local governments  to undertake
stormwater management programs.  Instead, local governments have a wide range
of possible roles available to them.  Stormwater management planning programs
can be directed toward the.review of existing State  and  county programs af-
fecting stormwater runoff and toward the evaluation  of alternative roles for
the local government.

Possible roles  for local  governments  in  stormwater management  include the
following:

     -  Planning - The term "stormwater management planning" refers to
        the process of developing policies, programs, regulations, and
        other recommendations to  chart  the future course of the com-
        munity in terms of stormwater management.   Such  planning can
        address existing problems or help to avoid future problems and
        community expenses.

     -  Regulations - Stormwater runoff control for each site plan and
        subdivision plan  can  be  reviewed  and  approved by  the  local
        government.

     -  Design  and  Construction  -  Storm  drainage  facilities  (e.g.,
        pipes,  basins, areas  for  retention)  can be  designed and con-
        structed by the local  government.  Purchase  of lands to serve
        as community stormwater retention areas may also be undertaken.

     -  Inspection  and   Maintenance   -  Requirements   for  regular
        inspection and maintenance of stormwater facilities, including
        drains and  retention  or  detention basins, may  be enforced by
                                     4-5

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        local  governments.   Requirements for  easements  are  usually
        part of maintenance programs.  Local governments may choose to
        undertake  maintenance  as  a  community  service  (such  as  a
        utility)  or   may  require  maintenance  through  contractual
        agreements with property owners.

The types  of programs developed and the role assumed by  a  local government
should, of course, reflect  available financing  options as well  as program
needs and management gaps.

FINANCIAL AND INSTITUTIONAL CONSIDERATIONS2

The traditional  planning approach would  ideally  culminate in  the successful
implementation of a detailed  design.  In many cases, however,  this objective
is not accomplished due  to financial and institutional constraints.   Often a
study team will  fail  to  adequately consider such institutional and financial
issues as  who will  manage the system and how will  it be financed, thus cre-
ating a gap  between technical planning and implementation.  This omission is
illustrated  in Figure  4-2.
ANALYSIS \
OF \J
TECHNICAL A
ALTERNATIVES/
v /
SELECT
TECHNICAL
ALTERNATIVES
DETAILED i
DESIGN 1
                                                                SUCCESSFUL
                                                               IMPLEMENTATION
               Figure 4-2.  Incomplete Water Quality Planning
The  implementation gap that  results  from the  traditional  planning approach
has occurred all too often in attempts to control urban runoff.

As an illustration of the need to integrate financial and technical planning,
consider  the  traditional process  for developing  a program to  control con-
struction runoff.  A typical outcome of the process is  a  new ordinance.  To
reach this outcome,  some  of  the issues that are normally considered from the
technical perspective include:

     -  What are the technical construction requirements to be set out
        in the ordinance?

     -  What control measures will be required?

     -  How will compliance be monitored?
   This  material is  largely from the  draft document, Planning  for Urban
   Runoff Control:  Financial and  Institutional Issues, December 1981, pre-
   pared for FMAP by  the Government  Finance Research Center of the Munici-
   pal Finance Officers  Association, Washington, D.C.
                                     4-6

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To balance the planning  process,  this technical analysis  should  be expanded
to include financial and institutional issues such as:

     -  Does the city have legal  authority  to implement each require-
        ment in an ordinance?

        How much will each cost,  and who will pay  for implementation
        of the control measures?

     -  Who will conduct  compliance  review, and who  will  pay  for the
        reviews?

Numerous additional factors increase the need for financial and institutional
analysis in all water quality management planning.   Examples might include:

        Implementation of  control programs  occurs  at the  local  level,
        and local budgets are  being tightened as water  quality expend-
        itures compete with other local demands.

        Benefits from water  quality projects are difficult to quantify
        and often accrue to people living downstream.

        It is becoming more difficult  to  obtain  municipal  funds through
        the bond market because of high interest rates.

        The cost of pollution controls is often sizable and difficult to
        allocate to specific  polluters or beneficiaries.

These problems affect most  areas of water  quality  management, but  they are
especially important in identifying  and  implementing solutions to urban run-
off pollution.

Integrated Approach

An integrated  planning  approach helps water quality planners  make  the best
control decisions in  light of many complex  issues.   This  approach takes the
traditional planning  process  and  adds  to  it  financial   and  institutional
elements  at  each step  along  the  way.   This integration  is  shown  in Fig-
ure 4-3, with the traditional  approach illustrated  along the upper track and
the financial and institutional elements added along the lower track.

During the early planning stages,  financial and  institutional  issues are re-
viewed on  a  preliminary basis.  This  information  becomes  more detailed and
refined as planning proceeds.   Ultimately,  the  information forms  the basis
for a financial and institutional plan that supports the detailed design of a
control alternative.

When very complex problems are  being evaluated,  it  may be  advisable to use a
preliminary matrix  early  in  the  evaluation process  for screening-out unac-
ceptable alternatives.  This  approach permits a more detailed evaluation of
issues surrounding  the two or  three best alternatives before  a final selec-
tion is made.   An example of  a preliminary matrix is given in Figure 4-4.
                                     4-7

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  ANALYSIS
    OF
 TECHNICAL
ALTERNATIVES /
 PRELIMINARY
 FINANCIAL &
INSTITUTIONAL
  ANALYSIS
 FINANCIAL AND
 INSTITUTIONAL
  ASPECTS OF
EACH ALTERNATIVE
                                  SELECT
                                 DETAILED
                                 TECHNICAL
                                ALTERNATIVES
                                  DESIGN
                                           SUCCESSFUL
                                                                         IMPLEMENTATION
                                                            FINANCIAL AND
                                                            INSTITUTIONAL
                                                                PLAN
 IN-DEPTH
ANALYSIS OF
 SELECTED
ALTERNATIVE
                Figure  4-3.   Integrated Water  Quality Planning
CONTROL
APPROACH
• SEPARATE
SEWERS
• SELECTIVE
EXPANSION
OF
UNDERSIZED
TRUNK SEWERS
• CONSTRUCTION
OF DETENTION
BASINS
TECHNICAL
DESCRIPTION
CONSTRUCT
NEW STORM
SEWERS IN
COMBINED
AREAS
REMOVE
BOTTLENECKS,
REDUCE
NUMBER
OF OVERFLOW
EVENTS
CONSTRUCT
10 DETENTION
BASINS SIZED
TO HOLD THE
FIRST FLUSH
FROM A
STORM
EFFECTIVENESS IN
CONTROLLING
POLLUTION
100%
EFFECTIVE
IN
ELIMINATING
CSOs
50%
EFFECTIVE
30%
EFFECTIVE
FINANCIAL
ISSUES
NET
PRESENT
VALUE
$1 BILLION
$200
MILLION
$50
MILLION
ABILITY TO PAY
EXCEEDS
CITY'S BONDING
CAPACITY
IF STAGED
OVER 10
YEARS,
COULD BE
FINANCED BUT
WOULD RESTRICT
OTHER PROGRAMS
IF STAGED
OVER 5
YEARS,
COULD BE
FINANCED;
COULD RESTRICT
OTHER PROGRAMS
INSTITUTIONAL
ISSUES
EXISTING
INSTITUTIONS
COULD HANDLE
THE PROJECT
EXISTING
INSTITUTIONS
COULD HANDLE
THE PROJECT
NEW
ORGANIZATION
MIGHT BE
NEEDED TO
MAINTAIN AND
AND OPERATE
BASINS
    Figure 4-4.
     Preliminary Matrix for Selection of  a Control Approach
              (Combined  Sewer Overflows)
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Once  a control  approach is  selected, a  detailed design  and a  financial and
institutional plan  can be prepared.   Figure  4-5 illustrates the  major fea-
tures  of a  financial and  institutional  plan.  Key  features of  the detailed
analysis  required  to  prepare  this   plan  are  discussed  in  the  following
section.
   INSTITUTIONAL SECTION

     • RESPONSIBLE AGENCY
       - OPERATING PLAN
       - STAFFING NEEDS
       - ORGANIZATIONAL STRUCTURE
     • LEGISLATIVE NEEDS
       - LEGAL ANALYSIS
       - DRAFT ORDINANCES
       - ASSISTANCE NEEDED
FINANCIAL SECTION

  • PROGRAM COST
    -  OPERATING BUDGET
    -  CAPITAL REQUIREMENTS
  • PROGRAM REVENUE
    -  FUNDING SOURCES
    -  FLOW OF FUNDS
    -  PROGRAM CASH FLOW
    -  COST ALLOCATION FORMULA
  • OTHER FACTORS
    -  FINANCIAL BURDEN ON PARTIES PAYING
       FOR THE PROGRAM
    -  SENSITIVITY OF COST AND REVENUE
       ESTIMATES TO CHANGES IN
       FINANCIAL ASSUMPTIONS
    -  INDIRECT IMPACTS
                                                                                CO


                                                                                CO
     Figure  4-5.   Major Components of  a Financial and Institutional Plan



Key Financial  and Institutional Elements

There  are six essential  elements3  of  financial and  institutional  analysis
which provide  a structure for the integrated planning process;

        institutional assessment,

        cost analysis,

     -  revenue analysis,

        ability-to-pay analysis,

        sensitivity analysis, and

        indirect  impact analysis.
3  These  elements were  first defined in  Planning for Clean Water Programs;
   The  Role  of   Financial  Analysis,   U.S. EPA's   Financial   Management
  • Assistance  Program  by  the Government Finance Research  Center of  the
   Municipal Finance Officers Association, September 1981.
                                      4-9

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Each of these elements  threads  through  the  planning process and becomes more
definitive  as  the process  proceeds.   The following discussion  defines each
element and identifies  its major features.

Institutional Assessment

The  institutional assessment identifies  the organizations  or. participating
agencies that would be  affected or involved in implementing a particular con-
trol program.  The role of each entity in a program is evaluated with respect
to its  interest in solving  the problem and its planning,  management,  oper-
ating,  and  regulatory capabilities.  If  the  study team  identifies  an  urban
runoff problem, a preliminary institutional analysis can provide insight into
capabilities of agencies that may be asked  to play a role in the implementa-
tion and can, in some cases, aid in determining the types of technical alter-
natives that are analyzed.

The  key factors to consider  in evaluating an agency's  capabilities are its
statutory authority  and organizational ability.   In order  to  control  urban
runoff, an agency must have or be able to obtain the authority to implement a
control measure.   The authority of an  agency  can be  assessed  by thoroughly
reviewing  applicable federal,  state,  and  local  legislation.    This  review
helps to  determine which agency  can  best manage  a given problem  and  high-
lights areas where additional legislation or local ordinances are needed.

Cost Analysis'*

A cost analysis is performed to identify the additional capital, operational,
maintenance, and administrative costs of each activity that is part of a con-
trol program.   These  costs  are estimated for each agency responsible for an
activity.  Cost estimates  are prepared in uninflated  dollars  (using today's
cost for  all  projections into the future) and brought back to their present
value  (or present worth)  for  comparison  among  alternatives.   The  interest
rate  to  be used  in the  present  value analysis is  the  agency's current
interest rate for borrowing funds minus the expected rate of inflation.5

Cost analysis  of  control  alternatives  is  included in  increasing  detail in
each step of  the  planning process.   It begins with  "ball park"  estimates in
early stages which are  refined as the process progresses and finalized in the
detailed financial plan.
   A  substantial part  of  this material  is  from a  report,  Collection  of
   Economic Data  from Nationwide  Urban Runoff Program Projects,  prepared for
   EPA   by    the   Midwest    Research    Institute,    425 Volker Boulevard,
   Kansas City, MO 64110.

   For  a  further discussion of present value analysis,  see pp 36 to  42  of
   Facilities  Planning  1981,  U.S.  Environmental  Protection Agency,  FRD-20,
   1981.
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Cost estimates  cannot  be static.  They are  prepared on a  preliminary basis
when an alternative is first considered and detail is added as an alternative
becomes more  feasible.  As  the  planning  process progresses,  estimates  are
updated on a regular basis to account for changing costs.

To update  and improve available data  on  the costs of  specific urban runoff
BMPs, EPA conducted a program to guide, assist, and coordinate the efforts of
selected NURP  projects in gathering cost data on  the  BMPs and  BMP  systems
which they were evaluating as part of  the NURP national workplan.  A report^
was prepared to summarize the preliminary economic data submitted by the NURP
projects.  Economic  data were submitted  for street sweeping,  detention  ba-
sins, catch  basin cleaning,  ocean  discharge  control  systems,  and a public
education/information program by nine  projects.   The data  must  be considered
preliminary and subject  to  change,  particularly  annual  operating cost data.
Most of  the  capital cost data are well documented and  represent the actual
cost of the BMP control and will not change.  The annual operating cost data,
however, range from detailed analyses  to  estimates,  and some of the data re-
ported are incomplete.   Since most of  the projects were still in progress,
incomplete operating cost data were to be expected.

The capital costs of street sweepers varied from $21,988 (in 1975) to $40,000
in 1981.  The  annual operating costs of street sweeping programs varied from
$53,445 to $1,138,097.   The  unit cost  varied from $16.80 to  $45.45 per hour
of operation,  and from $5.95 to  $23.36 per curb-mile swept.  This wide range
indicates that many variables affect  the  actual  cost  of operating a street
sweeper.

The installed  capital costs of recharge basins in Fresno,  California, ranged
from $933,750  to $5,587,000.  BMP modifications  to three detention basins in
Oakland County, Michigan, cost $2,345  to  $8,442.   The  installed capital cost
of the  modifications to the  wet pond  in the Lansing,  Michigan  project  was
$50,149.  Construction of the wet pond in the Salt Lake County, Utah project
cost $41,138;  modifications to the dry pond included placing aluminum plates
in an existing underdrain and  installing  a redwood outlet  skimmer at a nom-
inal cost of $371.

The  annual operating  costs  of  the Fresno,  California,  basins  range  from
$1,625 to $7,975.  The annual cost for the basin in Lansing,  Michigan is in-
complete and  includes only  the  interest  cost  on a 7  percent, $38,500 bond
used to help  finance the project.   The annual operating costs  for the ponds
in the Salt Lake County,  Utah project were estimated at $560 for the wet pond
and $200 for the dry pond.

The costs of the structural control alternatives  to control discharge to the
ocean in Myrtle Beach, South Carolina,  were presented in detail and are valid
estimates of the costs that will be incurred if one of them is constructed.
   Collection of Economic Data From Nationwide Urban  Runoff Program Projects
   - Final Report, April 7,  1982, EPA Contract No. 68-01-5052.  Detailed cost
   data provided by the projects are  included in the appendices  of this Re-
   port to show how the various projects prepared the data for submission.
                                     4-11

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The 1980  construction  cost estimates ranged from $32,849,200 to $50,973,500,
and the annual operating cost estimates ranged from $3,735,400 to $5,301,900.
The cost of the public education program at Salt Lake County, Utah, was esti--
mated at $1,550.  The project will report the actual cost of the program upon
its completion.

Revenue Analysis

The revenue analysis identifies the funding sources needed to match the esti-
mated cost  for control activities by participating agencies.   This analysis
is important  because  it ensures adequate funding to  implement the technical
solution to an urban runoff problem.

There are three categories of funding that are typically used to pay for run-
off control:  Federal and State funds, local public funds, and private funds.
These sources  include  a  variety of different financing mechanisms, each with
advantages  and disadvantages.   The  use  of any  or  a  combination of  these
sources requires consideration regarding:

     -  Revenue  adequacy -  Will funds  be  available  in the  long- and
        short-term?

     -  Equity  -  Are  the  beneficiaries of  the control  program paying
        their  full share?

     -  Economic efficiency  - Is the charge that is assessed equal  to
        the social cost of the program?

     -  Administrative  simplicity  -  Can  the  funds  be  managed  and
        directed  to the  control program  without  significant adminis-
        trative problems?

Ability-to-Pay Analysis

The ability-to-pay analysis  evaluates the implementing  agencies'  and  the in-
dividual  user's  ability to pay  for the proposed program by determining how
reasonable  a  proposed  revenue program  is in terms  of  its  overall impact on
the community  as a whole as well as on individual residents.

For a given revenue source, the additional burden of the program is expressed
as a percentage  of the base costs.   For example, if  the proposed program is
to be financed by  property taxes and it adds $.50 to a $1,000 tax bill, the
additional tax burden is .05 percent.  In this instance, it would appear that
the homeowner's ability to pay is quite high.

An important  factor to remember is that programs to control urban runoff are
not the only programs that are placing a burden on the people or institutions
who must  support  them.   Hence,  the cost of  a control program may not be ex-
cessive but cannot be  imposed  because ability to  pay has  already been ex-
ceeded due to  other projects.
                                     4-12

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Sensitivity Analysis

The sensitivity analysis identifies the extent  to  which local ability to pay
varies with changes  in  the assumptions used to estimate costs and revenues.
Major assumptions that influence costs and  revenues  are:  phasing of capital
improvement,  anticipated  local funding  requirements,   rate  of  inflation,
growth rate, and local fee policies.

The first  step in this  analysis is to determine  a  range of  values  for key
cost and revenue  assumptions that  could  occur  during the program.   (For ex-
ample, inflation  may vary between  5  percent and  15 percent.)   The ability-
to-pay analysis  is then  repeated  using the  high and  low values  for these
assumptions.   The final  step  is  to  evaluate  the  changes  in burden  with
"best-"  and "worst-" case situations in  comparison with burden  under the
"most likely" assumption.

The purpose of this  analysis  is to identify control programs  that are least
vulnerable to  changing  conditions.   It also helps to make the planner aware
of best- and worst-case scenarios so  that contingency plans can be developed
to cope with such events.

Indirect Impact Analysis

The indirect impact analysis is an  assessment  of the costs and benefits that
are not directly  attributable  to a proposed program.   These  costs and bene-
fits can be economic, social,  and/or environmental.  Quantifying the indirect
impacts of  a program is  usually  quite difficult,  so  the  planner generally
resorts to qualitative measurement.

An Example;  Planning an Educational Program

To illustrate further the  process of  identifying and resolving the financial
and institutional  issues  connected with  implementation  of an  urban runoff
control program,  the following spells out  the steps involved in evaluating
one control approach applicable  in  already developed  areas.  The  example
chosen is an   educational program  to  inform citizens,  industry,  and public
agencies of  the  problems  caused by  runoff-borne lawn  and garden chemicals,
oil and chemical residuals from industrial yards, and pesticides, herbicides,
and fertilizer from parks and golf  courses.

In this  example,  the activities would  include:  development  of an informa-
tional brochure,  including printing  and  distribution,  and maintenance of an
information center.  In Figure  4-6, the institutional  characteristics needed
to accomplish these activities are  compared with the capabilities of existing
agencies.  The matrix shows that  the County Department  of Pollution Control
could provide the  technical input  to  the  Public Information  Center to write
the brochure.   The Council of Governments might  coordinate  the  effort and
assume overall responsibilities for getting the job done.
                                     4-13

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INSTITUTIONAL
CHARACTERISTICS
NEEDED
• COMMITMENT TO
PROGRAM GOALS
• WORKING KNOWLEDGE
OF EACH WASTE
CONTRIBUTION TO THE
RUNOFF PROBLEM
• ABILITY TO WRITE
CLEAR AND CONCISE
INFORMATION FOR THE
PUBLIC
• ABILITY TO PRINT AND
AND DISTRIBUTE
BROCHURE

• STAFF TO RECEIVE
FOLLOWUP CALLS
• ABILITY TO ACCEPT
FUNDS FROM SEVERAL
AGENCIES TO PAY
FOR THE PROGRAM
AGENCIES
STATE
*

*

















COUNCIL
OF
GOVERNMENTS
*

*











*

*



DEPARTMENT
OF
POLLUTION CONTROL
*

*

















DEPARTMENT
OF
PLANNING
*

*







*









PUBLIC
INFORMATION
CENTER
*





*













CHAMBER
OF
COMMERCE
*










*
DISTRIBUTE
TO INDUSTRY






                                                                   83-206144
        Figure 4-6.
Institutional Assessment for Educational Program
  to Control Chemical Substances
Cost Analysis.   Cost  analysis determines  the  additional  funds  needed  to
implement a control alternative, including capital improvements and operation
and  maintenance.   Additional  administrative  costs  are  less  significant
because most  of these  projects are  undertaken  by a  public agency  that  is
already performing the function to some extent.

Capital cost  estimates are best prepared by  the water  quality  planner with
the assistance  of  the municipal  engineer  and in some  cases  his/her outside
engineering advisor.  These estimates identify all  costs related to the pur-
chase of a  new  facility or piece of  equipment for  a  project and may require
some  research into vendor prices and bids on  similar projects  around the
country.  For programs which  require changes to existing  practices (street
sweeping, etc.), the  cost attributable to  the  water quality program is the
incremental cost of the program.

Ultimately, the  cost  analysis  is used to identify the  least-cost method(s)
for reducing  pollution problems.  It  is important to remember that all costs
associated with  a  given  program must be considered.  It  is  incorrect to as-
sume  that  educational efforts,  for   example, are provided at no  additional
cost.
                                     4-14

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As an example of a cost analysis,  a possible budget sheet for the educational
program for the current year is presented in Figure 4-7.
ACTIVITIES
1. DEVELOP BROCHURE
2. PRINT BROCHURE
3. DISTRIBUTE BROCHURE
4. CONDUCT INFORMATIONAL
MEETINGS
5. STAFF FOLLOWUP
FOR PROGRAM
TOTAL
AGENCIES
STATE



$2.000

$2,000
COUNCIL
OF
GOVERNMENTS



$ 5,500
$24,000
$29,500
DEPARTMENT
OF
POLLUTION CONTROL



$2,000

$2,000
DEPARTMENT
OF
PLANNING

$1,500
$ 800


$2,300
PUBLIC
INFORMATION
CENTER
$13,000




$13,000
TOTAL
$13,000
$ 1,500
$ 800
$ 9,500
$24,000
$48.800
         Figure 4-7.  Cost Analysis for Educational Program to
               Control Chemical,  Herbicide,  Fertilizer and
                            Pesticide Runoff
Revenue Analysis.  After the program cost estimate is prepared, the potential
sources  of  revenue   are   analyzed.   There are  several  critical  factors in
analyzing revenue for urban runoff programs including:

     -  .Cost/Revenue Balance -  Will the revenues be  sufficient  to cover
        the costs on an annual basis?

     -  Equitable Allocation of Costs to Different  Groups - Do those who
        contribute to  the  problem  pay  their fair  share?  Do those who
        benefit from the program pay their fair share?

     -  Revenue Agreement - Do groups understand their participation in a
        program and its  revenue formula?  Have written  agreements which
        define the cost allocation procedure been prepared ?

Revenue analysis will  vary  with the type of control  approach selected.  The
critical factor in the revenue  analysis  is  the  identification of each entity
that will  provide  revenues and the development of an understanding by that
entity of the problem, the  control approach, and its share of the cost.

Ability-to-Pay Analysis.  Most  of the costs  to  control runoff from developed
areas are imposed on the general public or the  benefiting population as a new
and additional  governmental  expense.   The  ability-to-pay analysis evaluates
this increased  burden on  the   local  community  as  a  percentage of  property
taxes,  average income, property evaluation,  or  other appropriate measures.

Figure 4-8 illustrates an ability-to-pay analysis for the educational program
example.  The key parameters to determine homeowners'  ability to pay in this
case are the cost of the program per household,  cost as a percentage of aver-
age annual household income, and cost as a percentage of property taxes.
                                     4-15

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        A. TOTAL PROGRAM COST (ONE-YEAR PROGRAM)

        B. NUMBER OF HOUSEHOLDS AFFECTED

        C. COST PER  HOUSEHOLD
           (A DIVIDED BY B)

        0. MEDIAN HOUSEHOLD INCOME

        E. COST AS A % OF MEDIAN HOUSEHOLD INCOME
           (C DIVIDED BY D TIMES 100)

        F. AVERAGE ANNUAL PROPERTY TAXES

        G. COST AS A % OF PROPERTY TAXES
           (C DIVIDED BY F TIMES 100)
$48,000

 19,000



$14,700



$ 1,200
$2.57
.02%
          .21%
     CONCLUSION: PROGRAM APPEARS TO NOT PLACE EXCESSIVE BURDEN ON
                LOCAL HOMEOWNERS
          CO
          o
          PM
      Figure  4-8.   Ability to Pay Analysis for Educational  Program
              to Control Chemical, Herbicide, Fertilizer  and
                             Pesticide Runoff
Sensitivity  Analysis.  The sensitivity  analysis will vary depending  upon the
revenue  mechanism and  program selected for  implementing a proposed  program.
The  most  common  revenue mechanisms for  programs  controlling  runoff  from
developed  areas  are  general  funds and fees.   Analyzing  the sensitivity  of
general  revenues  requires  a  review of  past  collections  relative  to  key
parameters—inflation,   housing starts,  collection  rates,  capital  improve-
ments,  and so  on.   Collections are  then projected  for worst  and best  case
scenarios.

An additional consideration  in the sensitivity  analysis is revenue  require-
ments.   This relates to phasing a program,  either handling capital  improve-
ments  or starting  a program  on a  limited basis  with  expansion  to come  in
later  years.  For  any  one program,  numerous   options   exist for  staggering
cash  flows,  and  different  scenarios  should  be  developed to  assess  their
impact on the program as part of the sensitivity analysis.

Indirect Impact.   The  indirect   impact  of  a  runoff  control  program  for
developed  areas  are  extremely  difficult  to quantify.   Educational  programs
will raise  community awareness regarding the impacts  of local activities  on
water pollution.   Other  indirect impacts  from  control programs may relate  to
recreational benefits,   local  improvements in quality  of life, and  increased
tourism.
                                      4-16

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RELATIONSHIP BETWEEN NURP AND WQM PLANS

Of the locations selected for projects under the NURP effort, some 80 percent
had state-approved (i.e., certified by the Governor)  water quality management
(WQM) plans with elements which addressed urban runoff.  For 5 of these loca-
tions, the  NURP project  constituted  the urban  runoff element of  the plan.
For the other locations,  however,  the original 208 effort was  unable  to de-
velop the necessary  information  on either water quality  effects  or perform-
ance  of  best  management  practices  (BMPs)   to  justify  structuring  formal
implementation plans for urban runoff control.  Consequently, the typical WQM
plan  elements  dealing  with urban  runoff  identified  the  need  for  further
study, usually specifying problem  assessment  and BMP performance evaluation.
These elements became the focal points of the activities funded by NURP.

The WQM plans  for the  remaining  20 percent of the  locations  which partici-
pated in the  NURP program did not  contain a specific urban runoff element.
Presumably this was due to time and resource constraints in relation to other
issues which were  assigned  higher priorities in planning  efforts.   In these
cases, the NURP projects provided the opportunity  to address a water quality
issue not adequately addressed in the original 208  planning studies.

Over two-thirds of the NURP project locations reported that NURP findings and
recommendations have  or will be  incorporated in  the  next  annual  update of
their formal WQM  plans.  The remainder  generally  indicate  that  they  expect
the planning issues  to  be addressed at the local  level or  that NURP results
will support planning and implementation  activities, even though they  do not
anticipate formal incorporation in WQM plans at this time.

Over half of the  NURP project locations report  either active  or planned im-
plementation efforts based on the  results  of  NURP.  Thirty percent indicated
that no implementation  is being planned  because  the  need  for or value of ur-
ban  runoff  control was  not demonstrated.  The  balance   (20 percent)  of the
NURP locations suggest that while implementation activities are not currently
planned,  they expect  NURP results to influence  future deliberations  on this
issue.
                               4-17/4-18 blank

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                                  CHAPTER 5
                             METHODS OF ANALYSIS
INTRODUCTION

This chapter identifies and briefly discusses the methods adopted to assemble
and  analyze  the  large  data base  developed by  the NURP  projects  and  also
provides the methods employed to develop  and interpret results.   The chapter
is  structured  according  to  the  three  prime  areas  of  program  emphasis;
(1) characteristics of pollutants in urban  runoff,  (2) water quality effects
of urban runoff discharges  including water  quality criteria/standards viola-
tions and impairment or denial of beneficial uses  of receiving water bodies,
and  (3) the effectiveness of control measures to reduce pollutant loads.

The  procedures  employed  in this assessment were designed to  provide gener-
alized  results and findings  about  urban  runoff  issues   of  interest  for
nationwide use.   This national  perspective,  and  the need  to consider  the
fundamental variability of  urban runoff processes,  has prompted some signif-
icant advancements in the application of statistical methods and models.   The
basic  methods used were,  however,  largely developed  under different  EPA
efforts, many  under the  sponsorship of the Office of Research  and Develop-
ment,  or  other programs.   In  some cases,  similar or equivalent procedures
were applied in individual  NURP projects; in other cases,  methods adopted by
individual projects in response to local  needs and interests were different.
Where possible, comparisons have been  made  between  either  detailed results,
or  conclusions drawn  from such  results,  as derived from  both  local  and
national perspectives.

The descriptions provided in this chapter are  brief and  intended to communi-
cate  the  technical  framework  upon  which  the results  and conclusions  are
based.  More detailed information on the methods and techniques are contained
in other documents developed by NURP.   Pertinent NURP reports cover, in sepa-
rate  volumes,  probabilistic methods  for  analyzing  water  quality effects,
detention and  recharge  basins  for control  of urban stormwater  quality,  and
street sweeping for control of  urban stormwater quality.   The Data Management
Procedures Manual,  another  of the project documents,  is  an additional source
of information on details of the analysis methods utilized.

Because field measurements  and sampling formed one  of  the  most important in-
formation sources, it was essential that the monitoring and analysis programs
produce  consistent and  sound  data.   Accordingly,  NURP  required that  all
projects adopt  Quality Assurance/Quality  Control elements as  integral parts
of their work plans.  Key components of these plans include the following:

     -  Program Coordination.   Projects  were  required  to  designate  a
        QA/QC coordinator, responsible for the entire QA/QC effort.
                                     5-1

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     -  Field Quality Assurance.  Guidance was  provided to the projects
        for all key aspects of the data collection process.

     -  Laboratory Quality Assurance.  A manual prepared by EPA's Envi-
        ronmental Monitoring and  Support  Laboratory was provided to all
        projects and contained analytical quality control information.

     -  Data Management.  A manual entitled "Data Management Procedures"
        was provided  to  all projects and covered  such topics  as  data
        formatting, data  reduction, and some analysis.

     -  Data Analysis.   To encourage innovative  approaches  and respon-
        siveness to  local conditions, uniform  methods  of  data analysis
        were not  stressed.   Technical guidance  and  mandatory  review of
        analytical procedures were provided.

URBAN RUNOFF POLLUTANT CHARACTERISTICS

General

A substantial component of the individual NURP projects was the acquisition
(and subsequent analysis) of  a data base for a number  of  storm events, con-
sisting of  precipitation  and  the resulting quantity and quality  of runoff
from a number of local urban catchments.  One of the principal EPA objectives
in the  analysis  of these data has been  to  develop a concise  summary of the
characteristics of urban  runoff.  There  are  a  number of questions concerning
urban  runoff  characteristics which  need to be addressed for  water quality
planning purposes, including what are the appropriate measures of the statis-
tical characteristics of  urban runoff (e.g.,  population distribution, central
tendency, variability,  etc.)?  Do distinct subpopulations  exist and what are
their  characteristics?   Are  there   significant differences  in  data  sets
grouped according  to  locations  around the  county  (geographic  zones),  land
use, season, rainfall  amount,  etc.?   How may these variations be recognized?
What is the most appropriate manner in which to extrapolate the existing data
base to locations for  which  there are  no  or  limited  measurements?  Though
these questions cannot be fully answered given  the current state of knowledge
concerning  urban  runoff,  these   are  the types of  issues  addressed by the
methods described in this chapter and the results presented in Chapter 6.

The principal thrust  of the individual NURP projects,  and  thus this nation-
wide assessment report, was the  characterization of what has been adopted as
"Standard  Pollutants" of primary concern  in  urban runoff.   These include
solids, oxygen  consuming constituents,  nutrients,  and  a number of  the more
commonly encountered  heavy metals.    The  methods used  to  characterize  these
standard pollutants are described under a separate heading below.

In approximately two-thirds of the NURP  projects the occurrence of compounds
on EPAs list of "Priority Pollutants" was investigated.  This program element
is  also described under  a separate heading below.   A  number  of  additional
factors have also been addressed  in the program.  These are briefly discussed
                                     5-2

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below because they  relate  closely to the general  issue  of pollutant charac-
teristics.  These include the following:

     -  Soluble  vs  Particulate  Pollutant Forms.   The  distribution  of
        soluble  and  particulate forms  of a pollutant in  urban  runoff
        (particularly metals  and nutrients)  was  examined in both  the
        standard conventional pollutant and priority  pollutant  aspects
        of  the   study  because  certain  beneficial use  effects  depend
        strongly on the  form  in which the contaminant is  present.   The
        priority  pollutant   program  additionally  determined   "Total
        Recoverable" fractions, corresponding to contaminant  forms  used
        in EPA's published toxic criteria guidelines.

     -  Coliform Bacteria.  Fecal coliform bacteria counts (and  in  some
        cases total coliform  and fecal streptococcus as well)  in urban
        runoff were monitored during a significant number  of  storms by
        seven of the NURP  projects.   Though the data  base for bacteria
        is restricted,  useful results are provided in Chapter 6.

     -  Wetfall/Dryfall.    As  part  of  program  elements  designed  to
        examine  sources  of  pollutants  in  urban  runoff,   a  number  of
        projects  operated  atmospheric  monitoring stations  for  char-
        acterizing pollutant contributions  from precipitation (wetfall)
        and from dry weather deposition  (dryfall).   Results of this  work
        are  reported  in  individual  project  reports  and   not  included
        herein.

Standard Pollutants

The following constituents were adopted as standard pollutants characterizing
urban runoff:

                        TSS - Total Suspended Solids
                        BOD - Biochemical Oxygen Demand
                        COD - Chemical Oxygen Demand
                        TP  - Total Phosphorus  (as P)
                        SP  - Soluble Phosphorus (as P)
                        TKN - Total Kjeldahl Nitrogen (as N)
                    NO   -N - Nitrite + Nitrate (as N)

                        Cu  - Total Copper
                        Pb  - Total Lead
                        Zn  - Total Zinc

The list  includes pollutants  of general interest  which  are usually examined
in both  point and  nonpoint source  studies  and includes  representatives  of
important categories of pollutants—namely solids,  oxygen consuming  constitu-
ents, nutrients, and heavy metals.

The pollutant  concentrations  found  in  urban runoff vary  considerably, both
during a storm event, as well as from event to event at a given site and from
site to site within a given city and across the country.   This variability is
the natural  result  of  high variations in rainfall intensity  and occurrence,
                                     5-3

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geographic  features  that  affect  runoff  quantity  and quality,  and  so  on.
Considering  this  situation, a measure  of the magnitude of  the  urban runoff
pollution level and methods for .characterizing its  variability  were needed.
The  event  mean concentration  (EMC),  defined  as  the  total  constituent  mass
discharge divided by  the  total  runoff  volume,  was  chosen as  the primary
measure of the pollutant load.   The  rationale for adopting the EMC for char-
acterizing urban  runoff is discussed in  the  receiving water effects section
of this chapter as well  as  in subsequent  chapters.  Event mean concentrations
were calculated for  each event at  each  site  in the accessible data base.   If
a  flow-weighted  composite  sample  was taken,  its concentration was  used to
represent the  event mean  concentration.   Where  sequential  discrete samples
were taken over  the hydrograph,  the  event mean concentration was determined
by  calculating the  area under  the   loadograph  (the curve  of concentration
times discharge rate over  time)  and  dividing it by the area under the hydro-
graph  (the  curve  of  runoff volume over  time).   Details of  the calculation
procedure have been  described  in the  Data Management Procedures Manual.   For
the  purpose  of determining  event  mean  concentrations, rainfall  events  were
defined to  be separate  precipitation events  when there was  an intervening
time period of at least  six hours without rain.

A statistical  approach  was  adopted for  characterizing the  properties of EMCs
for  standard pollutants.  Standard statistical procedures were used to define
the  probability distribution,  central tendency (a mean or  median) and spread
(standard deviation  or  coefficient of variation)  of EMC data.   EMC data  for
each  pollutant from all  storms  and monitoring  sites were  complied in  a
central data base management system at the National Computer Center.  The SAS
computer  statistical routines and other  standard statistical  methods  were
used to explore and  characterize the  data.  The statistical methods used are,
for  the  most  part,  not explained in  this  report  since  these  are readily
available in the  literature.  Nor are the  operations of  the  SAS routines,
which are available  at most computer  centers.

The  underlying probability  distribution  of  the  EMC  data  was  examined  and
tested by both visual and  statistical methods.  With relatively few isolated
exceptions,  the probability distribution  of EMCs  at  individual  sites can be
characterized by  lognormal  distributions.  Given this, concise characteriza-
tion of  the  variable urban runoff characteristics  at each of  the  sites is
defined by only two values, the  mean or median and the coefficient of varia-
tion (standard deviation divided by  mean).   Because the underlying distribu-
tions  are lognormal,  the  appropriate  statistic  to employ  for comparisons
between individual  sites or groups of sites is the  median  value, because it
is  less  influenced  by the  small number of  large  values typical of  lognormal
distributions  and,   hence,  is a more  robust measure  of   central tendency.
However,  for  comparisons   with  other  published  data  which  usually report
average values  and  for  certain  computations  and  analyses  (e.g., annual mass
loads), the mean value  is more appropriate.

Relationships among  a number of  statistical properties of interest are easily
determined  when  distributions  are  lognormal.   Figure 5-1  illustrates  some
relationships  for lognormal distributions.   In  (a) the frequency distribu-
tions  of two  variable  data sets which  are  log-normal and have  the  same
median  are  shown.  The log transforms of the  data   result  in  normal  bell
                                     5-4

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                    MEAN
                  LOG VALUE
    (a)
                    VALUE
(b)
                                                  3.0
                                                  2.5
1.5
                                                  1.0
                                                    (c)
                                               u 
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shaped  distributions;  more variable  data  (higher coefficient  of variation)
result  in a  greater spread.  Frequency  histograms prepared  using untrans-
formed  data  values produce  skewed  distributions,  as  shown by  (b) which
illustrates two data sets which have the same arithmetic mean.  The effect of
coefficient of  variation is shown as  well  as the relation between mean and
median  for  lognormal  distributions.  An  established relationship  exists
between median and mean, as shown by  (c) and described by:
                           Mean
                          Median
=\1  +  (Coef Var)2
When a  distribution is known to be lognormal the best  estimate  of the popu-
lation  mean is  that derived  from the  lognormal  relationships.   For small
samples  it can be  expected to  be different than  the  result of  a straight
arithmetic  averaging of  sample data;  the  two  estimates  of the mean will give
similar values when the  number of  samples is very large.

In addition, the expected value  at any probability or frequency of occurrence
(X ) can be determined by:
                          X -  exp  (u,   + Z  a,  )
                           a         Inx    a  Inx
where:
     Z    =  the standard normal probability

     y,   =  mean of log- trans formed data
      Inx              ^
     o,   =  standard deviation of log- trans formed data
      Inx

X  can be expressed as  a ratio to the median value by the following equation

which defines the ratio  in terms of the coefficient of variation
                        = exp  (Z   In  (1 +  (Coef Var)2)).
This  relationship  is  shown by  (d) for  90th  percentile  values  (10 percent
exceedance, Z  =  1.2817).

The  establishment  of  the  fundamental  distribution  as  lognormal,  and  the
availability  of   a  sufficiently  large sample  population of EMCs  to provide
reliable derived  statistics, has a  number of benefits:

     -  Concise summaries of highly variable data can be developed.

        Comparisons  of results from different  sites,  events,  etc.,  are
        convenient  and are more easily understood.
                                     5-6

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        Statements can be made  concerning  frequency of occurrence.   One
        can express how  often  values will exceed various  magnitudes of
        interest.

     -  A more useful method of reporting data than the use of ranges is
        provided; one which is less subject to misinterpretation.

        A framework is provided for  examining "transferability"  of data
        in a quantitative manner.

Priority Pollutants

In  cooperation  with  EPA's  Monitoring and Data Support  Division  (MDSD),  a
special study element was built into two-thirds of the NURP  projects  (20 of
28) to identify which of the compounds on EPA's list of "Priority Pollutants"
are found in  urban  runoff,  and the concentrations at which  they occur.   The
base  effort  collected 121 samples of urban  runoff  which were  analyzed for
priority  pollutants.    A   supplementary   special   metals  study   secured
147 samples.  Methods  utilized in this  study  element  are described  in the
following report which covers this activity:

     "NURP Priority Pollutant Monitoring Project:  Summary of Findings",
     December 1983; EPA Monitoring and Data Support Division, Office of
     Water Regulations and Standards, Washington, D.C.

In  addition  to  the above special  study,  as previously mentioned,  most NURP
projects monitored  selected heavy metals  (principally  total copper,  total
lead,  and  total zinc)  in  their  routine  monitoring programs.   Summaries of
these data are presented in Chapter 6.

Hydrometeorological Statistics

Consistent with the adoption of a  storm "event" as the fundamental time scale
used in the analysis of data and the interpretation of effects,  rainfall data
were analyzed to define  "event" statistics for a significant number of loca-
tions throughout the  country.   The SYNOP program was employed for developing
the  statistical parameters  of  rainfall  intensity,  duration,  volume,  and
interval between storm  events.   This program  has  been detailed  in  the NURP
"Data Management Procedures Manual."

In addition to rainfall, rainfall-runoff relationships were characterized for
monitored  storm events.  The  runoff coefficient,  defined  as  the  ratio of
runoff volume to rainfall volume,  was computed, and effects of such catchment
characteristics as  land  use  and imperviousness were investigated.  Long-term
streamflow  records  for numerous stations   across  the  country  were  also
analyzed to characterize regional  trends.

RECEIVING WATER QUALITY EFFECTS

General

A  number  of individual NURP projects examined the  site-specific  impacts of
urban runoff  on water quality  for a  variety of beneficial uses  and receiving
                                     5-7

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water  types.   These results provide  important information on  the  extent to
which urban runoff constitutes a "problem" as well as "ground truth" measure-
ments  against which more generalized techniques  can be  compared.   Method-
ologies  employed  in  these  local  studies  vary and  are  described in  the
individual project reports.  Relevant site-specific project results are cited
in Chapter 9.

Receiving water  impact analyses cannot be readily  generalized  because  there
is a high  degree of site-specificity to the  important  factors.   The type of
beneficial use dictates  the pollutants  which are of principal  concern;  the
type of  water body  (e.g., stream,  lake,  estuary)  determines  how  receiving
water  quality responds to loads;  and physical  characteristics  (e.g.,  size,
geometry,  flows)  have a  major  influence on  the magnitude of  response  to a
particular load.

Despite the inherent limitations of a set  of generalized receiving water im-
pact analyses, a  screening level analysis  was considered a necessary element
for a  nationwide assessment of  the general significance of  urban  runoff in
terms  of  water  quality  problems,   especially  adverse effects  on beneficial
uses.  Accordingly,  a  set of analysis methodologies were adopted and utilized
as screening  techniques  for  characterizing water  quality effects  of  urban
runoff loads  on  receiving water bodies.  A  key  requirement was to delineate
the severity  of  water quality  problems by quantifying  the  magnitude,  and in
the case of intermittent  loads,  the frequency of occurrence of water quality
impacts  of  significance.  These  procedures  are  identified and  described
briefly below.  Significant technical  aspects  are  detailed further in  the
supplementary NURP report which addresses the receiving water impact analysis
methodology.

It was not possible  to perform  a "National Assessment"  in the usual sense of
the term.   NURP has determined that  it is not realistic (if the  basis is
effect on  beneficial use  of a  water body)  to estimate the  total  number of
water quality problem  situations in the nation which result from urban storm-
water  runoff   or  the  cost of   control  which  would  ultimately result.   The
available analysis methods do permit an assessment of a different kind.   NURP
applied the analysis procedures as a  screening  type analysis  to define the
conditions under which problems  of  different types  are  likely or unlikely to
occur.  From  the  results  of  these  screening analyses,  NURP has drawn infer-
ences  and  made general statements  (Chapters 7 and  9) on the significance of
urban  runoff.  Where  it  has  been possible or  practical to  do  so,  these
general  screening  analyses  were  applied  to  local  situations  which  exist
within  certain  of  the   individual  NURP  projects.   Comparisons were  made
between  specific water quality effects or  broader conclusions  relative to
problems derived from both local analysis and general screening methods.

Time Scales of Water Quality Impacts

There  are three  types  of  water  quality impacts associated with urban runoff.
The first type is characterized by  rapid, short-term changes in water quality
during and shortly after  storm events.  Examples of this water quality impact
include periodic dissolved oxygen  depressions due to  oxidation  of contami-
nants, or  short-term increases  in  the receiving water  concentrations  of one
                                     5-8

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or more toxic  contaminants.   These short-term effects are  believed  to be an
important concern and were the prime focus of the NURP analysis.

Long-term water quality impacts, on the other hand, may be caused by contami-
nants associated with suspended solids that settle in receiving waters and by
nutrients which enter receiving water  systems with long  retention times.   In
both instances, long-term water quality impacts are caused by increased resi-
dence  times  of  pollutants  in  receiving waters.   Other examples  of  the
long-term water quality impacts include depressed  dissolved oxygen caused by
the  oxidation  of organics  in bottom  sediments,  biological  accumulation of
toxics as a result  of up-take by organisms in the  food  chain,  and increased
lake entrophication as a  result of the recycling  of nutrients contributed by
urban runoff discharges.   The long-term water quality impacts of urban runoff
are  manifested  during critical periods  normally  considered  in  point source
pollution studies, such as summer,  low stream  flow conditions,  and/or during
sensitive  life cycle  stages of  organisms.   Since  long-term water  quality
impacts occur during  normal  critical periods,  it  is necessary to distinguish
between the relative  contribution of urban runoff  and the  contribution from
other sources, such as treatment plant discharges and other nonpoint sources.
A site-specific analysis is required to determine the impact of various types
of  pollutants  during critical  periods,   and  this  aspect  of  urban  runoff
effects was not addressed in detail in NURP.

A third type of receiving water impact is related to the quantity or physical
aspects of flow and includes short-term water quality effects caused by scour
and  resuspension  of pollutants  previously deposited in  the sediments.  This
category  of  impact  was  not addressed  by NURP,  in  general,  although  one
project provides some information.

As indicated previously,  the first type of change in water quality associated
with discharges from  urban runoff is  characterized by short-term degradation
during and shortly after  storm  events.  The  rainfall process is highly vari-
able in both  time and space.   The intensity of  rainfall at a  location  can
vary from  minute  to minute  and from location to  location.   Phenomena which
are driven by rainfall such as urban runoff and associated pollutant loadings
are  at least  as variable.   Short  term  measurements,  on  a time  scale of
minutes, to define  rainfall, the runoff flow hydrograph,  and concentrations
of  contaminants  (pollutographs)  feasibly  can be taken  at only a  rather
limited number  of locations.  These measurements have usually  been employed
in  an  attempt to refine  or  calibrate calculation  procedures for estimating
runoff  flows  and  loads.   Most  urban areas  contain a  network  of  drainage
systems which  collect and discharge urban runoff  into one  or more receiving
water bodies.   Since  the  rainfall,  runoff, and pollutant loads  vary in both
time and  space,  it  is impossible to determine by  calculation or measurement
the  very  short time scale (minute-to-minute) changes  in water quality of a
receiving  water  and   assign the  changes  to  specific   sources  of  runoff.
Although very short duration exposures (on the order of minutes) to very high
concentrations  of toxics  can produce  environmental damage (mortality or sub-
lethal  effects)  to aquatic  organisms, it  is  likely  that  exposures  on  the
order of hours  have the highest possibility  of  causing adverse environmental
impacts.   This results,  in  part,  from  the  smoothing  obtained by  mixing
numerous sources which have high frequency (short-term)  variability.
                                     5-9

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In view of  the  above discussion,  the time scale used by NURP for analysis of
short-term  receiving water  impacts  is  the rainfall event time scale which is
on the order  of hours.   To represent the average concentration of pollutants
in urban  runoff  produced during  such an  event,  NURP  used the  event  mean
concentration.

Criteria/Standards and Beneficial Use Effects

As discussed  in  previous  chapters, three  definitions  have been  adopted to
assess receiving  water problems associated with urban runoff; (1) impairment
or denial  of  beneficial use,  (2) violation of numerical criteria/standards,
and  (3) local perception of a problem.   The  procedures  and methods employed
in the NURP assessment  focus on  the first two problem definitions.  A frame-
work  for  identifying target  receiving water  concentrations  associated  with
the criteria  standards  and beneficial use  problems  are  provided below.   The
third  problem  type,  local  perception  of  a  problem and  degree  of  concern
cannot be addressed by these quantitative procedures.

The analysis  methods employed make it possible to  project  water quality ef-
fects  caused  by intermittent,  short-term urban  runoff discharges.   Where
appropriate, these effects are expressed  in terms of the frequency at which a
pollutant concentration  in  the water body is equalled or exceeded.  However,
if the basis  for determining the significance  of  such  water quality impacts
(and  hence  the  need  for control)  is taken to be the  effect such receiving
water  concentrations have on  the  impairment  or  denial of  a  specific  bene-
ficial use, then  it  is necessary to go one  step further.  A basis is required
for judging the degree to which a particular water quality impact constitutes
an impairment of a beneficial use.   With intermittent  pollutant discharges;
effects are variable and are best expressed in terms of a probability distri-
bution from which estimates can be made  of the frequency with which effects
of various  magnitude occur.

There  is a  rather broad consensus  that  existing  water  quality criteria, and
water uses  based  on  such criteria, are most relevant when considered in terms
of continuous  exposures  (ambient  conditions).   Even where  continuous  dis-
charges are involved,  there has been  discussion  and debate  as  to whether a
particular  criterion should be interpreted  as  some appropriate "average" con-
dition or  a  "never-to-exceed" limit.   The basic  issue is whether  the  more
liberal interpretation  will provide acceptable protection  to the beneficial
use for which the criterion  in question  has been  developed.  The only reason
such  distinctions become  an issue is because the  practical  feasibility or
relative economics,  or  both, are sufficiently  different  that one is encour-
aged  to  question whether  the  more restrictive interpretation is  overly  (or
even  excessively)  conservative  in  terms  of providing protection for the as-
sociated beneficial use.

The  issue   (i.e., whether  traditional  ambient criteria  are  excessively  con-
servative  measures  of   conditions  which  provide  reasonable assurances  of
protection  for  a beneficial use when exceeded only  intermittently)  is  par-
ticularly appropriate in the case of  urban storm runoff.   Analysis of rain-
fall  records  for a  wide distribution of locations in  the  nation indicates
that, even  in the wetter parts of the country, urban runoff events occur only
                                     5-10

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about 10 percent of the  time.   There are regional  and  seasonal differences,
but typical values  for annual average  storm characteristics in  the eastern
half of the United States are:

Storm Duration
Interval Between
Storm Mid-Points
Average
(Hours)
6
80
Median
(Hours)
4.5
60
90th Percentile
(Hours)
15
200
These estimates are based  on results from an  analysis  of long-term rainfall
records  for  40 cities throughout  the country.   Median  and  90th percentile
values are derived from data mean and variance based on a gamma distribution,
which has  been shown  to  characterize the  underlying distribution  of storm
event parameters quite well.

In the  semi-arid  regions  of the western  half of the country,  average storm
durations tend to be  comparable to the above, but  average intervals between
successive storms increase substantially (two to  four fold)  and  are highly
seasonal.  With urban  storm  runoff, therefore, one  is dealing with pollutant
discharges which  occur over a  period of a  few  hours every  several  days or
more or  after  long  dry periods.  In  advective rivers  and streams, the water
mass influenced by urban runoff tends to move downstream in  relatively dis-
crete pulses.  Because of  the variability in  the magnitude of  the pollutant
loads from different  storm events, only  a  small percentage  of  these pulses
have high pollutant concentrations.

There are currently no formal "wet weather"  criteria and, thus,  no generally
accepted way intermittent exposures having time scale characteristics typical
of urban runoff can be  related to  use  impairment.  In  the  belief  that it
would be inappropriate to  ignore such considerations in a general evaluation
of urban runoff, NURP  has  developed  estimates for concentration levels which
result  in  adverse impacts  on beneficial  use when  exposures  occur intermit-
tently  at  intervals/durations   typical   of  urban   runoff.   These  "effects
levels" were used to interpret the significance of the variable, intermittent
water quality  impacts  of urban runoff.   It  should be  understood  that these
effects  levels  do not represent  any formal  position taken by  EPA,  but are
simply  the most  reasonable yardsticks available to  meet  the  immediate needs
of the  evaluation of urban runoff.   As used in the screening analysis proce-
dures,  alternative  values   for  "effects   levels"  may be  readily  substituted
when either more accurate  estimates  can  be  made, or more  (or less) conserva-
tive approaches are indicated in view of the importance of a particular water
body or beneficial use.

Table 5-1  summarizes  information on  water  quality  criteria  for a number of
contaminants  routinely found   in  urban   storm runoff.   The  data presented
include:

     -  Water quality  criteria  for  substances on EPA's priority pollut-
        ant  list (45 FR No. 79318, 11/28/80).  These  criteria  provide
                                     5-11

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                                         TABLE  5-1.    SUMMARY OF  RECEIVING WATER TARGET CONCENTRATIONS USED  IN
                                                                 SCREENING  ANALYSIS  - TOXIC  SUBSTANCES
                                                          (ALL CONCENTRATIONS  IN  MICROGRAMS/LITER,
ui
 I
M
Contaminant
Copper



Zinc



Lead



Chrome (+3)

Chrome (+6)
Cadmi urn


Nickel


Water
Hardness
mg/1
(as Ca C03)
50
100
200
300
50
100
200
300
50
100
200
300
50
100
300
-
50
100
300
50
100
300
Freshwater
Aquatic Life
24 Hour
5.6
5.6
5.6
5.6
47
47
47
47
0.75
3.8
12.5
50.0

(44)
(C)
0.29
0.01
0.02
0.08
56
96
220
Max
12
22
42
62
180
321
520
800
74
172
400
660
2,200
4.700
15,000
21.0
1.5
3.0
9.6
1,090
1,800
4,250
Saltwater
Aquatic Life
24 Hour
4.0
4.0
4.0
4.0
58
58
58
58

(25)

(C)

N.P.
18

4.5


7.1

Max
23
23
23
23
170
170
170
170

(670)

(A)

(10.300)
(A)
1260

59.0


140.0

Human
Ingestion
(1)
NP



NP




50.0



170.00
50.0

10


13.4

Estimated Effect Level
For Intermittent
Exposure
Thresh-
hold
20
35
80
115
380
680
1,200
1,700
150
360
850
1.400

8,650

3
6.6
20



Significant
Mortality
50 - 90
90 - ISO
1ZO - 350
265 - 500
870 - 3.200
1,550 - 4,500
2,750 - 8,000
3.850 - 11,000
350 - 3,200
820 - 7,500
1,950 - 17,850
3,100 - 29.000



7 - 160
15 - 350
45 - 1,070



                                   NOTES:

                                   -  NP = No criteria proposed.

                                   -  Some toxic criteria are related to Total Hardness  of receiving water.  Where this applies, several values are  shown.  Other
                                      values may be calculated from equations presented  in EPA's Criteria Document (Federal  Register,  45,231, November 28, 1980).
                                      Where a single value is shown, water hardness does not influence toxic criteria.

                                   -  Concentration values shown within parentheses (  )  are not formal criteria  values.  They reflect  either chronic  (C) or acute
                                      (A) toxicity concentrations which the EPA toxic  criteria document indicated have been  observed.   Values of this type were
                                      reported where the data base was insufficient (according to the formally adopted guidelines which were used in developing the
                                      criteria) for EPA to develop 24 hour and Max values.

                                   -  Note (1):  The "Human Ingestion" criteria developed by the EPA Toxic Criteria documents are indicated to relate to ambient
                                      receiving water quality. The Drinking Water Criteria relate to finished water quality at the point of delivery for
                                      consumption.

                                   -  Estimated Effects levels reflect estimates of the  concentration levels which would impair beneficial uses under the kind of
                                      exposure conditions which would be produced by Urban Runoff.  They are an  estimate of  the relationship between continuous
                                      exposure and intermittent, short duration exposures (several  hours once every several  days).   Threshold concentrations are
                                      those estimated to cause mortality of the most sensitive individual of the most sensitive species.

                                      Significant Mortality concentrations are shown as  a range which reflects 50 percent of the most  sensitive species and
                                      mortality of the most sensitive individual of the  25th percentile species  sensitivity.

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        an  extensive set  of  numerical  values  derived  from  bioassay
        studies.

     -  Estimates of  "effects  levels" which  are  suggested by  NURP an-
        alysis  to  be relevant  for the  intermittent exposures charac-
        teristic of urban runoff.

By  incorporating  the numerical  values  for  EPA's  ambient  water  quality
criteria  and  the  concentration  levels  suggested  by  NURP for intermittent
effects in the same table (or on the  same graph in  Chapter 7) ,  a convenient,
concise comparison is provided of the practical implications  of applying one
or the  other  as the  yardstick  for judging the protection or  impairment of
water use.  The two sets of numerical values thus  provide measures for two of
the three options  for defining a problem:  violation of criteria  or actual
impairment of a beneficial use.

Comparison of the  pollutant  concentrations  in urban  runoff showing the fre-
quency  and  magnitude  of  exceedance  of  ambient  criteria and intermittent
effects levels provides a qualitative sense of the  control requirements  (and
implications  regarding  costs)  attendant  on the adoption of either problem
definition as the operative one.

Rivers and Streams

The approach  adopted to  quantify the water quality effects of urban runoff
for rivers  and  streams  focuses  on  the  inherent variability  of the runoff
process.   What  occurs  during  an  individual  storm  event  is  considered
secondary to the overall effect of a  continuous spectrum of storms  from very
small to  very large.  Of basic concern  is  the probability of  occurrence of
water quality effects of some relevant magnitude.

To consider  the intermittent  and  variable nature  of  urban  runoff,  a sto-
chastic approach was adopted.   The method  involves a  direct calculation of
receiving water  quality  statistics using the  statistical properties  of the
urban  runoff  quality  and other  relevant variables.   The  approach  uses  a
relatively simple model of the physical  behavior  of the  stream or  river (as
compared  to many of the deterministic  simulation  models).  The  results are
therefore an approximation, but appropriate  as a  screening tool.

The theoretical  basis  of  the technique  is  quite  powerful as it  permits the
stochastic nature of runoff process to be explicitly considered.  Application
is  relatively  straightforward,  and  the procedure  is  relevant to  a  wide
variety of cases.   These  attributes  are particularly advantageous  given the
national scope of the NURP assessment.   The details of  the stochastic method
are summarized and presented below.

Figure 5-2 contains  an idealized  representation  of urban  runoff discharges
entering a stream.  The discharges usually enter the stream at  several loca-
tions but are  considered  here  to be  adequately represented by  an equivalent
discharge flow which-enters the system at a  single point.

Receiving water  concentration  (CO) is the resulting concentration after com-
plete  mixing of  the runoff and stream  flows and is interpreted as the mean
                                     5-13

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                                                                  CM
                                                                  CO

                                                                  8
                                                                  C\I
                                                                  00
       URBAN RUNOFF
   QR  =FLOW
   CR •= CONCENTRATION
  STREAM  FLOW
                                         \
                                  URBAN \
                             - m
                 UPSTREAM

           OS = FLOW
           CS ^CONCENTRATION
    DOWNSTREAM
    (AFTER MIXING)
    =  FLOW
CO =  CONCENTRATION
      Figure 5-2.  Idealized Representation of Urban Runoff Discharges
                            Entering a Stream
stream concentration  just downstream of all of the discharges  as  shown  in
Figure 5-2.  The four input variables considered are:

     -  Urban runoff flow  (QR)

     -  Urban runoff concentration (CR)

        Stream flow (QS)

        Stream concentration  (CS)

Each is considered to be a stochastic random variable, which together combine
to determine  downstream flow and  concentration.  In addition, all variables
are assumed to be  independent,  except urban runoff  flow and streamflow where
correlation effects can be incorporated  as warranted.
                                   5-14

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An essential condition of the current computational structure is that each of
the four variables which contribute to downstream receiving water quality can
be  adequately  represented  by  a  lognormal  probability  distribution;  from
analysis of data  or other estimating procedures,  the  statistical properties
of each of the  input  parameter distributions are  defined.   Examination  of a
reasonably broad  cross-section  of data indicates  that  lognormal probability
distributions can adequately represent discharges from  the rainfall/runoff
process, the  concentration  of contaminants  in  the discharge, and  the daily
flow record  of  many  rivers  and streams,  particularly  for a  national scale
screening approach.   It  should be noted,  however, that modifications  of the
computation techniques could be made to accommodate the use of other distri-
butions (e.g., gamma,  exponential) for some or all of the  parameters.

The analysis procedure is described in more  detail in  the supplementary NURP
report cited earlier.   It essentially operates as follows:

     -  Downstream Concentrations.  Stream concentrations  of a pollutant
        are considered to result from the combination of upstream flow
        at background concentration and runoff  flow at  its concentra-
        tion.   Variations  in  stream  concentrations  below  the  urban
        runoff discharge result from variations in each of these inputs;
        the most significant source of variation being whether or not an
        event is  occurring   (i.e.,  whether runoff  flows  and  loads are
        present).   Stream flows must be considered because of the major
        effect  of dilution  on  the resulting concentrations.   Upstream
        concentrations can,  however,  be  set at  zero  for  the calcula-
        tions; in  which  case,  the  result  obtained  is  the  .exclusive
        effect of urban  runoff  discharges, and  not the overall expected
        stream concentration.  Effects of urban  runoff  can be evaluated
        by considering only the periods during which runoff occurs.

     -  Parameter Estimates.  Estimates for  runoff flows  and concentra-
        tions  are  developed  from  information  derived  from the  NURP
        monitoring programs.  Information on stream flow can be obtained
        from analysis of local stream gage records.  Upstream concentra-
        tions  tend to  be  very  site-specific;   for  this  reason,  the
        screening  analysis  calculated only  the  effect of  urban runoff
        discharges.

     -  Statistical   Calculations.   From  the   statistical  properties
        (specifically, the means  and standard deviations)  of the flows
        and  concentrations,  properties  of  the  dilution  ratio  can  be
        defined,  and  the statistical  properties  of  the   resulting in-
        stream  concentrations  are  calculated  directly.    The frequency
        with  which any  particular target  concentration  is  exceeded
        during wet  weather  can be calculated from the  statistical pro-
        perties  of   stream  concentration,  using  formulas  or  scaled
        directly  from a  standard plot of  cumulative  (lognormal)  proba-
        bility distributions.

        The frequency with  which  the  target concentration  is exceeded
        during  all  periods  — wet and dry — is  simply  the  product  of
                                     5-15

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        the wet  weather frequency and the  probability (frequency)  that
        it is  raining.   The probability that it  is  raining at any time
        is defined  by the ratio  of  mean storm duration  to mean inter-
        storm period, derived from the rainfall statistics.

        D = mean duration of storms             ...        .
        •7	T-—	., .  .	 = fraction of time it is wet
        A = mean interval between
               storm midpoints

        Mean  Recurrence Interval.   In  the  presentation  of  results  in
        Chapter 1,  the  probability  distribution  of  event  mean stream
        concentrations   of  an  urban  runoff  pollutant  during  runoff
        periods  is  converted  to  a Mean  Recurrence Interval  (MRI)  as a
        device to  assist in the  interpretation of results.  The recur-
        rence  interval  is  defined  as  the  reciprocal of probability.
        Because  the basic  calculation  is  based  on  storm  events,  this
        definition  yields  the  overall average number  of  storms between
        specific .event  occurrences.   Event recurrence is  converted  to
        what  is  believed  to  be  a  more  meaningful  time  recurrence  by
        dividing by the average  number  of storms  per  year,  which  is
        developed from analysis of rainfall records and defined as

             Hours/year  = 8760                  „  .
             	A—:—	:—r—r	 = average # storms per year
             Average interval between        '           e
                     storm midpoints

        As an  example  of the MRI  calculations consider a stream concen-
        tration  which  has  an ' exceedance   probability  of 1.0 percent
        (Pr = 0.01)

             Recurrence  Interval = 1/Pr = 1/0.01 = 100

        The analysis  is in terms of storm  events, not time.  Therefore
        this result is interpreted  as one  storm  in  every 100 events  on
        average, will  produce  concentrations greater  than the selected
        value.  For an area where rainfall patterns  produce an average
        of  100 storms per  year,  the  average  recurrence  interval  ex-
        pressed in  time  units rather than events, is:

             Recurrence  _ event recurrence	100 events    _
             Interval      # events/year     100 events/year
              (time)
Currently, the primary use of the above procedure  is  as  a screening tool in
which  approximate results and  relative  values  are  of  interest.   In  this
regard, NURP  believes  the Mean Recurrence  Interval  is a  very useful defini-
tion.   It should be  interpreted as  the  long-term  average  interval between
occurrences.

When results  of this nature  are  interpreted,  the following factors should be
noted.  The recurrence intervals of most interest  relate to very low proba-
bilities  of   occurrence.   The tails  of distributions may  have  appreciable
uncertainty,  and in the natural water systems, distributions may be lognormal
                                     5-16

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over the bulk of the range but may  deviate from the assigned distribution at
the extremes.   Computed  stream concentrations  at long  recurrence  intervals
are likely to be  conservative,  that is, overstated because  there  are likely
to be practical upper  limits for runoff  concentrations and lower  limits to
stream flow.

It also should be noted that serial correlations  of  streamflows  or the tend-
ency of wet  and dry  years  to occur in clusters,  though not  a general behav-
ior, may  be  significant  in  some  cases.   This  situation  would  cause  the
average one year condition, for example,  not  to repeat itself every year but
rather to occur several times per year, at intervals greater than one year.

Other Receiving Waters

Other receiving waters of general interest in assessing urban runoff effects
include lakes, estuaries,  embayments,  and coastal zones.  The methods adopted
for lakes are briefly described below.  The other receiving  waters generally
require site-specific and often complex analysis  techniques  (numerical meth-
ods, multi-dimensional  modeling,  etc.).  Given this, a generalized screening-
level assessment  was  not  believed to be  appropriate  for  this  report.   A
number of  the individual  NURP projects  consider these  coastal  water bodies
and report on the specific methods adopted and results obtained.

For lake eutrophication problems,  the  time scale for analysis is considerably
longer  than  the  short (event  scale)  periods necessary  for estuaries  and
rivers.   For this case,  annual  average  loads were  used in  a  steady-state
analysis performed using the type of empirical model advanced by Vollenweider
and others.   The EMC  data developed  from NURP  monitoring  programs  can be
readily converted to annual loads  directly from annual  flows or  indirectly
based on annual rainfall.

For total  phosphorus,  typically  the  limiting  nutrient of  concern,  average
concentrations are calculated using the following formula:
                                     W
                             P = —;	 • 1000
                                 H/T •  U
                                        s

The input values  include  pollutant  mass loading  (W),  lake  physical charac-
teristics of depth (H)  and residence time  (T)  and reaction rate coefficients
(u ).   The relative  contribution of all load  sources to lake total P concen-
  s
trations can be defined by solving this equation for each of the sources.  By
comparing results in terms of lake  concentrations for initial conditions  (no
control), and then modifying loads  to  reflect various levels of  control, al-
ternative control operations can be compared directly to effect on lake water
quality.

Some judgement  is involved  in  defining acceptable  lake water  quality con-
centrations,   which depend in part  on water  use and  on regional  norms  and
expectations.
                                     5-17

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EVALUATION OF CONTROLS

General

The  evaluation  of  controls  has two  elements:    (a) characterizing  the  con-
trols'  performance capabilities and  (b) defining  costs.   For this report,"
only  the  characterization of  performance is emphasized;  cost relationships
are  addressed to  a  more limited  extent.   EPA's  Economic Analyses  Staff,
Office  of  Analysis and Evaluation, has  prepared the following report under
contract:

     "Collection of  Economic Data  from  Nationwide  Urban  Runoff  Program
     Projects," EPA Office of  Water Regulations  and Standards, April 7,
     1982.

This  report,  issued  at  an  early  stage  in the  NURP program, assembled  and
analyzed  cost  information  on  potential  control  measures.   Useful  cost
information for detention basins was developed by  the  Washington,  D.C.  area
NURP project and is discussed  further in Chapter 8.

Detention Basins

There are  a number of procedures which  can be adopted  for evaluation of  de-
tention basin control devices.  Procedures adopted by.  individual  NURP proj-
ects  are  described  in project  reports.   The procedure  adopted  by  NURP  to
generalize the  analysis  of  detention basins, and  provide a  planning level
basis for  estimating capabilities  and requirements, is detailed  in a deten-
tion basin handbook being issued by NURP as a supplementary report.

Results  presented  in Chapter 8 provide a summary of observed  performance
characteristics of the detention devices monitored under the NURP program and
a projection of long-term performance expected on the basis of basin size and
regional rainfall  characteristics.  The  latter result  is  based on the proba-
balistic analysis  methodology described in the  supplementary  report.  Plan-
ning  level cost  estimates for  control  of urban runoff using  this technique
are also presented.

Street  Sweeping

A number of the individual NURP projects adopted street sweeping as a princi-
pal  subject of investigation.   Procedures and results  are described in indi-
vidual project reports and are consolidated and summarized in Chapter 8.   The
adopted procedure  and detailed results  are  presented  in  the supplementary
NURP report, which was cited earlier.

Recharge Devices

Recharge  devices  include impoundments  or other  structures  such  as  pits,
trenches,  retention  basins, percolating catch  basins,  in-line  percolation
chambers or perforated pipes,  which  function  by  intercepting some portion of
storm runoff and allowing it to percolate into the ground.
                                     5-18

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One of the basic questions  which arises when controls of this  type  are con-
sidered is whether  the percolation  encouraged will produce  undesirable de-
gradation of  groundwater  quality.   This  aspect was  examined  by two  NURP
projects,  and is discussed in Chapter 7 of this report.

Evaluation of percolating basins of any  size is readily accomplished using
the standard storage/treatment routines of stormwater models such as STORM or
SWMM.  In such  cases the local  soil permeability (the percolation  rate)  is
applied as the  treatment  rate.   In  addition,  statistical  analysis procedures
described in  "A Statistical Method  for  the Assessment of  Urban Stormwater"
(EPA 440/3-79-023,  May 1979)  have  been developed.  A  probabalistic  analysis
methodology adapted from the latter approach has been used by NURP to provide
estimates  of  performance  capabilities   of   recharge devices,  which  are
presented in Chapter 8.  A detailed discussion of the methodology is provided
in the supplementary NURP report on detention/recharge devices cited earlier.
                               5-19/5-20 blank

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                                  CHAPTER 6
                       CHARACTERISTICS OF URBAN RUNOFF
INTRODUCTION

This chapter presents a condensed summary of data developed by the individual ,
NURP projects together with analysis results and interpretations based on the /
aggregated data from all projects.

Both the format for the summaries and the evaluations performed were selected
to best serve  the  NURP objective of developing a  national  perspective.  The
results presented  do not exhaust the  useful information and  insights which
can be derived from  the extensive data base that  has  been  assembled.   Indi-
vidual project reports and a  substantial  number of articles  published in a
variety of technical journals independently examine specific aspects of urban
runoff, often from the perspective of local issues.

Comprehensive tabulations of NURP data have been  assembled and  will be made
available to interested parties  for use in  local  planning  or  continuing re-
search or engineering activities.  As noted  below,  only  a portion of the en-
tire data  base generated  by  the  28 NURP projects has. been  made  generally
accessible at  this time.  Under an ongoing  effort, the entire  data base is
being subjected to final quality  assurance  checks  and placed into a separate
file, copies of which  will  be  made  available to interested parties  upon re-
quest.  In  addition,  a summary  of  the event  averaged  data,  used  for the
analyses presented in  this  chapter,  is reproduced  in  a  Data  Appendix issued
with this report.

Field monitoring was conducted to characterize urban runoff flows and pollut-
ant concentrations and mass loadings.   This was done for a variety of pollut-
ants at  a substantial  number  of sites  distributed throughout  the  country.
The  resultant  data represent  a  cross-section of  regional  climatology, land
use types, slopes, and, soil conditions and thereby provide  a  basis for iden-
tifying patterns  of  similarities or differences  and testing  for their sig-
nificance.  To meet the objective of maximizing the degree of transferability
of urban runoff data,  the  NURP approach involved  covering  a  spectrum of re-
gional and  land use characteristics,  requiring  consistent  quality assurance
programs among all projects,  and encouraging each  of  the projects to obtain
data for a statistically significant number of storm events at a site.

The portion of the NURP data base used in  the characterization of urban run-
off presented in this  section  excludes monitoring  sites  which are downstream
of devices  which  modify runoff  (e.g.,  detention basins).  The  data base of
acceptable "loading  sites"  consists  of 81 sites in 22 different cities, and
includes more  than 2300 separate  storm events.  The actual number of events
                                     6-1

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for specific pollutants varies, and is somewhat smaller than the total number
of storms monitored  because all pollutants were not measured  for  all storms
at all sites.

Data summaries and analyses were  performed using  storm event average values;
within-event  fluctuations are  not  considered.   An event  mean concentration
(EMC)  for pollutants  of  interest  has  been determined  for  each  monitored
storm.  Preliminary results presented in an earlier NURP report were based on
analysis  of  "pooled"  EMCs which were  available  at  the  time  regardless  of
site.  This provided a useful start,  a reference  for individual NURP project
activities,  and  established the  order of  magnitude  of  concentrations  of
various pollutants in  urban runoff.  With the  substantially  larger data set
now  available,  a more useful  approach  is possible.   For the  analyses  and
comparisons presented  in  this chapter, the storm event  average  data  were
aggregated by site to  describe site characteristics.   Site  mean values  were
then aggregated or compared.

Summaries, comparisons, and evaluations were restricted to concentrations and
runoff-rainfall ratios.  Although loading data  (Kg/Ha)  are also available for
all monitored storms,  they have not been used  in  comparisons for the follow-
ing reason.   Mass load is  very strongly influenced by the  size (volume)  of
the monitored storm  event.  Monitored events usually  represent a  very small
sample of all storms for  an area, are generally biased toward larger events,
and are different from site to site.   Therefore comparisons  between sites or
locations using  loading data derived from monitored storms  are quite likely
to present a distorted picture.

Event mean concentrations,  on the other hand,  have been determined to be es-
sentially uncorrelated with runoff volume,  as discussed further later in this
chapter.   Site  comparisons  can be made with  high confidence  levels  using
concentration data,  and the most meaningful load  comparisons  would be those
developed by using concentrations, area rainfall volumes, and runoff-rainfall
relationships.

Separate  summaries  of  results are provided below for  standard pollutants,
coliform bacteria, pollutant  loads, and priority pollutants.

LOGNORMALITY

As was pointed out in  Chapter 5,  the  key to the mathematical tractability of
the NURP  methodologies is  that the data can be well  represented  by a known
probability density  function  (pdf).  There are  actually two  issues involved;
(1) the  adequacy of  the  assumed  pdf  in terms  of  representing the essential
characteristics  of the data  set  in question,  and  (2)   the estimation of the
parameters of the population pdf that  the observed data set  is presumed to
represent.  These will be discussed in turn.

Adequacy of Representation

One can fit a polynomial  of order (n-1)  exactly to any data  set of n numeri-
cal items, but its utility  in predicting the probability of realizing a given
value on a subsequent  trial (either within or  outside  the  original data set,
                                     6-2

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i.e.,  the interpolation  or  extrapolation problem)  is  likely  to be  very
limited.  The number  of  parameters  involved and the  need  to investigate its
properties on an individual basis are  further  deterrents  to such a practice.
There is no dearth of pdf's  that have  been the subject of intensive investi-
gation.  However, the selection of a pdf is an objective  choice that is best
made based on professional knowledge of the processes deemed important to the
desired probability model and the use  to be made of  it.   For example,  if the
data are known  to  result from the  product of  many small  effects, their logs
will be the sum of the logs of these effects.   By appeal to the central limit
theorem, it is  known  that this sum is asymptotically normal and, therefore,
that the data will be lognormally  distributed.  Based upon such natural ex-
pectations and  prior  experience (of a growing body  of other  workers  in the
field as well),  the lognormal pdf was chosen.   The fact that the variables of
interest can assume only positive values with a finite mean and a finite non-
zero lower bound (even in a standardized form)  leads  to  the rejection of any
pdf defined over the  entire  real domain,  such  as the normal distribution for
instance.

There are a number of statistical procedures  for evaluating the normality of
a  complete  sample;  at  least nine  can be  found  in  the  current literature.
Some are origin and  scale invariant (e.g., the Shapiro-Wilk,  standard third
moment,  standard  fourth  moment, and studentized  range)  and thus are  appro-
priate for testing the composite hypothesis of normality.  Others require the
complete specification of the null distribution  (e.g.,  Kolmogorov-Smirnoff,
Cramer-Von Mises, weighted Cramer-Von  Mises,  modified Kolmogorov-Smirnoff-D,
and chi-squared) , and typically, the mean  and  variance of 'the specified nor-
mal hypothesis  are  taken to be the  known  mean and variance  of the complete
sample.  Some procedures  (e.g., chi-squared) utilize  the specified theoreti-
cal pdf, while others (e.g.,  the modified Kolmogorov-Smirnoff D-test) utilize
the cumulative frequency distribution.

In testing for  normality  (in  the logorithmic  domain  in our case), one speci-
fies the  level  of significance (a), i.e.,  the probability  of rejecting the
null hypothesis when it  is  in fact  true   (Type I error) .   The  choice  of a
requires tempered judgement,  however.  The power of  a test (6) is the proba-
bility of rejecting the  null hypothesis when  it is  in fact false.   The pro-
bability of accepting the null hypothesis  when it is  in  fact  false (Type II
error)  is 1-6.  For  a given  sample size and test, fixing  a value for a also
determines a value for 6  (i.e., they are not independent).  The smaller the a
level, the  less powerful the test.  Thus  one   is forced to make a trade-off
between the consequences of a Type  I or II error when selecting an a value.

The median EMC values for each  constituent at  each site were calculated, and
these  sample  sets  were  examined  for  lognormality  using the  Kolmogorov-
Smirnoff D test.  The a  levels  for TSS,  Total  P,  TKN, Total Pb, and Total Zn
were all greater than 0.15,  indicating a high  power  level.    In other words,
these sample sets are extremely well represented by a lognormal distribution.
For COD and nitrate + nitrite the a levels were 0.059 and 0.057 respectively,
indicating a  lower power level but  suggesting that  even  for  these constit-
uents  the lognormal  distribution  quite  well   describes  the  data.   Because
BOD, Soluble P, and Total Cu were measured at  fewer  than half of the project
                                     6-3

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sites,  the D-test  could not meaningfully  be used  (i.e.,  n is  too small).
Stated  another  way, at  the  a = 0.05 level,  the hypothesis  that  the samples
were drawn from a population with a lognonnal distribution cannot be rejected.
for any of the constituents examined.

Turning to the  individual sites, there  were very few instances  where  n was"
large enough to support  the meaningful use  of the D-test,  and so a different
approach for examining the appropriateness  of the lognormal distribution was
used.   Essentially  it consisted of  examining the cumulative  frequency dis-
tributions  (in  log space) and  third and fourth moment  based statistics for
adequacy of representation.   Taking  into account detection limit phenomenon,
uncertainties associated with  sampling  and  analytical  determination errors
(especially at  low concentration  levels),   and  an occasional  outlier,  well
over 90 percent of  the constituent distribution  at all NURP sites were quite
well represented  by the lognormal distribution.  For  the  few remaining data
sets, the  lognormal distribution, although  not perfect,  was adequate for our
purposes.

Estimation of Parameters

As noted in Chapter 5, the lognormal distribution is completely specified by
two  parameters,  the mean  and the coefficient of variation.   The  values of
these two parameters as  calculated from  the  sample data  set are the best es-
timates of  the  parameters of the underlying population  in the  maximum like-
lihood  sense.    For  this reason,  they  were used   in  the NURP  analysis.
However,  due  to  the  existence of  detection limit  problems  and  sampling/
analytical  determination  errors,  the reasonableness  of  this  decision  was
examined in general for  all  constituents and in great  detail  for Total Cu,
the results of which will be described below.

For  each  of the  49 NURP sites  where  at least  five  Total Cu determinations
were made, data were  plotted (in logarithmic  form)  on probability  paper.  A
line of best  fit  was  drawn in,  using  professional  judgement where detection
limit or outlier problems  existed, and the  values of the median and standard
deviation were read from the plot and converted into arithmetic space.  These
were  then  compared with those values calculated from  the  data  themselves.
One  example is given in  Figure 6-1  (the  116th and  Claude Street  site in
Denver).  Here the median and coefficient of variation from the plot  (20 pg/1
and  0.75)  compare  very well with  those calculated  directly  from  the  data
(22 yg/1 and 0.74).

An example of  an outlier  plot  is  given in  Figure 6-2  (the strip commercial
site in Knoxville, TN).  The one very low value  (1 ug/D  is one-twentieth the
typical detection limit  (20  yg/1) and clearly does  not belong  to  the same
distribution that  the  other values  do.  Ignoring it,  a  very good fit exists
and  the parameters  of  the  plot are  30 ug/1 and  0.37  for the median and
coefficient of variation as  compared with the 25 ug/1 and 1.35 values calcu-
lated  from the  data.   The difference in medians  is not too great,  but the
difference  in  coefficients  of  variation is quite  large  (over a  factor of
3.5).   This means that the upper end  of the tail of  the  pdf  is  quite over-
estimated  by the  parameters estimated from the data and, consequently, that
                                     6-4

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en
I
ui
      -1
      -2
      -3
      -4
       0.01    0.05 0.1 0.2   0.5   1    2
10
20
30   40  50   60   70
80
90
95
98  99
 1   i

99.8 99.9
99.99
                                  Figure 6-1.
   Cumulative Probability Distribution of  Total Cu

       at  CO1 116 and  Claude Site

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en
i
       -2
       -3
       -4
       -5
       -6
       -7
                                                                                                                            rt
                                                                                                                            oo
                I   I   I
        0.01
0.05 0.1  0.2  0.5   1    2
10
20   30   40   50   60   70    80     90    95    98  99
99.8 99.9
99.99
                          Figure 6-2.   Cumulative Probability Distribution of Total Cu at TNI SC Site

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subsequent analyses  will  be extremely  conservative,  i.e., higher  values of
copper concentrations will occur less often  than  predicted.   In general, the
effect of an  outlier is to increase or decrease  the  estimate of the median,
depending upon  whether the  outlier  is high  or  low,  and  to  increase the
estimate of the  coefficient  of variation as compared to  those obtained from
the remainder of the data.

An example of a  detection limit problem is given  in  Figure  6-3, the plot of
copper data of  the Durham, NH parking  lot  site.   Although only four points
appear on the plot,  actually n = 31, meaning that 27 points  are represented
by the first plotting position (90.6 percent).   These values  (all reported at
100 ug/1) are presumably  the detection  limit  of  the analytical laboratory.
Of course in reality not all 27 values are 100  ug/1; they are simply equal to
or less  than  this value.   Fitting  a  line to the  remaining  four data points
merely assigns  appropriate plotting positions  to these  "less  than" values.
The estimates of the median and coefficient of variation from the plot are
63 ug/1 and 0.36 respectively, as compared to the estimates  from the data of
103 yg/1 and 0.13.   In this  case, the  latter significantly overestimates the
median and  significantly   underestimates  the coefficient of  variation, and
this  is  the  general  effect  when a detection  limit problem  is present.  In
terms of the  effect  on prediction  of rare occurrences of high copper levels
(the upper tail  of the pdf)  these effects are  somewhat  counterbalancing.  To
the extent that  the  increase in the coefficient  of variation dominates, the
results of subsequent analyses will not be conservative, since larger concen-
trations will occur somewhat more frequently than would be predicted.

When the results of  this  exercise  are compared -for all  49 sites,  the median
as estimated  from  the plot was found to  be  higher than  that estimated from
all the  data  at  only six sites, was  equal  at five  sites,  and was  less at
38 sites.  However, at only  three sites was  the change  greater than 10 ug/1.
Considering the population of all copper sites,  the average median is 47 ug/1
and the coefficient of variation is 0.84 when the estimates  are based on all
the data.  If the  estimates  are based upon  the plots,  the respective values
are 42 ug/1 and  0.24  respectively.  The  significant reduction in the coeffi-
cient of variation in this latter case  deserves comment,  because it suggests
that much of the apparent variability from site to site  is due to data arti-
facts such as detection limit phenomena, outliers, and/or sampling/analytical
errors.  Similar comparisons of  the coefficients  of variation  for  each site
showed increases  at  21  sites,  6 unchanged, and decreases at  22 sites.  Con-
sidering all  sites,  the average coefficient of variation is  essentially un-
changed  (0.61 vs 0.63) as  is its variability (0.47 vs 0.49).

Based  on the  results of  the analyses  which have  been  performed,  the NURP
findings are as follows:

        Lognormal distributions adequately represent  both the storm-to-
        storm variations in pollutant EMC's  at  an urban  site, and site-
        to-site  variations  in  the  median EMC's  which  characterize
        individual sites.
                                     6-7

-------
        -1
        -2
CTi
I
CXI
-3
          0.01
        0.05 0.1  0.2  0.5   1
10
20   30   40  50   60   70
80
90
95
98  99
99.8 99.9
99.99
                                         Figure 6-3.   Cumulative Probability Distribution
                                                    of  Total Cu  at NH1 Pkg.  Site

-------
     -  More detailed analysis to compensate  for  sampling errors (e.g.,
        outliers and  detection  limit  problems)  would  result   in  some
        adjustments in the statistical parameters  tabulated  later on in
        this  chapter.   The  data  summaries   presented  are  based  on
        statistics   computed  directly  from the  log  transforms  of  the
        data.

     -  Such  adjustments  would   not  have  any  significant  effect  on
        overall  results   nor  on  the  general   conclusions   reached.
        However, at a small percentage  of sites,  the parameter estimates
        for some pollutants would change significantly.

        In general,  estimates of  the  site median EMC  would be  least
        affected; estimates of variability more  so.  It  is  likely  that
        the very high or very low  values  for coefficient of  variation
        (storm-to-storm variability) would be adjusted  to more  central
        values.

STANDARD POLLUTANTS

This grouping includes the following pollutants:

                    TSS - Total Suspended Solids
                    BOD - Biochemical Oxygen Demand
                    COD - Chemical Oxygen Demand
                    TP  - Total Phosphorus (as P)
                    SP  - Soluble Phosphorus  (as P)
                    TKN - Total Kjeldahl Nitrogen  (as N)
                NO    -N - Nitrite + Nitrate (as N)

                    Cu  - Total Copper
                    Pb  - Total Lead
                    Zn  - Total Zinc

It  includes  pollutants  of general interest  which are  usually  examined  in
other studies  (both point  and  nonpoint  sources)  and includes representatives
of important categories  of pollutants,  namely solids, oxygen  consuming con-
stituents, nutrients,  and heavy metals.

Condensed Data Summary

Tables 6-1  through 6-10  summarize  the  NURP  results  for these pollutants.
Monitoring sites are grouped in each of the tables according to dominant land
use.  Broad categories  have  been used;  residential,  commercial, industrial,
urban open/nonurban  (other),  and mixed,  this  latter category being  used for
sites which had no predominant land use.   It  should be noted that the indus-
trial category does not  include heavy industry sites,  but more  typically re-
flects an industrial park  type of use.   As a  result,  most of these sites are
more closely related to a commercial use than to the  typical image  called up
by the term industrial  site.   For subsequent comparisons, the data  shown in
Tables 6-1 through  6-10 for the commercial and industrial sites,  are combined
and designated as commercial land use.
                                     6-9

-------
                                            TABLE 6-1.   SITE MEAN TSS EMCs  (mg/£)
en
i
Residential

SUe
1
2
3
4
5
6
7
8
9
10
11
1?
13
14
15
16
17
ie
19
20
21
22
n
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
C01 Big Dry Cr
C01 Cherry
C01 116/Claude
DC1 Dufief
OCI Lakeridge
DC) Stratton
111 John N
KS1 Overton
HA? Hemlock
KOI Bui ton Hill
HOI Homeland
HOI Ht Wash
HD1 Res Hill
NYl Card's R.
KYI Unqua
HY3 Cranston
NY3 I. Roch.
Ill Rolltngmod
UA1 Surrey
Ull Rurbank
Ul) Hastings
FL1 Young Apts
TX1 Hart
TNI R?
DC1 Uestleigh
KS1 1C - 92nd
III John S.
TNI Rl
UA1 Lake Hills
1L1 Hattis S.
FL1 Charter Hdg
DC1 Fairldge
C01 Asbury
112 Comb Inlets
HA1 Locust
IICI 11023
HA] Jordan
(Id StedHick

Land
Use
I
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
too
100
100
100
99
97
96
93
92
91
91
91
90
89
88
86
85
as
84
79
7B

Area
(A)
33
57
167
12
68
8
54
58
50
14
23
17
10
73
-
166
346
60
95
63
33
9
378
36
89
41
63
39
69
102
28
42
19
127
524
154
324
110
27

Pop.
Den
(•/A)
19
24
14
.
21
-
18
8
5
30
9
12
55
13
-
5
18
3
9
15
17
-
9
IB
4
3
IB
11
12
22
_
.
9
8
11
6
10
15

I
IMP.
41
38
24
.
27
-
19
38
16
51
29
29
76
20
-
22
38
21
29
50
51
6
40
57
13
21
37
18
33
37
37
16
34
22
17
16
27
21
34

No.
of
08S
16
14
16
a
49
33
51
IS
S
18
13
20
13
23
6
10
7
9
113
45
33
12
15
23
11
41
13
49
11
126
59
12
47
9
27
6
66
9
47
TSS
Mean
383
180
365
56
175
54
205
2216
78
74
50
95
127
42
65
134
294
227
113
266
170
53
156
251
63
75
156
248
611
127
311
33
25
493
250
257
291
78
54
COV
1.04
.98
1.17
1.02
1.47
1.01
1.36
1.47
2.49
1.32
1.65
1.12
1.05
.85
.53
1.15
1.12
1.13
.51
.44
.68
1.23
1.61
.69
1.13
1.45
.84
1.50
.73
.80
1.08
1.76
1.55
.82
.75
1.75
1.92
1.74
1.02
Median
265
129
232
39
98
38
122
1247
29
45
26
63
88
32
57
88
196
150
101
243
141
34
82
206
42
43
119
138
492
100
211
16
14
380
200
128
135
39
38
901 Confidence
Limits
1B2-385
87-190
154-349
51-74
76-127
30-49
96-155
766-2032
8-111
30-68
15-46
44-89
57-135
25-42
41-80
52-150
101-380
85-263
94-108
219-270
117-169
21-56
49-137
165-258
25-68
33-57
83-171
106-178
345-704
90-110
174-256
9-30
10-18
244-593
161-249
48-339
104-17*
19-81
31-47























Mixed

Site
1
2
3
4
5
6
7
8
9
10
11
12
13
14
IS
16
17
18
19
20
KS1 Noland
M01 Hampden
IL1 Hattis N
Mil Uaverly
TNI SC
Wll Wood Ctr
MAI Rt 9
MAI Convent
Mil Grand R Ot
MI3 Pitt AA-S
NY2 Cedar
MAI Anna
M13 Pitt AA-N
Mil Grace N
Ml 3 Sol ft Run
SOI Meade
CA1 Knox
FL1 N. Jesuit
FL1 Milder
COI North Ave

Land
Use
I
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-

-
-

Area
(A)
36
17
17
30
187
45
338
100
453
2001
76
601
2871
164
1207
2030
1542
30
194
69.

Pop.
Den
(I/A)
3
40
3
11
3
12
7
1
5
2
-
9
7
5
2
-
12
-
-
9

I
IMP.
6B
72
58
68
43
81
23
33
38
21
5
12
26
28
4
-
-
13
97
50

No.
of
DBS
16
20
58
35
13
47
7
a
23
6
27
6
6
23
5
15
19
15
14
32
TSS
Mean
280
82
2B2
85
71
3B3
351
54
158
46
291
150
68
172
80
3093
283
87
33
492
COV
.91
1.62
1.01
1.28
1.07
.78
2.05
1.53
1.26
.37
1.92
2.95
.47
.85
.91
1.39
1.32
3.59
.71
.96
Median
208
43
199
52
48
302
154
30
98
43
134
48
61
131
59
1B04
171
23
27
354
901 Confidence
Units
148-292
28-67
165-239
39-69
31-74
255-357
60-395
14-63
69-139
32-58
89-202
14-166
42-flfl
101-171
28-124
1128-2897
115-265
11-48
20-37
278-451















Commercial

Site
1
2
3
4
5
6
7
8
9
10
C01 Villa Italia
NCI 1013 (CBD)
NV3 Southgate
Ull Post Office
NH1 Pkg Lot
TNI CBD
Ull Rustler
KS1 1C Metcalf
FL1 Nonna Pk
Ull State Fair
Land
Use
I
Coml
100
100
100
100
100
100
100
96
91
74

Area
(A)
74
23
179
12
1
26
12
SB
47
29

Pop.
Den
(I/A)
0
0
2
0
0
0
0
-
-
10

1
IHP.
91
69
21
100
90
99
100
97
45
77

No.
of
DBS
27
60
12
58
32
15
42
22
12
29
TSS
Mean
260
163
141
212
74
123
202
80
22
412
COV
1.89
1.16
.76
.86
1.66
.73
.68
2.12
1.13
.97
Median
12?
107
112
161
38
99
167
34
14
296
90t Confidence
Limits
81-163
88-131
79-159
131-197
27-54
74-133
142-196
21-65
9-2?
229-382

Urban Open and Nonurban
Site
1
2
3
4
5
6
7
8
CA1 Seaview
COI Rooney Gulch
NY3 Thornell
NV2 English Br
NV2 Uest Br
HV3 Thomas Cr
MI3 Travel- Cr
NY2 Sheriff Dock
Land
Use
t
Open
100
100
100
98
97
91
90
80
Area
(A)
633
405
28.416
5.248
5.338
17,728
2.303
552
Pop.
Den
(I/A)
-
0
-
-
-
1
-
-
I
IMP.
-
1
4
1
1
11
6
7
No.
Of
DBS
13
7
11
28
28
9
5
32
TSS
Mean
718
403
154
17
64
63
33
378
COV
.83
.63
.92
2.46
2.77
.74
.77
2.33
Median
551
341
113
6
22
51
26
149
901 Confidence
Limits
385-788
223-521
74-173
4-10
14-35
34-77 '
14-50^riU
99-^^|
Industrial


1
2
3
4

Site
MA? Addlson
Mil Indus Drain
KS1 Lenaxa
Mil Grace S.

Land
Use
t
100
100
56
52

Area
(A)
IB
63
72
75

Pop.
Den
(I/A)
0
0
-
5

t
IMP.
69
64
44
39

No.
of
085
5
IB
18
20
TSS
Mean
48
92
102
188
COV
.81
.82
1.33
.94
Median
37
71
61
137
901 Confidence
Limits
19-73
53-95
40-92
101-186

-------
TABLE 6-2.  SITE MEAN BOD EMCs (mg/H)
Residential
Site
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
16
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
C01 Big Dry Cr
COI Cherry
C01 lie/Claude
DC1 Dufief
OC1 Lakerldge
DC1 SI rat ton
111 John N
KS1 Overtoil
HA2 Hemlock
HOI Bolton Hill
HDI Homeland
HOI Ht Wash
M01 lies Hill
NV1 Carll's R.
NV1 Unqua
NV3 Cranston
NY3 E. Roch.
1X1 Rollingwood
UA1 Surrey
Ull Burbank
Ull Hastings
FL1 Koung Apts
T»l Hart
Ull Lincoln
TNI 02
DC1 Uestleigh
KS1 1C - 92nd
111 John S.
TNI Rl
WAI Lake Hills
IL1 Mattis S.
FL1 Charter Hdg
DC1 Falrldge
COI Asbury
IL2 Comb Inlets
HA1 Locust
NCI 11023
MAI Jordan
DC1 Stedwick
Land
Use
I
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
99
97
96
93
92
91
91
91
90
B9
88
86
85
85
84
79
78
Area
(A)
33
57
167
12
68
8
54
58
50
14
23
17
10
73
-
166
346
60
95
63
33
9
378
36
89
41
63
39
69
102
28
42
19
127
524
154
324
110
27
Pop.
Den
C/A)
19
24
14
-
21
-
18
8
5
30
9
12
55
13
-
5
18
3
9
15
17
-
9
18
4
3

18
11
12
22
-
.
9
8
11
6
10
15
I
IHP.
41
38
24
.
33
.
19
38
16
51
29
29
76
20
.
22
38
21
29
50
51
6
40
57
13
21
37
18
33
37
37
16
34
22
17
16
27
21
34
No.
of
DBS
0
0
0
0
0
4
0
5
0
0
0
0
0
0
0
0
0
0
0
28
20
12
0
11
10
3
5
0
9
0
0
12
5
0
0
0
7
0
3
BOD
Mean
-
.
.
.
.
.
_
12

_
_
.
.
.

_
.
_
.
;
9
16
.
18
9
-
28
-
14


13
5
.
.
-
11
.
-
cov
-
.
_
_
_
.
.
.59
_
.

.
_
.

.
_

.
.64
.62
1.10
.
1.23
.66
.
.66
.
.87
.

1.24
.64
-
-

.63
-
-
Median
-
.
-
.
.
.
_
11
.
.
-
_

_
.

-
_

6
8
11
-
12
7
.
23
-
11

-
8
4
-
-
.
10
-
-
90S Confidence
Limits
-
_
-
.
-
.
_
6-18
.
_
.
_
.
_
. '
.
-
.
.
5-7
6-10
7-17

7-20
5-10
-
13-41
'
7-18
-
-
5-13
2-7

-'
-
6-15
- .

Urban Open and Nonurban
Site
1
2
3
4
5
6
7
8
CA1 Seavlew
COI Rooney Gulch
NV3 Thome! 1
NV2 English Br
NV2 Uest Br
NY3 Thomas Cr
M13 Traver Cr
NY2 Sheriff Dock
Land
Use
I
Open
100
100
100
98
97
91
90
80
Area
(A)
633
405
28,416
5,248
5,338
17.728
2,303
552
Pop.
Den
(*/A)

0
-


1

-
I
IHP.

1
4
1
1
11
6
7
No.
of
DBS
0
0
0
0
0
0
5
0
BOD
Mean

-
-
-
-
-
2
-
COV
-


-
.
-
.41

Median
-
-
-
-
-
-
2
-
90% Confidence
Limits
-
-
-

-
-

-
Hlxed
Site
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
KS1 Noland
HDI Hampden
IL1 Mattis «
Mil yaverly
TNI SC
Ul 1 Uood Ctr
MA! Rt 9
HA1 Convent
Mil Grand It Ot
MI3 Pitt AA-S
NV2 Cedar
MAI Anna
H13 Pitt AA-N
Mil Grace N
MI3 Suift Run
SD1 Heade
CA1 Knox
FL1 N. Jesuit
FL1 Uilder
COI North Ave
Land
Use
t
-
-
-
-
-
-
-
-
.
-
-
-
-
-
-
-
-
-
-
-
Area
(A)
36
17
17
30
187
45
338
100
453
2001
76
601
2871
164
1207
2030
1542
30
194
69
Pop.
Den
(*/A)
3
40
3
11
3
12
7
1
5
2
-
9
7
5
2
-
12
-
-
9
I
IMP.
68
72
58
68
43
81
23
33
38
21
5
12
26
28
4
-
-
13
97
50
No.
of
CBS
3
0
0
21
12
31
0
0
13
6
0
0
6
11
5
14
0
15
15
32
BOD
Mean

-
-
9
14
14
-
-
8
5
-
.
6
8
3
19
-
16
16
-
COV

-
-
.64
.87
.54
-
-
.62
.49
-
.
.76
.78
.41
.75
-
.95
1.18
-
Median
-
-
-
7
11
13
-
-
7
5

-
5
7
3
15

12
10

90: Confidence
Limits
-
-
-
6-9
7-16
11-15
-
-
5-9
3-7
-
-
3-9
5-10
2-4
!!-?!
-
8-17
7-15
-
Coimercial
Site
1
2
3
4
5
6
7
8
9
10
COI Villa Italia
NCI 1013 (CBD)
NV3 Southgate
Ull Post Office
NH1 Pig Lot
TNI CBD
Ull Rustler
KS1 1C Hetcalf
FL1 No ma Pk
Ull State Fair
Land
use
Corn!
100
100
100
100
100
100
100
96
91
74
Area
(A)
74
23
179
12
1
26
12
58
47
29
Pop.
Den
(»/A)
0
0
2
0
0
0
0
-

10
I
IMP.
91
69
21
100
90
99
-
97
45
77
No.
of
DBS
0
23
0
35
33
13
27
13
12
15
BOD
Mean
_
18
-
9
17
13
13
8
12
19
COV
_
.86
-
.50
.86
.46
.79
.48
.88
.72
Median

13
-
8
13
12
10
7
9
IS
901 Confidence
Limits

10-17
-
7-9
10-16
10-15
8-13
6-9
6-13
11-20
Industrial

Site
1
2
3
4
MA2 Add! son
HI1 Indus Drain
KS1 Lenaxa
Mil Grace S.

Land
Use
I
100
100
56
52

Area
(A)
18
63
72
75

Pop.
Den
(I/A)
0
0
-
5

I
IMP.
69
64
44
39

No.
of
DBS
0
8
8
9
80D
Mean
-
10
14
5
COV
-
.58
.77
.34
Median
-
9
11
5
901 Confidence
Limits
-
6-13
7-17
4-6

-------
                                             TABLE 6-3.   SITE MEAN COD EMCs  (mg/£)
CT>
I
M
NJ
Residential
Stte
1
2
3
4
5
6
7
8
9
10
11
12
13
14
IS
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
C01 Rig Dry Cr
C01 Cherry
C01 116/Claude
DCI nufief
DC1 Lakeridge
DCI Stratton
IL1 John II
KS1 Overlon
NA2 Hemlock
MD1 Bolton Hill
HOI Hone land
HOI Ht Wash
HOI lies Hill
NY1 Carll's R.
Nil Unqua
NY 3 Cranston
11(3 E. Koch.
TXI Rollinguood
WAI Surrey
Ull Bur hank
Wll Hastings
FL1 Voung Apts
TX1 Hart
Ul 1 Lincoln
TNI R2
DCI Uestlelgh
KSI 1C - 92nd
111 John S.
TNI Rl
WAI lake Hills
111 Hauls S.
ai Charter Hdg
DCI Fairldge
C01 Asbury
IL2 Comb Inlets
HA1 Locust
NCI 11023
MAI Jordan
DCI Stedulck
Land
Use
I
100
100
100
100
100
ino
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
99
97
96
93
92
91
91
91
90
89
88
86
65
es
84
79
78
Area
(A)
33
57
167
12
68
8
54
58
50
14
23
17
10
73
-
166
346
60
95
63
33
9
378
36
89
41
63
39
69
102
28
42
19
127
524
154
324
110
27
Pop.
Den
(I/A)
19
24
14

21
_
18
8
5
30
9
12
55
13
.
S
18
3
9
IS
17

9
18
4
3
18
11
12
22
-
.
9
8
11
6
10
15
I
IMP.
41
38
24
-
33
.
19
38
16
51
29
29
76
20
.
22
38
21
29
SO
51
6
40
57
13
21
37
18
33
37
37
16
34
22
17
16
27
21
34
No.
of
OSS
16
14
IS
7
44
31
31
14
0
19
13
20
13
0
0
8
7
9
118
27
23
12
11
16
11
39
11
29
11
127
30
12
48
9
24
6
34
9
45
COD
Hean
129
122
137
64
60
51
126
162
.
218
172
168
177
.
.
33
86
70
48
39
41
73
82
91
45
51
176
111
120
44
180
55
51
234
138
104
90
79
45
COV
.72
.66
.74
.26
.66
.55
.80
.67
.
1.38
.73
.85
.85
_
.
.43
.31
.45
.54
.79
.55
.96
.83
.95
.39
.46
.98
.80
.96
.54
.72
.64
.46
1.12
.90
.45
.97
.53
.60
Median
105
102
103
62
50
45
98
135
_
128
139
128
135
_
_
31
82
64
42
30
36
52
63
66
42
46
126
87
87
38
146
47
47
156
102
95
64
70
39
90S Confidence
Units
79-139
77-136
76-139
51-74
43-58
39-53
79-122
101-180

85-193
101-192
96-170
94-194
.
.
24-41
66-102
49-84
39-46
24-38
30-44
34-79
42-94
46-94
34-52
41-52
80-197
69-108
56-135
36-41
119-178
35-64
42-52
89-273
78-134
67-135
51-82
51-95
34-45





















Mixed
Site
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
KSI Noland
KD1 Hampden
111 Hants N
Nil Uaverly
TNI SC
Ull Wood Ctr
MAI Rt 9
MAI Convent
Mil Grand R Ot
HI3 Pitt AA-S
NV2 Cedar
MAI Anna
M13 Pitt AA-N
HI 1 Grace N
MI3 SHlft Run
SOI "cade '
CA1 Kno>
FL1 N. Jesuit
FL1 Under
C01 North Ave
Land
Use
t
-

-
-
-
-

-
-
-
-
.
.
-
.
-
-
.
-
-
Area
(A)
36
17
17
30
187
45
338
100
453
2001
76
601
2871
164
1207
2030
1542
30
194
69
Pop.
Den
«/«)
3
40
3
11
3
12
7
1
5
2
-
9
7
5
2
-
12
-
-
9
1
IHP.
68
72
58
68
43
81
23
33
38
21
5
12
26
28
4

-
13
97
50
No.
of
OBS
12
20
35
27
13
39
6
8
18
4
0
6
3
17
5
14
21
15
15
32
COD
Hean
106
111
198
64
60
92
107
72
71
-
•
88
-
72
29
179
93
50
SI
280
COV
.66
.73
.68
.80
.70
.57
.68
.62
.47
-
-
.51
-
.43
.1?
.39
.60
1.18
.38
.74
Median
89
89
164
50
49
80
88
61
65
-
-
78
-
66
29
167
80
33
48
225
901 Confidence
Knits
65-122
69-115
138-196
40-63
36-67
69-92
53-146
42-89
54-78
-
-
53-116
-
55-79
26-33
140-200
65-99
22-50
41-57
185-275

















Conine rclal

Site

1
2
3
4
5
6
7
8
9
10

C01 Villa Italia
NCI 1013 (CBD)
NV3 Southgate
Wll Post Office '
NH1 Pkg lot
TNI CBD
Ull Rustler
KSI 1C Hetcalf
FL1 Nonna Pk
Ull State Fair

Ute
Coml

100
100
100
100
100
100
100
96
91
74

Area
(A)

74
23
179
12
1
26
12
58
47
29

Pop.
Den
(I/A)

0
0
2
0
0
0
0
-
-
10

I
IHP.

91
69
21
100
90
99
-
97
45
77

No.
of
OBS

27
40
9
40
33
IS
26
20
12
21
COO
Hean

184
120
40
57
98
73
59
55
41
113
COV

.87
.79
.34
.62
.72
.52
.76
.86
.47
.88
Hedian

139
94
38
48
79
65
47
41
37
84
901 Confidence
Limits

109-178
78-113
31-47
41-56
65-95
52-81
37-59
31-55
29-47
64-112
Urban Open and Nonurban
Site
1
2
3
4
S
6
7
8
CA1 SeavlCH
C01 Rooney Gulch
NY3 Thornell
N»2 English Br
NV2 Uest Br
NV3 Thomas Cr
MI3 Traver Cr
N»2 Sheriff Dock
Land
Use
I
Open
100
100
100
98
97
91
90
80
Area
(A)
633
405
28,416
5,248
5,338
17,728
2,303
552
Pop.
Den
(I/A)
.
0

-
-
1
-
-
t
IHP.
.
1
4
1
1
11
6
7
No.
of
OBS
14
7
8
0
0
6
5
0
COD
Hean
111
73
25
-
-
26
25
-
COV
.42
.33
.36

-
.26
.19

Median
102
69
23
-

26
25

90t Confidence
Limits
84-123
54-87
18-29
-
-
21-32
21-30 	
JM


Site

1
2
3
4
HA2 Addison
Hll Indus Drain
KSI Lenaxa
Hll Grace S.

Land
Use
J
Ind
100
100
56
52

Area
(A)

18
63
72
75
ndustrlal

Pop.
Den
(»/A)

0
0
-
5

%
IHP.

69
64
44
39

of
OBS

0
12
16
11
COD
Hean

-
67
58
60
COV

-
.46
.60
.79
Hedian

.
61
50
47
901 Confidence
Limits

-
49-77
39-64
32-69

-------
                                           TABLE 6-4.  SITE MEAN TOTAL P EMCs
cr*

M
CO
Residentla
Site
1
2
3
4
5
e
7
e
9
10
u
12
13
14
IS
16
17
ie
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
C01 Big Dry Cr
COI Cherry
C01 116/Claude
OC1 Dufief
DC1 Lakeridge
DC1 Stratton
111 John N
KSI Overton
KA2 Hemlock
M01 Bolton Hill
KOI Homeland
MD1 Mt Wash
M01 Res Hill
HY1 Card's R.
XVI Unqua
NY3 Cranston
NY3 E. Roch.
TX1 Rollinguood
UA1 Surrey
Ull Burbank
Ull Hastings
Fll Young, Apts
TX1 Hart
Ull Lincoln
TNI R2
OC1 Uestlelgti
KSI 1C - 92nd
ILI John S.
TNI RI
WAI Lake Hills
ILI Mattis S.
FLI Charter Hdg
DC1 Fairldge
COI Asbury
IL2 Comb Inlets
MAI Locust
NCI 11023
MAI Jordan
DC1 Stedalck
Land
Use
»
Res
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
too
100
100
99
97
96
93
92
91
9)
91
90
89
88
86
85
85
84
79
78
Area
(A)
33
57
167
12
68
8
54
58
50
14
23
17
10
73

166
346
60
95
63
33
9
378
36
89
41
63
39
69
102
28
42
19
127
524
154
324
110
27
Pop.
Den
(I/A)
19
24
14
-
21
-
18
8
5
30
9
12
55
13

5
18
3
9
15
17
-
9
18
4
3
-
18
11
12
22
-
-
9
a
n
6
10
15
!
IMP.
41
38
24
-
33
.
19
38
16
51
29
29
76
20
-
?2
38
21
29
50
51
6
40
57
13
21
37
18
33
37
37
16
34
22
17
16
27
21
34
No.
of
OBS
16
14
15
5
48
28
33
8
5
19
13
20
13
24
8
13
8
9
118
45
35
12
14
23
11
41
10
32
11
127
32
12
47
9
26
6
67
8
44
Total P
Mean
693
429
630
499
323
340
750
1636
314
932
421
556
4090
221
229
301
448
268
239
229
258
333
333
453
246
397
1297
732
705
264
587
395
351
1025
506
1228
529
448
388
COV
.94
.54
.65
.32
.78
.54
.62
.91
1.05
1.15
.70
.83
1.05
.54
.61
.54
.47
.56
.83
.45
.51
.65
.80
.69
.41
.75
1.31
.65
.35
.81
.69
1.61
.73
.71
.79
.79
.99
.95
.65
Median
505
377
513
475
256
300
636
1207
216
613
345
428
2825
195
196
265
405
233
184
209
230
279
260
373
227
319
787
604
665
204
483
208
254
834
397
966
375
324
326
90S Confi-
dence Limits
356-716
297-479
392-672
353-640
217-302
255-353
538-753
717-2031
95-491
425-883
253-471
324-566
1845-4326
163-233
134-285
206-340
300-546
169-3?2
164-205
188-233
201-264
205-380
179-349
298-466
183-282
268-380
441-1405
502-727
552-801
184-227
401-582
116-374
242-334
561-1239
314-501
545-1713
317-444
190-555
281-379
Urban Open and Nonurban
Site
1
2
3
4
5
6
7
8
CA1 Seavie»
COI Rooney Gulch
NV3 Thome II
NY2 English Br
NV2 West Br
NY3 Thomas Cr
HI3 Traver Cr
NV2 Sheriff Dock
Land
Use
I
Open
100
100
100
98
97
91
90
80
Area
(A)
633
405
28,416
5,248
5,338
17,728
2,303
552
Pop.
Den
(I/A)
-
0
-
-
-
1
-

%
IMP.
-
1
4
1
1
11
6
7
No.
of
OBS
13
7
13
30
31
12
S
33
Total P
Mean
590
420
193
27
52
195
91
264
COV
.82
.47
.46
1.20
1.27
.47
.38
1.01
Median
455
380
175
17
32
177
85
186
90t Confi-
dence Limits
319-649
274-528
141-217 .
13-23
24-43
140-223
60-121
145-238
Mined

Site
,
2
3
4
5
6
7
8
9
10
11
12
13
14
IS
16
17
IB
19
20
KSI lloland
HOI Hampden
III Mattis N
Mil Waverly
TNI SC
Ull Hood Ctr
MAI lit 9
MAI Convent
Mil Grand R Ot
MI3 Pitt AA-S
NV2 Cedar
MAI Anna
MI3 Pitt AA-N
Mil Grace N
M13 Sulft Run
SOI Meade
CA1 Knox
FL1 N. Jesuit
fll Ullder
C01 North Ave

Land
Use
I
_
-
-
-
-
.
. -
-

-
-
-
-
-
-
-
-
_

-

Area
(A)
36
17
17
30
187
45
338
100
453
2001
76
601
2871
164
1207
2030
1542
30
194
69

Pop.
Den
<*/A)
3
40
3
11
3
12
7
1
5
2
-
9
7
5
2
-
12
-
-
9

I
IMP.
68
72
58
68
43
81
23
33
38
21
5
12
26
28
4
-
-
13
97
50

No.
of
OBS
7
20
35
35
13
47
5
a
22
6
32
6
6
23
5
15
19
15
15
32
Total P
Mean
555
754
498
198
352
289
1176
459
458
103
363
534
268
394
134
1885
418
196
229
784
COV
.34
1.41
.58
.64
.64
.59
.63
1.99
.65
.50
1.20
.88
.47
.54
.56
1.28
.50
.71
.52
.60
Median
526
436
431
167
296
249
995
206
384
93
233
402
243
347
117
1163
374
160
204
673
90? Confi-
dence Limits
413-671
291-653
370-503
141-197
221-394
218-284
573-1726
88-481
309-477
63-137
176-309
216-749
168-351
285-410
71-193
743-1820
310-451
120-214
163-255
570-795
Commercial
Site
1
2
3
4
5
6
7
8
9
10
COI Villa Italia
NCI 1013 (C80)
NV3 Southgate
Ull Post Office
NH1 Pkg Lot
TNI CBO
Ull Rustler
KSI 1C Metcalf
FLI Itorma Pk
Ull State Fair
Land
Use
I
Coml
ICO
100
100
100
100
100
100
96
91
74
Area
(A)
74
23
179
12
1
26
12
58
47
29
Pop.
Den
(*/A)
0
0
2
0
0
0
0

-
10
t
IMP.
91
69
21
100
90
99
-
97
45
77
No.
of
OBS
27
61
12
60
27
15
44
20
12
29
Total P
Mean
704
395
216
108
273
212
105
246
151
511
COV
1.26
.58
.26
.56
1.21
.43
.79
.98
.50
1.19
Median
438
342
209
94
174
195
82
176
135
330
90i Confi-
dence Limits
318-603
304-383
183-239
84-105
127-238
162-235
69-98
128-242
106-172
245-443
Industrial
Site
1
2
3
4
MA2 Addlson
Mil Indus Drain
KSI Lenaxa
Mil Grace S.
Land
Use
I
Ind
109
100
56 .
52
Area
(A)
18
63
72
75
Pop.
Den
(I/A)
0
0
-
5
t
IMP.
69
64
44
39
No.
of
OBS
5
18
16
17
Total P
Mean
114
546
599
435
COV
.89
.58
.87
.71
Median
85
472
452
355
90% Confi-
dence Limits
41-176
378-589
325-628
271-465

-------
                                        TABLE  6-5.   SITE MEAN SOLUBLE P EMCs
en
i
Residential
Site
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
IB
19
?0
21
22
23
?4
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
C01 Big Dry Cr
C01 Cherry
C01 116/Claude
DC1 Dufief
OC1 Lakeridge
DC) St rat ton
111 John N
KS1 Overton
HA2 Hemlock
BD1 Bolton Hill
Mil Homeland
HD1 Ht Wash
HOI Res Hill
N»l Carll's R.
ml unqua
NY3 Cranston
NY3 E. Roch.
TX1 Rollingwood
WAI Surrey
ull Burbant
U!l Hastings
FL1 Young Apts
TX1 Hart
Ull Lincoln
TNI R2
DC1 Westleigh
KS1 1C - 92nd
IL1 John S.
INI RI
WAI Lake Hills
IL1 Hauls S.
Fll Charter Hdg
OC1 Fairidge
C01 Asbury
11.2 Comb Inlets
HA1 Locust
NCI (1023
MAI Jordan
DC1 Stedwick
Land
Use
1
Res
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
99
97
96
93
92
91
91
91
90
89
88
86
85
85
84
79
78
Area
(A)
33
57
167
12
68
8
54
58
50
14
23
17
10
73
-
166
346
60
95
63
33
9
378
36
89
41
63
39
69
102
28
42
19
127
524
154
324
110
27
Pop.
Den
(I/A)
19
24
14
-
21
-
18
a
5
30
9
12
55
13
-
5
18
3
9
15
17
-
9
18
4
3

18
11
12
22

-
9
8
11
6
10
IS
t
IMP.
41
38
24
-
33
-
19
38
16
51
29
29
76
20
-
22
38
21
29
50
51
6
40
57
13
21
37
18
33
37
37
16
34
22
17
16
27
21
34
No.
of
OBS
15
14
16
6
47
27
0
8
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
11
41
10
0
11
0
0
0
46
9
24
6
0
7
41
SOL P
Mean
193
212
196
44B
69
251

313
160
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
132
223
241
-
136
-
-

297
212
98
184
-
202
251
COV
.64
.47
.35
.55
.62
.65
-
.41
.89
-
-
-
-
-
-
• -
-

-
-
-
-
-
-
.63
.71
.62
-
.94
-
-
-
.87
.22
1.21
.42
-
l.ll
• '0.
Median
163
192
179
392
59
210
-
290
120
-
-
-

-
-

-

-
-

-
-
-
112
182
205
-
99
-
-

224
207
63
169
-
136
206
901 Confi-
dence Limits
125-213
155-237
154-208
257-598
51-68
173-256
-
223-378
58-249
-
-
-
-
-
-.
-
-
-
-
-
-
-
-
-
82-154
154-215
147-285
-
64-153
-
-
-
186-270
181-237
45-68
121-235
-
70-262
174-243
Urban Open and Nonurban
Site
1
2
3
4
S
6
7
8
CA1 Seaview
C01 Rooney Gulch
N»3 Thornell
NV2 English Br
IH2 Uest Br
NV3 Thomas Cr
MI3 Traver Cr
NV2 Sheriff Dock
Land
Use
S
Open
100
100
100
98
97
91
90
80
Area
(A)
633
405
28,416
5,248
5,338
17,728
2.303
552
Pop.
Den
(I/A)
.
0
-
-
-
1

-
I
IMP.
-
1
4
1
1
11
6
7
No.
of
OBS
12
7
0
18
26
0
S
32
SOL P
Mean
145
137

5
8
-
33
39
COV
1.24
.46

.35
.54
-
.55
1.11
Median
91
124
-
5
7
-
29
26
901 Confi-
dence Limi ts
55-150
90-171
-
4-6
6-8
- I
18-47^H
20-34^^1
Mixed
Site
1
2
3
4
5
6
7
a
9
10
11
12
13
14
15
16
17
18
19
20
KS1 Noland
MD1 Hampden
IL1 Mattis N
Nil tlaverly
TNI SC
Ull Uuod Ctr
MAI Rt 9
HA1 Convent
Mil Grand R Ot
MI3 Pitt AA-S
NY2 Cedar
MAI Anna
M13 Pitt AA-N
Mil Grace N
MI3 Swift Run
SD1 Meade
CA1 (Cno«
FLI N. Jesuit
FL1 Wilder
C01 North Ave
Land
Use
I
.
-
-
-
-
.
-
-
-


-
-
-
-
-
-
-
-
-
Area
(A)
36
17
17
30
187
45
338
100
453
2001
76
601
2871
164
1207
2030
1542
30
194
69
Pop.
Den
(I/A)
3
40
3
11
3
12
7
1
5
2
-
9
7
5
2
-
12


9
t
IMP.
68
72
58
68
43
81
23
33
38
21
5
12
26
28
4
-
-
13
97
50
No.
of
OBS
8
0
0
32
13
0
5
6
20
6
26
4
6
21
5
14
18
0
0
30
SOL P
Mean
165
-
-
43
197
-
160
106
66
13
49
-
59
47
39
87
169
-
-
226
COV
.52
.
-
.76
1.17
.
.38
1.63
.68
.37
1.16
-
.68
.47
.46
.61
.99

-
.95
Median
146
-
-
34
128
.
150
51
56
13
32
-
44
42
35
74
120
-
-
165
90S Confi-
dence Limits
105-203
-
.
2B-42
81-203
.
106-213
19-138
44-71
10-17
23-44

24-82
35-50
23-53
57-97
85-168
-
-
129-212'
Commercial

Site

1
2
3
4
5
6
7
8
9
10
C01 Villa Italia
NCI 1013 (CBO)
NV3 Southgate
Ull Post Office
NH1 Pkg Lot
TNI CBD
Ull Rustler
KS1 1C Metcalf
FLI Norma Pk
Ull State Fair

Land
Use
I
Coml
100
100
100
100
100
100
100
96
91
74

Area
(A)

74
23
179
12
1
26
12
58
47
29

Pop.
Den

0
0
2
0
0
0
0

-
10

I
IMP.

91
69
21
too
90
99
-
97
45
77

No.
of
OBS

26
0
0
0
0
15
0
21
0
0
SOL P
Mean

293
-

-

46
-
116
-

COV

1.09
-
-
-

.72
-
1.06
-

Median

198
-
-
-

37
-
80
-
-
90J Confi-
dence Limits

147-266

-

-
28-50
-
58-111
-
-
Industrial
Site
1
2
3
4
MA2 Addlson
Mil Indus Drain
KS1 Lenaxa
Mil Grace S.
Land
Use
»
Ind
100
100
56
52
Area
(A)
16
63
72
75
Pop.
Den
(I/A)
0
0
-
5
*
IMP.
69
64
44
39
No.
of
OBS
5
14
16
16
SOL P
Mean
75
127
,346
59
COV
.92
.72
1.66
1.24
Median
55
103
179
37
90t Confi-
dence Limits
26-116
76-140
108-296- '
24-S6

-------
TABLE 6-6.  SITE MEAN TKN EMCs
Residential
Site
1
i
3
4
5
6
7
8
9
10
11
1?
13
14
15
16
17
18
19
20
21
22
23
24
?5
26
27
28
29
30
31
32
33
34
35
36
37
38
39
C01 Big Dry Cr
C01 Cherry
C01 116/Claude
DC1 Ouflef
DC1 Lakeridge
DC1 Stratton
111 John N
KS1 Over-ton
HA2 Hemlock
HOI Bolton Hill
HOI Homeland
HOI HI Mash
HOI Res Hill
NY1 Card's R.
NY1 Unqua
NV3 Cranston
NV3 E. Koch.
TX1 Rollingwood
UA1 Surrey
Ull Burban*
Wit Hastings
FL1 Young Apts
T>1 Hart
Ull Lincoln
TNI 112
DCI Uestlelgh
KS1 1C - 92nd
111 John S.
TNI Rl
HA1 Lake Hills
IL1 Hauls S.
FL1 Charter Hdg
DCI Fairldge
C01 Asbury .
IL2 Comb Inlets
MAI Locust
NCI 11023
MAI Jordan
DCI Steduick
Land
Use
I
Res
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
99
97
96
93
92
91
91
91
90
89
ea
86
85
85
84
79
78
Area
(A)
33
57
167
12
68
8
54
58
50
14
23
17
10
73
-
166
346
60
95
63
33
9
378
36
89
41
63
39
69
102
28
42
19
1?7
524
154
324
110
27
Pop.
Oen
(•/A)
19
24
14
-
21
-
18
8
5
30
9
12
55
13
-
5
18
3
9
15
17
-
9
18
4
3
-
IB
11
12
22

-
9
8
11
6
10
15
t
IMP.
41
38
24
-
33
.
19
38
16
51
29
29
76
20
-
22
38
21
29
50
51
6
40
57
13
21
37
18
33
37
37
16
34
22
17
16
27
21
34
NO.
of
OBS
16
14
15
6
48
28
33
S
5
18
13
20
13
24
8
13
7
9
118

15
12
11
1
11
41
8
32
11
127
32
12
46
7
0
6
67
9
43
TKN
Mean
2,369
2.609
2,893
2,066
1,724
1.811
3.994
-
3.679
6.067
6.505
6.935
10,803
1,487
1,408
1,492
3,246
5,004
1,007
1,260
1,102
1,339
3,016
-
476
1,901
4,187
3,527
1,131
1,056
3,440
1,704
2,212
3,735
-
2,695
1,488
1,391
1.895
COV
.58
.39
.51
.13
.64
.39
.81
-
.55
.77
.40
.41
.43
.73
.26
.45
.90
2.37
.62
.50
.54
.70
.75
.
.33
.56
.94
1.04
.34
.73
.69
.83
.53
.56
.
.38
.94
.60
.57
Median
2041
2430
2501
2048
1450
1686
3107
-
3217
4815
6044
6408
9915
1201
1363
1358
2411
1942
857
1125
969
1097
2412
-
452
1660
3051
2441
1071
852
2825
1309
1958
3263
.
2522
1086
1194
1643
90S Confi-
dence Limits
1612-2584
2034-2904
2010-3112
1841-2278
1259-1670
1494-1904
2520-3831
_
1971-5252
3640-6370
4996-7312
5502-7463
8089-12154
955-1509
1148-1618
1098-1679
1369-4245
828-4554
785-935
908-1395
801-1173
791-1522
1674-3474 .
.-
379-539
1447-1904
1790-5200
1888-3155
894-1283
774-938
2343-3406
899-1905
1731-2215
2224-4788
-
1864-3412
923-1277
845-1681
1435-1881
Urban Open and Nonurban
Site
1
2
3
4
5
6
7
8
CA1 Seavion
C01 Rooney Gulch
NV3 Thome) 1
NV2 English Br
NV2 Uest Br
NV3 Thomas Cr
HI3 Traier Cr
NY2 Sheriff Dock
Land
Use
I
Open
100
100
100
98
97
91
90
80
Area
(A)
633
405
28,416
5,248
5,338
17,728
2.303
552
Pop.
Den
(I/A)

0
-
-
-
1
.
-
I
IMP.
-
1
4
1
I
11
6
7
No.
Of
OBS
13
7
13
15
24
10
5
33
TKN
Mem
3674
2954
1099
340
392
1111
889
963
COV
.59
.53
.50
.50
.52
.36
.11
.76
Median
3159
2615
982
305
347
1045
883
765
90t Confi-
dence Limits
2411-4139
1815-3768
778-1240
246-378
292-412
854-1279
796-981
628-932
Mixed
Site
1
2
3
4
S
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
KS1 Noland
ND1 Hampden
IL1 Hattis N
Mil Uaverly
TNI SC
Ull Wood Ctr
HA1 Rt 9
MAI Convent
Mil Grand R Ot
HI3 Pitt AA-S
NY2 Cedar
MAI Anna
MI3 Pitt AA-N
Mil Grace N
MI3 Swift Run
SOI Meade
CA1 Knox
FL1 N. Jesuit
FL1 Wilder
C01 North Ave
Land
Use
I
.
-
-
-
-
-
-
-
-

-
-
-


-
-

-
-
Area
(A)
36
17
17
30
187
45
338
100
453
2001
76
601
2871
164
1207
2030
1542
30
194
69
Pop.
Oen
(I/A)
3
40
3
11
3
12
7
1
5
2
-
9
7
5
2
-
12
-
-
9
S
IMP.
68
72
58
68
43
81
23
33
38
21
5
12
26
28
4
-
-
13
97
50
No.
of
OBS
0
19
35
35
13
16
5
8
23
6
21
6
6
23
5
13
20
15
15
23
TKN
Mean
.
6994
2822
1490
623
1452
2446
1080
1631
845
1237
1888
1056
1988
1116
4243
2220
1388
1107
4196
COV
_
.55
.64
.53
.50
.35
.50
.64
.42
.29
.83
.70
.22
.47
.15
.50
.75
.49
.31
.65
Median
_
6140
2372
1316
558
1369
2188
910
1506
811
951
1547
1031
1802
1104
3802
1775
1249
1056
3522
901 Confi-
dence Limits
_
5004-7533
2006-2805
1142-1516
442-705
1180-1589
1394-3432
615-1347
1304-1740
642-1025
724-1249
920-2601
862-1233
1536-2115
958-1273
3010-4802
1371-2298
1011-1542
920-1212
2847-4356
Commercial
Site
1
2
3
4
5
6
7
a
9
10
C01 Villa Italia
NCI 1013 (CUD)
NY3 Southgate
Ull Post Office
NH1 Pkg Lot
TNI CBD
Ull Rustler
KS1 1C Metcalf
FL1 Nonna Pk
Ull State Fair
Land
Use
I
Com!
100
100
100
100
too
100
100
96
91
74
Area
(A)
74
23
179
12
1
26
12
58
47
29
Pop.
Den
(I/A)
0
0
2
0
0
0
0
-
-
10
1
IMP.
91
69
21
100
90
99
-
97
45
77
Ho.
of
OBS
27
61
13
27
18
15
25
17
12
8
TKN
Mean
3657
1613
1256
1023
2112
646
1073
1175
826
1656
COV
.85
.70
.45
.44
.66
.41
.61
.73
.84
.65
Median
2785
1318
1144
936
1761
597
916
949
633
1389
901 Confi-
dence Limits
2186-3548
1152-1509
925-1414
815-1075
1376-2254
499-714
755-1110
720-1252
433-925
933-2068
Industrial
Site
1
2
3
4
HA2 Addlson
Mil Indus Drain
KS1 Lenaxa
Mil Grace S.
Land
Use
I
Ind
100
100
56
52
Area
(A)
18
63
72
75
Pop.
Den
(I/A)
0
0
-
5
I
IMP.
69
64
44
39
No.
of
OBS
5
18
12
18
TKN
Mean
2092
1274
1385
1713
COV
.49
.57
,73
.56
Median
1879
1107
1117
1493
901 Confi-
dence Limits
1207-2924
891-1376
796-1568
1205-1650

-------
                                  TABLE  6-7.   SITE MEAN NITRITE PLUS NITRATE EMCs
H-
en
Residential
Site
1
2
3
4
5
6
7
8
9
10
11
12
n
14
15
16
17
IB
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
C01 Big Dry Cr
C01 Cherry
C01 116/Claude
OC1 Oufief
DC1 Lakeridge
OCI Stratton
111 John N
KS] Overtoil
MA2 Hemlock
HD1 Bolton Hill
KOI Homeland
KOI Ht Wash
HOI Res Hill
NYl Carll's 8.
NYl tlnqua
NV3 Cranston
MV3 E. Roch.
TX1 Rolllngiiood
WAI Surrey
UI1 Burba nl
UI1 Hastings
FLI Voung Apts
TX1 Hart
UI1 Lincoln
TH1 R2
OCI Uestleigh
KS1 1C - 92nd
ILI John S.
TNI RI
WAI Lake Hills
III Hauls S.
Fll Charter Hdg
OCI Fairldge
C01 Asbury
IL2 Confc Inlets
HA1 Locust
NCI 11023
HA1 Jordan
DC1 Steduick
Land
Use
I
Res
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
99
97
96
93
92
91
91
91
90
69
88
86
85
85
84
79
78
Area
(A)
33
57
167
12
68
8
54
58
50
14
23
17
10
73
-
166
346
60
95
63
33
9
376
36
69
41
63
39
69
102
26
42
19
127
524
154
324
110
27
Pop.
Den
(•/A)
19
24
14
.
21
-
16
a
5
30
9
12
55
13
-
5
18
3
9
15
17
-
9
18
4
3
-
18
11
12
22
-
-
9
8
11
6
10
15
I
IMP.
41
38
24
-
33
-
19
36
16
51
29
29
76
20
-
22
38
21
29
50
51
6
40
57
13
21
37
16
33
37
37
16
34
22
17
16
27
21
34
Ho.
of
OSS
15
14
16
8
49
33
-
-
4
19
13
20
13
24
6
0
0
9
0
16
24
12
10
3
11
41
0
0
11
0
0
12
46
9
21
5
67
9
47
«°2,3-"
Hean
527
709
670
470
746
416
-
-

9535
6343
7822
6938
730
1533
-
-
879
-
775
625
311
1625
-
397
702
-
-
578
-
-
610
927
881
796
1705
716
1247
637
COV
.34
.40
.51
.35
.62
.66
-
.

1.59
4.56
1.56
1.08
1.38
-
-
-
.51
-
.46
.39
.64
.54
-
1.34
.59
-
-
.77
-
-
.77
.66
.21
.55
.69
.68
.55
.70
Median
499
657
579
445
633
317
-
-
-
5073
1358
4229
4707
442
-
-
-
763
-
699
582
262
1430
-
237
606
-
-
458
-
-
483
772
862
699
1406
591
1094
686
901 Confi-
dence Limits
429-580
547-788
469-715
354-556
552-725
254-395
-
-
-
3246-7930
570-3234
2753-6497
3046-7269
311-627
1020-1877
-
-
561-1055
-
580-843
510-664
193-355
1067-1917
-
136-412
525-700
-
-
315-665
-
-
339-688
667-893
758-980
576-648
776-2549
521-670
795-1505
568-600
Urban Open and Nonurban
Site
1
2
3
4
5
6
7
8
CA1 Seaview
C01 Rooney Gulch
NV3 Thornell
N»2 English Br
NV2 Uest Br
NV3 Thomas Cr
MI3 Traver Cr
HI 2 Sheriff Dock
Land
Use
t
Open
100
100
100
98
97
91
90
80
Area
(A)
633
405
26.416
5.248
5.338
17,728
2,303
552
Pop.
Den
U/A)
-
0
-
-
-
1
-

I
IMP.
-
1
4
1
1
11
6
7
No.
of
OBS
12
7
0
30
31
0
5
33
N02*3"N
Hean
1542
581
-
240
662
-
1108
383
COV
.49
1.03
-
.60
.53
-
.17
1.02
Median
1383
405
-
206
763

1092
268
90» Confi-
dence Limits
1087-1769
217-756
-
173-245
656-888
-
930-1283
A
Mixed
Site
1
2
3
4
5
6
7
6
9
10
11
12
13
14
15
16
17
18
19
20
KS1 Noland
MD1 Hampden
III Mauls II
Mil Uaverly
TNI SC
Wll food Ctr
MAI Rt 9
MAI Convent
Mil Grand R Ot
MI3 Pitt AA-S
NI2 Cedar
MAI Anna
MI3 Pitt AA-N
Mil Grace N
MI3 Sutft Run
SD1 Keade
CA1 Knox
FLI N. Jesuit
FLI Milder
C01 North Ave
Land
Use
I
_
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Area
(A)
36
17
17
30
167
45
338
100
453
2001
76
601
2871
164
1207
2030
1542
30
194
69
Pop.
Den
(I/A)
3
40
3
11
3
12
7
1
5
2
-
9
7
S
2
-
12
-
-
9
I
IMP.
68
72
58
66
43
61
23
33
38
21
5
12
26
28
4
-
-
13
97
50
No.
of
OBS
0
20
0
35
13
17
5
6
23
6
32
6
5
23
S
15
17
14
15
32
"°2,3-«
Hean
.
11,529
-
775
587
751
1.789
960
683
284
248
1.266
469
875
1.033
616
1,111
376
456
1,744
COV
.
4.00
-
.49
1.49
.69
.48
.39
.44
.46
.72
.60
.24
.43
.76
.40
.36
.54
.47
.92
Median
.
2793
-
696
327
618
1613
894
807
256
201
1086
456
803
821
571
1044
332
412
1286
901 Confl.
dence Li nits
.
1457-5355
-
610-794
192-558
474-805
1045-2490
656-1216
694-938
176-372
-
688-1714
364-571
693-931
431-1563
479-680
901-1210
261-422
336-505
1017-1626
Comnerclal
Site
1
2
3
4
5
6
7
8
9
10
C01 Villa Italia
NCI 1013 (CBD)
NY3 Southgate
UI1 Post Office
NH1 Pkg Lot
TNI CBD
HI] Rustler
KS1 1C Hetcalf
FLI Norms Pk
Mil State Fair
Land
Use
Coal
100
100
100
100
100
100
100
96
91
74
Area
(A)
74
23
179
12
1
26
12
58
47
29
Pop.
Den
(I/A)
0
0
2
0
0
0
0
-
-
10
I
IMP.
91
69
21
100
90
99
-
97
45
77
No.
of
OBS
27
61
0
28
28
15
26
0
12
12
N02,j-N
Hean
1180
1118
-
708
801
662
781
-
356
783
COV
.66
.55
-
.68
.64
.62
.69
-
.46
.50
Hedlan
895
980
-
584
615
562
642
-
323
702
901 Confi-
dence Limits
701-1143
878-1094
-
479-712
486-778
434-728
520-791
-
257-405
549-697
Industrial

Site

1
2
3
4
HA2 Addlson
Mil Indus Drain
KS1 Lena. a
Mil Grace S.

Use
I
Ind
100
100
56
52

Area
(A)

18
63
72
75

Den
(«/A)

0
0
-
5

I
IMP.

69
64
44
39

of
OBS

5
18
0
17
"U2t3""
Mean

1355
686
-
742
COV

.29
.40
-
.52
Hedlan

1301
637
-
657
901 Confi-
dence Limits

992-1706
544-746
-
' 534-808

-------
                                       TABLE 6-8.  SITE MEAN TOTAL COPPER EMCs
CTi
I
Residential

Site

1
2
)
4
5
6
7
e
9
10
11
12
13
14

15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
C01 Big Dry Cr
C01 Cherry
C01 116/Claude
OC1 Oufief
DC1 Lakeridge
DC1 St ration
IL1 John N
KS1 Overton
MA2 Hemlock
MD1 Bo] ton Hill
HOI Homeland
HD1 Mt Wash
HOI Res Hill
Ntl Carll's R.

NY1 Unqua
NY3 Cranston
NY3 E. Roch.
TX1 Rollingwood
WAI Surrey
Ull Bui-bank
Ull Hastings
FL1 Young Apts
III Hart
Ull Lincoln
TNI R?
DC1 Uestleigh
KS1 1C - 92nd
III John S.
TNI HI
UA1 Lake Hills
IL1 Mattts S.
FL1 Charter Hdg
DC1 Fairidge
C01 Asbury
1L2 Comb Inlets
HA1 Locust
NCI 11023
HA1 Jordan
DC1 Stednick

Land
Use
t
Res

100
100
100
100
100
100
100
100
100
100
100
100
100
100

100
100
100
100
100
100
100
100
99
97
96
93
92
91
91
91
90
89
68
86
65
85
84
79
78

Area
(A)

33
57
167
12
68
8
54
58
50
14
23
17
10
73


166
346
60
95
63
33
9
378
36
89
41
63
39
69
10?
28
42
19
127
524
154
324
110
27

Pop.
Den
I'/ A)

19
24
14
.
21
.
18
8
5
30
9
12
55
13


5
18
3
9
15
17
-
9
18
4
3
18
u
12
22
.
.
9
8
11
6
10
15

%
IMP.

41
38
24
.
33
.
19
38
16
51
29
29
76
20


22
38
21
29
50
51
6
40
57
13
21
37
18
33
37
37
16
34
22
17
16
27
21
34

No.
of
OBS

16
14
16
21
14
10
36
12
0
19
13
20
13
0

0
0
0
0
0
0
0
12
0
0
11
6
2
36
1 1
5
36
12
9
9
26
6
66
8
9
Total Copper.
Hean

32
35
28

38
28
83
91

107
312
26
42




.
.

.
-
6
.
-
28
37
43
61
22
45
10
26
59
49
107
39
74
30
COV

.82
1.48
.74
.
.55
.30
.85
.50

.70
.34
.78
.69




.
.

.
-
.36
.
-
1.54
.43
.84
60
.34
.76
.94
.39
.84
.53
.23
.60
.24
.35
Median

25
20
22

33
27
63
81

88
296
20
34



_
.
.

_
-
6
-
-
15
34
33
52
21
36
7
25
45
43
104
33
72
28
901 Confidence
Limits

18-34
12-33
16-29

26-42
23-32 .
51-78
93-103

68-112
252-349
15-26
25-46




.
•

_

5-7
-

8-27
24-48
26-40
38-70
15-29
30-44
5-11 .
19-31
29-71
36-51
86-125
29-37
_
23-35
























Mixed

Site
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15

16
17
18
19
20
KS1 Noland
KOI Hampden
IL1 Mattls N
Mil Waverly
TNI SC
Ull Uood Ctr
MAI Rt 9
HA1 Convent
HI 1 Grand R Ot
MI3 Pitt AA-S
NV2 Cedar
MAI Anna
HI3 Pitt AA-N
HI1 Grace N
H13 Swift Run

SD1 Meade
CA1 Knox
FL1 N. Jesuit
FL1 Uilder
C01 North Ave

Land
Use
t
-
-
•
-

-
-
-
-

-
-
-



-

-
-
-

Area
(A)
36
17
17
30
187
45
338
100
453
2001
76
601
2871
164
1207

2030
1542
30
194
69

Pop.
Den
(•/A)
3
40
3
11
3
12
7
1
5
2
-
9
7
5
2

-
12
-

9

t
IMP.
68
72
58
68
43
81
23
33
38
21
5
12
26
28
4

-

13
97
50

No.
of
OBS
9
20
37
16
13
0
7
7
13
0
0
5
0
9
0

0
17
15
15
32
Total Copper
Hean
48
81
48
15
42
-
112
105
30
-
-
54
-
14


-
98
7
6
77
COV
.38
.86
.81
.64
1.35
-
.49
.43
.63
-
-
.51

.31


-
1.14
.63
.84
.83
Median
45
61
37
13
25
-
100
96
26

-
48
-
13
_


65
6
5
59
901 Confidence
Limits
36-57
46-82
31-45
10-16
15-41
-
71-141
71-130
20-35

-
30-76
-
11-16
_

-
44-96
5-8
4-7
48-74















1
Commercial

Site
1
2
3
4
5
6
7
8
9
10
C01 Villa Italia
NCI 1013 (CBD)
NY 3 Southgate
Mil Post Office
NH1 Pkg Lot
TNI CBD
Ull Rustler
KS1 1C Metcalf
FL1 Noroa Pk
Ull State Fair

Land
Use
1
Coml
100
100
100
100
100
100
100
96
91
74

Area
(A)
74
23
179
12
1
26
12
58
47
29

Pop.
Oen
(I/A)
0
0
0
2
0
0
0
-
-
10

t
IMP.
91
69
21
100
90
99
-
97
45
77

No.
of
08S
27
61
0
0
31
15
0
6
12
0
Total Copper

Hean
33
70
-
-
104
42
-
41
11
-
COV
.87
.54
-
-
.13
.60
-
.33
.47

Median
25
61
-
-
103
36
-
39
10
-
901 Confidence
Limits
20-32
55-68
-
-
-
28-46
-
30-51
8-13
•
Urban Open and Nonurban
Site
1
2
3
4
5
6
7
8
CA1 Sea view
C01 Rooney Gulch
NY 3 Thornell
NY2 English Br
NY2 Uest Br
NV3 Thomas Cr
HI3 Traver Cr
NY2 Sheriff Dock
Land
Use
t
Open
100
100
100
98
97
91
90
80
Area
633
405
28.416
5.248
5.338
17.728
2,303
552
Pop.
Den
(I/A)
.
0
-
-
1
-
-
I
IMP.
-
1
4
1
1
11
6
7
No.
of
OBS
12
7
0
0
0
0
0
0
Total Copper
Mean
58
37
-
-
-
-
-
COV
.33
1.09
-
-
-
-
-
Median
55
25
-
-
-
-
-
901 Confidence
Limits
46-65
13-48
-
-
-
-
-
Industrial

Site

1
2
3
4
HA2 Addison
Mil Indus Drain
KS1 Lenaxa
Mil Grace S.

Land
Use
t
Ind
100
100
56
52

Area
(«)

18
63
72
75

Pop.
Den
(I/A)

0
0
-
5

I
IMP.

69
64
44
39

No.
of
OBS

0
6
5
7
Total Copper
Hean

-
36
36
25
COV


.53
.24
.65
Median

.
32
35
21
901 Confidence
Limits

-
21-48
28-44
14-32

-------
                                       TABLE 6-9.   SITE MEAN TOTAL LEAD EMCs
I
H
00
Residential
Site
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
JO
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
C01 Big Dry Cr
C01 Cherry
C01 116/Claude
OC1 Duflef
OCI Lakerldge
OC1 Stratton
III John N
KS1 Overton
HA2 Hemlock
HOI Bollon Hill
MD1 Homeland
MD1 Ht Wash
HD1 Res Hill
Nil Carll's R.
NVI Unqua
N»3 Cranston
Itn E. Roch.
TX1 Rollingwood
MAI Surrey
Mil Burbank
Ml] Hastings
Fll Young Apts
TX1 Hart
Ull Lincoln
TNI R2
DC) Mestleigh
KS1 1C - 92nd
III John S.
TNI Rl
MAI Lake Hills
111 Nattis S.
FLI Charter Hdg
DC1 Fairidge
C01 Asbury
IL2 Comb Inlets
MAI Locust
NCI 11023
MAI Jordan
OCI Steduick
Land
Use
t
Res
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
99
97
96
93
92
91
91
91
90
89
88
86
85
85
84
79
78
Area
(A)
33
57
167
12
68
8
54
58
50
14
23
17
10
73
-
166
346
60
95
63
33
9
378
36
89
41
63
39
69
102
28
42
19
127
524
154
324
no
27
Pop.
Den
(•/A)
19
24
14
-
21

18
a
5
30
9
12
55
13
.
5
18
3
9
15
17
-
9
18
4
3
-
18
11
12
22

-
9
8
11
6
10
15
I
1NP.
41
38
24
-
33
-
19
38
16
51
29
29
76
20
-
22
38
21
29
50
51
6
40
57
13
21
37
18
33
37
37
16
34
22
17
16
27
21
34
No.
of
08S
16
14
16
1
19
0
36
11
0
19
13
20
13
0
a
13
8
0
118
44
35
12
0
22
11
5
3
33
11
126
37
12
1
9
24
6
66
9
11
Total Lead
Nean
183
194
292
-
227
-
237
138
-
2745
76
86
461
-
88
34
193
-
152
95
108
76
-
303
133
186
-
217
440
192
595
49
-
433
322
271
254
168
141
COV
.88
.92
.87
-
.54
-
.73
.39
-
4.53
.46
.48
1.86
-
1.36
.77
.89
-
.51
.72
.67
1.03
-
1.14
.41
.17
-
.80
.61
.67
1.12
1.60
-
.72
1.01
.67
.98
.32
.41
Median
137
143
210
-
200
-
191
128
-
592
69
77
218
-
52
27
144
-
136
77
90
53

200
123
184
-
169
376
159
396
26
-
351
227
225
182
160
130
901 Confidence
Limits
98-191
99-207
151-292
.
164-245
'-
158-231
104-157
-
295-1188
56-86
65-92
119-399
-
26-103
19-38
86-240
-
126-146
65-91
75-107
34-82
-
143-280
99-153
157-216
-
138-208
277-511
146-174
308-508
14-47

253-524
169-304
136-371
153-215
132-194
105-161
Urban Open and Nonurban
Site
1
2
3
4
5
6
7
8
CA1 Seaview
C01 Rooney Gulch
NV3 Thornell
NY2 English Br
H12 Mest Br
NY3 Thomas Cr
MI3 Traver Cr
NY? Sheriff Dock
Land
Use
1
Open
100
100
100
98
97
91
90
80
Area
(A)
633
405
28,416
5,248
5,338
17,728
2.303
552
'op.
Den
(I/A)
-
0

-
-
1
-
-
t
INP.
-'
1
4
1
1
11
6
7
No.
of
OBS
7
7
10
21
25
12
0
33
Total Lead
Mean
214
52
12
9
38
35
-
132
COV
.89
.91
.42
.60
1.40
1.65
-
1.05
Median
159
39
11
8
22
18
-
91
90} Confidence
Limits
91-279
22-69
9-14
6-10
15-31
10-33
- ,^HI
71-^^1
Nixed
Site
1
2
3
4
5
6
7
8
9
10
11
12
13
14
IS
16
17
18
19
20
KS1 Noland
M01 Hampden
111 Nattls N
Nil Maverly
TNI SC
MM Mood Ctr
MA) Rt 9
MAI Convent
Nil Grand R Ot
NI3 Pitt AA-S
K>2 Cedar
NA1 Anna
NI3 Pitt AA-N
Nil Grace N
NI3 Sulft Run
SOI Neade
CA1 Knox
fll H. Jesuit
FLI Milder
C01 North Ave
land
Use
I
.
-
-
.
-
.
.
.
.
-
-
-
-
.
.
-
-
-
-
-
Area
(A)
36
17
17
30
187
45
338
too
453
2001
76
601
2871
164
1207
2030
1542
30
194
69
Pop.
Den
(I/A)
3
40
3
11
3
12
7
1
5
2
-
9
7
5
2
-
12
.
-
9
I
I HP.
68
72
58
68
43
81
23
33
38
21
5
12
26
28
4
-
-
13
97
50
No.
of
DBS
9
20
41
24
13
45
7
7
18
6
28
4
5
18
4
24
22
15
15
33
Total Lead
Mean
164
227
554
111
237
582
439
196
122
21
75
-
61
170
-
383
495
56
85
358
COV
.49
.82
1.06
1.09
.31
.94
1.02
.94
.90
1.63
1.25
-
.71
1.39
-
1.13
.99
1.22
.85
.81
Median
147
176
380
75
227
424
307
143
91
11
47
-
50
99
-
254
351
35
65
278
90S Confidence
Hilts
110-196
133-232
303-478
55-102
195-264
348-517
I65-S71
80-257
66-125
4-28
34-64
-
27-92
65-151
-
165-390
259-475
23-54
46-91
226-343
Conmercial

Site

1
2
3
4
5
6
7
8
9
10
C01 Villa Italia
NCI 1013 (CBO)
NY3 Southgate
Mil Post Office
NH1 Pkg Lot
TNI CBD
MM Rustler
KS1 1C Hetcalf
FLI Norma Pk
Mil State Fair

Land
Use
I
Coml
100
100
100
100
100
100
100
96
91
74

Area
(A)

74
23
179
12
1
26
12
58
47
29

Pop.
Den
(I/A)

0
0
0
2
0
0
0
-
-
10

J
IMP.

91
69
21
100
90
99
-
97
45
77

No.
of
OBS

27
61
13
59
33
15
44
7
12
27
Total Lead
Nean

262
382
47
193
208
158
121
-
46
409
COV

1.21
.81
.50
.83
.93
.52
.73
-
1.01
.86
Median

167
296
42
148
152
140
98
-
32
310
901 Confidence
Limits

122-228
254-345
33-53
126-173
121-192
112-175
83-115
-
21-49
243-396
Industrial
Site
1
2
3
4
MA2 Addison
Mil Indus Drain
KS1 Lenaxa
Nil Grace S.
Land
Use
t
Ind
100
100
56
52
Area
(A)
18
63
72
75
Pop.
Den
(I/A)
0
0
-
S
I
IMP.
69
64
44
39
No.
of
OBS
0
13
6
13
Total Lead
Nean
.
116

115
COV
.
.77
-
.76
Median
.
92
-
92
90t Confidence
Limits
-
66-129
-
66-128

-------
TABLE  6-10.   SITE MEAN TOTAL ZINC EMCs  (yg/Jl)
Residential
Site
1
2
3
4
5
b
7
8
9
10
11
12
13
14
IS
16
17
18
19
20
21
22
23
24
25
26
27
26
29
30
31
32
33
34
35
36
37
38
39
C01 eig Dry Cr
C01 Cherry
C01 116/Claude
OC1 Duflef
DC) Lakeridge
DC1 Stratton
Itl John H
KS1 Overton
HA2 Hemlock
M01 Bo I ton Hill
HOI homeland
HOI Mt Hash
HOI Res Hill
NV1 Carll's R.
lirl Unqua
OT3 Cranston
N»3 E. Roch.
TX1 Rollingnood
UA1 Surrey
Ull Burbank
Ull Hastings
Fl.l Voung Apts
IX 1 Hart
Ull Lincoln
INI R2
DC1 Uestlelgh
KS1 1C - 92nd
111 John S.
TNI Rl
UA1 Lake Hills
1L1 Mattis S.
FL1 Charter Hdg
DC1 Fairidge
C01 Asbury
IL2 Comb Inlets
HA1 Locust
NCI 11023
MAI Jordan
OC1 Stednick
Land
Use
1
Res
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
99
97
96
93
92
91
91
91
90
89
88
86
85
85
84
79
78
Area
(A)
33
57
167
12
68
8
54
58
50
14
23
17
10
73
.
166
346
60
95
63
33
9
378
36
89
41
63
39
69
102
28
42
19
127
524
154
324
110
27
Pop.
Den
(»/A)
19
24
14
.
21
-
18
8
5
30
9
12
55
13

5
IB
3
9
15
17

9
18
4
3
-
18
11
12
22
-
-
9
8
11
6
10
15
S
IMP.
41
38
24
-
33
-
19
38
16
51
29
29
76
20
-
22
36
21
29
50
51
6
40
57
13
21
37
18
33
37
37
16
34
22
17
16
27
21
34
No.
of
DBS
15
14
16
8
48
28
0
13
0
19
13
20
13
0
0
9
8
0
118
18
21
12
0
0
11
34
3
1
11
126
0
12
44
9
27
6
66
9
45
Total Ztnc
Mean
194
195
195
156
129
84
.
831
-
1388
120
92
531
-
.
415
488
-
124
106
108
60
-
.
93
67
-
-
412
120
.
54
86
349
230
247
178
218
91
COV
.80
.63
.66
.26
.70
.47
-
.97
.
2.21
.35
.54
1.20

.
.88
1.10
.
.42
1.34
1.20
.45
-
.
.57
.96
.
.
.59
.53

1.02
.52
.63
.69
.31
.81
.28
.70
Median
151
165
158
151
106
76
-
596
-
573
113
81
340
-
-
312
327
.
114
63
69
55
-
-
81
48
.
.
354
107
.
38
76
295
189
236
138
210
75
90t Confidence
Limits
110-208
125-217
121-206
127-179
91-123
66-88
-
399-891
-
337-973
96-134
67-98
213-542

.
195-499
180-594
-
107-121
42-95
49-99
44-69
-
-
61-109
38-61
-
.
263-477
99-115
-
25-59
67-86
206-422
154-232
184-303
119-160
177-249
64-88
Urban Open and Nonurban
Site
1
2
3
4
5
6
7
B
CA1 Seaview
C01 Rooney Gulch
HY3 Thornell
NV2 English Br
N(? West Br
N<3 Thomas Cr
MI3 Traver Cr
NY2 Sheriff Dock
Land
Use
I
Open
100
100
100
98
97
91
90
80
Area
(A)
633
405
28.416
5.248
5.338
17.728
2.303
552
Pop.
Den
(W
_
0
-
-
-
1

-
I
IMP.

1
4
1
1
11
6
7
No.
of
OBS
17
7
9
0
0
9
2
0
Total Zinc
Mean
190
105
792
-
-
1063
-
-
COV
.64
.58
2.39
-

3.14
-
-
Median
160
91
306
-

322
-
-
90t Confidence
Limits
125-205
61-135
130-720
-
-
124-839
-
-
Mixed
Site
1
2
3
4
5
6
7
a
9
10
11
12
13
14
15
16
17
IB
19
20
KS1 Noland
MD1 Hampden
IL1 Mattis N
Mil Uaverly
TNI SC
Ull Wood Ctr
MAI Rt 9
MAI Convent
Mil Grand R Ot
MI3 Pitt AA-S
NV2 Cedar
MAI Anna
MI3 Pitt AA-N
Mil Grace N
M13 Swift Run
SD1 Meade
CA1 Knox
FL1 N. Jesuit
FL1 Wilder
C01 North Ave
Land
Use
I
.
-
-
-
-
-
-

-
-
-
-
-
-
-
-
-

-
-
Area
(A)
36
17
17
30
187
45
338
100
453
2001
76
601
2B71
164
1207
2030
1542
30
194
69
Pop.
Den
3
40
3
11
3
12
7
1
5
2

9
7
5
2
-
12
-
-
9
t
IMP.
68
72
58
68
43
81
23
33
38
21
5
12
26
28
4
-
-
13
97
50
No.
of
OBS
9
13
0
17
13
27
7
7
14
4
0
5
4
9
2
0
21
15
15
33
Total Zinc
Mean
814
318
-
121
149
476
244
20?
245
-
-
178
-
149
-
-
303
94
51
543
COV
1.19
.35
-
.45
.40
1.21
.43
.59
.71
-

1.50
-
.35

-
.85
.68
.96
.82
Median
525
112
-
110
138
303
225
174
200
-
-
99
-
140
-
-
231
78
37
421
901 Confidence
Limits
293-940
225-340
-
92-132
114-167
22P-414
166-304
116-260
148-271

-
35-?79

113-173
-
-
175-305
59-103
26-53
341-520
Commercial
Site
1
2
3
4
5
6
7
8
9
10
C01 Villa Italia
NCI 1013 (CGD)
NY3 Southgate
Ull Post Office
NH1 Pkg Lot
TNI CBD
Ull Rustler
KS1 1C Metcalf
FL1 Norma Pk
WI1 State Fair
Land
Use
I
Coml
100
100
100
100
100
100
100
96
91
74
Area
(A)
74
23
179
12
. 1
26
12
58
47
29
Pop.
Den
(I/A)
0
0
2
0
0
0
0
-
-
10
S
IMP.
91
69
21
100
90
99
-
97
45
77
NO.
of
OBS
27
60
9
32
33
15
19
7
12
7
Total Zinc
Mean
320
533
1416
145
513
315
156
465
37
2BO
COV
.82
.51
2.55
1.16
.65
.43
.75
.78
.88
.66
Median
247
474
517
94
430
289
125
368
?8
234
90'. Confidence
Limits
195-313
428-526
214-1247
71-124
361-512
240-349
96-163
272-611
19-41
150-363
Industrial
Site
1
2
3
4
MA2 Addison
Mil Indus Drain
KS1 Lenaxa
Mil Grace S.
Land
Use
t
Ind
100
100
56
52
Area
(A)
18
63
72
75
Pop.
Den
(I/A)
0
0
-
S
t
IMP.
69
64
44
39
No.
of
OBS
0
7
6
7
Total Zinc
Mean
.
244
2721
223
COV
_
.42
3.29
.54
Median
-
225
791
196
901 Confidence
Limits
-
167-303
217-2882
135-284
                               *  All observations below detection limit.

-------
These tables  (one  for each pollutant) list each of  the  appropriate sites in
the data  base, grouped  according  to general land use category.   Some pert-
inent  site   characteristics   are   identified:    drainage  area,   population,
density, and  the percentage of the total area covered by impervious surfaces.
The number of  monitored . storms  at  each  site  is  tabulated.  Urban  runoff
quality is summarized by the  mean  and median EMC for all storms monitored at"
the site, the storm-to-storm variability of EMC's (defined by the coefficient
of variation), and the 90 percent confidence limits for the site median EMC.

Transferability of Data

The urban  runoff  loading site EMC data were  carefully examined in an effort
to determine whether  specific groupings of results would suggest the presence
of consistent patterns of similarities and/or differences that could be used
to support estimates  of  urban runoff characteristics at unmonitored locations
and sites.

Variability  of EMCs  at  a Site.  Inspection  and analysis of  the individual
site coefficient of variation entries in Tables 6-1  through  6-10 shows that
with very few  exceptions  (usually  associated  with  constituents  that  were
monitored  in  fewer than 10 storm events) the  coefficients  of variation fall
in the range  of 0.5 to 1.0.  This applies to all constituents except TSS, for
which the range in coefficients of variation is more like 1 to 2.

The frequency of occurrence of any EMC of interest  can  be estimated readily
from the  coefficient  of variation by  using  the  procedures outlined in Chap-
ter 5.   Thus,  for  TSS,  90 percent  of the individual storm events  at a given
site will  have EMCs that do  not exceed a. value of roughly 3  to  5 times the
median EMC value  for that  site.   For the  other constituents,  90 percent of
the individual  storm events  at  a  site will  have  EMCs  less than  about  2 to
3 times  the  median  EMC  value  for  that  site.  More  refined  estimates  and
values for other  exceedance probabilities  can be readily computed using the
relationships presented  in Chapter 5.

Effect of  Geographic  Location.   Figures 6-4  through  6-13 indicate the range
of  median EMC's  at  individual sites,  grouped by  project.   The  land  use
category  of  the site is indicated  by the  letter  R for  residential,  M for
mixed,   and C  for  commercial/industrial,  and the plotting  position  is  the
median value  as given by  the data in Tables 6-1 through  6-10.   The ends of
the bars  for each project  are  the highest and  lowest  90 percent confidence
limits for site median EMCs at the  project  for  the  constituent in question.
Inspection of Figures 6-4  through 6-13 indicates that,  for any  given con-
stituent,  each project  can be put  into one  of three  rather  general cate-
gories:   (I)  low  EMCs and tightly grouped;  (2)  average  characteristics;  and
(3) wide  range and high EMCs.   Using the  numbers 1, 2,  and  3  as shorthand,
project  categories   for each  constituent  are  summarized  in  Table 6-11.
Although no  site is category consistent for all constituents, WASHCOG (DC1),
Tampa (FL1) ,  Lansing (Mil) ,  and Ann  Arbor  (MI3)  tend  to  have  lower  and
more tightly grouped EMCs than  the  others  while  Kansas  City  (KS1),  Lake
Quinsigamond  (MAI), and  Baltimore  (MD1) tend to have a wider range and higher
EMCs than the others.  Thus we can conclude that some projects represented in
the database appear,  from the  monitoring sites  selected,  to tend towards
somewhat higher or lower EMC median values  and ranges than  the  bulk of the
projects.  However, there are no distinct geographical patterns revealed.
                                    6-20

-------
 CA1
 C01
 DC1
 m
 111
 IL2
 KS1
MAI
MA2
MD1
 Mil
 MI3
 NCI
 NH1
 NY1
 NY2
 NY3
 SD1
 TNI
 TX1
WAI
 WI1
) 11

r
|R RRRR F
1 1
CRMMR I

C C
1 ARM
1 1C
IRMRR R
1C M
IMMM
1
hrn
i
1 R'

IRM 1
1 R
G

) it
0 21
1 M
CR
LJ

RR N
1 1
R
RM

|
III MM 1
1
: R i

M
C 1


R
n
1 R CC
0 21
TS
0 30
1
R R


R J
1 1
M







1



1

1 R C
10 31
IS
0 41

M R





1







1




M 1
10 4
0 5(

















B



10 5
10 60

1














1128




10 61
0






JT 
-------
                              COD
  CA1
  C01
  DC1
  FL1
  111
  IL2
  KS1
 MAI
 M01
  Mil
  MI3
  NC1
  NH1
  NY3
  SD1
  TNI
  TX1
 WAI
  WI1
5 50
r
1 R RRRR
M C RMR

1 C C
|

dMM

I

R

1


M R
1
C MM
75 10
1
M
0 12
5 1!
0
225
RRR C R fr?M|275
II




R R R M<* 1196
II R 1

M R R {* 1180
M M R I

M RR R R X 1194
1
1
C

R C

1 R M
|
1 RR 1
R R CC
>.5 50
R
1


C
RR

R


C 1
C I
R 1
1


167
1 **MI200
R 1
1


M C 1
75 • 100 1
Z5 15
0
        Figure 6-6.   Range  of COD EMC Medians (mg/1)  by Project
CA1
C01
DC1
 FL1
 IL2
MAI
MA2
MD1
MI1
MI3
NCI
NH1
NY1
NY2
SD1
TNI
TX1
WI1
           0.5
1.0
TOT. ?

  1.5
2.0
2.5
                                  3.0

n
1 R R
IR CMN





|M M

1
1 R
IMJ
1 R M R

[
0
r
IRR R C
RRR R 1
IR 1
1 R 1
1 M 1

1
ICMM MMI
M
IR 1
C 1

m
: I
1 R
RRMCC 1
5 1
-R— 1
M



! M R
C
R


LJ

R


R

0 1

Z3



M
1


D


i


i

.5 2

















.0 2





]

M









.5 3






4.2 4.
^^/ RRR 1









0
      Figure 6-7.   Range of Total  P  EMC Medians  (mg/1)  by Project
                                    6-22

-------
                   SOL. P
c
CA1
C01
DC1
FL1
111
IL2
KS1
MAI
MD1
MM
NCI
NH1
TN1
WAI
1 2

1 Rl

| |
MRMRC



r
IMM


1 R
u
0 4

ICR
RRR RR

1 RRM
|
I CC
1
* R
MM C
IR

M C
\ 	 |
0 6
1
R n
1


R 1
M
M
ft
1
1

R

0 8
R
fl 1


R 1

1
R
A

O

1

0 1C
I





1
M 1
R


1


o 1:






~l
VI R



C I


.0 1<














0







1
1





                                                        296 R|349
Figure 6-8.  Range of Soluble  P EMC Medians (mg/1) by Project
                         TKN
[
CA1
C01
DC1
FL1
111
112
KS1
MAI
M01
MI1
MI3
NCI
NH1
NY1
NY2
NY3
SOI
TNI
WAI
WI1
I
U



1 RCMRM 1



r
1 RR
IMM
IM M 1


1 R
IMI
IRC



IRRC
1 11
10 21

RR C
1 R R

1 RR

ICCRRM 1
M M R
M
MCM 1

1 R
1 C


R
1
R C
IR Rl
C
10 21
10 31
1
R M
1 1


R

R 1
R


t



1
M
M

1
10 3C
10 4G
R
R


M


A



: I




i
R

C
0 41
0 5(
1



I














M
30 51
10 61

ID


D


1
1








3

11
10 6
0








?t 11188











)0
   Figure 6-9.  Range of  TKN EMC Medians (mg/1) by Project
                             6-23

-------
                       N02+3-N
(
CA1
C01
DC1
FL1
IL2
KS1
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Mil
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NH1
NY3
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(
) 11


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10
Figure 6-10.   Range of NO    -N EMC Medians  (mg/1) by  Project
                          Cu
          200
     400
600
800
1000
1200
1400
 CA1
 C01
 DC1
 FL1
 111
 K51
MAI
MA2
MD1
 Mil
 MI3
 NCI
 NH1
 NY1
 NY2
 NY3
 SD1
 TNI
 TX1
WAI
 WI1
fCRRJi
IR RR
ICM

1 c
1 «
iRfil LJTJ
RR R
MRR II
1 M R
C M
A R M



IR |
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1




1





£ > 2031
* £ 1726
   R  RM
         I   I
CRM

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(RRI

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1 1

1 M MMM C
IMM Mil
1 1 CR 1
1 RH 1
1 M 1
1C R R |
1 1





1 M J
                                    825R 4326
                                              (    11820
          200
    400
600
800
1000
1200
1400
Figure 6-11.   Range  of Total  Cu EMC Medians  (yg/1) by  Project
                                6-24

-------
                       Pb
           50
100
150
200
250
CA1
C01
DC1
IL2
KS1
MAI
MA2
Mil
MI3
NY2
SD1
TNI
1




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1 RM R RCR |
|R R RR R 1/392R 598



3141 H396R 501
1C M C R RU 378
1 M R M R |
C R
MMM MC|
|M MM I
ULJ

1 M |



I C R R M 1
5
0 11
10 1
10 21
10 2
50
Figure 6-12.  Range of Total  Pb EMC Medians (yg/1) by Project
i
CA1
C01
DC1
FL1
111
KS1
MAI
MA2
MD1
Mil
MI3
NCI
NH1
NY1
NY2
NY3
SD1
TNI
TX1
WAI
WI1
1
i 2 :
i
1 M 1
) 4
E
1 R RR C R M 1
1 R RRR RR 1
1 C MRMR


1

MR R R 1

t
IT C R 1
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IRRI I
ICCRRMC 1
i
1 2
3
1
5
5
Figure 6-13.  Range of Total Zn EMC Medians  (yg/1) by Project
                             6-25

-------
           TABLE 6-11.  PROJECT CATEGORY SUMMARIZED BY CONSTITUENT

TSS
BOD
COD
Tot. P.
Sol. P.
TKN
N02+3-N
Tot. Cu
Tot. b
Tot. Zn
rH
8
3
-
3
1
2
2
2
2
2
2
1-1
o
Q
1
—
1
2
3
1
1
1
1
1
iH
1
2
1
1
-
1
1
1
1
1
i-H
H
2
—
3
2
-
2
—
2
2
-
•H
C/J
3
3
3
3
3
2
—
2
1
3
rH
3
—
2
3
2
2
3
3
2
2
•-I
Q
S
1
—
3
3
-
3
3
3
3
3
i-t
H
1
2
1
2
2
1
1
1
1
2
ro
H
2
1
1
—
1
1
1
2
-
-
-
n
a
2
—
1
2
-
2
—
—
1
3
.H
z
EH
3
2
2
2
2
1
1
2
2
2
iH
H
2
2
2
2
2
-
1
1
—
2
2
It must  also  be  realized  that  had any  particular project  monitored  other
local sites  (or additional  sites) its categorization could well change.   This
can be seen  qualitatively by perusing Figures 6-4  through  6-13 and mentally
dropping the highest  or lowest  site from each grouping.  Although some loca-
tions, such as Tampa, will  undoubtably and appropriately be influenced by the
relatively low EMCs and  tight  groupings found there  in  estimating probable
values for other urban  sites  in  the area,  there  is  little to warrant attrib-
uting  similar  characteristics  to  other  locations  in  the  same geographical
region.  For the other  locations it would appear that individual site differ-
ences eclipse any possible  geographic ones.

Effect of Land Use  Category.   The data in Tables 6-1  through 6-10 were pre-
sented by land use  category;  residential, mixed,  commercial, industrial, and
open/non-urban.  The  question to be addressed here  is the  extent  to  which
such site categorization can be used to  assist  in  predicting EMC parameters
for unmonitored sites.    Two  approaches  were used.   In the  first,  the site
data for each  project with more than three sites were normalized by dividing
the site median and its upper and  lower  90 percent confidence  limits  by the
average project median  value  for the constituent in question.  This procedure
simply allows   all  constituents  to be  viewed  on  a  common  scale that  is
centered at  unity.    An example of  the  result is  given  in  Figure  6-14.   A
legend is provided  in Figure  6-14(a)  showing the lower 90 percent confidence
limit, the upper  90 percent confidence limit, and  the location of the  point
estimate of  the median within  this  confidence  interval  for a hypothetical
constituent.  Sites that  fall to the right of the unity line have higher EMCs
than average for this  location,  while  sites  that  fall  to  the left of the
unity  line  have lower  EMCs than average.  Thus, the  interpretation is that
for this  location,  Site  #1 is  the  "dirtiest"  (has  the highest  EMC value) ,
Site #3  is  the  "cleanest",  and   Site  #2  is  in  between,  being  somewhat
"dirtier" than average.   Since  the 90 percent  confidence  limits  for  these
three  sites  no not  overlap,  we know  that this difference  is  statistically
significant.
                                    6-26

-------
                                                       0.5    1.0    1.5    2.0




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-------
The actual data for the Denver  (CO1) project are presented in Figure 6-14(c).
With the exception of  nitrate + nitrite,  there is little to no statistically
significant difference among the majority of  the  sites  for each constituent-
examined.   The lack of consistency among  the sites  over the  various  con-
stituents  is  apparent.  One  can observe  that the Cherry  site  (residential)
tends to plot  at the lowest position for all constituents, suggesting that it"
is the  "cleanest,"  the Asbury  site  (also residential) tends  to plot  at the
highest  position,  suggesting  that  it  is  the   "dirtiest."   The  Big  Dry
Cottonwood site, which is  also residential,  tends to fall between these two.
Careful  examination  of  other  site  data  does not  provide  any evidence  to
explain this  difference in response for sites in  the  same land use category
at  the  same   location.    Thus,  based  on  the   information  presented  in
Figure 6-14(c), one  is  forced to conclude that  land  use category  does not
provide  a  useful basis for  predicting differences  in  site EMC values,  at
least for this project.

When the foregoing type  of analysis was applied to the other applicable NURP
projects,  the  results  were the  same.   As another  example,  the range of nor-
malized  EMC   medians   at   Tampa  (FL1)   and   WASHCOG   (DC1)  are   shown  in
Figure 6-15.   These  are  essentially   similar to the  Denver results  just
discussed.

The WASHCOG data presented  in  Figure  6-15(b) suggest that there  is  little
consistent difference  among  residential land  use  sites at that project.   The
data from  Champaign/Urbana  (IL1)  presented in Figure 6-16  suggest  just the
opposite.  As  a part  of this project's experimental design,  two  site pairs
were selected.  The  sites  of each pair were expected to respond in a similar
fashion.  That they do and that the responses of  the two pairs are different
from each  other for  most  constituents  is apparent in  Figure 6-16.   However,
there is no consistency  in the pair  responses. For  example, the Mattis pair
has significantly  higher  EMC values  for TSS,  COD,  and Total Pb,  while the
John Pair  is higher in Total P.   The  residential  land  use category for these
sites provides no explanation of these differences in response.

Based upon  the foregoing approach, we can conclude  that,  while there  can be
differences in the responses of different sites at a given location, signif-
icant differences do not appear to be widespread, and where they  occur, the
site  land use category  is  virtually  useless in  trying  to  understand  or
predict them.

The second  approach  to examining the effect of land use  category  on the EMC
parameters of  a site  makes  use of the observation,  discussed earlier,  that
geographic location  has no discernible effect on  site response.   Since  site
to site  variability  was shown  to  be  very well represented  by the lognormal
distribution,  analysis procedures similar to  those  described previously for
characterizing an individual site  were  applied.   Table 6-12 lists  the median
EMCs for all  sites within  each land use category.  The coefficient of varia-
tion quantifies the  variability of site characteristics within the  land use
category.  To  the  extent  that the sites included  in this  database provide a
"representative" sample of the  land use classifications, then the information
summarized  by Table 6-12  indicates  the effect of  land  use on urban storm
runoff pollutant discharges.
                                    6-28

-------
                                                     0.5    1.0    1.5    2.0
       0.5    1.0    1.5
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                                                     0.5    1.0     1.5    2.0
(a)   Tampa Sites
(b)   WASHCOG Sites
        Figure 6-15.   Range  of Normalized EMC Medians  at FL1  and DC1
                                        6-29

-------
         0.5
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-------
                                           TABLE 6-12.   MEDIAN EMCs FOR ALL SITES
                                                    BY  LAND USE CATEGORY
Pollutant
BOD
COD
TSS
Total Lead
Total Copper
Total Zinc
Total Kjeldahl Nitrogen
NO -N + NO -N
Total P
Soluble P
•
t
1
rng/S,



yg

,



/I


Residential
Median
10.0
73
101
144
33
135
1900
736
383
143
CV
0.41
0.55
0.96
0.75
0.99
0.84
0.73
0.83
0.69
0.46
Mixed
Median
7.8
65
67
114
27
154
1288
558
263
56
CV
0.52
0.58
1.14
1.35
1.32
0.78
0.50
0.67
0.75
0.75
Commercial
Median
9.3
57
69
104
29
226
1179
572
201
80
CV
0.31
0.39
0.85
0.68
0.81
1.07
0.43
0.48
0.67
0.71
Open/Nonurban
Median
-
40
70
30
-
195
965
543
121
26
CV
-
0.78
2.92
1.52
-
0.66
1.00
0.91
1.66
2.11
en
OJ

-------
Some caution in the interpretation of the information presented in Table 6-12
is  in  order since  statistical confidence limits  are  not given.   These are
indicated  in  Figure 6-17  (a through k),  which illustrates  land  use differ-
ences graphically, with  additional  statistical detail  derived from the basic
parameters listed in Table 6-11, to assist in  interpretation and comparisons.
The box  plots  which compare characteristics  of all sites within  a land use"
category identify the land use, median EMC, its 90 percent confidence limits,
and the  10, 25, 75  and  90 percent  quantities  for the sites.   Careful perusal
of  these box plots leads one  to the conclusion that only the open/non-urban
land use category  appears to be significantly different overall.  Responses
of  the  other  land use  categories are  varied  and inconsistent  among con-
stituents .   This may be  seen  in a somewhat  different way  by  observing the
plotting  positions  of  the  land  use  categories  presented in  Figures 6-4
through  6-13.   Here  also,  there  are  no  consistent tendencies.   There are
undeniably some  trends.   For  example, in  Figure 6-7 commercial sites occupy
the lowest plotting position  at each  project for total  phosphorus (Mil and
one WI1  site are exceptions),  which certainly suggests that there might be a
land use category difference for this constituent.

Review of Figure 6-17(j), however, suggests that while a trend to lower total
phosphorus EMC values is apparent  as one  goes from residential, to mixed, to
commercial land  uses, the  statistical significance may not be  great.  The
actual  site  median total phosphorus EMC  probability density  functions for
each  land use  are  presented  in  Figure 6-18.   Here  it can  be  seen that
although three different pdfs  can be drawn for residential,  mixed, and com-
mercial  land use  categories,  their degree of  overlap  is so  great that there
is  little  statistical significance to  the apparent difference.   Since this
was the  strongest  tendency  towards land use  effect,  we must  conclude that
using this approach there is again no truly discernible and consistent effect
of  land use on the quality of  urban runoff.

The one exception is the open/non-urban category which, as its name suggests,
includes  atypical  sites.  The data  in  Table 6-12  and the  box plots  of
Figure 6-12 suggest that the  pdfs for this land use category are quite dif-
ferent from those  of  the other land use categories, and this is in fact the
case.  Figure 6-18 shows it dramatically for total phosphorus.

Thus, regardless of the  analytical approach  taken, we are forced to conclude
that,  if land use  category effects are  present,  they  are  eclipsed  by the
storm  to storm variabilities  and that, therefore,  land use category  is of
little general use  to aid in predicting urban runoff  quality at unmonitored
sites or in explaining site to  site differences where monitoring data exist.

Correlation Between EMCs and  Runoff Volume.   To  examine the possible rela-
tionship between.the event mean concentration  of a particular constituent and
the runoff volume,  linear correlation  coefficients (r)  were  calculated.  The
null hypothesis  that  the two  variables are  linearly unrelated  was tested at
both  the 90  and 95 percent  confidence levels.   Since  it  is  possible for
correlation to be  either positive  or negative, the two-tailed test was used.
Failure  to reject  the null hypothesis is interpreted  as meaning that linear
dependency between the two variables in the population has not been shown.
                                    6-32

-------
                               LEGEND
        )
       (a)
                  90%
                 VALUE
                  75%
                 VALUE
                 MEDIAN
                 VALUE
                  25%
                 VALUE


                  10%
                 VALUE
 STATISTICAL
 SIGNIFICANCE
   OF THE
   MEDIAN
/   90%   \
VCONFIOENCE;
 INTER-
QUARTILE
 RANGE
                      GROUP A   GROUP B
                                                                IP
20


18


16


14


12


10


 8


 6


 4


 2


 0
                                                                                           BOO
                             (b)
                                       RESIDENTIAL
                                         SITES
                                        11
                                       MIXED
                                       SITES
                              11
                          COMMERCIAL
                             SITES
                                                                                                          1
                                                                                                         OPEN
                                                                                                         SITE

Ud  UJ
S  o
   ~
        500
        400
        300
        200
        100
                                  TSS
          33          19          14           8
       RESIDENTIAL      MIXED     COMMERCIAL      OPEN
/  x      SITES        SITES        SITES        SITES
      160


      140


      120





lit  80
I4j£

S8    6"


       40


       20


        a



   (d)
                                                                                                COD
                                                                                33
                                                                            RESIDENTIAL
                                                                               SITES
                                                      16
                                                    MIXED
                                                     SITES
                                                     13
                                                 COMMERCIAL
                                                    SITES
                                            5
                                           OPEN
                                           SITES
                             Figure  6-17.   Box  Plots of Pollutant EMCs for
                                               Different  Land  Uses
                                                         6-33

-------
100
90
80
70
60
1 50
40
30
20
10
0
•
•
•
•
[— '
L_

. q
.


>

TOTAL
COPPER

"

rj 1
. J \ / w
\ A A
P A 4^
T
23 12 10 2
RESIDENTIAL MIXED COMMERCIAL OPEN
SITES SITES SITES SITES
                                                               500
                                                               400
                                                               300
                                                               200
                                                                100
                                                                                             TOTAL LEAD
                                                                               1
                                                                        30
                                                                    RESIDENTIAL
                                                                       SITES
                                                            16
                                                          MIXED
                                                          SITES
                                                              11
                                                          COMMERCIAL
                                                             SITES
                                                            7
                                                          OPEN
                                                          SITES
(e)
                                  (f)
     500
     400
     200
     100
                  TOTAL
                   ZINC
             26
          RESIDENTIAL
            SITES
 12
MIXED
SITES
    13
COMMERCIAL
   SITES
(g)
 4
OPEN
SITES

                                                       b  *»
                                        5000
                                                               4000 •
                                                               3000
                                                               2000
                                                               1000
                                                                                              TKN
   32
RESIDENTIAL
  SITES
 18
MIXED
SITES
    14
COMMERCIAL
   SITES
 8
OPEN
SITES
                                  (h)
                     Figure  6-17.   Box Plots  of  Pollutant  EMCs for
                               Different Land Uses  (Cont'd)
                                               6-34

-------
  >;
cog
  u
2000


1800


1600

1400


1200

1000


 800

 600


 400


 200
                                NITRITE
                                  AND
                                NITRATE
                 24
             RESIDENTIAL
                SITES
 17
MIXED
SITES
                              11
                           COMMERCIAL
                             SITES
OPEN
SITES
       1000

        900

        800

        700

  2 =
=r 5 g   600
lSS
S-ll 500
    a.

« g <   400
  "S
        300

        200


        100

         0

 LAND USE
  NO SITES
                                                               TOTAL PHOSPHORUS
   34         19         14         8
RESIDENTIAL     MIXED    COMMERCIAL     OPEN
                        &         &
                     INDUSTRIAL   NON URBAN
   (1)
                                  (j)
        250
        200
         150
 35 g     100
   u
                                      SOLUBLE
                                    PHOSPHORUS
         50
                 16
             RESIDENTIAL
                SITES
  14
MIXED
SITES
                           COMMERCIAL
                              SITES
  6
OPEN
SITES
   (k)
                       Figure  6-17.   Box Plots of Pollutant EMCs  for
                                  Different Land  Uses  (Cont'd)
                                                  6-35

-------
                                                                                     URBAN LAND USE
                                                                    CM

                                                                    10
                                                                    o
                                                                    CM
                                                                    n
                                                                                 COMMERCIAL   (201)
                                                                                 MIXED        (263)
                                                                                 RESIDENTIAL   (383)
                                                        CV
                                                       0.67
                                                       0.75
                                                       0.69
                          URBAN OPEN
                              £
                          NON URBAN
                           (121
                           CV = 1.66
i
w
en
        10
100
1000
3000
                                                   SITE T.P. CONCENTRATION (pgjl)
                                  Figure  6-18.   Site Median Total  P  EMC Probability Density
                                               Functions for Different Land Uses

-------
The rejection of the null hypothesis means that there is evidence of a linear
dependency between the two variables in  the  population,  but it does not mean
that a cause-and-effect relationship has been established.

General guidelines  for the use  of this  test suggest  that it be  used with
caution for  values  of n less than  ten due  to  the high  uncertainties  asso-
ciated with  estimates of population variance with small  samples.   Further-
more, when n  is  2 a perfect  correlation will result but  is meaningless.   To
include as many  sites as possible in this examination,  all constituents for
which n was 5 or greater were included.   At the other extreme, when n is very
large, say over  100, correlation coefficients are  almost always significant
but can be so weak that they are meaningless.  For n = 100 the critical value
of r  at the  90 percent confidence level is  0.164,  meaning that the correla-
tion explains less than 3 percent of the concentration variability.

A total of 67 sites  from 20  of  the NURP projects were  examined for possible
correlation  for  nine constituents.  Of  the  517 linear  correlation coeffic-
ients  calculated   (not  all  constituents   were   measured  at  all  sites) ,
116 (22 percent)  were significant  at  the  95 percent  confidence  level  and
154 (30 percent)  were significant at the 90 percent confidence level.  Of the
r values that were significant,  83 and 87 percent were negative at the 90 and
95 percent  confidence  levels  respectively.  When sites with  fewer  than
10 events were dropped, the  foregoing  was  essentially  unchanged.   Greater
detail in terms  of  the number of significant linear  correlation by constit-
uent  is  provided in Table 6-13.  There it  can  be seen that  the greatest
tendency  for  positive  values  of r occurs  with  TSS,   followed by  soluble
phosphorus.   The  correlation  coefficients for  the other  7 constituents  all
strongly tend to be negative.

When the results are examined by sites, however, a clearer picture emerges.
Although it can be  correctly  argued that unless  a correlation coefficient is
statistically significant the number is  meaningless,  it also follows that in
such  a  case   they are as likely  to  be positive  as negative.  On  the  other
hand, if all  the correlation  coefficients (whether significant or  not) have
the same sign, it suggests a  tendency  for that  site.   The sign of the corre-
lation  coefficient   (if  greater  than  0.1)  for  each  site  and  constituent
examined is  given in Table 6-14.   Giving appropriate weight to significant
r values but  considering others  as well, some 37  of  the  sites  tend to have
negative correlations, 13 tend  to be  positive,  and the  remaining 17 tend to
be mixed.   Perusal of Table 6-14 reveals that this tendency for sites to have
either  positive  or  negative  correlation  coefficients  is  quite  strong,
especially for sites  with a large number of  significant correlations.  Sites
where erosion, scour,  system  lag, and such  are present  could be expected to
exhibit a tendency towards positive correlations.  Sites lacking such effects
could be  expected to  have  negative correlation  due  to  dilution associated
with larger runoff events.

The magnitude of the correlation coefficients  is indicated  in Table 6-15.
Two points stand out  in particular.  First,  the  r values are not very large,
averaging  around 0.55.  This means that the  correlation  is  only  able  to
explain about 30 percent of  the  concentration  variability.   The   few high
values are always associated  with very few observations  (n<10) for which the
                                    6-37

-------
TABLE 6-13.  NUMBER OF SIGNIFICANT  LINEAR
       CORRELATIONS BY CONSTITUENT
(a) ALL SITES
TOTAL #
POLLUTANT OF SITES
TSS
COO
TOT. P
SOL. P
TKN
N02+3-N
TOT. Cu
TOT. Pb
TOT. Zn
TOTAL
PERCENT
67
64
67
34
64
57
49
59
56
517

90% SIGNIFICANT CORRELATION
TOTAL #
13(19%)
24 (38%)
20 (30%)
10 (29%)
19 (30%)
17(30%)
17(35%)
15 (25%)
19 (34%)
154
30%
n NEG.
4
23
16
6
18
15
15
13
18
128
83%
#POS.
9 .
1
4
4
1
2
2
2
1
26
17%
95% SIGNIFICANT CORRELATION
TOTAL #
7 (10%)
19 (30%)
15 (22%)
7 (21%)
14 (22%)
13 (23%)
13 (27%)
12 (20%)
16 (29%)
116
22%
#NEG.
3
19
12
4
14
11
12
11
15
101
87%
#POS.
4
0
3
3
0
2
1
1
1
15
13%
(b) SITES WITH n > 10
TSS
COO
TOT. P
SOL. P
TKN
N02+3-N
TOT. Cu
TOT. Pb
TOT. Zn
TOTAL
PERCENT
56
52
53
23
50
41
31
45
37
388

9 (16%)
21 (40%)
17 (32%)
8 (35%)
17 (34%)
14 (34%)
13 (42%)
13 (29%)
14 (38%)
126
32%
4
20
15
5
16
12
12
12
13
109
87%
5
1
2
3
1
2
1
1
1
17
13%
7 (12%)
16 (31%)
12 (23%)
6 (26%)
12(24%)
12 (29%)
12 (39%)
1 1 (24%)
11 (30%)
99
26%
3
16
11
4
12
10
11
10
10
87
88%
4
0
1
2
0
2
1
1
1
12
12%
                                                             CO

                                                             CO
                   6-38

-------
                                          TABLE  6-14.   SIGN  OF CORRELATION COEFFICIENTS BY  SITES
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                ©INDICATES A SIGNIFICANT R VALUE
                 BLANK INDICATES EITHER R LESS THAN 0.1 OR NO DATA

-------
                                            TABLE 6-15.   CORRELATION  COEFFICIENT  VALUES BY SITE
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            (J INDICATES 95% LEVEL OF SIGNIFICANCE. OTHERS ARE AT THE 90% LEVEL
            U INDICATES AN UNMEASURED CONSTITUENT
            BLANK INDICATES NO SIGNIFICANT CORRELATION

-------
test  is  suspect  since  one or  two events  may dominate  the  correlation  or
otherwise cause it to be  overstated due to uncertainties  in parameter esti-
mation.  Second, only 25 percent of the  sites  account for over two-thirds of
the significant correlations.   In  fact, 33 of the 67 sites had  at  most one
significant correlation,  16 had 2  or 3,  and  18  had 4 or  more  significant
r values.

Data  for the  sites  with  many  significant  correlations  are presented  in
Table 6-16.   It  can be  noted  that the  r values for  all  constituents  are
around 0.55.  Thus, there  is no overall  tendency  to  have strong correlations
for some constituents and weak correlations for  others.   On  a site by site
basis, the  strength  of  the apparent  correlation  varies inversely with n as
does  the significance requirement.   Discounting  the  sites with  very  low or
high  values of  n, however, the r values for  the  remainder  are  again around
0.55, which is the average for  all 19 of these sites.   Turning  to land use,
it is significant that  half of the sites with many  significant correlations
have  a large commercial/industrial component.   Discounting sites with a small
number of observations (n _< 12), the sites in Table 6-16 are smaller (average
size  is  41  acres  vs 126 acres  for  all  sites) ,  more impervious  (average  of
65 percent  vs   40 percent  for  all  sites) ,  and  have  higher runoff  coef-
ficients (0.5 vs 0.3 for  all sites).   Thus,  one  could  conjecture that their
responses might tend to be somewhat less random and  more ameanable to deter-
ministic analysis  (i.e., with conventional modeling  approaches).   Since they
represent only around 25  percent  of the total  number of  sites,  however, and
the correlations  are rather weak,  any effect of  EMC  correlation  with runoff
volume can be ignored without serious overall error.

This  finding  of  no  significant linear  correlation  between EMCs and runoff
volumes  is  important• for  several  reasons.   First, in  stormwater monitoring
programs there  is a  natural and  appropriate  bias  that  favors  emphasizing
resource allocation to larger storm events.  This was generally the case with
the NURP projects as well.  However, because of differences in local meteor-
ological conditions, degree of  site imperviousness,  and other factors, there
are appreciable differences in the  average  sizes  of  storms monitored by site
in the NURP database.   Since  no significant  linear correlation  was found,
such  biases and differences are not expected to influence EMC comparisons to
any appreciable extent.

Secondly,  the   probabilistic  methodologies  for   examining  receiving  water
impacts identified in Chapter 5 assume, as they are now structured, that con-
centration and runoff volume are independent  (i.e.,  that there is no signif-
icant correlation).  Although the methods can be modified to account for such
correlations if they  exist, the finding of no significant correlation indi-
cates -that such refinement is not warranted at this time.

Other  Factors.  We have not exhaustively  analyzed all potential effects  of
other  factors that might  influence and hence  modify  our interpretations and
conclusions regarding site differences.  Factors such as  slope, population
density,  soil  type,  seasonal  bias  in  monitored events,  and precipitation
characteristics   (average   rainfall  intensity,   peak   rainfall   intensity,
rainfall  duration, time since last  storm event, etc.)  all  have a potential
                                    6-41

-------
TABLE 6-16.  SITES WITH MANY SIGNIFICANT CORRELATIONS

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VILLA IT.
DC1 WESTLEIGH
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MATTIS S.
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<«=
32
27
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12
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6

13
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8
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126
118
40
20
25


a
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30%C
100%C
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89%R
50%C
90%R
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100%R
100%C
100%C
100%R
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91%R

91%R
100%R
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100%C
74%C


%
IMPERVIOUS
50%
91%
21%
16%
58%
37%
44%

16%

76%
69%
90%
38%
99%
33%

37%
29%
95%
95%
77%


RUNOFF
COEFFICIENT
.239
.927
.119
.153
.639
.330
.540

.209

.486
.791
.658
.195
.206
.032

.199
.177
.899
.793
.622



-------
influence  on the median  and variability  of pollutant  concentrations  at  a
site.

On  the  basis  of limited  screening,  however,  we have  concluded  that  such
factors do not appear to have any  real  consistent significance in explaining
observed  similarities or  differences  among individual  sites.   Therefore,
although more detailed and rigorous analysis and evaluation of the NURP data-
base  may  well provide  additional useful  insight and  understanding  of the
influence of  such other  factors, we do not believe that the  basic findings
and conclusions presented in this report will be significantly altered by the
results of such efforts.   Furthermore,  the value  of  any  such insights as may
be  developed  are likely to  have limited  influence  on general  decisions on
control of  urban runoff.   For  example,  the  finding of  a strong seasonal
effect on  EMC values would have little influence on  a decision  to require
detention basins in all newly developing urban  areas, nor would it be likely
to influence their design.

Urban Runoff Characteristics

Having determined,  as discussed in  the preceding section, that  geographic
location,  land use category, or  other factors appear  to be  of  little utility
in  explaining  overall  site-to-site variability or predicting  the  character-
istics of  unmonitored  sites,   the  best  general  characterization  of  urban
runoff can be obtained by pooling the site data for all sites (other than the
open/non-urban ones).  This  approach is  appropriate, given the need for  a
nationwide  assessment and the general  planning thrust  of  this  report.
Recognizing that there tend  to  be exceptions to  any  generalization, however
realistic and appropriate, in  the absence  of better  information  the  data
given in Table 6-17  are recommended  for planning  level purposes as the  best
description of the characteristics of urban runoff.
         TABLE 6-17.  WATER QUALITY CHARACTERISTICS OF URBAN RUNOFF
Constituent
TSS (mg/1)
BOD (mg/1)
COD (mg/1)
Tot. P (mg/1)
Sol. P (mg/1)
TKN (mg/1)
Tot. Cu (yg/1)
Tot. Pb (ug/1)
Tot. Zn (yg/1)
Event to Event
Variability
in EMC's
(Coef Var)
1-2
0.5-1.0
0.5-1.0
0.5-1.0
0.5-1.0
0.5-1.0
0.5-1.0
0.5-1.0
0.5-1.0
0.5-1.0
Site Median EMC
For
Median
Urban Site
100
9
65
0.33
0.12
1.50
0.68
34
144
160
For
90th Percentile
Urban Site
300
15
140
0.70
0.21
3.30
1.75
93
350
500
                                    6-43

-------
Coliform Bacteria

Coliform bacteria counts  in  urban runoff  were  monitored for  a significant-
number of  storm events by seven of the NURP  projects  at 17 different sites.
Data were  collected at  twelve  of these sites for  more than five  and  up to
20 storm events.  Data  on either  Fecal Coliform  or  both  Fecal  and  Total"
Coliform  counts  are  available  for a  total of  156 separate  storm  events.
Although the data base for bacteria is thus considerably more restricted than
for other pollutants, useful results have been obtained.

Table 6-18 summarizes  the results of an analysis of these  data.   Some  vari-
ability exists  from site  to site,  and data are too limited  to identify any
land use distinctions.   However, results from the  different  sites  and  proj-
ects are  consistent in  showing a  very  dramatic seasonal  effect.   Coliform
counts in  urban runoff  during  the warmer  periods  of  the year  are approxi-
mately 20 times  greater  than those in  urban runoff that occurs during colder
periods.

The  substantial seasonal  differences  which  are  observed do  not correspond
with comparable  variations in urban activities.   This  suggests that seasonal
temperature effects and  sources of coliform unrelated  to those traditionally
associated with human health risk may be significant.

In addition to the summarized data presented here, special study reports pre-
pared by the  Long Island and Baltimore projects address  the  issue  of animal
and other  sources of  coliform bacteria using information derived from  field
monitoring and  the technical  literature.   The  Baltimore NURP  project also
conducted  small scale  site studies which  simulated  washoff by storms  and
identified that  quite  substantial differences in coliform  levels can result
from  the   general  cleanliness  of  an  area,  which they  associate  with  the
socio-economic   strata   of  the  neighborhood.    A  special   study  by  the
Long Island NURP project  examined salmonella counts in urban runoff and in an
adjacent  shellfish area  influenced  by  urban  runoff.  The Knoxville,  TN
project also conducted a special study on  Salmonella.   These project reports
may be obtained through NTIS.

Other issues  related  to  bacteria as a  health  risk were raised  and warrant
further investigation.   A better understanding is  needed of the contribution
of domestic  animals or  such wildlife  as may be  expected in urban areas to
observed coliform levels.

Though high  levels of indicator microorganisms  were  found in  urban runoff,
the analysis  as  well  as  current literature suggests that indicators  such as
fecal coliform may  not  be  useful  in  identifying health  risks from  urban
runoff pollutions.

PRIORITY POLLUTANTS

Background

The NURP priority pollutant monitoring project was conducted  to evaluate the
presence,  concentration,  and potential water quality impacts of priority pol-
lutants in urban  runoff.  A total of 121 urban runoff samples were collected
                                    6-44

-------
         TABLE 6-18.   FECAL COLIFORM CONCENTRATIONS IN URBAN RUNOFF
Project
and
Site
DC1 Burke
Westleigh
Stedwick
MD1 Homeland
Mt Wash
Res Hill
NCI (CBD) 1013
Res 1023
NH1 Pkg Lot
NY1 Carll
Unqua
SD1 Meade
TNI CBD
Rl
R2
SC


All Sites*
Warm Weather
Site
No.
Obs
1
1
2
7
1
1
11
2
20
12
7
9
7
6
6
7
76
Events
11
Median
EMC
(1000/
100 ml)
4.6
46
10
11
130
281
15
23
0.3
24
11
57
54
56
19
12


21
C.V.
_
-
—
1.8
-
-
1.6
—
0.5
0.9
1.6
0.7
1-5
. 2.0
6.2
2.8


0.8
Cold Weather
Site
No.
Obs
1
2
1
_
1
1
8
4
-
15
4
--
7
4
4
4
52
Events
9
Median
EMC
(1000/
100 ml)
0.02
0.35
0.2
_
3.3
330
1.0
2.6
-
1.4
0.9
-
1.0
1.6
0.5
0.9


1
C.V.
_
-
—
_
-
-
0.6
1.1
-
1.5
14
-
1.4
1.9
2.4
1.7


0.7
Notes:
        *  For  general  characterization  of urban  runoff, exclude  the
           following sites:

           -  NH1 - A  small  (0.9A)  Parking Lot;  concentrations  low and
              atypical.

              Four  sites  with  only   one  observation   for   season;
              variability is  too high for any  confidence in representa-
              tiveness of a single value.
                                    6-45

-------
at 61 sites  (two  storm events  per site)  in 20 of the NURP projects that par-
ticipated  in  this phase of  the  program.   These sites were  predominantly in
the  residential,  mixed,  or commercial  land  use  areas  as  defined  earlier. -
Thus, the  results of this effort cannot be attributed to  runoff  from indus-
trial facilities  or complexes.  Furthermore, an especially exhaustive quality
control component, over and  above the standard NURP QA/QC effort,  was imposed
on the priority pollutant  portion of the program,  resulting in the rejection
of nearly  14  percent of the data.  Therefore, there is a  high  level of con-
fidence in the results of this project.

Since only two  samples were collected at each site, no meaningful site sta-
tistic could be calculated.  Therefore the data were pooled for analysis.  In
view of the discussion in the preceding section, however,  this approach seems
to be justified.

A  detailed compilation  of  NURP  priority pollutant  analytical  results  in-
cluding city  and  site  where the  sample  was  collected,  date  of  collection;
discrete or composite sample, pH, and pollutant concentration can be found in
the final report  on the NURP Priority Pollutant Monitoring Program soon to be
issued by the Monitoring and Data Support Division of  the agency.  A summary
of the findings taken from the December 5, 1983 draft of that report follows.

Pollutants Not Included in  NURP.   Asbestos and dioxin  were excluded from the
NURP program.  However,  standard laboratory methods will  reveal the presence
of dioxin  at  concentrations of 1 to 10 yg/1,  and  most  laboratories  did scan
their chromatograms  for the possible  presence of this pollutant.   All such
scans were negative, and on  this basis dioxin  is included as "not detected".

Results Not Valid.   The NURP results for seven priority pollutants cannot be
considered  valid.   Recent  EPA  investigation has  revealed  that  standard
methods are not appropriate  for the measurement of hexachlorocyclopentadiene,
dimethyl  nitrosamine,  diphenyl  nitrosamine,  benzidine,  and 1,2-diphenylhy-
drazine.  Two other  pollutants,  acrolein and  acrylonitrile,  must  be analyzed
within  three days of  sample  collection.   Such  a time  constraint was  an
impractical one for the NURP program.

Pollutants Detected in Runoff

Seventy-seven  priority pollutants  were  detected  in the  NURP urban runoff
samples.   This   group  includes  14 inorganic  and   63  organic   pollutants
(Table 6-19).

Inorganic Pollutants.  As a  group, the toxic metals are by far the most prev-
alent priority pollutant  constituents of  urban runoff.   All  14 inorganics
(13 metals,  plus  cyanides;  asbestos excluded)  were detected,  and  all  but
three  at  frequencies  of  detection greater  than  10 percent.    Most  often
detected  among the  metals  were copper,  lead, and zinc,  all of  which were
found in  at  least 91 percent of the samples.   Their concentrations were also
among the  highest for any pollutant, and reached  a maximum  of  100,  460, and
2,400 yg/1,  respectively.   Other  frequently  detected  inorganics  included
arsenic, chromium, cadmium,  nickel,  and cyanide (Table  6-20).   Twelve of the
thirteen  toxic metals  (antimony  excluded) were also sampled in the  special
                                    6-46

-------
TABLE 6-19.  SUMMARY OF ANALYTICAL CHEMISTRY FINDINGS FROM
             NURP PRIORITY POLLUTANT SAMPLES1

(Includes information received through September 30, 1983)
Pollutant
I. PESTICIDES
1. Acroleln
2. Aldrin
3. o-Hexachlorocyclohexane (a-BHC)
(Alpha)
4. B-Hexachlorocyclohexane (6-BHC)
(Beta)
5. -r-Hexachlorocyclohexane (y-BHC)
(Gamma) (Lindane)
6. 6-Hexachlorocyclohexane (S-BHC)
(Delta)
7. Chlordane
8. ODD
9. DDE
10. DDT
11. Dleldrin
12. a-Endosulfan (Alpha)
13. B-Endosulfan (Beta)
14. Endosulfan sulfate
15. Endrin
16. Endrin aldehyde
17. Heptachlor
18. Heptachlor epoxide
19. Isophorone
20. TCDD (2,3,7,8-tetrachlorodibenzo-
p-dioxin)
21. Toxaphene
II. METALS AND INORGANICS
22. Antimony
23. Arsenic
24. Asbestos
25. Beryllium
26. Cadmium
27. Chromium

28. Copper

29. Cyanides
30. Lead

31. Mercury
32. Nickel
33. Selenium
34. Silver
35. Thallium
36. Zinc

III. PCBs AND RELATED COMPOUNDS
37. PCB-1016 (Aroclor 1016)
38. PCB-1221 (Aroclor 1221)
39. PCB-1232 (Aroclor 1232)
40. PCB-1242 (Aroclor 1242)
41. PCB-1248 (Aroclor 1248)
42. PCB-1254 (Aroclor 1254)
43. PCB-1260 (Aroclor 1260)
44. 2-Chloronaphthalene
Cities Where Detected2

Holding times exceeded
4,7,26
7,8,22,26

7,8

7,8,22,26

7,26

2,8,21,26
Not detected
26
7
26,27
7,26,27
Not detected
Not detected
Not detected
Not detected
7,8,27
7,26
7
Not included in NURP program

Not detected

7,24,26
2,3,7,12,19,20,21,22,26,27
Not included in NURP program
7,12,20,21
1,2,3,7,12,20,21,27
1 ,2 ,7 ,8,12, 17,19 ,20 ,21 ,22 ,26 ,
27,28
1,2,3,4,7,8,12,17,19.20,21,22,
23,26,27,28
4,8,19,22,26,27
1,2,3,4,7,8,12,17,19,20,21,22,
26,28
7,20,28
2,3,7,12,20,21,26,27
7,19,23
3,17,27
7
1,2,3,7,12,17,19,20,21,22,
23,27,28

Not detected
Not detected
Not detected
Not detected
Not detected
Not detected
2
Not detected
Frequency of
Detection3


6
20

5

15

6

17

6
1
6
19




6
2
3




13
52

12
48
58

91

23
94

9
43
11
7
6
94








1

Range of Detected
Concentrations (ug/i)11


0.002T-0.1M
0.0027-0.1M

0. 018-0. 1M

0. 007-0. 1M

0. 004-0. 1M

0.01L-10

0.007-0.027
0.1M
0.007-0.1
0.008-0.2




0.01-0.1M
0.003T-0.1M
10M




2.6-23A
1-50.5

1-49
0.1H-14
1-190

1L-100

2-300
6-460

0.6-1.2
1-182
2-77
0.2M-0.8
1-14
10-2400








0.03

                           6-47

-------
TABLE 6-19.  SUMMARY OF ANALYTICAL CHEMISTRY FINDINGS FROM
         NURP PRIORITY POLLUTANT SAMPLES1  (Cont'd)

(Includes information received through September 30, 1983)
Pollutant
IV. HALOGENATED ALIPHATICS
45. Methane, bromo- (methyl bromide)
46. Methane, chloro- (methyl chloride)
47. Methane, dichloro- (methylene
chloride)
48. Methane, chlorodibromo-
49. Methane, dichlorobromo-
50. Methane, tribromo - (bromoform)
51. Methane, trichloro- (chloroform)
52. Methane, tetrachloro- (carbon
tetrachloride)
53. Methane, trichlorofluoro-5
54. Methane, dichlorodifluoro-
(Freon-12)5
55. Ethane, chloro-
56. Ethane, 1,1-dichloro-
57. Ethane, 1,2-dichloro-
58. Ethane, 1,1,1-trichloro-
59. Ethane, 1,1 ,2-trichloro-
60. Ethane, 1,1 ,2,2-tgtrachloro-
61. Ethane, hexachloro-
62. Ethene, chloro- (vinyl chloride)
63. Ethene, 1 ,1-dichloro-
64. Ethene, 1,2-trans-dichloro-
65. Ethene, trichloro-.
66. Ethene, tetrachloro-
67. Propane, 1,2-dichloro-
68. Propene, 1,3-dichloro-
69. Butadiene, hexachloro-
70. Cyclopentadiene, hexachloro-
Cities Where Detected2

Not detected
Not detected
4,17,22

28
28
28
4,17,20,22,23,27,28
4.28

2,4,24,28
Not detected

'Not detected
4,28
28
4,2,7,22,24
28
4
Not detected
Not detected
28
20,28
2,4,8,24,28
8,17,22,28
28
28
Not detected
Standard methods inappropriate
V. ETHERS
71. Ether, bis(chloromethyl )5 Not detected
72. Ether, bis(2-chloroethyl ) Not detected
73. Ether, bis(2-chloroisopropyl ) Not detected
74. Ether, 2-chloroethyl vinyl Not detected
75. Ether, 4-bromophenyl phenyl Not detected
76. Ether, 4-chlorophenyl phenyl Not detected
77. 8is(2-chloroethoxy) methane Not detected
VI. MONOCYCLIC ARMOMATICS (EXCLUDING PHENOLS, CRESOLS, PHTHALATES)
78. Benzene
79. Benzene, chloro-
80. Benzene, 1,2-dichloro-
81. Benzene, 1,3-dichloro-
82. Benzene, 1,4-dichloro-
83. Benzene, 1,2,4-trichloro-
84. Benzene, hexachloro-
85. Benzene, ethyl -
86. Benzene, nitro-
87. Toluene
88. Toluene, 2,4-dinitro-
89. Toluene, 2,6-dinitro
4,17,27
7,20,26,28
Not detected
Not detected
Not detected
Not detected
Not detected
4,8,17,20,26,28
Not detected
4,17
Not detected
Not detected
Frequency of
Detection3



11

1
1
1
9
3

5



3
1
6
2
2


2
4
6
5
1
2











5
5





6

3


Range of Detected
Concentrations fug/i)1*



5-14. 5A

2
2
1
0.2T-12L
1-2

0.6T-27



1.5A-3
4
1.6-10H
2-3
2G-3


1.5-4
1-3
0.3T-12
1M-43
3
1-2











1-13
1G-10H





1-2

3-9


                            6-48

-------
TABLE 6-19.  SUMMARY OF ANALYTICAL CHEMISTRY FINDINGS FROM
         NURP PRIORITY POLLUTANT SAMPLES1 (Cont'd)

(Includes information received through September 30, 1983)
Pollutant
VII. PHENOLS AND CRESOLS
90. Phenol
91. Phenol , 2-chloro-
92. Phenol, 2,4-dichloro-
93. Phenol , 2,4, 6-trichloro-
94. Phenol, pentachloro-
95. Phenol , 2-nitro-
96. Phenol , 4-nitro-
97. Phenol, 2.4-dinitro-
98. Phenol, 2,4-dimethyl-
99. m-Cresol , p-chloro-
100. o-Cresol 4,6-dinitro-
VIII. PHTHALATE ESTERS
101. Phthalate, dimethyl
102. Phthalate, diethyl
103. Phthalate, di-n-butyl
104. Phthalate, di-n-octyl
105. Phthalate, bis(2-ethylhexyl )
106. Phthalate, butyl benzyl
IX. POLYCYCLIC AROMATIC HYDROCARBONS
107. Acenaphthene
108. Acenaphthylene
109. Anthracene
110. Benzo (a) anthracene
111. Benzo (b) fluoranthene
112. Benzo (k) fluoranthene
113. Benzo (g,h,i) perylene
114. Benzo (a) pyrene
115. Chrysene
116. Dibenzo (a,h) anthracene
117. Fluoranthene
118. Fluorene
119. Indeno (l,2,3-c,d) pyrene
120. Naphthalene
121. Phenanthrene
122. Pyrene
Cities Where Detected2

4,7,26
28
Not detected
Not detected
4,8,19,20,26,27,28
8
4,7,8,20,26,28
Not detected
4,7,8,26
4
Not detected

&
3,4,17,20,21
4,22,24
8,20,26,27,28
4,12,19,22,21,26
2,8,26

Not detected
Not detected
2,17,20,21,26,28
2,21,27
26,27
2,21,27
21
2,21,26,27
2,7,17,21,26,27
21
2,8,12,17,21,26,27,28
28
21
4,24,26,28
2,8,17,20,21,26,27,28
2,3,8,12,17,21,26,27,28
Frequency of
Detection3

14
1


19
1
10

8
1


1
6
6
6
22
6



7
4
5
3
1
6
10
1
16
1
1
9
12
15
Range of Detected
Concentrations (ug/t)1*

1L-13T
2


1T-115
1M
1T-37

1T-10M
1.5A


1L
1-10M
0.5T-11
0.4T-2G
4T-62
1-10M



1-10M
1-10M
1-5
4-14
5
1-10M
0.6T-10M
IT
0.3T-21
1
4
0.8T-2.3
0.3T-10H
0.3T-16
                            6-49

-------
         TABLE 6-19.    SUMMARY  OF ANALYTICAL  CHEMISTRY  FINDINGS FROM
                       NURP PRIORITY  POLLUTANT  SAMPLES1   (Cont'd)


          (Includes information received  through  September  30,  1983)
                   Pollutant
                                               Cities Where Detected2
                                                                      Frequency of
                                                                      Detection3
Range of Detected
Concentrations  (pg/l)*
X.  NITROSAMINES AND OTHER NITROGEN-CONTAINING  COMPOUNDS
    123.  Nltrosamlne, dimethyl (DMN)
    124.  Nltrosamlne, dlphenyl
    125.  Nltrosamlne, d1-n-propyl
    126.  Benz1d1ne
    127.  Benzidlne, 3,3'-d1chloro-
    128.  Hydrazlne, 1,2-dlphenyl-
    129.  Acrylon1tr1le
                                         Standard methods Inappropriate
                                         Standard methods Inappropriate
                                         Not detected
                                         Standard methods Inappropriate
                                         Not detected
                                         Standard methods Inappropriate
                                         Holding times exceeded
Based on 121 sample results  received as. of 9/30/83, adjusted for quality control review.
Cities from which data are available:
 1.  Durham, NH
 2.  Lake Quinsigamond, MA
 3.  Mystic River, MA
 4.  Long Island, NY
 7.  Washington, DC
 8.  Baltimore, MD
12.  Knoxvllle, TN
17.  Glen Ellyn, IL
                                  20.  Little Rock, AR
                                  21.  Kansas City, KS
                                  22.  Denver, CO
                                  23.  Salt Lake City, UT
                                  24.  Rapid City, SO
                                  26.  Fresno, CA
                                  27.  Bellevue, WA
                                  28.  Eugene, OR
   19.  Austin, TX

   Numbering of cities conforms to NURP  convention.

Percentages rounded to nearest whole number.
Some reported concentrations  are qualified by STORET quality control  remark codes, to wit:  A = Value reported is the
mean of two or more determinations; G =  Value reported is  the maximum of two or more determinations; L = Actual value
1s known to be greater than value given; M » Presence of material  verified but not quantified; T « Value reported is
less than criteria of detection.  One value in this column indicates  one positive observation or that all  observations
were equal.
No longer included as a priority pollutant.
                                                   6-50

-------
         TABLE 6-20.  MOST FREQUENTLY DETECTED PRIORITY POLLUTANTS
                        IN NURP URBAN RUNOFF SAMPLES1
   Priority Pollutants Detected in 75 Percent or More of the NURP Samples

         Inorganics                            Organic s

    30.  Lead (94%)               None
    36.  Zinc (94%)
    28.  Copper (91%)

Priority Pollutants Detected in 50 percent to 74 percent of the NURP Samples

         Inorganics                            Organics

    27.  Chrominum (58%)          None
    23.  Arsenic (52%)

Priority Pollutants Detected in 20 percent to 49 percent of the NURP Samples

         Inorganics                            Organics

    26.  Cadmium (48%)      105.  Bis (2-ethylhexyl) phthalate  (22%)
    32.  Nickel (43%)         3.  a-Hexachlorocyclohexane  (20%)
    29.  Cyanides  (23%)

Priority Pollutants Detected in. 10 percent to 19 percent of the NURP Samples

         Inorganics                            Organics  .

    22.  Antimony  (13%)      12.  a-Endosulfan  (19%)
    25.  Beryllium (12%)     94.  Pentachlorophenol  (19%)
    33.  Selenium  (11%)       7.  Chlordane  (17%)
                              5.  Y~Hexacfrl°rocycl°hexane  (Lindane)  (15%)
                            122.  Pyrene  (15%)
                             90.  Phenol  (14%)
                            121.  Phenanthrene  (12%)
                             47.  Dichlorome thane  (methylene chloride)  (11%)
                             96.  4-Nitrophenol  (10%)
                            115.  Chrysene (10%)
                            117.  Fluoranthene  (16%)
       Based on 121 sample results received as of September  30,  1983, adjusted
       for quality control review.  Does not include special metals  samples.
                                    6-51

-------
metals  project  in order  to  determine  the  relationships among  dissolved,
total,  and  total recoverable  concentrations.   The discussion and  result of
this separate effort are in a  subsequent section of this chapter.

A comparison  of individual urban  runoff sample concentrations  undiluted by
stream  flow (i.e., end of  pipe concentrations) with EPA  water  quality cri-
teria  and  drinking  water  standards  reveals numerous  exceedances of  these
levels, as  shown in Table 6-21.  Freshwater acute  criteria were exceeded by
copper concentrations in 47 percent of the samples and by lead in 23 percent.
Freshwater  chronic exceedances were  common for  lead  (94 percent),  copper
(82 percent), zinc  (77 percent), and cadmium (48 percent).  One organ oleptic
(taste and  odor) criteria exceedance was observed.  Regarding human toxicity,
the  most  significant  pollutant was  lead.    Lead  concentrations  violated
drinking water criteria in 73 percent of the observations.

Whenever an exceedance  is noted above, it  does  not necessarily imply that an
actual  violation of  criteria  did or  will take  place  in receiving  waters.
Rather, the enumeration of exceedances  is  used as a screening  procedure to
make a  preliminary identification of those pollutants  for which their pres-
ence in urban runoff requires highest priority for further  evaluation.  Ex-
ceedances of  freshwater chronic criteria  levels may not persist  for  a full
24-hour period,  for  example.    However,  many  small  urban streams  probably
carry only  slightly diluted runoff  following  storms,  and acute criteria or
other exceedances may in fact be real in such circumstances.

Among the inorganics, the most frequently  detected pollutants are also those
which are found  at the highest  concentrations,  which most frequently exceed
water   quality   criteria   and  which  are   the  most   geographically  well-
distributed.  One  additional  observation can be made concerning the samples
from Washington, D.C.   These  samples  accounted for  a  preponderance  of the
detections  of many  of the  less frequently  detected  inorganics,  including
antimony, beryllium, mercury, nickel, selenium,  and thallium.   No sampling or
analytical  irregularities have been identified which explain this result.

Organic Pollutants.   In general, the  organic pollutants  were  detected less
frequently  and  at  lower  concentrations  than  the  inorganic  pollutants.
Sixty-three  of  a  possible 106 organics  were  detected.   The most  commonly
found organic  was  the plasticizer bis  (2-ethylhexyl)  phthalate (22 percent)
followed by the pesticide ot-hexachlorocyclohexane  (a-BHC)  (20 percent) .  An
additional  11 organic pollutants  were  reported  with  detection frequencies
between 10  and  20 percent; 3  pesticides,  3 phenols,  4  polycyclic aromatics,
and a single haloginated aliphatic (Table 6-20).

Criteria  exceedances  were less  frequently observed among the  organics than
the  inorganics.   One  unusually  high  pentachlorophenol  concentration  of
115 ug/1  resulted  in the only exceedance  of the  organoleptic  criteria  (Ta-
ble 6-21).  This observation and one  for  the  chlordane  exceeded  the  fresh-
water acute criteria.   Freshwater  chronic  criteria exceedances were observed
for pentochlorophenol,  bis  (2-ethylhexyl)  phthalate, y-hexachlorocyclohexane
(Lindane),  a-endosulfan,  and  chlordane.   All other  organic  exceedances were
in  the  human  carcinogen  category and were most  serious for  a-hexachloro-
cyclohexane  (a-BHC),  y-hexachlorocyclohexane (y-BHC or Lindane),  chlordane,
phenanthrene, pyrene, and chrysene.
                                    6-52

-------
       TABLE  6-21.    SUMMARY OF  WATER QUALITY  CRITERIA  EXCEEDANCES  FOR
          POLLUTANTS  DETECTED  IN AT  LEAST  10  PERCENT  OF NURP  SAMPLES:
                        PERCENTAGE  OF SAMPLES  IN WHICH  POLLUTANT
                               CONCENTRATIONS  EXCEED  CRITERIA1
Pollutant
I. PESTICIDES
3. a-Hexachlorocyclohexane
5. Y-Hexachlorocyclohexane (Llndane)
7. Chlordane
12. a-Endosulfan
II. METALS AND INORGANICS
22. Antimony
23. Arsenic
25. Beryllium
26. Cadmium5
27. Chromium5'6
28. Copper5
29. Cyanides
30. Lead5
32. Nickel5
33. Selenium
36. Zinc5
IV. HALOGENATED ALIPHATICS
47. Methane, dlchloro-
VII. PHENOLS AND CRESOLS
90. Phenol
94. Phenol, pentachloro-
96. Phenol, 4-nitro-
VIII. PHTHALATE ESTERS
105. Phthalate, bis(2-ethylhexy1)
IX. POLYCVCLIC AROMATIC HYDROCARBONS
115. Chrysene
117. Fluoranthene
121. Phenanthrene
122. Pyrene
Frequency of
Detection (%)

20
15
17
19

13
52
12
48
58
91
23
94
43
11
94

11

14
19
10

22

10
16
12
15
Detections/
Samples2

21/106
15/100
7/42
9/49

14/106
45/87
11/94
44/91
47/81
79/87
16/71
75/80
39/91
10/88
88/94

3/28

13/91
21/111
11/107

15/69

11/109
17/109
13/110
16/110
Criteria Exceedances (X)3
None





X













X

X




X


FA


2





8

47
3
23


14




!*•








FC

8
17
10



6*
48
1*
82
22
94
5
5
77




11*


22*





OL




















1








HH








1


4
73
21
10














HC*

8,18,20
0,10,15
17,17,17



52,52,52-
12,12,12









0,0,11







10,10,10

12,12,12
15,15,15
DU






1

1
1


73

10














*  Indicates FTA or FTC value  substituted where FA or FC  criterion not available (see below).
1  Based on 121 sample results received as of September 30, 1983, adjusted for quality control review.
2  Number of times detected/number of acceptable samples.
3  FA • Freshwater ambient 24-hour instantaneous maximum criterion ("acute"  criterion).
   FC = Freshwater ambient 24-hour average criterion ("chronic" criterion).
   FTA « Lowest reported freshwater acute toxic concentration.   (Used only when FA is not available.)
   FTC » Lowest reported freshwater chronic toxic concentration.  (Used only  when FC is not available.)
   OL • Taste and odor (organoleptic) criterion.
   HH = Non-Carcinogenic human health criterion for ingestion  of contaminated water and organisms.
   HC - Protection of human health from carcinogenic effects for ingestion of contaminated water and organisms.
   DW = Primary drinking water criterion.
u  Entries in this column indicate exceedances of the human carcinogen value  at the 10"5, 10" ,  and 10"   risk level, respectively.  The
   numbers are cumulative, i.e., all 10'5 exceedances are included in 10"6 exceedances, and all  10"  exceedances are included in 10"
   exceedances.
5  Where hardness dependent, hardness of 100 mg/1 CaCO^ equivalent assumed.
6  Different criteria are written for the trivalent and hexavalent forms of chromium.  For purposes of this analysis, all chromium  is
   assumed to be in the less toxic trivalent form.
                                                     6-53

-------
An additional  50 organic  pollutants were  found in one to nine percent of the
samples.  These frequencies of detection  are  low,  and the pollutant is noted
in Table 6-22.

Among the PCB  group,  there was only a  single, detection of one PCB type among
all the  samples.   Approximately  two-thirds  of the halogenated aliphatic com-"
pounds were detected.  Among those cities reporting these compounds, the city
of Eugene,  Oregon, figured prominently.  For  example,  eight pollutants from
this group  were  found in Eugene only.   None of the pollutants in the ethers
group were detected.

Monocyclic  aromatics were  rarely detected  in the  samples.   However,  many
reported detections of benzene and toluene, two commonly reported pollutants,
had to be withdrawn due to contamination problems.

Of the 11 phenolics,  four have not been reported in urban runoff, while three
have been  observed  only  once.   The  remaining four  have been  found fairly
frequently  but at  low  concentrations.   Exceedances  of criteria  were noted
only for pentachlorophenol.

All the  phthalate esters were  detected at  least  once in the NURP program,
with bis  (2-ethylhexyl)  found most  frequently.   Several times  the reported
concentration  exceeded the  lowest  observed  freshwater acute  toxic concentra-
tion for this  pollutant.  Given  the  significant blank contamination problems
with  the  phthalates,  however,   these  findings   must be   interpreted  with
caution.

Only two of  the  polycyclic aromatic  hydrocarbons were  not  detected  in  at
least one sample.   Crysene, phenanthrene, pyrene,  and fluoranthene were each
found at least 10 percent of the time.   All  the  observed concentrations for
the first three of these  pollutants  exceeded the  criteria for the protection
of human health from carcinogenic effects  (there  are no such  criteria for
fluoranthene).  Results for the polycyclic aromatics were generally free from
quality control problems.

There were  no detections of nitrosamines or  other nitrogen-containing com-
pounds.  Due  to methodological  and  holding time  problems,  however,  results
for only two compounds can be used.   Moreover,  for one  of  these compounds,
3,3-dichlorobenzidine, performance evaluation results were  unacceptable  in
several cases.

Pollutants Not Detected In Urban Runoff

Some 43 priority pollutants were not detected in  any  acceptable runoff sam-
ples (Table 6-22).  All of these pollutants are organics.  This group of sub-
stances  should be  considered  to  pose a minimal  threat  to the  quality  of
surface waters from runoff contamination.

While the priority pollutants which  were not  detected  are of less immediate
concern  than  those pollutants  found often, they cannot safely be eliminated
from all future  consideration.   Many  of these  pollutants   have  associated
water  quality  criteria which are below the limits of  detection of  routine
                                    6-54

-------
           TABLE 6-22.  INFREQUENTLY DETECTED ORGANIC PRIORITY
                 POLLUTANTS IN NURP URBAN RUNOFF SAMPLES1


Priority Pollutants Detected in 1 percent to 9 percent  of  the  NURP Samples

     51.  Trichloromethane  (9%)
    120.  Naphthalene  (9%)
     98.  2,4-Dimethyl phenol  (8%)
    109.  Anthracene  (7%)
      2.  Aldrin (6%)
      6.  5-Hexachlorocyclohexahe  (6%)
      9.  DDE (6%)
     11.  Dieldrin  (6%)
     17.  Heptachlor  (6%)
     58.  1,1,1-Trichloroethane  (6%)
     65.  Trichloroethene  (6%)
     85.  Ethylbenzene  (6%)
    102.  Diethyl phthalate  (6%)
    103.  Di-n-butyl phthalate  (6%)
    104.  Di-n-octyl phthalate  (6%)
    106.  Butyl benzyl phthalate  (6%)*
    114.  Benzo(a)pyrene  (6%)
      4.  8-Hexachlorocyclohexane  (5%)
     53.  Trichlorofluoromethane  (5%)2
     66.  Tetrachloroethene  (5%)
     78.  Benzene  (5%)
     79.  Chlorobenzene  (5%)
    111.  Benzo(b)fluoranthene  (5%)*
     64.  1,2-trans-dichloroethene  (4%)
    110.  Benzo(a)anthracene  (4%)
     19.  Isophorone  (3%)
     52.  Tetrachloromethane  (carbon tetrachloride)  (3%)
     56.  1,1-Dichloroethane  (3%)
     87.  Toluene  (3%)
    112.  Benzo(k)fluoranthene  (3%)
     18.  Heptachlor epoxide  (2%)*
     59.  1,1,2-Trichloroethane  (2%)*
     60.  1,1,2,2-Tetrachloroethane  (2%)*
     63.  1,1-Dichloroethene  (2%)
     68.  1,3-Dichloropropene  (2%)*
    113.  Benzo(g,h,i)perylene  (2%)
     10.  DDT (1%)*
     43.  PCB-1260  (1%)*
     48.  Chlorodibromomethane  (1%)*
     49.  Dichlorobromomethane  (1%)*
     50.  Tribromomethane  (bromoform)  (1%)*
     57.  1,2-Dichloroethane  (1%)*
     67.  1,2-Dichloropropane  (1%)*
     91.  2-Chlorophenol  (1%)*
     95.  2-Nitrophenol  (1%)*
     99.  p-Chloro-m-creosol  (1%)*
    101.  Dimethyl phthalate  (1%)*
    116.  Dibenzo(a,h)anthracene  (1%)*
    118.  Fluorene  (1%)*
    119.  Indeno(l,2,3-cd)pyrene  (1%)*

                                   6-55

-------
       TABLE 6-22.  INFREQUENTLY DETECTED ORGANIC PRIORITY
        POLLUTANTS IN NURP URBAN RUNOFF SAMPLES1 (Cont'd)
         Priority Pollutants Not Detected in NURP Samples

  8.  ODD
 13.  B-Endosulfan
 14.  Endosulfan sulfate
 15.  Endrin
 16.  Endrin aldehyde
 21.  Toxaphene
 37.  PCB-1016
 38.  PCB-1221
 39.  PCP-1232
 40.  PCB-1242
 41.  PCB-1248
 42.  PCB-1254
 44.  2-Chloronaphthalene
 45.  Bromomethane (methyl bromide)
 46.  Chloromethane (methyl chloride)
 54.  Dichlorodifluoromethane (Freon-12)2
 55.  Chloroethane
 61.  Hexachloroethane
 62.  Chloroethene (vinyl chloride)
 69.  Hexachlorobutadiene
 71.  Bis(chloromethyl) ether2
 72.  Bis(chloroethyl) ether
 73.  Bis(chloroisopropyl) ether
 74.  2-Chloroethyl vinyl ether
 75.  4-Bromophenyl phenyl ether
 76.  4-Chlorophenyl phenyl ether
 77.  Bis(2-chloroethoxy) methane
 80.  1,2-Dichlorobenzene
 81.  1,3-Dichlorobenzene
 82.  1,4-Dichlorobenzene
 83.  1,2,4-Trichlorobenzene
 84.  Hexachlorobenzene
 86.  Nitrobenzene
 88.  2,4-Dinitrotoluene
 89.  2,6-Dinitrotoluene
 92.  2,4-Dichlorophenol
 93.  2,4,6-Trichlorophenol
 97.  2,4-Dinitrophenol
100.  4,6-Dinitro-o-cresol
107.  Acenaphthene
108.  Acenaphthylene
125.  Di-n-propyl nitrosamine
127.  3,3'-Dichlorobenzidine
                               6-56

-------
            TABLE 6-22.  INFREQUENTLY DETECTED ORGANIC PRIORITY
             POLLUTANTS IN NURP URBAN RUNOFF SAMPLES1 (Cont'd)
    Priority Pollutants Not Analyzed for or Withdrawn for Methodological
                     Reasons or Holding Time Violations

       1.  Acrolein
      20.  TCDD (Dioxin)
      24.  Asbestos
      70.  Hexachlorocyclopentadiene
     123.  Dimethyl nitrosamine (DMN)
     124.  Diphenyl nitrosamine
     126.  Benzidine
     128.  1,2-Diphenyl hydrazine
     129.  Acrylonitrile

*  Detected in only one or two samples.

1  Based on  121 sample results received  as of  September  30,  1983,  adjusted
   for quality control review.

2  No longer on the priority pollutant list.


analytical methods.  Some  of  these  substances may in  fact have been present
in the  NURP  samples.  Four priority pollutants not detected  in runoff were
found in street dust  sweepings from  Bellevue,  Washington,  suggesting that
further  urban  runoff samplings can  be expected  to detect  more priority pol-
lutants.  More  sensitive  analytical methodologies must be  used and dilution
effects considered before it can be  said with assurance that these pollutants
are not  found  in urban stcirmwater runoff at  levels  which, without dilution,
pose a threat to human health or aquatic life.

DDD, chloromethane, 1,2-dichlorobenzene, and 2,4-dichlorophenol were detected
in runoff samples  at least once,  but these observations had to be withdrawn
for quality control  reasons.   Therefore,  among  the  not  detected pollutants,
these four can  be  considered to have a slightly elevated  possibility of ac-
tually being present in the runoff samples.

RUNOFF-RAINFALL RELATIONSHIPS

A runoff coefficient (Rv), defined  as the  ratio  of runoff  volume to rainfall
volume,  has been determined for each of  the monitored storm events.   As with
the EMCs, the runoff coefficient values at  a  particular  site are, with rela-
tively  few  exceptions,  well  characterized  by a  lognormal  distribution.
Table 6-23 summarizes the statistical properties of Rv's at the loading sites
in the data base.

Figure 6-19 illustrates the relationship between percent impervious  area and
the median runoff coefficient for the site.  Sites which monitored fewer than
5 storms are  excluded.  The upper plot (a) groups the results from 16 of the
                                    6-57

-------
                                    TABLE 6-23.  RUNOFF COEFFICIENTS  FOR LAND USE SITES
I
Ul
00
Residential

SUe
1
2
3
4
5
6
7
a
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
C01 Big Dry Cr
C01 Cherry
C01 116/claude
DC1 Duflef
PCI Lakeridge
PCI Stratton
Fit Young Apt
111 John N
KS1 Overton
MA2 Hemlock
HO] Bo! ton Hill
HOI Homeland
KOI Nt Nash
ND1 Res Hill
NY1 Carll's R.
NV3 Cranston
NY3 E. Roch.
TX1 Rollingxood
WAI Surrey
Ull Burbank
Wll Hastings
TX1 Hart
Ull Lincoln
TNI R2
OC1 Uestleigh
KS1 1C - 92nd
III John S.
TNI RI
UA1 Lake Hills
IL1 Hattis S.
FL1 Charter H.
OC1 Fa i ridge
C01 Asbury
IL2 Comb Inlets
MAI Locust
NCI 11023
MAI Jordan
DC1 StedHlck
Land
Use
I
Res
100
100
100
100
100
100
100
ino
100
100
100
100
100
100
100
100
100
100
100
100
100
99
97
96
93
9?
91
91
91
90
89
88
86
85
85
84
79
78

No.
of
Events
16
15
24
57
48
31
12
87
13
6
19
15
20
13
29
13
9
9
119
44
33
14
19
11
39
14
79
9
121
89
11
44
18
29
6
83
9
45
Drain-
age
Area
(Acs)
33
57
167
12
68
9
9
54
58
50
14
23
17
10
73
166
346
60
95
63
33
•378
36
89
41
63
39
69
102
28
42
19
127
524
154
324
110
?7
Popu-
lation
Density
(Pers/Acre)
19
24
14
2
21
2
-
IB
8
5
30
9
12
55
13
5
18
3
9
15
17
9
18
4
3

18
11
12
22
.

9
8
11
6
10
15

J
Imperv
41
38
24
19
27
22
-
19
38
16
51
29
29
76
20
22
38
21
29
50
51
40
57
13
21
37
18
33
37
37
16
34
22
17
16
27
21
34
Runoff Coef
(Rv)
Median
.32
.Ifi
.15
.06
.18
.37
.85
.15
.08
.36
.44
.34
.14
.49
.21
.16
.20
.02
.18
.27
.27
.09
.38
.04
.1?
.05
. 17
.03
.20
.33
.15
.36
.19
.17
.21
.10
.22
.20
Coef
Var
.47
-.45
.40
?.47
1.32
.98
.95
.77
.81
.66
.72
.75
1.25
.54
..61
.33
.42
.74
.56
.92
.37
.95
.55
.67
1.15
1.08
.54
.98
.52
.66
4.65
1.32
.97
.48
.93
.67
.65
1.07























Mixed

Site
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
KS1 Noland
MP1 Hanpden
IL1 Mattis N
Mil Uaverly
TNI SC
Ull Uood Ctr
MAI Rt 9
MAI Convent
Mil Grand R Ot
FL1 Wilder
M13 Pitt AA-S
NY2 Cedar
FL1 Jesuit
HA1 Anna
HI3 Pitt AA-N
Mil Grace N
MI3 Swift Run
SOI Heade
CA1 Knox
C01 North Ave
Land
Use
1
-
-
-

-
-
-
-
-
-

-
-
-
-
-
-
-
-
-
No.
of'
Events
15
22
82
35
12
44
7
8
23
15
6
32
15
6
6
23
5
16
42
33
Drain-
age
Area
(Acs)
36
17
17
30
187
45
338
100
453
194
2001
76
30
601
2871
164
1207
2030
1690
69
Popu-
lation
Dens 1 ty
(Pers/Acre)
3
40
3
11
3
12
7
1
5
-
2
-
-
9
7
5
2
-
12
9

t
Inperv
68
72
58
68
43
81
23
33
38
-
21
5
13
12
26
28
4
-
-
SO
Runoff Coef
(Rv)
Median
.09
.29
.64
.36
.12
.76
.20
.50
.11
.41
.19
.08
.32
.17
.10
.11
.21
.10
.20
.24
Coef
Var
1.04
.53
.52
.25
.48
.42
.99
.98
.50
1.12
.46
1.05
1.03
6.64
.43
.41
.38
.57
.77
.59
















Conmercial

Site

1
2
3
4
5
6
7
8
9
10
C01 Villa Italia
NCI 1013 (C80)
NV3 Southgate
Wll Post Office
Ull Rustler
NH1 Pkg Lot
TNI CBO
KS1 1C Metcalf
FL1 Nonna Park
Ull State Fair
Land
Use
t
Com
100
100
100
100
100
100
100
96
91
74
No
of
Events
23
112
13
54
39
34
14
22
12
27
Drain-
age
Area
(Acs)
74
23
179
12
12
1
26
58
47
29
Popu-
lation
Density
(Pers/Acre)
0
0
2
0
0
0
0
-
-
10

t
Imperv
91
69
21
100
100
90
99
97
45
77
Runoff Coef
(Rv)
Median
.93
.79
.20
.90
.79
.66
.21
.46
.48
.62
Coef
Var
.45
.49
.28
.19
.19
.50
.41
.55
.86
.24

Urban Open and Nonurban
Site
1
2
3
4
5
6
7
8
CA1 Seaviex
C01 Rooney Gulch
NY3 Thornpll
NY2 English Or
m? Uest Rr
NY3 Thomas f.r
MI3 Traver Cr
NY2 Sheriff Oock
Land
Use
I
Open
100
ion
100
9R
97
91
90
80
No.
of
Events
38
7
13
?9
30
13
5
33
Drain-
age
Area
(Acs)
633
405
28,416
5,248
5,338
17,728
2.303
552
Popu-
lation
Density
(Pers/Acre)
-
0
-
-

1

-
%
Imperv
1
1
4
1
1
11
6
7
Runoff Coef
(Rv)
Median
.03
.04
.06
.OR
.07
.04
.11
.05
Coef
Var
5.86
6.04
.93
4.03
1.44
.56
l.Jlta
Ji
Industrial

Site
1
2
3
4
MA2 Addison
Mil Indus Drain
KS1 Lenaxa
Mil Grace S.
Land
Ose
>
Ind
100
100
56
52

of
Events
6
18
19
20
Drain-
age
Area
(Acs)
18
63
72
75
Popu-
lation
Density
(Pers/Acre)
0
0
-
5

I
Imperv
69
64
44
39
Runoff Coef
(Rv)
Median
.58
.10
.54
.11
Coef
Var
.53
.71
.37
.43

-------
        UJ
        i
        UJ
        a
        u
        it
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0.7
0.6
0.5
0.4
0.3
0.2
0.1
n







o
o
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1









             0
                           % IMPERVIOUS
                      (a)  16 Projects
I.U
0.9
0.8
£ 0.7
^
| 0.6
|o.5
u
| 0.4
i 0.3
0.2
0.1
n



















o









,









. *




.



O

















•


* a

























0

o


            0  10  20  30   40   50  60  70   80   90  100
                          % IMPERVIOUS

            (b)   4 Projects (KS1, Mil, TNI,  TX1)
Figure 6-19.   Relationship Between  Percent Impervious Area
                and Median Runoff Coefficient
                            6-59

-------
20 projects  investigated.   The  lower  plot  (b) groups  results from  the re-
maining four projects  (KS1, Mil, TNI, TX1).  The reason for the difference is
unexplained.   However,  the separate grouping  is  based on the  fact that the
relationship for  these  sites  is  internally consistent and significantly dif-
ferent than the bulk of the project results.

Figure 6-20  illustrates the  same impervious  area/runoff coefficient  rela-
tionship, but  shows the 90 percent confidence limits for median Rv's.

POLLUTANT LOADS

Although the EMC  median concentration  values are  appropriate for many appli-
cations  (e.g.,  assessing water quality impacts in  rivers  and streams), when
cumulative  effects such as  water quality  impacts  in lakes  and  comparisons
with other sources on  a long-term basis  (e.g.,  annual or seasonal loads) are
to be examined, the EMC mean concentration values should be used.  Taking the
EMC median and coefficient of variation values given  in  Table 6-17,  we have
converted them into mean  values  using the  relationship  given in Chapter 5.
These EMC mean concentrations and the values used  in  the  load comparison to
follow are listed in Table 6-24.

The range  shown for site  mean concentrations  for  both  the  median  and 90th
percentile urban  sites  reflects  the  difference  in means  depending on whether
the higher or  lower value of coefficient of variation listed  in Table 6-17 is
used to  describe  event-to-event  variability of  EMC's  at urban  sites.   The
range  in  values  shown  for use  in the load comparisons  below reflects the
median and 90th percentile site mean concentrations, using the average of the
range caused by coefficient of variation effects.
            TABLE 6-24.  EMC MEAN VALUES USED IN LOAD COMPARISON

Constituent

TSS (mg/1)
BOD (mg/1)
COD (mg/1)
Tot. P (mg/1)
Sol. P (mg/1)
TKN (mg/1)
N°2+3~N (mg/1)
Tot. cu (ug/D
Tot. Pb (ug/D
Tot. Zn (ug/1)
Site Mean EMC
Median
Urban Site
141 - 224
10 - 13
73 - 92
0.37 - 0.47
0.13 - 0.17
1.68 - 2.12
0.76 - 0.96
38 - 48
161 - 204
179 - 226
90th Percentile
Urban Site
424 - 671
17 - 21
157 - 198
0.78 - 0.99
0.23 - 0.30
3.69 - 4.67
1.96 - 2.47
104 - 132
391 - 495
559 - 707
Values Used in
Load Comparison
180 - 548
12 - 19
82 - 178
0.42 - 0.88
0.15 - 0.28
1.90 - 4.18
0.86 - 2.21
43 - 118
182 - 443
202 - 633
                                    6-60

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       1.0
       0.9
       0.8
       0.7
    Sj  0.6
    u

    S  0.5
    ft  0.4
       0.3
       0.2
       0.1
           I'l
         0   10   20   30   40   50  60  70   80   90   100
                         % IMPERVIOUS

                     (a)   16 Projects
        1.0
        0.9
        0.8
        0.7
        0.6
        0.5
     tt 0.4
        0.3
        0.2
        0.1
          0   10   20  30  40  50   60   70   80   90  100
                          % IMPERVIOUS

         (b)   4 Projects  (KS1, Mil, TNI,  TK1)
Figure 6-20.   90 Percent Confidence Limits for Median
                   Runoff Coefficients
                           6-61

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It is a straightforward procedure to calculate mean annual load estimates  for
urban runoff constituents on a  Kg/Ha basis by assigning  appropriate  rainfall
and  runoff  coefficient values  and selecting  EMC  mean  concentration  values
from Table 6-24.  In and of themselves, however,  such estimates seem  to be of
little utility.   Therefore, it was  decided  to do  a comparison of the mean
annual loads from urban runoff with those of  a "well run" secondary treatment
plant.  We chose to use TSS = 25 mg/1,  BOD =  15 mg/1, and Tot.  P = 8  mg/1  for
the  effluents  from such plants for  the  purposes  of this order  of magnitude
comparison.  For  a meaningful  comparison  for a specific  situation,  locally
appropriate values should be used.   Based upon Table 6-24,  the corresponding
urban runoff mean concentrations used were TSS = 180 mg/1, BOD  = 12 mg/1,  and
Total P = 0.4 mg/1  as  typical  and  TSS =  548 ug/1,  BOD =   19  mg/1,   and
Tot. P = 0.88 mg/1 as a "worst case" for comparison purposes.

The value of 0.35  was selected as a typical mean runoff  coefficient.  It is
the  median of  the NURP  mean  runoff  coefficient  database for the  twenty
projects discussed earlier; their  average  is 0.42,  but we believe that this
number is overly weighted by the disproportionate number  of highly impervious
sites in the database.  Assuming an  average  population density of 10 persons
per  acre   (the  average of  the NURP  sites)   and  a  mean  annual rainfall of
40 inches per  year,  urban  runoff  averages  104 gallons  per  day per  capita.
This  is  also a reasonable  estimate of  sewage generation in an urban area.
Therefore, as  a first  cut, the  ratio of mean  pollutant concentrations of
urban runoff and POTW effluents will also be  the ratio of their annual loads.
Thus, we have;
           TSS =    - ~ 7 ; BOD = r  ~  0.8 ;  Tot.  P =     =  0.05
                  25              15                    o

using typical urban runoff values, and;
using the "worst case" values.  These numbers  suggest  that  annual  loads  from
urban runoff are approximately one order of magnitude  higher  than  those  from
a well run secondary treatment plant for TSS,  the same  order of magnitude for
BOD, and an order of magnitude less for Tot.  P.

If the hypothetical  urban area just described were  to go  to  advanced waste
treatment and achieve an effluent quality of  TSS = 10 mg/1,  BOD = 5 mg/1, and
Total P = 1 mg/1  and no  urban runoff  controls  were  instituted,  the  mean
annual load reductions to the receiving water would be:


     TSS -180125 *7% -• BOD - ii^Ts = 37% ; Tot- p =o^ri- *83%

for. our typical case, and;


     TSS = 548 + 25 * 3% '• B°D " iK-T? = 29% ' T0t' P = 0888 I 8  * ?9%
                                    6-62

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for  our  "worst case."   On the  other hand,  if urban  runoff  controls  that
reduced TSS by 90 percent, BOD by 60 percent,  and  Total P by 50 percent were
instituted, (typical results from a well-designed  detention basin) ,  the mean
annual load reductions to the receiving water would be :
for our typical case, and;

   mc,_   548 - 55   0_   „„   19-8    ,_„_   _ ^ .  „   0.88 - 0.44
   TSS = 548 + 25 = 86% ;  B°D = TTTTs * 32% ;  T°tal P =  0.58+-8   * 5%


Thus, if these pollutants are  causing  receiving  water quality problems,  con-
sideration  of  urban runoff  control appears  warranted  for  TSS,  both  urban
runoff control and AWT might  be  considered for BOD,  and only AWT  would be
effective for Total P.

The foregoing should be viewed as illustrative of a preliminary screening for
trade-off  studies that  can  be  performed  using  appropriate  values  for  a
specific urban area, rather  than  as  description  of any particular real-world
case.  They are, however, believed  useful in providing order  of magnitude
comparisons.  Local values for  annual  rainfall,  runoff coefficient,  or point
source characteristics that are different than those used in the illustration
will of course change  the results shown; although in  most cases the changes
would  not  be  expected  to  cause  a  significant  change  in  the  general
relationship.                 •

As a final perspective on urban runoff loads, Table 6-25 presents an estimate
of annual  urban  runoff loads,  expressed as Kg/Ha/year,  for  comparison  with
other data  summaries of  nonpoint source loads  which state results  in  this
manner.   Load  computations  are based  on site mean pollutant concentrations
for the median urban site and on the specified values for annual rainfall and
runoff coefficient.   Typical values  for mean runoff coefficient  (based on
NURP data)  have been assigned for residential land use (Rv = 0.3), commercial
land use (Rv = 0.8), and for an aggregate urban area which is assumed to have
representative fractions  of  the  total  area in  residential,  commercial,  and
open uses (Rv = 0.35).

Several useful observations  can  be  made.  The  annual load  estimates  which
results  are comparable  to  values  and  ranges  reported  in  the  literature.
Although the  findings  presented earlier  in this chapter indicated  that  the
land use category does not  have  a  significant  influence on  site concentra-
tions of  pollutants , on  a  unit  area  basis total  pollutant loads  are  sig-
nificantly  higher for  commercial  areas because  of  the higher degree  of
imperviousness typical of such areas.   For broad urban  areas,  however,  the
relatively  small  fraction of land with this use  considerably  mitigates  such
an effect.

Finally, the annual loads shown by Table 6-25 have been computed on the basis
of a 40 inch  annual rainfall volume.  For urban areas in regions with higher
                                    6-63

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              TABLE 6-25.  ANNUAL URBAN RUNOFF LOADS KG/HA/YEAR
Constituent
Assumed Rv
TSS
BOD
COD
Total P
Sol. P
TKN
N02+3-N
Tot. Cu
Tot. Pb
Tot. Zn
Site Mean
Con.mg/1

180
12
82
0.42
0.15
1.90
0.86
0.043
0.182
0.202
Residential
0.3
550
36
250
1.3
0.5
5.8
2.6
0.13
0.55
0.62
Commercial
0.8
1460
98
666
3.4
1.2
15.4
7.0
0.35
1.48
1.64
All Urban
0.35
640
43
292
1.5
0.5
6.6
3.6
0.15
0.65
0.72
    NOTE.  Assumes 40 inches/year rainfall as a long-term average.
or  lower  rainfall,  these  load  estimates must  be  adjusted.   The  results
presented  earlier  suggest that pollutant concentrations are not sensitive to
runoff volume; however, total  loads  (the product of concentration and volume)
are strongly  influenced by the volume of runoff.   For estimates using equiv-
alent site conditions  (Rv), loads for areas with, other rainfall amounts are
obtained by factoring  by the  ratio  of local rainfall  volume  to the 40 inch
volume  used for the  table.   Planners who believe  that the  average  annual
runoff  coefficients  in their  local  areas  are substantially  different from
those used in the table can make similar adjustments.
                                    6-64

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                                  CHAPTER 7
               RECEIVING WATER QUALITY EFFECTS OF URBAN RUNOFF
INTRODUCTION

The effects of urban  runoff  on receiving water quality are  very site speci-
fic.  They  depend on the  type,  size, and hydrology  of the water  body,  the
designated beneficial use and the pollutants which affect that use, the urban
runoff (URO)  quality  characteristics,  and the  amounts of  URO  dictated  by
local rainfall patterns and land use.

A number  of the NURP projects examined  receiving water impacts  in some  de-
tail, others less rigorously.  Because of the uniqueness of URO water quality
impacts,  individual project results are considered best used for confirmation
and support, rather than as a basis for broad generalizations.

Accordingly, this chapter is structured to address each of the principal cat-
egories of  receiving  water  bodies  separately;   streams  and  rivers,  lakes,
estuaries and  embayments,  and groundwater  aquifers.   Some  can  be addressed
more thoroughly  than  others  at this  time.   The  approach taken  to  develop a
general,  national scale screening assessment  of  the  significance of URO pol-
lutant discharges is to compute anticipated effects using analysis methodolo-
gies identified  in Chapter  5,  where  these  are  appropriate and  to  compare
anticipated effects indicated by such generalizations to specific experiences
and conclusions drawn by relevant individual NURP projects.

As with any generalization,  there will be  exceptions.   Specific local situa-
tions can be  expected which  are  either more or  less  favorable than the gen-
eral case.  The  results  presented herein should  therefore be  interpreted as
representative estimates of  a substantial percentage of urban runoff sites,
but not all of them.

Receiving waters have distinctive general characteristics which depend on the
water body type  (e.g., stream, lake,  estuary)  and relatively unique individ-
ual characteristics which depend on  geometry  and hydrology.   Given a minimum
acceptable amount of data on water bodies  and their  setting, it appears pos-
sible to  make useful generalizations  regarding  the quantitative  effects  of
urban runoff on  concentrations of various  pollutants  in the  receiving waters
and to draw inferences concerning the  influence  urban runoff may have on the
beneficial uses  of  the water bodies.  However extending the results  of such
an analysis to an assessment of the prevalence of urban runoff induced "prob-
lems" on  a  national scale  cannot be  accomplished in a way  would provide  an
acceptable level of confidence in any  conclusions drawn therefrom.   In addi-
tion to the importance of  local hydrology, meteorology,  and  urban character-
istics, the  emphasis placed on  each  of the  three  elements  that  influence
problem definition;

     (1)   Denial or serious impairment of beneficial use;
                                     7-1

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      (2)  Violation of ambient water quality standards; and

      (3)  Local perception;

will result in a  high degree of site-specificity to the determination of the
existence of a problem.

RIVERS AND STREAMS

General

Flowing  streams  carry pollutant discharges downstream  with  the stream flow.
For  intermittent  stormwater discharges, a  specific stream  location  and the
biota associated  with it are exposed  to a sequence of discrete  pulses con-
taminated by  the  pollutants which enter with  urban runoff.   Because  of the
inherent  variability  of  urban  runoff  (URO),  the average  concentrations  in
such pulses vary, as do  their  duration and the  interval  between successive
pulses.  Table 7-1 summarizes average values for storm duration and intervals
between storm events  for  selected locations in the U.S., based on analysis of
long  term  rainfall   records  using  a  methodology  (SYNOP)  presented  in  an
earlier  NURP  document  (the NURP Data  Management  Procedures  Manual).   The
information presented provides a sense of the temporal aspects of such inter-
mittent pulses and, by inference, the intermittent exposure patterns to which
stream  biota  are subjected.  For many  locations, storm pulses are produced
for about six hours every three days or  more, on average.

A probabalistic methodology has  been used  to  examine the concentration char-
acteristics of the storm _pulses produced in streams, given the variability of
the relevant processes which are directly  involved.   Stream flow rates, run-
off flow rates, and concentrations vary  and result in variable stream concen-
trations.  For streams, it  is not the runoff volume per se that is important.
The combination of stream and runoff flow rates  (together with runoff concen-
tration)  determine the  pollutant concentration  in the  stream  pulse.   The
duration  of the  runoff   event and  the  stream  velocity dictate  the  spatial
extent  of the storm  pulse  in  the  stream.  The  analysis presented  in this
section addresses the frequency  and  magnitude  of pollutant concentrations in
the instream storm pulses which are produced.

Runoff and Stream Flow Rates

The  local combination of stream and runoff flow  rates  for an urban location
are, as  indicated, important determinants  of  the stream concentrations which
will  result.   For long-range projections, the  most  appropriate data sources
for characterizing these  parameters are  long-term stream flow gauging records
(USGS) and long-term  rainfall records  (USWS).

Figure 7-1(a)   illustrates  the  regional variation  of  average daily  stream
flows expressed as cfs/sq mile of drainage area, based on long-term (50 years
or  more)  gauging records at over  1000 stations.  Figure 7-1(b)  presents  a
somewhat  simplified   regional pattern  for  average  rainfall  intensity.   The
data  base  for  this  plot  is  considerably smaller,  consisting  of  rainfall
records  (usually  10  to  30 years of  record)  for approximately 40 cities.
Localized peturbations exist, but are smoothed out by contours presented.
                                     7-2

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TABLE 7-1.  AVERAGE STORM AND TIME BETWEEN STORMS FOR
       SELECTED LOCATIONS IN THE UNITED STATES
Location
Atlanta, GA
Birmingham, AL
Boston, MA
Caribou, ME
Champaign-Urbana , IL
Chicago , IL
Columbia, SC
Davenport , IA
Detroit, MI
Gainesville, FL
Greensboro , SC
Kingston, NY
Louisville, KY
Memphis, TN
Mineola, NY
Minneapolis , MN
New Orleans, LA
New York City, NY
Steubenville, OH
Tampa , FL
Toledo, OH
Washington, DC
Zanesville, OH
Mean
Denver , CO
Oakland, CA
Phoenix, AZ
Rapid City, SD
Salt Lake City, UT
Mean
Portland , OR
Seattle, WA
Mean
Average Annual Values in Hours
Storm
Duration
8.0
7.2
6.1
5.8
6.1
5.7
4.5-
6.6
4.4
7.6
5.0
7.0
6.7
6.9
5.8
6.0
6.9
6.7
7.0
3.6
5.0
5.9
6.1
6.1
9.1
4.3
3.2
8.0
7.8
6.5
15.5
21.5
18.5
Time Between
Storm Midpoints
94
85
68
55
80
72
68
98
57
106
70
80
76
89
89
87
89
77
79
93
62
80
77
81
144
320
286
127
133
202
83
101
92
                         7-3

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 Figure 7-1(a).   Regional Value of Average Annual Streamflow (cfs/sq mi)
 .025
                        .045
                                      03
                          .055
                            .065
                                                                     .105
                                                                   125
                               .075
Figure  7-1 (b).   Regional Value of  Average Storm Event  Intensity (inch/hr)
                                     7-4

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Variability of daily stream flows was determined  for a smaller sample (about
150 sites) of the stream sites.  Variability of storm event average intensi-
ties was  determined  for  all of the rain gauge locations  in the current data
base.  These results are summarized in Table 7-2.

Total Hardness of Receiving Streams

Where the  beneficial use of principal  concern  is the protection  of aquatic
life, the URO pollutants of major  concern  appear  to be heavy metals, partic-
ularly copper, lead and zinc.   The potential toxicity of these pollutants are
strongly  influenced  by total  hardness,  as indicated  by Table 5-1  in  Chap-
ter 5.  Other beneficial uses  deal  with pollutants and effects  that are not
influenced by  total hardness  or  (as with drinking  water  supplies) do not
modify the assigned  significance of heavy metal  concentrations  on the  basis
of total hardness.

As with stream flow  and  precipitation,,  distinct regional  patterns also  exist
for receiving water total hardness concentrations.  Figure 7-2 delineates the
national  pattern  of regional  differences.  These  patterns impose  an  addi-
tional regional influence on the potential of urban runoff  to create problem
conditions in streams and rivers.

Technical Approach To Screening Analysis

The magnitude and  frequency of occurrence of intermittent  stream concentra-
tions of  pollutants of  interest,  that  result  from  urban  runoff,  has  been
computed using the probabilistic methodology discussed in Chapter 5.

The input  data  required for application  of the  methodology  includes repre-
sentative values  for the mean and variability  of stream flow,  runoff  flow,
and runoff pollutant concentrations.  The  material presented earlier in this
chapter provides  the basis  for  assigning  values  for the flows;  the results
summarized in Chapter 6  provide the  basis for specifying  pollutant concen-
tration inputs.   In order to translate the probability distribution of stream
concentrations (which is the basic output  of the  analysis methodology)  to an
average recurrence  interval,  which  is  considered to  provide a  more under-
standable basis  for comparisons,  the  average  number  of  storms per  year is
also required.  This is  estimated directly from the average interval between
storm midpoints  generated by  the  statistical  analysis  of hourly rainfall
records.

For a general  screening  on a  national  scale,  an  estimate  of  typical values
for a selected geographic location must  be made.   This has been done, and the
set of  input values  considered  to be  typical  of geographical  location are
described and summarized below.   The values used should be  considered  rea-
sonably representative of the  majority of sites  in the area, but it should be
recognized that not all potential sites  will have  conditions either as favor-
able or unfavorable as those listed.

We have worked with a limited  sample  in  assigning typical values.   A greater
data base on rainfall and stream flow would permit greater spatial definition
                                     7-5

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                                                                                     en
                                                                                     5
                                                                                     a
                                                                                     (M
                                                                                     A
HARDNESS AS CaC03
IN PARTS PER MILLION
           Under 60
           60-120
         120-180
         180-240
         Over 240
Figure 7-2.   Regional Values for  Surface Water Hardness

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than shown in  the  results.   Specific regions or  states  could,  with develop-
ment of a more detailed spatial definition of stream flows and rainfall, ex-
tend  the  analysis  presented to  provide a  considerably  more  comprehensive
assessment of  problem potential  for local  areas.   This  would  involve the
development  of input parameters  (rainfall  and  streamflow)  readily  derived
from available long term  USGS  stream flow records and USWS rainfall records
and their use  in the methodology  with quality parameters based either on the
NURP analysis presented in Chapter 6, or on local monitoring activities.

The analysis methodology  presently available permits computation of the pro-
bability distribution of instream concentrations, incorporating the effect of
upstream  (background) concentrations  of the pollutant of  interest.   The re-
sults presented here assume  upstream concentrations  of  zero, principally be-
cause  of  our  inability   at  present  to  make reliable  estimates  of  typical
values for the magnitude and variability  for  pollutants  of interest,  espe-
cially on the  broad national scale being examined.   As  a  result, the summa-
ries will  show the  effects of urban  runoff contributions only.   In  cases
where the background is small relative to the URO contribution, the summaries
will represent actual conditions quite closely.   However, where background is
high and has appreciable variability,  the implications  of the URO contribu-
tion will be overstated, particularly  the  inferred  improvement  which  could
result from control of URO.

In order to perform a national screening of regional influences on urban run-
off impacts, eight geographical regions illustrated  by  Figure 7-3 have been
delineated.   Using the information summarized by Figures 7-1 and  7-2, typical
values  for  the pertinent rainfall/runoff  and  stream  parameters have  been
assigned for each  of the  regions.  Table 7-2 summarizes  the values for these
parameters which are used in the screening analysis.
                     TABLE 7-2.  TYPICAL REGIONAL VALUES
Area
1
2
3
4
5
6
7
8
Event Average
Rainfall Intensity
Mean
(in/hr)
0.04
0.10
0.08
0.055
0.04
0.03
0.045
0.025
c.v.
1.00
1.35
1.35
1.25
1.10
1.10
1.20
0.85
Average
Number
of
Events/year
110
100
90
110
63
70
30
80
Average
Runoff Flow Rate
Mean Event
(cfs/sq mi )
5
12
10
7
5
4
5
3
c.v.
0.85
1.15
1.15
1.05
0.95
0.95
1.00
0.75
Stream Flow Rate
(Daily Avg Flows)
Mean
(cfs/sq mi )
1.75
1.25
1.00
0.75
0.35
0.05
0.05
4.50
c.v.
1.25
1.25
1.25
1.25
1.25
1.25
1.25
1.25
Stream
Total
Hardness
(mg/1)
50
50
50
200
200
300
200
50
Average  stream  flow  and rainfall intensity were  taken  from the plots, which
are based  on sources previously described.  The  estimate  for variability of
daily stream flows (coefficient of variation) is based on computed values for
a sample of about 150 perennial streams.  Results for a number of regional
                                     7-7

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I
CO
                                                                                                                    CM
                                                                                                                    cS
                              Figure  7-3.   Geographic Regions Selected for Screening Analysis

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groupings indicated median  values for  coefficient  of variation to  fall be-
tween approximately 1 and 1.5.   Since  there were no  clear  regional  patterns
apparent, a  uniform value  for  coefficient of  variation  of stream  flows of
1.25 was assigned.

The coefficient of variation of  rainfall  intensities  was  taken directly from
the statistical analysis of the  rainfall  records  examined.   This was reduced
by 15 percent to provide estimates of  the coefficient of  variation of runoff
flow rates,  based on a recent published report, "Comparison of Basin Perform-
ance  Modeling Techniques",  Goforth,  Heaney  and  Huber,  ASCE  JEED,  Novem-
ber 1983, using the SWMM model on a long-term rainfall record.

The quality  characteristics of urban  runoff  used in the  screening  analysis
are listed  in Table 7-3,  and are based on  the results summarized  in Chap-
ter 6.   The  analysis  results have  been rounded  in the selection of repre-
sentative site median EMCs  and are interpreted as being representative of an
array of urban sites discharging into the receiving stream being analyzed.

Average site conditions are based on the  50th percentile  of all urban sites.
Since the data analysis indicated that sites  at some  locations tend to clus-
ter at either the higher or lower ends of the range for all sites, high range
and low  range site conditions  were  also  selected  for use  in the screening
analysis.  High range site conditions are nominally based on the 90th percen-
tile of all  site median concentrations;  the low range on the  10th percentile
site.   The variability of  EMCs  from storm  to storm at any  site  is  based on
the median  of the coefficients  of  variation  of  EMCs at sites  monitored by
NURP.   This  value was used  for  the low range  and average  site condition and
was increased nominally for the high range site condition.
              TABLE 7-3.  URBAN RUNOFF QUALITY CHARACTERISTICS
                       USED IN STREAM IMPACT ANALYSIS
                          (Concentrations in yg/1)

Low Range of
Site Conditions
Average
Site Conditions
High Range of
Site Conditions
COPPER
Site Median
EMC
15
35
90
Coef
Var
0.6
0.6
0.7
LEAD
Site Median
EMC
50
135
350
Coef
Var
0.75
0.75
0.85
ZINC
Site Median
EMC
75
165 .
450
Coef
Var
0.7
0.7
0.8
An illustrative example  of  a site-specific application of  the probabilistic
analysis methodology employed is presented in'order to:

     1.  Illustrate the nature of the computational results produced;
                                     7-9

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     2.  Assist in the interpretation of the tabulations presented later.
         which  summarize   results   of   the  national  scale  screening
         analysis;

     3.  Indicate how magnitude/frequency of instream concentrations may
         be  interpreted   for   inferences   concerning  the  absence  or
         presence  of a "problem"  and where  a  problem is  concluded to
         exist, its degree  of severity; and

     4.  Demonstrate how  alternative URO control  options  may be  eval-
         uated  in  terms of their  expected  impact on water  quality and
         potential effect on problem severity.

From selected  representative  values for mean and variability of  stream  and
runoff conditions, the probability distribution of resulting instream concen-
trations during storm  events can be  computed.  Figure 7-4  illustrates a plot
of such an  output.   Uncertainty in estimates for  specific  inputs  can be  ac-
commodated by  sensitivity analyses which incorporate upper  and  lower bounds
for specific parameter values.   Results are then  presented  as a band rather
than a specific projection. The probabilities  which are  the basic output of
the analysis may be converted to average recurrence intervals to provide what
is believed to be a more understandable basis for  interpreting and evaluating
results.

Figure 7-5 presents  results converted to the average  recurrence interval at
which specific  stream  concentrations  will  be  produced during  storm runoff
periods.

The significance of  a  particular magnitude/frequency pattern of stream con-
centrations caused  by  urban runoff  can be  evaluated by comparing them with
concentrations  which are  significant  for  the  beneficial  use  of  the  water
body.  In the  example  presented, we have excluded comparisons with drinking
water criteria  on the  basis  that urban streams  are  not  generally  used as
domestic water  sources,  and  in any event,  the criteria  relate  to finished
water, and surface water supplies almost invariably receive treatment.

Protection of aquatic  life  is  selected for  the  screening analysis of the im-
pact of urban  runoff because  it is believed  to  be the  predominant potential
beneficial  use  for  urban  streams  on  a national  scale.   The  concentrations
which result from urban runoff are compared with stream target concentrations
associated with different degrees  of adverse impact, as discussed and tabu-
lated in Chapter 5.

In  the  site  specific   situation illustrated,  the stream  concentrations of
copper caused by  untreated urban runoff discharges  exceed the  "EPA Maximum"
criterion more  than  ten times per year  on  average.   The  concentration level
suggested by the NURP  analysis  to  be the Threshold level  of adverse biologi-
cal impacts is  exceeded an average of five  times per year (recurrence inter-
val 0.2 year), and significant mortality of more sensitive biological species
occurs about once  every three years on  average.   Although this  stress level
may not be  great enough  to result in a total  denial of the use,  there  are
many who would  argue that it  represents an  unacceptably severe  degree of im-
pairment of this beneficial use.
                                    7-10

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  100
                 99
                           90
                                       SO
                                                   to
        EPA MM
  10
I
i
  0.1
                                                              RUNOFF
                                                             EFFICIENCY
        COPPER
STREAM TOTAL HARDNESS <
  DRAINAGE AREA RATIO <
                                                                  SOmtfl
                                                                  100
                           10           50           90
                       PERCENT OF STORM EVENTS EQUAL TO OR LESS THAN
                                                             99
Figure  7-4.   Probability Distributions of  Pollutant Concentrations
                        During  Storm Runoff Periods
                                                        COPPER
                                                STREAM TOTAL HARDNESS - 50 agfl
                                                  ORAINAEE AREA RATIO - 100
                             1       2         S
                           MEAN RECURRENCE INTERVAL YEARS
   Figure 7-5.   Recurrence  Intervals  for  Pollutant  Concentrations
                                      7-11

-------
The projection  labeled "treated urban runoff" may be  taken  to represent the
in-stream result for either the originally considered discharge following the
application of  controls which  effect  a 60 percent reduction,  or of an uncon--
trolled urban runoff site with lower levels of copper in the runoff.  In this
case, threshold levels are reached only once every 3  or  4 years  on average,
and  significant mortality levels  are  virtually never  reached.   Even though"
the ambient "EPA MAX"  criterion  is exceeded  once  or  twice a  year on average,
one might conclude  that the  implied degree of stress is tolerable and is not
interpreted to  represent a significant degree of impairment of the use.

The Threshold and Significant Mortality levels are estimates, which have been
explained earlier.  In addition, the "acceptable" frequency at which specific
adverse effects can be tolerated is subjective at this time, since there are
no formal guidelines.   However,  an approach of this nature must  be taken in
any  evaluation of  the significance of  urban runoff  and the  importance of
applying  control measures.   There are  two  reasons why  this  is necessary.
First, because  of the stochastic  nature  of  the system we are dealing with,
virtually any  target  concentration we elect  to  specify will  be  exceeded at
some  frequency, however  rare.   Secondly,  from  a practical  point  of  view,
there are limits to the capabilities of controls, however rigorously applied.
In the illustration presented, the untreated urban runoff site assigned urban
runoff copper   concentrations  equivalent  to the  average  urban  site.   Since
NURP analysis  data  indicate that  the copper  in  urban runoff has  a soluble
fraction  of  about 40 percent, the  level  of  removal  used  in  the  example re-
flects a control efficiency approaching the practical limit.   Receiving water
impacts are significantly reduced, but not totally eliminated.

Results of Screening Analysis

A projection of stream water quality responses has been made for each of the
eight  geographical  areas  shown by  Figure 7-3.   The  rainfall,  runoff,  and
stream  flow estimates used  in  the  computations  are those summarized in
Table 7-2.  The urban runoff quality characteristics used are those presented
in Table 7-3.

To consolidate  screening  analysis  results for easier comparison,  results are
not  presented   as continuous  concentration/frequency  curves  as used  in the
illustrative example  presented  above.   Instead,  the  comparison  plots which
follow  show only  the recurrence  interval  at   which specified  biological
effects levels  are  exceeded.   The  concentrations which correspond with these
effects  are  strongly  influenced by  stream  total hardness,  and  hence  vary
regionally.  Table  7-4, based on  information presented in Chapter 5,  summa-
rizes  the  stream  target  concentrations used   in  the  screening  analysis
summary.

Analysis results are presented for Copper  (Figure 7-6), Lead  (Figure 7-7) and
Zinc  (Figure 7-8).  Each  individual bar  represents  a  different geographical
region, and  the analysis is performed for two drainage  area ratios.   Since
regional  stream flow  differences  are  based on  unit  flows  (cfs/sq mile of
drainage area)  , actual flow in a receiving stream at a particular location is
                                    7-12

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       TABLE 7-4.  REGIONAL DIFFERENCES IN TOXIC CONCENTRATION LEVELS
                          (Concentrations in yg/1)

Pollutant
Copper


Lead


Zinc


Stream
Total Hardness
yg/i
50
200
300
50
200
300
50
200
300
Geo-
graphic
Regions
1,2,3,8
4,5,7
6
1,2,3,8
4,5,7
6
1,2,3,8
4,5,7
6
FPA
MAX
12
42
62
74
400
660
180
570
800
Suggested Values For
Threshold
Effects1
20
80
115
150
850
1400
. 380
1200
1700
Significant Mortality2
(a) (b)
50
180
265
350
1950
3100
870
2750
3850
90
350
500
3200
17,850
29,000
3200
8000
11,000
        Threshold Effects - mortality  of  the most  sensitive individual
        of the most sensitive species.


     2  Significant Mortality

        Level  (a) - mortality  of  50  percent  of  the  most  sensitive
        species.

        Level  (b) - mortality  of  the  most  sensitive  individual  of
        25th percentile sensitive species.
a  function  of
drainage area.
both  the  unit  flow rate  and the  size of  the  contributing
The  "drainage area  ratio"  (DAR) used  in  the  analysis  is
                 _ Urban Area Contributing Runoff
                   Stream Drainage Area Upstream of Urban Input

It is a measure of  the  location  of  the urban area relative to the headwaters
of the receiving stream.

The  shading  scheme used  on the  bars  duplicates  that  used  earlier  in  the
illustrative example (Figure 7-5), and identifies the recurrence interval for
each of the  target concentrations.   For example,  instream copper concentra-
tions during storm  runoff  periods in geographic region  1,  with average site
conditions for  copper concentrations  in  urban runoff,  and a  DAR = 10,  are
projected to be as follows (middle plot, Figure 7-6).

        EPA  MAX - ambient  criterion  is   exceeded at   a  frequency  of
        0.02 year (= 50 times/year)  or  about every other storm event on
        average.
                                    7-13

-------
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                                                                COPPER

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                                                                   LEAD

-------
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-------
        Threshold  concentration  levels  at  which  adverse  biological
        stress for short duration exposures is projected to occur have a
        recurrence interval of about 0.05 years (20 times/year).

     -  Significant mortality levels are  exceeded  at intervals of about
        0.5 year (twice/year) for the less  severe  effect,  to about once
        in 5.5 year for the more severe impact specified.

The plot is terminated at an upper level for recurrence interval of 50 years.
Although  the  analysis procedure  computes  specific  recurrence  intervals  in
excess of  this  value, a realistic  interpretation  suggests  that such condi-
tions are  for practical purposes quite unlikely  to ever be  reached or ex-
ceeded.   At computed recurrence intervals of about 10 years or more estimates
are not considered to be reliable and are very probably conservative.  There-
fore, indicated mean recurrence intervals in excess of 10 years probably (and
50 years certainly) should be interpreted as "unlikely" or "highly unlikely".

Discussion

An  inspection of  the  screening analysis  results  (Figures 7-6  through 7-8)
indicates the reason why it  is  unrealistic  to attempt a broad generalization
on  whether  urban runoff is,  or is  not a  "problem" in rivers  and streams.
Water g_uality impacts can vary widely, depending on regional  rainfall and
stream hydrology,  urban site  quality  characteristics,  drainage  area ratio
(reflecting the size of the receiving stream relative to the urban area), and
the  total  hardness of the  receiving stream.   While the  screening analysis
results provide an informative and useful perspective on the issue, it should
be recognized that any specific site may differ considerably from the typical
conditions used  to characterize rainfall and  stream flow for  the area, and
further, that local  variations in runoff quality  characteristics within the
range defined by the NURP data can also have significant influence.  The dom-
inant indication of  the  analysis is  that the problem potential  for urban
runoff is highly site-specific.  Nevertheless some useful generalizations can
be made.

Perhaps the major  factor which dictates  whether  urban  runoff discharges  of
copper,  lead,  or zinc will adversely impact aquatic life is the natural hard-
ness of  the receiving streams.  As  a  result,  the southeast  and gulf coast
areas are consistently indicated to be more sensitive than other areas of the
country.  Of  the remaining soft water areas, the  northeast  is somewhat less
sensitive; the Pacific northwest  markedly less.  This  is  attributed to sig-
nificantly lower storm intensities  in these areas,  coupled  in the northwest
with appreciably higher stream flows.

Drainage  area ratios have  an  important  effect,  reflecting  as they  do the
magnitude of  stream  flow at  the urban  location.   The  effect is much greater
for  geographical  regions with  high  unit flow  (cfs/sq mile)  than  for lower
stream flow regions.

Finally,  the  quality characteristics of  the  urban  sites  have a significant
influence.  Stream concentrations differ  markedly depending  on whether the
local urban sites tend to cluster toward the lower or higher end of the range
of site median concentrations indicated by the NURP data base.
                                    7-17

-------
A comparison  of the  relative  position of  the  bars on  Figures  7-6,  7-7 and
7-8,  is  sufficient to  indicate  the comparative sensitivity  to  urban runoff
pollutant  discharges.  However,  it is  also desirable  to decide  whether  a"
given stream effect constitutes  a serious  degree of impairment of an aquatic
life  beneficial use.   There  are  no  formal guidelines,  and interpretations
that are either more  liberal  or more restrictive  than  those suggested below
may be  preferred by  others dealing with specific  stream  segments.   For the
interpretation  of  the national  scale  screening  analysis, the following deci-
sion basis has  been used to  identify the situations in which urban runoff is
likely to  result in  a water use  "problem",  (i.e.,  cause an unacceptable de-
gree of use impairment):

     -  Threshold  effects  -  (mortality  of  the most sensitive individual
        of the  most sensitive  species)  occur more often than about once
        a year  on average.

        Significant mortality - using the lower of the two levels  (i.e.,
        50 percent mortality of the most sensitive species), occurs more
        often than about once every 10 years on average.

Using these  guidelines for assessing  the  occurrence of problem situations,
copper  is  shown to be the most  significant of the three heavy metals con-
sistently found in urban runoff at elevated concentration levels.  Where site
concentrations  are at the  high range of observed urban site conditions, prob-
lems are expected  in all  geographic regions at a DAR = 10,  and in all geo-
graphic  regions  except   region 8  at  DARs  as  high   as  100.   When  site
concentrations  are in the  average range  of  observed conditions,  problem
situations are  restricted to  geographic regions 2  and 3  (plus region 1 at
DAR = 10) .   When  site  copper   concentrations  are  in  the  lower range  of
observed  site   conditions, problem situations  are restricted  to geographic
regions 2 and 3 at low DARs.   They are. marginal (significant mortality once
every 5 years)  but remain  a problem according to the definition  adopted.  The
"marginal"  attribution  is used  here,  because the  more  severe  degree  of
significant mortality (most sensitive individual of 25th percentile sensitive
species) is indicated by the analysis virtually never to occur.

Thus, copper discharges in urban runoff are indicated to represent a signif-
icant threat to  aquatic  life  use in  regions  2 and  3 (southeast  and Gulf
Coast) under almost all possibilities  for  urban site runoff quality.  In re-
gion 1  (northeast), problems would be expected  at  all  but the lower range of
site concentrations.   In the  hard water areas  (regions 4,  5, 6, 7) problems
are expected only  where site  runoff quality is  in  the  high  end of the range
of observed site median concentrations.

It should  be  noted that the analysis has been  based on total copper concen-
trations in urban runoff.  Toxic effects are usually considered  to be exerted
by the soluble  form of the metal,  and  EPA  defines an "active" fraction based
on  a mild  digestion  which  converts  some  of  the inactive  particulates  to
soluble forms,  to  account  for  transformations which may occur in the natural
water  systems.   Copper in urban  runoff has a typical soluble  fraction of
about  50 percent,  and the active fraction would therefore  fall somewhere
between  50 and  100 percent of the total concentration  used in the analysis.
The  analysis has  been performed  using the total fraction,  since adequate
                                    7-18

-------
information  is  not available  at present  to reliably  adjust  these  values.
However, although the problem assessment presented above may be somewhat con-
servative, further refinement  along  these  lines would not  change  the infer-
ences drawn from the screening analysis results.

Zinc,  like  copper,  has  an  indicated  soluble  fraction   in   the  order  of
50 percent, and the screening analysis indications will also be unaffected by
this consideration.   It  is indicated  to be unlikely  to pose  a  significant
threat  to aquatic  life  in  most urban  runoff  situations.  Exceptions  are
restricted to soft water areas in  the east and south, lower DARs,  and sites
with high zinc concentrations in urban runoff.

Lead results must  be  viewed  with greater caution, because  soluble fractions
in  urban  runoff  are  indicated to  be  quite  low  (less   than 10 percent) .
Problem indications are therefore likely to be  reasonably conservative, i.e.,
overstate  the problem potential.  Problem  situations  may  be expected  to be
restricted to soft water areas in  the east and Gulf areas when  urban sites
have average  site concentrations  and DARs  are low, and  even at  high DARs
when site concentrations are in the high range.   Lead  is not  indicated to be
a threat  to  aquatic life  in  the hard water areas  of  the  country  or in the
Pacific  northwest,  except  for  the  combination  of  low DAR  and  high  site
concentration.

In performing the screening analysis, upstream concentrations were assumed to
be  zero;  that is, the  receiving stream had only a diluting  effect  on the
urban runoff  pollution.   In  actual  cases  background concentrations  will be
greater than zero, and in  some instances upstream contributions (e.g., agri-
cultural runoff, another city)  could be significant and result in more severe
conditions than those identified in the screening analysis.

On  the basis  of the  foregoing, it  appears appropriate to  identify copper as
the key toxic pollutant in  urban runoff,  for the following reasons:

        Problem situations anticipated for lead  and zinc  do  not occur
        under any  conditions  for  which copper  does not  show up  as a
        problem as well -  and with  more  severe impacts.   On  the other
        hand, copper  is  indicated  to  be  a problem  in  situations where
        lead or zinc are not.

     -  Based on  the ratios  between concentrations producing increas-
        ingly severe  effects,  copper is  suggested to be a more generic
        toxicant.   It has  an  effect on a broad range  of species.  This
        is  in  contrast  to  lead and  zinc  for  which  a  substantially
        greater degree of  species  selectivity  is  indicated.   Some spe-
        cies  are  sensitive,  others  relatively  insensitive to  lead and
        zinc.

        From  the  NURP data,  locations which tend  to  have site  median
        concentrations in  the low,  average,  or  high  end   of  the  range
        have generally consistent patterns  for  each of  the three heavy
        metals.
                                    7-19

-------
     -  Control measures  which produce reductions  in  copper discharges
        to  receiving waters could  be  expected to  result  in equivalent
        reductions in zinc, and greater reductions in lead, by virtue of
        its significantly greater particulate fraction.

Copper  is  accordingly suggested to be  an effective indicator  for  all heavy
metals  in  urban runoff relative  to aquatic life.   It might be used  as the
focus   for  control   evaluations,   site   specific   bioassays,   monitoring
activities, and the like.

It should be noted that while  immediate water  column impacts of lead are not
as significant  as those  for copper, the  high particulate  fraction  of lead
would tend to result in greater accumulations in the stream bed.  This aspect
has not been  addressed by  the  NURP program in sufficient  detail  to warrant
any comment on its potential significance.

The results of  the screening analysis summarized by Figures 7-6 through 7-8
are  approximate,   because  they  are  influenced by  the  suitability  of  the
typical values for stream and runoff flows which were assigned.  This however
can be  refined  by the use of appropriate values which can be developed from
readily  available  data bases,  and  thus  adjusted for  local variations which
are to  be  expected.   A second issue relative to the reliability of the pro-
jections is the validity of the computations, given that the input parameters
are representative.  This has been confirmed by a number of validation tests,
discussed in the NURP supporting document referenced earlier, which addresses
the stream analysis methodology.

The.  remaining  issue  for  evaluating  the  reliability  of the  indications  of
problem potential produced by the screening analysis is the reasonableness of
the  intermittent  exposure  concentration  levels,  which  have  been associated
with various biological  effects levels, and the guidelines adopted for this
discussion, which determine  whether or  not a problem is  expected.   While
rather  tenuous at this time, the information available does provide support.

Two of  the NURP projects examined  aquatic  life effects in streams receiving
runoff  from monitored sites.

     -  Bellevue,  WA concluded that  whatever adverse  effects  were ob-
        served  were  attributable to habitat impacts  (stream  bed scour
        and  deposition)   as opposed  to  chemical  toxicity.    For  this
        project,  heavy  metal  concentrations   in   the  monitored  urban
        runoff  sites were typical  of  the average for  all urban sites.
        The  screening analysis  results  under  these conditions  do not
        indicate the expectation of a problem.

        Tampa, FL  conducted extensive bioassay  tests but failed to show
        any adverse  effect  of water column concentrations of pollutants
        in  urban  runoff.    The  screening  analysis  results  presented in
        Figure 7-6 indicate marginal problem conditions at low DAR for
        this geographic region.  At this  project  however,  all monitored
        sites show heavy  metal concentrations  significantly lower than
        the low  range conditions used in the  screening analysis.   When
                                    7-20

-------
        the  screening  analysis  is  repeated  using site  concentrations
        representative of Tampa monitoring  results, a problem situation
        is not predicted, even at DARs lower than is  probably  the case
        for this location.
LAKES
Because lakes provide  extended residence times for pollutants,  the signifi-
cant time scale for evaluating urban runoff impacts is at least seasonal, and
usually annual or longer, rather than the storm event scale used for streams.
The screening methodology identified in Chapter 5, uses annual nutrient loads
to assess the tendency for development of undesirable eutrophication effects.

Figure 7-9 illustrates the effect of urban  runoff on  average lake phosphorus
concentration.  The very significant influence of area ratio is evident.  The
larger the urban area  which  drains  into a lake of a  given size,  the greater
the annual loading, and  the  higher  will be  the lake  phosphorus concentration
and the eutrophication effects produced.

The phosphorus concentrations characteristic of the urban sites surrounding a
particular lake are also seen to be significant.  The three  bands  shown re-
flect the range of possibilities, based on  the NURP  data.   The same basis is
used to estimate the phosphorus  loads  from average urban  sites  and those at
the higher  and lower  ends of  site conditions,  as  was  described  for heavy
metals in  the previous  section.   In this  case,  because  it is  annual mass
loads which  are of  interest, site median concentrations have been converted
to site mean values for use in the computations.

Lake  phosphorus  concentrations  are  also  influenced by  the annual  runoff
volume  (annual  precipitation  and  runoff coefficient).   The  results  illus-
trated are based on an  annual rainfall of  30 inches and  an overall average
runoff coefficient of 0.2.  Plotted results may be scaled  up or  down in pro-
portion to the ratio between local values for these parameters and those used
in the illustration.

Finally,  the  lake morphology and hydrology influence the  outcome;  specific-
ally depth  (H)  and residence  time  (T) .   This is  reflected by the  width of
each of  the  bands,  which  are based on  a range of values  for H/T  (1 to 10)
estimated to be fairly typical for lakes in urban settings.

If an average lake  phosphorus concentration of 20 ug/1 is used as a reference
concentration to assess the tendency for producing undesirable levels of bio-
stimulation,  it is  apparent that only lakes  with rather small area ratios are
likely to be unaffected by urban runoff nutrient discharges.  Since the three
bands represent different concentration levels of phosphorus in urban runoff,
qualitative inferences may be drawn concerning the beneficial use impacts of
control activities.   More detailed estimates may  of course be made  by use of
the methodology with site specific parameters.

The salient  feature of  the  situation,  as  generalized by  the analysis sum-
marized by  Figure  7-9,  is that the problem potential  of urban runoff  for
lakes is quite site  specific.  The illustration  considers  only  urban runoff
loads; in  an actual situation, all  nutrient  sources (point  and  nonpoint)
                                    7-21

-------
   1000
e   100 -
u
a
             URBAN SITE QUALITY
               CHARACTERISTICS
              SITE MEAN TP CONCENTRATION
                                                                    HIGH RANGE

                                                                    AVERAGE
                                                                    LOW RANGE
                                          ANNUAL RAINFALL = 30 in/year
                                        RUNOFF COEFFICIENT = 0.2
                                           DEPTHIRESIDENCE
                                           RATIO FOR LAKE
                  H|T=  1 to IQmlyr

                     IDmlyr
                                          SETTLING VELOCITY Vs
                                           (TOTAL P)
                                10
                100
1000
                                  RATIO
   URBAN AREA
LAKE SURFACE AREA
  Figure  7-9.   Effect of  Urban Runoff  on Lake  Phosphorus Concentrations
                                          7-22

-------
would be considered, and this would  tend  to modify the relative significance
of urban runoff on lake conditions.

Several of the NURP projects addressed impacts on lake quality in some depth.
These projects include the following:

     -  Irondequoit Bay,  NY - Lake   has  been highly  eutrophic, due  to
        point and nonpoint discharges.  Sewage  treatment  plant and com-
        bined  sewer overflow  discharges  have  been   removed,  so  that
        residual sources  are  recycle from  lake sediments  and nonpoint
        sources, including urban runoff,  from the  contributing drainage
        area.  Further reductions are considered necessary  to meet tar-
        gets.  (Area ratio is high at this location.)

     -  Lake George, NY - Lake is oligotrophic;  the study addressed the
        concern that urban runoff from present  and potential future de-
        velopment . would unacceptably accelerate  degradation of existing
        water quality.   (Area ratio  is low at this location.)

     -  Lake Quinsigamond, MA - Urban runoff was determined to be one of
        a  number  of sources  preventing  water  quality objectives  from
        being met.  Some  control of urban  runoff phosphorus  loads was
        recommended as one  of  the  elements of  an  overall management
        plan.

Each of  the above  situations  is sufficiently  unique,  and the mix of urban
runoff and other load sources is sufficiently different to suggest that it is
inappropriate to attempt  a broad generalization.  The  interested  reader may
refer to  the individual project documents  which are  available  through NTIS
for more information.

ESTUARIES AND EMBAYMENTS

These water bodies are normally of sufficient size and complexity that simple
screening  analyses  have not  been considered to  be  sufficiently  useful  or
effective to justify their use.

The  Long  Island,  NY NURP  project  examined  and  confirmed  that  urban runoff
sources  of coliform bacteria  are the  principal  contributors to  the water
column concentrations that result in closure of shellfish beds in a number of
embayments  (principally the  Great  South Bay).  Estimates of control activi-
ties that  would allow  the  opening  of presently closed  areas were  also made.
The reader is referred to the project documents for further information.

The significance of urban runoff and other nonpoint source loads on eutrophic
levels in  the  Potomac  estuary is being  investigated  under  a  study which  is
not associated with the NURP program.  However, among other objectives of the
WASHCOG NURP project,  estimates of urban  nonpoint  source  loads have been de-
veloped to support this study.

Although  specific   situations where  urban  runoff is  significant  have  been
identified, no general  assessment for water bodies of this  type can  be made
at this time.
                                    7-23

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GROUNDWATER AQUIFERS

Much of  the  precipitation which falls on  an area either percolates directly"
into the  ground,  or does so after  relatively  short  overland flow distances.
This condition is  essentially  uncontrollable and distinctly  different from
the case  where urban runoff from impervious  areas  is deliberately collected
and routed to  a recharge device which causes it to percolate to groundwaters.

This type of control  approach is  a  practical and effective technique for re-
ducing pollutant  loads which would otherwise  reach surface waters  as dis-
cussed in Chapter 8.  The concern addressed  here is  with the extent to which
groundwater aquifers may be contaminated by this practice.

The Long  Island, NY and Fresno, CA  NURP  projects examined this issue through
extensive tests  utilizing recharge basins ranging  from recent installations
to  others which  have been  in  service  in excess  of 20 years.   A somewhat
simplified consolidation  of the  salient findings of these two  projects  is
presented below.  The interested reader is referred to the individual project
report  documents,  available  through  NTIS,   for the  important  details  and
qualifications.

     -  Most pollutants  of importance  in urban  runoff  are intercepted
        during  the  process  of   infiltration  and  quite  effectively
        prevented   from  reaching  the groundwater   aquifers  underlying
        recharge basins.  The pollutants tested and  found  to  behave in
        this manner include the heavy metals,  an appreciable  number of
        the  organic priority pollutants and  pesticides,  and  coliform
        bacteria.

     -  Chlorides,  which  are  sometimes  present in urban  runoff  at
        elevated  concentrations  due to road deicing practices,  are not
        attenuated  during recharge.

     -  Pollutants  accumulate  in  the upper  soil layers.   The concen-
        trations found are  a function of  the length of time a basin has
        been in service.  Effective retention of pollutants takes place
        with all  soil types  tested,  ranging  from  clays to  sands.  The
        depth  of pollutant penetration is affected by soil type; however
        in no  case did  contaminant enrichment  of   soil  exceed several
        meters  depth, and  highest  concentrations  were found  near the
        surface.

     -  The limit of the ability of the soil to retain the pollutants of
        interest is unknown.  Additional  study of this aspect is appro-
        priate.  However  given  the long service periods  of a  number of
        the recharge  basins studied,  this does  not  appear to represent
        an imminent concern.

     -  At both  of these NURP  locations, groundwater  surfaces  were at
        least  20 feet, and often appreciably more, below the base of the
        recharge device.  The  indicated findings may not be applicable
        at locations with shallow depths to groundwater.
                                    7-24

-------
No   significant   differences   in   interception/retention   of
pollutants  is  apparent for  basins with  bare versus  vegetated
recharge surfaces.  However  vegetation does  apparently  help to
maintain infiltration rates normal for the soil type.

Surface soil accumulations of  priority pollutants  in  dual pur-
pose installations used  for  both recharge and  recreational use
warrants further  investigation  to determine  whether such prac-
tice creates unacceptable health risks or requires appropriately
designed and conducted maintenance procedures.
                       7-25/7-26 blank

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                                  CHAPTER 8
                            URBAN RUNOFF CONTROLS
INTRODUCTION

This  chapter  summarizes  the  information  developed by  the individual  NURP
project  studies  relating to  performance  characteristics  of  selected  tech-
niques  for the  control  of  urban  runoff quality.   The  number of  control
practices  addressed here  is  considerably  smaller  than the  array of  best
management practices  suggested  in prior  studies  and publications.  This  is
not  intended  to  exclude consideration  of other  approaches.    However,  the
techniques discussed  in this  chapter may be  taken as an  expression of  con-
trols considered  by the agencies involved  to be potentially  attractive  and
practicable at localized planning levels.  They represent  the practices  for
which performance data  were obtained under  the  NURP program and which  can be
analyzed and evaluated in this report.

Most  of  the  NURP  projects  provide  in  their  project  reports a  detailed
analysis and evaluation of the controls that were studied.  These reports are
available through NTIS.   In addition to  this  information source, an analysis
was performed by  EPAs  NURP headquarters  team,  using results  available  from
all project studies.  The objective was  to provide an overview and a generic
description of  performance  characteristics  in a  format  considered  to  be
useful  for planning activities.  Thus,  in  addition to  providing  a consoli-
dated summary  of project  results,  this  chapter  presents  a summary of  the
results of applying analysis  methodologies  developed under the NURP program.
Further detail on the former can be obtained by reference to relevant project
report documents; a more  comprehensive development  of the latter is provided
in  separate NURP documents  ("Detention  and  Recharge  Basins  for  Control  of
Urban Runoff  Quality",  and  "Street  Sweeping  for Control  or  Urban  Runoff
Quality").

The  types  of  control  techniques  which received  attention  (to  a  greater  or
lesser  degree)   in  the  NURP  program  can   be  grouped  into  four  general
categories.

     -  Detention Devices - These include  normally  dry detention basins
        typically  designed  for  runoff  quantity  control,  normally  wet
        detention basins, dual  purpose  basins, over-sized  drain pipes,
        and catchbasins.

     -  Recharge  Devices -  These  include infiltration  pits,  trenches,
        and ponds;  open-bottom  galleries and  catchbasins; and porous
        pavements.

     -  Housekeeping Practices -  These are  principally street  sweeping,
        but also  include sidewalk  cleaning,  litter  containers,  catch-
        basin cleaning, etc.
                                     8-1

-------
     -  Other - These  include  the  so-called "living filter" approaches,
        grassed swales, wetlands, etc.

DETENTION DEVICES

General

Detention basins  proved to  be one of  the  most popular approaches  to  urban
runoff quality  control selected at the  local  level,  based on  the  number of
individual projects  which  elected  to study them and  the number of detention
devices tested  in  the  study.  It is perhaps instructive to  note that nearly
all  the  detention facilities  studied were either  already in place, or  re-
quired  only modifications  of  outlet  structures  before  initiation of  the
NURP-supported  studies.   In general, detention devices proved  to  provide a
highly effective  approach  to  control of urban runoff  quality,  although  the
design concept has a significant bearing on performance characteristics.

Table 8-1 lists the NURP projects that included detention devices as elements
of their study program.  Both the number of devices, and the number of storms
analyzed vary considerably,  as indicated in Table 8-1, depending  on project
priorities and  other relevant  activities.   As  a result, not all of the  sites
are incorporated in the summary presented below.  The Washington Area Council
of Governments  (WASHCOG) conducted a particularly  thorough and comprehensive
investigation of  control  techniques, particularly  detention basins.   They
have prepared several  useful and informative  analyses of performance results
on these devices.

Dry Basins

This is  a type  of detention  basin which  is  currently in  fairly  extensive
service in various  parts of the country.   The performance objective of such
basins is commonly called "peak  shaving", that is,  to limit the maximum rate
of runoff  to some preselected magnitude,  usually  a  maximum pre-development
rate.  The  purpose  is to  control  flooding and erosion  potential  in  areas
downstream of new  development.  Such basins employ a bottom outlet having a
hydraulic capacity  restricted to  the maximum allowable   flow.   Runoff from
smaller storms  flows along  the bottom of the  basin and is discharged without
restriction.  Flows  in excess of design are  backed up in the  basin tempor-
arily and ponding  occurs only during larger storms and for relatively  short
periods of time.  This class of retention basin is thus normally dry.

Performance  of  such  basins,  from a pollutant removal  aspect, range from
insignificant to quite poor.  Accordingly,  the limited data available are not
discussed in this chapter.

Wet Basins

This designation  covers  detention  basins which maintain a permanent pool of
water.   They may vary  considerably  in  appearance,  ranging   from  natural
ponds or small  lakes dedicated urban runoff  control to  enlarged sections in
                                     8-2

-------
           TABLE 8-1.  DETENTION BASINS MONITORED BY NURP STUDIES
Project
CO1 Denver
DC1 Washington, D.C.
IL2 N. Illinois
Mil Lansing
MI 3 Ann Arbor
NY1 Long Island
Site
North Ave
Burke
Lakeridge
Stedwick
Westleigh
Lake Ellyn
Dryer Farms
Grace St. N*
Grace St. S*
Waverly Hills
Pitt-AA
Traver
Swift Run
Unqua Pond
Design Type
Dry Basin
Wet Basin
Dry Basin
Dual-Purpose
Wet Basin
Wet Basin
Dry Basin
Wet Basin
Wet Basin
Wet Basin
Wet Basin
Wet Basin
Wet Basin
Wet Basin
No . Events
in/out
39/21
60/35
49/41
48/34
41/45
29/23
2/8
23/21
20/22
35/30
6/6
5/5
5/5
8/8
*  These are oversized storm drains installed below street level.  Inverts of
   control sections are below the  general grade  line,  so a permanent pool is
   maintained.
constructed drainage systems.  Runoff  from  an  individual storm displaces all
or part  of the prior  volume,  and the residual is  retained until  the  next
storm event.  This pattern may or may not be modified by natural base inflows
during dry weather depending on the local situation.

Detention basins  utilizing this design  concept  have been shown by  the  NURP
studies to be capable of highly  effective performance  in urban runoff appli-
cations,  as  summarized  below.   Although  performance  characteristics  of
individual basins ranged from poor to excellent,  analysis shows these differ-
ences to be attributable  to the size of the basin  relative  to the connected
urban area  and  local  storm characteristics.  Performance data also  indicate
that in addition  to removal  of particulate  forms or pollutants by sedimenta-
tion, . some  basins  exhibit  substantial  reductions  in  soluble  nutrients
(soluble  phosphorus,  nitrate +  nitrite nitrogen).   This  is attributed  to
biological processes which are permitted to proceed in the  permanent  water
pool.
                                     8-3

-------
There are a  number of ways to characterize detention basin performance.  The
primary basis  selected by NURP  for  doing so is to  define performance effi-
ciency  on  the  basis  of  the  total pollutant mass  removed over  all storms.
This provides  a meaningful general  measure for comparison,  is  relevant for
water quality  effects associated  with extended time  scales  (e.g., nutrient.
load  impacts  on  lakes) ,  and conforms  with the  capabilities  of  the NURP
analysis methodology  developed  to provide a planning-level  basis for esti-
mating  cost/benefit differences  in size or application  density  of this type
control.

Table 8-2 tabulates performance  in terms of reduction in pollutant mass loads
over all  monitored storm events.   The analysis methodology  developed under
the NURP program  activities suggests  that  performance should be expected to
improve as the overflow rate  (QR/A =  mean  runoff  rate * basin surface area)
decreases and  as the volume ratio  (VB/VR = basin volume * mean runoff volume)
increases.   The NURP  basins  used in  the  analysis are  listed  in increasing
order of expected performance capabilities.

The  wide  range of relative  basin  sizes provided  by  this data base  is
apparent, and  performance is  seen to generally  correspond with expectations.
The  poorest  performance  occurs  in  a basin  with an  average overflow rate
during  the  mean   storm  of  about six times  the median  settling  velocity
(1.5 ft/hr)  of particles  in urban runoff.  In  addition,  less than 5 percent
of the mean  storm runoff  volume  remains in this basin following the event, to
be  susceptible  to  additional  removal  by  quiescent  settling   during  the
interval between storms.  The basins which exhibit high removal efficiencies,
at the  other end of  the  scale,  have  size  relationships  which  result  in the
mean  storm  displacing  only about  10 percent of  the  available  volume,  and
producing  overflow rates which are  only  a small  fraction of  the  median
particle settling velocity.

This rationale is  described more completely  in  the  supporting NURP document
on  detention  basins   identified earlier.  The  testing  of  the  methodology
against the  NURP monitoring  data is  presented,  and the basis  for the per-
formance projections illustrated below is documented.

Figure  8-1 presents a projection  of  removal  efficiency of urban runoff de-
tention devices as a function  of basin  size  relative  to the  contributing
catchment  area and regional  differences  in  typical rainfall patterns.  The
removal rates  apply for  TSS,  which are all settleable,  and must be factored
by the  particulate/soluble fraction  of  other pollutants  which  have signif-
icant soluble  fractions  in urban runoff.    It applies  for the specific basin
average depth  and area runoff coefficient indicated  (which are fairly typical
based on  NURP data).  However  performance relationships  could  be different
than indicated based on relevant local values for the controlling parameters.

An alternate approach  for characterizing performance of detention basins con-
centrates on the variable characteristics of  individual  storm events and how
these are  modified by the  detention  device.  A comparison of  the  mean and
coefficient  of variation of  basin inflow  and  discharge concentrations pro-
vides   another measure of  performance of  an urban  runoff detention device.
                                     8-4

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                                 TABLE 8-2.  OBSERVED PERFORMANCE OF WET DETENTION BASINS

                                          REDUCTION IN PERCENT OVERALL MASS LOAD
Project
and
Site
Lansing
Grace St. N.
Lansing
Grace St. S.
Ann Arbor
Pitt-AA
Ann Arbor
Traver
Ann Arbor
Swift Run
Long Island
Unqua
Washington, D.C.
Westleigh
Lansing
Waverly Hills
NIPC
Lake Ellyn
No.
of
Storms
18
18
6
5
5
8
32
29
23
Size Ratios
QR/A
8.75
2.37
1.86
0.30
0.20
0.08
0.05
0.04
0,10
VB/VR
0.05
0.17
0.52
1.16
1.02
3.07
5.31
7.57
10.70
Average Mass Removals - All Monitored Storms (Percent)
TSS
(-)
32
32
5
85
60
81
91
84
BOD
14
3
21
(-)
4
(TO
•
69
•
COD
(-)
(-)
23
15
2
C=7)
35
69
•
TP
(-)
12
18
34
3
45
54
79
34
Sol.P
(-)
23
(-)
56
29
•
71
70
•
TKN
(-)
7
14
20
19
(-)
27
60
•
N0_ _
2+3
(-)
1
7
27
80
(-)
•
66
•
T.Cu
(-)
(-)
•
•
•
•
•
57
71
T.Pb
9
26
62
•
82
80
•
95
78
T.Zn
(-)
(-)
13
5
(-)
•
26
71
71
00
I
Ul
          Notes:  (-)  Indicates apparent negative removals.


                   •   Indicates pollutant was not monitored.

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CD
I
                                                                                     BASIN DEPTH = 3.5 FT
                                                                                     RUNOFF COEF = 0.20
                                                                                      RM = ROCKY MT (DENVER)
                                                                                      NW = NORTHWEST
                                                                                      NE = NORTHEAST
                                                                                      SE - SOUTHEAST
                                                                                                                  CM
                                                                                                                  m
                                                                                                                  CO
                                      BASIN SURFACE AREA AS % OF CONTRIBUTING CATCHMENT AREA
                             Figure 8-1.  Regional Differences in Detention Basin Performance

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This approach  provides  more useful  information for  subsequently evaluating
the effect of  controls  on water quality  impacts on rivers  and  streams.   As
evident from the  discussion in Chapter 6, reductions  in the mean  and vari-
ability of  runoff concentrations  (and the  inferred  reduction  in mean  and
variability of runoff rates) will have a significant beneficial effect on the
severity of impacts on flowing streams.

Table 8-3  summarizes detention  basin performance  when  assessed  in  this
manner.  It should be noted that in most cases  more  inlet  storm events were
monitored than  discharge  events, and  that  some inlet  events  do not  have a
matching discharge  event  and vice-versa.   Further,   for  the larger  basins
where  storm  inflow  displaces  only  a  fraction  of  the  basin  volume,   it  is
unlikely that  influent  and effluent for a specific event  represent the same
volume of water.   The tacit assumption in  this analysis is that the  inflow
events which  were monitored  provide  a  representative  sample  of  the total
population of all influent  event mean  concentrations  (EMCs).   Similarly,  the
monitored effluent events  are assumed to be a  representative sample  of  all
basin discharge EMCs.   The appropriateness  of this assumption  is  obviously
more  uncertain where the  number  of  individual storm  events monitored  is
small.

For each basin  influent and effluent, the arithmetic  mean  and variance were
computed based on the relationships  for lognormal distributions.  The percent
reduction in  the mean  concentration  and  the  coefficient  of variation  are
tabulated (Table 8-3).  Note that where the  number  of monitored events shown
in this table  differ from those  listed in Table 8-2,  it is  because the mass
removal  computations were restricted  to  synoptic  storms   (i.e.,  matching
influent and effluent results were available for an event).

Performance characteristics are  generally consistent  using  either approach,
even  though  each  displays  a different  type  of   information.   Performance
improves with detention basin  size  relative to  catchment size  and hence  the
magnitude of the runoff processed.   Giving  greater  weight  to the sites moni-
toring large numbers of storms,  indications  are that  for most pollutants  wet
ponds also generally result in a considerable reduction in the variability of
pollutant concentrations.

A significant  exception  to this  tendency to reduce variability  is shown  for
the  soluble  nitrogen forms  (NC>2 +  NC>3) .   The positive removal efficiency
indicated by  reduction of mean concentrations must  be attributed to bio-
logical  processes rather   than  sedimentation.  A  substantial   increase  in
variability is  consistently indicated by  the data.  Among  the heavy metals,
lead which is nearly all in particulate form shows  significant reductions in
variability.    Copper and  zinc which  have  high (40 to 60  percent)  soluble
fractions show an ambiguous pattern with regard  to changes in variability.

In  a  few of  the cases  where atypical results are indicated,  unique local
conditions suggest  plausible  explanations.   For example,  at  the  Ann Arbor
(Traver) site, erosion  from an unstabilized  bank at the outlet of this newly
constructed basin  is attributed to  the  poor  suspended solids  removal  ob-
served.  The  poor  removal characteristics  at  the  Unqua site  for TKN  and.
nitrate may be associated with  the  significant wildfowl population  at this
site.
                                     8-7

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            TABLE  8-3.   OBSERVED PERFORMANCE OF  WET  DETENTION BASINS
                   (PERCENT REDUCTION IN  POLLUTANT CONCENTRATIONS)
(a)   Mean EMC
Project
and
Site
Lansing
Grace St. N.
Lansing
Grace St. S.
Ann Arbor
P1tt-AA
Ann Arbor
Traver
Ann Arbor
Swift Run
Long Island
Unqua
Washington, D.C.
Westlelgh
Lansing
Waverly Hills
NIPC
Lake Ellyn
No.
of
Storms
(1)
23/20
18/17
6/6
5/5
5/5
8/8
40/40
35/30
25/20
Percent Reduction In Mean EMC
TSS
(6)
22
38
0
83
34
83
87
92
BOD
(26)
4
17
(66)
11
(TOC=
.
52
•
COD
15
(3)
23
12
(3)
26)
33
52
64
TP
(10)
6
28
37
(38)
38
59
69
61
Sol.P
(26)
0
(2)
63
21
.
70
56
62
TKN
11
(5)
11
19
25
(31)
19
30
•
N02+3
(1)
(20)
8
28
77
(10)
28
54
82
T.Cu
(9)
25
•
•
•
•
10
53
88
T.Pb
39
14
59
.
86
78
•
93
91
T.Zn
(9)
7
22
19
.
•
10
58
87
(b)   Coefficient  of Variation of EMCs
Project
and
Site
Lansing
Grace St. N.
Lansing
Grace St. S.
Ann Arbor
P1tt-AA
Ann Arbor
Traver
Ann Arbor
Swift Run
Long Island
Unqua
Washington, D.C.
Westlelgh
Lansing
Waverly Mills
NIPC
Lake Ellyn
No.
of
Storms
(1)
23/20
18/17
6/6
5/5
5/5
8/8
40/40
35/30
. 25/20
Percent Reduction In Coef of Variation of EMCs
TSS
14
(7)
17
14
(5)
(87)
46
38
44
BOD
49
(59)
(6)
(109)
39
(TOC=
.
S
•
COD
35
39
10
58
50
66)
(26)
69
41
TP
(7)
13
28
(3)
(150)
47
15
34
71
Sol.P
(13)
0
(84)
42
0
.
20
26
48
TKN
30
20
37
(ISO)
20
19
41
(8)
•
N02+3
0
21
0
(82)
(150)
(66)
(280)
(198)
(115)
T.Cu
0
17
•
•
•
.
0
(22)
60
T.Pb
45
18
53
.
26
65
•
34
19
T.Zn
(31)
15
(5)
0
.
.
(14)
(36)
41
       Notes:  (1)  In/Out; numbers are approximate, and vary with pollutant. Removals in parentheses indicate
                  negative removal.

              Dot  (•) indicates pollutant either not monitored or number of observations is too small for
                  reliable estimate of percent reduction.
                                             8-8

-------
The ability of detention basins to reduce coliform bacteria concentrations is
also of considerable  interest  because  of the significant  impact  these urban
runoff contaminants exert on recreational  or  shellfish harvesting beneficial
uses.  Other  than at the  Unqua site  of  the Long  Island NURP project,  the
number of observations made for indicator  bacteria  were too few to support a
reliable  assessment  of  the  ability of  detention  basins  to effect  quality
improvements.  However, extensive data of  this nature  were secured on deten-
tion basin  influent  and effluent  during all monitored storms  at  the Unqua
site.

Since coliform bacteria  have a high rate of die-off in natural waters,  per-
formance characteristics based on  total mass  reductions are not particularly
meaningful.   The  Unqua site data  were analyzed  to evaluate performance in
terms of reductions in concentration levels.  Over  eight monitored storms at
this site, covering a wide range in storm size,  the mean EMC (MPN/100 ml)  was
reduced by 94 percent for total coliform,  91  percent for fecal  coliform,  and
95 percent  for  fecal   streptococcus  bacteria.    Variability   of  bacteria
concentrations in  the pond outlet  increased, with effluent coefficients of
variation  ranging from  about  10  to  100 percent  greater  than  influents.
Accordingly,  detention  basins  employing  permanent pools  (wet  ponds)  are
indicated to be capable of substantial  reductions in indicator  bacteria.

Dual Purpose Basins

In the absence of  a  well defined  terminology, we have  adopted  this designa-
tion to  define basins  that  are normally  dry,  and hence retain  their  full
potential for flood control, but  which have outlet designs that  result  in a
slow release rate  for  detained  storm  flows.   Detention  time  is  extended
considerably compared with that provided  by dry basins  employing conventional
outlet designs.

One of the detention basins examined by .the WASHCOG NURP project, was of this
type.   This  project  designates  such designs  as  "Extended   Detention  Dry
Ponds."  The pond was converted from a  conventional dry pond by replacing the
outlet pipe with a perforated riser enclosed in. a gravel jacket.  The modifi-
cation was designed to detain  stormwater runoff for up to 24  hours,  instead
of the 1 to 2 hours typically observed  in conventional  dry ponds.

For undetermined reasons, average detention periods during the  study were in
the  order  of 4 to  8 hours,  and hence considerably shorter than  the design
objective.  Nevertheless, based on monitoring of more  than  30  storm events,
the  removal  of particulate  forms  of urban pollutants  was  typically high and
comparable to the performance efficiency  of wet ponds.

Observed  removals for  this  site   (Stedwick)  are  summarized   by  Table 8-4,
showing percent reductions in both mass and concentration distributions.   The
principal differences in performance of dual purpose basins compared with wet
basins are suggested by the available data to consist of the following:

     -  Soluble pollutants (e.g.,  soluble P and Nitrate/Nitrite) are not
        effectively reduced because  of the absence of  a permanent pool
        within which  biological reactions  have an  opportunity  to occur
        in addition to sedimentation.
                                     8-9

-------
     -  The  variability  of  pollutant  EMC's   does  not  appear  to  be
        modified to the extent that this occurs in wet ponds.
                TABLE 8-4.  PERFORMANCE CHARACTERISTICS OF A
                        DUAL-PURPOSE DETENTION DEVICE

               (Stedwick Site - Washington Area NURP Project)
Pollutant
TSS
COD
Total P
Sol P
TKN
Organic N
N°2+3
T. Cu
T. Pb
T. Zn
Percent Reduction In
Pollutant Mass
Load Over All
Monitored Storms
64
30
< 15
1
•
30
10
•
84
57
Poll
El-
Mean
63
41
11
(4)
8
•
13
•
•
43
.utant
IC's
Coef Var
(31)
17
0
(13)
(11)
•
6
•
•
33
Although the performance characteristics of basins of this type are indicated
to be  somewhat inferior to  the  potential  offered by wet  ponds,  there are a
number  of  considerations  which  make dual  purpose basins  highly attractive
candidates for quality  control of urban runoff.   These include the fact that
flood  control  requirements are  likely to be more economically obtained than
with wet  basins  and that  many  existing stormwater management  basins  may be
readily modified to  significantly enhance  their  capability for improving the
quality of  urban runoff.   In  areas where  ordinances  requiring conventional
stormwater  management  ponds are already  in  existence,   the  only  changes
required would be an alternate specification of the outlet design.

Costs

The information  presented  here  is intended to provide  an  order of magnitude
estimate of the cost of providing different levels of control of urban runoff
pollutant discharges, when wet detention devices are used as the best manage-
ment practice  (BMP).  The  summary is based on  the size  versus  performance
relationship presented  earlier in Figure 8-1 and on the size versus cost re-
lationships presented below.
                                    8-10

-------
The  analysis  is  based  on  cost  information  developed by  the WASHCOG  NURP
project and discussed in detail in one of their  project  reports produced for
the NURP effort.  Construction cost  estimates as a function  of basin volume
are  shown  by  Figure 8-2,  adopted from  this source.  This  estimate  compares
quite favorably with a similar cost/size relationship developed previously by
the Soil Conservation Service (SCS).

The cost relationship shown by this  figure  applies  to "dry pond" designs and
relates only to expected cost of construction  activities.   For specific cost
estimates,  the results derived from  Figure 8-2 should be modified  as appro-
priate, in accordance with the following:

     -  The highly  variable  capital cost  of land  acquisition  is  not
        included in the construction costs.

     -  Outlet modifications to provide a dual purpose basin design will
        increase construction costs by about 10 to 12 percent.

        Pond designs  which meet  the  peak shaving requirements  of  con-
        ventional (dry)  pond designs, but also provide a  permanent  pool
        of water may have costs up to 40 percent greater  than indicated
        by the cost relationship  shown by Figure 8-2.                       —
     -  An  additional allowance  equal  to  25 percent  of  construction
        costs is  suggested to allow  for planning,  design,  administra-
        tion, and construction related contingencies.

     -  Operation  and maintenance  costs are  estimated  to  involve  an
        annual  expenditure  of  approximately  3 to 5 percent  of  base
        construction cost, that is,  before application of the 25 percent
        factor for  design,  planning,  and administration.  The  total  is
        composed of  two  elements:   2 to 3 percent of  construction cost
        estimates the annual cost of  routine maintenance  and upkeep;  an
        additional  1 to 2 percent  of construction  cost  estimates  the
        annualized  cost  of  sediment  removal operations  for a  10 year
        clean-out cycle.

Planning  agencies  often  distinquish  between "on-site"  controls, which  are
applied  to  relatively  small  urban  catchments,  often  installed  by  the
developer of an urban property, and "off-site" controls, which involve larger
basins and  serve  substantially larger urban drainage areas.  Because of  the
appreciable  economy  of scale  inherent  in the cost relationship  defined by
Figure 8-2,  this   factor  must  be   taken into account in  developing  cost/
performance  summaries  for  urban   runoff  quality  control  using  detention
basins.  Accordingly, the control costs presented below for wet basin designs
indicate the differences  based on  the size of the urban  catchment the basin
is designed to serve.

Figure 8-3 presents  a planning level  approximation of both present value  and
annual cost  of  wet detention basins.  Amoritization  of costs is  based on a
20 year basin life and an interest rate of 10 percent.
                                    8-11

-------
    100.000
at


ci
LU
a
a
u
o


CJ

oc

CO


o
u
10,000
      1.000
                                                                      COST = 77.4VDS1
                                                                                                             CSI



                                                                                                             CO
                                                                                                             m

                                                                                                             CO
         1.000
                                  10.000                         100,000



                                     VOLUME OF STORAGE-V (CUBIC FEET)
1.000,000
                   Figure 8-2.   Average Stormwater Management  (Dry)  Pond Construction

                                   Cost Estimates Vs. Volume of  Storage

-------
                                     APPROXIMATE REMOVAL EFFICIENCY FOR TSS
                                                                                                                 APPROXIMATE REMOVAL EFFICIENCY FOR TSS
                     2000
                     1500
00
U)

5*5
1*"   1000
                      500
                               20-30
                               0.05
                                          IL.
                                         30-50
                                                                 SIZE OF URBAN  /
                                                                 AREA SERVED  /
                                                                 BY BASIN =  20 ACRES
                                          0.10
                                                        0.25
                                                                  0.50
                                                                             1.0
                                            DETENTION BASIN SIZE
                               (BASIN AREA AS A PERCENTAGE OF URBAN DRAINAGE AREA)
                                                                                           ££!
                                                                                                   200
                                                                                                   tso
                                                                                                   100
                                                                                               £    50
                                                                                              2030
                                                                                                %
5*75
 %
BO-90
 %
                                                                                                                              SIZE OF URBAN ,
                                                                                                                              AREA SERVED .
                                                                                                                              BY BASIN = 20 ACRES
     95%

•/
                                                                                                             0.05
                                                                                                                       0.10
                                                                                                                                    0.25
                                                                                                                                               0.50
                                                                                                                                                          1.0
                                                                                                            DETENTION BASIN SIZE
                                                                                               (BASIN AREA AS A PERCENTAGE OF URBAN DRAINAGE AREA)
                                                           BASIS WET BASINS-CONSTRUCTION COSTS 40% GREATER THAN FIGURE 82
                                                                ANNUAL O&M COST-5% OF BASE CONSTRUCTION COST
                                                                BASIN AVG DEPTH  3.5 FEET
                                                                INTEREST RATE    10%
                                                                BASIN LIFE      20  YEARS
                                                      Figure  8-3.    Cost of  Urban Runoff  Control Using
                                                                         Wet  Detention Basins

-------
The performance  levels  associated with a particular basin  size  are  shown at
the top  of  the plots as  a range for long-term  average  removal  efficiencies
for TSS.  The  range associated with a particular  size  reflects  the  regional-
differences in performance which  can be  expected (Figure 8-1)  as a result of
regional differences in storm characteristics.  Approximate removal efficien-
cies for pollutants other than TSS can  be estimated by  factoring the indi-"
cated TSS removal  by the particulate fraction of  the pollutant  of interest.
The supplementary  NURP  document  dealing  with detention basins  provides  in-
formation to  permit  further refinement.   A  more  concise  local  summary  of
cost/performance  relationships can  be  developed  using  the  NURP data  and
analysis methods,  if  local rainfall and  land  use characteristics,  and design
and planning preferences are utilized.

The  generalized .relationships shown  by  Figure 8-3 can  be  summarized  as
follows, if an urban catchment size of 20 to 40 acres is taken to represent a
typical  "on-site"  control  application,  and  an  "off-site"  application  is
reflected by detention basins serving 640 to 1000 acres.
Control
Application
On-site

Off-site

Approximate
Level of
Control
(% TSS Reduction)
50
90
50
90
Cost Per Acre of Urban Area
(Approximate)
Present
Value
$500 - $700
$1000 - $1500
$100
$250
Annual
Cost
$60 - $80
$125 - $175
$10
$25
RECHARGE DEVICES

Control measures which enhance the infiltration of urban runoff are indicated
by the NURP studies to be techniques which are practical to apply and capable
of effective  reductions  in urban runoff quantity and  quality.   This finding
is based on project  reports and on the results of a screening analysis using
a probabilistic  methodology  described in a  supplementary NURP  document  on
detention basins.

The  issue  of  the potential contamination  of groundwater  aquifers due  to
enhanced  infiltration  of  urban storm  runoff  has been  discussed  in  the
previous  chapter  dealing  with  receiving  water  impacts.    The  favorable
findings support  further  consideration of  this technique.  At the same time,
it  must be  emphasized  that  specific local  conditions  may make  recharge
inappropriate.   Such conditions can  include steep slopes,  soil conditions,
depth  to  groundwater,   and  the  proximity  of  water   supply wells.   Sound
planning and  engineering judgement must be applied to determine the accept-
ability of this control approach in a  local situation.

However, where local conditions premit, a wide variety of design concepts are
available  for use.   These  range  from off-site  applications consisting  of
                                    8-14

-------
large retention basins,  to  small individual on-site units which include in-
filtration pits and trenches, percolating, catch  basins,  and  porous pavement.
The operating  principle  is the  same  regardless of  size or  design concept.
The important  elements are  the  surface area provided  for  subrsurface perco-
lation and  the storage volume  of the device.   Overall  performance  will  be
related to the size of the recharge device relative to the urban catchment it
serves and the permeability (infiltration rate)  of the soil.

The context  in which  the  performance capabilities  of recharge  devices are
evaluated is  the  extent to which urban  runoff  is "captured"  and prevented
from discharging directly to  surface  waters.  Pollutant  removals are reduced
in direct proportion to the runoff volume which is intercepted and recharged.
Load reductions will be further enhanced if quality improvements occur in the
portion of the runoff which is not  captured.  The  combination of soil infil-
tration rate and percolating area provided determines the "treatment rate" of
a specific  recharge  device.   When  storm  runoff  is applied to  the device at
rates of flow  equal  to or less  than this  rate,  100 percent  of the runoff is
captured during that event.  At  higher  applied rates,  the   fraction  of the
runoff flow in excess of the  treatment  rate will  escape and  discharge  to
surface waters.

Most recharge devices other than porous pavement also provide storage volume.
This improves  performance  capability because portions of the  excess runoff
can be retained for subsequent percolation when applied rates subside.  Over-
flow to surface water occurs only when the available storage is exceeded.

The Long Island  and Metropolitan Washington, D.C.  (WASHCOG)  NURP projects
examined the  performance  of  on-site  recharge  devices.   An interconnected
system of  percolating catch  basins in Long  Island  was  estimated  to reduce
surface water discharges  of  storm  runoff  by  more  than 99 percent.   The
WASHCOG project  found that a porous pavement  site produced  pollutant  load
reductions  on the  order  of  85  to  95 percent  depending  on  the  specific
pollutant  considered.   An  infiltration  trench  studied  by  this  project
produced reductions in the order of 50 percent.

The NURP analysis methodology was employed in a  screening analysis to assist
planning evaluations  by  establishing the  relationship  between performance
level  and  device  size and soil  percolation rates.   Figure 8-4  presents  a
planning level estimate  of  the  influence of  size,  soil  characteristics, and
regional rainfall differences on the performance of recharge devices.

The upper  plot illustrates the  significant  effect regional  differences  in
rainfall characteristics  can  have  on  the performance of  identical recharge
devices.   Basin depth, soil percolation rate, and  runoff coefficient for the
urban  catchment  are  the  same  for  each  case.   The performance differences
result from differences in the intensity  and  volume of the average storms in
each region.  Basin size is represented on the  horizontal axis by expressing
the percolation area that is provided as  a  percentage of  the area  of the
contributing urban catchment.   For  example,  a recharge device  with a perco-
lating surface area equal to.  0.10 percent of  an  urban  catchment represents a
design  which  provides (43,560 sq ft/acre x 0.10/100% =) 43.5 square feet of
                                    8-15

-------
   100


    90


    80


|   «


z   60

|

1   50

|
|   40
£

*   30


    20


    10
NORTHWEST

  /
  NORTHEAS
       '  /
       OUTHEAST
                      AVERAGE DEPTH = 5 FT.

                 SOIL PERCOLATION RATE = 3 INCHIHOUR

                        RUNOFF COEF = 0.25
     .01
                          0.05       .10                  0.5        1.0

                         PERCOLATING AREA AS % OF CONTRIBUTING CATCHMENT AREA
                                                                                      5.0

                          H = 5,  JH = 1
                                                                         GREAT LAKES PRECIP
                                                                                MEAN   C.V.
                                                                         VOLUME  0.25    1.8
                                                                         INTENS  O.OS    1.4
                                                                         DELTA   72     1.0
                                                                             HV = 0.2
                                                                      P = SOIL PERC RATE (INIHR)
                                                                      H = BASIN DEPTH (FEET)
     .01
                           0.05       .10                   0.5        1.0

                         PERCOLATING AREA AS % OF CONTRIBUTING CATCHMENT AREA
  Figure  8-4.   Long Term Average  Performance  of  Recharge  Devices
                                            8-16

-------
percolating  surface  area for  each  acre of  urban catchment it  serves.   The
long-term average reductions in urban  runoff volume  and pollutant load which
can be expected will be approximately 35 percent in the southeast, 45 percent
in the northeast and 65 percent in the Pacific northwest.

The lower plot illustrates the much  more  significant influence of the amount
of storage volume provided (incidated by basin average depth),  and the perme-
ability of the soil through which the storm runoff must percolate.  The rain-
fall  characteristics  used in this  analysis are  typical  of the  Great Lakes
region  of the  United States  and  are roughly  comparable  to  those  in  the
northeastern part of the  country.  As  might be  expected,  the permeability of
the soil in which the recharge device is constructed has a dominant influence
on performance capability.  However significant compensation for low percola-
tion  rates  can  be  achieved  by  increases  in percolation area  and storage
volume.

When  the  screening  analysis  results are considered  along  with the favorable
results from the NURP studies, the NURP findings indicate that with a reason-
able degree of design flexibility to compensate for soils with lower percola-
tion  rates,  recharge  devices  provide a very effective  method  for control of
urban runoff.
STREET SWEEPING

End-of-pipe urban  runoff  pollutant concentrations have  been commonly viewed
as being, a  function  of two prime factors — accumulation  of contaminants on
street surfaces  and  rainfall/runoff washoff.  The .postulated beneficial ef-
fect  of  street  sweeping  was  to reduce  contaminant accumulation.   Prior to
NURP, emphasis of street sweeping investigations was placed on street surface
mechanisms  (e.g., accumulation and washoff)  and sweeper equipment performance
in removing street dirt.  While these studies provided valuable insights into
the possible benefits of street sweeping, measurements of end-of-pipe concen-
trations are  the only  direct measures  of  street sweeping  effectiveness in
water quality terms.

Recognizing this,  NURP was designed  to provide  a  large data base  of urban
runoff water  quality concentrations for both  swept and unswept conditions.
In addition, the NURP street sweeping projects gathered and evaluated data on
atmospheric deposition  (i.e., wetfall and dryfall),  street surface accumula-
tion and washoff, and street sweeper removal rates and costs.  The individual
project reports  look at these other issues,  and  the  results are not repeated
herein.  Of prime  interest  and provided below  is the effectiveness of street
sweeping in reducing end-of-pipe urban  runoff pollutant concentrations  (and
ultimately receiving water  impacts).  The findings  presented below are based
upon  the analyses performed  by the  individual  projects,  as well  as other
statistical  techniques,  and  are  generally  consistent with the  projects'
conclusions.
                                    8-17

-------
Five of the  28 NURP  prototype  projects had the evaluation of street sweeping
as a central element of their work plans.  These projects were as follows:
                     Project                    Number of Sites

              Castro Valley, CA                        1

              Milwaukee, WI                            8

              Champaign-Urbana, IL                     4

              Winston-Salem, NC                        2

              Bellevue, WA                             2
Long Island,  NY and  Baltimore, MD  also  collected  limited  street  sweeping
data.  The experimental designs of the  projects  varied in detail,  but essen-
tially followed either a paired basin or serial basin approach to gather test
and  control  data,  with some  projects  using  both  approaches.  The  general
concept was that during a test period street sweeping would be more intensive
(up to daily) and thorough  (e.g., with operator training, parking bans, etc.)
than during control periods when the streets were to be swept as usual or not
at all.

In the paired basin approach, two adjacent  or close-by basins were operated
in a  "control" or unswept  mode for certain periods  of time  to  establish a
baseline comparison, and then street sweeping was performed in a "test" basin
while the other remained as a control.  The data provided an overall compari-
son between  basins  as well as  a  series of  synoptic  events  for both basins.
In the serial approach, a basin was periodically operated in either a control
or test mode,  with  the  periods adjusted so that all seasons of the year were
represented  in each mode.  Here,  rather  than  synoptic data pairs,  one has
data strings for both "swept" and "unswept" conditions.

There  are  no  well  established or prescribed  procedures for  evaluating the
possible reduction  in runoff concentrations due  to  street  sweeping.   Issues
of concern  include  storm size  and  intensity effects,  time  since  last rain,
ability to select truly paired basins,  seasonal effects, etc.  In an attempt
to sort out these issues, an exploratory data analysis was performed, and the
following findings were established:

     -  Street  sweeping  has not been  found to change  the  basic proba-
        bility  distribution of event  mean concentrations.  That is, the
        fundamental  assumption of random,  lognormal behavior  is  valid
        during  sweeping operations.

     -  The  runoff  quality characteristics  of  a basin  during  swept or
        unswept  conditions  is  best measured by  the  maximum likelihood
        estimator of  the  median EMC,  with  the  uncertainty  indicated by
        the 90 percent confidence interval of the median.
                                    8-18

-------
        There is in most cases no significant  correlation  (and in a few
        cases a weak negative correlation)  between EMCs and storm runoff
        volume.  EMCs  and  storm runoff  intensities are also  generally
        uncorrelated (but in isolated cases exhibit a weak positive cor-
        relation) .   The  implication of these  findings is  that differ-
        ences  in concentrations between swept  and unswept  conditions
        will be largely unaffected by the size of the  storms  during the
        monitoring periods.   Because  of this  independence  between con-
        centration and  volume,  effects  of  sweeping on EMCs  will also
        indicate effects on mass pollutant loads.

     -  EMCs for synoptic  events on paired basins  are,  in  general, not
        significantly correlated or in some cases are weakly correlated;
        however, over  the  longer  term  (e.g.,  mean,  frequency  distribu-
        tion,  etc.),  there are no  significant differences between the
        distribution of EMCs of paired basins.   These  results  show that
        basins are independent  from storm to  storm, and thus, compari-
        sons  between basins  should  not be   attempted using  synoptic
        events,  but  the basins do  have similar  statistical  properties
        and thus can be considered  paired.

To evaluate the effectiveness of street sweeping, a series of bivariate plots
were  constructed for projects  using the  serial  basin approach.  The site
median  EMCs  for swept  and unswept  conditions  form the data pairs  of  the
plots.  Bivariate plots  are presented in Figure  8-5 for TSS,  COD,  TP, TKN,
and  Pb  concentrations, respectively.   Each plot  contains  swept  or  unswept
conditions for multiple project sites.   The  assumption' of the  analysis  is
that  a  large enough data base was  collected  to negate  any temporal effects
such  as seasonal,  land use conditions,  parking patterns, and  other possible
factors  (as  noted  earlier,  storm  volume  and  intensity  effects  are  not
believed to  be significant).   Examining the bivariate  plots,  it is observed
that,  for  the  NURP data,  the median  concentrations  are  as  likely  to  be
increased as decreased by street  sweeping.   Further,   street  sweeping never
produced  a  dramatic   (e.g.,  >50 percent)   reduction  in concentrations  (or
loads).

Street  sweeping  performance,  as measured by  the percent change  in the site
median EMC,  for  selected NURP sites is graphically displayed  in Figure 8-6.
The results are for five constituents (TSS,  COD, TP, TKN, and Pb) at 10 sites
nationwide) .   For  each site, the median  EMC  is  based on  data from between
10 and  60 events, with 30 events typical.  Based on Figure 8-6  a number  of
important observations are evident.

        Performance as measured by  change  in  site  median EMC  is highly
        variable.

        Where   reductions   occur,   they   generally   occur    for  all
        constituents.

        Reductions never exceed 50 percent.
                                    8-19

-------
       (TSS Concentrations)
                                        (TKN Concentrations)
  «n
1
  200
  100
1 0     100    200    300    400
         UNSWEPT TSS Ing/D
                                           10
                                           U>
                                                  1.0    10    Ifl
                                                     UNSWEPT TKN Img/D
       (COD Concentrations)
                                        (Pb Concentrations)
  ISO
8 100
         SO     100    ISO
            UNSWEPT COD (mg/0
                                           as
                                           0.4
                                               oj    0.4    0.6
                                                 UNSWEPT Pb Img/D
       (TP  Concentrations)
   '•Or
           UNSWEPT TP Img/n
       Figure 8-5.  Bivariate  Plots of Median EMCs  for
                   Swept  and Unswept Conditions
                                 8-20

-------
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STATE FAIR
WISCONSIN
RUSTLER
WISCONSIN
SURREY DOWNS
WASHINGTON
LAKE HILLS
WASHINGTON
RESIDENTIAL
NORTH CAROLINA

CBD
NORTH CAROLINA
MATTIS S
ILLINOIS
MATTIS N
ILLINOIS
JOHN ST. S
ILLINOIS
JOHN ST. N
ILLINOIS
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                                                            Pb
                                                            TKN
                                                            TP
                                                            COD
                                                            TSS
       Nouonoau 01/113 %
        Figure 8-6.   Street Sweeping Performance
                           8-21

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In  evaluating  the results,  it  is  critical  that  the  uncertainty  in  the
estimate of median EMCs based on limited observed data,  and  thus  the uncer-
tainty in  performance estimates, be  assessed.   This is  especially true  for
the cases .of apparent increases in concentrations indicated by Figure 8-6.

For each of  the 10 sites considered, the 90 percent  confidence  intervals of
the site median EMCs were computed as indicated in Figure 8-7.  This analysis
indicates  that  there is  generally  no significant difference  between median
EMCs for swept  and unswept  conditions.   The  implications of this analysis of
uncertainty are as follows:

     -  Based on statistical  testing, no significant reductions  in EMCs
        are realized by street sweeping.

     -  The  indicated  changes   in   site  median  EMCs  (increases  or
        decreases)  are much  more likely  due to random sampling than
        actual effects of sweeping operations.

     -  Benefits  of street sweeping  (if any) are  masked by  the  large
        variability of  the  EMCs,  therefore the benefit is certainly not
        large (e.g.,  >50  percent), and  an even larger site  data  base is
        required to further identify the possible effect.

     -  In  the  above  context,   the hypothesis  that   street  sweeping
        increases  EMCs  is  generally  not shown by  the  data,  though  it
        could occur in isolated, site specific cases.

Urban runoff loads  are  the  product of long term   (e.g.,  annual) runoff volume
and event  mean  concentration.  Under this definition,  statements  concerning
EMCs also hold for loads.

OTHER CONTROL APPROACHES

Several best management practices (BMPs) in addition to  those discussed above
should be identified on the basis that local planning efforts determined them
to be  practical to apply and to have  the  potential to provide significant
improvements  in  the  quality characteristics  of  urban runoff.   They  are
grouped  together  in  this  section  and  discussed only  briefly,  principally
because,  for  one  reason  or  another, sufficient  data  to characterize  their
performance capabilities was  not developed during the NURP program.

Grass Swales

Three grass swales  were monitored by the Washington, D.C. area NURP project.
No significant  improvement  is urban  runoff quality  was indicated for pollut-
ants  analyzed.   Increases  in zinc  concentration which were observed  were
attributed to mobilization of zinc from  the galvanized culverts which carried
runoff under  the driveways at the monitored  residential sites.   However the
project  study  report  concluded  that   modifications  which  would  increase
residence  of  runoff in the swales and  enhance infiltration capability could
make this BMP effective for control of urban runoff.
                                    8-22

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             Figure  8-7.  Effect  of Street Sweeping  on

                   Site Median EMC Values  (Cont'd)
                                  8-24

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The Durham, New  Hampshire  NURP project monitored performance  of a carefully
designed artificial  swale  which  received runoff  from a  commercial  parking
lot.   Over  11 monitored storms,  both soluble  and particulate  fractions  of
heavy metals  (Cu, Pb,  Zn,  and Cd) were reduced by  approximately 50 percent.
Reductions in COD, nitrate, and ammonia were on the order of 25 percent.  The
swale  did  not prove to  be effective  in  reducing concentrations  or  organic
nitrogen, phosphorus,  or  bacterial  species.   It should  be  noted that  the
performance  capabilities  indicated   are  based   only  on  the  concentration
changes produced in the stonnwater which passes completely through the swale.
To the extent that infiltration of a portion of  the runoff is effected by a
swale, load reductions would be increased in proportion.

The NURP results  suggest that grass  swales represent  a  practical and poten-
tially effective  technique for control of urban  runoff  quality;  that design
conditions are of major  significance;  and that additional study is necessary
to establish such parameters.

Wetlands

The potential of either natural  or artificially  created wetland areas  to
effect favorable  modification of  urban runoff pollutant loads  (particularly
sediment, nutrients, and heavy metals) has been  widely  suggested.   The NURP
experience reinforces  this expectation,  but has  not  developed  the detailed
performance data  to permit  either characterizing general performance capa-
bilities or identifying general design principles and parameters.  Additional
study will be required to develop such information.

Miscellaneous

This  category encompasses a variety  of  BMPs  which were identified  at  the
local  level as  techniques  of quality  control  which appeared  to be relevant
for the  circumstances which were operative.   They are grouped  under this
category because  (a) their  applicability tends  to  be  site-specific  rather
than general, and (b)  while  their effectiveness  as a  BMP may be substantial
on a relatively  small  spatial scale, the broad-scale  effect  on urban runoff
loads has not been possible to document.

BMPs  in  this category include erosion  control  practices and  urban  house-
keeping practices.   As an example of the former, the  Little  Rock, Arkansas
NURP project  widened  and  stabilized  (with  rip  rap)   a  segment of an urban
stream to reduce  erosion potential.   The  Baltimore NURP project data clearly
indicated the substantial  difference  in urban  runoff quality  that can result
from the general level of cleanliness maintained in an urban neighborhood.
                               8-25/8-26 blank

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                                 CHAPTER 9
                                CONCLUSIONS
INTRODUCTION

The Nationwide Urban Runoff Program has  addressed  such issues as quantifying
the characteristic  of  urban runoff, assessing  the water quality  effects on
receiving water bodies attributable to urban runoff discharges, and examining
the effectiveness of  control practices  in  removing the pollutants  found in
urban runoff.   This chapter summarizes  NURP's  conclusion relating  to these
issues and is based on  the  results presented in Chapters 6,  7, and 8 of this
report.  Conclusions reached  by the individual NURP projects  are  also pre-
sented to further support the results of the national level analysis.

URBAN RUNOFF CHARACTERISTICS

General

Field monitoring  was  conducted to characterize urban runoff  flows  and pol-
lutant concentrations.  This  was  done  for a variety  of  pollutants  at a sub-
stantial number of  sites  distributed throughout the  country.   The resultant
data  represent a cross-section  of  regional  climatology,  land use  types,
slopes, and soil  conditions and thereby  provide a  basis  for identifying pat-
terns of similarities or differences and testing their significance.

Urban  runoff  flows and concentrations of  contaminants  are  quite  variable.
Experience shows  that substantial variations occur within a particular event
and from one event  to the  next at a particular  site.  Due  to the high vari-
ability of urban  runoff, a  large  number  of sites and storm events were moni-
tored, and a statistical  approach was  used  to  analyze the  data.  Procedures
are available for characterizing variable data without requiring knowledge of
or  existence  of  any  underlying  probability  distribution   (nonparametric
statistical procedures).  However, where a  specific type of probability dis-
tribution is known  to  exist,  the  information content  and  efficiency of sta-
tistical  analysis  is  enhanced.   Standard statistical procedures  allowed
probability  distributions  or  frequency  of occurrence  to  be  examined  and
tested.  Since  the  underlying  distributions were determined to be adequately
represented by the lognormal distribution, the log  (base e) transforms of all
urban runoff data were used in developing the statistical characterizations.

The event  mean concentration  (EMC),  defined as the  total  constituent mass
discharge divided by the total runoff volume, was chosen as the primary water
quality  statistic.   Event mean concentrations   were  based on  flow weighted
composite samples for  each event at each site   in  the accessible  data base.
EMCs  were  chosen as  the  primary water  quality characteristic subjected to
detailed analysis,  even though  it is recognized that mass loading character-
istics of urban runoff  (e.g.,  pounds/acre for  a specified  time interval) is
                                     9-1

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ultimately " the  relevant  factor  in many  situations.   The  reason  is  that,
unlike  EMCs,  mass  loadings are  very  strongly  influenced  by the  amount of
precipitation and runoff,  and  estimates  of typical annual mass loads will be
biased  by  the size of  monitored  storm events.  The most reliable  basis for
characterizing  annual  or  seasonal mass  loads  is  on  the  basis of  EMC and.
site-specific rainfall/runoff characteristics.

Establishing  the fundamental distribution as  lognormal  and the availability
of  a sufficiently  large  population of  EMCs  to provide reliability  to the
statistics derived has  yielded a  number of benefits, including the ability to
provide:

     -  Concise  summaries of highly variable data

     -  Meaningful comparisons of results from different sites, events,
        etc.

     -  Statements concerning  frequency  of occurrence.  One can express
        how often  values  will be  expected to  exceed various magnitudes
        of interest.

     -  A more  useful method of  reporting data  than the  use of ranges;
        one which is  less subject to misinterpretation

     -  A framework for examining "transferability" of data in a quanti-
        tative manner

Conclusions

1.  Heavy metals (especially copper,  lead and zinc) are by far the most pre-
    valent priority pollutant constituents found in urban runoff. End-of-pipe
    concentrations  exceed  EPA  ambient water  quality  criteria  and drinking
    water standards in  many instances.   Some of the metals are present often
    enough and in high  enough concentrations to  be potential threats to bene-
    ficial uses.

    All  13  metals  on  EPA's priority pollutant  list were  detected in urban
    runoff  samples,   and  all but  three  at frequencies of  detection greater
    than 10 percent.  Most  often  detected among  the metals were copper, lead,
    and zinc, all of  which  were found in at least  91 percent of the samples.

    Metal  concentrations  in  end-of-pipe  urban  runoff  samples  (i.e., before
    dilution  by receiving  water)  exceeded EPA's water quality  criteria and
    drinking  water standards numerous times.   For example, freshwater acute
    criteria  were exceeded by copper  concentrations  in 47 percent  of the
    samples and by lead  in 23 percent.   Freshwater chronic exceedances were
    common for lead  (94 percent),  copper  (82 percent), zinc  (77 percent), and
    cadmium   (48 percent).   Regarding  human  toxicity,  the  most significant
    pollutants  were  lead and  nickel,  and for  human carcinogenesis, arsenic
    and beryllium.   Lead concentrations violated  drinking  water criteria in
    73 percent of the samples.
                                      9-2

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    It should be stressed that the exceedances noted above do not necessarily
    imply that an actual  violation of standards will exist  in the receiving
    water body in question.  Rather, the enumeration of  exceedances serves a
    screening function to identify those heavy metals whose presence in urban
    runoff warrants  high priority for further evaluation.

    Based upon the much more extensive  NURP  data  set for total copper, lead,
    and zinc, the site median EMC values for the median urban site are:  Cu =
    34 yg/1, Pb = 144 yg/1, and Zn = 160 yg/1.  For the 90th percentile urban
    site the  values  are:   Cu  =  93 yg/lf Pb  =  350 yg/1, and  Zn = 500 yg/1.
    These values are suggested to be appropriate for planning level screening
    analyses where data are not available.

    Some individual NURP  project sites  (e.g., at DC1, MD1,  NH1) found unus-
    ually high concentrations of certain heavy metals  (especially copper and
    zinc) in urban runoff.  This was attributed by the projects to the effect
    of acid rain on  materials used for gutters, culverts, etc.

2.  The  organic  priority  pollutants were  detected less  frequently  and  at
    lower concentrations than the heavy metals.

    Sixty-three  of  a  possible 106 organics  were detected  in  urban  runoff
    samples.   The most  commonly   found  organic  was  the  plasticizer  bis
    (2-ethylhexl)  phthalate    (22 percent),   followed   by   the   pesticide
    ct-hexachlorocyclohexane  (a-BHC)  (20 percent).   An additional 11 organic
    pollutants  were  reported  at   frequencies  between   10  and  20 percent;
    3 pesticides, 3  phenols, 4 polycyclic aromatics, and a single halogenated
    aliphatic.

    Criteria  exceedances  were less  frequently observed among  the organics
    than the  heavy metals.  One unusually high pentachlorophenol concentra-
    tion of 115 yg/1  resulted in  exceedances  of  the  freshwater  acute  and
    organoleptic criteria.  This  observation and one for chlordane also ex-
    ceeded  the  freshwater  acute  criteria.   Freshwater  chronic  criteria
    exceedances  were  observed  for  pentachlorophenol,   bis   (2-ethylhexyl)
    phthalate, gamma-BHC, chlordane, and alpha-endosulfan.  All other organic
    exceedances were in  the human carcinogen category and  were most serious
    for  alpha-hexachlorocyclohexane  (alpha-BHC),  gamma-hexachlorocyclohexane
    (gamma-BHC or Lindane), chlordane, phenanthrene, pyrene, and chrysene.

    The  fact  that the  NURP priority pollutant monitoring effort was limited
    to two samples at each site leaves us unable to make many generalizations
    about those organic pollutants which occurred  only  rarely.  We can spec-
    ulate that their occurrences tend to be  very  site  specific as opposed to
    being a generally  widespread phenomena,  but much more data would  be re-
    quired to conclusively prove this point.

3.  Coliform bacteria  are  present  at high  levels  in urban runoff  and  can be
    expected  to  exceed  EPA water  quality criteria  during  and immediately
    after  storm  events  in many surface  waters,   even  those  providing  high
    degrees of dilution.
                                     9-3

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    Fecal coliform  counts  in urban runoff are typically in  the  tens  to hun-
    dreds of  thousand per  100 ml during warm  weather conditions, with  the.
    median for  all sites being around 21,000/100 ml.  During cold weather,
    fecal coliform counts are more typically in the 1,000/100 ml  range, which
    is the median  for all sites.  Thus, violations of fecal coliform stand—
    ards were  reported by  a number of NURP  projects.  High fecal coliform
    counts may  not cause actual  use  impairments,  in  some instances,  due to
    the location of the urban runoff discharges relative to swimming areas or
    shellfish beds and the  degree of  dilution/dispersal and  rate of die off.
    The same is true of total coliform counts, which were found to exceed EPA
    water quality criteria  in  undiluted urban runoff  at virtually every site
    every time it rained.

    The substantial  seasonal differences  noted above  do not correspond with
    comparable variations in urban activities.  The NURP analyses as  well as
    current  literature  suggest  that  fecal  coliform may  not  be the  most
    appropriate  indicator organism  for identifying  potential   health  risks
    when the source is stormwater runoff.

4.  Nutrients are generally  present in urban  runoff,  but with a  few individ-
    ual site exceptions, concentrations do  not  appear to be  high in compari-
    son with other possible  discharges to receiving water bodies.

    NURP data for total phosphorus, soluble phosphorus, total kjeldahl nitro-
    gen, and nitrate  plus nitrite as nitrogen were carefully examined.  Me-
    dian site EMC median  concentrations in  urban  runoff were TP  = 0.33 mg/1,
    SP =0.12.mg/1, TKN = 1.5  mg/1, and NO2+3 - N  = 0.68 mg/1.   On an annual
    load basis,  comparison  with  typical monitoring data,  literature  values,
    and design objectives for  discharges  from a well  run secondary treatment
    plant suggests  that  mean  annual  nutrient  loads  from  urban  runoff  are
    around an order of magnitude  less than those from a POTW.

5.  Oxygen demanding substances are present in urban runoff at concentrations
    approximating  those  in  secondary treatment plant discharges.   If dis-
    solved oxygen problems  are present  in receiving waters  of interest, con-
    sideration of urban  runoff controls as well as advanced waste treatment
    appears to be warranted.

    Urban runoff median site  EMC median concentrations of  9 mg/1 BODS  and
    65 mg/1 COD are reflected  in  the NURP data, with 90th percentile site EMC
    median values being  15  mg/1 BODS  and  140  mg/1  COD.  These concentrations
    suggest that, on an annual load basis, urban runoff is comparable in mag-
    nitude to secondary treatment plant discharges.

    It  can  be  argued that urban  runoff  is  typically well oxygenated  and
    provides increased stream  flow  and,  hence, in  view of  relatively long
    travel  times  to  the   critical  point,   that   dissolved  oxygen  problems
    attributable solely to urban  runoff should not be widespread occurrences.
    No NURP project specifically  identified a low DO condition resulting from
                                     9-4

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    urban runoff.   Nonetheless, there  will  be  some  situations where  con-
    sideration of urban runoff controls  for oxygen demanding substances in an
    overall water quality management strategy would seem appropriate.

6.  Total suspended solids concentrations in  urban  runoff  are fairly high in
    comparison with  treatment  plant discharges.   Urban  runoff control  is
    strongly indicated where water quality problems  associated with TSS,  in-
    cluding build-up of contaminated sediments, exist.

    There are  no formal water  quality  criteria for  TSS relating  to either
    human health or aquatic  life.   The  nature  of  the  suspended  solids  in
    urban runoff is different from those in treatment plant discharges, being
    higher in  mineral  and man-made products  (e.g.,  tire and street surface
    wear particles) and  somewhat lower  in  organic particulates.   Also,  the
    solids  in urban  runoff  are  more   likely  to  have  other  contaminants
    adsorbed onto  them.   Thus,  they cannot  be simply considered  as benign,
    nor  do  they only  pose an  aesthetic issue.   NURP  did  not examine  the
    problem of contaminated sediment build-up due to  urban  runoff,  but  it
    undeniably exists,  at least at some  locations.

    The suspended solids in urban runoff can also  exert deleterious physical
    effects by sedimenting  over egg deposition  sites,  smothering  juveniles,
    and altering benthic communities.

    On an annual load basis, suspended solids contributions from urban runoff
    are around an order of magnitude or  more  greater than  those from second-
    ary  treatment  plants.   Control of urban  runoff, as opposed to advanced
    waste treatment, should be  considered where  TSS-associated water quality
    problems exist.

7.  A  summary  characterization  of  urban runoff has been  developed  and  is
    believed to  be appropriate  for use   in estimating urban  runoff pollutant
    discharges from  sites where monitoring  data  are  scant or lacking,  at
    least for planning level purposes.

    As a  result  of extensive examination,  it was  concluded that  geographic
    location,  land use category  (residential, commercial, industrial park, or
    mixed), or other factors  (e.g.,  slope,  population density, precipitation
    characteristics)  appear to  be of little  utility in  consistently explain-
    ing overall  site-to-site  variability in urban runoff  EMCs or  predicting
    the  characteristics  of urban  runoff discharges from  unmonitored sites.
    Uncertainty  in  site  urban  runoff characteristics  caused  by high event-
    to-event variability at most sites  eclipsed  any site-to-site variability
    that might have  been present.   The  finding that EMC  values  are essen-
    tially not correlated with  storm runoff  volumes facilitates the transfer
    of urban  runoff characteristics  to unmonitored  sites.    Although there
    tend to be exceptions to  any generalization,  the suggested summary urban
    runoff characteristics given in Table 6-17 of  the report are recommended
    for planning level purposes as the best estimates, lacking local informa-
    tion to the contrary.
                                     9-5

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RECEIVING WATER EFFECTS

General

The  effects of  urban runoff  on  receiving  water  quality  are  highly site-
specific.   They  depend on the  type,  size,  and hydrology of  the water body;
the  urban  runoff quantity and  quality  characteristics;  the designated bene-
ficial  use; and  the  concentration  levels  of  the specific  pollutants  that
affect that use.

The  conclusions  which follow  are based  on  screening analyses  performed by
NURP,  observations and  conclusions  drawn by  individual NURP  projects  that
examined receiving water effects  in differing levels of detail and rigor, and
NURP's three levels  of problem definition.   Conclusions  are organized on the
basis  of  water body type:   rivers and streams, lakes,  estuaries  and embay-
ments,  and  groundwater  aquifers.    Site-specific   exceptions  should  be
expected,  but  the statements  presented are  believed to  provide an accurate
perspective on the general  tendency  of urban  runoff  to contribute signifi-
cantly to water quality problems.

Rivers and  Streams
1.  Frequent exceedances  of heavy metals ambient water  quality criteria for
    freshwater aquatic life are produced by urban runoff.

    The Denver  NURP project  found  that in-stream  concentrations  of copper,
    lead,  zinc,  and cadmium  exceeded State ambient water quality standards
    for the South Platte  River during essentially all storm events.

    NURP  screening analyses  suggest that  frequent exceedances of  both EPA
    24-hour  and maximum  water  quality criteria  for  heavy metals  should be
    expected on a relatively  general basis.

2.  Although a  significant  number  of  problem  situations could  result from
    heavy  metals  in  urban  runoff,   levels  of freshwater aquatic  life use
    impairment  suggested  by the magnitude and  frequency of ambient criteria
    exceedances were not  observed.

    Based upon the magnitude  and  frequency of freshwater aquatic life ambient
    criteria  exceedances,  one  would  expect  to  observe  impairment of this
    beneficial  use in  most  streams  that  receive  urban  runoff  discharges.
    However, those NURP  project  studies which examined this  issue did not
    report significant use  impairment problems associated  with urban runoff.

    The  Eellevue,  Washington NURP  project concluded  that toxic  effects of
    urban runoff pollutants did not appear to be a  significant factor.

    The  Tampa,   Florida  NURP project  conducted  biological  studies of the
    impact  of  stormwater  runoff  upon  the  biological  community  of  the
    Killsborough River.   They conducted animal bioassay experiments on five
    sensitive species  in  two samples of urban  runoff  from the Arctic   Street
    drainage basin.  Thirty-two bioassay experiments were  completed including
    22 acute tests and 10  chronic  tests.   Neither sample  of  stormwater was
    acutely  toxic to  test  organisms.  Long-term  chronic  experiments were
                                     9-6

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    undertaken with two species and resulted in no significant effects attri-
    butable to stormwater exposure.

    NURP screening  analyses  suggest that  the potential  of urban  runoff  to
    seriously impair this beneficial use will be strongly influenced by local
    conditions and the frequency of  occurrence  of concentration levels which
    produce toxic  effects  under the  intermittent,  short  duration  exposures
    typically produced by urban runoff.

    While the application of  the screening analysis to the Bellevue and Tampa
    situations supports the absence of a problem situation in these cases,  it
    also suggests that a  significant number of problem  situations  should  be
    expected.  Therefore, although not the general, ubiquitous problem situa-
    tion that  criteria exceedances  would  suggest,  there  are  site-specific
    situations in which urban  runoff could be expected  to cause significant
    impairment of freshwater  aquatic life uses.

    Because of  the inconsistency  between  criteria exceedances  and observed
    use  impairments due  to  urban  runoff,  adaptation  of current  ambient
    quality criteria to better  reflect  use  impacts where pollutant exposures
    are  intermittent  and  short duration  appears to  be  a useful area  for
    further investigation.

3.  Copper, lead and zinc appear to pose a significant threat to aquatic life
    uses in  some  areas of the  country.   Copper is suggested to be the most
    significant of the three.

    Regional differences in surface water hardness, which has a strong influ-
    ence on toxicity, in conjunction with  regional variations in stream flow
    and  rainfall  result  in significant differences in susceptibility to ad-
    verse impacts around the  nation.

    The  southern  and  southeastern regions  of the country  are  the  most sus-
    ceptible to aquatic life effects due to heavy metals,  with the northeast
    also a sensitive area,  although somewhat less so.

    Copper is the major toxic metal in  urban  runoff,  with  lead and zinc also
    prevalent but a problem  in more restricted cases.   Copper  discharges  in
    urban  runoff  are,  in  all but  the  most  favorable  cases,  a significant
    threat to aquatic life uses in the  southeast  and  southern regions of the
    country.   In  the  northeast, problems  would  be expected only  in rather
    unfavorable conditions (large  urban area  contribution  and high site con-
    centrations) .  In the remainder of the country (and for the other metals)
    problems would only be expected  under  quite unfavorable site conditions.
    These statements are based on total metal concentrations.

4.  Organic priority pollutants in urban runoff do not appear to pose a gen-
    eral threat to freshwater aquatic life.

    This conclusion is based on limited data on the frequency with which or-
    ganics are found in urban runoff discharges and measured end-of-pipe con-
    centrations   relative  to   published   toxic   criteria.   One  unusually
    high pentachlorophenol  concentration of  115 yg/1 resulted in the only
    exceedance  of the organoleptic criteria.  This observation and  one  for
                                     9-7

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    chlordane   exceeded  the   freshwater    acute    criteria.     Freshwater
    chronic  criteria   exceedances  were  observed   for  pentochlorophenol,
    bis    (2-ethylhexyl)    phlhalate,    y-hexachlorocyclohexane   (lindane),
    a-endosulfan, and chlordane.

5.  The physical  aspects  of urban runoff,  e.g., erosion and  scour,  can be a
    significant  cause  of habitat  disruption  and  can  affect  the  type  of
    fishery present.   However,  this  area  was  studied only  incidentally  by
    several of  the projects under the  NURP program and more concentrated
    study is necessary.

    The Metropolitan  Washington Council of Governments  (MWCOG)  NURP project
    did an analysis of fish diversity in the Seneca Creek Watershed,  20 miles
    northwest of Washington, D.C.  In this study, specific changes in fishery
    diversity  were  identified  due  to  urbanization  in  some  of  the  sub-
    watersheds.  Specifically, the number of fish species present are reduced
    and the  types  of  species present  changed  dramatically,  e.g.,  environ-
    mentally sensitive species were replaced with more tolerant species.  For
    example, the  Blacknose  Dace replaced  the  Mottled Sculpin.  MWCOG con-
    cluded that the changes  in fish diversity were  due to habitat deteriora-
    tion caused by the physical  aspects of urban runoff.

    The Bellevue, Washington  NURP project  concluded  that   habitat  changes
    (streambed  scour  and sedimentation) had  a  more  significant effect than
    pollutant concentrations,  for the changes produced by urbanization.

6.  Several projects identified possible problems in the sediments because of
    the build-up  of  priority pollutants  contributed wholly  or in part  by
    urban runoff.  However,  the  NURP  studies  in this area were few in number
    and limited in scope, and  the findings must be considered only indicative
    of the need for further study, particularly as to long-term impacts.

    The Denver  NURP project found significant  quantities of  copper,  lead,
    zinc,   and  cadmium  in river sediments.   The  Denver Regional Council  of
    Governments is concerned that during periods of continuous low flow, lead
    may reach levels capable of  adversely affecting fish.

    The Milwaukee NURP project reported the observation of elevated levels of
    heavy metals,  particularly  lead,  in the  sediments of a  river  receiving
    urban runoff.

7.  Coliform bacteria  are present at high levels in  urban runoff and can be
    expected to  exceed  EPA water  quality criteria  during  and immediately
    after storm events in most rivers and streams.

    Violations  of the fecal coliform standard  were  reported by  a  number of
    NURP projects.   In some  instances,  high fecal  coliform counts  may not
    cause  actual  use  impairments  due to  the location  of the  urban  runoff
    discharge relative  to swimming areas and the degree  of  dilution or dis-
    persal and rate of die off.

    Coliform bacteria  are generally accepted  to be  a useful  indicator of the
    possible presence  of  human pathogens when the source of  contamination is
    sanitary sewage.  However, no such relationship has been demonstrated for
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    urban runoff.  Therefore, the  use of coliforms as an  indicator of human
    health risk when the  sole  source of contamination is  urban  runoff,  war-
    rants further investigation.

8.  Domestic water supply systems  with  intakes  located  on  streams  in close
    proximity to urban runoff discharges are encouraged to check for priority
    pollutants which have been detected in urban  runoff,  particularly those
    in the organic category.

    Sixty-three of a possible 106 organics were detected in urban runoff sam-
    ples.   The  most   commonly   found  organic   was  the  plasticizer  bis
    (2-ethylhexl)  phthalate   (22  percent),   followed  by  the     pesticide
    a-hexachlorocyclohexane  (a-BHC)  (20 percent).   An additional  11 organic
    pollutants  were   reported  at  frequencies  between  10  and  20 percent;
    3 pesticides, 3 phenols, 4 polycyclic aromatics, and a single halogenated
    aliphatic.

Lakes

1.  Nutrients  in urban  runoff may  accelerate  eutrophication problems  and
    severely limit recreational  uses, especially  in  lakes.   However, NURP's
    lake  projects  indicate  that  the degree  of  beneficial use  impairment
    varies widely,  as does the significance of the urban runoff component.

    The Lake Quinsigamond  NURP project  in  Massachusetts  identified eutrophi-
    cation as  a major problem in  the lake,  with  urban runoff being a prime
    contributor of the critical nutrient phosphorus.  Point source discharges
    to the lake have been eliminated almost entirely.  However,  in spite of
    the abatement  of point sources,   survey data  indicate that the lake has
    shown little improvement over  the abatement period.   In particular, the
    trophic status of  the lake has shown no change,  i.e., it is  still clas-
    sified as  late mesotrophic-early eutrophic.   Substantial  growth is pro-
    jected in  the  basin,  and  there  is  concern  that Lake Quinsigamond will
    become more eutrophic.   A proposed water quality  management  plan for the
    lake includes the objective of reducing urban runoff pollutant loads.

    The Lake George NURP project in New York State also identified increasing
    eutrophication as a potential  problem  if current  development  trends con-
    tinue.  Lake George is not classified as eutrophic, but from 1974 to 1978
    algae production in the lake increased logarithmically.  Lake George is a
    very  long  lake,  and  the limnological  differences between the  north and
    south basins provide evidence  of  human  impact.  The more  developed,
    southern portion of the lake  exhibits lower  transparencies,  lower hypo-
    limnetic dissolved  oxygen  concentrations,  higher phosphorus  and chlor-
    ophyll £ concentrations, and a trend toward seasonal blooms of blue-green
    algae.  These differences in water quality indicators  are associated with
    higher levels  of cultural activities  (e.g.,   increased  sources of phos-
    phorus)  in the southern portion  of  the lake's watershed,  and continued
    development will tend to accentuate the differences.
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    The Lake George  NURP project estimated that urban  runoff from developed
    areas currently  accounts  for only 13.6 percent of  the  annual phosphorus.
    loadings to  Lake George as  a whole.   In contrast,  developed areas con-
    tribute 28.9 percent of the  annual phosphorus  load to the   NURP  study
    areas at  the south  end of  the  Lake.   Since there are  no  point source-
    discharges, this phosphorus loading is due solely to urban runoff.  These
    data  illustrate  the significant  impact  of  urbanization on phosphorus
    loads.

    The NURP screening  analysis suggests  that lakes  for which the contribu-
    tions of  urban  runoff are  significant  in  relation  to  other  npnpoint
    sources (even in the absence of point source discharges) are indicated to
    be highly susceptible to eutrophication and that urban runoff control may
    be warranted in such situations.

2.  Coliform bacteria discharges  in  urban  runoff  have a significant negative
    impact on the recreational uses of lakes.

    As was the case with rivers  and  streams,  coliform bacteria in urban run-
    off can cause  violations  of criteria for the recreational use of lakes.
    When unusually high  fecal coliform counts are observed,  they may be par-
    tially  attributable  to sanitary  sewage  contamination,   in which  case
    significant health risks may be involved.

    The Lake Quinsigamond NURP  project in  Massachusetts found that bacterial
    pollution was  widespread throughout  the  drainage  basin.   In  all  cases
    where samples were taken, fecal coliforms were in excess of  10>000 counts
    per  100 ml,  with conditions  worse in the  Belmont  street  storm drains.
    This project concluded  that  the  very high fecal coliform counts in their
    stormwater are at least partially  due  to  sewage contamination apparently
    entering the stormwater system throughout the local catchment.

    The sources  of  sewage contamination  are  leaking  septic tanks, infiltra-
    tion from sanitary sewers into storm sewers, and leakage at manholes.  In
    the  northern basin,  the  high  fecal  coliform  counts are  attributed to
    known sewage contamination sources on Poor Farm Brook.  The data from the
    project suggest that  it would be unwise to permit body contact recreation
    in the northern basin of the  lake during or immediately following signif-
    icant storm  events.   The project concluded  that disinfection at selected
    storm drains should be  considered in the future, especially  if the sewage
    contamination cannot be eliminated.

    The Mystic River NURP project in Massachusetts  found various areas where
    fecal coliform counts  were extremely high  in  urban  stormwater.   Fecal
    coliform levels  of up  to  one million with an  average  of 178,000/100 ml
    were  recorded  in Sweetwater  Brook, a  tributary to  Mystic River, during
    wet weather.   These  high  fecal coliform levels  were specifically attrib-
    uted  to surcharging in  their  sanitary  sewers,  which  caused  sanitary
    sewage  to  overflow  into  their  storm  drains via the  combined manholes
    present in this catchment.  Fecal coliform levels above the  class B fecal
    coliform standard of 200 per  100 ml were found in approximately one-third
    of the samples tested in the  upper and lower forebays of  the Upper Mystic
    Lake and occasionally near  the lake's  outlet.   In addition, Sandy Beach,
    a public  swimming   area on Upper Mystic Lake,  exceeded  the  State fecal
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    coliform criteria in July of 1982, and warnings that swimming may be haz-
    ardous to public health were posted for several days.  It is important to
    note that  sewage  contamination of surface waters  is a major  problem in
    the watershed.   The project concluded  that  urban runoff  contributes to
    the bacteria  load during wet  weather but,  comparatively, is  much less
    significant than the sanitary sources.

Estuaries and Embayments

1.  Adverse effects of urban runoff  in marine  waters will be a highly speci-
    fic local  situation.   Though estuaries and embayments were  studied to a
    very  limited  extent  in NURP,  they  are  not  believed  to be  generally
    threatened by urban runoff, though specific  instances where use  is im-
    paired or  denied can  be  of significant local and  even  regional  impor-
    tance.   Coliform  bacteria  present  in  urban  runoff  is  the  primary
    pollutant of concern,  causing  direct  impacts  on shellfish harvesting and
    beach closures.

    The significant  impact of  urban runoff on shellfish harvesting has been
    well documented by the Long Island, New York NURP project.  In this proj-
    ect, stormwater  runoff was identified  as  the major  source  of bacterial
    loading to marine waters and,  thus,  the indirect cause of the denial of
    certification by the New York  State Department of Conservation for about
    one-fourth of  the  shellfishing  area.  Much  of this  area is  along the
    south shore, where  the annual  commercial shellfish  harvest  is valued at
    approximately $17.5 million.

    The Myrtle Beach, South Carolina  NURP project found that stormwater dis-
    charges from the City of Myrtle Beach directly onto the beach showed high
    bacterial counts for short  durations  immediately after storm events.  In
    many instances these counts violated EPA water quality criteria for aqua-
    tic life and contact recreation.  The high bacteria counts, however, were
    associated with standing pools formed at the  end of collectors for brief
    periods following the  cessation  of rainfall  and before the runoff perco-
    lated into the  sand.   Consequently,  the threat  to public  health was not
    considered great enough to warrant closure of the beach.

Groundwater Aquifers

1.  Groundwater aquifers that receive deliberate  recharge of urban runoff do
    not appear to be imminently  threatened  by  this practice at the two loca-
    tions where it was investigated.

    Two NURP projects  (Long Island and Fresno) are situated over sole source
    acquifers.  They have  been  practicing recharge with urban runoff for two
    decades or more at some sites,  and extensively investigated the impact of
    this practice on the quality of  their groundwater.   They both found that
    soil processes  are  efficient in retaining urban runoff pollutants quite
    close to  the  land  surface,  and  concluded that  no  change in  the  use of
    recharge basins is warranted.

    Despite the fact that some of these basins have been in service for rela-
    tively long  periods of time and pollutant breakthrough of the upper soil
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    layers has  not occurred, the ability  of the soil to  continue  to retain
    pollutants is unknown.  Further attention to this issue is recommended.

CONTROL EFFECTIVENESS

General

A limited number  of techniques for the control of urban  runoff quality were
evaluated by  the  NURP program.   The  set is considerably  smaller  than prev-
iously published  lists of potential management  practices.   Since the control
approaches  that  were  investigated were  selected  at the  local level,  the
choices may be taken as  an initial  indication of local perceptions regarding
practicality and  feasibility from the standpoint of implementation.

Conclusions

1.  There is a  strong  preference  for  detention  devices,  street sweeping, and
    recharge devices  as  reflected  by the  control  measures selected  at the
    local level for detailed investigation.  Interest was also shown in grass
    swales and wetlands.

    Six NURP  projects  monitored  the  performance of a total  of 14 detention
    devices.   Five  separate  projects  conducted  in-depth  studies  of  the
    effectiveness of street sweeping  on  the control  of urban runoff quality.
    A  total  of 17  separate study catchments were  involved in  this effort.
    Three NURP projects  examined  either  the potential of recharge devices to
    reduce discharges  of urban runoff to surface waters  or  the potential of
    the practice  to contaminate groundwaters.  A total  of 12 separate sites
    were covered  by this  effort.

    Grass swales  were  studied by two NURP  projects.   Two swales in existing
    residential areas, and one experimental  swale constructed to serve a com-
    mercial parking lot were studied.

    A  number  of NURP  projects  indicated interest in  wetlands  for improving
    urban runoff  quality at early stages of the program.  Only one allocated
    monitoring activity to this control measure, however.

    Various other management practices were  identified as having local inter-
    est by  individual  NURP projects,  but  none  of  them was  allocated the
    necessary resources  to be  pursued to a point which allowed an evaluation
    of  their ability  to  control  pollution  from  urban  runoff.   Management
    practices  in  this category  included  urban  housekeeping  (e.g.,  litter
    programs, catch basin  cleaning,  pet ordinances)   and  public information
    programs.

2.  Detention basins are  capable  of providing very  effective removal of pol-
    lutants  in  urban  runoff.   Both  the design  concept  and the  size  of the
    basin in relation  to the urban area served have  a critical influence on
    performance capability.

    Wet basins   (designs which maintain a  permanent water  pool)   have the
    greatest performance capabilities.   Observed pollutant reductions varied
    from excellent  to  very poor in the basins which were monitored.  However,
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    when basins  are  adequately sized,  particulate  removals  in  excess  of
    90 percent (TSS,  lead)  can be obtained.   Pollutants with significant sol-
    uble fractions in urban runoff  show lower reductions;  on the order  of
    65 percent for total P and approximately  50  percent  for BOD,  COD,  TKN,
    Copper,  and Zinc.  Results  indicate  that biological processes  which are
    operative in the  permanent  pool produce significant reductions (50 per-
    cent or  more)  in soluble  nutrients,  nitrate and soluble  phosphorus.
    These performance characteristics are indicated by both the NURP analysis
    results  and conclusions reached by individual projects.

    Dry basins,  (conventional stormwater management  basins), which  are de-
    signed to attenuate peak runoff rates and  hence only very briefly detain
    portions of flow from the larger storms, are indicated  by NURP data to be
    essentially ineffective for reducing pollutant loads.

    Dual-purpose basins (conventional dry basins  with modified outlet struc-
    tures which significantly extend detention time)  are suggested by limited
    NURP data  to  provide  effective reductions  in urban runoff  loads.   Per-
    formance may  approach  that of wet ponds;  however, the  additional proc-
    esses which reduce soluble  nutrient  forms do  not  appear to be operative
    in these basins.   This design concept is  particularly promising because
    it represents a  cost  effective approach  to combining flood  control and
    runoff  quality  control  and  because of  the potential for  converting
    existing conventional stormwater management ponds.

    Approximate costs of wet pond designs are estimated to  be in the order of
    $500 to  $1500 per acre  of  urban area  served, for on-site applications
    serving  relatively small urban areas, and  about $100 to  $250 per acre of
    urban area for  off-site  applications   serving   relatively large  urban
    areas.   The costs reflect present value  amounts which  include both capi-
    tal and operating costs.  The difference  is  due  to an  economy of scale
    associated with large  basin volumes.  The range  reflects differences in
    size required to produce particulate removals in  the order of 50 percent
    or 90 percent.  Annual costs per acre of urban area served are estimated
    at $60 to $175,  and $10 to $25 respectively.

3.  Recharge Devices are capable of providing very effective control of urban
    runoff pollutant discharges to surface waters.  Although continued atten-
    tion is warranted,  present evidence does  not indicate  that significant
    groundwater contamination will result from this practice.

    Both individual project results and NURP screening analyses indicate that
    adequately sized recharge devices are capable of providing high levels of
    reduction in  direct  discharges of urban  runoff  to surface  waters.   The
    level of  performance  will depend on both the size of  the unit  and the
    soil permeability.

    Application will  be restricted to areas where conditions are favorable.
    Soil type,  depth  to  groundwater, land  slopes,   and  proximity of  water
    supply  wells  will  all  influence the  appropriateness  of this  control
    technique.
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    Surface accumulations  which  result from the high efficiency  of  soils to
    retain pollutants,  suggest  further attention in applications  where dual
    purpose recharge  areas also serve  as  recreational fields  or playground"
    areas.

4.  Street sweeping is generally ineffective as a technique for improving the
    quality of urban runoff.

    Five NURP projects  evaluated street  sweeping  as  a  management practice to
    control pollutants  in  urban  runoff.  Four of  these  projects concluded
    that  street sweeping  was  not  effective  for this  purpose.   The  fifth,
    which had  pronounced  wet and  dry  seasons, believed that  sweeping just
    prior to the rainy  season could produce some  benefit  in terms of reduced
    pollution in urban runoff.

    A large data base  on  the  quality of  urban  runoff from  street  sweeping
    test sites was obtained.  At 10 study  sites selected  for detailed analy-
    sis, a total of 381 storm events were monitored under control conditions,
    and an additional 277 events during periods when  street  sweeping opera-
    tions were in effect.   Analysis of  these  data indicated that no  signifi-
    cant reductions in pollutant concentrations in urban runoff were  produced
    by street sweeping.

    There may be special cases in which street cleaning applied at restricted
    locations or times of year  could provide  improvements in  urban  runoff
    quality.   Some examples that have been suggested, though not demonstrated
    by the NURP program, include periods following snow melt or leaf  fall, or
    urban neighborhoods where the general  level of  cleanliness could be sig-
    nificantly improved.

5.  Grass swales  can  provide moderate improvements  in  urban  runoff  quality.
    Design conditions are  important.   Additional study  could significantly
    enhance the performance capabilities of swales.

    Concentration  reductions of about 50 percent  for  heavy  metals,  and
    25 percent  for  COD,  nitrate,  and ammonia  were observed  in one  of the
    swales studied.   However the swale  was  ineffective  in  reducing concen-
    trations  of organic  nitrogen,  phosphorus,  or  bacterial  species.   Two
    other swales  studied failed to demonstrate  any quality  improvements in
    the urban runoff passing through them.

    Evaluations by the  NURP projects  involved concluded,  however, that this
    was an attractive control  technique whose performance could be  improved
    substantially by application of appropriate design considerations.  Addi-
    tional study to develop such information was recommended.

    Design considerations  cited  included slope, vegetation type and mainte-
    nance, control of flow velocity  and residence  time,  and  enhancement of
    infiltration.  The  latter  factor  could  produce load  reductions greater
    than  those  inferred from concentration changes  and effect reductions in
    those pollutant  species which  are  not  attenuated by flow  through the
    swale.
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6.  Wetlands are considered to be a promising technique for control of urban
    runoff quality.  However, neither performance  characteristics nor design
    characteristics in relation to performance were developed by NURP.

    Although a number of projects indicated  interest,  only one assigned NURP
    monitoring activity to a wetland.  This  was  a  natural wetland, and flows
    passing though  it  were uncontrolled.  Results suggest  its  potential to
    improve quality,  but  the  investigation  was  not  adequate  to associate
    necessary design factors to performance capability.  Additional attention
    to this  control technique would  be useful,  and should include factors
    such  as the  need  for  maintenance  harvesting to prevent  constituent
    recycling.

ISSUES

A number  of issues  with respect  to  managing  and controlling  urban runoff
emerge from the conclusions  summarized above.   In  some instances they repre-
sent  the  need  for additional  data/information or for  further  study.   In
others they point to the need for follow-up  activity by EPA, State, or local
officials to assemble  and  disseminate what is already  known regarding water
quality problems caused by urban runoff and solutions.

Sediments

The nature and scope of the potential long-term  threat posed by nutrient and
toxic pollutant accumulation in the sediments of urban lakes and streams re-
quires further study.  A related issue is  the safe and environmentally sound
disposal  of  sediments collected  in  detention basins  used  to  control urban
runoff.

Priority Pollutants

NURP clearly demonstrated that many priority pollutants can  be found in urban
runoff and noted that a serious human health risk could exist when water sup-
ply intakes are in  close proximity to urban  stormwater discharges.  However,
questions related to the sources, fate,  and  transport  mechanisms of priority
pollutants borne  by urban  runoff  and their  frequencies  of occurrence will
require further study.

Rainfall pH Effects

The relationship  between pH and heavy metal  values in urban  runoff has not
been established  and  needs  further study.   Several NURP  projects (mostly in
the northeastern states)  attributed high heavy metals concentrations in urban
runoff to the effects of acid rain.  Although it is quite plausible that acid
rain increases the level of pollutants in urban runoff and may transform them
to more toxic and more easily assimilated forms, further study is required to
support this speculation.

Industrial Runoff

No truly  industrial  sites  (as  opposed to  industrial parks)  were included in
any of  the NURP projects.   A  very limited  body of data  suggests, however,
that runoff from industrial sites may  have  significantly higher contaminant
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levels than runoff  from other urban land use sites, and this issue should be
investigated further.

Central Business Districts

Data on  the  characteristics of urban runoff  from central business districts
are quite  limited  as  opposed to other  land use  categories  investigated by
NURP.  The data do suggest,  however, that  some  sites  may produce pollutant
concentrations  in runoff that are  significantly higher than those from other
sites in a given urban  area.  When combined with  their typically high degrees
of imperviousness,  the  pollutant loads from central business districts can be
quite high indeed.   The  opportunities  for  control in  central  business dis-
tricts are quite limited, however.

Physical Effects

Several  projects  concluded  that  the physical  impacts of  urban  runoff upon
receiving waters have  received too little attention and,  in  some cases, are
more important  determinants of beneficial use  attainment than  chemical pol-
lutants.  This  contention requires much more detailed documentation.

Synergy

NURP did not evaluate  the synergistic effects that might result from pollut-
ant concentrations  experienced in stormwater runoff,  in association with pH
and temperature ranges  that occur  in the receiving waters.  This type of in-
vestigation might  reveal that  control  of a specific  parameter,  such as pH,
would adequately reduce an  adverse synergistic  effect caused by the presence
of other pollutants in  combination and  be  the  most cost effective solution.
Further investigations  should include this issue.

Opportunities for Control

Based upon the  results  of NURP's  evaluation of  the performance  of urban run-
off controls,  opportunities for significant  control  of urban runoff quality
are much greater for  newly developing  areas.   Institutional considerations
and availability of space are the key factors.   Guidance on  this issue in a
form useful  to  States  and urban planning authorities  should  be prepared and
issued.

Wet Weather Water Quality Standards

The NURP experience suggests  that  EPA  should  evaluate  the possible need to
develop  "wet weather" standards, criteria, or modifications to ambient crite-
ria  to  reflect differences in impact due  to  the  intermittent,  short dura-
tion  exposures characteristic of  urban runoff and  other  nonpoint source
discharges.

Coliform Bacteria

The  appropriateness of using coliform  bacteria as indicator  organisms for
human health risk where the source is exclusively urban runoff warrants fur-
ther investigation.
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Wetlands

The use of wetlands as a control measure is of  great interest in many areas,
but the  necessary information on  design performance  relationships required
before cost effective applications can be considered has not been adequately
documented.   The  environmental  impacts  of  such  use  upon wetlands  is  a
critical issue which, at present, has been addressed marginally, if at all.

Swales

The use  of grass swales was  suggested by two  NURP projects to  represent a
very  promising  control  opportunity.   However,  their  performance is  very
dependent upon design  features about which information  is  lacking.  Further
work to address this deficiency and appropriate maintenance practices appears
warranted.

Illicit Connections

A number of the NURP projects identified what  appeared to be illicit connec-
tions of  sanitary  discharges  to  stormwater sewer systems,  resulting in high
bacterial counts and dangers  to  public health.  The costs  and complications
of locating and  eliminating  such connections may pose a substantial problem
in urban areas, but the opportunities for dramatic improvement in the quality
of  urban stormwater  discharges  certainly  exist where  this  can  be  accom-
plished.  Although  not  emphasized in the NURP  effort, other than  to assure
that the selected monitoring  sites were  free  from sanitary sewage contamina-
tion, this BMP is clearly a desirable one to pursue.

Erosion Controls

NURP  did not  consider  conventional erosion  control  measures because  the
information base concerning them  was considered to be  adequate.   They are
effective, and their use should be encouraged.

Combined Sewer Overflows

In order to address urban runoff from separate storm sewers, NURP avoided any
sites  where  combined  sewers  existed.   However,  in  view of their relative
levels  of contamination, priority should be  given  to  control  of combined
sewer overflows.

Implementation Guidance

The NURP studies have greatly increased  our  knowledge of the characteristics
of urban runoff, its effects  upon designated  uses, and of  the performance
efficiencies of  selected control measures.   They have also confirmed earlier
impressions that some States and  local communities have actually begun to
develop  and  implement  stormwater  management  programs  incorporating  water
quality  objectives.   However, such  management  initiatives  are,  at present,
scattered  and  localized.   The experience  gained from such  efforts  is both
needed and sought  after by many  other States and localities.  Documentation,
                                     9-17

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evaluation,  refinement and transfer  of.management and  financing mechanisms/
arrangements, of  simple  and reliable  problem assessment methodologies, and of
implementation  guidance  which can  be used by planners  and officials  at the'
State and  local  level are  urgently needed as is  a forum for  the  .sharing of
experiences  by  those already involved, both among themselves  and  with those
who are about to  address nonpoint source  issues.
                          US. EPA Headquarters Libran,
                          1PnnpMailCOde32^
                          120° Pennsylvania Avenue NW
                            Washington DC  20450
                                      9-18

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