FINAL REPORT
OF THE
as
111
o
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.
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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.
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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).
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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
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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
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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
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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
2-9
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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
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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.
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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
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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.
4-3
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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)
4-8
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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.
4-10
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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
-------
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
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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.
-------
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
-------
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
-------
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
-------
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
-------
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
-------
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
-------
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
-------
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
-------
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
-------
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
-------
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
-------
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
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-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
MAI
MD1
Mil
NCI
NH1
NY3
TNI
WAI
WI1
(
) 11
|R RRR
ICMRR R
1 1
IR
1 R
1 RR C
) 11
10 21
r~
I RR
R R I
J
1 R
A M
R
MM M
1 R
r
M
RR|
C
10 21
10 31
R
R C F
1
RMR
M
MC
C
C 1
10 3
)0 4
n
1
1
C
1
R
1
1
RR
R
A
10 4
10 51
M
R
C
C
I
I]
90 5
10 6C
n
M 1
R
I]
C
10 6
10
791
M£ C 12882
•>* 1973
? ^ 11247
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 |
R
Rl\
1
1
1
£ > 2031
* £ 1726
R RM
I I
CRM
|cc
IRR 1
(RRI
R RMC R I
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
CZ M i
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
1 M R M MR 1
I
1 C R 1
1 C MMM M 1
IM MMI
IR C 1
C
1 C 1
R R 1
1 1
i
9.9
1 R RM RffRI12.2
C R R 1
IRMC R 1
M 1
1 R R 1
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
0 0.5 1
SITE n 2
-IT103 1 ' * '
/ / f —
0 0.5 t
(a) Significantly
0 0.5 1
C-VIUA IT.
;0 1.5 2.0 _ R-CHERRY
=
*•"•••• n Jjii,*.. *uc
" C-VIUA IT.
CUPPER 90S CONFIDENCE LIMIT B-tlBIC
« IE on M-NQRTH AVt.
.0 1.5 2.0 C-VIUA IT
R-IISIC
R-CHERRV
Different Sites »:ANOHHVAVE.
R-BIG DRV C.
R-I18IC
R-CHERRV
M-NORTH AVE.
C-VIUA IT.
B-BIG ORV C.
B- 11 SIC
R-CHERRV
R-ASBURV
fl-BIG DRV C.
B-I1SC
fl-CHERDV
R-BIG DRV C.
M-NORTH AVE.
C-VIUA IT.
0 1.5 2.0 R-CHERRV
',
Jfi 4 , M-ifO^TH AVE
'$/. C-VIUA IT.
7^ ""' '* H-HIU UHV C.
1 — *
l
h
h
' )
t» • • t
'//;
y/.
, $
*v/
\ +Y/'
\- '-»
( — *-
I — *-
t—
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4
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////
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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
2.0
C-IORMA
M- WILDER
C-NORMA
M- WILDER
M-JESUIT
M- WILDER
M-JESUIT
C-IORMA
M-WILDER
M-JESUIT
C-MORMA
fl-YQUflG
M-WO.OE8
M- JESUIT
R-YQUK6
C-NORMA
I—
r—
.
,
_ ;
•
i
M
//\
S/A
/ft
,
,
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1
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i
1—4
t— *
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* *• • '
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7
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xd
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1
,
— » «
BOD
TOT. P
TKN
N02+3.N
TOT. CU
TOT Pb
i TQT ZN
0.5 1.0 1.5
2.0
R-DUFIEF
R-LAKERIDGE
B-WESTLEIGH
R-FAIRIOGE
R-STEBWICIC
R-STRATTOI
R-DUFIEF
fl-UKEHIDGE
R-WESTLEHSH
B-fAIRIDGE
fl-STEOWICK
H-STRATTDI
R-OUFIEF
R-LAKERIDGE
fl-WESTLEIGH
R-FAIRIDGE
H-STEOWICK
B-STRATTOI
R-DUFIEF
R-tAKERIDGE
fl-VKESTLEIGH
R-FAIRIOGt
R-STEDWIH
.R-STRATTOI
R-DUFIEF
R-LAKERIDGE
R-WESTLEIGH
R-FAIRIDGE
R-STEDWICK
R-STRATTO»
R-OUFIEF
R-LAKERIOGE
R-WESTIEIGH
R-FAIRIOBE
R-STEDW1CK
R-STRATTOI
R-OUFIEF
R-UWERIOGE
ft-WESTUIGH
R-FAIRIDGE
R-STEDWICK
R-STRATTOI
R-DUFIEF
R-LAKERIDGE
B-WESTLEIGH
R-FAIRIDGE
H-STEBWICK
R-STRATTOI
R-OUFIEF
R-UKERIDGE
R-WESTLEIGH
R-FAIRIDGE
B-STEDWICK
R-STRATTOI
1 • 1
m
h
t-
2%
30
M
't
i__ ;
h '
h- *
i
i— *— i
h- *
h-*
l-#
H
H-
• — 1
\
i—+Z
^
1 ,. 1
* — 1
<
4
1^. .)
^
4
H
—t
— *
H
>— I
-H
— — *
H ^ (
-*•! i
; * i
!l
• i
4
TSS
COD
TOT. P
SOLP
TKN
N02+3-N
TOT. CU
TOT. Pb
TOT. ZN
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
1.0
1.5
2.0
R MATTIS S.
M-MATTIS N.
R-JOHN N.
R-JOHN S.
DMATTIC C
M— MATTIS N
R_ IflHN M
n— junii ra.
R— inmu 9.
R— MATTIS S
M MATTIS N
R— JOHN M
R— JOHN S
DMA-Trie o
M M ATTIC M
IVI — MAI HO fll.
o milM M
n — jutin n.
D intiM c
n — junra o.
R_M ATTIC ^
MHfl ATTIC HI
— MAI lib N.
D inuiu M
n — JUnnl n.
R mufti
1 YV//A
ysssft
\ffl\
Y7///A
1 V,
^
!
. £
Vs
ys/jSA
^/m
m>
, W'
v////\
Y//SA
Y&\
W//A
5 1
^V/V^X/yVJ
V£^/A
'/7//////A
\/4////s/\
w^\
v/yy/yvs*
S ' ' ^A ' ' "^jl 1
W%M/\ '
//J9////A
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W////M,
*\//////w///>
0 1
'/XX
-------
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
cn
U)
10
CA1 KNOX
S. VIEW.
C01 ASBURY
B. DRY C.
CHERRY
N. AVE.
ROONEV
nuunc i
VILLA IT.
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DC1 DUFIEF
FAIRIDGE
LAKERIDGE
STEDWICK
STRATTON
uucoTicinu
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mPMARTFRIH
unnni cnjn
YOUNG
NORMA P.
IL1 JOHN N.
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BLANK INDICATES EITHER R LESS THAN 0.1 OR NO DATA
-------
TABLE 6-15. CORRELATION COEFFICIENT VALUES BY SITE
CTi
I
PAt KNOX
S. VIEW.
C01 ASBURY
B. DRY C.
CHERRY
N. AVE.
RODNEY
VILLA IT.
11EIC
DC1 DUFIEF
FAIRIDGE
LAKERIDGE
STEDWICK
STRATTON
WESTLEIGH
FL1 CHARTERJH
YOUNG
NORMA P.
IL1 JOHN N.
JOHN S.
MATTIS N.
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U
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(Jl)®) U ®) U ®)®) U
U U
KS1 LENAXA
METCALF
NOLAND
OVERTON
MAI ANNA
CONVENT
JORDAN
LOCUST
RT. 9
MA2 ADDISON
HEMLOCK
MD1 BOLTON
HAMPDEN
HOMELAND
MT. WASH.
RES. HILL
Mil GRACE S.
GRACE N.
GRAND
IND. DR.
WAVERLY
NCI 1013
1023
NH1 PKG.
z
co 3 .a Z
a.' o. +, « °- *
®® U U .80
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(77) ® u u
U U (67)
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as u (94)
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NY1 CARLL R.
NY2 CEDAR
NY3 CRANSTON
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SOUTHGATE
TNI CBD
R1
R2
SC
TX1 HART
R'WOOO.
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83-2061-34
(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
C01 NORTH AVE.
VILLA IT.
DC1 WESTLEIGH
FL1 CHARTER/H
IL1 MATTIS N.
MATTIS S.
KS1 LENAXA
MA
1 LOCUST
MO-
1 RES. HILL
NC1 1013 (CBD)
NH1 PKG.
NY3 E. ROCHESTER
TNI CBD
R1
WA-
1 LAKE H.
SURREY D.
WI1 P.O.
RUSTLER
STATE FAIR
AVERAGE r2
AVERAGE r
CO
CO
1—
—
-
-
—
-
-
-
.80
-
-
-
-
-.48
.82
-
-
-.39
-.37
-.47
.34
.58
a
o
-.58
-.70
-.32
-.62
-.64
-.61
-.70
-
-.79
-.58
-.58
-.79
-
-
-.33
-.34
-.28
-.55
-.48
.33
.58
a.
o
l—
-.47
-.58
-
-.54
-.59
-.55
-.51
.91
-
-.46
-
-.84
-.62
-
-
-.30
-.24
-
-.47
.29
.53
a.
CD
CO
-.42
-.67
-
U
U
U
u
-
u
u
u
u
-.47
-.62
U
U
U
U
U
.31
.55
z
h-
-.72
-.69
-
-.68
-.48
-.53
-
-
-.58
-.57
-.49
-.70
-.56
-
-.34
-.21
-.46
-.39
-
.30
.55
z
CO
CN
CD
Z
-.52
-.44
-.39
-
U
U
U
-.82
-
-.67
-.46
U
-
-
U
U
-.53
-.37
-.72
.30
.55
o
-.47
-.46
-.84
-.54
-.40
-.34
-.80
-
-.55
-.32
-.50
U
-.51
.72
U
U
U
U
U
.31
.56
-a
a.
-.42
-.55
-
-.67
-.46
-.46
-
.78
-
-.29
-.41
-.72
-.51
.85
-.29
-.18
-.23
-
-
.28
.53
-.46
-.65
-.44
-.56
U
U
-
-
-
-.54
-.58
-.72
-.65
.82
-.37
-.23
-
-
-
.32
.57
C3
.28
.35
.29
.37
.27
.26
.46
.69
.42 '
.26
.26
.57
.30
.57
.11
.07
.14
.18
.30
CD
.52
.59
.54
.60
.52
.51
.68
.83
.65
.51
.51
.76
.55
.77
.33
.26
.37
.43
.55
<«=
32
27
35
12
35
33
16
6
13
61
33
8
15
11
126
118
40
20
25
a
Z uj
30%C
100%C
93%R
89%R
50%C
90%R
50%l
85%R
100%R
100%C
100%C
100%R
100%C
91%R
91%R
100%R
100%C
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
I.U
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
n
o
o
!'V
e
0 ,
* t,
.
k
• . •
° •
t
.
.
•
"
•
«
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
-------
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
-------
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
-------
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
-------
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
-------
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
-------
(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
-------
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
-------
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
-------
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
-------
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
-------
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
-------
I
CO
CM
cS
Figure 7-3. Geographic Regions Selected for Screening Analysis
-------
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
-------
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
-------
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
-------
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
-------
I
M
*»
COPPER
SHE URO flUAUT*
I IOW RAHGE SITES
POILUTAIT
SO
9
S
lu I
U
i
tqr
Lr1
i i i i i i_ i i i
i ill i I
I 2 3 4 t I 7 I-*—I "\ 1145178
DM - 10 GEOGRAPHIC DM - IDO
HEGIOI
SITE URO OUAUTt
| AVERAGE SITES |
COPPED
HIGH HUGE SITES
OJ1I
1 2 3 4 i I 7 I « | » I
DM • 10 GEOGRAPHIC
OAI
2146171 J
DAD - 100
1 1 4 I I 7 I •« r—••!
BAD . tO 6EOGRAPHIC
2 1 4 i I 7 I
OAR - 100
Figure 7-6. Exceedance Frequency for Stream Target Concentration
COPPER
-------
POUUIAKt
SITt UBO OUAUTt
lOW »A«Ci SITES
I "
s
a '
OJI
12145678
U t I
urn
1234567 l~
OAK " 10 GEOGRAPHIC
3 4 6 fi 7
QAR • 1QQ
I
3ITE UBO QUAHTY
| »ViflACE SITES
I "" I
SITE UBO OimiTt
| HIGH RA»6i SITES |
12145676
J
DAB •
2 1 4 5 6 7
OAR - 100
5
g .
oat
214567
DAB - 10
GEOGRAPHIC
BEGUM
2145)7
OAR - 100
Figure 7-7. Exceedance Frequency for Stream Target Concentration
LEAD
-------
POUUTAKT
s
a
2
OJJI
SITE DUO OUAIITV
LOW BA1CE SITES
POUUTAIT
ZWC
SITE DM QUALITY
| AVERAGE SITES |
POUUTMT
I ™ I
SITE UBO OIIAUH
I HIGH HUGE SITES
1
1
2
.
-
2
3
-
^
J
0«
4 S 1 7 g 1
MIIQ
R - 10 REGION
2
2
3
3
)AI
4 S 1 7 t
HHt
4 S S 7 1
- 100
S
i 50
1
a
s
c ,
a
| O.I
-
i
|
1
i
|
-
_
i
i
1
i-
•_
l
OA
4
|
-J
4
R -
S
«•
6
II
|
Ml
_
1
7
M
7
1
w
1— '
1
••—I •
GEOGRAPHIC
REG! 0»
1
^~
1
2
2
1
a
1
DA
45171
'V
4 S t 7 0
1 • 100
O.I
12345671
1 t 1 4 6 I 7 I
I 2 1 4 S I 7 I'
DM - 10
GEOGRAPHIC
ftEGKN
OM • 100
Figure 7-8. Exceedance Frequency for Stream Target Concentration
ZINC
-------
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
-------
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
-------
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
-------
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.
-------
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
-------
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
-------
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
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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
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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
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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
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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
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(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
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ILLINOIS
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Pb
TKN
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COD
TSS
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Figure 8-6. Street Sweeping Performance
8-21
-------
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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STREET SWEEPIIG PERFORMAICE-
SITE MEDIM EMC
400
g 300
I
3 200
3 too
300
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a 100
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o
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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
-------
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
-------
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
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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.
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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
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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
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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,
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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
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