PP35-136 SCO
Oh.n: nc* ^ :• i ;•;:-..-; .I-,.] Cr
Cleaning
Pitt (RoS
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FPA/600/2-85/038
Anvil 1985
i.'M ami Cor troll ing Urban Runoff
Street ano Sewerage Cleaning
by
Robert Pitt
Consulting Environmental Engineer
Blue Mounds, Wisconsin 53517
Cooperative Agreement CR-805929
Project Officer
Richard Field
Storm and Combined Sewer Program
Water Engineering Research Laboratory
Edi -on, New Jersey 08837
This study was conducted
in cooperation with the
Storm and Surface Water Utility
Bellevue, Washington 98009
WATER ENGINEERING RESEARCH LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
CINCINNATI, OHIO 45268
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TECHNICAL RETORT DATA
//V. Jir rr:.i ,'j.iin. . : • •.-< ,"i f'-r rnr". iV/ivr f.i — -/C."T'
'- ' ' \ v ->
j PA| . - ;7~°r' ,-pe
t'h.v--,, V-->:ino aid Controlling Urban Runoff Through
Street and Sev.erane Cleaning
A ^ T n , "" ^ V
Robert Pitt
1 r-tHFCBV NG ORGANIZATION MAMC AND ADDRESS
Robert Pitt
Consulting Environmental Engineer
Route One
Blue Mounds, Wisconsin 53517
1 : S"C-,?.,?=> NAME A NO ADDRESS
Water Engineering Research Laboratory--Cin . , OH
Office of Research and Development
U.S. Environmental Protection Anencv
Cincinnati , Ohio -15268
3 fll ^»i li ff 1 •(, Aut !-S--. -WNC r-
\ -* s L ^ - J '-• L^^>
c, RF^O^TC^'E.
April 19S5
6 PtRFORMING ORGANIZATION CODE
8 PERFORMING ORGANIZATION REPORT NO
10 PROGRAM tLEMENT NO
11 CONTRACT GRANT NO.
Grant, CR-8059P9
13 TYPE OF REPORT AND PERIOD COVERED
Final ; 1980-1983
14. SPONSORING AGENCY CODE
EPA/600/14
is SJPPLEVENTARY NOTES
Project Officer: Richard Field; telephone (201)321-6674
16 ABSTRACT
A series of projects conducted from 1978 through 1983 in Bellevue, Washington,
to investigate Bellevue's urban runoff sources, effects, and potential controls.
This report presents results of trie project conducted by the City of Bellevue that
was sponsored by the Storm and Combined Sewer Section of the U.S. EPA. The project
lasted from 1980 to 1983 and was mostly concerned with urban runoff characterization
and control by street and sewerage cleaning. This project completely monitored more
than 300 urban runoff events in two residential areas during the project period.
Flow-weighted composite samples were analyzed for a core list of important constitu-
ents. Complete flow monitoring results allowed detailed descriptions of urban run-
off quality and quantity, and allowed estimates to be made concerning the contribu-
tions of flows and pollutants from different source areas. Street surface and sew-
erage particulates were also collected and analysed to determine the effectiveness
of street and sewerage cleaning. Most of the heavy metals were determined to ori-
ginate from street dirt, but street cleaning was found to only control urban runoff
by a maximum or about ten percent. A special modified street cleaner was tested and
found to he much more effective in removing the smaller sized street dirt that is
washed off these streets by rains. Catchbasin cleaning twice a year was estimated
to be about 25 percent effective, at the most.
17. KEY WORDS AND DOCUMENT ANALYSIS
J DESCRIPTORS
13 DISTRIBUTION STATEMENT
RELEASE TO PUBLIC
b. IDENT'FIERS/OPEN ENDED TERMS
19. SECURITY CLASS (Tha Report)
UNCLASSIFIED
20 SECURITY CLASS (This past)
UNCLASSIFIED
c. COSATI Field/Group
21 . NO. OF PAGES
476
22. PRICE
EPA Forr- 2IIO-1 (S-73)
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DISCLAIMER
Although the information described in this document has been funded
wholly or in part by the United States Environmental Protection Agency
through assistance agreement number CR-S05929 to the City of Be^^vue, it
has not been subjected to the Agency's required peer and administrative
review and therefore does not necessarily reflect the views of the Agency
and no official endorsement should be inferred.
ii
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FOREWORD
Thp U.S. Environmental Protection Agency is charged hy Congress with
protect i nij PIP Nation's land, air, and water systems. Under a mandate of
national environmental laws, the agency strives to formulate and imple-
ment actions leading to a compatible Balance between human activities and
the ability of natural systems to support and nurture life. The Clean
Water Act, the Safe Drinking Water Act, and the Toxics Substances Control
Act are throe of the major congressional Jaws that provide the framewor<
for restoring and maintaining tne integrity of cur Nation's water, for
preserving and enhancing the water we drink, and for protecting the
environment frc'n toxic substances. These laws direct the EPA to perform
research to define our environmental problems, measure the impacts, and
search for solutions.
The Water Engineering Research Laboratory is that component of EPA's
Research and Development program concerned with preventing, treating, and
managing municipal and industrial wastewater discharges; establishing
practices to control and remove contaminants from drinking water and to
prevent its deterioration during storage and distribution; and assessing
'he nature and controllability of releases of toxic substances to the
air, water, and land from manufacturing processes and subsequent product
uses. This publication is one of the products of that research and
provides a vital communication link between the researcher and the user
cpmnuni ty.
A comprehensive evaluation of the sources and control of urban runoff
was conducted during a two-year study in Bellevue, Washington. This project
was one of several cooperating studies that examined the effects of urban
runoff on receiving water beneficial uses, the sources of problem pollutants
and flows, and the control of urban runoff in Bellevue. The unique Bellevue
rain conditions enabled another urban runoff perspective to be obtained.
Much data was also obtained on urban runoff characteristics and the washoff
of street surface participates during rains. These data allowed simple re-
lationships between rain conditions and contributing source areas to be
developed.
Francis T. Mayo
Di rector
Water Engineering Research Laboratory
11
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ABSTRACT
A series of projects were conducted from 1978 through 1983 in Bellevue,
Washington, to investigate Bellevue's urban runoff sources, effects, and
potential controls. These projects were conducted by the City of Bellevue,
the U.S. Geological Survey, the University of Washington, and the Municipality
of Metropolitan Seattle. This report presents results of the project conducted
by the City of Bellevue that was sponsored by the Storm and Combined Sewer
Section of the U.S. EPA. This project lasted from 19RO to 1983 and was mostly
concerned with urban runoff characterization and control by street and sewerage
cleaning. This project completely monitored more than 300 urban runoff events
in two residential areas during the project period. Flow-weighted composite
samples were analysed for a core list of important constituents. Complete flow
monitoring results allowed detailed descriptions of urban runoff quality and
quantity, and allowed estimates to be made concerning the contributions of flows
*.id pollutants from different source areas. Street surface and sewerage parti-
culates were also collected and analysed to determine the effectiveness of
street and sewerage cleaning. Most of the heavy metals were determined to
originate from street dirt, but street cleaning was found to only control urban
runoff by a maximum of about ten percent. A special modified street cleaner
was tested and found to be much more effective in removing the smaller sized
street dirt that is washed off these streets by rains. Catchbasin cleaning
twice a year was estimated to be ,=
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CONTKNTS
Foreword
•\bsti-.ict
(on fonts
Ackp-,w Le
1. Kxooutive Sunmary
1. Introduction ........ . ................ . ........................ -"-
Obj ert ives . . ........... . ..................................... 2
Methodology ............ . ...................................... 2
2 . Summary ind Conclusions ....................................... 4
Identification of Problem Pollutants .......................... 4
Sources of Problem Pollutants ................................. 6
Selection of Control Measures ................................. 7
3. Study Area Description ........................................ 10
II. Urban HydrolDgy
4. Bellevue Rain Conditions ...................................... 15
5. Runoff Quantity ............................................... 24
Observed Rainfall and Runoff Volumes .......................... 24
The Effects of Land Use on Runoff Quantity .................... 28
Seasonal Trends ..n Runoff and Baseflow Quantity ............... 42
III. Urban Runoff Water Cuality
6. Urban Runoff Quality .......................................... 48
Introduction .................................................. 48
Observed Urban Ruroff and Baseflow Quality .................... 49
Comparison of Observed Urban Runoff Constituent
Concentrat1' ens with Water Quality Criteria..... ............ 58
Mass Yields of Pollutants from Urban Areas, ............... .... 66
Source Area Contributions of Uuban Runoff Pollutants .......... "74
IV. Street Dirt and Stirm Drainage Particulates
7. Street Dirt Characteristics ................................... 88
Factors Affecting Street Cleanliness .......................... 88
Street Surface Particulate Accumulation
and Deposition Rates ........................................ 93
The Distribution of Street Dirt in Driving
and Par):ing Lanes ...................................... ..... 102
Chemical Strengths cf Street Surface Particulates ............. 107
8. Sewer Systen Particulate Accumulation Studies ................. 115
Catchbasin Observations ....................................... 115
Fine Survey and Observations .................................. 132
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V. I'i ban Runut t Control Measures ,,,
9. Street Cleaning Effects on Observed Runoff Quality -
IJu
K ishoff of Street Dtrt
Runoff Water Quality Concentrations and Yields During
Periods ot Different Street Cleaning Activities
Relationships Between Street Load, Runoff Yield,
a id iUmof f Volumes
Coraparisio-is of Observed Runoff Concentrations
in the Two Test Basins f
Summary • •
10. Street Cleaner Performance..... •
Street Cleaning Test Schedule
Performance Tests 188
Bellevue Street Cleaning Routes, Operating
Characteristics, and Costs
11. Effects of Storm Drainage Particulates on Runoff Quality 215
VI . References 223
VII. Appendices
A. Rain and Runoff Data 226
B. Street Dirt Characteristics 307
C. Street Cleaner Performance 382
D. Storm Drainage System Data 417
E. Sampling Procedures * 426
Stormwater Sampling 426
Street Surface Partlculate Sampling
and Experimental Design 428
Driving Lane Test 436
Across the Street Tests 436
Catchbasin Inventory and Sampling 437
F. Street Dirt Sample Preparation and Data Handling 438
Introduction 438
Sample Description 438
Information to be Noted During Street Cleaning
Operations and Sample Collection 438
Physical Analysis , 441
Calculation of Street Loading Values 445
Summaries of Rain Events 448
Preparation of Loading Summaries 451
Sample Compositing for Chemical Analysis 451
Summary 455
G. Sources of Urban Runoff Pollutants 458
Chemical Quality of Rocks and Soils 459
Street Dust and Dirt PoJ lutant Sources. 459
Urban Agricultural Sources of Urban Runoff Pollutants 460
Atmospheric Resuspension, Transportation and
Redeposition of Urban Runoff Pollutants , , 461
Resuspension of Source Area Particulates 462
H. Reactions and Fates of Urban Important
Runoff Pollutants
VI
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'>CK.NOWL;:DCMKMS
Sinr.TL- gratitude goes to Mr. Richard Field of the U.S. Environmental
Pnu < ' 1,111 Agency (Storm and Combined Sewer Section, Edison, New J. rsey), for
• .ipport and assistance during this project.
The considerable field woi'k for this project could not have been carried
out without the effort and cooperation of the Balievue Storm and Surface
Water Utility. Special thanks are extended to Joy Wherley, David Renstrom,
and Lnrrie Murray. The extra effort extended by the street cleaner operators
and other Public Works personnel who participated in this study is
appreciated. This project would not nave been successful without the support
and encouragement of Pam Bissonnette, the Storm and Surface Water Utility
Manager, and Bellevue's Principal Investigator for the Bellevue Urban Runoff
Program.
The help of Roger Sutherland, of CH2M-HILL, in assisting with the
sewerage observation study plan and data analysis was invaluable. The
cooperation ?nd sharing of preliminary results from the other Bellevue Urban
Runoff Program participants (University of Washington, Seattle METRO, and the
USGS) was very important and appreciated. Special thanks are extended to the
USGS, especially Edmund Prych, for assistance in obtaining crucial field data
during the study.
VI1
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SECTION 1
INTRODUCE ' u.N
The Bellevue urban runoff program is one of about 30 urban runoff
projects being conducted throughout, the country as part of the Nationwide
Urban Runoff Program (NURP) for the U.S. Environmental. Protection Agency
Ch-PA). The Bellevue program is made up of four different coordinated
projects. These include projects conducted by the U.S. Geological Survey
(USGS) (funded by the USGS arm NURP - the Water Planning Division of the
EPA), the University of Washington (funded by the Corvallis Lab of the EPA),
Seattle METRO, and the City of Bellevue (funded by the Storm and Combined
Sewer Section of ths CPA and the City of Bellevue). The project described in
this report was conducted by the City of Be'levue.
A major task in Bellevue's project included n.onitorlng the qualit;1 and
quantity of stormwater runoff from two urban basins in the City of Bellevue.
Street surface particulate samples were collected in these two basins, along
with selected storm drainage sediment samples. The City of Bellevue conducted
various street cleaning operations in the two test basins. The USGS (Ebbert,
Poole, and Payne, 1983, and Prych and Ebbert, undated) also monitored storm
runoff quality and quantity in these two test basins; they used different
sampling techniques to monitor fewer stortns, but in more detail. The USGS
monitored rainfall and dustfall quality and quantity along with the
performance of a series of detention basins at a third Bellevue test site
(148th Avenue SE). The USGS and the City of Bellevue projects were carefully
coordinated to enable all objectives to be met with minimum interference. The
Seattle tETRO project (Galvin and Moore, 1982) involved collecting urban
runoff and other urban water and dirt samples for priority pollutant
analyses. The City of Believue project was also coordinated with the METRO
project to supply the urban runoff and street surface particulate samples for
the priority pollutant analyses. The University of Washington's projects
(Pedersen, 1981; Richey, 1982; and Scott, Steward, and Stober, 1982)
invrstigated receiving water conditions near the Bellevue test basins and in
other locations unaffected by urban runoff. The University of Washington
project studied physical, chemical, and biological qualities of various
receiving waters to identify impacts associated with urban developments on
receiving water quality. Therefore, a substantial amount of information
concerning Bellevue's urban runoff conditions and effects is available from
these four associated projects. A summary report prepared by Pitt and
Bissonnette (1983) reviews all these separate project reports and presents
overall Bellevue urban runoff conclusions.
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llu- project ciMuiuc t ed hv the City of Bellevue included objectives to
s.itislv (.lie Nationwide l;rh,m Runott Crogr.in, the ETA's Storm a.id Combined
.Newer Seet icn, Kei'.lon X of the Kl'A, and objectives specific lor the City of
m'llevne's Storm Dr.iin.igi.- Utility . The project objectives are described
be low:
1) The principal project objective was to determine the effectiveness of
street cleaning <.n controlling urban runoff pollutants in bellevue. Several
other projects have been conducted in other parts of the country previous to
tnis project. Several of the other Nt'RP projects are also currently
evaluating street cleaning under a variety of climatic and geographical
conditions. Hie Bellevue climatic conditions are unique in that the moderate
arrounl of rainfall occurs relatively evenlv throughout the year, with no long
periods without any rain. The erosion potential of undisturbed areas is low.
From previous studies, it is known that the street surface particulate
loadings in Lru Pacific Northwest are naturallv low and the urban runoff is
of relatively h'.gh quality. These conditions contrast with the conditions for
most of the comprehensive street cleanint management projects conducted
elsewhere, especially in the San Francisco Bay Area where tiie rainfall is
much less and is concentrated in fewer months of the year. The street
loadings in other test cities car. be quite high and the urban runoff quality
can be quite poor. These Bellevue tests will therefore be useful in defining
the applicability of street cleaning as an urban runoff best management
practice under significantly different environmental conditions.
2) Stormwater quality and quantity characterization information
obtained during this study is a significant contribution to the urban
stormwater data base. Many urban runoff events were monitored during this
project and the information obtained has been added to the STORET National
Water Quality Data Base. The other NURP projects also have their runoff water
quality snd quantity data included in this data base. Site specific
runoff/rainfall relationships for Bellevue have been obtained which will
allow predictions of runoff changes due to urban development to be made.
3) Sources of urban runoff pollutants, especially street surface
paruiculates, were also cr.isidered in this project. The effects of source
area pollutant loading! on runoff water quality were examined.
4) The runoff water quality ana qua: <.iry data and the street surface
particulate loading data obtained can be usi-d by the City of Believue as the
beginnings of a more comprehensive data bas? for the whole city. This can
support a water quality management p'an as part of the City of Bellevue's
Storm Drainage Utility.
METHODOLOGY
All elements of Bellevue's urban runoff project were coordinated with
the three other local projects being conducted by the USGS, Seattle METRO,
and the University of Washington. Early in the project planning phase, it was
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.1.,-idr.l t,..u two study anas ;.houlu bv selected. These areas, whi.'h are
i.Vs.Til.,-,1 1-1 .section j, ,ue quite similar and iairly close. Hits' are both
t.'lalU i.rhmi-.ed with mist ly sirigle family mousing. Their .storm drainage
s\s.te.us were' thorough!v 'napped and investigated to ensure no
cin.ss-coMPecr i-ms or illegal discharges, hach of the two basins drain at a
sin.1!.- initial! and are e i-\\ about 100 acres (40 ha) in size. A single
stoi.T.watei i.Hin: torinr, station was located at the outfall of each <>l these
basins lor stormwater sampling. The sampling equipment selected tor this
project was capable ol ,:utonatica1ly sampling total storm flow-weighted
,.oir,josite samples tor a broad variety of storm conditions. Appendix h
descrioes the sampling equipment and procedures in detail. The information
obtained trom '.hese automatic samplers and flow meters i>ere supplemented hy
tiie. sampling and monitoring equipment operated by the USCS at the same
locations. As many storms as possible were sampled during the ^wo-year study
program at each of these two locations. Almost all storms havi'.ig more than
0.1 inch (2.5 mm) of total rain and many of the smaller rains were completely
sampled.
During the two-year project period, extensive street cleaning was
conducted in either one or the other test basin, except for a several month
r..riod of time for basin calibration when no street cleaning operations u^re
conducted. Intensive street cleaning was conducted during both wet and dry
reasons in each basin. This allowed comparing the observed runcff water
quality in each basin with and without street cleaning.
btreet --urface particulate samples were also obtained immediately btfore
and atter --ich street cleaning operation and intermittently duri ng periods of
no street cleaning. This resulted in a much more detailed description of the
effects of the street cleaning operations jn this potentially important urban
runoft pollutant source area. Periodic samples of sediments from the storm
drainage s\stem were also obtained and analyzed to estimate the potential
benefits of sewerage cleaning on improving urban runoff quality.
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SECTION J
SUMMARY AND CONCLUSIONS
I !u-re art three separate phases in designing an urban runoff control
;•• '>;r.i",i. Those include identification of the problem pollutants, determining
Vu> sources o, the problem pollutants, ard selecting the most appr r.riate
contiol measures. The four Bellevue urban runoff projects addressee these
i ssucs .
IDENTIFICATION OF PROBLEM POLLUTANT?
The University of Washington study examined existing effects that urban
runoff may be having on aquatic organisms. The other three Bellevue urban
runoff projerts all have important characterization aspects. These projects
identify potential problem pollutpnts by comparing the observed runoff water
qualitv with beneficial use water quality criteria and with concentrations
found in other waste streams ard receiving waters. This information can be
used to identify vhich, if any, pollutants need to be controlled and to what
extent. The unique assimilative capacities of the Bellevua receiving waters
needs to be considered. Pollutants that are causing potential problems can be
identified and appropriate control goals can be estimated.
The meteorological conditions at Bellevue are discussed in Section 4 and
Bv-^levue urban hydrology conditions are discussed in Section 5 of this
report. These two sections point out some of the special circumstances
associated with Believue's urban runoff. Bellevue receives a moderately large
amount of rain every year (about 35 inches, or 890 mm) with several summer
months drier than the other noi.chs. However, the dry periods between rain
events are quite small, even during the dry season. Dry periods of more than
a week are quite rare, but may occur. Rains come on the average about once
every two or three days throughout the year. Slightly more than 100 rains may
occur per year, with each rain being quite small. Most of the rains are less
than 0.25 inch (6.4 mm) in volume, although the largest rains monitored
duiing this study were several inches. This is in sharp contrast to most
other locations in the country. In the San Francisco Bay Area, where previous
comprehensive street cleaning and urban runoff studies have been recently
completed, the annual rainfalls are much less than in Bellevue, but the rains
are typically larger in size. The interevent period in the San Francisco Bay
Area is several days during the wet winter season, but can be several months
during the summer. The total annual rainfall at Bellevue is similar to the
total rainfall at some of the other NURP project sites in the country that
are currently investigating the effects of street cleaning on urban runoff;
however, the average rairs in these other areas are much larger than the
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.u,r.,o- rains in Bellevne, with significantly longer interevent periods
( spi-cit leal ly Milwaukee and Wins ton-Salem)
The .-mount of rain that drains off an urtwn area as urban runoff is
dependent. uron nuny factors. These factors are discussed In Section 5 and
mchui, ,uch things as soil moisture conditions, soil infiltration capacity,
rain i.Uensitv. and rain duration. The moist soil conditions in Bellevue (due
Lo the hiKli frequency of ruins) tends to increase the fraction of rain that
occurs as nmotf. However, the small volunes and the small intensities of
each individual rain allows much of the water to infiltrate into the soil.
tor both stud} years and test Nasins , only about 25 percent of the rain that
fell in the test basins left the basins as runoff. There was a substantial
amount of scatter in this value, but the smaller rains typically had the
smallest Kv (the ratio of unit area runoff to rainfall) values (rains of
about u.l inch, or 2.5 mm, had Rv values of about 0.1 for the dry season and
about U.2 for the wet season), while the largest rains had larger Rv values
(rains of about 2.5 inches, or 64 mm, had Rv values of about 0.2 to 0,3
during the dry season and about 0.3 to 0.4 during the wet season).
Base flows were also monitored and sampled during this project. An
important amount of the total urban water flows in both of the test basins
occurred between rains, as baseflow. The base flow in the Surrey Downs basin
accounted for about 25 percent of the total urban flow, while the base flow
in Lake Hills was only about 12 percent of the total urban flew. Observed
urban flow and quality variations were much less than found in more arid
areas. This has a major influence on the effects of urban runoff. Immediate
urban runoff effects (during storm flows) are mostly related to fast and
major changes in receiving water quality and quantity (as in a slug flow
situation). If the flows and quality do not change radically, the receiving
water aquatic organisms do not experience as much stress because the existing
organisms have already adjusted to a long-term degraded condition.
The runoff water quality data presented in Section 6 shows that the
observed Bellevue runoff water quality was much better than observed in many
other locations. The baseflow quality, on the other hand, was much worse than
expected. This was probably because the study basins were completely
urbanized and the baseflows were mostly polluted percolated urban sheet flows
from previous storms that were draining out of the surface soils. In basins
with undeveloped upstream areas, the baseflow would originate mostly from
nonurbanized upper reaches and would have much better quality. The urban
hydraulic conditions in Bellevue allow the observed runoff water quality to
be compared to beneficial water quality criteria. Typically, urban runoff
should not be compartd to water quality criteria because the published
criteria were established for continuous discharges, while urban runoff is
usually considered e slug discharge. However, as previously noted, ^he
baseflow ard urban runoff qualities in Bellevue do not differ greatly.
Therefore, as an approximation to identify potential problem pollutants, the
beneficial use water quality criteria for aquatic life, published by EPA
(I97b), was compared with the observed Bellevue urban runoff quality. It was
found that direct receiving water effects from urban runoff may not be
significant for most rain events (except possibly for ammonium and nitrate
nitrogen). Most of the Bellevue urban runoff water quality problems are
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t'\|-i->ii-d I" In- ,is.-,n, i.iu ' with lung-term effects caused by settled organir
•i'1'] iiuu v-.in -. i- dehiis and ,>.i r t i m 1 ,u es . This material ran silt up spawn i PR
'1t'l'i; in r IM IVllt'vue in h,in streams and po.sibly introduce high concentrations
ot toxic r,.it cria 1 s dinclly to the sed i ITHMI t s . Identified potential long-term
problem pollutant.', are settleable s.ilids, lead, and zinc. The University of
Washingi,vi studies (!Vd-> rsen, 1981; Kichey, 1982; and Scott, Steward, and
Stober, 1 ^>2 ) and the Seattle MK.TKO study (Calvin and Moore, 1982) will
address this issue In more detail.
SOUKCtS OF KKOBLtM POLLUTANTS
The seeond phise in designing an urban runoff control program is to
determine the sources of the problem pollutants in the watershed. An
understanding of where the problem pollutants accumulate in the catchment is
needed before appropriate cont-rols may be selected. Sections 5 and 6 discuss
the sources of urban runoff flows and pollutants in the test basins. In
Section 5, which deals with urban runoff flows, it was found that the
impervious surfaces (including street surfaces, driveways, parking lots, and
rooftops) can account for almost three-fourths of the runoff flows in both
basins during any season. There are few vacant lots or parks in the test
basins , so the remainder of the urban runoff flows originates from landscaped
front or back yards. For very small rains (<0.1 inch, or <2.5 mm), however,
street surfaces alone contribuls from one-half to three-fourths of the total
runoff flows. Driveways and parking lots make up the remainder for the
smallest rains. During these very small rains, rainwater infiltrates into the
soil in the pervious areas, with runoff primarily originating from the
impervious areas. The contribution from street surfaces decreases with larger
rains and remains fairly constant for rains larger than about 0.1 inch. The
observed variation of runoff sources from different areas as a function of
r&in quantity is smaller than for locations previously studied (Ottawa,
Ontario; Pitt, i.982 and Castro Valley, California; Pitt and Shawley, 1981).
Because of variations in sheetflow quality from the source areas during
runoff events, the contributicns of pollutants from each source differs from
the contributions of runoff flows. Using some sheetflow runoff quality data
obtained previously in other locations, and with an understanding of the
local Bellevue conditions, estimates of pollutant contributions from these
different source areas were made in Section 6. It is estimated that total
solids (for most rain events) originate mostly from the back and front yards
in the test basins and that street surfaces contribute only a small fraction
of the urban runoff total solids discharge. Street surfaces, however, are
expected tc make up most of the lead, zinc, and COD contributions to the
urban runoff. Phosphates and total Kjeldahl nitrogen are mostly contributed
from street surfaces, driveways, and parking lots combined. Back and front
yards make up slightly less than half of these nutrient contributions to the
outfall. Therefore, street cleaning operations cannot be expected to
significantly improve the urban runoff total solids loadings or
concentrations. If the available street surface particulate loadings could be
reduced by one-half, then many of the other pollutants may be reduced by
about 25 percent at the outfall.
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.sort.on 7 discus-s in .IctaiL the observed street surface particulate
conL.^ir,,
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identities. Street cleaning can only operate un streets and parking lots (arid
possibly sidewalks and driveways); cons :rnction erosion control only affects
cons t^uci ion areas; runoff storage and subsequent LL catgut can affect all
source and accumu'atirn areas. T >•;,_- effectiveness of the applicable control
measures in reducing problem pollutant concent rations and yields at the
outfall must be evaluated. When pollutants are removed from a watershed (such
as by erosion control or by street cleaning), much more needs to be removed
than the amount necessary to meet the discharge goai at the outfall. As an
example , about ten pounds of a pollutant may be needed to be removed by
street cleaning to prevent one pound of the pollutant from entering the
receiving water. After the control measures' applicability and effectiveness
values are known, the urban runoff control program can be designed. In order
to meet water quality objectives, a combination of several different control
measures may be needed. Complex decision analyses procedures may be necessary
if multiple objectives are important.
Secticn 9 of this report evaluates the urban runoff data, dividing it
into periods of intensive street cleaning and no street cleaning. Very
little, i: any, difference can be detected at the outfall based upon these
two street cleaning programs. The roost important reason why any potential
changes were not detected are based on the variations in rainfall and
subsequent runoff quality and quantity observed at the two basins. As noted
in Sections 4 and 5, the rainfall variation at the two test basins can be
greater than 25 percent most of the time. This 25 percent difference in
rainfall corresponds to a much greater difference than 25 percent in runoff
yield. This is because larger rains result in a larger percentage of the rain
occurring as runoff. Therefore, runoff improvements measured at the outfall
at a level substantially greater than 25 percent would be necessary to detect
an improvement under most of the rain conditions during this study period.
Sampling, laboratory, and analyses errors also contribute to masking any
effect that may have occurred. The analyses included in Section 9 attempted
to eliminate most of these flow differences using appropriate transformation
and analytical techniques. The data was separated by season and street
cleaning program. The intensive street cleaning program was rotated between
the test and control basins on a seasonal basis tc eliminate some of the
differences associated with rain conditions.
Section 10 describes the effectiveness of the street cleaning equipment
in removing street surface participates. Street cleaning equipment cannot
remove particulates from the street surface unless the loadings are greater
than a Certain residual amount. .This value was about 500 Ibs/curb-mile (140
g/curb-tneter) in the test basins. If the initial street surface loading
values are smaller than this value, some of the street surface material can
be "loosened", but not removed. The street surface particulate loadings after
the street cleaning operation may then be greater than the initial values.
The frequent rains may be more effective than street cleaning in keeping
Bellevue streets clean. The street surface loadings after rains were between
2UO and 400 Ibs/curb-mile (57 and 110 g/curb-meter), but the street cleaning
equipment could only remove street surface particulates down to about 500
Ibs/curb-mile (140 g/curb-meter). If the street cleaning was conducted more
frequently than the rain intervals, then street cleaning may result in
-------
c leaner streets.
The intensive street cleaning program that was conducted during these
tests can result in about a 25 percent reduction in street surface loadings
when compared to no street cleaning. If the street jurface contributes about
half of the total source for a specific pollutant, intensive street cleaning
may only remove about ten percent of the pollutant yield at the outfall.
Typical runoff reductions by street cleaning are estimated to be about five
to ten percent. As noted previously, it would require a fairly substantial
reduction in discharge yield uo be statistically significant based upon
outfall measurements. The. effectiveness of street cleaning equipment in
controlling urban runoff is very site specific. If the street surface
loadings were much greater than the breakeven street cleaning point, and
there were less fvequent rains, street cleaning might control important
tractions of the total urban runoff flow. Street cleaning in Bellevue may not
be an appropriate urban runoff control measure, especially at a cost of about
$2U/curb-mile ($12.50/km). With such small potential improvements in urban
runoff quality, other street cleaning benefits are more important.
Special tests were conducted using a modified regenerative-air street
cleaner. It was demonstrated that this equipment was much more effective in
removing the finer street dirt material than the regular mechanical street
cleaner tested. This finer material can be washed from the streets by rains
more easily than larger material. Therefore, urban runoff quality can be
imprcved slightly more with the use of this modified equipment (to about ten
percent reductions).
Sections 8 and 11 discuss the potential effects that sewerage cleaning
may have on urban runoff control. The sewage inlet and catchbasin sediments
had relatively constant accumulation rates after cleaning for about one year.
After a year, the sediment volumes remained quite constant, with little
effect on the runoff yield. A major rain event during the second year after
cleaning did not result in any net average or total sedimert loading change.
Sewage inlet and catchbasin cleaning is therefore recommended on about an
annual basis. This should result in annual total solids and lead storm runoff
yield reductions of between ten and 25 percent. The other constituents
studied (CUD, TKN, TP, and Zn) may be controlled by between five and ten
percent. More frequent cleaning would not increase these reductions, as the
observed sediment accumulation rates appeared to be constant, until the
constant volume value was obtained. Only about 60 percent of the available
sump volumes were used for detention. Large sumps had less of their volumes
utilized. Catchbasins with large sump volumes could be cleaned less
frequently because th -y held larger volumes of sediments. Allowing pollutants
to remain in a sump foi long periods of time, however, may increase their
solubilities, enhancing heir washout potentials and making them more
available to receiving weter organisms.
-------
SKCri'JN 3
STUDY AREA DK3CK1PT1UN
Figure 3-1 shows where the City of bellevue is located in the Pacific
NorUnest BelJcvue is located en the other side of Lake Washington from
Su.itr.lt?. .Washington, and is within commuting distance. Lake Samma-nish borders
Boiievue on the east. Bellevue n ;eives about 35 inches (891! mm) of rain per
year, while substantially greater amounts of rain occur on the Olympic
Teninsu.'a to the west and much smaller amounts of rain occur in eastern
Washington to the east.
''igure 3-2 shows the locations of the Surrey Downs and Lake Hills
catchments in the City of Btllevue. These two sites are located about three
mile.- (i> km) apart and are each about 100 acres (40 ha) in size. They are
botl fully developed as mostly single-family residential areas.
The Surrey Downs basin is 95.1 acres (38.5 ha) in size and include? the
Brllevue Senior High School in addition to single-family tomes. Most of the
.•Aopes in the basin are moderate, with some steeper slopes on the west side
of the basin. Table 3-1 shows that about 60 percent of the Surrey Downs b&sin
is pervious. Back and front yards make up most of the land surface area in
the basin, with streets making up a typical ten percent. The streets are
generally in good condition with smooth to intermediate textures. There are a
few locations wheru the curb needs repair. Westwood Homes Road and 108th
Street do not havr; curbs. There is relatively little automobile traffic in
the Surrey Downs basin and the on-street urrking density is low. The storm
drainage system discharges into an artificial pond located in an adjacent
development. This pond discharges info Uercer Slough which eventually drains
to Lake Washington and Puget Sound.
The Lake Hills catchment is 101.7 acres (41.2 ha) in size and contains
the St. Louise Parish Church and School in addition to single-family homes.
Lake Hills has a slightly larger percentage of pervious areas than Surrey
Downs, but a slightly smaller typical lot size. The slopes in Lake Hills are
also more moderate (with a few exceptions) than those found in Surrey Downs.
Tne street surface and gutter systems are also similar to those in Surrey
Downs. Most of the streets in Lake Hills also carry low volumes of traffic
and have low parking densities, except for two busy roads that cross through
the area. The Lake Hills storm drainage system outfalls into a short open
channel which joins Kelsey Creek just downstream from Larsen Lake. Kelsey
Creek also discharges into Mercer Slough and finally to Lake Washington and
Puget Sound.
10
-------
Olympla
FIGURE 3-1
Northwest Washington State and the City of Bellevuo
1 lnch = 10.8 Miles
11
-------
N
FIGURE 3-2
City of Ballevue, Washington
Stream System and Study oites
12
-------
Table 3-1. SITE CHARACTERISTICS
Vacant
Parks
Backyards
Frontyards
Rooftops
Driveways
Parking Lots
Sidewalks
Streets
Total
Area (acres)
Fraction
Impervious
Fraction
Pervious
# o Homes:
Lot Size:
Frac. Res id.
Frac. Indus.
Frac. Commer.
% Inst.
Frac. Open
area
Curb-miles
of Streets
Surrey Downs
106 ft2 *
0.06 1.6
0.08 2.0
1.45 37.1
0.89 22.8
0.67 17.1
0.20 5.2
0.15 3.9
0 0
0.40 10.3
3.90 10C#
95.1
0.40
0.60
274
0.3 acre
0.91
0
0.06
0.03
5-5(1)
Lake Hi
106 ft2
0
0.14
1.52
1.01
0.79
0.20
0.01
0
0.48
4.15
101.7
0.35
0.65
355
0.25 acre
0.90
0
0.07
0.03
7.0
11s
*
0
3.4
36.5
24.4
18.9
4.9
0.2
0
11.7
100*
"'Westwood Homes Road = 0.5 miles
108th Ave. = 1.5 miles
Cleaning Area = 3.5 miles
13
-------
A de!-u>|',r.iphi c survey was conducted in the Lake IMJls and Surrey Downs
cat chi.K-iUs at t h _> bet; i nn i in; of the project. Slightly more than three people
per Household were reported in both basins, while the population density per
acie was about 1.-! in Lake Hills and about 9 in Surrey Downs (2V and 22 per
hectire, respectively). Almost 25 percent of the households in Lake Hills had
;iiure than b people, while only about 14 percent of the Surrey Downs houses
had that many people per household. More than half of the households in both
basins did not have any dogs or cats, but the remainder of the households had
one ot each, or more. On the average, there was about one dog or cat per
household. Slightly more than two cars per household were reported, with
about ten percent of the households in each basin reporting four or more
cars. About one-third of the households used unleaded gasoline while Ihe
remainder used leaded regular or leaded premium grades of gas. Most of the
automobile oil was disposed properly i" the household garbage, 01 recycled,
but between five and ten per.ent of the households used oil to treat
fenceposts, dumped it onto the ground or into the storm sewers. Most of the
people carried their grass and leaves to the du.r.p or put them in the garbage,
and about one-third composted the organic debris on their lots. It was not
possible to cbta.i.n adequate data on the quantity of fertilizers or pesticides
that were used in the basins.
-------
SECTION 4
BELLhVUE RAIN CONDITIONS
One important prerequisite of any urb;-.n runoff control program is an
understanding of the local r^in conditions. In order to gain this
understanding, the rain conditions during the period of study should be
representative of long term conditions. The ^elltvue monitoring program
lasted for two years, during which fairly t,;Jical rains occurred. The
probability ol unusual rain conditions lasting for a long period of time is
reduced compared to lasting for a short peviod of time.
Differences in rainfall quantities res.\lt in differences in runoff
quantities. The differences in runoff quantities in tur.i produce differences
in runoff yields. Therefore, abnormal rain conditions during an urban runoff
study period will result in abnormal runofi quantity and quality data.
Similarly, short term fluct"ations or differences in rainfall conditions, of
time or area (unusually dry or wet months, or areal rainfall variations), can
result in unrepresentative runoff yield predictions.
The most important task of this project was to monitor the effectiveness
of street cleaning operations. One element of this analysis involved the
comparison of observed runoff quality conditions in study sites with and
without street cleaning. If the rainfall conditions varied between test and
control sites during a test period then the observed runoff yields might not
be indicative of the control measures1 effectiveness. This report section
describes the rainfall conditions (including variations and differences) that
occurred at the two Bellevue test areas during the two-year study period.
Rainfall monitoring equipment was located at each runoff monitoring
station at Surrey Downs and Lake Hills. During parts of the study, additional
rainfall monitoring gauges were located at other locations in and adjacent to
these monitored basins. Rainfall monitoring bepan at the Lake Hills station
in the midale of February, 1980, and about two weeks later at the Surrey
Downs station. Rainfall monitoring was completed at the end of January, 1982,
at both basins. Tables A-l and A-2 in Appendix A summarize the monitored
rains at both of these locations throughout the two year study period. More
than 20U rains were monitored at each of these basins. Table 4--1 summarizes
the rain conditions on an average monthly basis for both basins combined.
The total annual rainfall averaged about 37 inches (940 mm) with about
lOb rain events per year. The year can be separated into dry and wet seasons
with the dry season lasting from the first of March to the end of September.
This dry season has monthly rain totals of less than about three inches (76
mm), while the wet season, lasting from the first cf October to the end of
15
-------
Table 4-1. AVERAGE LAKE HILLS AND SURREY DOWNS RAIN CO'lOITfO'lS
PERIOD OF STUDY (FEBRUARY 1980 THROUGH JANUARY 1982)
Rain Number
per of rain
month events per
(in.) month
January
February
March
April
May
June
July
Auqust
September
October
November
December
Annual
3.6
3.3
2.6
2.8
1.6
2.4
1.2
0.8
3.0
3.7
5.6
6.4
37.0
(tot)
11
6
9
11
9
10
3
4
8
7
14
16
108
(tot)
Rain Duration
per of each Preceedinq
storm storm dry oeriod
(in.) (hours) (hours)
0.33
0.54
0.30
0.29
0.19
0.27
0.39
0.21
0.38
0.49
0.40
0.41
0.34
(avq)
12
22
14
10
8
8
8
9
11
11
12
12
11
(avq)
53
70
68
59
72
79
115
650
81
110
37
34
120
avq)
Average
rain '
int.
Mn/hr)
0.03
o.o?
0.02
0.04
0.03
0.05
0.05
0.04
0.05
0.03
0.04
0.03
0.04
(avq)
Peak 30
•nin . r i in
int.
Mn/hr)
0.09
O.H
0.11
o.i:;
0.10
0.13
0.14
0.12
0.19
0.14
0.15
0.14
0.13
(avq)
Season
wet
wet
drv
drv
dry
drv
dry
drv
drv
wet
Wot
wet
—
-------
tcbi-uarv, iuis monthly tain U r ils between thrco and 6.5 inches (76 and
mm). Each storm during the wet season had about twice as much rain as eacn
*rorm during the dry season. The wet season rains also lasted about one and a
halt to two times as long as dry season rains. The maximum preceding
interevent dry periods during the dry season were substantially greater thon
during the wet season, especially for July and August. The average and peak
Ji'-winute rain intensities for both wet and dry seasons were quite similar.
The average r .in intensities were about one third of the peak intensities.
Uhe.i Tables A-l and A-2 are examined, the overall ranges in observed
conditions tor any nonth are seen to have been quite large. The. maximum
storms during the wet season were typically about 1.5 inches (38 ram) while
they were about 0.5 inches (13 mm), or less, during the dry season. These
conditions compare relatively well with the rain period of April, 1975,
through January, 197/, which was analyzed as part of the first Bellevue
report. That previous period had an annual average rainfall of about 34
inches (87U mm\ with about 60 storms per year. This earlier period included
less than typical rain quantities. The wet and dry season divisions, however;
were still the same as observed during this more recent stuuy period.
The variation in monthly rain totals, as shown in Figure 4-1, shews that
the first months of the two wet seasons studied (October and November) have
more rain than the following months of the wet season. The latter months in
the dry season (July and August) have less rain than the earlier dry season
months. This results in a general caw-tooth pattern, where the rain total
starts out low at the end of the dry season and then rises radically at the
beginning of the wet season. The monthly rain totals then decrease with each
succeeding month to a low point at the end of the dry season. During the
first year, November was the wettest month, while during the second year,
October was the wettest month. These wide variations in monuhly rain
characteristics, and the possibly repeating pattern of rains may be important
in designing a street cleaning program that is much more intensive before
these initial large rains of the wet season.
Most of the rain events that occurred during the study period were
completely monitored at both the Lake Hills and Surrey Downs sites. Appendix
Tables A-3 through A-5 summarize the observed rainfall characteristics for
these two basins on a storm by storm basis. These tables present the observed
total rainfalls, rain durations, and average and peak 30-minute rain
intensities for both basins. Ratios of the rain totals observed at each basin
were calculated. Duration ratios and differences in the start times for each
rain event are also shown on these tables. A total of 165 paired storm events
were monitored during this two-year study period. Lake Hills rain totals
averaged 12 percent more than the Surrey Downs rains. The average duration of
the Lake Hills rains.was about 11 percent longer than for the Surrey Downs
rains. The Lake Hills rains also started about 1/2 hour before the Surrey
Downs rains. The ranges of the individual storm values, however, varied
greatly. The total rain and duration ratios range from less than one-tenth to
more than three times, while the time differences are as great as 16 hours.
The following paragraphs discuss the major variations in rain characteristics
at the two sites on a seasonal basis.
17
-------
FIGURE 4-1
MONTHLY RflIN TOTflLS
LRKE K'LLS
JRRET DOWNS
UY t
Iff 11 12 13f U 15 16. 17 1£
0123456789
2Cf 21 27 23 24
MONTH OF STUDY
(from Feb. 1980 to Jan. 19B2)
-------
KU-uro «-2 shows tin- distribution of rain events and corresponding
runott volumes tor both studv sites and all study periods combined. Most of
the rain OV.MU s had les. than 0.25 inches (b.4 mm) of rain and less than ten
Percent ot the rain events had volumes greater than one inch (25.4 mm). VThen
Mu- raintall quantities are considered, most of the rainfall is associated
with rain events greater than about 0.6 inches (15 mm). The common small
rains do not add up to much rain volume. Rains smaller than 0.25 inches (6.4
mm) accounted tor less than 25 percent of the total rainfall volume, while
about 30 percent of the total rainfall volume was associated with rains
greater than one inch (25.4 mm).
The distribution of the runoff volume is also shown on Figure 4-2. Most
of the runoff is associated with rains greater than 0.75 inches (19 mm) while
the most common rainfalls of less than 0.25 inches (6.4 mm) produced less
than ten percent of the total runoff. The relationships between runoff and
rainfall are discussed in detail in Section j. The weighted averse Rv values
(runoff/rain) for both of the study sites was about 0.25. This value means
that about 25 percent of the rainfall left the watershed as surface runoff.
Three-fourths of the rainfall either evaporated or entered the soil. Much of
the rainfall entering the soil later left the study areas in the form of
baseflow between runoff events. The rest of th-? infiltrated rainwater either
recharged the underlying groundwater or was lost through evapotranspiration
by plants .
Differences in observed rain quantities for the same storm periods for
Lake Hills and Surrey Downs are shown on Figures 4-3 and 4-4. About half of
the rains that were observed simultaneously at both basins had a difference
in rain quantity greater than plus or minus 20 percent. This difference was
much greater for the small rain events than for the larger rain events. As an
example, several rain events measured about 0.3 inch (7.6 mm) in one basin
while only measuring 0.1 inch (2.5 -.-a) in the ether basin. This can result in
much more than a three to one difference in the observed runoff yields. As
described in Section 5, the smaller events result in a smaller fraction of
runoff than larger events due to infiltration and surface detention/storage.
When the resultant runoff yields from the two basins are compared for a
specific storm, differences in observed rains may be much more important than
differences in control measure applications. This is important for the
discussions in Part 4 on control measure effectivenesses.
Figures A-l through A-6 show the average monthly rainfall parameters for
two different basins. In most cases, the two basins have very similar
patterns in parameter trends, but the individual values for a specific rain
event may vary significantly.
Figures A-7 through A-9 present scatter plots of Lake Hills and Surrey
Downs rain totals, durations, and peak intensities transformed by natural
logarithms. This transformation allows certain statistical uests to be made
if the resulting distribution of data points is normal (having a "bell"
shapeV it also reduces the apparent importance of extreme values (helps to
identify real "outliers"). Figure A-7 plots the natural log of the Lake Hills
rain quantities against the natural log of the Surrey Downs rain quantities
for all observed rains. This figure shows the much greater variation in
-------
FIGURE 4-2
ro
O
RflIN EVENTS-RflIN VOLUMES-RUNOFF VOLUMES
30
25.
15.
a/
<0.1JG.l 0.2 I 0.3 I 0.4 I 0.5 I 0.6 I 0.7 I 0.8 I 0.9 I 1.0 >1.1
1- NUMBER J7"> RAIN FALL [ )- RUNOFF Raln Int(,;val
OF EVENTS VOLUME VOLUME
(Value shown is bocj inning of int»-rval
-------
FIGURE 4-3
LflKE HILLS/SURREY DONN5 WET 5ER50N RfllNS
X v x *
•***:*>•*
J I L
I I I
J I L
1 2
LBKE HILLS RflIN, INCHES
-------
FIGURE 4-4
LflKE HILLS flND SURREY DONNS RRIN5
1.25
o
a
.5.
* J®
.25
^
"'y'-v •-'+//>
.5 ' .75 1
LfllCE HILLS RfllN, INCHES
DRY SEASON
1.25
1.5
-------
V
observed rain quantities for the smaller rains than for the larger rains.
Rains having a total rain quantity of 0.05 Inches (1.3 mm) (corresponding to
a natural log, or In, \alue of about minus three) can have corresponding
rains in the other basv.1 .ranging from 0.03 to 0.15 inches (0.8 to 3.8 mm).
However, rains of 1.5 Inches (38 mm) in quantity have a much smaller
ariation, ranging from about 1.25 to 1.75 inches (32 to 44 mm) in the other
basin. The duration variation pattern, as shown on Figure A-H, is similar to
the variation pattern shown for total rain quantities. Short duration rains
in on^ basin can occur simultaneously with a wide range of possible duration
values in the other basin, while the longer duration rains have more equal
values in both basins. Figure A-9 compares the observed peak rain intensities
at the two basins. This figure is plotted upside down, with negative natural
log values. The data prints in the upper right hand corner of the figure
correspond to low rain intensities in both basins, while the data points in
the lower left hand corner correspond to the higher values. Again, the
pattern of variations is similar as for the duration and the quantity plots,
in that the small intensities have a much greater variation than '_he large
intensities. All of the intensities vary by much greater values than for the
other two rain parameters.
23
-------
SECTION 5
RUNOFF QUANTITY
03SERVED RAINFALL AND RUNOFF VOLUMES
As noted in Section 4. there is a major difference in the production of
runoff associated with rains having different volumes. This difference is due
to a changing runoff coefficient value for storms of different sizes and for
di/ierent initial soil moisture conditions. The runoff coefficient monitored
in this studv was the ratio of runoff volume to total rainfall volume, both
being expressed in inches over the test Hasins. This coefficient (Pv)
considers evaporation, transpiration, detention/storage, and soil
infiltration. When soil moisture conditions are low and/or if the total
rainfall volume is small, then the observed Rv value is small. If the ground
is wet at the beginning of the rain and/or if the total rainfall volume is
large, then the Rv value is larger. The soil can accept rain that is falling
directly on it at a rate equal to its infiltration capacity. If this
infiltration capacity is exceeded, the excess rainfall will run off the soil.
Therefore, runoff production on pervious surfaces is dependent upon the soil
infiltration capacity for the specific soil moisture conditions, vegetation,
the rainfall intensity, the rainfall duration, and the total rainfall amount.
Wh'^n rain falls on an impervious surface, much of the rain will flow off
the surface. The heat of the surface will result in some evaporation of the
water upon contact with the surface (flash evaporation), but this is more
important in areas having very hot days and sudden thunderstorms. Rain may
infiltrate through cracks or holes in the otherwise impervious surface and
enter the subsoil beneath, or it may be directed off of the impervious
surface to pervious areas for infiltration. Also, much concrete is slightly
pervious. If the runoff water is directed towards a lined (with impervious
materials) channel or to the street and gutter system, it can be called a
directly connected impervious t:ea. These areas may include rooftops,
sidewalks, and parking areas. Even for these areas, however, some of the rain
does not reach the urban runoff system. If the surface is in poor condition,
rain can infiltrate through the system, as noted previously; or if the
surface is not graded appropriately, water may pond on the surface for future
evaporation and "leakage". If the rain is very small, most of the sheet flow
could be gone before it has a chance to leave the impervious area. For large
rains, however, much more of the rainfall results in runoff from impervious
areas.
About 200 rain events were monitored for rainfall quantity and runoff
parameters in Surrey Downs and Lake Hills during the two-year study period.
Some of the smallest rain events (<0.1 inch or 2.5 mm) were not monitored
24
-------
because tl.ey did not pro^u.e significant runofl. At other times, 8Oir.e rain
events were not monitored because of equipment malfunction or because cne
equipment was being modified and not available.. Almost 99 percent of the rain
events that occurred at Surrey Downs and about 91 percent of the Lake Hills
-vents were monitored. Tables A-6 and A-7 in Appendix 1 list the rainfall and
associated discharge characteristics for each of the monitored rains in both
Surrey Downs and Lake Hills. Thes.- tables also show the total rain (in
inches) and the total discharge (in inches) and calculates the runoff
coefficient (Rv) ratio (runoff/rain) for each rain event. The rain durations
and the runoff durations are also compared. Typically, the runoff duration
can be expected to be greater than the rain duration, depending upon the lag
time at t'>e beginning of the rain between the start of rain and the start of
runoff. The average rainfall to rain duration ratio in Surrey Downs was 1.14
while this value was 1.24 at Lake Hills. For the smaller rains, this duration
ratio was actually less than one because of the proportionately larger amount
of infiltration of rain into the soil. The data presented in these two tables
are used in this section and elsewhere in this report for rainfall and runoff
quantity and quality calculations.
Relationships between runoff volume and rain volume are dependent on
many conditions. However, these conditions may be simplified by dividing the
study period into appropriate seasons and considering each area separately.
The antecedent soil conditions are usually satisfactorily considered in the
seasonal breakdown, while the different study areas consider the different
land-use configurations. Table 5-1 separates the rainfall and runoff
characteristics by season and study area. The total rain volume was slightly
greater in the wet season for boch areas; there were not as many of the
larger rain events during the dry periods of the study, and although there
were many more of the smaller rain events, most of the rain quantity occurred
during the larger events. During the wet seasons, most of the rainfall volume
was associated with rains greater than about 0.4 inct.as (10 mm). The median
rain volumes associated with the runoff were greater than for the rainfall
because of the increasing Rv values for increasing rain volumes.
Fiqures A-10 through A-13 in Appendix A show the distribution of these
rainfall and runoff parameters for both study areas and wet and dry seasons
separately. These are similar to Figure 4-2 in the previous section which
combined all of this data. The average Rv value in Lake Hills during the wet
season was about 0.3, and about 0.1 during the dry season. The Rv values in
Surrey Downs were less.
In order to separate the study period into seasons, characteristics of
the rainfall and runoff for each month were examined. Table 5-2 shows
equation coefficients corresponding to straight-line relationships between
rainfall and runoff (both expressed in inches). The resultant r values
(vhich is an indication of how well the calcvlated curve fits the data
points) were very good. In most cases, the CL value was greater than 0.95
with a value of 1.0 being a perfect fit. These equations are only good for
the larger rains and do not produce appropriate values for rains that are
smaller than about 0.1 inches (2.5 mm). (The predicted runoff volumes were
negative for these smaller raimi). The ota&erved runoff volumes for the small
rains were very small, but could obviously not be negative. The bottom of
25
-------
Table 5-1. RAIN AND RUNOFF VOLUMES
Lake Hills
wet
dry
total
Surrey Downs
wet
dry
total
Number
of events
113
107
220
98
102
200
Median rain
volume (in.)
0.23
0.17
0.20
0.23
0.20
0.21
Total rain
durina study
(in.)
44.96
30.55
75.51
42.79
28.15
70.91
Total runoff
during study
(in.)
14.36
6.08
20.44
10.56
4.91
15.47
Overall
Rv
0.32
0.20
0.27
0.25
0.17
0.22
All Combined
420
0.21
146.42
35.91
0.25
-------
Table 5-2. STRAIGHT-LINE EQUATION COEFFICIENTS TO
RUNOFF FROM RAIN VOLUMES (FOR PAINS GREATER THAN THE
MINIMUM VALV". SHOWN)!1)
Lake Hills
Surrev Downs
Month
January
February
March
April
May
June
July
AlJQUSt
September
October
November
December
lotal Wet
Total Dry
Rain
(inches)
0.01
0.1
0.2
0.4
0.8
1.6
2.5
Min.
intercept slope R? N Value
(rain)
-0.017 0.41
-0.0028 0.29
-0.048 0.40
-0.020 0.30
-0.011 0.21
-0.0090 0.22
-0.031 0.30
-0.013 0.26
-0.024 0.30
-0.046 0.39
-0.018 0.39
-0.029 0.45
-u.u^u u.jy
-0.023 0.30
Lake
wet
calc. calc
Runoff Rv
-O.oif
0.019 0.19
0.053 0.29
0.14 0.34
0.29 0.37
0.60 0.38
0.96 0.38
0.93 20 0.07
0.94 12 0.16
0.96 9 0.19
0.98 21 0.18
0.95 16 0.10
0.96 21 0.08
0.98 6 0.15
0.95 8 0.08
0.96 16 0.12
0.99 11 0.16
0.98 30 0.09
0.97 31 0.16
u.% yy o.iu
0,95 97 0.12
Hills
dry
calc. calc.
Runoff Rv
-0.020
0.007 0.07
0.037 0.19
0.097 0.24
0.22 0.27
0.46 0.29
0.73 0.29
Min.
intercepts! ope Ra N Value
-0.0047 0.26 0.98 19 O.C9
-0.0080 0.35 0.79 6 0.16
-0.010 0.25 0.93 20 0.11
-0.014 0.21 0.95 21 0.11
-0.011 0.23 0.97 17 0.14
-0.011 0.20 0.94 17 0.1]
-0.0096 0.19 0.99 7 0.15
-0.0056 0.17 0.94 7 0.08
-0.012 0,20 0.98 4 0.14
-0.026 0.29 0.99 13 0.16
-0.0017 0.24 0.98 25 0.05
-0.0098 0.31 0.95 31 0.08
-u.uo// u.'^y u.% 94 0.07
-0.010 0.21 0.93 98 0.11
Surre
wet
calc. calc.
Runoff Rv
-0.0049
0.020 0.20
0.048 0.24
0.10 0.26
0.22 0.27
0.44 0.28
0.69 0.28
y Downs
dry
calc, calc.
Runoff Rv
-0.0079
0.011 0.11
0.032 0.16
0.074 0.19
0.16 0.20
0.33 0.20
0.52 0.21
(1) runoff = intercept + slope (rainfall)
example for 0.5 inch rain in Lake Hills during April:
runoff - -0.02 + 0.03 (0.5) = 0.13 inches
and the Rv = ™noff/rain = 0.13/Q.5 = 0.26
27
-------
I able 5-£ allows tiow the Kv value increases with increasing rain volumes. Phis
table also shows that the wet season Rv values can be as much as two tines
the dry season Rv values for rains smaller than about 0.25 inches (6.4 mm).
The Lake Hills site also had generally larger Rv values tnan the Surrey Downs
site for rains greater thaa 0.1 inch (2.5 mm).
Figures r>-l through 5-« are nlots of observed rainfall versus runoff
volumes for both Lake Hills and Surrey Downs and separated for dry and we<-
seasons . These figures show how the smaller rain events have very low Rv
values, which then increase rfith the size of rain. The variations in observed
runoff for the smaller rains were quite large. This percentage error
decreases as the rain volume increases. The wet seasons included z single
rainstorm that wad about twice as large as the next largest rain. This very
large rain event (about; four inches , or 100 mci) accounted for much of the
total annual runoff. That single event rain volume is infrequent in Believue,
wich a return interval of once every several years. Even for this large rain,
the resultant Rv value was only about 0.4 in Lake Hills and about 0.3 in
Surrey Downs .
A detailed analysis of rain and runoff characteristics wac carried out
for most of the Lake Hills data. A multiple regression analysis relating Rv
to total rain, average rain intensity, peak rain intensity, and days since
last rain was made for each month. These analyses showed that the rainfall
volume alone accounted for about 95 percent of the calculated Rv value. The
peak rain intensity values accounted for between five and ten percent of the
total Rv value. Increases in Rv values were caused by increases in peak
intensity values. As the number of days since the last rain increased, the Rv
value Decreased. This antecedent factor can reduce the Rv value by about five
percent. These decreases in Rv with increase in antecedent dry periods was
probably due to the soils drying. It was found that average rain intensities
affected the Rv values by less than about five percent. The season of the
year was extrenely important in determining the runoff and rainfall
relationships. The Rv values for the winter (wet) months of November through
February were about 35 percent larger than the Rv values for the drier summer
months of March through October for the same rain characteristics. It was
concluded that there is no real need to adjust the calculated Rv values based
on rain intensity or preceding length of dry period: it is only necessary to
consider total rainfall and season.
THE EFFECTS OF LAND-USE ON RUNOFF QUANTITY
\ runoff model specific for Surrey Downs and Lake Hills was constructed.
This model crnsidered the specific land covers in each of the two basins and
the distribution of observed rains during the two year period of study. Table
3-1 in Section 3 listed the land covers in the Surrey Downs and Lake Hills
basins. This breakdown includes the percentage of the area and the total
square footage for vacant land, parks, back yards, front yards, rooftops,
driveways, parking lots, and streets. The resultant impervious and pervious
fractions were also calculated. It is important to separate the pervious
areas into these several classifications. These classifications are mostly
based upon their distance from the drainage system, size, and the amount of
28
-------
rj
UD
in
UJ
in
LJ
Z
o
z
.3.
.2.
.1.
FIGURE 5- 1
LRK.E HILLS DRY 5EH50N RfilN/RUNOFF
S
,6 ' .9
RflTN, INCHES
1.2
1.5
-------
.5
.4.
FIGURE 5-2
SURREY DOWNS DRY SER50N
o
Z
.1.
*****
I --L
I I
6 .9
RfilN, INCHES
i I
1.2
1.5
-------
1.5
FIGURE 5-3
LRKE HILLS NET SER50N RfllN/RUNOFF
in
5
.9.
x .
MM I I I I I I I I I 1 I I I I
1.5 2 '2.5
RfllN, INCHES
3.5
-------
FIGURE S-4
SURREY DOWNS WET 5ER50N RflIN/RUNOFF
1.25
O
1
.71
.5.
.25
X v * X
., ,tC XX
.5
1 I I I I I I I I I I I I LLU I I I I
1.5 2 2.5
RflIN, INCHES
_LJ_
3.5
4.5
-------
surface disruption. For those areas that are far fro™ the drainage area, much
of the rainfall could infiltrate before reaching the drainage system. Large
pervious areas, such as vacant lots and parks, may have more infiltration
than front yards that are located adjacent to the drainage systen- - Roof tops,
even though they are usually considered impervious, have most of their
uowr.spours in these two basins directed towards the surrounding back or front
ynriSs. This allowed much of the rooftop runoff to infiltrate into the soils
around the house. A portion of the driveways and parking lots are also
directed towards surrounding pervious areas. However, all of the street
surfaces are directly connected to the drainage system.
As previously discussed, the overall Rv value for the drainage basins
were very small for small rains, but then increased rapidly to a fairly
constant value for the larger rains. When this is considered in conjunction
with the runoff characteristics from the different land covers, the amount of
runoff originating from each of the land-use covers in the test basins can be
determined for each type of rain. This is very important when considering the
effectiveness of various control measures. If a control measure can
thoroughly clean a sub-area in the drainage basin, the observed effect on the
overall basin runoff quality is highly dependent upon the runoff and
associated pollutant contributions from that sub-area. This discussion will
consider the runoff quantity that originates from each of these land covers
for different rain types, study basins, and seasons of the year. Section 6
will discuss runoff quality and estimate the runoff pollutant contributions
from each of these land-use covers.
Table 5-3 shows how the composite Rv value is made up of different
land-use configuration runoff joef'•li-.ients (k). These individual land-use
coefficients are multiplitd by Lh" traction of the total area that each of
these land covers occupy (as shown p-e^iously in Table 3-1). Theae individual
land cover runoff coef1.cients a" 1 increase with increasing rain volumes and
as the distance to the drainage systec decreases. These runoff coefficient
values are much greater for the in pervious areas than for the pervious areas
for the same rains. Fcr very sroall rains, no runoff is expected to occur from
the pervious areas and froit the impervious areas that drain to these pervious
areas. Starting at about 0.1 inch (2.5 mm), however, the coefficients are
about 0.3 to 0.5 times the inaximum values that they are likely to have. The
dry season runoff coefficient values are less than the wet season values, due
to lower soil moisture conditions.
The runoff coefficient values for the impervious areas are lower than
most people would expect, especially for the smaller rain events. Especially
during the dry summer season, rainfall falling on these impervious areas can
be flash evaporated and/or ponded for future evaporation. These two factors
are extremely important for the smaller rain events. Even for the largest
rain events, the impervious component runoff coefficient values may be as low
as O.b for the dry season and 0.7 for the wet season. Runoff coefficient
values for paved areas are usually expected to range from about 0.7 to 0.95.
Values within this range are expected for large rains. Runoff coefficient *
values that are usually used in runoff modeling are also shown on this table.
These values from Claycomb, 1970, are usually within the values found for the
pervious areas and for moderate to large rain events. When a storm drainage
33
-------
5-3. F'JNOFF COEFFICIENT RELATIONSHIPS
SURREY PPWNS DRY SEASON
k values for each land cover and rain total
Rainfall (inches)
Land Cover
Vacant
Par'vS
Backyard
Front yards
Rooft oo s
Dri veways
°arkinq Lots
Streets
0.01
0
0
0
0
0
0.1
0.1
0.1
0.1
0.05
0.05
0.05
0.05
0.1
0,2
0. 2
0.35
0.2
0.05
0.05.
0.05
0.1
0.15
0.3
0.3
0.5
0.4
0.05
CL05
0.05
0.15
0.15
0.6
0.6
0.6
0.3
0.05
0.05
0.05
0.15
0.15
0.6
0.6
0.6
1.6
0.05
0.05
0.05
0.15
0.15
0.6
0.6
0.6
2.'
0.1
0.1
0.1
0.2
0.2
0.6
0.6
0.6
inches)
Literature
(Claycomb, 1970)
C.I to
0.1 to
0.1 to
0.1 to
0.75to
0.2
0.2
0.2
0.2
0.95
0.75 to 0.35
0.7
0.7
to 0.95
do 0.95
Ccmoosite °v
value: 0.02 0.10 0.15 0.20 0.20 0.20 0.24
SCS (1975)
values: too small for SCS method 0.1 0.3 0.4
LAKE HILLS - DRY SEASON
k values for each land cover and rain total
inches)
Land Cover 0.01
0.1
Rainfall (inches)
0.2 0.4 0.3 1.6
Literature values
2.5 (Claycomb,1970)
Vacant
Parks
Backyard
T rontyards
Rooftops
Driveways
Parking Lots
Streets
0
0
0
0
0
0.
0.
0.
1
1
1
0.05
0.05
0.05
0.05
0.1
0.2
0:2
0.35
0,05
0.05
0.05
0.1
0.15
0.3
0.3
0.5
0,05
0.05
0,05
0.15
0.25
0.4
0.4
0.6
0.05
0.05
0.1
0.15
0.3
0.65
0.6!,
0.7
0.05
0.05
0.1
0.2
0.4
0.7
0.7
0.75
0.]
0.1
0.15
0.3
0.4
0.7
0.7
O.S
0.1
0.1
0.1
0.1
0.75
0.75
0.7
0.7
to
to
to
to
to
to
to
to
0.2
0.2
0.2
0.2
0.95
0.35
0.95
0.95
Composite
Rv value: 0.02 0.10 0.15 0.20 C.25 0.29 0.34
SCS (1075)
values: too small for SCS method 0.1 0.3 0.4
34
-------
Table 5-3. R'JNOT COEFFICIENT RELATIONSHIPS (cont.)
SURREY OWNS - WET SEASON
k values for each land cover and rain total (inches
Rainfall 1
Land Cover
Vacant
Parks
Backyard
Frontyards
Rooftops
Driveways
Parking Lots
Streets
0.01
0
0
0
0
0
0.1
0.1
0.1
0.1
0.05
0.05
0.1
0.15
0.2
0.4
0.4
0.5
0.2
0.05
Q.05
0.1
O.L
0.2
0.5
0.5
0.6
0.4
0.05
0.05
0.1
0.2
0.2
0.6
0.6
0.63
( inches)
0.8
0.1
0.1
0.1
0.2
0.2
0.6
0.65
0.67
1.6
0.1
0.1
0.1
0.2
0.25
0.6
0.7
0.7
2.
0.
0.
0.
0.
0.
0.
0.
0.
5
15
15
15
2
3
6
7
7
Literature vaU
(Claycomb, 197
0.
0.
0.
0.
0.
0.
0.
0.
1 to
1 to
1 to
1 to
75 to
75 to
7 to
7 to
0.2
0.2
0.2
0.2
0.95
0.85
0.95
0.95
Composite
Rv value: 0.02 0.20 0.23 0.24 0.25 0.26 0.29
SCS (1975)
values: too small for SCS method 0.1 0.3 0.4
LAKE HILLS - WET SEASON
k values for each land cover and rain total (inches)
Rainfall (inches)
Land Cover
Vacant
Parks
Backyard
Frontyards
Rooftops
Driveways
Parking Lots
Streets
Composite Rv
value:
SCS (1975)
values:
0.01
0
0
0
0
0
0.1
0.1
0.1
0.02
too
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
small
1
05
05
1
15
2
4
4
5
20
for
0.2
0.05
0.05
0.17
0.22
0.25
0.5
0,5
0.6
0.26
SCS
0.4
0.1
0.1
0.18
0.28
0.33
0.6
0.65
0.67
0.31
method
0.8
0.1
0.1
0.18
0.3
0.38
0.7
0.75
0.75
0.34
0.1
1.6
0.1
0.1
0.2
0.3
0.4
0.75
0.8
0.8
0.36
0.3
Literature values
2.5 (Claycomb,
0.15
0.15
0.2
0.35
0.5
0.8
0.9
0.9
0.40
0.4
0
0
0
0
0
0
0
0
.1 to
1 to
!i to
.1 to
.75 to
.75 to
.7 to
.7 to
.1970)
0.2
0.2
0.2
0:2
0.95
0.85
0.95
0.95
35
-------
s'-'-tf. is iVs ix.rifd , tlu- Jf-ii^n stom Is a lar^e storm in order to reduce the
t ,i---. I ir,>; pot i-nt. ial in the en .linage basin. Very little research has been
"iri-cted to-Mrds i he nuch mure numerous smaller events.
These cr,.--i.:>nent runoff coefficient values were estimated based upon the
nv'i'i^ored c-iraposite Kv values, the rain totals, and the land rover
cor.t i ..;urjt ions. A trial and error procedure was used to fit the corresponding
runott coefficient values. Data from other locations and other land—use types
were also used in this analysis (especially Ottawa, Ontario; Pitt, 1982, and
Castro Valley, California; Pitt and Shawley, 1981). Unfortunately, the Surrey
Downs and LaKe Hills sites were auite similar- When the Bellevue 148th Avenue
runoff/rainfall Information becomes available from the USGS, then these
runoff coefficients can be confirmed for a different local land-use.
The calculated composite Rv values are within ten percent of the
observed v^lvies . They are also compared to values obtained using the SCS
(.1975} curve number method on Table 5-3. The SCS method was also developed
for the larger storm events and is not useful for those rains smaller Lhan
about one inch (25 nun). Unfortunately, almost all of the Bellevue rains are
smaller than one inch (25 mm). However, the SCS calculated Rv values were
high in all categories, except for the very largest rain events during the
Lake Hills wet season. There are modifications tnat can be made to these
initial SCS estimates that consider antecedent dry periods and more specific
soil information.
The portion of the total urban runoff flow (as measured at the outfall)
that originates from each of the land covers within the basin can be
calculated. Each individual runoff coefficient value ^as shown in Table 5-3)
can be multiplied by the corresponding land cover fractions (from Table 3-1)
to obtain the relative contribution of runoff that originates from each of
those land covers for different rains. Figures 5-5 through 5—8 show these
calculated estimates for different seasons and different size rain events.
Street surfaces are seen to contribute most of the urban runoff flows only
for the very smallest rain events (less than about 0.03 inch, or 0.8 mm, of
rain). The contributions of street surface flows to Lake Hills urban runoff
flows is greater than for Surrey Downs. For rains greater than about 0.1 inch
(2.5 mm), the contributions of street surface flow to the urban runoff yield
is estimated to be about 25 pel cent for both basins during the dry season.
These percentage contributions may decrease even more for the very large
events when more runoff comes from the pervious areas. For the very smallest
events, the only land covers that contribute any runoff at all are the street
surfaces, driveways, and parking lots. The rooftops and pervious areas start
to contribute runoff in important quantities after about 0.1 inch (2.5 mm) of
rain. When driveways and parking lots are added to the street surfaces, these
areas can contribute more than 50 oercent of the runoff in Surrey Downs and
more than about 40 percent in Lake Hills for most rains. Because of the small
number of vacant lots and parks in these basins, runoff in these areas
typically contribute only a few percent of the total runoff reaching the
outfall.
The resultant hydrograph frcm ? typical urban basin is made up of
various components from each of the land cover areas. Figure 5-9 shows how
36
-------
FIGURE 5-5
RUNOFF SOURCES Surrey Downs - Wei Season
100
DRIVEWAYS AND PARKING LOTS
0 P
0.01
0.025 0.05
0.1 0.2 0.4
RfllN (inches)
1.6 2.5
-------
FIGURE 5-6
CO
RUNOFF SOURCES Lake Hills - Wet Season
100
•f
c.
u
CD
Z
o
I
or
VACANT LOTS AND PARKS
DRIVEWAYS AND PARKITiG LOTS
0.01 0.025 0.05 0.1 0.2
RfllN (lnch«s)
0.4
0.8
1.6 2.5
-------
Co
UD
FIGURE 5-7
RUNOFF SOURCES Surrey Downs - Dry S
100
eason
OS
O
LJ
U_
U.
O
20_|
fio-Jl.
o m.
0.01
VACANT LOTS AND PAf
DRIVEWAYS AND PARKING LOTS
STREETS
0.025 0.05 0.1 0.2 0.4
RfllN (Inches)
0.8
1.6 2.5
-------
FIGURE 5-8
o
103
RUNOFF SOURCES Lake Hills - Dry Season
VACANT LOTS AMD PARKfX
o.oi
0.025
0.05
0.1 0.2 0.4
RRIN (Inches)
1.6 2.5
-------
150
FIGURE 5-9
Hypothetical Hydrogrcph for Urban Watersheds
Source from Amy, Pitl. Singh. Bradford and La Graf!. 1974
41
-------
tlu' initial Hows dur i n; -in urban runoff event will originate mostlv from
stiri't surtiu'os. Oil't-r in>pet ious areas located fuither from the drainage
Vsti-m start contributing fljws at later times and finally, after the ground
bocoiri-s saturited and it the rain lasts for a long enough period of time,
pervious surfaces start contributing flows. Flows from the directly connected
Impervious areas (street sir
-------
1E+0
FIGURE 5- 1 0
LflKE HILLS TOTflL FLOWS BT MONTH
E PLUS STORM RUNOFF
Iff 11 17 13 14* 15* 16 17 Iff 19T 201 21
10flfllfl13fiSEFlJ
l'23'4S6789
MONTH SINCE BEGINNING OF TESTS (2/80 TO 1/82)
23 24
-------
u
FIGURE 5- 1 1
SURREY DOWNS TOTRL FLOWS BY MONTH
750031}
SOdflL
0
1
60013 30.
550X1111
500030.
450010.
400030.
350030.
300030.
250030.
200010.
150030.
100030. \
BflSE PLUS STORM RUNOFF FLOW
234567
MONTH SINCE BEGINNING OF TESTS (3/S3 TO 1/82)
-------
FIGURE 5- 1 2
LRKE HILLS BRSE FLON (percent by month)
MflRCH
BPRIL
RUSLJST
SEPTEMBER
OCTOBER
FEBRUflRT
JflNURRT
DECEMBER
NOVEMBER
-------
FIGURE 5-1 3
LRKE .HILLS RUNOFF FLOW (percent by month)
RPRT { , . MHRCH
MflV
JUNE
JULT_.
RUOJST
SEPTEMBER
OCTOBER
NOVEMBER
FEBRUflRT
JRNUflRT
DECEMBER
-------
Table 5-4. Sl> rY DOWNS WO LAKE HILLS
BASE FLO* AND RUNOFF FLOWS
Surrey Downs
Lake Hills
Month
Z/80
3/80
4/80
5/80
6/SO
7/80
8/80
9/30
10/80
11/80
12/80
Total
1/81
2/61
3/81
4/81
5/81
6/81
7/81
8/81
9/81
10/81
11/81
12/61
Totul
1/&?
Base
flow
(ft3)
-
127,455
62,728
50,410
48,040
47,830
50,130
50,660
47,120
89,880
110,350
684,603
98,510
108,980
74,880
15,640
44,120
41,180
36,850
39,600
27,750
44,040
52,600
120,160
704,310
66,780
Total
runoff
(ft3)
_____
- 233,662
178,230
84,137
165,870
18,950
68,960
97,160
47,830
553,920
625,215
2,074,034
161,200
349,880
121,840
73,880
90,340
90,000
102,430
6,340
195,260
5bl,500
317,310
541,370
2,601,350
216,100
Base
F low
(ft3)
35,050-
69,870
51,720
23,632
22,610
21,850
27,780
30,900
22,830
44,730
87,235
433,207
78,720
43,410
77,310
38,890
?0,980
13,640
23,310
21,820
20,630
27,700
60,330
93,140
525,880
82,150
Total
runoff
(ft3)
293,940
315,440
285,240
73,165
204,500
17,530
91,550
145,200
56,210
817,790
879,800
3,175,365
205,790
340, 5? .0
157,420
185,360
118,840
128,610
175,390
3,860
416,880
684,010
539,030
801,280
3,756,990
357,600
Grand Total 1,455,693
4,891,484
1,046,237
7,289,955
47
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SFCTION b
URBAN KUN'OFF QUALITY
INTRODUCTION
Ore of the principal tasks of the Bellevue urban runoff project was to
collect samples representing as many runoff events as possible from the two
test basins. About 700 rains occur)Ci; in each basin during the two year study
period. Samples were collected for analyses from as many is 160 of these
rains in each basin using automatic samplers and flow meters. Appendix E
describe0 the sampling equipment and how it was used. Th.3 samp] ing equipment
vas set to initiate sampling it a predetermined runoff flow rate and to
obtain flow weighted samples throughout the duration of the runoff event.
The sampling equipment was modified to discharge the. samples into a
single 50-gallon (190-liter) Nalgene container wiuh plastic bottles
containing ice as a preservative. Because of the large sample container, the
sampling equipment was capable of collecting samples from small to very large
rain events. The smallest rain event that was monitored was about 0.04 inches
(1 mm) of rain. The largest rain events were more than four inches (100 mm).
The large events did require soone sampler servicing during the rain events.
The smallest rains were represented by about six subsamples collected
throughout the runoff period, while the large events contained several
thousand runoff subsamples. The samples vere removed from the sampling
equipment within several hours of the end of the event. The chilled samples
were then brought to the City of Bellevue's water quality laboratory where
they were separated into different containers that had appropriate
preservatives i'or the different chemical analyses. The Bellevue laboratory
analyzed the samples for r>H, turbidity, and specific conductance. The
preserved samples were sent to a commercial laboratory in Seattle for
analyses (Am Test, Inc.). The commercial laboratory anplyzed the runoff
samples for total solids, total Kjehldahl nitrogen (TKN), chemical oxygen
demand (COP), lead (Pb), zinc (Zn), and total phosphorus (P).
T.ie ranoff monitoring equipment was installed in mid-March in Surrey
Downs and in mid-April in Lake Hills in 1980. Because of some equipment
problems at the beginning uf the study period (due to the .lack of event
markers on the flow recorders) each station was temporarily deactivated for
equipment modifications. Some small runoff events (less than 0.1 inch, or 2.5
mm) w^re not monitored because the automatic stage activator (which turned on
the sampling equipment) could not detect small increases in runoff volumes,
above the existing base flows, without mary falsa starts. Therefore, only
about three-fourths of al1 of the rain events were sampled. Because the
larger runoff events were much more effectively sampled, a much larger
percentage of the total runoff volume was sampled.
48
-------
Uurlnr the period ot runoff monitoring, street surface particulate
sa;,p>^ were also collected c~* analyzed (as described in Section 7). The
bt-rert clcaninv program was varied during the runoff sampling program. The
urban runoff data was therelore separated into different groups corresponding
to the study d-eas, seasons, and street cleaning programs. Section 10
describes the street cleaning program and measurements in detail. Generally,
extensive street cleaning was used in one basin for a period of time, without
any cleaning in the other basin. After several months, this was reversed so
that extensive street cleer.ing was conducted in the opposite basin. Over the
two—car period of time, extensive street cleaning was conducted in eac'.i
basin during both the wet and dry seasons. Periods of no street cleaning also
occurred during the wet and dry periods in each basin. Runoff during a period
of time was also monitored corresponding to no street cleaning in either
basin at the same time. This schedule enabled the urban runoff quality and
yield data to be compared on the basis of street cleaning effort and by
season. Two extreme levels of street cleaning were used to simplify the
analyses and to present extreme cases for comparison. The extensive street
cleaning effort involved cleaning all streets in the drainage basin three
tiones a week. This has been sh iwn in previous studies (Pitt, 1979; and Pitt
and yhawley, 1981) to result in streets nearly is clean as possible using
conventional street cleaning equipment. More frequent street cleaning (every
day or even multiple passes in a single day) may result in slightly cleaner
streets, but at a much greater cost.
This section presents the urban runoff quality data by these study
period divisions. This data is also compared to the preliminary Nationwide
Urban Runoff Program (NURP) urban runoff quality data. The statistical
distributions of the concentration data is examined and variations in runoff
quality as a function of season are also shown. Baseflow sample/; are also
discussed. The observed urban runoff quality data is compared to beneficial
use water quality criteria. Calculated mass yields T-JI. the different storm
events and estimated seasonal and annual discharges are also shown. The
section finishes with a discussion of the potential source areas of the
different urban runoff pollutants.
OBSERVED URBAN RUNOFF AND BASEFLOW QUALITY
Much urban runoff quality data was collected during this project. Tables
A-8 through A-15 in Appendix A present the urban runoff quality data
collected during this study representing completely monitored runoff events.
Additional data was also collected for partial runoff events, but was not
considered in the analyses because it could be misleading. Table 6-1
summarizes this observed data. Average, minimum, and maximum values for the
water quality parameters, along with the flow and rain volumes, are shown for
eight project periods. Most of the periods have from 20 to 30 monitored rain
events. The Surrey Downs dry weather category unfortunately includes 51 data
sets without street cleaning and only four data sets with street cleaning.
Therefore, these two periods cannot be efficiently compared.
Table 6-2 comparts this observed Bellevue runoff water quality with
preliminary Nationwide Urban Runoff Program (NU.RP) data. The preliminary NURP
49
-------
I able 6-1. r8SERVED URSW RUNOFF QUALITY (COMPLETE
COMPOSITE STORM EVENT MEASUREMENTS ONLY) (• v Weather
Without. Street Cleaning
Runoff
Volume
(ftJ)
average 23,400
minimum 1,210
maximum 132,000
number of events: 23
With Street Cleaning
average 16,800
minimum 2,830
maximum 36,900
number of events: 24
Lake Hills Wet Weather:
Rain
(in)
0.35
0.04
1.33
0.27
0.08
0.53
Total
Solids
110
24
270
110
27
240
TKN
1.4
<0.5
5.9
1.1
<9.5
4
COO
54
13
120
44
20
120
Total
Phos.
0.42
0.015
3.6
0.28
0.1
1.2
Spec.
Cond.
Cwnhos/l
Lead
0.25
'0.1
0.56
0.17
<0. 1
0.5
Zinc
0.14
0.067
0.29
0.12
0.061
0.26
pH
5.
5.
fi.
6.
5.
7
(
1
3
6
1
2
c,n
42
22
140
30
17
61
Turb
(NTU)
15
6
35
24
6
67
Without Street Cleaning
average 61,400
minimum 3,060
.maximum 209,000
number of events: 32
With Street Cleaning
average 45,200
min imum 2, 590
maximum 223,000
number of events: 20
Surrey Downs Dry Weather
0.50
0.07
1.58
0.15
0.11
1.55
78
33
230
130
27
440
0.66
<0.5
1.4
1.0
<0.5
3.8
32
17
77
43
13
83
0.14
0.071
0.34
0.30
o.nc
0.92
0.11
< 0. 1
o'.4
0.18
< o. 1
0.31
0.094
0.03
0.22
0.11
0.053
0.?3
6.
5.
7.
6.
5
U .
6
5
1
0
5
8
40
22
85
31
19
55
16
6
82
38
1.7
150
Without Street Cleaning
average 18,600
minimum 1,263
maximum 10-3,000
number of events: 51
With Street Cleaning
average 39,700
minimum 8,590
maximum 78,800
number of events: 4
0.34
0.05
1.65
0.65
0.18
1.18
130
31
620
120
43
200
1.3
<0.5
4.3
1.2
0.5
2.7
61
21
150
40
15
54
0.32
0.068
1.2
0.29
0.097
0.59
0.18
< 0. 1
0.82
0.85
0.21
< 0.1
0.14
0.07
0.37
0.13
0.093
0.2
6.
5.
7.
..
_.
-.
2
2
4
38
16
95
-.
16
4
41
_,
50
-------
Table 6-1. OBSERVED URBAN RUNOFF QUALITY (c.ont.)
Surrey Downs Wet Weather
- Without Street Cleaning
average
minimum
maximum
number of events
Runoff
Volume
(ft3)
50,100
2,460
250,000
: 34
Rain
(in)
0.57
0.04
2.2
Total
Solids
95
29
270
TKN
0.84
<0.5
2.0
COD
43
19
no
Total
Phos.
0.17
0.002
0.38
ipec.
Cond.
(i
-------
Table 6-2. BELLEVUE RUNOFF WATER QUALITY CWPAREP TO NATIONWIDE (SU3P) DATA
Constituents
PH
turoidHy
Sotc. cond.
toUl sol ids
Chemical Oxygen
Demand (tiq/1)
Total Kjeldahl
Nitrogen {mg/1
Total Phosphorous
(rac/1)
Lead
Zinc
(rag/1)
Lake Hills
nin fiax nedian
5.2 7.1 6.2
6 150 17
17 140 32
24 440 37
13 120 36
<0.? 5.9 0.78
0.015 3.6 0.19
<0.1 0.56 0.10
0.030 0.29 0.11
* of
ofcser
31
96
93
98
99
99
9S
99
99
Surre) Downs
rnfn max -sedisn
5.2 /.4 6.3
4 67 14
16 300 38
29 620 95
15 150 42
<0.5 4.3 0.84
0.003 1.2 0.17
-'0.10 0.8^ 0.10
0.047 0.37 0.11
# of
obser
98
102
100
107
106
105
106
106
106
All Mm? Data
(as of 10/81)
m1n max median
2.8 10.1 7.0
0.2 4900 51
1.0 4400 330
21 23,700 ?40
0.3 1430 52
0.01 520 2.0
-------
da,a was available as of October, l'»81, and included data from many urban
runoff monitoring locations throughout the country. The Bellevue urban rur.off
i, of much better quality than typically found elsewhere. The median Bellevue
runoff water quality constituent concentrations are about half of the average
WAV concentration values reported. The Bellevue specific conductance values
are about one-tenth of the NURP axerage values. The amount and type of rain
at Bellevue, along with the urban land-use development practices were
probably responsible for these lower observed concentrations. The annual
rainfall at Bellevue (about 34 inches, or 86C mm) is not that much different
from the annual rainfalls at itany of the NURP project sites. However, the
typical Bellevue rains are much smaller than elsewhere, with many more rains
occurring in a year, and with resultant shorter interevent periods. With a
short interevent period, pollutants have a shorter time to accumulate. In
addition, the seller rains at Bellevue do not possess enough energy to
remove much of the deposited pollutants in the urban areas. The ranges of the
NURP event mean concentration va.1 ues are quite large and the Bellevue median
values are closer to the minimum than the maximum values. The mjch larger
range in reported NURP concentrations, compared to Bellevue concentrations,
is due to the much broader range of conditions and the larger number of
observations included in the NURJ' data base.
Ihe distributions of the observed concentrations for total solids is
shown in Figure 6-1. Distributions for the other constituents are shown in
Figures A-16 through A-23 in Appendix A. Those distributions show that the
most conmonly observed concentrations for each constituent are much closer to
the low side of the observed range than for the higher values. This is quite
common in many physical measurements that cannot have negative values.
Minimum values are bounded >> the zero value, while there is no absolute
limit to the upper values, c'eriodically, very large values may be observed
due to unusual circumstances. The distribution for pH values in Figure A-21,
however, shows a more "normal" distribution with the most common value
centered in the observed range. This is because pH is a measure of the
hydrogen ion concentrations in the water expressed as a negative log to the
base ten. This implies tnat the distribution of concentration observations
may be expressed as a Ijg-normal distribution. The actual form of the
distribution is import,-nt because it defines and restricts the use of certain
statistical tests that can be used to indicate differences and similarities
in the data. Many of ;he common statistical analyses (including least squares
linear regression analyses to determine an equation that fits the data
points, and Student's "T" test which indicates significant differences in
paired or unpaired .ata sets) require normally distributed values and equal
variances along the range of observations. If the data can be transformed to
fit a normal pattern, then these basic and powerful statistical analyses
procedures can be legitimately used.
Figure 6-2 shows a log-probability plot of total solids" concentration
values. Figures A-24 through A-30 in Appendix A shows the log-probability
plots for the other constituents (except pH). A straight line on normal
probability charts indicate a normal distribution of the observed data. When
the logarithmic transformation is made, nearly straight lines result for all
of the constituents, especially between the probability rangas of five and 95
percent on the log-normal charts. In some cases, a straight line occurs from
53
-------
a
60
40
38
20
<50
100
FIGURE 6- 1
TOTflL SOLIDS
150
200
«n
250
300
350
400
450
500
>550
HILLS Q-5URRET DOWNS
Concentration (Value shown is beginning of interval, mq 1
-------
7OO^
600
500
40O
too-
90
80-
w 7r- —
Surrey Downs
Lake H Us
10
FIGURE 6-2
20 30 40 50 60 ""0 80
Percent Less Than Concentration Values
95
98 99 99 5 99 8
Frequency Distribution of Total Solid* Concentration*
-------
the one to yy percent probaL'lity values. In many cases, however, the extreme
lo.j or high values do not iall on the straight line. This can be expected
because 01 the relatively small number of observations in each data set.
However, these small deviations in the extreme tails of trie observations do
not significantly alter the conclusions associated with the statistical
tests.
The previous bar graph non-transformed distribution plots and these log
probability plots show the observations for Surrey Downs and Lake Hills
separately. For total solids, COD, zinc, and specific conductance, the Surrey
Downs concentrations are greater than the Lake Hills concentrations. No
noticeable difference appears for the other constituents over the entire
range of constituent concentrations observed.
Concentrations also varied by month. Table 6-3 shows the average monthly
runoff concentrations observed for both the Lake Kills and Surrey Downs
sites. A general cycling of the concentrations was observed: the
concentrations were typically greater during the dry months than during the
wet months. These variations may have been caused by differences in the rain
characteristics (especially rain totals and frequencies) during the seasons.
If the pollutants are source limited in the drainage basin, then the larger
rain events would result in lower runoff concentrations. This, of course,
requires that the small rain events have sufficient energy to remove the
contaminants from the drainage basin. Some of the pollutants, such as lead on
street surfaces, may be considered source United, but other pollutants,
especially total solids, could not be considered source limited because
erosion potential usually increases with increasing rains.
Figures A-31 through A-38 in Appendix A are plots of observed runoff
concentrations as a function of rain magnitude for each of the two basins and
for the wet and dry seasons. The most common feature of all of these scatter
plots (with the exception of the pH plots) is that the maximum observed
concentrations occur for rains smaller than about 0.5 or 0.75 inch (13 or 19
mm). The concentrations of the runoff associated with rains greater than
these volumes fall into a much narrower band. The small rain events, however,
also contain many low mean event concentration values. These relationships
signify a dilution effect by the larger rains and an uneven amount of energy
to remove pollutants by the smallest rains, caused by varying rain
intensities. Even though the large rains observed include the largest rains
that are likely to occur in the area, increases in total solids or other
contaminants associated with pervious areas did not occur. In other areas
that experience much larger rains, increases in total solids concentrations
may be evideut for the very largest rains. These scatter plots also
differentiate observations obtained during dry and wet periods. Generally,
the highest concentrations for almost all of the rain volumes are associated
with the dry seasons. However, many wet season observations are also
relatively high. Again, the dry season rains would have long periods of
pollutant accumulations between them.
Baseflow samples were collected about once a month during the second
year of the project. These baseflow samples were collected using the
automatic samplers on a time sampling mode. The samples represent average
56
-------
Table 6-3. AVERAGE MONTHLY RUNOFF CONCENTRATIONS (mq/1)
Oan
Feb
Mar
Apr
May
June
July
Aug
Sept
Oct
Nov
Dec
Total
Solids
LH SD
120 126
112 93
69 95
89 110
130 110
115 170
98 120
130 270
130 130
90 100
100 86
81 94
COD
LH SD
39 50
38 46
36 48
37 43
46 67
51 74
45 60
86 IOC
54 56
42 39
37 40
32 36
TKN
LH SD
0.67 0.81
0.86 0.75
0.83 0.75
0.88 1.0
0.97 1.2
1.4 1.7
1.0 1.1
3.7 2.4
1.3 1.3
1.2 1.0
0.79 0.94
0.68 0.63
TP
LH SD
0.24 0.16
0.26 0.18
0.14 0.19
0.26 0.27
0.21 0.26
0.34 0.46
0.26 0.23
1.5 0.75
0.30 0.28
0.20 0.19
0.25 0.17
0.14 0.14
Lead
LH SD
0.18 0.16
0.20 0.12
0.10 0.13
0.16 0.17
0.21 0.13
0.24 0.22
0.16 0.14
0.37 0.44
0.23 0.17
0.16 0.11
0.12 0.11
0.11 0.11
Zinc
LH SD
0.095 0.11
0.089 0.090
0.094 0.11
0.095 0.11
0.12 o.n
0.13 0.16
0.11 0.14
0.23 0.25
0.15 0.15
0.11 0.11
0.11 0.13
0.094 0.11
-------
b.isot low concentrations over about 24 hours of Lime. Table h-A summarizes the
hasetlow wafer i|u,ilit' observations at the two sampling sites. The observed
hasetlow concentrations ot CUD, TKN , total phosphorus, lead, and zinc were
about the same as tor the storm runofl concentrations. However, the baseflow
total solids and speeitic conductance values were much greater than observed
in the storm runoff. The total solids material during storm runoff events is
mostly suspended solids, while the total solids during baseflow conditions is
mostly dissolved solids (based on ratios of specific conductance to total
solids). The similarities in baseflow and storm runoff nutrient and heavy
metal concentrations is surprising. In other areas (especially at the Castro
Valley MlKH site; Pitt and Shawley, 1981) the bnseflow and nutrient
concentrations were much less than the storm runoff concentrations. However,
the Castro Valley baseflow dissolved solids, specific conductance, and major
ion concentrations were all much greater than observed in the storm runoff.
In Castro Valley this implied that the baseflow was mostly associated with
diachargini; groundwater that originated in non-urban areas above the study
area. At the two Bellevue sites, however, the complete basins are urbanized
and the groundwater that discharges to the storm drainage systems between
rain events was much more contaminated than the rural groundwater discharges
observed at Castro Valley.
The nutrient and heavy metal urban runoff concentrations at Bellevue are
.uch less than observed at other NURP project sites. The Bellevue baseflow
concentrations are also much less than the average NURP runoff data, except
for total solids and specific conductance. In a later subsection, the
contribution of baseflow discharges will be compared to the annual storm
runoff discharges.
Additional Bellevue urban ""unoff information is included in the USGS
report on their portion of the Bellevue urban runoff project (Prych and
Ebbert, undated). The USGS used elaborate samplers that collected many runoff
samples at different time intervals during rain events. They analyzed many
samples for their monitored rain events for many more constituents than were
included in this program phase. However, the USGS sampled many fewer rain
events than included in this project.
Seattle METRO (Galvin and Moore, 1982) is also conducting a project
associated with the Bellevue urban runoff program. METRO'S study is directed
towards monitoring priority pollutants is urban runoff, urban runoff source
areas, and receiving waters. These priority pollutants include many
pesticides and industrial chemicals that have been shown to be carcinogenic.
Several heavy metals are also included as priority pollutants.
COMPARISON OF OBSERVED URBAN RUNOFF CONSTITUENT CONCENTRATICNS WITH WATER
QUALITY CRITERIA
Published water quality criteria are not really appropriate for urban
runoff problem identification. These criteria, even when expressed in terms
of safety factors for organisms present in the receiving waters, are designed
for continuous discharges and relatively constant concentrations. In most
locations, receiving water pollutant concentrations during periods of runoff
58
-------
Table 6-4. Base Flow nuality
Lake Kills Surrey Downs
Min. Max, Average # of Min. Max. Averane f of
Constituent mq/1 mq/i mq/1 Samples mq/1 mq/1 mq/1 Samples
Total Solids 108 326 210 13 130 226 195 13
COD 9.1 67 27 13 6.8 45 19 13
TKN 0.20 1.9 0.56 13 0.34 2.4 1.0 13
TP 0.027 0.?2 0.11 13 0.034 1.2 0.20 13
Lead <0.1 0.1 <0.1 13 <0..l 0.1 <0.1 13
Zinc 0.03 0.14 0.073 13 0.026 0.47 0.10 13
Spec. Cond 138 430 270 9 146 300 240 9
( pmhos/cm)
59
-------
v.i'v di ,11,;.11 i r;i 1 1 v I r urn t hi ha<<.'tlow coneon t r;i t i ons . In mist rapes, the
'-In,.tic. ;i.Uuii' ot stvirm rui'.ol' cannot he i-or.ip.i red to the water quality
t r i .1 I'.i.-.t ,ir- ti.-so' iatrd with cont inucvjs d i s^rlia rges . However, as was
d in i It.- l,i:. t subject tun, t lie Kisoflow and -form ruru'tl concentrations in
.ue rut that dissimilar, except lor total solids. The published
,...iv , t hr !"i't ore , be applicable when evaluating the storm runoff
di s.-li.n >,v conditions .it hei'''vue, especially fo\. "totally developed"
v.-uorOu-ds . Another important project associated with the Rellevue urban
lunott program was cond.icted by the University of Washington (Pcdersen, 1981;
Ki.M-rv, I'-'.V; and S<-ut t , Steward, and Stober, 198-i) through t.ie Corvallis Lab
ol tlie Kl'A and addressed receiving water measurements and effects from urban
run.>tl. 1 he (.Diversity of Washington study included actual beneficial use
impiirmrnt waturements by sampling the aquatic organisms most directly
atiect-'d by urban, runout. The observed biological conditions in selected
belK'vue urban runoft receiving waters were compared to the biological
conditions in similar bodies of water unaffected by urban runoff. This
subsection wtil compare published water quality criteria with urban runoff
con.-entrat ions observed during thi^ study. Refer to the University of
Washington study toi a more detailed discussion of probable urban runoff
ellects at Br.llevue.
Dissolved Oxygen
No dissolved oxygen measurements of urban runoff were obtained during
tiiis st.udy. Previous studies show that the DO of urban runoff is near
saturation due to the turbulence and thin sheet flow nature of most urban
runoff source waters. However, urban runoff contains various chemicals and
organic matter that can consume oxygen in the receiving water over a period
of time. Uroan runoff can be characterized as a wastowater having low levels
of organic matter and nutrients and high levels of heavy metals and possibly
other directly roxic materials. Urban ru-
-------
in the
,; hvdrogen sulfide, and the ueveloprcenf of .arbon dioxide and methane
n he sediments. Dissolved oxv^en in the wjter column can also cause
ch.-nncal oxidation ,,nd subsequent leaching of iron and manganest from
sediments. The eftects of dissolved oxygen on freshwater fish is complicated
becaus- fish vary in their o::ygeu requirements according to the specific
spe.ies, tt.eir age, activity, water temperature, and by the amour.t of food
present. Msh ;u e capable of surviving for short periods of time at very low
oxygen conditions. Most, researchers, however, report a dissolved oxygen
concentration of at least four mg/1 needed to support a --aried fish
population. However, greater concentrations will usually result in a greater
variety of species present. Fish embryonic and larval stages are especially
vulnerable to low oxygen conditions because of their lack of mobility. In
addition, low dissolved oxygen levels can adversely affect aquatic insects
and other animals upon which fish feed. As long as dissolved oxygen
concentrations remain sufficient for fish, no significant impairment of the
fish's resources, due to dissolved oxygen, are likely to occur-
Solids
Observed total solids concentrations in the storm runoff during this
study varied from about 20 to more than 500 mg/1. The average event mean
concentration value was slightly less than 100 mg/1. The total solids
concentrations during baseflow conditions averaged about twice these
concentrations. The total solids during storm runoff events are mostly made
up of suspended solids while the total solids during baseflow conditions are
mostly made up of dissolved solids. Much of the so-called suspended solids
during urban runoff events may settle out in the receiving water as
sediments.
The criteria for suspended solids and aquatic life beneficial uses is
usually considered about 80 mg/1. This is about equal to the observed total
solids concentrations during most of the urban runoff events in Bellevue. The
total dissolved solids criteria varies appreciably depending upon the
resistance of the aquatic species and other uses. Tl:Js total dissolved solids
criteria is usually associated with restricting the salinity of the water and
would usually be much greater than observed during the storm runoff events or
during baseflow. Therefore, the most important effects of solids is
associated with the suspended solids during storm runoff events and the
accumulation of settleable solids on the stream beds.
Susi ,..ided solids can affect fish life in several ways; by directly
killing une fish, or by reducing their growth rate or their resistance to
disease, for example. Suspended solids also affect fish by limiting
successful development in fish eggs and larvae. Suspended solids can also
modify natural movement and migration of fish and can reduce the abundance of
fish food available. The most direct effects of suspended solids are the
reduction of light penetration into the water column and the heating of the
surface waters. Settleable materials associated with urban runoff solids
blanket the bottom of waterbodies and damage the invertebrate populations,
ruin gravel spawning beds, and, if they are organic, can remove substantial
quantities of dissolved oxygen from overlying water. The most important
51
-------
I'liect ot urban ruiintt s>:l; 's in Bi'llevut? receiving writers is probably the
rout i i 1ml ion of se 11 leablt' s i 1t s and rlay;; covering the gravel spawning beds.
The .ibrasion ot fish gills by Che solids may also be important.
N i t ro^.rn
The only form of nitrogen monitored by this urban runoff project was
total Kjeluahl nitrogen, which is a combination of the organic nitrogen forms
and ammonia. The most common forms of nitrogen not included in this analysis
are nitrates and nitrites. Organic nitrogen may make up most of the total
Kjeldahl nitrogen in some cases, and ammonia may be more prevalent in other
cases. The un-ionized ammonia (ammonium) form of nitrogen ammonia is toxic to
aquatic organisms. This un-ionized ammonium is usually less than about 25
percent of the total ammonia concentrations in the urban runoff. Average
ammonid concentrations in Bellfwue storm runoff and baseflow would be much
less than sevetal hundred mlcrograms per liter. However, the maximum observed
total Kjeldahl nitrogen concentrations, as high as about six mg/1, signify
the potential for high ammonia concentrations. At these very high total
Kjeldahl nitrogen concentrations, the mi-ionized ammonium concentrations may
be several hundred micrograms/liter.
Rainbow trout have been reported to be the most sensitive fish to
un-ionized ammonium (the most toxic form of ammonia). Concentrations of 0.2
ing/1 ammonium are lethal to rainbow trout, while values less than this can
exert adverse physiological or histopathological effects. At concentrations
or three mg/1 total amnionia, trout have been reported to become
hyperexcitable and, at eight mg/1 total ammonia, 5U percent of the trout died
within 20 hours. Carp are usually the least sensitive fish to ammonium.
Sublethal exposures to ammonium can cause extensive necrotic changes and
tissue degradation in various organs. Concentrations of 2 mg/1 un-ionized
ammonium can be lethal to carp (EPA, 1976); The observed total Kjeldahl
nitrogen concentrations indicate the potential for some adverse ammonium
concentrations, but this would likely be restricted to rare runoff events.
The typical sto-rai runoff concentrations do not indicate recurring ammonia
toxicily problems.
Nitrate concentrations in storm runoff may also be important. Even
though not included in the total Kjeldahl nitrogen analyses, the presence of
large amounts of organic nitrogen and ammonia may indicate high nitrate
concentrations. Nitrate is a common major ion and was monitored as part of
the USGS monitoring program. Preliminary results from the USGS (Ebberu,
Poole, and Payne, 1983) show nitrate concentrations of about 0.025 mg/1.
Maximum concentrations of several mg/1 were also observed.
The 96-hour concentration of nitrates capable of killing half of the
bluegills in a test (96-hr LC-50) was two mg/1, while a value of 0.09 mg/1
nitrate plus nitrite had no significant effect on growth or feeding habits of
largemouth bass and channel catfish (EPA, 1976). However, rainbow trout are
much iiore susceptible to nitrate concentrations. Trout weighing 200 grains
experienced no mortalities after ten days with nitrate plus nitrite
62
-------
tom-,nr.r,tions ot L-..
-------
1'he dissolved lead COIK nt rat ion values that have been shown to bo
lethal to tish are much greater than the dissolved lead concentrations
exported in the Bellevue urban nnioft or receiving waters. A small fraction
ol total load that was observed in the Beilevue urban runoff is expected to
oeeui as eitlor organic, lead forms or other soluble lead forms. However, the
aecimui la t ion of paniculate lead iorms in sediments receiving urban runoff
has ho en shi.-.-n to potentially cause adverse effects on the benthic organisms
U'itt and Bozeman, 1982).
The observed total zinc concentration in the Believue urbin runoff was
about D.I mg/1 and Tnaxitnum values were about 0.4 mg/1. The base flow
concentrations were slightly less.
Rainbow trout have been reported to be the most sensitive fish to zinc
in hard waters, with lethal concentrations for coarse fish being three to
tour Limes the rainbow trout values. Immature insects seem to be less
sensitive than many of the test fish. For fathead minnows, 96-hour LC-50
values in hard water were reported to be 33 mg/1. However, at the
much-reduced zinc concentration of 0.18 mg/1, an 83 percent reduction in egg
production was found, as compared to a zinc concentration of 0.03 mg/1. One
to two gram fathead minnows had 96-hour LC-50 valu~ , of 8.2 to 21 mg/1
anhydrous zinc sulfate. Fathead minnow eggs experienced 24- to 96-hour LC-50
values of 1.8 to 4.0 mg/1, also with anhydrous zinc sulfate. Fathead minnow
fry 24- to 96-hour LC-50 values were less, at 0.87 to 0.95 mg/1 anhydrous
zinc sulfate. Two to three gram fathead minnows 96-hour LC-50 values were
greater, at about nine to 13 mg/1 anhydrous zinc sulfatt. Juvenile rainbow
trout 96-hour LC-50 values in hard water were about 7.2 mg/1 zinc sulfate and
were reduced to 3.2 mg/1 for 48-hour exposures to elemental zinc. One to two
gram bluegills experienced 24- to 96-hour values of about 41 mg/1 anhydrous
zinc sulfate (EPA, 1976)
The observed total zinc urban runoff concentrations in Bellevue are less
than most of the reported dissolved zinc concentrations that may cause
potential problems. As for most heavy inetal.s, EPA recommends a water quality
criteria value of 0.01 of the critical LC-50 values for the aquatic organisms
present. Again, since most of this total zinc is in a particulate form, the
dissolved zinc levels in the urban runoff and baseflows are still likely to
be less than these roore critical values. However, settleable particulates may
contain these relatively high zinc concentrations and may cause long-term
adverse effects for the benthic organisms in the sediments.
Summary
It is evident from the preceding discussion that the forms of Fiany of
the water quality constituents determine their toxicities. During a previous
urban runoff study in San Jose, California (Pitt, 1979), typical urban runoff
constituent concentrations for a broad list of common ions and heavy metals
64
-------
wore a.aH.ed usir^ an equilibrium water chemistry computer program. This
prorrar, w',s used to estimate the specific inorganic chemical compounds that
wrre proKiSly present in t -,e urban nmoff and to estimate which pollutants
would probably remain soluble and which pollutants would probably accumulate
in urban runoff sediments.
Most of the urban runoff pollutants were predicted to be in soluble
forms and would, therefore, be carried in the water column. However, this was
not t.ie case for some pollutants. For example, 95 percent of the inorganic
lead was predicted to be insoluble. Depending upon the size of these
paiiicles (or the particles to which they may become attached), the lead
could remain in suspension or could settle out in the storm drainage system
and/or the receiving waters. Chromium and phosphate may also settle out. The
settling of lead particles co the sediments was substantiated in field
studies in ?an Jose, as relatively high concentiations of lead were found in
urban Coyote Creek sedir.-nts (Pitt and Bozeman, 1982).
The soluble fractions of other inorganic constituents monitored were
primarily insoluble ionic forms, including calcium, magnesium, sodium,
potassium, sulfatc, chloride, and nitrates. Most of the carbon dioxide is
expected to be in bicarbonate forms. Most of the phosphate is expected as
soluble phosphoric acid, but important fractions of phosphate may occur as
insoluble calcium phosphate and lead phosphate forms. Almost all of the lead
is expected to be in particulate lead carbonate or lead phosphate forms, with
only a few percent of the lead occurring as soluble lead ions or soluble lead
carbonate forms. Almost all of the zinc and copper are expected to occur as
soluble ionic forms, while the chromium is expected to occur as soluble
chromium hydroxide.
This computer analysis considered equilibrium conditions and only
inorganic forms. Urban runoff is definitely not at chemical equilibrium and
many organics are also present. However, long-term sediment conditions are in
equilibrium and many organic complexities have small effects on solubility.
These expected chemical forms can be used as guidelines when estimating the
potential for toxic materials to accumulate in sediments.
In summary, direct urban runoff receiving water effects during rvnoff
events may not be significant. Potential immediate dissolved oxygen demand is
balanced by the supersaturated oxygen conditions in urban runoff. In special
conditions, dissolved oxygen during runoff events may be important.
Suspended solids concentrations during runoff events may not be
important, except for infrequent very high suspended solids concentrations.
Ammonium and nitrate nitrogen concentrations may periodically be in adverse
concentrations during storm events. Most of the Bellevue urban runoff water
quality problems are expected to be associated with long-term problems caused
by settled organic and inorganic debris and particulates. This material can
silt up salmon spawning beds in the Eellevue streams and introduce high
concentrations of toxic materials directly to the sediments. Oxygen depletion
caused by organic sediments and the lead and zinc concentrations in the
sediments may all affect the benthic organisms. These benthic organisms are
important food for the fish in the receiving waters and they may be adversely
65
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• )!tiiii-il ovri luiij', pet tin's ' l i mi . Drii^Lic cl.,)n>;es in benthlc organism
l"Mn' ' ••' l >lils -md tin- .ihseuce ot di.'si r;)hle tlsh have ixjcn noted in other urban
MiiMtl rei r i v i 11)-. w.Uer studies (Titt and Bor.eman , 1982).
'•'.ASS YIM.nS OF 1'OLl.UTAMS FROM LKHAN ARF.AS
The urban runoff quality data and the runotf volume da'^a presented
e.irlier were used to calculate the urban ninoff pollutant mass yields for
t'.ich rain event monitored. Tables A-16 through A-23 in Appendix A list these
calculated values tor the different drainage basins, seasons of the year, and
periods of different street cleaning practices. These yield values occurred
over wide ranges because of the wide ranges ot runoff volumes and
concentrations observed. Table 6-5 summarizes the estimated annual mass
yields for baseflow and runoff in both basins. The observed runoff yields
from the monitored stortns were used to predict the expected runoff yields
from the storms that were not monitored. The urban runoff annual discharges
shown on this table are based on about 75 percent direct measurements and
about 25 percent estimates. The baseflow values are based on the two-year
baseflow volumes between all storm events but only on the year two baseflow
quality concentrations.
There is an apparent difference between the runoff discharges in Lake
Hills and Surrey Downs when expressed on a pounds per acre basis. However,
the total annual runoff plus baseflow discharges from the two basins arc
quite similar. This implies that a much larger ftactioa of the total urban
runoff in Surrey Downs occurs as baseflow between rain events. The runoff
events in Lake Hills are more sharply defined and the Lake Hills baseflow is
a much smaller fraction of the total urban mass yields.
The estimated annual mass yields of the urban pollutants expressed in
pounds per acre per year are similar to those reported in San Jose,
California (Pitt, 1979), and in Castro Valley, California (Pitt and Shawley,
1962). The much smaller urban runoff pollutant concentrations observed in
Bellevue when compared to these other two locations is compensated for by the
much larger amount, of runoff that occurred.
Figures 6-3 and 6-4 show the variations of the annual runoff and
baseflow mass yields by month for total solids in the two basins. May through
August only contributed about five percent of these annual mass yields in
each month. November and December each contributed between 15 and 20 percent
of the annual mass yields. The contributions of runoff and baseflow volumes
were greater in those months that had high runoff volumes. The runoff and
baseflow concentrations for many pollutants were similar. The effects of
different flow volumes on total runoff yields for each event was also
studied .
Figures 6-5 through 6-8 show variations for total solids and lead for
both Lake Hills and Surrey Downs. These scatter plots show log transformed
value:; of flow versus lop transformed values of storm yields. These log
transformations were necessary to even out the observed data distribution.
These transformed distributions were analyzed using curve fitting routines
66
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Table 6-5. Annual Urban Runoff Mass Yields (Ibs/acre/year)
Constituted
Lake Hills
base storm total
flow runoff
Surrev Downs
base storm total
flow runoff
Total Solids
COD
TKN
TP
Lead
Zinc
67
8.7
0.18
0.035
0.02
0.024
250
100
2.4
0.61
0.40
0.27
320
110
2.6
0.65
0.42
0.29
100
10
0.53
0.10
0.03
0.053
180
79
1.6
0.35
0.23
0.21
28C
89
2.1
0.45
0.26
0.26
67
-------
LRK.E HILLS
29
16.
O
4»
O
7; 8
c
a:
«*-
o
FIGURE 8-3
Total Solids Yield by Month
FEB
RUNOFF
MRft
JUNE I JULY I RUG I SEPT
n
OCT
NOV
hBfiSEROW
J
DEC
-------
FIGURE 6-4
SURREY DOWNS - Total Solids Yield by Month
20
MRR
RPR
MfiT
JUNE
JULY
RUG
SEPT
OCT
R
NOV
DEC
RUNOFF Q-BflSEFLOW
-------
FIGURE 6-5
LRK.E HILLS - Total Sol ids by Season
54 .6
20.1
£
O
u
03
7.39
2.72
1.00
O
O
0.37
0.
0.051*
1100
O WET
A 0
o° Q
*
0 „
2980
8100 22,000 59,900
FLOW (cubic feet)
163,000 4 4 2 , C ~ 0
-------
SURREY DOWNS
FIGURE 6-6
- Total Solids by Season
54 .6
0.05
HOC
WET
2980
A DRY
8100 22,000 59,900 163,000 442,000
FLOW (cubic feet)
-------
FIGURE 6-7
LfiKE HILLS - Lead by Season
0.00091
0 . 0 0 0 3 4
0.00012
0.000045
1
* a * A
° *< v^
A * n° --<*
/ A* A 0 0-
./- , - o* e* »
A A »• j,
- /^ 0
i— ^ ^/ 0 0
A
/'
x-'" ^f'
^ / A
/^^^ <*
,/ 0-
/•
o wiv.
22000 09,1,00
FLOW (cuhic
-------
u . 0 5 C
0.018
0.0067
<
0 . 0 0 0 9
0.0003-i_
0.00012-
0 . 0 0 0 0 4 :j
1100
FIGURE 6-8
SURREY DONN5 - Leod by Season
e *
2980 8100 22,noo 59,9GO
A DRY FLOW (cubic fuc. t)
-------
t!..H rr.j'iirrd evonlv distributed data. "I he data show on fie.-.e figures are
se-.-.ir.-i'i d in1 season, and bands of equal concent ratio-1 values are drau-r on
t!'<.':.f figures tn ir.Jioate si >.;ni { i t-,-,n t concentration shifts for different flow
v •'. .-,; ,i's . The total solids concentrations associated with the small events (of
abi.n'. 1 ,000 to !'),(.(nr cubic feet, or 2K,i>00 to 280,000 liters of flow) had
concentrations of about li.'H mi;/1 of total solids. When the runoff volumes
ii1' ;eased subt, t ant i a 1 1 y to about 1OO.OOO cuhic feet (2.8 million liters;, th.-
i»i <1 solids eor.cenr ! t.t ions decreased to about 75 mg/1. Again, these figures
sh'.v t lu appreciable spread in observed concentrations for events in all flow
c i tev'.ori es . The Ica.i da t i are much more grouped because of the high detection
1 i ;T' i t >'•[ the lead analysis procedure useu. These data transformations are
UM.I) in Section 9 to identify changes in runoff mass yields for the different
pollutants as a function of season, runoff flow, and street cleaning program.
b-Ul'-KCK ARLA C'lMKlBllluNS OF URBAN RUNOFF POLLUTANTS
Determining the relative importance of different urban areas in
contributing MI bar runoff pollutants must be based on an understanding of the
natui il and ma i-related processes and ouppi^mented by limited data. It is
very difficult to monitor individual source area components and attempt to
n.-.ke an urban runort mass balance. This would require a very substantial
monitoring effort over a fairly long period of time. Several types of each
contributing source area Must be monitored because of seemingly minor
differences th.'.t can result in major differences in sh?et flow runoff
qualities. The previous discussion on urban runoff water sources from
different source areas is extremely important in trying to determine sources
of urban pollutants. Most of these source areas, however, are expected to
have different pollutant strengths. Some urban sheet flow grab samples bave
been collected and analyzed for important ui ban runoff pollutants in San
Jose, California (t'itt and Bozejian, 19^2). Castro Valley, California (Pitt
and Shawley, 1981), and in Ottawa, Ontario (Pitt, 1982). The site-specific
urban runoff flow information previously described can also be used with
local measurements of urban runoff partlculate strengths and source area
particulate strengths.
Urban runoff particulate strengths can be estimated by dividing the
ru'ioff constituent concentration by the associated total solids
concentration. This results in a unit of milligrams of constituents-per
kilogram ot total solids, or parts per million (when multiplied by 1000).
These runoff relative c "entraiions can be compared to the concentrations
found for source area particulates (such as street dirt, soils, drainage
sediments, etc.). If the urban runoff relative ^trengch is greater than for a
specific source area particulate strength, then that source area is not an
iir.povtant contributor for that specific constituent. In other words,
particulates from other source areas have stronger relative concentrations
and;or are mere effe:tive in reiching the outfall. Hcwever, if a specific
source area relative strength is greater than the urban runoff relative
strength, then that source area is probably an important urban runoff
pollutant source for that constituent.
-------
7'- relative concentration of the urban runoff constituents can be
cal,-ul.u,-.l iron the concentration data shown in Tables A-8 through A-15 of
<...r«".^lx A. TIIC resultant relative concenti at ions can be expressed as
mlllif-r^« ot constituent per kilogram of total solids, or parts per million.
The runotl relative concentration values for Bellevue are surprisingly ni?h,
possiMv bcc.n.se ot the relatively low concentrations rf total solids in the
rum,tl.'Mud. of the chemical oxvgen demand and the nutrients are expected to
be as soluble forms. These dissolved strengths are higher than the street
dirt pollutant solids strengths discussed in Section 1. The total Kjeldahl
nitrogen and ;inc runoft pollutant strengths are five to ten times greater
than the observed street dirt pollutant strengths while the total phosphorus
pollutant strengths in the runoff are about three to five tiroes the street
dirt strengths / The chemical oxygen demand and lead strengths are about twice
the street dirt strengths. Vhe runoff concentrations and loadings observed
for Bellevue are relatively low, but the street dirt strengths were about the
same as compared to other locations studied. The higher particulate strengths
in the runoft v,l.ei-. compared with the street dirt pollutant strengths may
indicate an accumulation of the larger, less polJuted street dirt
particulates in the storm drainage system.
important sources of problem pollutants ar.j related to various uses and
processes. These include natural sources, sucli as rock weathering to produce
soil, groundwater infiltration, volcanoes, and forest fires. Automobile use
usually affects the road dust and dirt more than other particulate sources of
street runoff. The road dust and dirt quality is affected by vehicle fluid
drips and spills (such as gasoline and oils), gasoline combustion, and
vehicle wear products. Local soil erosion and pavement wear products can also
significantly contribute to street surface particulate loadings. Urban
landscaping practices potentially affecting urban runoff include vegetation
debris disposal and fertilizer and pesticide uses. Animal wastes also affect
urban runoff quality. Other sources of urban runoff pollutants that may be
important in specific cases include fireworks debris, wildlife, and sanitary
wastewater infiltration. The quality of rain, snow, and atmospheric dust
fallout are all affected by urban particulate resuspension after initial
deposition. Many manufacturing and industrial activities also affect urban
runoff quality, especially settleable air pollutants. Therefore, it is
extremely difficult to identify a small number of activities that contribute
most of the significant urban runoff pollutants.
Some relationships between sources and specific pollutants are evident.
Natural weathering ana erosion products of rocks probably contribute the
majority of the hardness and iron in urban runoff. Road dust and associated
autoirobile use activities contribute most of the lead in urban runoff. In
certain situations, paint chips can also be a major source of lead. Urban
landscaping activities can be a major source of cadmiuw. Electroplating and
ore-processing activities may also contribute cadmium.
Many pollutant sources are t'lso specific to a particular area and
ongoing activities. Iron oxides, for example, are associated with welding
operations and strontium, used in the production of flares and fireworks,
would probably be found on the streets in greater quantities around holidays,
and/or at the scenes of traffic accidents. The relative contribution of each'
75
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iii those potential u'b.in nmot t |ollutant sources is ther"tore highly
v.iri.ible. di p'".ut i',u; on spiel tic ,k"lt.e conii i t. ions atii! seasons.
Tables t>-b and h-7 ar«> qualitative summaries th.it show the Types of
ui ban runott pollutants i.er/rally associated with different source areas.
Thev indicate that no single area should be vKwed as c.ont rit.ut irr the
m.ijoritv of anv given type of pollutant, desp'te the fact that certain areas
are consistently important sources of certain pollutants. For example, street
surfaces ate consistently shown 1.0 be responsible for significant
contributions of many heavy metals. Similarly, oxygen domandinj; materials and
nutrients are shown to originate r.ostly from landscaped and vacant areas.
Table (j-b do lines the urban runoff pollutants in terms of general classes of
water quality jarameters (.e.g., nutrients, bacteria, and heavy metals). Table
d-7 is similar jut defines the urban runoff pollutants in terms of various
common materials (e.g., auto exhaust, litter, and feces).
An important information netd for urban runoff sources studies is
knowing the relative contributions from different pollutant sources in the
watershed to the outfall yield. Sources that are far from the storm drainage
system and require considerable overland flow have a very low yield of most
pollutants when compared with parking lots or street surfaces which are
impervious and located adjacent to the drainage system (hydraulically
connected). Those areas that are further awiy from the drainage system may
require directed or sheet flows of the runoff to pass over pervious areas.
This increases the infiltration of the polluted waters into the soils and
enhances their uptake by vegetation along the drainage routes. Barriers can
also cause ponding and settling of polluted sediments from the runoff. All of
these factors significantly act to prevent the contaminated particulates from
reaching the receiving waters. However, during large storms, especially when
the ground is saturated, the erosion of these now contaminated soils may
significantly degrade orban .runoff quality. In addition, the resuspended
contaminated street surface particulates (by wind and automobile induced
turbulence) can be redeposited in adjacent non-paved areas. These street
surface particulates that contaminate the nearby soils reduce the quantity of
street surface particulates directly affecting the receiving waters. These
redeposited street surface particulates can then be washed into the receiving
waters duriag periods of high erosion.
As mentioned previously, some urban runoff sheet flow samples have been
collected and analyzed in other areas. Sheet flow samples during several rain
events were collected from small watershed areas such as building roofs,
parking lots, vacant lots, and gutters. Rainfall samples were also collected
In many cases. Table 6-8 shows the relative concentrations of pollutants in
source area runoff in San Jose as summarized by Pitt and Bozeman (1982).
Rainwater was found in roost cases to have the lowest pollutant concentrations
while parking lot and gutter flow samples had the highest concentrations.
Puddles in a park area were also sampled and found to have higher specific
conductance values and concentrations of total solids and nitrates than other
samples.
More recent sampling in Ottawa, Ontario (Pitt, 1982), indicated that
almost all of the lead in u^ban runoff originated from parking lots and
-------
Table 6-6 SOURCES OF I!R"AM RUNOFF POLl'ITANT":
Street Parking Landscaped
Rooftops Surfaces Lots Areas
jC t i
Sediment
Oxygen Demanding Matter
Nutrients
Bacteria
Heavy Metals
Pesticides & Herbicides
Oils and grease
Floating matter
Other toxic materials
Land
Source: from Pitt and Bozeman, 1982
-------
Tahlo 6-7. SOURCF', Of MATERIAL" WHICH LFAO TO 'P",A'| '"HOT P'iL'
I awn and
L'lrul'.r apod Vacant °arHnn
, Lot;'; Roof'.np'; '"i i'l'"//-! 11^ s l.o*''; r
Sourer.-: from Pitt and Bo/ornan, I9.fi/1
Oustfall X XXX XX
Precipitation X XXX XX
Tiro Woar X X X y
Auto Fxhair.t
P.:rt ic u
Othf-r Auto Ike:
(Fluid Orins,
Woar Prod.) y X
Von«>t,ition I. it tor XX XXX
Coir,truct ion
Fro-; ion X
Othor Lit tor x XXX
Bird Foros X XXX
Dog Foco-s XX XXX
Cat For,os X X
Forti1i/or Uso X
Pr.-,tir; ido U',o X
\
-------
Table 6-8. Relative Concentrations of Pollutants in Ruroff
from Major Areas (^
Parkinn Lots, Residential Landscaped
Driveways, Roofs Areas
and Streets
Constituent
pH 1.1 1.0 1.1
Spec. Cond. 4.0 1.0 220
Turbidity 300 <1 23
Total Solids 21 1.0 130
COD 9.0 1.0 3.5
Total Phosphate 4.7 1.0 .4.0
TKN 2.0 1.0 1.8
Lead 70 1.0 2.0
Zinc 19 15 1.0
'! The lowest reported concentration of a snecific constituent is
arbitrarily assigned 1.0. The other source values are multiples of this
lowest value.
Source: frctn Pitt and 3ozeman, 1982.
79
-------
street sutt.uos w\ t !x \vrv 1 i t1 lo lead found in rutiot f front root" Lops , vacant
a!".v! lav,v{v«-apod aicas, , relative flow
contributions as shown in Figures ^5 t.uoux',h 5-8 in Section 5. Estimates of
the impottance ot vaiious source1 areas vvr° nvuic and are shown as Figures b-9
through ii-l-». These figures are only es'. 'mates -9 shows
that street surfaces contribute very small amounts of the rvnot t~ total solids
Articulates tor rains greater than 0.1 inch (2.5 nu ). The na^or sources o,.
total solids for almost all rains in Bclltvue are expected to be the
landscaped front and hack yards. Figure fc-10 shows that street surfaces
contribute important fractions of the urban runoff GCD for almost all rains.
Driveways and parking lots also tikiy contribute i^.ixirtant quantities oi COD.
The previous areas surprisingly contribute relatively small fractions of the
expected urban runoff CUD. Tne rel.iCive contributions of phosphates and total
KjelJ^hl nitrogen as shown in Figures 6-11 and o-12 are, as expected,
similar. However, streets may contribute important aiaounts of these
nutrients, especially for ihe stiller rains, becavse during the sraallev
rains, street surfaces contribute alraost all of th= runoff flows. Pervious
and iipervious source areas contribute about equal amounts of the nutclents
tor taost of the rains. As expected, lead, as shown in Figure 6-13, is mostly
contributed by street surfaces for all rains, rrivevays and parking lots
supply almost all of the rest cf the lead in urban runoff. Zinc is also
contributed mostly by street surfaces, driveways, and parking lots; but, for
soiae reason, high rooftop zinc concentrations have been noted.
Rainfall is typically less effective in removing aa^erials from rough
pavement (e.g., streets surfaced with oil and screens or streets in poor
condition) than from smootn pavenent (e.g., asphalt sTeets in good
condition). It is thought that the increased roughness mechanically traps
particulate matter and also reduces sccur velocities at the pavement/water
interface. These mechanisms have the effect of preventing some of the
materials which havt eroded frosa surrounding areas from reaching the storta
drainage systeia.
The araovmt and character of runoff pollutants from a given site depend
on factors sxich as the intensity and duration of the stona event and the
length oi the antecedent dry period (i.e., the period of pollutant
accumulation). Large storms (ones with high intensities a:id/ar large rainfall
volumes) result in sisall co».trioutions of the street surface particulates,
relative uo the total runoff partlculate yield. This pattern is sore
pronounced when tiift antecedent dry periods ate short. During such conditions,
the street surfaces stay relatively clean (because of the iret;uent rains). A
large rain will result in significant erosion froa the surrounding saturated
pervious *reas, so that eroded aaterials becoas deposited on the streets
after the storm's end. It is expected that areas with moderate raiafail
intensities and long periods of accumulation (i.e., dirty street surfaces and
dry surrounding soil conditions) would have raost of their urban runoff output
associated with street surface washoff.
-------
FIGURE 6-9
00
URBRN RUNOFF SOURCES FOR TOTHL SOLIDS
100
DRIVEWAYS AND PARKING LOTb
0.01
0.025 0.05 0.1 0.2
RRIN (Inches)
1.5
-------
00
INJ
0.01
FIGURE 6- 1 0
URBflN RUNOFF SOURCES FOR COD
YARD?
VACANT LOTS A:;D PAPK.,-
FRONT YARDS
DRIVEWAYS AND PARKING LOTS
0. 025 0. 05
0.1 0.2
RflIN (Inches)
0.4
0.
1.6 2.5
-------
c»
OJ
FIGURE 6- 1 1
URBflN RUNOFF SOURCES FOR PHOSPHRTE5
c
01
u
L
0)
CL
CD
•—•
o:
O
LJ
U)
O
in
0 Z
0.01
VACANT LOT3 AND PARK::
BACK YARDS
FRONT YARDS
DRIVEWAYS AND PARKING LOTS
0.025 0.05
0.1 0.2
RfllN (Inches)
0.4
0.
1.6 2.5
-------
0.01
FIGURE 6-12
URBflN RUNOFF SOURCES FOR TKN
0.0^5 0.05
0.1 ('. 2
RflIN (Inches)
0.4
-------
100
80.
8 70.
L
01
- 60.
o
CO
u
a;
50.
40_
20_
10.
0
0.01
FIGURE 6-13
URBHN RUNOFF SOURCES FOR LEflD
Kj()E'TO.r)S AND ALL PLi'V I Ol\; AIT.A:;-
DP IVLUY.YS A:;D PARK m; LOTS
STRLF.TS
0.025 0.05
0.1 0.2 0.4
RflIN (Inches)
0.8
1.6
-------
FIGURE 6- 14
0 p
0.01
URBflN RUNOFF SOURCES FOR ZINC
0.025
0.05
0.1 0.2
RflIN (Inches)
(i.4
0 . 8
1
-------
Pui-i:::; storms ot moderate to low intensity, the <:>• ,;nt ul truf'ic has
K'LU tound to have an important influence on lv- -^,-ree to which poll-Hants
will be transported into the storm sown '.,, ;-•;.• ."em. T:.,;tic can suppl> some
ot thi' energy needed at Che street ;,urfa<.-e r> loosen partii'u! n res V
increasing tlu- scour ;i-.d viear velocities; .U th(> w.-iter/s>tre-ct Inferio.
When Light. srt.'-ais ccrnr a f. nlghc (or at or bur tii.itiy of low traffic), very
Jtttif street ij.!rt jould W loosened, am1 there would be little opportunity
for it to be transported along the street and gutter systerc. In summary,
estima'ed yields from different source areas in a watershed are very site and
tiir.e dependent (i t is necessary to c<-,-.sider pavemei.: characteristics,
antecedent weather conditions, current storm character Istics , and traffic
condit ions).
Appendix G includes a more detailed discussion of the sources of urban
runoff pollutants, based upon studies conducted from many location.'
throughout the country. Appendix C also describes the chc.mlcal quality, of
soils in urban areas, the mechanisms of automobile use tt.'at contribute heavy
metals, the role of landscaping activities In urban areas that contribute
runoff pollutants, and the internal cycling of various pollutants lr an urban
area due to atmospheric resuspension of urban dusts with subsequent
particulate red-aposition. Appendix H reviews the reactions and fates of
import ant urban runoff pollutants, also based upon literature i.iformation.
This appendix discusses the chemical reactions of urban runoff pollutants
after they enter receiving waters, especially the redox reactions. Absorption
and ion exchange are also discussed.
87
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SKC1 li'N 7
SJKI-.hl I'IKi U1.\KACTKKl hi ICS
This section discusses characteristics ot street surface pa rt icu lates .
Thf topics considered are factors at letting street r lea ;i 1 i nes •_ , street
suitart1 i> i r t i cu la t e accumulation and deposition rates, t ht >J i s t ; i bu t i on of
street dirt in driving and parking lanes, and the chemical strengths of
stteet surface particulates. The Hellevue street paniculate characterization
information was also compared to similar characteristics determined for other
areas. The uniquo HeLlevue climatic conditions, as described previously in
Section s attect certain street surface paniculate characteristics.
FACTORS AFhECTING STREET CLEANLINESS
Appendix E describes Che experimental design sampling that was conducted
as part of the Bellevue tests. The experimental design street surface
particulate samples were collected from about 20 to 50 locations throughout
each of the three Surrey Downs sub-areas and the Lake Hills and 148th Avenue
areas. These samples were collected about every six months and were designed
to measure the street surface particulate loading variabilities that occurred
in each of these areas as a function of season. Appendix E also describes how
the street surface sampling effort was modified periodically to reflect the
changes in variabilities that were noted.
Each of the many samples in each test area were accompanied by complete
sampling area descriptions. The most important information noted related to
street condition, traffic density, topography, and land-use. The season of
the year was also noted. This data was used to identify the characteristics
most important to determining street surface loading values. Each series of
experimental design samples were collected within one or two days and had
similar accumulation periods. In some cases, data were not used in this
analysis because the experimental design sample collection effort was
interrupted by rains. Because each experimental design sample location was
the same for each of the sampling periods, a paired Student's "T" test was
used to identity significant differences in observed loadings due to season
only. A paired "T" test was used because the street condition, street
density, topography, and land-use would not change for the same loca ion at
different times during the two years. There were three sample sets in Surrey
Downs: April and November of 1980 and July of 1981. The April and July
sampling times were conducted during dry seasons while the November sampling
effort was conducted during a wet season When the April and July samples
were compared using a paired "T" test, no significant difference in sample
88
-------
lo.tdiTH's uvrt- observed. However, when the November sample data were compared
t,, botn in- Anril .md July data independently, the loadings were
si/niticantlv different at greater than a 95 percent level. The average
Surrey Down/ loadings in April and July were about 400 Ibs/curb-mile (110
£/ curb-meter ) in November.
Similar analysed were conducted during two sampling periods for Lake
Hills. An October, 198U, sample series was compared with a July, 1981, sample
series using a paired Student's "T" tet't. For these Lake Hills tests, no
significant difference was found between these wet and dry season dates. The
average street surface loading values were about 220 Ibs/curb-mile (62
g / curb~'jieter ).
Samples from two test dates (April, 1980, and July, 1981) were available
for the lOHth Street sub-area in Surrey Downs. The paired "T" tests for these
two dry..season samples again showed no significant difference. The average
loadings in this sub-arta were about 400 Ibs/curb-mile (110 g/curb-meter).
Only one set of experimental design samples were available for the Westwood
Homes Road sub-area in Surrey Downs (April, 1980). The average loading values
were about 2,000 Ibs/curb-mile (570 g/curb-meter). There was also a single
set of experimental design samples available for i48th Avenue (March, 1981).
These samples resulted in an average street surface loading value of about
1 ,01'U Ibs/curb-mile (280 g/curb-meter). These experimental design data
pointed out the need to separate the Surrey Downs area into subsections,
especially considering that Westwood Home Road and 108th Street did not have
curbs and could not be cleaned by the city street cleaning equipment.
Using a nonpalred Student's "T" test, dry season samples collected in
Surrey Downs were compared with dry season samples collected at 108th Avenue,
for Westwood Homes Road and in Lake Hills. There was no significant
differences found for the Surrey Downs and 108th Street samples. However,
very significant differences were detected between the Surrey Downs and The
Westwood Homes Road samples and the 108th Street and the Westwood Homes Road
samples. The July 1981 samples for Surrey Downs and 108th Street were also
compared and were not significantly different.
Additional Student's "T" tests were conducted by grouping the
experimental design data into categories corresponding to different street
conditions, topography, and season. In some cases, there was disagreement in
the street condition and topography at the same sites during the different
sampling periods. This data was therefore eliminated from the analyses. The
ma]or difference observed in Lake Hills was for topography, where levels of
significance greater than 95 percent were observed in both the July and
October sampling periods. Flat areas during both sampling periods had average
loads of about 240 Ibs/curb-mile (68 g/curb-meter) while the area in Lake
Hills with some slope averaged about 140 Ibs/curb-mile (40 g/curb-meter). As
noted previously, there were major seasonal differences observed in Surrey
Downs, but not in Lake Hills. There were no significant differences observed
in Lake Hills based upon the differences in street conditions, probably
because of the narrow range in street surface conditions that existed within
the study areas.
89
-------
!'i : ! L-ri-iirt •; i:i ••!-!••-•'.•[ lo.icM -t-.s uti )4Hth Aveimp due to street slope <,ere
n-.. ir, •.:..!',! v s i >-ii 11 : c.i'.t ,a tin- hi) percent levp]. F.'.it stretches of 14Hth
..vi-:;ij'j !•.ni slnrt suiMrt: 'u.uiinr.s ot about 1,H)U ibs/curb-pile (280
V. ciiru-En ti-r). it «.ou]d !>> expertH.l that steeper slopus would result in lower
t>trt.'et surlaee loadings, such a.-; occurred in Lake Hills.
y-.'caus" ot the results of the Student's "T" tests, further statistical
tests UMIIJ; factorial analyses were conductpd on the experimental design
liit). A two-level, tlTt-e-wy factorial analysis was conducted on both the
La..- Ill lib and Surrey IJovns experimental design data. The three factors
cu iis i«J.--i i d were strict condition, topograohy, and season. The two levels were
traded tor fair or poor versus good street surface conditions; flat streets
versus streets-, with greater slopes; and dry versus wet seasons. The data was
codt-d uhln^; plus one values for those conditions expected to increase street
iiirlace loadings (lair or poor street surface conditions, flat topography,
and dry seasons). The other level for each condition was assigned a minus one
coding value corresponding to expected decreases in resultant loading values.
AK^in, data with conflicting coding values on the data sheets were eliminated
from this analysis. A total of eight different possibilities can occur for
these three factors. From two to seventeen observations were available for
each of these eight factors for the Lake Hills data. Many more data were
available for the Surrey Downs test site.
figures 7-1 and 7-2 show the results of these factorial analyses. Figure
7-1 shows the resultant calculated effects on probability paper for these
three main factors and their inteiactions. Those main effects and
interactions corresponding to a straight line on the probability paper .nay
occur randomly and are, therefore, not important effects. Major effects or
interactions that do not fall on the straight lines are significantly
different and are not likely to occur due to random conditions. In Lake
Hills, the only significant effect observed was associated with season. The
resultant model shows that loadings during the wet seasons are expected to tx?
about 145 Ibs/curb-mile (41 g/curb-meter), while the loadings could increase
to about '.'.35 Ibs/curb-mile (67 g/curb-meter) during the dry season. This
confirms the Student's "T" test observations by indicating the overall
importance of seasonal effects on the Lake Hills data.
The Surrey Downs data is also shown on Figure 7-1 and does not indicate
a single overriding effect. The diffarences in loadings observed in currey
Downs were associated with the interactions between all three effp^ts. The
expected Surrey Downs loadings could range from a low of about I'D
Ibs/curb-mile (48 g/curb-meter) for a negative three-way interacLion code
value to a high of about 460 Ibs/curb-mile (130 g/curb-meter) for a resultant
positive three-way interaction code value. A negative three-v?ay coding value
would occur vhen any one of the effects are negative and the other is
positive, or if all three effects are negative. The three-way interaction
would be positive if any one of the three conditions is positive, with the
other two being negative, or if all three are positive. This is obviously a
confusing interaction and shows che importance of obtaining as much
information as possible during a set of field studies.
90
-------
Enc-cf
1) Street Condition
2) Topography
3) Season
Coding:
4- 1 : Fair/Poor- 1. Good
4- 1: Fiat 1: Slope
4- 1: Dry • 1: Wet
Surrey Downs •
Lake Hills *k
• 123
78 5
64.3
- 35.7
Models:
Surrey Downs: y = 317 + 144 &
Lake Hills: y=216 + 185«'2
(usey =190+ 45*2)
C 50
Estimated EHoct
ISO
ZOO
coo
23 Factorial Analysis Results
for Experimental Design Street Paniculate Loading Data
FIGURE 7-1
91
-------
Surrey Downs •
Lake Hills ir
' •
* ..'*
18 75
-150
-100
Modal Residuals (y-V)
Residual Analysis of Factorial Models
for Exptr mental Design Street Paitlculate Loadings
FIGURE 7-2
92
-------
Figure 7-2 is a prcbaMlity plot of f.e residual values using these
raodeis. The calculated residuals for each of the eight possible combinations
of main effects and interactions can be fitted to straight lines, within
reason. The residuals (deviations from the calculated results using the
model) are therefore random and are not expected to be associated with any
other effects, except those shown to be important using the factorial
analysis.
These results are site specific and are probably different not only for
other cities but also for other locations in the same city. As noted, street
surface conditions did not appear to be a major consideration ia determining
the street surface loadings in any one of the Bellevue sites, because the
range in street surface conditions was not very great. A similar factorial
analysis was conducted using the Castro Valley. California, street surface
loading particulate data collected in 1978 and 1979 (Pitt and Shawley, 1981).
The Castro Valley study area had a much greater range in street surface
conditions than the Bellevue study sites. A five-way, two-level interaction
examined with the Castro Valley data included street condition (fair or poor :
versus good), traffic density (moderate or heavy versus light), land-use ;
(residential or vacant lots versus commercial or school), topography (flat
versus moderate or steep slopes), and season (summer versus winter). Again,
the datj was coded with positive values for variable levels probably
associated with increasing street dirt loadings. Instead of the eight
possibilities associated with the tests conducted with the Bellevue data, 32
possibilities were associated with the Castro Valley data. Each of the 32
data sets had one to twenty-two data points. The seasonal effect was found to
be very large in relationship to the other effects. The next most important
effect was street condition, followed by a random occurrence of the other
effects. The data was then separated into the two different seasons and
further factorial analyses were conducted. During the winter conditions, the
three-factor interaction of street condition, traffic density, and topography
was the only important factor. During the summer, however, street condition
was the only important factor. During the winter season, the expected street
surface loadings would vary from about 600 to about 700 Ibs/curb-mile (170 to
200 g/curb-meter) depending upon the three,-way interaction described. During
the summer, however, the street surface particulate loadings could be much
greater, ranging from a low of about 1,400 Ibs/curb-mile (400 g/curb-meter)
to a high of about 2,800 Ibs/curb-mile (800 g/curb-meter), depending upon the
street surface condition. The three-factor interaction during the winter
caused a relatively small change in the expected loading value, while the :
street condition contributed a much greater change in the expected loading
value during the summer months. ;'
STREET SURFACE PARTICULATE ACCUMULATION AND DEPOSITION RATES
A major element of the Bellevue urban runoff project involved collecting
street surface samples to compare with the monitored storm runoff yields and
to determine street cleaner performance. Another important use of this
information was to estimate the deposition and accumulation rates for the *
vaiious street surface contaminants.
93
-------
Hy the midd'e ot January, 1982, about 60U good street surface
arrunui lat ion samples wer>> colK-cted from five test areas (198 in the Surrey
Downs oleaniar, area, 104 on lUHth Ave, 52 on Westwood Home Road, 28 on 148th
Avenue S . E . , ar.d 220 in the Lake Hills area).
In Appendix B, Tables B-l through B-13 present the loading values for
these bUU street surface particulate samples. These tables show the date of
sample collection, the sample identification number, the days from the last
significant rainfall and the number of days from the last street cleaning.
The observed r_.tal solids street surface loading values are shown along with
the calculated median particle sizes using procedures described in Appendices
E and F. The data from these particle size analyses were used to calculate
the median pnr^icle size. These tables also inclvde the street cleaning
effectiveness data (loadings on the street before and after street cleaning)
that will be discussed in Section 10. These tables divide the data into the
five test areas and by season. The Surrey Downs and Lake Hills data -ire also
divided nto categories associated with periods of intensive street cleaning
and periods of no street cleaning.
Each street surface sample is identified with a specific accumulation
period. This accumulation period is the time since that test area was last
cleaned with mechanical street cleaning equipment or the time since a
signific t rain washed the area. A significant rain is defined as a rain
capable ot washing most of the available street dirt from the street
surfaces. Based on the rainfall and washoff analyses from this and past
street dirt collection projects, a significant rain is estimated to be one
with a total of about 0.2 inches (5 mm) or more of rain falling within
several hours (irrespective of traffic conditions), rain with a peak
instantaneous five-minute intensity of at least 0.5 inches (13 mm) per hour
(also irrespective of traffic conditions), or a rain with an average
intensity of 0.1 inches (2.5 mm) or greater per hour with moderate to heavy
traffic. Rains and traffic conditions which meet one of these criteria are
capable of imparting enough energy to the street surface to loosen the
available contaminants and to supply sufficient water to flush them along the
street surface and gutters and on to the storm sewerage inlets. If sufficient
runoff is not available to carry the particulates through the storm sewerage
to the outfall, material will be deposited in the sewerage system.
The observed street surface particulate loading values for each sample
were plotted to observe changes in loadings with time and to determine the
initial deposition and long-term accumulation rates. The deposition rate is
the initial accumulation rate which occurs over the first several days. The
two factors which affect the accumulation rate arc the deposition rate and
the removal rate. The accumulation rate equals the deposition rate minus the
removal rate. The deposition rate is a function of various characteristics of
the area, specifically climate, land-use, traffic, and street surface
conditions. The removal of pollutants can be accomplished either by street
cleaning, traffic-induced turbulence, or naturally by winds or rains. The
difference between the accumulation and deposition rates at any time is
assumed to be caused by material blown from the street surface by wind or
traffic-induced turbulence. This material can remain suspended in the air,
but most of it settles to the ground within about 30 feet (10 meters) of the
94
-------
roadway.
figures 7-3 and 7-4 are plots showing the observed street surface
loading%alu.-s as a function of accumulation time for the Surrey Downs bcsin.
Plots for the other study areas are shown in Appendix B as Figures B-l
through B-5. The data has been separated by test area, season, and if the
test ba-in i-as undergoing intensive street cleaning or no street cleaning.
figuie 7-3 shows that for periods of no street cleaning in the dry season,
accumulation periods of up to about 45 days were observed in some cases.
However, during periods of intensive street cleaning, the accumulation
periods were much shorter and did not exceed five days.
There is appreciable scatter in this data, especially for the low
accumulation periods. Much of this scatter is because of the relatively low
street surface loadings observed. The accumulation curves shown on these
figures were determined using a combination of least squares multiple
regression curve fitting techniques and Student's "T" analyses. The curve
fitting procedures used require that the variations be evenly distributed
throughout the range of conditions and that the observations are evenly
spread over the range of the independent variable (accumulation period in
this case). Therefore, the accumulation data was log transformed before the
curve fitting techniques were used. Even so, the resultant curves had very
poor regression coefficients. The accumulation information was also analyzed
by stratifying the data into relatively short accumulation periods. These
periods corresponded to a tenth of a day or less, a tenth to two days, two to
five days, five to ten days, ten to fifteen days, fifteen to twenty-five
days, and greater than twenty-five days. The data was also separated for the
dry and wet seasons.
Significant differences were identified by Student's "T" analyses
conducted on accumulation data for tha different seasons. The median values
for each of several accumulation period groupings were used to construct the
accumulation trend shown on these figures. If two adjacent accumulation
periods did not show significant differences, then they were combined and the
trend was flat over that range of accumulation. The dry season samples were
also separated for data collected during 1980 and for data collected during
1981. In almost all cases, the 1981 dry period had street surface loading
values significantly greater than the 1980 dry period during the time of no
street cleaning. The wet season data is not separated for analyses by year
because mcdt of that data was collected during continuous months during the
fall and winter of 1980 and 1981. The 1980 and 1981 dry seasons, however,
were separated by the five month wet season. It is not known why the 1981
loadings were significantly greater than the dry period 1980 loadings. During
a previous study in Reno and Sparks, Nevada (Pitt and Sutherland, 1982),
street surface loading values were obtained from a variety of street surface
conditions throughout the Truckee Meadows area during two adjacent six-week
periods during the summer of 1981. The observed loading values were
significantly different during the two adjacent periods possibly because one
of the periods was associated with much greater winds. In most cases, the.
windy period had much larger street surface loading values and larger
deposition and accumulation rates. This was probably due to the nature of the
sources of street surface particulates in the Reno and Sparks area (probably
95
-------
FIGURE 7-3
SURREY DOWN5-HITHOUT STREET CLERNIMG
1033.
93n_|L
IE
830_1_
i
_Q
I/I
2 53
B_J
un
2 40L
_j
o
a:
2 20E
13C
3
L^T ©
SE.0-
» Q
i i
A
0 O
DPY
e
V;LT
A A
-Q "A DRY (1930) _Q__
i H
tl 13
A WET SEAt:OU
m DRY SEASOrl (1980)
6 DRY SEASON (1981)
23 33
RCCUMULflTION (Doysl
43
53
-------
FIGURE 7-4
SURREY DOWN5-WITH STREET CLERNING:RCCUM
500
e
_a
u
ut
.0
in
a
40£
30i
S 20E
o
in
a:
o
10
0 b
"A
A
&
AQ
Q
0
0
i
&
DRY
0
0
o
A
WET _...
A
A
0 1
1 WET SEASON
d DRY SEASON
2 3
flCCUMULRTION (Days)
-------
I i .uispui tfd sands i rum the surrounding dry areas or from nearby unlnndscaped
or oil.is t ruet ion areas). It is not known if tlie wind conditions during these
^wo uty periods in Hellevue were significantly diffetent.
Table 7-1 summarizes the estimated accumulation and deposition rates
along with the street surface loading values associated with different times
ol accumulation. Al so shown on this fiblc are the calculated standard
deviations associated witli the observed loadings during each time period. The
standard deviations range from about 50 to 2GJ 1bs/curb-mile (14 to 57
g/curb-meter) per day, while the loading values range from about 200 to 1,000
Ibs/curb-mile (.57 to ''80 g/curb-me ter) per day. In many cases (especially for
very clean street surfjce conditions) the observed loading variptions can be
quite large when compared with the loading values. The expected variations in
loadings decrease for the larger loading values associated with the longer
accumulation periods. The standard deviation values can be used to construct
the approximate confidence intervals. The band that is one standard deviation
wide on both sides of the mean value would contain about two-thirds of the
data points. A band three standard deviations wide would contain about 95
percent of the data points. When all of these calculated curves with their
confidence intervals are plotted together, most of the bands ./verlap, but
three separate categories are evident. The lowest loadings were found on
148th Avenue S.E. throughout a long accumulation period, even though the
initial loading values were not the lowest. Lake Hills and 108th Street
(during the dry 198U season and during periods without street cleaning) had
higher accumulation rates than most of the other areas and always had higher
loadings than the other areas. The rest of the categories all seem to fall
together, with initial loading values ranging from about 150 to 350
Ibs/curb-mile (42 to 100 g/curb-meter) per day and loadings of about 350 to
550 Ibs/curb-mile (10000 to 160 g/curb-meter) per day after about a maximum
of 40 days accumulation. The 148th Avenue site had observed loadings between
about 200 to 250 Ibs/curb-mile (57 to 70 g/curb-met^r) per day throughout a
long accumulation period. The 108th Street and Lake Hills dry 1980 period?
had much higher loading values, ranging from initial values of 450 to 500
Ibs/curb-mile (130 to 140 g/curb-meter) increasing to high values of between
800 to 1,000 Ibs/curb-mile (230 to 280 g/curb-meter). The Lake Hills periods
with street cleaning also had very low accumulation rates, comparable to the
low rates observed in 148th Avenue. The Surrey Downs (with street cleaning)
accumulation rates, however, were quite large and were comparable to the dry
1980, Lake Hills and 108th Street rates.
These Bellevue loading values and accumulation rates are compared with
values obtained in other locations on Table 7-2. The initial loading rates
for Bellevue, which range from 200 to 500 Ibs/curb-mile (57 to 140
g/curb-meter), are within the low range of values reported elsewhere, and
generally correspond to other locations having smooth streets in good to fair
condition. Rough streets in other locations had loadings more than five times
the Bellevue loadings. Similarly, the observed Bellevue deposition rates alu-o
appear to be on the low end of the rates observed elsfcwhere, and also
generally correspond to smooth streets in good to fair condition or in
residential areas.
98
-------
Table 7-1. Approx. Total Solids Street Dirt Loadings
and Acrimulation Rates
Surrey Downs
Days of Accumulation
2 " 5 10 15 25
.1) average loading value (lb; urb-mile)
,2) approx. standard deviation of the loading value
(3) approx. accumulation rate (Ib/curb-mile/day)
40
- without
cleaning
with
cleaning
Westwood
Homes Road
- without
cleaning
108th Street
- without
cleaning
wet
stason
dry
(1980)
dry
(1981)
wet
season
dry
season
wet
season
dry
(198U)
dry
(1981)
wet
season
dry
(1980)
.(1)
-'(2)
rate(3)
a
rate
X
a
rate
X
o
rate
X
a
rate
X
0
rate
X
0
rate
X
a
rate
X
0
rate
X
o
rate
340
90
-
285
60
-
360
80
-
130
30
-
315
70
-
270
140
-
350
110
-
160
60
-
245
130
-
460
200
-
345
170
4
300
70
8
375
90
8
170
80
20
350
80
18
290
150
10
370
60
13
180
70
10
260
140
10
490
220
17
360
190
4
320
80
7
400
100
8
200
110
10
365
90
5
310
220
8
410
270
10
210
90
10
290
140
8
540
240
16
380
140
4
340
90
4
430
110
6
_
-
-
_
-
-
350
90
7
460
170
10
250
120
8
320
100
6
620
320
15
390
50
2
350
70
2
450
90
4
_
-
-
_
-
-
380
230
6
500
130
8
290
40
8
330
40
3
680
480
14
410
50
2
370
160
2
490
210
4
_
-
-
_
-
-
420
260
4
550
80
5
350
90
6
360
130
2
82 u
390
12
~
390
50
1
525
80
2
_
-
-
_
-
-
_
_
-
570
80
1
390
130
3
.
_
-
920
430
7
99
-------
Table 7-1. Loadings and Accu"i. Rates (Con't)
nf Accumulation
virr^v P^wns
I'^th Street
(Con'M
wi M~iout
cleani nq
Lake Hi 11s
- without
cleani nq
Lake Hills
- wi th
cleani nq
143th Ave. SE
- without
cleani nq
dry
(1931)
wet
dry
(1930)
dry
(1931)
wet
dry
dry
rate
0
rate
X
T
rate
o
rate
).
a
rate
X
c
rate
\
a
rate
0
300
120
-
170
60
-
500
160
-
170
50
-
170
60
-
170
50
-
200
60
-
2
320
110
10
200
60
15
540
190
20
200
70
20
185
60
3
185
65
8
205
60
3
5
340
100
7
270
230
20
600
350
20
270
160
15
195
170
3
195
120
3
210
80
2
10
360
100
4
290
80
4
660
310
12
290
140
4
_
-
-
-
-
215
100
1
15
3RO
100
4
30^
130
3
710
330
10
305
140
3
_
-
-
_
-
-
220
70
1
25
4'0
150
4
-
-
750
270
4
310
no
1
_
-
-
_
-
-
225
30
1
40
440
,?10
1
-
770
420
1
320
170
1
_
-
-
_
-
-
230
10
1
100
-------
C-LLFVJE ST^ET DIRT DEPOSITION RATES COMPARED
WITH' DATA FROM OTHFR AREAS
Locit ion
Rellevue, Vashinqton
Lake Hills and 103th St., Dry period 1980
143th Ave., S.E. (heavy traffic)
All other studv sites and periods
Reno/Sparks, Nevada(l)
Smooth streets and gutters in oood
condition
Other smooth streets and intermediate
streets
Rough streets
New residential areas
Smooth and intermediate streets with
smooth Tatters (windy)
Smooth and intermediate streets with
lipped qutters (windy)
Rough streets (windy)
San Jose, Calif(2)
Smooth asphalt, good condition
Smooth asphalt, fair to poor condition
Rough asphalt, poor condition
Oil and screens
Castro Valley, Calif(3)
Smooth asphalt
Ottawa, Ontario(4)
Smooth and moderate textured streets
Rough streets
Very rough streets
Nationwide(5)
Residential (smooth asphalt/good to fair)
Industrial (rough asphalt/poor)
Commercial (smooth asphalt/good)
Initial
Loadinq
Value
Ib/curb-mi)
500
200
250
710
2,200
2,500
880
1,300
1,900
130
290
780
1,800
300
140
700
1,100
400
670
300
Deposition
(Initial
Acc'jnrilation)
Rate
;ib/curb-mi/dav)
20
3
12
2.6
6.1
36
61
24
53
120
15
15
20
20
40
70
70
70
20
40
15
Sources:
2)
(3)
(4)
(5)
Pitt and Sutherland, 1982
Pitt, 1979
Pitt and Shawley, 1981
Pitt, 1982
Sartor and Boyd, 1972; and Pitt and Amy, 1973
101
-------
iiit. ;Uhrt\l MTluN OK Si'KKKT DIRT IN DRIVING AND PAKKINC LANKS
The amount of uwti'rijl present in the parking lanes is av;':'lable for
n'T.ov.i I by Street cle, 1:1 ing equipirent operating next to the curb. The street
s-u r I ii L o pa r t i cvi l,i tes in the driving lanes, however, cannot bt removed by
normal street cleaning operations. Tables 7-3 and 7-4 show the results of a
serie-; ot tests conducted in the Lake Hills and Surrey Downs areas to measure
the distribution of street dirt across the street. The test procedures are
described in Appendix E and involve taking a second set of subsamples in a
test area irunediately alter a normal full street width sample is obtained.
The second set of samples couJd either be taken from the center of the street
to th-e edge of the parking lane (for driving lane loadings) or from the edge
of the parking lane to the curb (for parking lane loadings). These samples
were divided into eight different particle sizes for analyses. The full
street width loadings for each particle size were compared with the
corresponding particle size loadings in the driving lane and parking lane.
The values shown in Table 7-3 for Lake Hills were all obtained during a
period of intensive street cleaning, while the values shown in Table 7-4 for
Surrey Downs were obtained during a period of no street cleaning. In both
cases, about 55 to 65 percent of the total street surface loadings were found
in the parking lanes. The actual loading values varied substantially,
depending upon the street cleaning operations. For the Lake Hills studies,
about 50 to 100 Ibe/carb-mile (14 to 28 g/curb-meter) of total solids were
found in the parking lane, while 200 to 300 Ibs/curb-mile (57 to 85
g/curb-meter) were found in the parking lane in Surrey Downs with no street
cleaning. The observed differences in loadings in the driving lanes were much
less. The driving lane loadings in Lake Hills ranged from about 50 to 75
Ibs/curb-mile (14 to 21 g/curb-meter), while they ranged from about 125 to
150 Ibs/curb-mile (35 to 42 g/curb-meter) in Surrey Downs with no street
cJ earing. This indicates that driving lane loadings are probably increased
when the parking lane loadings are also high, due to winds transporting
particulates out into the street. High parking lane loadings have been found
to be associated with high winds or traffic-induced turbulence blowing the
particulates from the center of the street towards the curb (Pitt, j.979). It
appears that this process can work both ways and that the percentage
distribution of the loadings may remain constant over the relatively narrow
range of loadings observed in Bellevue.
The percentage of the larger particulates (between 500 and 6350 microns)
in the parking lanes in Lake Hills during street cleaning were quite low due
to the street cleaning equipment being much more effective in removing these
particulates. Only about 30 to 40 percent of the particles in these particle
sizes were found in the parking lanes, while about 60 to 70 percent of the
smaller particles were found in the parking lane. The percentage of the
largest particle sizes (greater than 6350 microns) in the parking lane in
Lake Hills with street cleaning was surprisingly high (about 90 percent) but
the actual loadings were very low. The distribution of particulate sizes near
the curb was much more even in Surrey Downs durirg the period of no street
cleaning. Generally there were smaller fractions of the finer particulates in
the parking lane than for the larger particulates. Again, almost all of the
largest sized particles (greater than 6350 microns) were found in the parking
102
-------
Table 7-1. LAKE HILLS: DISTRIBUTION OF STREET 51RT
IN PARKING AND DRIVING LANES
(During a period with street cleaning)
Fart.clc Size (Microns)
63- 125- 250- 500- 1000- 2000-
125 250 500 1000 2000 6350 >6350
Driving % in
lane: size
loading
(Ib/curb-mi)
% of whole
street load
Parking% in
lane: size
loading
(Ib/curb-nii)
% of whole
street load
Total
3/:7/Sl
Whole % in
street: size
loadi nq
( Ib/curb-mi )
Driving % i.i
lane: sice
loadi ng
(Ib/curb-mi)
% of whole
street load
Parking % in
lane: size
loading
(Ib/curb-mi)
% of whole
street load
16
27
10
5.
20
19
22
79
.7
.9
.3%
7
.4%
,9%
.2
.6%
13.6
22.7
0.4
3.5
15.4
17.2
19.2
84.6
18.8
31.3
11.1
6.1
19.5
22.7
25.2
80.5
21.9
36.8
20.6
11.4
31.0
22.9
25.4
69.0
15.2
25.4
25.5
14.2
55.9
10.0
11.2
44.1
6.8
11.3
14.0
7.8
71.7
2.9
3.2
28.3
5.5
9.2
12.1
6.8
73.9
2.2
2.4
26.1
1.5
2.4
0.0
0.0
o.o
2.2
2.4
1CO.O
100
in
100
56
33.
100
111
66.
.0%
,0%
2%
.0%
8%
4/17/81
Whole % in
street: size
InarH nn
(Ib/curb-mi)
15
28
.8%
.8
13.3
24.3
19.9
36.3
2h-6
39.3
15.1
27.6
6.7
12.3
5.4
9.9
2.2
4.1
100
183
.0%
11.0% 8.6 13.9 21.8 23.7 12.2 7.1 1.7 100.0%
7.9 6.2 10.0 15.7 17.1 8.7 5.1 1.2 72
27.4% 25.5 27.5 39.9 62.0 70.7 51.5 29.3 39.3%
18.9% 16.4 23.7 21.3 9.5 3.3 4.3 2.6 100.0%
20.9 18.1 25.3 23.6 10.5 3.5 4.8 2.9 111
72.6% 74.5 72.5 60.1 38.0 29.3 43.5 70.7 60.7%
103
-------
(Continued)
Table 7-3. LAKE HILLS: DISTRIBUTION OF STREET DIRT
IN PARKING AND DRIVING LANES
(During a period with street cleaning)
<63
Particle Size (Microns)
63- 125- 250- 500- 1000- 2000-
125 250 500 1000 2000 6350 >6350
Total
5/8/81
Whole % in
street: size
loadi ng
(Ib/curb-m-i)
Dri -/ing % in
lane: size
loading
(Ib/curb-mi)
% of whole
street load
Parking % in
lane: size
loading
(Ib/curb-mi)
% of whole
street load
10.6%
12.1
8.3%
4.8
39.7%
13.1%
7.3
60.3%
9.5
10.8
8.0
4.7
43.5
11.0
6.1
56.5
15.7
17.9
13.3
7.8
43.6
18.2
10.1
56.4
24.3
27.8
23.0
13.5
41.1
25.7
14.3
58.9
21.4
24.4
26.2
15.4
63.1
16.2
9.0
36.9
9.1
10.4
13.3
7.8
75.0
4.7
2.6
25.0
6.9
7.9
7.7
4.5
57.0
6.1
3.4
43.0
2.5
2.9
0.2
0.1
3.4
5.0
2.8
96.6
100.0%
114
100.0%
59
51.4%
100.0%
55
44.6%
Average: % of
Whole street
load in:
Driving Lane:
Parking Lane:
29.2%
70.8%
28.1
71.9
30.2
69.8
37.3
62.7
60.3
39.7
72.5
27.5
60.8
39.2
10.9
89.1
42.6%
57.4%
104
-------
Table 7-4. SURREY DOWNS: DISTRIBUTION OF STREET DIRT
IN PARKING AND DRIVING LANES
(Qurinq a pe-iod of no street cleaning)
Particle Size (Microns)
63- 125- 250- 500- 1000~ 2000-
-63 125 250 500 1000 2000 6350 >6350
% in
lane: size
loadinq
(Ib/curb-mi)
% of whole
street load
Total
3/5/81
Whole % in
street: size
loadi nq
( Ib/curb-mi)
Dr i v i n g % in
lane: size
loac'i nq
( Ib/curb-mi)
% of whole
street load
Parkinq % in
lane: size
loadinq
(Ib/curb-mi)
% of whole
street load
4.0%
14. J
4.0%
5.8
38.9%
4.0%
9.1
61 . 1%
5.2
19.5
4.5
6.5
33.3
5.7
13.0
66.7
li.3
4?.l
9.6
13.8
32.8
12.3
28.3
67.2
19
73
17
25
34
20
47
65
.6
.2
.6
.3
.6
.9
.9
.4
22.9
35.7
25.1
36.0
42.0
21.6
49.7
58.0
IS.
68.
21.
31.
45.
16.
37.
54.
4
9
9
4
6
3
5
4
15.1
56.3
15.9
22.9
40.7
14.5
33.4
59.3
3.5
12.9
1.4
2.1
16.3
4.7
10.8
83.7
100.0%
374
100.0%
144
38.5%
100.0%
230
61.5%
4/l~'81
Whoie % in
street: size
loadinq
( Ib/curb-mi)
Drivinq % in
lane: size
loadi ng
( Ib/curb-mi)
% of whole
street load
4.5%
14.2
8.1%
9.8
69.0%
5.0
15.9
5.7
6.9
43.4
9.6
30.3
8.8
10.7
35.3
16
51
16
19
38
.5
.9
.4
.8
.2
20.9
65. S
25.0
30.3
46.0
17.
53.
20.
24.
45.
1
6
0
2
1
17.4
54.5
15.6
18.9
34.7
9.0
28.1
0.4
0.5
1.8
100.0%
314
100.0%
121
38.5%
2.3% 4.7 10.1 16.6 18.4 15.2 18.4 14.3 100.0%
4.4 9.0 19.6 32.1 35.5 29.4 35.6 27.6 193
31.0% 56.6 54.7 61.8 54.0 54.9 65.3 98.2 61.5%
-------
Table 7-4. SURREY DOWNS: DISTRIBUTION OF STREET DIRT
IN PARKING AND DRIVING LANES fcont.)
(During a period of no street cleaning)
<63
Particle Size (Microns)
63- 125- 250- 500- 1000- 2000-
125 250 500 1000 2000 6350 >6350
Total
5/06/31
Whole * in
street: size
loadi nq
(Ib/curb-mi)
Driving * in
lane: size
loa'li nq
( Ib/ourb-mi)
% rf whole
street load
Parking % in
lane: size
loadi nq
( Ib/curb -mi)
* of whole
street load
8.
36
8.
10
29
8.
25
70
4*
.0
4*
.7
.7
X
• ^
.3
6.6
28.5
6.0
7.6
26.7
6.9
20.9
73.3
10.8
46.6
8.9
11.2
24.0
11-7
35.4
76.0
15.
65.
15.
19.
29.
15.
46.
70.
3
6
5
6
9
2
0
1
17.5
75.0
25.3
31.8
42.4
14.2
43.2
57.6
14.6
62.9
19.?.
24.3
38.6
12.7
38.6
61.4
15.6
66.9
15.1
19.1
28.5
15.8
47.8
71.5
11.2
48.3
1.6
2.1
4.3
15.2
46.2
95.7
100.0*
430
100.0*
126
29.4*
100.0*
303
70.5*
Average: * of
Whole street
load in:
Driving Lane:
Parking Lane:
45
54
.9*
.1*
34.5
55.5
30.7
69.3
34.
65.
2
8
43.5
56.5
43.1
56.9
34.6
65.4
7.5
92.5
35.5*
64.5*
106
-------
lane in both test areas.
CHEMICAL STRENGTHS OF STREET SURFACE PARTICULATES
All of the street particular samples collected during this study were
divided into eight separate particle sizes as described in Appendices E and
F. Composites of the different samples were made to represent each test area,
specific particle size rangas, and time periods. They were then sent to a
commercial laboratory (Am Test, Inc., in Seattle) for chemical analyses. The
chemical composition information was then used to calculate total sample
pollutant values for each sample collected. Tables B-14 through B-18 in
Appendix B present the chemical test results. These tables are separated for
each test area, and show the observed chemical concentrations of the street
dir'_ for eight particle sizes lor up to ten composite periods. Each composite
is associated with a specific time period of about two months. The means,
standard deviations, and relative standard deviations (standard deviation
divided by the mear) of the particle concentrations for each size range and
test area are also shown.
The Sur.ey Downs and Lake Hills street dirt chemical characteristics
were separated into wet and dry seasons and were compared using Student's "T"
analysis. In most cases, there were no significant differences observed
between the wet and dry seasons. However, many of the very largest particle
sizes did show significant differences between the wet and dry seasons. In
addition, about half of the particle, sizes for lead showed significant
differences between the wet and dry seasons.
Figures 7-5 through 7-7 show the particle size distributions for dry
season participates, COD, and lead for eight particle sizes and five test
areas. Figures B-6 through B-9 in Appendix B show the particle size
distributions for wet season particulates, total KJeldahl nitrogen, total
phosphorus and zinc. The solids particle size distributions show that the
smallest particle sizes account for a very small fraction of the total
material, especially during the wet season when rains are most effective in
removing the smallest particles (see Section 9 for a discussion of storm
washoff of particulates). During the dry season, the larger particle sizes
account for relatively small fractions of the total solids weight. In all
cases, i48th Avenue had most of its total solids weight in the particle size
range of 250 to 1,000 microns.
The chemical oxygen demand, KJeldahl nitrogen, and phosphorus
concentrations all show high concentrations associated with the smallest
particle sizes, small concentrations with the intermediate sizes, and then
large concentrations with the larger sizes. This is probably because of the
presence of leaves and other organic material associated with the largest
particle sizes. The lead and zinc distributions showed typical particle size
distributions for heavy metals with the highest concentrations associated
with the smallest particle sizes. The lead particle size distributions are
also interesting whp.n comparing the different test arsas. Westwood Homes Road
in the Surrey Downs basin usually had the smallest lead concentrations for
all particle sizes, probably because of the small amount of traffic on that
107
-------
FIGURE 7-5
o
oo
DRY SEnSOK1 PRRTICLE SIZE DISTRIBUTION
63- 125- 250- 503- 1000- 2000- >£>3"»o
[Tj-108th ~SD ~LH T-148th
-------
FIGURE 7-6
COD CONCENTRRTION5 BY PRRTICLE SIZE
450
(g/kg
9> 25CLZ.
o
LJ
63- 125-
J7J- 108th
1
250-
500- 1000- 200C- >6370
m-LH - 148th
-------
3000
FIGURE 7-7
LERD CONC. BY PRRTICLE SIZE (mg/kg
25flfl_
2QOn_
o>
o> , c
£ -iS
Q
d
UJ
10flfl_
SQL
on_
<63
hWHR
234 I| i -j j i
n
I i 3 4 H ' 2. J
63- 125- 250-
JTJ-108-th Q]~5D
500- 1000- 2000- >6350
[Tj-LH Q]-148-th
-------
road, however, 148th Avenue is a well travcJled street and showed very high
lead concentrations, especially in the smallest particle sizes.
Table 7-5 summarizes the size-weighted total particle chemical
strengths, along with the median particle sizes The largest dir fc.rence in
chemical characteristics is shown for lead, especially when comparing
Westwood Homes Road with 148th Avenue. The Lake Hills lead concentrations are
also greater than the Surrey Downs basin lead concentrations. This may be
because of the smaller median particle sizes associated with the Lake Hills
samples. Because of the much greater concentrations of lead with the smaller
particle sizes, a smaller median particle size would result in a much greater
total solid lead concentration. The total solids median particle size for
lUBth Street street dirt is much greater than the total solids particle sizes
for the other test areas, and indicate the presence of many more larger
particles on that road than in the other test basin.s.
Table 7-6 compares these street dirt constituent concentrations with
data from other locations. In all cases, the observed 3ellevue chemical
concentrations are well within the range of values found in the other
locations. There is a much smaller difference for these Bellevue street dirt
chemical concentrations when compared to other areas than there is for the
observed urban runoff concentrations or for the street dirt loadings.
Therefore, the street dirt in Bellevue is very similar to the street dirt in
other locations studied, but the frequent rains prevent the street dirt from
accumulating to large loading .alues. The total annual rainfall in Bellevue,
however; is also similar to many other locations studied. Because of the
smaller but more frequent rains in Bellevue, each rain can remove fewer
street surface particulates, and the additional runoff volume per rainfall
(because of the moist soils) dilutes the pollutants more than for other
areas.
Ill
-------
Table 7-5. TOTAL STUDY PERIOD STREET DIRT CHARACTERISES (no/ka)
Test Area
Surrey Downs
Main Bas in
Surrey Downs
108th St.
Surrey Downs
Westwood Homes Road
Lake Hills
148th Avenue S.E.
Const i tuent
Total Solids
COD
TKN
Total Phosphorus
Lead
Zinc
Total Solids
COD
TKN
Tota Phosphorus
Lead
Zinc
Total Solids
COD
TKN
Total Phosohorus
Lead
Zinc
Total Solids
COD
TKN
Total Phosphorus
Lead
Zinc
Total Solids
COD
TKN
Total Phosohorus
Lead
Zinc
Si ze-Weiqht^c1
Strength
—
145,000
1600
575
745
170
—
51,300
455
510
460
130
239,000
2195
590
190
90
—
192,000
2310
640
1170
230
—
104,000
850
460
1540
190
Median Particle
Size (microns)
520
810
420
670
290
350
1370
1680
780
1860
440
1180
840
1960
780
890
420
640
420
730
400
430
225
260
610
1080
765
260
320
360
112
-------
Table 7-6. BELLEVUE STREET DIRT CONSTITUENT CONCENTRATIONS
COMPARED WITH DATA FROM OTHER LOCATIONS (mg/kg)
Constituent
Cadmium
Chromium
Lead
Zinc
COD
Phosphorus
Nitrate-N
Nitrite-N
Kjeldahl-N
Bellevue
Surrey
Downs
___
---
745
170
145,000
575
—
—
1600
108th St.
--.
—
460
130
51,000
510
.--
~—
460
Westwood
Homes Rd
-_.
.._
190
90
240,000
590
_„
—
2200
Lake
Hills
--.
—
1200
230
190,000
640
...
—
2300
148th
Ave S.E.
_--
_._
1500
190
100,000
460
—
_—
850
Reno/Sparks 1 San
<3
30
100 to 2 ,500
200
100,000
800
25
5
150
Smooth
Asphalt
2
450
5,500
750
120,000
—
—
—
2,000
Jose'2'
Poor
Asphalt
3
450
2,000
500
110,000
—
---
- —
2,300
Oil and
Screens
1
350
1,000
250
80,000
—
---
—
1,000
Castro
VaTiev
Smooth
fsoh^lt
_.-
200
1,600
200
90,000
500
---
---
1,600
1 Pitt and Sutherland, 1982
2 Pitt, 1979
(3> Pitt and Shawley, 1982
-------
Table 7-6. BELLEVUE STREET D[t
-------
SKCTION 8
SKWKK SYSTLM FAKTICULATK ACCUMULATION STULHLS
An important element of the Bellevue urban runoff project was the study
of storm drainage participates. The objective of this portion of the program
was to describe the quantities and characteristics of storm drainage
particulates in the study areas. The storm drainage particulate studies
involved both observation and sampling of catchbasin particulates and
particulars accumulated in the pipes throughout the Lake Hills and Surrey
Downs study areas. Data obtained from these studies were compared to
monitored street surface loadings and total runoff yields measured at the
outfalls of the two study areas. These mass relationships help define the
importance of storm drainage to the total runoff yield. This section of the
report provides a summary of the storm drainage particulate data collected
during the study.
CATCHBASIN OBSERVATIONS
As part of the experimental design task, random sampling and chemical
analyses ot about ten catchbasin sediments and water supernatants were
collected in both Lake Hills and Surrey Downs. This initial sampling was
conducted on December 27 and 28, 1979. The chemical analysis results for the
catchbasin samples taker from the Lake Hills study area are presented in
Tables 8-1 and 8-2.
Catchbasin sampling and analyses were conducted two times during the
first year. The sediment portion of the samples were dried and sieved after
their specific gravities were measured, and then composited for chemical
analyses. The supernatant portion of the samples were then chemically
analyzed. The 'chemical analysis results for the sediment portion of
catchbasin samples collected March 19 and 20, 1980, are presented in Table
8-3. The average wet specific gravity was approximately 1.3 grams per cubic
centimeter, or 80 Ibs/cubic foot. This average value MS lower than expected.
The procedures used to obtain these initial catchbasin sediment samples may
not have provided representative undisturbed cores. Since the freezing core
sampler did not work adequately for the shallow sediment depths encountered,
the sediment samples were obtained by hand scooping. The specific gravities
and total solids percentages may be low because of the extra water obtained
in the scooping procedure. This problem was corrected for the future samples.
Additional samples were collected from January through June of 1981 in
selected catchbasins throughout Lake Hills and Surrey Downs. About ten
catchbasins were sampled during each of these three sampling efforts. Each
115
-------
Table 0-1. CATCHBASIN SUPRNATAN1
(Lak5 Hills, 12/27-28/1979
catch-
bas in
number
592
616
626
524
523
535
549
554
578
582
total
sol ids
(mq/1)
r9l.(D
L91.
88.
124.
85.
111.
272.
34.
49.
158.
rl50.
U50.
chemical
oxygen
demand
(mn/1)
24.
27.
24.
24.
81.
244.
22.
r29.
L 36.
90.
20.
toUl
Kjelnahl
ni troqen
(nq/1 as N;
<.50
.90
1 . 20
4.73
2.20
3.04
r.98
L 1.40
.50
r5.60
1 5.50
.70
total
Phosohoruc
(mq/1 as P)
.325
.132
.218
.638
.322
r 6.90
1 6.75
.082
.078
.690
.135
Lead
(mq/1)
.08
.07
.07
r.22
L.05
.14
.11
.09
.08
.45
.12
Zinc
(ma/1)
1.19
.045
.079
.018
.105
.218
.033
.088
.126
.037
data shown with brackets are reolicates
116
-------
Table 8-2. CATCHBASIN SEDIMENT QUALITY (LAKE HILLS, 12/27-28/1979)
catch-
basin
number
592
616
626
524
528
535
549
563
578
582
total
so 1 i ds
27.0
6.82
20.3
4.37
4
.887
26.4
2.49
64.8
6.22
52.9
total
K.ieldahl
nitrogen
(jja/q as N)
744.
342.
r747.
••1010.
1020.
778.
56.0
353.
1470.
2010.
560.
Learl
^0.
236.
278.
262.
149.
13.0
407.
507.
46">.
479.
Zinc
166.
15Q.
146
93.0
53.5
37.0
123.
211.
104.
120.
-------
Taole 8-3. CATCHBASIN SEDIMENT QUALITY (3/19-20/1980)1'!]
Test
Basin
Surrey Downs
Surrey Dowis
Surrey Downs
Surrey Downs
Surrey Downs
Lake Hills
Lake Hills
Lake Hills
Lake Hills
Lake Hills
catch-
basin
number
510
548
559
531
534
524
535
578
626
616
Spec if ic
Gravity
( gtn/cm')
1.108
1.048
1.660
1.041
1.055
1.738
1.932
1.026
1.088
1.014
Total
Solids
9.29
19.2
56.6
(-5.98
15.51
r5.83
'6.11
19.1
•-71.5
'69.5
5.31
13.8
26.2
Chemical
oxyaen
dem.md
26.9
12.1
r-9.95
1.6. 59
48.9
44.5
4.24
1.57
26.7
3.41
1.45
Total
Kjeldahl
n i trogen
.971
.396
.791
rl.41
Ll. 03
2.75
.144
55.6 (jg/g
1.12
.463
.213
Total
phosphorus
(jjg/g-P)
2020.
411.
168.
2124
3720
199.
28.4
2170.
(-978.
L 833.
282.
Lead
5070.
806.
1325.
(-5937.
'4370.
2890.
880.
[-16.8
L14.2
2930.
1880.
604.
7. i nc
540.
137.
245.
r 1010.
L1380.
1000.
318.
(-36.1
L39.8
595.
906.
226.
results on a dry weight basis, except for specific gravity and total solids.
118
-------
.-atcl.h.u in sample was drieJ, nocnanica 1 1 y sieved, and Ihen we^'hed. fc'qual
tractions ot each size cat^ory wpre combined for enoi sa.nplinfi period, and
ucre .-her-.U-cUlv analyzed, lables 8-4 and 8-5 show the chemical analysis
ret.ults tor these three sampling periods and eight particle sizes for both
UiKe Hills and Surrey Uowr.s . The catchbasin pedirent samples hi'd particle
si;e concentrations very similar to the concenttations found in the street
dirt in the respective areas. This indicates that the catchhasin sediment
-naterial was mostly made up of street dirt. Tab~tes 8-4 and 8-5 also show
calculated total sample chemical concentrations during the early experimental
design sar.plir.g. These total samples concentrations are reasonable when
compared with the particle size breakdowns, but do show very large variations
(.especially when compared to the small variations in the composited size
data). This implies that the particle size distributions changed radically
from catchbasin to catchbasin, even though the particles mak.Ing up the total
sediment are quite similar in properties.
Tables D-l through D-6 in Appendix D show the measured sediment volumes
for all structures examined. Most of the catchbpsins were about 28 fay 22
inches (700 by 5bU mm), but some catchments with manholes were as large as
four feet (1.2 meters) in diameter. During the first survey, the sediment
depths ranged frooi zero to about 15 inches (0 to 380 mm) in Lake Hills (0 to
b.3 cubic feet, or 0 to 0.2 cubic meter) and zero to 27 inches (0 to 690 mm)
in Surrey Downs (0 to 15 cubic feet, or 0 to 0.4 cubic meter). Tables D-7 and
D-8 show the relative sediment and supernatant quality observed in the
catchbas-'ns during the early sampling periods. The extreme ranges of
strengths (mg constituent/kg total solids, or pp-jO observed, implies that the
particle size varies substantially, by location in the test areas and by
time. These values also demonstrate the importance of chemical transfer
between the sediments and supernatant, especially since a much smaller storm
can flush out all of the supernatant whereas a larger storm would be needed
to remove a substantial quantity of sediment. This appears to be more
important for COD which is shown to be more soluble than the other
constituents observed.
Nine complete catchbasin sediment accumulation inventories were
conducted during the project. The first survey was conducted in December,
1979, and the last survey was conducted in January, 1982. The depth of
sediment was measured for each catchbasin in which access rould be obtained.
A summary of the results are presented in Table 8-6. Figures 8-1 through 8-4
are plots of the observed loading conditions for each sampling period.
The sewage systems in Lake Hills and Surrey Downs were cleaned before
the beginning of this sampling program. Private streets in Surrey Downs
(specifically Westwood Homes Road) did not have their associated drainage
systems cleaned. Figures 8-1 through 8-4 (corrected for missing data) show
that it required about one year for the sewerage system inlet structures
(catchbasins, inlets, and manholes) to reach a steady state loading
condition. During the second project year (1981). more frequent (about
monthly) observations were made and indicate very little net removal or
increase in loadings between the observations. Table 8-7 summarizes the
typical stable period loadings and the accumulation rates after cleaning
before these stable .loading values are obtained. The Lake Hills steady state
119
-------
Table 8-4. SLI39EY DOW'IS CATCHBASIN SEDIMENT CHEMICAL QUALITY (mgAg) BY PARTICLE SIZE
particle Size: microns
Chemical Mxvqen Demand:
1/13/81"
l/,?6 2/4/81
2/?6 6/17/81
average
standard deviation
Total Kjeldahl 'itrogen
1/13/81
1/26 2/4/81
2/26 6/17/81
average
standard deviation
Total Phosphorus
1/13/81
1/26 2/4/81
2/26 6/17/81
average
standard deviation
Lead
1/13/81
1/26 2/4/81
2/26 6/17/81
average
standard deviation
Zinc
1/13/81
1/26 2/4/81
2/26 6/17/81
average
standard deviation
'63
153,000
158,000
15fi,000
157,000
1,200
3190
2570
2980
2910
320
340
1130
1180
380
470
1100
1200
1200
1170
(50
332
456
397
395
6.?
Total sample analyses (3/19 2
COD
mean 2EO.OCO
standard deviation 1£0,000
number of catcnbasins 5
63-
125
145,000
127,000
113,000
130,000
11,000
2110
1930
2160
2070
120
450
793
840
690
210
910
840
870
870
35
3">0
303
300
320
40
/80) (mg/kg)
TKN
1225
820
5
12J-
250
90,400
89,200
95 , 200
91,fiOC
3,200
1640
1290
1560
1500
180
626
635
630
630
5
670
650
530
620
76
166
2??
196
195
28
TP
1690
1450
5
250-
500
116,000
73 , 800
103,000
100,000
19,000
1800
1430
1563
1600
190
694
578
D70
610
70
550
570
550
56C
12
185
217
196
200
16
Pb
3400
2080
5
500 -
1000
177,000
115,000
137,000
143,000
31,000
1900
1450
1290
1580
280
366
642
652
550
160
540
520
570
540
25
180
216
208
200
19
Zn
720
490
5
1000-
2000
210,000
205,000
320,000
245,000
65,000
2760
2000
3050
2600
540
970
1030
791
930
i?0
550
500
570
540
36
214
246
223
230
17
2000-
6350
242,000
213,000
327,000
272,000
^7,000
2740
1900
27PT
2450
470
1C90
1050
1030
1060
30
530
370
540
480
95
171
198
207
190
19
'6350
176,000
237,000
320,000
244, (CO
72,000
1660
2100
2390
2050
370
830
844
620
760
120
250
360
250
290
64
107
173
170
ISO
37
120
-------
Table 8-5. LAKE HILLS CATCHBASIN SEDIMENT CHEMICAL DUALITY (mg/kg) CY PARTICLE SIZE
ChPmical Oxygen Demand:
1/13/31
1/26 2/5/81
3/17 6/17/81
average
standard deviation
Total Kjeldahl Nitrogen
1/13/81
1/26 - 2/5/81
3/17 6/17/81
average
standard deviation
Total Phosphorus
1/13/81
1/26 2/5/81
3/17 6/17/81
average
standard deviation
Lead
1/13/81
1/26 2/5/81
3/17 6/17/81
average
standard deviation
Zinc
I/. '3/81
1/26 2/5/81
3/17 6/17/81
average
standard deviation
'63
218,000
225,000
243,000
229,000
12,900
3360
3820
3610
3600
230
231
1030
1440
900
610
2800
1300
1800
1970
760
621
413
532
520
100
f - —
63-
125
159,000
162,000
197,000
173,000
21,100
2330
2540
3160
2680
432
398
744
1050
730
330
2400
HOC
1400
1630
680
453
321
404
190
67
Total sample analyses (early samples only):
COO TKN
mean (mg/Kg) 74,700 700
standard deviation 108,000 540
number of :atchbasins 5 15
125-
250
157,000
101,000
165,000
141,000
34,900
1870
1950
2170
2000
155
574
589
941
700
210
2000
830
1200
1340
600
278
232
359
290
64
TP
750
790
5
250-
500
173,000
114.0CC
143,000
143,000
29,500
2100
1930
2170
2070
120
574
567
693
610
71
1200
650
920
920
?80
210
223
332
260
67
Pb
610
770
15
500-
1000
278,000
191,000
251,000
240,000
44,500
3090
2620
3360
3020
370
742
645
1095
830
240
950
670
1100
910
220
235
236
437
300
120
Zn
210
230
15
1000-
2000
300,000
240,000
295,000
270,000
33,300
3780
3260
3220
3420
310
2160
957
15£0
1570
600
1000
430
970
820
290
282
203
372
286
85
2000-
6350
231,000
1^3,000
333,000
752,000
72,400
2100
1900
3020
2340
600
1550
1280
1750
1.530
240
500
410
940
620
280
171
284
440
300
135
'6350
71,500
205,000
? 01, 000
193, OX
115,000
379
1200
4840
2140
2370
865
894
3652
1800
1600
160
260
890
440
400
92
599
367
350
250
121
-------
Table 8-6. SUWARY OF OBSERVED CATCHBASIN, INLET AND
MAN-HOLE SEDIMENT VOLUMES, DFC. 1979 THROUGH JAN, 1982 (ft3)
Catchbaslns
Inlets
Man-holes
Total
Surrey
max avg total
11.2 1.9 80
19.2 1.7 45
25.9 3.1 19
25.9 1.9 144
Downs
fraction
of total
loading
56%
31
13
100%
number of
structures
43
27
6
76
Lake H
max avg total
8.3 0.8 55
5.5 0.6 28
15.8 3.0 45
15.8 1.0 128
ills
fraction
of total
loading
43%
22
35
100%
numoer of
structures
71
45
15
131
-------
FIGURE 8-1
01
01
JD
U
0
U
•f
in
-6
c
LU
(V
tl
(U
in
o
(V
o>
a
01
a:
Surrey DoNns-flve. Sediment in Structure
3.5
M
Dec 79 I Rug 80 I Jon 81 I Feb 31 I flpr 81 I Jun 81 I Jul
•Inle-ts FT^l-Man-Holes fii-Totol
81
flug 81
V
Jon 82
-------
01
01
61
I
t/1
FIGURE 8-2
Lake Hills-five. Sediment in Structures
f
c
UJ
c 2
i
01
in
6
& 0
o
01
(X
s_
Li_
5_
—
_
—
•^
— .
•""
\
—
-
_
—
-
~T\-
\
\
\
\
\
\
\
i
Dec 79
Q~CB
*
V\
Jul
\L
\i
80
C
T
/
/
_.
\
\
\
\
\
\
\
\
\
\
\
\
\
\
\
\
i
1
u
Jon 81
f
I
nl eis
T
/
/
/
pn
\
\
\
\
\
\
\
\
\
\
\
\
Mar 81
cr
/
/
/
Tl
_
>
\
\
\
\
\
\
1
T
1
1
flpr 81
/
/
/
•n
-
\
\
\
\
\
\
\
\
\
\
J
\
\
Jun 81
Mon-Hol es
' /
/
'
\1
-
\
\
\
\
svx
\
N
\
\
\
\
\
1
j
i
!
1
1
i
1 Jul 81
4
7
/
/
/
m
\
\
\
\
\
\
\
\
\
1
". \\
\|
\ !'!''j
\ li' ''
Rug 81
T
/
/
/
T
\
\
\
\
\
\
\
\
\
\
\
1
, ;,
1 v'i
X |i \\
V. !
\ i ' ':
'- ; ; ij
Jon 82
KT-To-tol
-------
FIGURE 8-3
r-o
en
01
«4-
u
u
c
w
CD
c
c
01
T)
01
in
at
E
3
"a
>
Surrey DoNns-Tota1 Sediment in btructures
200
17E
125
IOC
75.
50.
25.
0
\I
P
I/
171
Dec 79 flug 80 Jon 81 Feb 81 flpr 81 Jun 81 Jul 81 flug 81 Jon 82
J7"2J-G3 Pi-Inlets [VM-Mon-holes
-------
01
01
Cl
CTJ
c
01
FIGURE 8-4
Lake Hills-Total Sediment
ISO
in Structures
J^ 125
75.
71
171
Dec 79 Jul 80 Jon 81 Mar 81 Flpr 81 Jun 81 Jul 81 flug 81 Jon 82
^CB I hlnlets F^xj-Mon-Holes
-------
Table 8-7. TYPICAL SEWERAGE INLET STML'CTHRK
SEDIMENT VOLUMES AND ACCUMULATION RATES
stable volume accum. rate approx. months
(ft3) (ft3/month) to stable volume
Surrey Downs:
Catchbasins 2.2 0.17 13
Inlets 2.0 0.10 20
Man-holes 2.7 0.14 19
Average 2.2 0.15 15
Lake Hills:
Catchbasins 0.9 0.05 18
Inlets 0.7 0.05 14
Man-holes 3.2 0.14 23
Average 1.1 0.06 18
-------
\ > I u;--i •-. *iTi' about one-ha 1 1 of the Surrey Downs volumes (.except tor
r.<:',!: •.<•:,). The appr< >\ i r i: e lime period ot p.i r t i r u l.i Le ar cumu 1.11 ion bctore the
'•lab i i- ve!u;;:e is obtained is also shown on Table h-7. These periods are
bel-W- on one ,i;ul two years, with Ltie mure roirmon i. ,1t rhha s i ns 'equiiin,* about
I * i.e:iilis in Surrev Downs (where the iiilet dtnsity is about U.H inlets/ane,
or ,.'.n inlets/ha) and 18 months in Lake Hills (with a greater inlet density
ot about I.J inlets/acre , or 3.2 inlets/ha). A conservative estimate, based
on the available data, would be about on" year. (Observations weie not
started imr..od i at e ly after the initial cltaning.) Catchbasin, inlet, and
manhole cleaning should therefore be performed on about an annual basis to be
most cost-etfecLive . Slightly more frequent cleaning may be necessary for
smaller inlet st rnc i >.. res , less dense spacing of inlets, or during periods of
;',] eater than usual riin. Cleaning every six months can probably be considered
the maxinum effort warranted. A city-wide survey of inlet sizes, inlet
densities, and close-by sodiwent sources (as discussed in the following parts
ot this section) can be used to effectively determine the optimum cleaning
frequency. The additional inlet sediment surveys, carried out by the Bellevue
Stoi.Ti Drainage Utility, will be an effective tool in designing the most
appropriate inlet cleaning program.
The total amount of runoff particu1ales that may accumulate in the inlet
structures are sho*.n on Table 8-8. These quantities are about what would be
accumulated before the stable volumes" are obtained. These quantities coulri
be continuously removed, if the inlets are cleaned before the stable volumes
are obtained. After the stable volumes are obtained, urban runoff is little
affected by the structure. The constant stable volumes experience very little
washout and reaccumulations (as shown by the second year loading data).
During October, 1981, a very large storm occurred (about four inches).
However, no significant difference between the average or total August, 1981,
and January, 1982, observations was noted.
An analysis of inlet structure size (volume and depth below outlet) and
performance was conducted for the Surrey Downs data. Table 8-9 summarizes
these dimensions fov catchbasins, iniets, and manholes. The catchbasins and
inlets had about one foot (300 mm) available for storage below their outlets,
while most of the manhole outlets were on the bottom. Between three and four
cubic feet (O.U8 and 0.11 cubic meter) of storage wero available in the
catchbasins and inlets. Table 8-10 shows the observed average volumes and
depths of seiinenf in the inlet structures. Also shown are the portions of
the available storage containing the sediment. The stable sediment volumes
during the second year were about 60 percent of the available sump volumes
for the catchbasins and inlets. Only about one-half inch (13 mm) of sediment
was found in the manholes, with outlets on the structure bottoms, while about
six inches (150 mm) of sediment were in the inlet and catchbasin sumps. When
analyses were conducted for individual structures, wide variations were
observed. The depth below the outlet appeared to be the most important
factor, but the larger capacity sumps did not always contain the largest
amount of sediment. Larger sump volumes would allow less frequent cleaning,
while smaller outlet tc sump bottom distances were associated with more
scour. Manhole #577 (a grease trap with a storage volume of about 48 cubic
feet, or 1.4 cubic meters) had the largest sump volume of all inlet
structures observed, and usually contained the largest sediment volume. Its
128
-------
Table 8-8. ANNUAL ACCUMULATION OF SEDIMENTS IN STORM SEWER INLET STRUCTURES
Annual Total Detention(l)
number avg detention total total
of rate solids solids
structures (ft3/month) (ft3) (Ibs)
Surrey Downs:
Catchbasins
Inlets
Man-holes
Total /average
Annual
Lake Hills:
Catchbasins
Inlets
Man-holes
Total /aver age
Annual
43
27
6
76
detention
71
45
15
131
detention
0.17
0.10
0.14
0.15
(Ib/ac
0.05
0.05
0.14
0.06
88
32
10
130
re /year) :
43
27
25
95
(Ib/acre/year) :
8300
3000
940
12,200
130
4 mo
2500
2400
8900
88
COD
(Ibs)
2100
750
240
3100
33
300
190
180
670
6.6
TKN
(Ibs)
10
3.6
1.2
15
0.16
2.8
1.8
1.7
6.2
0.06
TP
ill
14
5
1.
21
0.
il
6
22
3.0
1.9
1.8
6.7
0.
.07
Pb
(Ibs) (
28
10
3
42
0.44
2.4
1.5
1.5
5.4
0.05
ZM percent
'. 1 b s ; of to t a 1
6
2
1
9
0.10
0.8
0.5
0.5
1.8
0.02
67%
25
8
100%
46%
28
26
100%
(l)Assuming l.Sg/cm^, or 94 Ib/ft^ and typical pollutant concentrations
-------
Table 8-9. SURREY DOWNS INLET STRUCTURE SIZES
Man-holes
Catchbaslns Inlets (excluding #577)
Diameter of outlet (inches):
Average
Minimum
Maximum
12
8
18
10
6
36
all 24
Depth below outlet to bottom (feet):
Average 1.1
Minimum 0
Maximum 2.8
0.9
0
3.4
0.02
0
0.1
OJ
o
Cross-sectional area (square feet):
Average 3.4
Minimum 2.5
Maximum 6.0
3.°
1.4
17.4
65.7 (partial'1
52.8
73.9
Volume below outlet to bottom (cubic feet):
Average 3.9
3.3
1.3
Man-hole #577 is an oil separator that is 4.1 feet in diameter, with a
depth below the 12 inch outlet of 3.7 feet. The total storage volume is
48.3 ft'. This "man-hole" contained almost all of the debris found in
all of the man-holes combined; the other man-holes were empty for most
observations.
-------
Table 8-10. SURREY DOWNS INLET STRUCTURE NORMALIZED VOLUMES COMPARED TO AVAILABLE
Stable
Dec
1979
Auq
1980
Jan
1981
Feb
1981
Acril
1981
June
1981
July
1981
Auo
1981
Jan Peri or
Catchbasins
Average volume (ft3) 0.37 0.67 2.86 2.77 1.81 2.12 '2.05 1.88 7,^7 2.?8
Average depth (ft) 0.11 0.20 0.84 0.81 0.53 0.62 0.60 0.55 0.72 0.67
Percent of available storage 9.7% 17.5% 73.7% 71.1% 46.5% 54.4% 52.6% ;8.2% 53.2% 58.^"
Inlets
Average volume (ft3) Q.33 0.67 1.89 2.04 2.07 2.07 2.11 1.82 2.11 ?.n"
Average depth (ft) 0.09 0.17 0.49 0.53 0.54 0.54 0.55 0.47 0.55 0.5'
Percent of available storage 10.0% 20.0% 57.6% 62.4% 63.5% 63.5% 64.7% 55.3% 64.7% 61.7*
Man-Holes
Average volume (ft3) 1.22 1.78 2.78 1.78 1.67 2.00 3.22 2.00 3.11 2.17
Average depth (ft) 0.02 0.03 0.05 0.03 0.03 0.04 0.06 0.04 0.06 0.04
Percent of available storage not applicable —
-------
.-;l.:hle sediro-.Mit volume uMy only about 3i> percent, of Itb lull capacity,
An an. i lysis ot the sediment data for the first: two sampling periods
_,iiliH'O sor-.e interesting observat Ions . Nine of the ten most heavily loaded
cat chbas ii-« in tiit> first summer inventory for Surrey Downs are located on, or
jii'-t upstream tn>m, the only two streets in the study area that do not have
curbs, both of the streets (lUbth Avenue and Westwood Homes Road) have
extensive ott-stieeu sedime.it sources located along then and were i:ot cleaned
during the study. These nine catchbasint. accounted for about 40 cubic feet
(l.l cubic meters) of sediment, or 58 percent cf the sediment observed in
Surrey Downs catchbasins during that summer inxentory. They alsc accounted
for 73 percent of the increase in sediment loadings observed between the
first winter and summer inventories.
Table 8-11 shows the heaviest sediment -loaded catchbasins in Surrey
Downs during the first two inventories. Eight out of the twelve heaviest
loaded catchbasins in the summer inventory were also part of the ten most
heavily loaded caf-ehbasins during the winter inventory. Many of these
catchbasins v:fcre located in the headwaters of the Surrey Downs study area and
they nay not receive the high runoff rates needed to flush them. However,
some flushing was observed farther down in the pipe system (i.e., #566 and
#572). A significant portion of the sediment observed in the Surrey Downs
catchbasins may not be easily available for runoff transport.
Table 8-12 presents data for the most heavily loaded catchbasins
observed in the L^ke Hills test area during the first two inventories. Six of
the eleven heaviest loaded catchbasins in the summer inventory were also part
of the most heavily loaded catchbasins observed in the winter inventory.
However, the sediment accumulations in Lake Hills were more evenly
distributed among the catchbasins than those in Surrey Downs. The top ten
catchbasins in Lake Hills accounted for only about 30 percent of the observed
sediment in the summer, whereas the top tun catchbasins in Surrey Downs
accounted for about 60 percent of the total summer loading.
PIPE SURVEY AND OBSERVATIONS
A survey of pipe lengths, diameters, slopes, and directions throughout
each of the study areas was made during the early months of the project.
Frequent observations of sediment accumulations in pipes throughout the two
study areas were also made. Very few pipes in either Surrey Downs or Lake
Hills had slopes less than 0.01 ft/ft (one percent slope), the slope assumed
to be critical for sediment accumulation. In Lake Hills, the average slope of
tne 118 pipes surveyed was 0.04 ft/ft (4 percent slope). Only nine pipes, or
7.6 percent of those surveyed, had slopes less than 0.01 ft/ft. In Surrey
Downs, the average slope of the 75 pipes surveyed was 0.05 ft/ft (five
percent). Nine pipes or 12 percent of those surveyed had slopes less than
".01 ft/ft.
The pipe system data indicates that the two study areas are drained by
steeply sloping pipe systems. The chances of finding significant
132
-------
Table 8-11. SURREY DOWNS CATCHBASIN INVENTORIES - HIGHEST SEDIMENT LOADINGS
CO
CO
Catchbasln Description
Type
Number CB (1)
MH (2)
577
569
562
583
579
580
573
575
534
578
548
552
566
572
559
CB - oil
Inlet
CB
Detention
pipe
Inlet
CB
CB
CB
CB
CB
Inlet
Inlet
CB
CB
CB
Location
Longest run of
upstream pipe
(ft)
Sep. 220
0
370
0
0
500
1000
340
335
160
0
0
2000
111-.0
340
SUMMER
Sediment loadinq
Rank
(out of all
catchbasins)
1
2
3
-1
5
6
7
8
9
10
11
12
Sediment
Volume
(ft3)
15.182
3.640
3.563
2.700
2.695
2.475
2.464
2.341
2.203
2.147
2.016
1.870
0.332
0.167
1.059
WINTER
Sediment loadinq
Rank
( ou t of all
c=>tchbasins)
1
6
13
2
4
Sed iment
Volume
(ft3)
10.034
1.040
0.712
2.70
1.617
0.165
0.493
0.195
10
3
8
7
5
9
11
0.801
2.362
1.008
1.020
1.102
0.836
0.792
Chame
Winter
Sediment
Volume
+5.148
in 1 na H i nq
to S'JTier
Percent ioe
chame
+ 51
+3.500 +336
+2.851
0
+1.078
+2.310
+1.971
+2.146
+1.402
-0.215
+1.008
+1.833
-0.770
+400
0
+67
+ 1400
'400
+1100
+175
-9
-100
+180
-70
-0.669 -90
+0.267
+34
(!) Catchbasln
(2) Manhole with catchment
-------
Table 8-12. LAKE HILLS CATCH8ASIN INVENTORIES - HIGHEST SEDIMENT LOADINGS
Catchbasin Description
Number
394
564
530
622
521
547
539
523
602
587
528
533
535
581
579
CB (1)
MH (2)
Inlet
CB
MH
Inlet
CB
CB
Inlet-MH
MH
Inlet
Inlet
C3
MH
MH
MH
MH
Location
Longest run of
upstream pipe
(ft)
0
30
3400
0
55
1730
0
3630
0
0
30
3350
195
2360
2450
SUMMER
Sediment loading
Rank
(out of all
catchbasins)
1
2
3
4
5
6
7
8
9
10
11
13
Sediment
Volume
(ft3)
1.766
1.584
1.418
1.392
1.350
1.282
1.255
1.256
1.191
1.157
1.140
1.005
0.706
0.707
0.353
WINTER
Sediment loading
Rank
(out of al 1
catchbasins)
Sediment
Volume
(ft3)
0.784
0.079
1
5.674
0.119
10
1.157
0
9
4
1.257
2.513
0.278
7
6
5
2
3
8
1.543
1.596
1.885
5.655
5.650
1.410
Change
Winter
Sediment
Volume
+0.932
+1.505
-4.256
+1.273
+0.193
in loading
to Summer
Percentage
change
+ 125
+1900
-75
+ 1000
+17
+1.282
-0.001
-1.257
+0.913
-0.386
-0.456
-0.880
0
-50
+328
-25
-29
-47
-4.949 -88
-4.943
-1.057
-88
-75
Catchbasin
Manhole with catchment
-------
.u-c'irau hi lions of sediment, in the pipe system are low since scour velocities
rar, le IB .r.tained in about 90 percent of the Lake Hills and Surrey Downs
storm drainage systems.
During the collection of catchbasin sediment data, routine observations
w.;re not made on the amount of sediment; in the pipes. However, a special
survey was conducted on October 30, 1980. The objective of that survey was to
observe the magnitude and characteristics of sediment in the pipes of the two
study areas. The following general observations were made:
1. The number of pipes throughout the sewerage systems
of both Lake Hills and Surrey Downs that had
sediment in their inverts appeared to be minimal.
2. As expected, the pipes that contained significant
amounts of sediment were either: mildly sloped
(1.5 percent or less); located close to an
off-street source of sediment such as steep,
sparsely vegetated, unprotected soil slopes; or
both mildly sloped and located near a sediment
source.
3. The physical characteristics of the sediment in the
pipes appeared to correlate well with those of the
sediments deposited in the nearest downstream
catchbasin or manhole.
Based on the observations made during the October, 1980, field survey,
the volume of sediment accumulated in the pipes throughout Lake Hills was
approximately 50 cubic feet (1.4 cubic meter). Assuming a specific gravity of
2.0 grams per cubic centimeter, sediment in Lake Hills totaled about 6200
pounds (2800 kg). In Surrey Downs, the pipe sediment volume was estimated at
over 700 cubic feet (20 cubic meters) or 87,000 pounds (39,000 kg). Most of
this sediment was observed in silted-up pipes along 108th Avenue and Westwood
Homes Road. (These streets are not being swept.) The pipe sediment volume
estimated to be available for runoff transport in Surrey Downs was about ten
cubic feet (0,3 cubic meter) or 1250 pounds (570 kg), and was observed in the
pipes connecting catchbasins 506, 507 and 509.
135
-------
SKCT10N 9
STKhET CLEANING EFFECTS ON OBSERVED RUNOFF QUALITY
The coordination of street surface sampling, street cleaning operations,
ard runoff monitoring allowed many different data analyses procedures to be
used to investigate possible effects of street cleaning on runoff water
quality. The use of two test basins and the rotation of the street cleaning
operations also allowed one basin to be compared against the other basin,
along with internal basin comparisons. This section is divided into two
subsections. The first discusses the washoff of street dirt while the second
discusses the observed water quality conditions at the different sites under
various street cleaning operations.
WASHOFF OF STREET DIRT
Student's "T" Tests to Compare Before and After Rain Loadings
The first method used to determine the amount of streec dirt that was
washed off by rain events used data given in Tables B-l through B-13. The
total solids street dirt loadings having less than two days of accumulation
were separated into two groups. One group contained loading values that had
been affecced by a significant rain within two days of sample collection
while the other group of data contained total solids loadings that were
affected by street cleaning within two days. In addition, these groups were
subdivided into dry and wet seasons for each of the five study areas. Paired
Student's "T" tests were then conducted to identify significant differences
between the loadings before and after street cleaning or rains. Student's "T"
tests were also used to compare before and after loadings during wet and dry
seasons in each of the five basins.
In about half of the cases, the loadings on the street after the rains
were significantly different for the dry versus the wet seasons. Much of this
difference may be due to the characteristics cf the rains during the two
seasons. During the dry season in Lake Hills, the before storm loadings were
about 320 to 400 Ibs/curb-mile (90 to 110 g/curb-meter) and there was a
significant difference between the residual loadings after street cleaning
versus after rains. The streets after street cleaning were about 50
Ibs/curb-mile (14 g/curb-meter) cleaner than after the rains. During the wet
season, th° difference was reduced to about 20 Ibs/curb-mile (6
g/curb—meter), but the difference was not significant. During the wet season
in Lake Hills, the s.reet loadings after street cleaning were about 15 to 20
Ibs/curb-mile (4 t? 6 g/carb-meter) less than after the rains, but these
136
-------
oiti.-n-nc-s were also not si-nifleant. The Lake Hills wet season after street
cie.,nin^ or rain loadings were all about. 175 and 225 Ibs/curb-miie (50 to 64
>: / curb-me tor) .
Fdirdd "T" test were used to examine the leadings on the streets before
the rains and the loadings on the streets after rains in the Surrey DC. , and
Lake Hills main basins. This data was also separated into three major
categories corresponding to runoff volumes of less than 0.1 inch (2.5 mm),
between 0.1 and 0.4 inch (2.5 and 10 mm), and greater than 0.4 inch (10 mm).
For both the Surrey Downs and Lake Hills data, the small runoff volumes
rtsuited in a street loading difference between 35 and 50 Ibs/c.urb-mile (10
and 14 g/curb-meter) at very significant levels. The removals during runoff
events of 0.) to 0.4 inch (2.5 to 10 mm) were much smaller (between 10 and 2.0
Ibs/curb-mile, or 3 and b g/curb-meter) and were not significant. For runoff
events greater than 0.<* inch (10 mm), however, the removals were between 75
and 125 Ibs/curb-mile (21 and 35 g/carb-meter). also at significant levels.
These results were quite surprising as it was thought that the very smallest
runoff events would not result in any removal of street surface particulates.
It was found in Castro Vallay, California (Pitt and Shawley, 1981), that
rains having more than 0.4 inch (10 mm) in runoff volume usually corresponded
to increases in street surface loadings due to erosion material being left on
the streets after these larger rain events. Most of the street dirt removal
in Castro Valley was found to occur during rains of between 0.1 and 0.4 inch
(2.5 and 10 mm) in runoff. When all of the Bellevue data were considered
together, between 35 and 45 Ibs/curb-mile (10 and 13 g/curb-meter) were
removed by the rains. The typical loadings on the streets before rains in
Lake Hills was about 210 Ibs/curb-mile (59 g/curb-meter), with about 36
Ibs/curb-mile (10 g/curb-meter) removed. In Surrey Downs, the loadings on the
streets before rains were larger (330 Ibs/curb-mile, or 93 g/curb-meter) and
the removals were about 46 Ibs/curb-mile (13 g/curb-meter).
The median particle sizes shown on Tables B-l through B-13 were also
compared using paired "T" tests. In all cases the median particle sizes were
found to increase by about 100 microns (at significant levels) in Surrey
Downs and (at marginr.lly significantly levels) in L,aLp Hills. When the Surrey
Downs data were separated into these three runoff size groupings, the.
particle size changes associated with the smallest and the largest rains were
significant, while the medium rains did not result in any significant changes
in median particle sizes. The intermediate runoff volume range had median
particle size values that decreased after the rains (but at insignificant
values). Large incr. dses in median particle sizes occurred for the largest
runoff events (an increase of about 500 microns in Surrey Downs, from initial
particle sizes of 570 microns to residual sizes of about 1,100 microns). This
very large change could be caused by large removals of small particle sizes
and/or increased loadings of the larger particle sizes. '.This would be
expected during the larger rain events which carry substantial erosion
material from surrounding areas, some of which may be deposited onto the
street's gutters. Table 9-1 summarizes these paired Student's "T" test
results for total solids and median particle sizes for both Surrey Downs and
Lake Hills.
137
-------
Table 9-1. STREET DIRT LOADING CHANGES DUE TO DIFFERENT STORM VOIUME5
CO
00
Surrey Downs
Total Solids - all
<0.1" runoff
0.1 - 0.4" runoff
>0.4" runoff
Median Size - all
<0.1" runoff
0.1 - 0.4" runoff
>0.4" runoff
Initial
330 Ib/curb mi
370
270
310
680 microns
650
780
570
Residual
280
320
250
190
770
730
740
1110
Change_
-46
-47
-20
-120
90
83
-37
540
% deduction
13.9
P.7
7.4
33.7
13.2% increase
12.8% increase
4.7% reduction
94.7% increase
Siqnif icanco
rjf r; h 1 1"1 0 e
>99.9%
99. 5%
30%
93%
96%
95%
65%
96%
Lake Hills
Total Solids - all
<0.1" runoff
0.1 - 0.4" runoff
>0.4" runoff
Median Size - all
210 Ib/curb mi 170
190 150
210 200
280 200
570 microns 680
-35 7.1% reduction 99.5%
-36 18.9% reduction 97.5%
-12 5.7% reduction 65%
-78 27.9% reduction 95%
110 19.3% increase 85%
-------
o
Because of these consistent, (but unexpected) results in loadings and
Particle size changes for different runoff volumes, street dirt washofi was
further analysed to determine effects associated with rair. volumes and peak
rain intensities. The street surface loadings for total solids and for each
or the chemical constituents were plotted on log-log paper. The initial
Loadings were plotted aga\nst the residual loadings and the associated runoff
volumes were narked at ef.ch point on the graph. The results showed that the
residual loadings were apparently unaffected by heavy runoff volumes, but
somewhat affected by th> initial loadings. About 65 percent of the cases
resulted in actual street dirt removals, while the other 35 percent had
increases in street loadings due to rain. The average, runoff volumes vert:
about 0.1 inch (2.5 r.m) .
Other plots were made on log-log paper comparing the initial street
surface loadings against the runoff volumes. The event mean concentration
(erne) values for che runoff events were plotted at each corresponding point.
Table 9-2 summarizes the minimum initial street surface loadings for each
coi.stituent that corresponded to a fairly small region of maximum runoff
concentrations. In almost all cases, the runoff volumes associated with this
region of maxixum concentrations ranged from about 0.04 to 0.08 inch (1.0 to
2.0 mm). The. vegion for COD was much greater and less defined. There were
several exceptions on each plot, but the street loading values shown may
indicate a reasonable street cleaning goal to minimize maximum runoff
concentrations. The cause and effect relationship on these diagrams, however,
was not clear and the presence of the few maximum observed runoff events in
this snull region may only be coincidental.
Regression Analysis of Street Dirt Washoff
The previous discussion showed that washoff was roost likely dependent
only on the street loadings before the rain for the rain conditions observed.
Figures 9-1 and 9-2 plot the observed initial and residual street surface
loadings for each of the three Surrey Downs areas and the Lake Hills and
148uh Avenue areas. These plots were In-transformed in order to obtain a more
evren spread of the data, so regression analysis could be performed. Again, it
is seen that some data points occurred in the region of loading increases,
while some also occurred in the region of loading decreases. Table 9-3
summarizes the linear regression equations for each of the study sites and
some corresponding washoff values. The regression equations did not have very
good regression coefficients. The main Surrey Downs basin had the best
regression coefficient of about 0.8, Ths other regression coefficients were
about 0.5. Additional regression relationships were determined for residual
load as a function of the peak rain intensity, the residual load as a
function of runoff volume, and the initial median particle size versus the
residual particle size.
Figures 9-3 and 9-4 show the changes in median particle size for the
Surrey Downs, Lake Hills, and 148th Avenue test areas. Again, a large amount
of data scatter was observed. ]u the Surrey Downs basins, 108th Street had
the largest initial and residue 1 sazes for most of the data points observed.
Westwood Homes Road had some very rlgh median particle sizes restricted to
139
-------
Table 9-2. STREET SURFACE
LOADINGS CORRESPONDING TO A REGION OF
MAXIMUM RUNOFF CONCENTRATIONS (LAKE HILLS)
street runoff max.
Constituent load (Ib/curb-mi) depth (in) runoff cone, fmg/1)
Total Solids 150 0.045 - 0.075 >200
Lead 0.16 0.045 - 0.08 ^0.3
Zinc 0.035 O.C4 - 0.075 >0.15
Phosphorus 0.08 0.045 - 0.075 >0.5
TKN 0.25 0.045 - 0.07 >1
COD 15 0.02 - 0.3 >50
-------
FIGURE 8-1
SURREY DOWNS WflSHOFF OF STREET DIRT
7.2
7
6.8_
"3 6.6_
__
e 6.4_,
( «• =— I
-0
L 6.2_
u
j3 6
jc 5.8_
o S'6-
a:
OCX
i o . it —
ac 5.2_
~"^
2 c
in
U-l
« 4.8_
4.6_
4.4
s'
0
— INCREASED LOADINGS /' "
A
/ ' A
~~~~" / A
-
Q El /
0 =Q ,^x e
A A* o oe * A
_ A x/ A_j ^ °C CP
^^ 0
B ^x' *e
G^/X A B
O C^/^ A
0 / AQ 0 DECREASED LOADINGS
/*
/^ B Q
it * ^ j*%r- r-^sr— j ^- ^ r-^^*- ^•^*^j ^ ^ ^ *** — •
7.2
• SURREY DOWNS
A 108th St.
Q WESTWOOD HOMES RD.
LORD On Ib/curb-mlleJ
-------
p.
(NJ
LRKE HILL5
6.2
FIGURE 9-2
148th flVE
_J I I \
EET DIRT wnSHOFF
E
U
a
ct
o
cr
a
i—i
un
IU
a:
INCREASED LOADINGS
4 4.2 4.4
S LAKE HILLS
A 148th Ave. S.E.
4.6 4.8 E 5.2 5.4 5.6
INITIRL LOfl.T (In Ib/curb-ml le)
5.8
6.2
-------
-C.
CO
Table 9-3. MODELED WASHOFF OF STREET SURFACE PARTICULARS BY RAIT,
(1) (2) (3)
Surrey Downs Surrey Downs Lake Hills Combined"
initial
load*
100
200
400
600
800
1000
1200
main
resid
load
103
185
332
463
595
702
830
basin
wash-
** off***
-3
15
68
137
205
298
370
108th
re;id.
load
141
220
344
444
537
610
693
St.
wash-
off
-41
-20
56
156
263
390
507
res id.
load
95
162
278
377
475
554
646
wash-
off
5
38
122
223
325
446
554
res id.
load
108
136
322
440
557
651
761
wash-
off
-8
14
73
160
?43
349
439
(!) In (resid. load) = 0.83[in (initial loadQ + 0.80 r2 = 0.77 N = 38
(2) In (resid. load) = 0.64fln (initial load£| + 2.02 r2 = 0.50 N = 23
(3) In (resid. load) = 0.76C_n (initial loadQ + 1,02 r2 = 0.45 N = 27
(4) In (resid. load) = 0.78(in (initial load)] + 1.08 r2 = 0.55 N = 108
Includes all 3 Surrey Downs sites, Lake Hills and 148th Avenue combined.
* initial loads before rain
** residual loads after rain
*** washoff = initial load - residual load
-------
FIGURE 9-3
SURREY DOWNS INITIRL SIZE VS RESIDURL SIZE
2500
S3
o
b
a
>-H
in
0;
i— «
o
S
ex.
cr
a
>— *
in
300
300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500
• SURREY DOWNS
A- 108th St.
0 WESTWOOD HOMES RD.
INITIRL STREET DIRT SIZE (microns)
-------
FIGURE 8-4
LRKE HILLS & 148th RVE SIZE CHRNGi
C
2403
o
b
in
ft
-------
th'1 r.r.',:.- ot ;ilout inu to l,('i>U microns. The 14.-Uh Avenue test area and the
!,•.'» <• Kills an;; h;io nirdia,. particle sizes that vere qul'.e similar and ranged
1 rom about J';l! to t>OU microns in most cases.
I'lots of w^slujfl as a function of runoff volume are shown as Tables B-10
an
-------
ininfjll. TMs can be expressed in inches if the k value is multiplied by 60.
This equation then simplifies to the following form:
.. .,
N=N e
o
The k constant is equal to about 0.6 inch (15 mm) for the particle sizes of
concern, and R is the total rain expressed in inches.
This equation was determined from many controlled tests in Bakersfield ,
California. An artificial rainfall apparatus was used on typical street
surfaces. This portable rain simulator applied water uniformly over a section
of the street at various controlled "rainfall" rates. The water was supplied
from nearby fire hydrants and was sprayed vertically, about four to six feet
(1.2 to J .8 meters) high through hundreds of small jets. The water broke into
discrete droplets about the size of common raindrops before they fell to the
street surface. The device produced a water flow pattern on the street
surface which had the appearance of a moderate to heavy rainfall. Sartor and
Boyd found that the soluble street dirt contaminant fractions go into
solution with the impacting raindrops and the horizontal sheetflow provided
good mixing turbulence and a constant supply of clean water to remove the
materials to the gutters. The particulate matter was moved by the impact of
falling drops which were then bounced along the street surface by repeating
impacts of other drops and carried by sheetflow. They noted that a
substantial amount of the particulatej- were found in small pits, cracks, and
other irregularities in the street surface and were not easily removed.
These field tests were conducted on street surfaces having moderate to
heavy loadings of total solids in all particle sizes. One concrete and two
asphalt streets were flushed by the simulated rainfall for a period of 2.25
hours. Samples of the runoff and the particulates in the gutters were taken
every 15 minutes. At the end of the test, the streets were flushed thoroughly
with firehoses to wash off any remaining particulates and soluble material.
Only two rainfall rates, corresponding to 0.2 and 0.8 inch (5.1 and 20.3 mm)
per hour, ^ere used in these tests. Unfortunately, even the smallest rainfall
rate was many times greater than any sustained rainfall rate observed in
Bellevue. The maximum rainfall rate was much greater than what could ever be
expected in Bellevue under most conditions. These very high intensities may
only occur for very short periods of time.
Sartor and Boyd found that the initial flows from the streets were quite
dirty, but they then became cleaner and cleaner during the period of the
test. The pattern of contaminant concentrations in the runoff water followed
very similar patterns for each of the test areas and the two rain
intensities. The washoff patterns were also similar for all particle sizes.
Again, they found that the transport of the particles across the strest
surfaces fitted the exponential function given previously. The curve fits for
these tests were quite good, and total accumulative washoff s for most
particle sizes reaching constant values after about 30 minutes of rain. They
found that the proportionality constant (k) in the runoff equation was
dependent upon the street surface properties, but was not dependent upon the
147
-------
t1'1' TMi;it,,il itif ens i t it-s t'l-u were monitor:is-t II-IL •.<' -1 ni't vi r;- -:r''aLLy for different pa/tide sizes.
Tin-so votv i :i t o r o y L int; field tests contributed mic.h to the knowledge of
street surl.u-''1 p.trticul^te washoff, but thev were conducted in very
controlled situations using rainfall intensities that were not typical of at
least Bellevuo cord i. L ions , and pre prob.ib'y much greater than are likely
Uiund in most i-artt. of the country. These tests also did not consider the
effects of traffic G> the stieet surface? during rains. Traffic would have a
tendency to remove moie of the '"treet dirt part i cula tes during rainfall
events (Pitt, 1979). The tests were also conducted on very hot streets during
very hot summer days. This is far different than is lively to occur in
be_leVL.e during rain events where the street surfaces and air temperatures
are much cooler. The drier and hotter conditions are thought to help retain
the soluble materials on the street surfaces and could result in substantial
flash evaporation of the rain upon contact with the street surfaces.
Observed Washoff as a Function of Particle Size
Figures B-16 through B-23 are plots of the initial street surface
loadings versus the residual surface loadings for each of ths eight different
particle sizes. Also shown on these figures is the percent washoft, or
increase, for each of the rains studied. The smallest particle sizes have
most of the data points falling in the washoff category, but some rain events
did produce increases in loadings. For particle sizes greater than 2,000
microns, more storm events produced street surface loadings increases than
decreases. The befcre and after street surface loadings for the Lake Hills
site were compared using Student's "T" tests to identify significant
differences in loadings. There were no differences observed for wet versus
dry season washoff quantities, but the initial loadings were significantly
greater than the residual loadings for particle sizes smaller than about 500
microns. The snaxlest particle sizes have the greatest significant washoffs,
while particle sizes greater than about 500 microns had lower significant
washoff valuti, . When the washoff conditions are averaged, removals show a
distinct pattern. Figure 9-5 shows the average percent washoff for each of
these particle size ranges. In r.he smallest particle sizes, the washoff
varied from about 40 to 50 percent, while increases were found in the larger
particle sizes. The overall washoff averaged about 16 percent. Figure 9-6
shows the size distribution of the washoff material. This size di-.tributlon
is very similar to the pattern shown in Figure 9-5. Most of the material thac
washes off the street surfaces occurs in particle sizes less than about 125
microns. Only about ten percent of the washoff material is greater than about
500 mioroas in size. Again, the largest particle sizes are notably absent
from washoff material. Figure 9-7 shows the quantity of material that is
washed off of Lake Hills streets by particle sizes. A total of about 30 to 35
Ibs/curb-mile (8 to 10 g/curb-meter) is removed from the street surfaces,
with about 15 to 20 pounds (7 to 9 kg) of this material in particle sizes
smaller than 125 microns.
Table 9-4 shows the estimated washoff percentages for the street surface
pollutants. For all sites, about 14 percent of the total solids would be
140
-------
FIGURE 9-5
PERCENT NflSHOFF BY PflRTICLE SIZE
TOTRL
Q-WET
SEflSON
-------
en
O
FIGURE 8-6
HRSHOFF SIZE DISTRIBUTION
40
3 35
6350
-DRT
Q-WET SERSCN
-------
E
JD
h^
(J
u.
u_
o
FIGURE 9-7
LHKE HILLS STREET DIRT WflSHOFF
33-
125-
SERSON
250-
500-
1000-
2000-
>6350
-------
Table 9-4. ESTIMATED WASHOEF OF STREET SURFACE POLLUTANTS (PERCENT)
Surrey Downs
108th Street
Westwood Homes Rd.
Lake Hills
148th Avenue, S.E.
Median
Particle
Size of Washoff
(Microns)
190
380
190
160
220
Total
Solids
16%
9
13
18
15
cnn
15
10
10
16
12
TKN
19
15
15
20
15
TP
16
7
13
19
15
Pb
22
18
20
25
21
Zn
21
11
16
23
n
Average:
230
14
13
17
14
21
18
-------
rc-oved lor the rair.d that we: • observed during these tests. The percentage
it- about the same, or slif:hUy less, for COD and total phosphorus, while it
is slightly more for total Kjeldahl nitrogen and zinc. The washoff percentage
is substantially greater for lead because of the greater abundance of lead in
the snuller particle size ranges. The 108th Street area had much smaller
wasnoffs than any of the other sites, probably because of the greater
abundance of larger sized particles on that street. Westwood Homes Road also
had smaller washoffs, again because of the larger particle sizes found there.
RUNOFF WATER QUALITY CONCENTRATIONS AND YIELDS DURING PERIODS OF DIFFERENT
STREET CLEANING ACTIVITIES
Figures B-24 through B-31 are simple plots relating observed storm
runoff concentrations as a function of the total rain. These figures show
this information for the two different study sites and for the wet and dry
seasons separately. The two symbols on the plots represent periods of time
when streets were not cleaned and when the screets were intensively cleaned.
These are similar to the figures shown in Section 6, except that these plots
are separated by periods of different street cleanliness. Again, the highest
concentrations are generally associated with rhe small rain volumes. However,
many more data points are available for the smaller rain events and if
additional data were available for the larger events, then a greater spread
in data may have occurred.
Vv"1"'.- The lowest concentrations for any rain event are many times associated
with periods of time when the streets were not being cleaned. Increased
concentrations during periods of intensive street cleaning may be associated
with loss of armoring. Sutherland (1982) states that bed armoring occurs when
large stable particles rest upon and pin smaller unstable particles that
would otherwise have been lifted and transported. Since the street cleaner is
removing or disturbing a significant portion of these larger particles, the
runoff is more efficient in removing the smaller particles that remain. Other
activities such as wind, traffic, and local erosion may have the same effect
as street cleaning, since they disturb the particle size distribution and
magnitude of the accumulation. These other activities will also have the
tendency to increase cue effectiveness of runoff in removing the smaller
particles ,'hs.t remain on the street or were added to the accumulation.
Figures B-32 through B-35 show this same data, but transformed. The
total solids and lead loads for each storm are plotted against the observed
flows. These plots have their scale on a log basis to more evenly spread out
the data. Again, the data is separated by season, study area, and street
cleanliness. The even distribution of the data for these plots indicate that
regression analyses are possible. Figures 9-10 through 9-14 show the results
oi these regression analyses. A 95 percent confidence interval is shown
representing "concentrations" for periods of street cleaning and periods of
no street cleaning. These confidence bands contain 95 percent of the
observations for each of these cleaning situations. The total solids figures
for Lake Hills and Surrey Downs for the wet and dry seasons (the Surrey Downs
Hry season is missing due to very few data collected during that period of
time) show that the confidence intervals for the two street cleaning
153
-------
FIGURE 9-10
TOTflL SOLIDS - Net Season - Lake Hills
14
t 13-
O
-p
•
b 12-
o
1/1
_o
- 11-
U-
o
+ 10
c
in
a q
>— i j
_i
o
in
o
8
g ? a 11
FLOW (Ln of cubic feet)
12
13
-------
14
FIGURE 9-1 1
TOTflL SOLIDS - Dry Season -Lake Hills
o
w
X.
01
u
o
w
-O
12.
- 11.
14-
O
O
in
a
K-4
o
in
a
8
X. '
9 10 11
FLOW (Ln of cubic feet)
12
13
-------
TOTRL SOLIDS
14
FIGURE 9-1 2A
Net Season
- Surrey Downs
E
L
O
01
L
U
O
x.
in
-O
13.
12.
" 11.
O
-------
Is
01
u
u
-5 4
w
_O
^ 3
Q
CC
0
FIGURE 9- 1 2B
LERD - Net Season - Lake Hills
8
<~t^?i'
, ^>-'
0v5J-v-'x<-.>'-7
*-V» ^^ * -^^ *- /
' /.'•'S'^
9 '10 ' 11
FLOW (Ln of cubic feet)
12
13
-------
u
VI
-Q
o 3
FIGURE 9- 1 3
LEflD - Dry Season - Lake Hills
cr
LU
r
i
-t-
i-
9 10 11
FLOW (Ln of cubic feet)
12
13
-------
E
01
U
-5 4
I/I
.0
o
«—I
C
d 2
a
cr
UJ
0
FIGURE 9-14
LEflD - Wet Season - Surrey Doun
8
9 10 11
FLOW (Ln of cubic feet)
12
13
-------
•.i tu.it ions are not di K t ir.ct :. overlap through mi ch of the aata ranges.
H.r.uros '-'-IJ .-i,-j 9-la ate 'or lend n.M also ^-'-ow substantial ovprlap of the
i-.'!'t iv-.i-ru o h,4i!ti~ t*->r clean a, i dirty street conditions. There is a somewhat
.;:i,itoi Migration in the confidence bands for lead than there is for total
solids. However, they are not completely separated and significant
dittereiues tat the 95 percent confidence level) cannot Vv - .isidered for the
two different street cleaning periods c/er the complete range of flov
conditions. Hie estimated confidence intervals that may correspond to
separ.'te confidence bands for th» lead analyses are at about the 60 percent
level, which is very low. During the Lake Hills wet season, the dirty street
surface conditions sometimes resulted in a lower runoff yi.^ld for constant
flows than during clean street surface conditions (possibly due to bed
armoring eftects discussed previously). During the Lake Hills dry season and
during the Surrey Downs wet season, however, the cleaned street surface
conditions resulted in typically lower concentrations. Again, the confidence
level of these conclusions is very poor.
RELATIONSHIPS BETWEEN STREET LOAD, RUNOFF YIE1D, AND RUNOFF VOLUMES
Preliminary analyses of the Bellevue runoff yield and street surface
loading data were performed in the first annual report (Pitt, et al, 1981).
This early data analysis effort included plotting the ratio of street surface
load to runoff yield as a function of runoff volume. These early efforts were
successful as the regression coefficients were quite high (approaching 0.95).
The ratios were high (several hundred) for low runoff volumes (less than 0.1
inch, or 2.5 mm of runoff) and then decreased rapidly wi;h increasing runoff
volumes. It was thought that these plots showed the sensitivity of runoff
yields to street surface loadings. During low runoff volumes, the amount of
material on the street before the rain was many times greater than the toe a1.
runoff yield observed. For large runoff, however, ihe initial street surface
loading values were fairly close to the total runoff yield for such
constituents as lead, zinc, and COD, but was much smaller than the runoff
yield for nutrients. This conclusion made sense when recognizing the washjff
processes in an urban area. The small rain volumes are only capable of
removing the material from the directly conn2cted impervious areas, as the
rain intensity is only large enough to dislodge the materials and flush them
along the street surface. As the rain and runoff volumes increase, all of the
street surface material may have been removed, but additional materials from
adjacent areas were washed onto the streets and drainage systems through
erosion processes. During very large rains, the erosion materials would be
much greater than the quantity of street surface loadings removed.
Similar observations relating the street load to runoff yield ratio
versus runoff volume were obtained previously in Castro Valley, California
(Pitt and Shawley, 1981). In Castro Valley, more constituents were analyzed,
but for fewer rains (a total of about 25 complete data sets wer» available).
In Castro Valley, the regression coefficients were mostly 0.95 or greater,
showing very good agreement of the data with this conceptual model. In
addition, the relative placement of the curves for the different constituents
also satisfied these washoff hypoLtieses. As expected, lead itaintained the
highest ratio of initial street surface loads to runoff yields over the
163
-------
complete ratine of runoff volumes when compared to the other constituents. In
other u.uds, the load street 'oads were quite important when compared to the
lead runoff yields for most rains. Following lead in order of decreasing
sensitivity were total solids, arseriic, COD, total phosphate, zinc, total
Ivjeldahl nitrogen, and orthophosphate. This order is probably a fairly
accurate order of the importance of street dirt constituents to runoff
yields .
upon reviewing this data analysis procedure, it was determined that
spur-'.ous self-correlations may be responsible for a large portion of these
high regression coeffirients. Spurious self-correlations may occur when the
dependent parameter contains the independent parameter as part of its
definition. An example of this would be relating a parameter having very
la-:ge values against these same values minus a relatively small, but random,
variable value. If the large values were in the range of 1,000 to 10,000, and
i. the other parameter values were these same large v.ilues minus a smaller
independent value (say in the range of about 100), then the linear regression
coefficient between these two values would be very high. Even if the large
and tne small parameters were completely independent and random, the
regression coefficient could be 0.9 or greater (a very good straight line
fit) for this example. The dependent j,=.rameter would vary between 90 and 100
percent of the independent parameter. This same problem may occur through
other normalization procedures, such as multiplicatioi or division of the
independent parameter.
The relationship between the street surface load and runoff yield ratio
versus runoff volume was thought to possibly be seli-cormlated . The runoff
yield is the concentration times the runoff volume. Therefore, these
relationships are really street surface load divided by concentration times
runoff volume, while the independent variable was runoff volume. In order to
determine the importance of self-correlation (because the runoff volumes were
included as both the independent and as part of the dependent variable)
various random number distributions were used as raw data testing these
different relationships. Random log-normal distributions representing the
typical range of street surface loading values for total solids, runoff
concentrations and runoff volumes were selected using a simple computer
program. These random distributions were completely independent and
uncorrelated. The runoff yield for these random values was calculated by
multiplying the concentration times the volume times the appropriate
conversion factor. The initial street surface load was multiplied by the
total number of curb-miles in the basin to obtain a dijiensionless ratio of
initial street surface load to runoff total solids yield. This ratio was
plotted against the runoff volume, expressed in inches. Figure 9-15 shows
this random log-normal distribution. The data scatter pattern is similar to
the forms obtained using the real data, but the random data has much more
scatter. The upper boundary at the data plots generally represents the shape
of the curve determined using real data. The regression coefficients using
these random values ranged from about 0.2 for a straight line to a high of
about 0.4 for a hyperbolic curve. Other curve forms attempted had regression
coefficient values intermediate to these two values.
161
-------
FIGURE 9-15
e
JD
o
o
Log-Normal Random Ratio of Loads
150
14
13
12!
Ill
101
90.
80.
7CJ.
60.
50
40
30
20
10
0
X
XX X
XX
X
v *x
x
X
x
.05 .1 .15 .2 .25
Runoff Volume/ Inches
.3
Id
s
,35
.4
-------
Figure 9-16 shows the ratio of the log-normal random initial street
surface leads to the random runoff concentrations plotted cgainst ranaom
runoft flows. These value are not self-correlated because the concentration
values were directly measured and are not highly correlated with the runoff
flows (as discussed'in Section 6). The largest regression coefficient using
this type of procedure was about 0.18 for a y-yperbolic curve. All of the
other curve forms had extremely low regression coefficients.
The regression coefficients for these types of data analyses can be
assumed to be the minimum values possible without getting into significant
spurious seJf-correlation problems. If the regression coefficients for the
real data were substantially greater than the regression coefficients for
these randotr number values, then the calculated values using the real data
can be important. As noted earlier, the regression coefficients for the
preliminary Bellevue data analyses were somewhat higher than these lo£ normal
random number values, while the values using the Castro Valley data were much
larger than these values. Therefore, this analysis procedure can be
important, but care must be taken in its use and interpretation.
Lake Hills dat? were used in these analyses because the whole basin was
cleaned by the street cleaning equipment. In Surrey Downs, only 3.5 miles
(5.6 km) of the 5.5 miles (8.8 km) of street were cleaned and, therefore,
street cleaning would have less potential beneficial effects on runoff water
quality. Figure 9-17 shows a plot relating the ratio of initial total solids
street surface loads to the runoff yield versus the runoff volume. The
pattern of the data scatter shown is very similar to the relationships found
in the preliminary analyses. The location of the knee of the curve indicates
the importance of street surface loadings to runoff yield and occurs at about
0.1 inch (2.5 mm) of runoff. If the knee of the curve is located at a high
runoff volume, the street loadings and street contaminant washoffs would be
more important over a wider range of rain and runoff conditions than for a
contaminant whose curve knee occurs s.t a lower runoff volume. There is quite
a bit of scatter beneath the upper boundary of the data points, but the
scatter is much less than was shown on the random data plot of Figure 9-15.
Figure 9-18 relates the ratio of the observed total solids street
wa&hoff to the runoff yield against the runoff volume. The pattern of the
data scatter is quite similar to Figure 9-17, with the knee of the turve
somewhat less than 0.1 inch (2.5 mm) of runoff. Figure 9-19 relates the ratio
of street surface washoff of lead to runoff yield against the runoff volumes.
Figure 9-20 relates the ratio of total solids street load to runoff
concentration against the runoff volume. In this case, the only relationship
observed is a constant value for the ratio of about one to twc Ibs/curb-mile
(0.3 to 0.6 g/curb-meter) per mg/1. This ratio is somewhat constant over the
complete range of runoff volumes, but some very high values intermittently
occurred. This constant relationship was further investigated in Figure 9-21
which relates the initial »-otal solids ."oad on the street to the observed
runoff concentrations. No apparent relaiionship was observed for this case.
Figures B-36 through B-39 relate the ratio of street surface washoff to
runoff yield values for total Kjeldahl nitrogen, COD, phosphorus, and zinc
against the runoff volumes. The patterns of all of these scatterplots are
163
-------
FIGURE 9-16
Log-Normal Random Ratio of Loads/Cone
o>
E
u
c
o
-o
o
o
7
6
5
4
3
2
1
XX
X
X
-x *
X *o<*
XX
XX
X X
X*'
X X
X X
X X* X
x x
X
.05 .1 .15 .2 .25
Runoff Volume, Inches
.3
.35
.4
-------
FIGURE 9- 1 7
TOTflL SOLIDS LORD/YIELD FOR LRK.E HILLS
100
o
£ 90_
cr
a;
UJ
U-
o
o;
g 50.
o
UJ HU-
UJ
Qi
tn 30_
in
a
80
70
60.
20.
o
1/1
o
°
© o
.05 ' .1 .15 .2 .25 .3
RUNOFF VOLUME (Inches)
.35
.4
.45
-------
25
22
20.
u_
u.
o
* 15.
o
in
-------
FIGURE 9-19
LEflD WflSHOFF/RUNOFF YIELD
40
2 35
i—
en
CK
R 30
— i •*»*
UJ
t—4
t 25~
o
xi 20
u.
o
§ 15
UJ
tn
§ 5
UJ
0
o
o
o
o
o
e 0
® 0 °
0 0 0
0 r> O O
0 e o
a
.M ««r* « d r~ 'N i^«— *-V *^r- a
.45
RUNOFF VOLUME (Inches)
-------
FIGURE 9-20
cr>
30
TQTflL SOLIDS STREET LORD/RUNOFF CONC RflTIO
13 .
E
I
-O
U
LJ
O
U
u.
o
z
a
cr
o
UJ
UJ
Qi
in
in
o
in
d
i—
o
7
6
5
4
3
2
1
0
.4
0
o
1.4 1.9 2.4 2.9
RUNOFF VOLUME (5+In Inches)
3.4
3.9
4.4
-------
FIGURE 9-i> 1
TOTflL SOi_ID5 STREET LORD VS RUNOFF
450_
~ 40Q_
o>
~ 350_
LJ
§ 30Q_
u.
o 250_
* 20Q_
d
»— i
^- ion_
o
h-
50
0
0 i
0
o
0
0
~ * 0 °
© 0
0 O
0
O
0
IK *— f* •«•«• • r- ** ^\/Mm ^* r— /» *~\t*f* **ir— m i f»*m » r- rm
450 500
INITlflL TOTRL SOLIDS STREET LORD Ob/curb-mlle)
-------
! i ! • ..--•.-:•! I at io-, ' ! M 1 ( e t •-•,,;; ,M e wa-nhi-: 1 to ruiiot !
•- -i" • i * . . : :' <•.», ii c> •••:•', i ',','.,_;•. A,M i t i • ." .<:;a i . sos r>- ~ .11 i ->;
!-•' : •'• • ' -•'!' t i; . i a.4,-. t.: runot, o-ncent i a t i i'ti a,:ai:,>t In
t:.i^'...; • .'. t I-.-!! \':.l',-.-. ..••[. r..,do t-T all .-i vs t i L u--:i t s . In ail ~ases, a
•'••.•r'. ;, •••.i.-..-r ii"r u-,., nh--iTvr.'. uiti'. ;' i t 11.> r c i: t ap p r i- x i ~..i: c ratios for each
•.>'••. t i t n,'-.t . '. .M i i >, -,i . d i :-, i.', u s ,( ,st ' • et load s ye r -i,? rxin.,: 1
o'".i'"Li iti"1 -, !AIU.\..T, !-<•.--. • i- si.owed a signiti'-ant rel 11 iorT, h i -> fi.r any of
t. tv .-<>•!': ' 1 t lie'" >- .
n -:r ••Kl.siiNh (r ISV'HX:--) RVr'OKr (.VNa.MKATloNS V.- THK 1\!' TLhT BASINS
A i'M >,'. v,)--?,i.:o ^f usir.i; tost ina control basins is Ll'e ability to
c.-.'n(',:iri: C ;u n:-.o'l ^n.iLity tu.. i nv; d-ftiT(?nt test conditions in the difKrent
!>.;-i;is. i-.t c1.'-'. V-- strc-'t clt-.ining operations were rotated, so that street
cl.- i-iif.,• oci'\irrtd in hoth Kisins during wet and dry seasons, while the otlr r
Ui>;l:i did not have any street cleaning. In addition, about two months during
b<>: '' tl.c iirv ,rid the wet seasons did not have anv strjet cleaning in either
ba-^ir.. The period of time with no street c leaning was used to "ralibra'e" the
txi>i.'.s. Urban runotf conditions at the i.wo -j t^s during these r.o cleaning
[.ft'ii'ds we^^ comp;;i ed to determine "natural" dirlirences and variations.
Table 9-5 idontil~-i.es the stunns for the period of time when street
cieaiinj; was not conducted in either bafin. ,\lso shown on this table are the
rain totals thit occurred in each basin for these calibration storms, al'ng
with the ratio 3f rain totals for the two basins. Several other rains also
occurred during this time period that were completely Tnonitored, but the
ditrereuces in rain volumes at the two sites were very large. This was quite
cr.-r.ion with tht smallest rain events as described p-eviously in Section A.
".'hose st ir-is «ri^h quite different rain volumes for the same rt.in period were
eliminated trom tliese analyses. This table shows that 20 storms were
completely nonitored during periods of no street cleanini; in either basin.
The average rain in prt'i basins ^7as about 0.45 inch (11 min) , or about twice
the volune of the -tverajTe rains during the complete study period. The range
of rains during this calibration period were from about 0.04 inch (1 mn) to a
Kifb, of about 1.25 i-.ches (32 mm). These calibration rains, however, were
weighed more towards th^ larger rain events than the typical distribution of
rai-is. The srr.,-.ller rai:i events experienced much greater variations in
observed rainfall and runoff volumes and more of the smaller events were
eliminated from the analyses.
Table 9-b summarizes the ttorm information during periods when intensive
street cleaning was conducted in Lake Hills, while no street cleaning
occurred in Surrey Downs. The 27 monitored storms were divided about evenly
between the wet and dry seasons. Again, the average rain volume during this
period was quite a bit larger than the average rain volume over the complete
period of testing. Table 9-7 is a similar listing, showing rain data when
intensive street cleaning was con-ducted in Surrey Downs, but no r.treet
cleaning was conducted in Lake Hills. Almost all of these storms occurred
during the vet season because of early sampling equipment problems in Surrey
bowns as described in Sections 5 and 6.
\ 70
-------
TiMe 9.5. COMPLETE STORM DATA DURING PERIODS Of NO STREET
CLEANING IN EITHER BASIN (CALIBRATION DATA)
Storm
n.ite
7/11/80
7/U
3/J6
8/27
9/1
9/6
9/12
9/13
11/23
12/14
12/20
12/24
12/24
12/26
12/29
7/6/81
7/13
1/10/82
1/15
1/17
Season
dry
dry
dry
dry
dry
dry
dry
dry
wet
wet
wet
wet
wet
wet
wet
dry
dry
wet
wet
wet
Storm
N'jThor
21
22
25
26/26+27(1)
28+29/28
30
31
32
51
55
56
58
59
61
62
114
116
156
158
159
average:
minimum:
maximum:
N = 20
Lake Mills
Piin
(in)
0.28
0.15
0.04
0.43
0.52
0.23
0.12
0.16
0.83
0.17
0.43
0.26
0.44
0.32
1.11
0.64
1.25
0.35
0.98
0.18
0.45
0.04
1.25
Surrey Downs
Rain
(in)
0.22
0.15
0.08
0.55
0.50
0.27
0.08
0.14
0.86
0.11
0.43
0.26
0.51
0.34
1.14
0.53
1.17
t0.30
1.10
0.16
0.45
0.08
1.17
Rain Ratio
(LH/SD)
1.27
1.00
0.50
0.78
1.04
0.85
1.50
1.14
0.97
1.55
1.00
1.00
0.86
0.94
0.97
1.21
1.07
1.17
0.89
1.13
1.04
0.50
1.55
LH/SO storm numbers, if different
171
-------
e 9-6. O'"1ETE Sinc-M PATA H'lRIN" FJRHDS OF
STREET CLEANING IN LAKE HILLS ONLY
Lake Hills
5 to nr
Pit?
9/20/SO
10/3
10/1'
.0,24
10/3!
11/1
11/3
11/8
11/14
11/19
11/20
1/17/31
1/28
2/11
2/13
3/24
3/28
4/5
4/5
4/7
4/10
4/12
4/27
5/24
6/12
6/12
6/30
Season
dry
wet
wet
wet
wet
wet
wet
wet
wet
wet
wet
wet
wet
wet
-------
Table 9-7. COMPLETE STORM DATA DURING PERIODS OF
S"IRECT CLEANING IN SURREY DOWNS ONLY
Storm
Date
4/18/80
10/8/81
10/28
10/30
11/11
11/13
11/30
l?/3
12/4
12/9
12/13
12/14
12/17
12/18
12/23
Season
dry
wet
wet
wet
wet
wet
wet
wet
wet
wet
wet
wet
wet
wet
wet
Storm
Number
8
127
129
131
132
133
137
140
141
148
149
150
151
152
154
average:
minimum:
maximum:
N = 15
Lake Hills
Pain
(in)
1.33
0.27
0.20
0.07
1.58
0.14
0.12
0.16
1.43
0.84
0.30
0.96
0.21
0.69
0.26
0.57
0.07
1.58
Surrey Downs
Rain
(in)
1.18
0.24
0.17
0.09
1.50
0.11
0.14
0.19
1.27
0.78
0.35
0.87
0.?9
0.79
0.27
C.35
0.09
1,50
P, a i n o -i •: i o
(LM/'^i
1.23
1.13
1.18
0.73
1.05
1-27
0.86
j.84
1.13
1.08
0.83
1.10
0.72
0.87
0.96
1.00
0.72
1 27
-------
Ki>,m~»-s r>-* ' ll-ri'n.-'i H-M i ,11 r s.-.'.ttri p,uts ^h iwing tot;,! mi! id.; yields
.u':,i i ":iv i-r.t r it inn il: I ! (''. f \ i i i> s in i..ikf Kills ,iiid SutTi'v ',Xiv.-- fii- b" t h the dry
.<-.! '-'• i '-t'.i.- iir1- . l>>n ii'.r. the !ry se.ison, i.nlv the calibration d.-itn and the
d.it.j vhi-n iiili':";tve rli'.iniiv. t,rcur'--d in 1. ike Hills arc sh.'wn. There < t> a
i.i:,c ,i;r.>'ur,! t>l s.,ittri and statistical 11 s I s did not sh iw s i ,;n i f It an t
<.!; i 1 t'Veiici-s in i.-.-, 1 i bi a t i on conditions tor dry and wet S
-------
FIGURE 9-22
TOTflL SOLIDS CONCENTRflTION COMPRRISION5
35C
in
2 30C
t—
cr
UJ
LJ
z
o
LJ
cn
a
o
1/1
(X
f—
o
in
3
o
a
UJ
a;
in
25C
200_
15C
IOC
50.
0
CLEANING IN LAKE HILLS ONLY-
CALIBRATION (NO
CLEANING)
'"' CLEANING IN SURREY DOWNS ONLY
I
25 50 75 100 125 150 175 200
LflKE HILLS TOTRL 50LID5 CONCENTRHTIONS
225
250
-------
FIGURE 8-23
TKN CONCENTRnTION COMPRRISIGNS
4.5
3.32_
10
o
O 1C
z 2.25 _
o
LJ
1.Ba-
z
i i..
>-
LU
in
ti (f.'o cLF.Ar;rr;c>—^^' ,
I--'
..^^•"'IN LAKI;
.--•*••
CLEANING IN SURREY DOWNS ONLY
44 .88 1.33 1.77 2.22 2.66 3.11 3.55 4
LflKE HILLS TKN CONCENTRfiTIQNS (mg/1)
-------
150
140.
~ 130_I_
2 12C
100
90.
o 7Q
LJ ' u— •
a
o
in
o
a
SO-
SO.
40.
30.
20.
10.
0
FIGURE 9-24
COD CONCENTRflTION COMPHRI5ION5
CALIBRATION (NO CLEANING)-^/'
*'•''' ^<--'"^
xf S* ^.f/-'*'" CLEAN ING IN LAKE HILLS ONLY
^ I ^-/*'""
^i^»''xf-/C CLEANING IN SURREY OOWNS ONLY
10 20 30 40 50 63 70 80 90 100 110 120
LflKE HILLS COD CONCENTRATIONS (mg/1)
-------
FIGURE 9-25
in
z
o
CE
cc:
UJ
LJ
in
r:
o
in
ui
o
Q_
in
o
a
LU
LH
PHOSPHORUS CONCENTRRTION COMPRRISION5
1.2
CALIBRATION (NO /\
CLEANING) _ /
..''CLEANING IN LAKE HILLS ON_LY->-'
..
CLEANING IN SURREY DOWNS ONLY
2 .3 .4 .5 .6 .7 .8 .9 1
LflKE HILLS PHOSPHORUS CONCENTRflTIONS (mg/1)
1.1 1.2
-------
FIGURE 9-26
LEflD CONCENTRRTION COMPfiRISIONS
.55
.5
^ .45_
in 4
-jr . H
o
I-H
t— qq
(X • •J-J—
ft:
t—
Z q
ULJ • *3
LJ
Z
S ,25_
a
ac
|j-i 2
i
1/1
I -15-
0
a
. .1
>— • •*
LU
a:
§ .05_
vn
0
CALIBRATION (NO CLEANING)-. ^-x
— • x '
^ , -
^^ .--''
^X ,.-''
- "^ „ *
x x ,-"'
• s •' ^ C~
•** .'" ^ ^"
x- "" .-•'' - " **
— CLEANING IN SURREY ,"^.--'' _.''"' __..--
DOWNS ONLY ( +• ) ^ •''].•-"" ^ - "* " _..- \
. f •* f-' ^ -.-*"
* _,-* f.-' *""..--•'' CLEANING IN LAKE
^-.r-'"*' „•*".*'•"'"" HILLS ONLY
,-<-'"'' t '-•"''
-*'** f^*
. .•i*-*1 ***
i^ * -->->
T * -•**'
1 f + * **
! ^* - *^ x
* * _
, ^
«• ^»«— * « r™ ^\ ^^ -^ *-kf~ j j i— r—
0
1
LRKE HILLS LERD CONCENTRRTIONS (mg/l)
.55
-------
oo
o
FIGURE 9-27
ZINC CONCENTRRTION COMPRRISION5
.35
^ .3-
en
E
§ •*
.2.
LJ
O
LJ
-z.
>—t
M
.1.
o
a
UJ
a;
a:
CALIBRATION (t;o cLI:A:;i:.c)•
. -J '
'CLEANING IN LAKE HTLL:;
r
k-
•CLEANING
IN SURREY DOWNS ONLY
0 .025 .05 .075 .1 .125 .15 .175 .2 .225 .25 .275
LflKE HILLS ZINC CONCENTRflTIONS (mg/1)
.3
-------
7.4
7.2.
7 _
6. a.
6.5_
C A
6. 4_
FIGURE 9-28
PH COMPflRISIONS
o
UJ
1
01
CLEANING IN SURREY DOWNS ONL
s-
CALIBRATION (NO CLEANING)
__-'".7-"CLEANn;G IN LAKE HILLS ONLY^.
»•*--•"
5.8.
5.&_
5.4^
5.2
I--'
5.3 5.5 5.7 5.9 6.1 '6.3 6.5 6.7 6.9 7.1
HILLS PH
-------
CD
ro
FIGURE 9-29
SPECIFIC CONDUCTRNCE COMPRRI5IGNS
120
E . , p
U 1 1C
W
_g IOC
E
a
g 80.
LJ
70
S 60.
LJ
£ 50.
I C
LJ
£ 40.
LO
£ 30.
o
UJ
in
1CL
CALIBRATION f.o C'l.i'.AN I :.<;)
X
X
xl
X
X
r
-T- I .--r.
.-1 •
v-
10 20 ' 30 40 50 60 70
LflKE HILLS SPECIFIC CONDUCTRNCE ;umhos/cm)
80
90
-------
oo
CO
6G.
en
Q
>-
t—
i—i
a
CD
oi
t—
£ 30.
ac
o
Q
u] 20.
a;
a:
in
FIGURE 9-30
TURBIDITY COMPRRISION5
CLEANING IN SURREY
DOWNS ONLY
^CLEANING IN LAKE HILLS < )'.'.l.'i
0 I
0
10 ' 20 30 40 50 60
LfKE HILLS TURBIDITY (NTU;
70
80
i
-------
stoini u.'sh.-!t Ivr.iiis,
i- 1 ea n i in: ec; u 1 (n.en t . an remove a t a i r 1 y
si.il.u->- p,i r t ic u i a t fs , but they a r •• n;it the
stores urder the conditions observed in
er p,i r t Icu i a t es hy street (leaning nay
of tlic inss of tbi-- arjrnriiiH ctfccts.
and den.--id tipu;-, specific r.ilntall
i-i-no i t ; .'-is U's j't-i i ,i I 1 v iiUon-j i l i vs , intert",ent fimes, and total r.iinlail
.j-.iriii I i t i .'- ) ,iiul Nlret't. surface conn i t :' ons (especially Ct-xtur-.' and state of
repair). In t'.istro Valley, California (Pitt and Sluwlev, 19^1), the quite
oiilerei.t raintall and street surface conditions permitted street cleaning to
i ropr. ive rvirol t water qviality bv a maximum of about J 3 to 4t) percent tor lead,
total '•.!)! ids, and CnL). hven under those more appropriate conditions ior
street cle.ming, street cleaning had very little effect in controlling
nutrient runott concentrations and vields.
One of the ,uiin reasons Bellevue was selected as a test site by the
htivi roiiment al Protection Agency, was because of its significantly different
rain conditions wh_>n compared to other street cleaning test cities. The larga
nuaber of rain events occurring evenly throughout the year (with each having
small rain volumes and intensities) and the smooth street surfaces resulted
in the frequent rains being capable of maintaining the street sarface
loadings at low levels, especially for the smaller particle sizes. Intensive
street cleaning operations did significantly decrease the street surface
loading conditions, but only for the larger particle sizes. The benefits of
street cleaning in controlling nuisance and safety related street surface
particulates are described in the following Section 10.
184
-------
'SECTION 10
STREET CLEANER PERFORMANCE
The design of an effective street cleaning program requires not only a
determination of accumulation rates but also an assessment of the specific
street cleaning equipment performance for the actual conditions encountered.
Service goals which consider efrects on water quality, air quality, public
safety, esthetics, and public relations are the driving forces in
establishing a street cleaning program. The major objective addressed in this
section of the report is to determine the effectiveness of street cleaning
equipment in reducing street particulate loadings. The previous Section 9
addressed the effects that reducing the street loads have on improving runoff
water quality. It was seen that the measured runoff yields during periods of
intensive street cleaning did not differ significantly from the runoff yields
that were measured during periods of no street cleaning. However, Section 6
earlier had shown that jtreet surface runoff contributes significantly to
runoff yields for several pollutants. It was also shown in Section 9 that
rain is most effective in removing the smallest street particulates. This
section wl'' Discuss the effectiveness of street cleaning equipment in
removing particulates of different sizes. It will be shown that conventional
street cleaning equipment is most effective in removing the largest particle
sizes: those that are not effectively removed by rains during storms. A
series of special tests were also conducted and described using a modified
regenerative air street cleaner that shows promise in effectively removing
the smaller particle sizes. This section, therefore, describes the results of
the full-scale street cleaning tests that were conducted during the runoff
monitoring activities, the special tests using the modified street cleaner,
special tests conducted to examine street cleaning effectiveness in other
Bellevue areas, and tests conducted to examine the redistribution of street
dirt during street cleaning. The effects of street cleaning on reducing
runoff pollutants are also estimated, based on typical street dirt loading
values observed for the different street cleaning programs and tne washoff
potentials for the different particle sizes. Finally, the Bellevue street
cleaning program, equipment operating characteristics, and costs are
presented.
Street cleaning performance depends on many conditions, including the
character of the street surface (texture, condition, and type), street oirt
characteristics (loadings and particle sizes), and other environmental
factors. Street cleaning variables that most affect cleaning performance
include the cleaning frequency and equipment adjustments. The most important
measure of street cleaning effectiveness is "pounds per curb—mile" for a
specific program condition. This removal value, in conjunction with the unit
curb-mile costs, allows the cost for removing a pound of pollutant for a
185
-------
-' ' • i '- i *' s i i ri t '• I • .1111 :':',. pt ogr.un to be Crt 1 ( n 1.1t re1 . The ' pe rcent of the ht' f ore
'"•i'!i">' i fii.iv.'d ' is COL. 'only used, hut ran be mi s ] eau i ng . The pe rcenlige
tn-Mved is I-.'t ;i irk'.isiire ol the iTur.n i t ude of material removed. A street
' 'li'.ni ..r, pr.n'i.mi T"*IY li.ive a ve r >' low pv rcen t ane removal , but a large amount
01 loiter i a l n,iv tx' removed it the initial loading is lar>-e. The percentage
renov.il v.ilue^ can tx> useful when normalized values are needed, such as when
con.r.u i >n; two ditterent programs under similar loading conditions.
Sll
-------
Table 10-1. FULL-SCALE STREET CLEANINR TEST SCHEDULE
00
—I
Season
Month
Cleaning dates for:(l)
Surrey Downs Lake Hills
dry
dry
dry
dry
dry
dry
wet
wet
wet
wet
wet
dry
dry
dry
dry
dry
dry
dry
wet
wet
wet
April, 1980
Hay
..une
July
August
September
October
No /ember
December
. January, 1981
February
Mar:h
Apr' 1
May
June
July
Augu/it
September
October
November
December
2,7,11,16,18,21,23,25,30
5,7,9,12,14,16,19,30
4,11,13,15,18,20,30
2,7,9
none
none
none
none
none
none
none
none
none
none
none
none
none
29,30
2,12,16,20,21
2,5,16,24
7,11,14,16,21,23
none
none
nonp
none
none
15,17,22,24,25,29
1,3,6,10,13,17,22,27,29
5,10,12, 17, 19, 24, ?6
15
5,9,12,19,21,30
2,4,13,17,20,23
2, 4, 6, 9, 11, 13, 16, 20,24,25, 27
2,3,6,8,10,13,15,17,21,23,24,29
1,4,6,8,12,13,15,21,22
1,5,11,17,23,24,26,29
1
none
none
none
none
none
approximately three times a week street cleaning, except for holidays
and dc'ys of rain
-------
i'i IH'Ctrd iln i ing tin.' project.
Figure 1U-1 js .in example ot this data p,'o':tec for a hS-day period for
l-iu rey iiovii:. 1 rcim August ,:4 to October 28, 19H1. At the beginning of this
period, Surrey Downs was not bein^ cleaned. Street clearing startco on
ieptcnuier J^th. The street cleaning days are shown oil the plot, along with
the rain periods. The street loadiigs ranged from about 300 to 5(M)
I bs/ cur h—mi Le I,b3 to 14U g/curb-meter) ;with ar extreme value of about 900
Ibs/curb-mile , or 2u'i g/curb-meter) during the period of no street clearing.
The loading:; reduced ti; values from about 150 to 250 Ibs/curb-mile (40 to 70
g/curb-meter) shortly af;er the start of street cleaning. Median particle
sizes are shown on this figure and are also seen to decrease with the start
of cleaning. The significant effects that rains had on the street dirt
loadings and particle sizes is evident. The r&in periods shown all reduced
the street loadings appreciably (except for the largest rain observed dviring
the study which occurred during this period) and increased the median
paTticle size values. This indicates that the rains washed off the fine
material more efficiently than the larger material, (as discussed in Section
9). The largest riin had little effect on the net loading change, probably
because of substantial arosion material carried to the street during this
major storm.
This figure indicates that the street loadings responded rapidly to
street cleaning. The loading data collected can therefore be considered
responsive to the street cleaning conditions, with little lag time between
changes in the street cleaning program. Changes from periods of strtet
cleaning to no street cleaning were not as rapid. However, the street
cleaning accumulation rates, as described in Section 7, were shown to be
largely controlled by the frequent rains during periods of no street
cleaning. Therefore, loading values are expected to be stabilized t?fter about
three street cleanirgs or rains.
PERFORMANCE TESTS
Several types of street cleaning performance tests were conducted during
this project. The large scale tests described above required the most effort
and resulted in the most data. Selected tests were also conducted at a
variety of other land-use sites in Bellevue to check the transferability of
the full-scale test results. Two tests were also conducted to measure th3
redistribution of street dirt across the road caused by street cleaning. An
intensive series of tests were also conducted to examine the effectiveness of
a modified regenerative air street cleaner. These test results are presented
and discussed in the following subsections.
Full-Scale Tests
The street loading data presented in Appendix B contains the total
solids initial and residual loading values and median particle sices for the
full-scale tests. Complete data lists for all particle sizes are too bulky to
present in this report, but are contained in the STORET data base operated by
188
-------
FIGURE 1 0- 1
C
o
U
E
01
Isl
c
O
TJ
c
O
00 ^
E
I
_O
L
U
V.
-O
O
o
w
"O
o
in
c
4>
o
Surrey DONHS Street Loads (8/24-10/28/81)
10GOr
0
10
15
20
30
90Q_
80Q_
70Q_
60Q_
50Q_
400-
300-
20Q_
100_
0
_/\
J 1
^,
^
c
/
A
±-1
Mil
.
\
\
D
^)
'
\
1 i
A
/ \
\
/
/
V
1
SIZE
\J.
LOAD
MM
..
,/
\^r*~-
1 1 1 1
.,
LT
•^t
q
I
i
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i
i
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* 1
\ '
t
I
MM
=L
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c
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,
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>
'•,
',
/
k
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,
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)
/
t /
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\
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1
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\
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CO
LT
C
^
1
/
I
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\
1
1
MM
^s t-
i
0
O
"N
^
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/
, —
a
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7'
cc
r^
*-r
.
£z z
•JC< «£
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1 (|
! i'l
r ' 1
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*i,r'
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i i,'
\
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1 1
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ID
1 1
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*"il— 1 j ff
i
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^ 3 ^-^
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^- f ^
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^f
XT M* ^e
x^ffl I ^^
s /"^ d— ®"^
V— «/
v w
1 II 1 1 1 II II 1 1 II 1 1
45
50
55
60 65
Day Number (from Rugus* 24 to October 28, 1981)
-------
L.tke llill. Vl'i'K'.T stati»n number is Mi.Kiij-j,],()S^2 and tht station
r Siirri'v !\ u'M' I'i JO ^HKL.L.l'iH i. Those are special Ni'K!' STnRKT files
ront.iin street iirt loading information. The S'»nKKT data can be urfcd
in run i unel ion wi t'i the .iata presented in Appendix B tor a complete
ik-so r i pt ion oi the street loading history at the two main Bellevue street
clean i!'.;; tisL sites.
The most useful way to present street clsaning effectiveness data is on
.1 graph relating residual loadings to initial loadings. Such figures are
shown as Figures 1U-2 and iO-3 for total solids and median particle size.
Appendix C contains figures for particle sizes ranging from greater than 6370
microns (about 1/4 Jnch) to less than 63 microns (Figures C-l to C-8). The
relatively large number of street cleaning tests (121) enabled the
effectiveness relationships to be described in detail. It was found that both
Lake Hills and Surrey Downs data could be combined for statistical analyses.
The Surrey Downs data represented loadings over a wider range of initial
loading conditions (from about 80 to 700 Ibs/curb-mile, or 23 to 200
g/curb-meter) than the Lake Hills data (from about 90 to 390 Ibs/curb-mile,
or 25 to 110 g/curb-ineter) . The lower Surrey Downs data is shown to overlay
the Lake Hills data on these figures.
In earlier studies (Pitt, 1979, and Pitt and Shawley, 1981), the fewer
data available indicated "straight-line" relationships between the initial
and residual loads, with "negative" removals associated with the lowest
loadings. The greater number of data available during this project, however,
has refined this model. The effectiveness figures presented in this section
and in Appendix C indicate no effective removal by street cleaning until a
minimum initial loading value is obtained. Above this minimum value, street
cleaning can be quite effective. The scattered data before this minimum value
is obtained include many cases whera the residual loadings were greater than
the initial leadings. These negative removal values may be associated with
street wear (as was noted in Pitt's 1979 San Jose study, especially for
multiple street cleaning passes every day on streets in poor condition). This
data scatter may also be due to sampling error, as the street dirt sampling
procedures were designed to result in errors of about 25 percent.
The minimum value before street cleaning is eff^'ive varies for each
particle size, street surface texture and condition, and equipment operating
characteristic. Table 10-2 summarizes these minimum values for the Surrey
Downs, Lake Hills, and S.E. 30th study areas. Also shown are the maximum
values under which the loadings are usually maintained for these street
cleaning operations. It can be seen how referring to percent removals can be
misleading. For Lhe same aree, cleaning frequency, and equipment type, the
percent removal varies from nothing until the minimum value is obtained, then
slowly increases to values approaching about 30 percent for total solids. In
sone cases, the maximum percent removal values may be as large as 80 percent.
If the street loading values must be maintained below a certain maximum
loading value, then each cleaning event required would have very low percent
remo\al values.
These figures show how ineffective typical mechanical street cleaning
can be for removing small particle sizes. For the conditions observed, there
190
-------
FIGURE 10-2
Street Cleaner Performance: Total Sol ids
800
DC
0 100 200
e SURREY DOWNS(Mobil)
A LAKE HILLS (Mobil)
T: Tymco (SURREY DOVvNS)
M: Modified Tymco (SURREY DOWNS)
300 400 500
Inlilol Lood (lb/curb-ir.lle)
600
vca
80u
-------
FIGURE 1 0-3
Street Cleaner Performan
1000
ce: Part i c)e 5 ize
0 100 ' 200
o SURREY DOWNS
A LAKE HILLS
300 400 500 603
Inlilol Size (microns)
70G
eca
9GO
JGOC
-------
TA8LE 10-2. TYPICAL MINIMUM LOADS FOR EFFECTIVE CLEANING
AND MAXIMUM LOADS AFTER CLEANING (I BS/CURB-MILE).
Si^e (n.icrunr.)
SO and LH :
TS
>6350
2000 - 6350
1000 - 2000
500 - 1000
250 - 500
125 - 250
63 - 125
<63
<37
< 2
SE-30th
TS
>6350
2000 - 6350
1000 - 2000
500 - 1000
250 - 500
125 - 250
63 - 125
<63
<37
<2
MOBIL
Minimum Maximum
initial exnected
load before residual
removal load
350
5
15
25
60
70
/O
--
--
__
--
insufficient
450
15
30
50
80 +
90 +
90 +
--
—
--
--
data
TYMCO
Minimum
load
before
removal
100
--
3
5
10
10
10
10
20
5
0.1
200
5
20
50
50
50
25
15
25
20
0.2
Maximum
expected
residual
load
300
3
10
20
50
60
50
30
40
__.
500
10
40
__
_ —
— _
200
— —
60
__
193
-------
v>'.ts no ( Itcr'ivi. i i-muv.i 1 ot particles smal'er than about 125 microns. Vcrv
,-uhs (. .r.it i .11 r"\nov,tls were u,! isured tor larj'.f panicles, however. Figure l'i-3
inj i r,i L rb the dr,ir,,,itic decr>,is" in median particle size as the street
cleaners pre 1 e ren t i al ly removed, the Larger particles.
Street Cleaning Effectiveness at Other Bellevue Locations
During the second year of the project (April and May, 1981), street
cleaning tests were conducted at eight other land-use sites in Bellevue. The
l.ind-uses included downtown Bellevue, shopping centers, high density
residential areas, low density residential areas, and industrial areas. Table
C-l shows these data for all particle sizes. Unfortunately, only one or two
tests were conducted at each site, so individual analyses of the land-uses
were not possible. Figure 10-4 is a plot of the initial versus residual
values for all of this data combined. These data appear to fall on the total
solids curve presented earlier (as Figure 10-2) for the large-scale tests.
The S.L. 3uth and 2nd Avenue industrial sites had much greater initial loads
than elsewhere, but the street cleaners -'-re quite effective in substantially
reducing the loadings. The minimum initial loadings before effective removal
was about JOO to 40U Ibs/curb-mile (85 tp 11U g/curb-meter), quite similar to
the values shown in Table 10-2 for the Surrey Downs and Lake Hills sites.
Figure 10-5 shows the strong relationship between percent removals and
initial loadings. The clean streets had very low removal percentages, while
the very dirty streets had high removal percentages, even though the Figure
iO-4 data seem to fit the general model. Such different percentage removal
values imply different removal models.
Redistribution of Street Dirt Across the Street During Street Cleaning
Two special tests were conducted in and near the Surrey Downs test area
to examine the loading gradient across the streets, before and after street
cleaning. This data, for all particle sizes, is shown ±r Appeneix Table C-2.
Figures 10-6 and 10-7 show the total solids unit area loading data plotted.
The unit area loadings in the ten inches (254 mm) next to the curb were
reduced substantially in both tests. The other street segments experienced
variable loading changes. These changes indicate substantial movement of the
near curb dust and dirt away from the curb by the gutter brooms. The main
pick-up brooms were not able to remove all of this moved material. These
results are similar to tests conducted on a variety of different street
cleaners in the past (Sartor and Boyd, 1972, and Pitt, 1979).
Effectiveness of Modified Street Cleaners
A series of special tests were conducted during September and October,
1982, to compare the effectiveness of a modified street cleaner to standard
street cleaners. Air Pollution Technology, Inc. (APT), of San Diego,
California, designed and installed many modifications to a standard
regenerative air street cleaner while under contract to EPA (William
194
-------
FIGURE 10-4
Cleaning Productivity for
4500
isc. 5 : te
:D
1500 2000 2500 3000
I nit to) Load (1b/curb-mMe)
3500 4003 4500
+ 2nd Ave.
x 120th
•KELSEY ST. PARKWAY
• Hath
* S. K. 30th
* DELLEVUE WAY
-------
FIGURE 10-5
% Removal vs. Initial Load (misc. sites
80
63.
5 40.
o
E
0)
a:
3 20.
L
OJ
-20
500 1000 1500 2000 2500 3000
Inltlol Load (1b/curb-mI 1e)
3500
4000
-------
36
30.
Q)
01
24
o ^ -
3
cr
w
-O
X
o
0
18.
S 12.
6
0
FIGURE 10-6
Redistribution of Street Dirt
Removal
OVL'.KALL: -70-'. { i ncr o a •;< •<} load)
•RESIDUAL LOAD
•INITIAL LOAD
-53%
-21%
1
6 ' 9
Distance from Curb (ft.)
115 110th Ave. S.E. Site
12
15
-------
01
c
o
o
FIGURE 10-7
Redistribution of Street Dirt
7 4'4 Removal
INITIAL LOAD
-12%
151
RESIDUAL LOAD
OVL'P.ALL: 2 (U ( doc r-a r;oa loom
-7%
110-
6 ' 9
Distance from Curb (ft.)
405 110th Ave. S. K. Site
12
15
-------
Kuykendal, Project OiUcer, Research Triangle Park, North Carolina). The
purpose ot the modifications was to reduce respirable fugitive dust emissions
during street cleaning activities. Th° modifications included partial hoods
around the gutter brooms, a pressure controller to better regulate the air
flows, and a venturi scrubber with a settling chamber in the street cleaner
hopper. The water spray bar was also disconnec'ed. These modifications were
described in the first phase report prepared by APT for EPA (EPA Contract No.
68-02-31*8). APT was awarded a second contract phase to refine the
modifications and conduct extensive field trials of street cleaner
effectiveness. An arrangement was made to test the modified street cleaner in
Bellevue, in order to take advantage of the preexisting information relating
street cleaning and rurc.M" water quality. The modified street cleaner was
compared both to a standard broom street cleaner that was used during the
previous Bellevue tests, and to itself, with the modifications disconnected.
The purpose of these special Bellevue tests was to estimate any effect the
modifications may have on improving urban runoff water quality. APT has
conducted additional tests in San Diego to study air quality effects during
street cleaning.
Surrey Downs and S.E. 30th Avenue (an industrial street Chat was
previously determined to be one of the dirtiest streets in Bellevue) were
used for most of the tests. Each area was divided into six subsampling
sections. The three equipment types were rotated through these sub-areas at
various cleaning frequencies. This allowed the street loadings to vary over a
relatively wide range of values for each equipment type. Table C-3 shows the
results of these tests for all particle sizes. Four or five cleaning tests
were conducted for each equipment type. In addition, several test
measurements were made separating the cleaning width loadings from the full
street width loadings. Figures 10-8 and 10-9 are the usual initial load
versus residual load effectiveness diagrams for Surrey Downs and S.E. 30th,
respectively. Appendix Figures C-9 through C-30 show the effectiveness
relationships for each particle size. These figures represent full street
width loadings, and are therefore comparable with the earlier full-scale test
figures. The broom cleaner results are very similar to the previously
reported results, but the regenerative air cleaner (modified and not
modified) shows substantially better performance. This is especially true
when the finer particle sizes are considered. The broom cleaner shows very
little removal (the loadings are too low) for particle sizes less than 1000
microns. The regenerative air cleaners appear much more suited for these
lower loadings for the smaller particle sizes. The data for the smallest
particle sizes (less than 125 microns) are inconsistent, implying little
consistent removal effectiveness by any of the street cleaners. Similar
results are shown for both the study sites. The smallest particle size (less
than two microns) showed better removal effectivenesses for the regenerative
air street cleaners than for the broom street cleaner, in most cases.
To differentiate the modified and standard regenerative air street
cleaners, data art presented in Figures 10-10 and 10-11 for total solids
loadings in the cleaning width only. The modified street cleaner is seen to
have almost a constant residual loading value in the cleaning width after
cleaning, irrespective of the initial loading. This indicates a very
important advantage in cleaning effectiveness for the modified regenerative
199
-------
O
O
700
FIGURE 10-8
Surrey DONHS Total Sol ids
100
200 ' 300 400 500
Initial Lood (1b/curb-m!1e)
600
700
-------
FIGURE 10-9
5.E. 30-^ Total Sol ids
0 ' 200
1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 3UOO 3200
InKlol Load Hb/curb-ml 1e)
-------
o
no
0
FIGURE 10-10
Surrey Douns Cleaning Width
50
100 ' 150 200
Initial Load ()b/curb-mI 1e)
2aO
300
350
-------
O
CO
1200
0
FIGURE 10-11
5.E. 30-th Cleeni ng Width
O MODIFIED TYMCO
200
400 600 800
Inltlol Load (Ib/curb-mMe)
1000
1200
-------
Thit-- di t fe retire is not apparent with the full street
T\pK'al initial ind residual loadings for these tests are shown in the
bar civ-its, l-\v;ures 1U-12 and 10-13. The modified regenerative air street
cleaner is si-own to have been more effective than the other street cleaners
tor almost ail particle sizes, and for either area. The largest differences
were observed in the smaller particle sizes (less tnan 125 microns) in the
S.b. 3uth area.
Figures IU-2 and 10-4 (and Appendix Figures C-l through O8) have the
Surrey Downs regenerative air data plotted along with the full-scale broom
cleaner data. It is seen that the regenerative air street cleaners are core
effective, especially at the lower initial loading values. Table 10-2 shows
the minimum effective loading values for each type of street cleaner. The
modified street cleaner data are not shown on this table because they had
performance characteristics close to the standard regenerative air cleaner
(when considering the daca variations on these figures).
These data results are similar to the results found by Pitt and Shawley
in Castro Valley. California (1981), where they compared a regenerative air
street cleaner with a standard broom street cleaner. They found that the air
cleaner performed better with lighter loads, especially for the finer
material. However, the broom cleaner was found to perform better for heavier
loads, especially for heavy litter s id leaf loads. Pitt also compared vacuum
street cleaners to brcom street cleaners in San Jose, California (1979). He
found no significant difference in performance of the several types of street
cleaners tested under a wide variety of street conditions and cleaning
frequencies. One model of a broom street cleaner did result in substantially
more residual loading values that were larger than the initial values for
very intensive cleaning on oil and screens streets (it appeared to be
loosening the street pavement material).
Effects of Intens » ••. • Street Cleaning on Washoff Potential
Typical loading values for the different particle sizes are shown on
Table 10-3 for periods of no cleaning and for periods of intensive cleaning.
These values are averaged Lake Hills and Surrey Downs loadings during the
complete project period. Total solids loadings averaged about 390
Ibs/curb-mile (110 g/curb-meter ) with no street cleaning. The frequent
Bellevue rains were capable of keeping these smooth asphalt streets quite
clean (when compared to typical loadings elsewhere on the West Coast for no
cleaning periods). Intensive, three times a week, street cleaning reduced
these loadings to about 290 Ibs/curb-m.ile (80 g/curb-meter). The most
significant loading reductions were in the large particle sizes. No loading
reductions were noted for particle sizes less than 250 microns in size. The
washc.ff estimates given in Section 9 were used to estimate the washoff
potential associated with these loadings. These values are also shown on
Table 10-3. The washoff potential changes between the no cleaning and
intensive cleaning periods was from about 70 to 63 Ibs/curb— mile (20 to 18
g/curb-meter), or a reduction of about seven Ibs/curb— mile (two
204
-------
FIGURE 10-12
rv>
O
ng Special Tests-Surrey Downs
•no clean I ngFTj-Mobl 1
(initial loal)
250- 500- I 1030- 2333-
T-Tymco I l-Modlfled Tymco
(residual load)
>6353 Microns
-------
FIGURE 10-13
o
01
Loadings During Special Tests-S.E. 30th
500
*— *
QJ
- 40Q_
E
I
f 350_
;£ 30Q_
a. 250_
c
—
L)
g 20CL
_j
£ 150_
Q
"f* 1 PIP!
01 J UD
01
w 50
n
r-\
O
g
37-
H
S
f
G
B
*
••r
7"
I
2
,— _
\
\
\
[53^
*o
r^
1
mm
i
-0
s
/
'
CO
i — .
\
\
125-
OP
o
CO
i
i
i
^H
^
js /
0^
^H
-r-)0^
\
\
\
\
r-
250-
;
j
;
i
| c
; "n
• ~i"*r
i
i •
^
r
UJ
-n
\
\
500-
0\0
. — 1
r-
J
% 1
~^^-J u jV.
-1 'c { ^'i-
y i n
1000- 20CO-
w
>6350 Mictrir
iM~ no c 1 eo n I n9J [~rtob I 1
(initial load)
r~[-Tyinco I 1-Modlfled Tymco
(residuol load)
-------
TABLE 10-3, EFFECTS OF STREET CLEANING ON TOTAL STREET LOADS
AND WASHOFF LOADS (LAKE HILLS AND SURREY DOUNS)
ro
o
Particle
Size
(Microns)
> 6350
2000 - 6370
1000 - 2000
500 - 1000
250 - 500
125 - 250
63 - 125
<63
Total solids
No Clean ing
Typical Total
Load
Ib/curb %of total
mi le i n £ize
23.8 6. IX
36.9 9.5
38.9 10.0
68.3 17.5
81.1 20.7
64.8 16.6
38.4 9.9
37.9 9.7
390 100.0%
Available for
Washoff
%of load Ib/curb
for washoff mil •>
i
or. o
0 0
6 2.3
10.5 7.2
17 13.8
24 15.6
38 14.6
44 16.7
18% 70.2
Intensive Cleaninq
Typical Total
Load
Ib/curb %o'f tota'
mile in size
2.5 0.9*
10 3.5
20 7.0
56 19.5
60 20.9
62 21.6
38 13.3
38 13.3
290 100.0%
Available for
Washoff
%of load Ib/curb
for Washoff mile
0% 0
0 0
6 1.2
10.5 5.9
17 10.2
24 14.9
38 14.4
44 16.7
22% 63.3
-------
>;/curb-mpto: ) . A/,atn, if (.!••• ^mjll particles were reduced more by street
cleaning, the washoff potential would be reduced more.
figure 10-14 graphically shows these load and runoff potential
reductions. The percentage reductions are the same fnr both loads and runoff
potential for sizes less than 2000 microns. Rain washes off very few of these
larger particles. Street cleaning reduces the runoff potential for more
narttrlps in rhf size range of 250 to 500 microns than for any other size
rafge. This figure shows that street cleaning has very little effect in
removing the small particles that are most effectively washed off the street
by rain.
Table 10-4 shows estimates of the effectiveness of street cleaning in
reducing runoff yields of various pollutants. For very small rains, streets
contribute about 60 to 65 percent of the total runoff yield for these
pollutants. For larger storms, other source areas are more Important than
streets and the street contributions are reduced (except for lead which
mostly originates from streets during all rains). The runoff yiej.d reduction
estimates are about six percent for th° smallest storms, and about one to six
percent for the larger storms. The modified regenerative ai*~ street cleaner
may have removals about 1.25 times these values, or uo to about eight
percent. With such small potential benefits, it is ob. ious why the runoff
monitoring activities did not result in any monitored reductions. It is
expected that other areas, with less frequent rains, would have greater
runoff potential reductions. Pitt and Shawley found runoff reductions
associated with street cleaning as great as 40 percent in Castro Valley,
California (1981). Castro Valley has less rain than Bellevue, but more
importantly, it has long dry summers that result in very dirty streets if
there is no street cleaning. These dirty streets can be effectively cleaned
in late summer before the beginning of the rain season in Castro Valley. The
different rain seasons in Bellevue are not as dramatic, and the streets never
become so dirty without street cleaning.
BELLEVUE STREET CLEANING ROUTES, OPERATING CHARACTERISTICS, AND COSTS
There are no foimal street cleaning routes in Bellevue. The city is
usually divided at 3th Avenue NE, with one street cleaner operating north and
the other street cleaner operating south of this street. The operators clean
in areas that they feel require cleaning. They estimate that the downtown
area is cleaned about once a week, arterials are cleaned about once a month,
and residential areas are cleaned once every two months. The operators are
radio dispatched to trouble areas, as needed. An interim storage area for the
debris is located about two blocks from the municipal service center (where
the street cleaners are stored). About nine cubic yards (seven cubic meters)
per day per street cleaner is handled during the winter (about double this
amount if the streets are sanded). During the spring and summer months, the
debris quantity is reduced to about six cubic yards (4.5 cubic meters) per
day per street cleaner. The fall is the heaviest debris period, with about 20
to 25 cubic yards (15 to 19 cubici meteis) per day per street cleaner
handled. About ten to fifteen percent of the city streets are rough, or have
208
-------
0 I
FIGURE 10-14
Load and Runoff Reductions
>6370
dirt removal! hwashoff reduct.
:D
Percent reduction when intensive cleaning is corr.oared
to no cleaning.
-------
Table 10-4. EFFECTS OF STREET CLEANING ON RUNOFF IOAOSU
Approximate
percent of total
runoff load from
street washoff
Percent runoff
load reduction for
intensive street c'ea
Runoff
Pollutant
Total Solids
COD
Phosphates
Total Kjeldahl Nitroqen
Lead
Zinc
0.01 in. rain
65%
62
61
i 61
60
61
-0.1 in. rain
10%
40
31
31
60
45
0.01 in. rain
6 . &%
6
6
6
6
6
.>0.1 in.
1*
4
3
3
6
4.5
(1) The values shown are based on the 4-wheel mechanical street clean'3'" test's.
The regenerative air street cleaners are estimated to be about 1.25 times
as effective as the above values, due to their better performance on
removing the more washable fine particles.
-------
nc.- curbs, or both.
The city of Bellevue has two street cleanors that are described on Table
10-5. They are both four-wheel mechanical broom cleaners, with dual gasoline
engines, and 3.5 cubic yard (2.7 cubic meter) hoppers. They clean between 15
and 18 railed (24 and 29 km) each day, while cleaning at seven miles (11 km)
per hour. During special tests in Reno and Sparks, Nevada, Pitt and
Sutherland (1962) found that seven miles (11 km) per hour cleaning speeds
••ere much less effective than the usually recommended four miles (6.5 k-u) per
Hour cleaning speeds. This was especially important at heavy loadings
^greater than 15UU Ibs/curb-mile, or 430 g/curb-meter). The current Bellevtie
street cleaning program productivity may therefore be improved by reducing
the vehicle speeds, but at an increase in coot (if the cleaning frequency
remains the same). The speed effects may no: be as important in Bellevue
because of the lower street dirt loadings, bowever. Reducing the speeds on
the dirtier industrial streets may be worthwhile.
The street cleaners are maintained on a daily schedule, with appropriate
inspections and lubrications. The main pick-up broom is changed about every
14GU to 1500 miles (400 to 425 ka). Oil changes and other maintenance
operations are also conducted during broom changes. The street cleaners are
in the repair shop about 25 to 50 percent of the time. This downtime is about
average for street cleaners elsewhere.
Bellevue street cleaning costs are shown on Table 10-6. Street cleaning
is a labor intensive activity, with about 73 percent of the total street
cleaning costs associated with labor and labor overhead. The total cost is
about $20 per curb-mile ($12.50/curb-meter). Most of this cost is associated
with operation activities, and about one-fifth is associated with both
maintenance and debris disposal operations. Table 10-7 compares these
Bel'evue street clearing costs with street cleaning costs for other western
U.S. cities. The Bellevue costs are quite close to the total costs at these
other cities.
211
-------
Table 10-5. !,EL!_EU'JE STREET CLEANER OPERATING CHARACTERISTICS
Mike of Equipment: Mobil Athev
Models: 2TE3, 4-wheel mechanical broom sweenpr (1971)
2DF3, 4-wheel mechanical bro i sweeoer (1973)
Engine tyoe. dual gasoline engines, with hydraulic controls
Hooper capacity: 34 yds^
Fuel Efficiency: 35-40 miles/day (including t-avel)
17-20 gal (both engines ooerating)
= 2.1 mi 1es/qal
Sweeping miles: 15-18 mi'ies/day
Debris disposal practices: interim storage area with seoarate transfer to
land-fil1 as required
Speed during cleaning: 7 moh
Type of gutter broom: steel
Type of main pick-uo broom: polyethylene
Broom replacement intervals: main broom 1400 sweeoinq miles
gutter broom 300 sweeoing miles
Broom rotation speeds: unknown
Strike pressure of main pick-up brocm: 4" oattern
Maintenance schedules:
1. "A" service - when main broom is changed, aporoximately every
1400-1500 sweeoing miles, engine oil change, chassis
lube
2. Daily - refuel, inspection lube conveyor chains and bearings
3. As needed, esoecially at broom chances
212
-------
Table 10-6. BELLEVUE STREET CLEANING COSTS (19RO -
Item
Labor:
Repair labor
Disoosal labor
Operator labor
Labor overhead
Equipment operation, maintenace,
Depreciation
Disposal equipment
Outside services
Repair parts (includes brooms)
Tires
Oil
Gasol ine
Total
Typical
Cost per year
(S/.year)
$10,780
9,130
61,280
14,210
disposal, etc. :
5,300
12,400
675
10,240
710
120
5,890
$130,735
per year
Percentane
of total
costs (%)
8.3%
7.0
46.8
10.9
4.1
9.5
0.5
7.8
0.5
0.1
4.5
100%
Unit
Cost
(S/curb-fiile)
$1.68
1.42
9.49
2.21
0.83
1.93
0.10
1.58
0.10
0.02
0.91
$20.27
per curb mi le
Sub-totals:
All labor and overhead: 73.0%
All maintenance (labor, outside services, and repair parts): 18.1%
All disposal (labor and equipment): 17.7%
All operaton (labor, depreciation, tires, oil and qasoline): 64.?%
-------
Table 10-; STREET CLEANING COSTS AT VARIOUS CITIES (1902/1983 ADJUSTED COST")
ro
H-»
-p.
Labor
Operators
Maintenance and repair
Supervisors
Debris transfer
Overhead (secretary,
dispatcher, etc.)
Subtotal
Street cleaning equipment
Depreciation
Maintenance and repair
Operation (fuel, etc.)
Subtotal
Disposal (Includes labor)
Transferring and hauling
equipment
LandfilUng fees
Subtotal
Total
Bellevue, WA
$/C)eaned Percent
Mile of total
$ 9.49 4/X
1.68 8
-( In overhead)-
1.42 7
2.21 11
14.80 73
0.83 4
1.68 8
1.03 5
3.54 17
1.93 10
1.93 10
S20.00 100*
San Josfi, CA^1'
$/Cleaned Percent
Mile of total
$ 9,53 41X
5.35 23
2.32 10
-(Under disposal )-
-(Included above)-
17.20 74
0.7C 3
2.79 12
0.70 3
4.19 18
1.86 8
S23.00 100*
Alameda ,-,
County, CA1 ;
$/Cleaned Percent
Mile of total
-
$13.47 7H
0.64 3
3.52 19
4.16 22
1.35 7
$19.00 100*
RpnoL NV '
S/Cleaned Percent
«ile of total
S3.25-S5.60 13-19%
0.94- 1.58 5
0.59- I. 00 3
0.20- 0.34 1
0.20- 0.34 1
5.18- 8.76 28-30
11.12-18.80 61-64
2.00 11
(est.)
(4)
2.00 11-7
S18.00-S30.00 100*
:o,^ -,;''»
S/C 1 >•"? *r~'r>i : r'r'r C '""" S
Mile V ' • " \ I
$ 3.2<3 1«
0.22 1
1.10 5
0.20 1
0.45 2
5.26 25
13.32 65
2.00 10
(est.)
2.00 10
$21.00 100X
Sources:
1
2
3
(4)
P1tt. 1979
P1tt and Shawley, 1981
PHt and Sutherland, 1902
Alameda County reported a landfllUng fee of $8.50 per cubic yaro of street dirt to be disposed. If 0.13 cubic yards/curb
mile are removed (as reported by Reno for the core area), this would be about $1.10 per mile cleaned. For 0.48 cubic
yards/curb mile removed (Reno residential area), this would be about $4.00 per curb nlle for landfill fees.
-------
SECTION 11
EFFECTS OF STORM DRAINAGE PARTICIPATES ON RUNOFF QUALITY
The role of storm drainage particulates in urban runoff discharge and
control was investigated during this Bellevue project. As described in
Section 8, samples were periodically obtained from catchbasin sumps and storm
drainage sewerage during the course of the two-year project. An indication of
quantity and quality of storm drainage particulates was, therefore, obtained.
Increases in catchbasir. sump contents from the initial cleaning through the
project period wera used to estimate both the quantity of material that can
be accumulated in tha sumps and the best catchbasin cleaning frequency. The
data obtained were also useful in estimating the role of catchbasin and
storm drainage particulates in contributing to urban runoff pollutants end
how catchbasin cleaning or storm sewerage cleaning practices may improve
urban runoff quality.
Catchbasin sediment is mostly made up of street surface particulates
that have been removed from the street surface during rain events and were
accumulated in the sumps instead of being discharged at the outfall. Table
11-1 compares the chemical characteristics of eight different particle sizes
for the street surface samples and the catchbasin samples. The data for the
street surface samples represent the full two-year project period during both
wet and dry seasons. The catchbasin samples, however, represent fewer samples
and may be biased for the wet season. Even with possible differences in
sampling tines, it is seen that the catchbasin sediment chemical
characteristics agree well with the chemical characteristics of the street
dirt. These common chemical characteristics imply a strong association
between the catchbasin sediments and street surface particulates. Because the
average interevent time between rains in Bellevue is only five days, major
chemical changes in catchbasin sediment quality may not be as important as in
other locations having long dry periods between rains.
When the total sediment chemical characteristics are compared with th'e
total street surface chemical characteristics, differences are much more
pronounced. Table 11-2 compares relative constituent concentrations (mg
constituent/kg total solids) for street dirt, catchbasin sediment, catchbasin
supernatent, and runoff. The large differences in catchbasin sediment and
street dirt are associated with the differences in particle size
distributions. Even though the individual particle sizes have very similar
chemical characteristics, the different particle size distributions are quite
different, so that the overall mass characteristics are different, as shown
on Table 11-2.
215
-------
Tiblp II-1:. rO"r>ftn ['.r.'i <~f ^Torry r,;pr
' Hfw.ICAL O'JMITY SY PAPTICLE ',T7r
Pirtir.li> Size ("••'•-nr', )
r. jrr py 0<"J*ns
'J;1r bas in
W'-o
l'"'th
ratr.hbasl I?
7- N:
M >, ( n basin
WHR
10=30
Citchbav; ".s
TP:
Main basin
WHR
108th
catchbas ins
Lead:
Main basin
WHR
106th
cstchba^-:
t i nc :
Miin basin
WHR
108th
catchbas 1ns
COO:
street dirt
catchbaslns
7KN:
street dirt
catchbaslns
tP:
street dirt
catchbaslns
Lead:
street dirt
otchbsslns
71nc:
street dirt
catchbaslns
• 63
IPO, QOQ
n VTJO
150,000
15 //no
2900
3300
loOO
2910
830
810
690
880
1400
440
1600
1170
320
180
270
395
230,000
230,000
3500
3600
940
900
1900
2000
370
520
63-
1?5
150,000
1 90 , noo
100,000
Uu/iOO
2600
3300
1200
2070
610
630
510
690
1200
330
"MOO
870
260
140
210
320
180,000
170,000
3200
2700
740
730
1900
1600
330
390
125-
?50
100,000
150 /on
54,000
91.6^0
1700
"^00
970
1500
470
470
330
630
1100
250
HOO
620
210
100
160
195
110,000
140,000
1900
2000
550
700
1700
1300
270
290
750-
V)0
94,000
1 '- i , ' fif)
u.ooo
lOO.nrio
1300
1700
410
1600
420
520
300
610
840
180
910
560
170
80
120
200
100,000
140,000
1600
2100
440
610
noo
920
220
260
500-
1000
130,000
170/00
37,000
1-13,000
1400
1900
460
1580
480
530
380
550
680
160
570
540
160
75
130
200
210,000
240,000
2300
3000
570
830
900
910
180
300
1000-
?000
190,000
?°, 0,000
37,000
745,000
1600
7500
340
2600
690
580
620
930
420
370
240
540
170
100
130
730
240,000
280,000
2100
3400
760
1600
630
820
180
290
?ooo-
6350
170,000
300,000
55,000
777,000
1700
7400
790
2450
750
640
640
1060
240
50
130
480
110
75
100
190
270,000
250,000
7000
2300
740
1500
350
620
130
300
•fi350
780,000
380,000
70,000
?14,000
1500
1800
360
7060
740
6?0
620
760
780
80
90
200
100
85
150
160
470,000
190,000
3700
7100
750
1800
210
440
140
360
216
-------
Table 11-2. COMPARISON OF RELATIVE CONCENTRATIONS
(mg constituent/kq total solids)
Surrey Downs
runoff
catchbasin supernatant
catchbasin sediments
street dirt
COD
TKN
TP
Pb
Zn
405,000 9300
190,000 8200
250,000 1230
145,000 1600
2100 2900 1100
8400 1290 850
1690 3400 720
575 745 170
110
680
Lake Hills
runoff
catchbasin supernatant
catchbasin sediments
street dirt
J9J.OOO 9500 2600
470,000 20,000 5200
75,000 700 750
190,000 2300 640
1600 1060
1300 2000
610 210
1170 230
110
120
-------
Tahlp 11-2 can also he used to indicate the importance of different
sources to the total urban tunoff yield, Uifortunately, it is not possible to
obtain „ good particle size distribution of the urban runoff particulates
and, especially, associated chemical characteristics for each urban runoff
particle size. Th_ urban runoff relative concentrations (mg constituent/kg
total solids) for the complete runoff samples are quite different from most
or the olher samples. This, however, implies preferential washoff of the
finer particulates; the lass pollutsd larger particulates do not wash off of
the street surfaces or other potential pollutant source areas as well as the
finer partic lates (as discr'.sed in Section 9). The larger particulates are
also more effectively accumulated in catchbasin sumps or in the storm
drainage than the finer particulates.
It is clear that most of the catchbasin sediments are street surface
particulates that have been washed off the street during rain events but have
not been discharged to the outfall. Table 11-3 compares the estimated
catchbasin sediment accumulations of different urban runoff pollutants with
the street dirt accumulations and total urban runoff flow discharges. It is
interesting to note that the total urban flow unit area discharges are in the
same order of riagnitude as the total street dirt and catchbasin sediment
accumulations. The catchbasin sediment accumulation values are the rates
observed after initial cleaning, before the stable volumes were obtained. A
larger catchbasin sediment accumulation rate may be expected because of the
possible flushing effects of rains during this period of time. The catchbasin
eediment discharge values shown on this table are therefore minimum values
and could easily be greater.
Street dirt accumulation values do not totally contribute to the urban
runoff discharges. It has been shown in previous sections that not all of the
street dirt is washed off the street. Some washed off street dirt is also
accumulated in sewerage or catchbasins for indefinite periods of time. In
addition, some of the street surface particulates are lost to the air due to
fugitive dust emissions caused by winds or traffic-induced turbulence. Those
particulates settle out on adjacent areas, or the finer particulates can
remain suspended for some time. The amount of street dirt particulates that
are lost to the. air as fugitive emissions are quite small for the Bellevue
area when compared to more arid areas. The short interevent periods do not
allow the street surface particulate loadings to becom<= very large and more
exposed to the winds. The amount of material lost tn the air is calculated
based on the daposition rate minus the accumulation rate. As the interevent
period increases (to greater than four or five days, or the typical
interevent period) the amount of material lost to the air becomes important.
These losses do not become very large until after about ten to twenty days of
accumulation, which would be quite rare and would only occur several times a
year during the dry season.
If a very large storm occurred that was capable of removing "all" of the
particulates from the street surface and totally flushing the catchbasin
sediments and sewerage sediments, the resultant urban runoff discharge may be
very large. The erosion yield during a storm of this size would also be
extremely Large. Table 11-4 shows typical loadings that can occur at any one
time in the Surrey Downs and Lake Hills areas that would potentially wash off
218
-------
Table 11-3. DISCHARGES AND ACCUMULATIONS IN URBAN AREAS
Annual Discharge or Accumulation (Ib/acre/vr)
Total
Solids
Surrey Downs
storm runoff
basef low
total urban flow
street dirt (accumulation) (1)
street dirt (washoff)(2)
street dirt (fugitive losses(3)
catchbasin sed. (accumulation) (4)
Lake Hills
storm runoff
basef low
total urban flow
street dirt (accumulation) (1)
street dirt (washoff)(2)
street dirt (fugitive losses(3)
catchbasin sed. (accumulation) (4)
180
100
280
170
27
15
130
250
67
320
310
56
17
88
COD
79
10
89
22
3
2
33
100
8.7
110
60
10
3
6.6
TKN
1.6
0.53
2.1
0.2
0.04
0.02
0.16
2.4
0.18
2.6
0.7
0.14
0.04
0.06
TP
0.35
0.10
0.45
0.1
0.02
0.01
0.22
0.61
0.035
0.65
0.2
0.04
0.01
0.07
Pb
0.23
0.03
0.26
0.1
0.02
0.01
0.44
0.4
0.02
0.42
0.4
0.1
0.02
0.05
Zn
0.21
0.053
0.26
0.03
0.005
0.003
0.10
0.27
0.024
0.29
0.07
0.02
0.004
0.02
1)
11
(4)
Using average 2-5 day accumulation periods and appropriate rates
See Table S-4
Calculated based on deposition rate minus accumulation rate times
average interevent period, by month (fugitive dust loses to the air).
See Table 8-8
-------
ro
ro
O
Table 11-4 TYPICAL LOADINGS AT ANY ONE TIME, POSSIBLY AVAILABLE
FOR WASHOFF DURING MAJOR EVENTS (Ib/acre)
Surrey Downs
street dirt (5 days)
catchba:-'n sediments
sewerage sediments
average runoff event observed
maximum runoff event observed
Lake Hills
street dirt (5 days)
catchbasin sediments
sewerage sediments
average runoff event observed
maximum runoff event observed
Total
Solids
20
100
13
2.7
38
21
140
61
2.2
15
con
3
25
3
1.0
8.9
4
12
5
0.8
4.4
TKN
0.02
0.13
0.02
0.022
0.27
0.05
0.1
0.04
O.J2
0.14
TP
0.01
0.13
0.02
0.005
0.06
0.01
0.1
0.05
0.006
0.07
Lead
C.01
0.4
0.05
0.004
0.04
0.03
0 1
0.04
0.003
0.02
Zinc
0.004
0.08
0.01
0.003
0.03
0.005
0.02
0.01
0.002
0.015
-------
during a very large event. Typical loadings are shown for street dirt,
catchbasin sediment, and sewerage sediment. In addition, the maximum and
average event runoff yield loadings that were observed are shown for
comparison. The maximum runoff event that was monitored during the two-year
study period was very large and would only occur several times in a decade in
Bellevue. The maximum observed runoff event discharge is still only about ten
to twenty-five percent of the total pollutants that are residing on the
street surfaces, in the catchbasins, and in the sewerage .•» Thfijef ore, urb.in
runoff pollutants are definitely not source limited in Bellevue. Of course,
the more available finer particle sizes which are also more heavily polluted
are more limited in availability and may affect the potential storm yields
for the large events. As noted in Section 6, only about ten percent of the
total solids urban runoff discharge is expected to be associated with street
surface particulates. This value increases to about 50 percent for lead for
most storms. Section 9 estimates that only about 15 percent of the street
surface particulates may wash off the street. The average urban runoff event
in Lake Hills and Surrey Downs only discharges between two and three pounds
oi dirt per acre (2.3 and 3.4 kg/ha). The total solids street dirt loadings
were about ten times this value. About half of the total annual urban runoff
discharge may be residing on the street surfaces and tied up in catchbasin
and storm drainage sediments at any one time. If the Bellevue rain events
were capable of removing much of this material, then the urban runoff
discharge yields would be much greater than nenitored.
It is obvious that it is most important to preferentially remove the
finer, more heavily polluted and more available materials before the rain
events occur. As shown in Section 1(1, normal street cleaning equipment is not
capable of effectively removing these finer, more polluted particles. The
sediments in the catchbasins and the sewerage are mostly made up of the
larger particles that do get washed off the street. These sediments have a
much smaller median particle size than the street surface particulates.
Catchbasin or sewerage cleaning can remove large quantitieo of these more
potentially polluting particulates than the normal street cleaning
operations. Catchbasin and storm drainage sediments, however, mav not
contribute large quantities of pollutants to the total urban n off
discharge, except for very rare events. If the catchbasins are "full", they
will have little effect on the runoff yields. Catchbasin sump sediments can
be relatively conveniently removed to eliminate a major potential source of
urban runoff pollutants. Because the catchbasin sediment accumulation rate is
quite low, frequent cleaning of catchbasins would not be necessary. It is
expected that cleaning catchbasins twice a year at the most would be
sufficient.
The City of Bellevue is currently conducting a more comprehensive
city-wide sampling program of catchbasin sediments and that infonnition can
be very useful in designing a catchbasin cleaning program.
It is not possible_to currently estimate the effectiveness of catchbasin
cleaning in controlling Bellevue's urban runoff. Because of its low
frequency and because it has the ability to remove more of the potentially
polluting sediments, it is probably more cost effective than street cleaning
in improving urban runoff quality in Bellevue. Because of the varying amounts
221
-------
i 'i.il tl..it ,ire in the c.) ;. clibat, i ns at any time, certain catchbasins and
I'.i's o; M-UC r.ir.e .ire r.nch more important potential scc-.ir sourct.s than
laiH'is. II10 ilr.i ; n.ii'.e ^y^tcr, Jocated near the uny'.nt tertd sections of Westwood
l-onii's Kivid .i:-.u Ichth Street in the Surrey Downs basing were much more heavily
li'.uleu Lli.ri ^he seuer.Hic- ,tnd en t chha s ins observed elsewhere in the study
.ue.j.s. 1'i.c ront ri but ions of these local erosior, sources to the storm drainage
svsteni, and probably to the outfall, may be significantly reduced by
iiutallim: curbs and gutters.
Table 11-3 showed that catchbasin sediments that may accumulate in clean
sumps may be a significant fraction of the urban storm runoff yield. Annual,
or twice a year, cleaning may be capable of reducing these storm discharges
by ten to 23 percent Tor lead and total solids, and between five and ten
percent for the other pollutants studied (COD, TKN, TP, and Zn). Cleaning
less frequently than about once a year would reduce these expected
improvements. These removals would occur for about the first year after
cleaning, then the constant-volume values would be obtained with little
effect on the runoff yields until the next cleaning. Leaving the catchbasin
"full', however, increases the chances of increasing fhe runoff yield during
very large scouring everts. Some pollutants may also be chemically charger! by
oxidation-reduction reactions in the catchbasins, and could be connected to
more availaole, soluble, toxic forms before discharge. Therefore, it is
recommended that the storm sewer inlets be cleaned at least annually.
222
-------
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1972.
Scott, J.R., C.R. Steward, and O.J. Stober. Impacts of Urbcn Runoff on Fish
Populations in Ke]sey Creek, Washington. U.S. Environmental Protection
Agency, Corvall.is Environmental Research Lab., Contract No. R806387020,
Corvallis, Oregon, May 1982.
Solomon, ^.1,. and D.F.S. Natusch. ^'ol . Ill: Distribution and Characterisation
of Urban Dusts. Environmental Ci-^. •:": n."1 tion by Lead and Other Heavy Metals,
G.L. Rolfe and K.A. Reinbold, eds. irvsiitute for Environmental Studies,
University of Illinois, Urbana-Champ i i ,7-1, Illinois, July 1977.
Spring, R.J., R.B. H.,well, and E. S'lirlty. Dustfall Analysis for the Pavement
Storm Runoff Study (1-405 LOP An-eU^l. Office of Transportation Lab.,
California Department of Trcnsn •;:'. *' -' n, Sacrrmento, California, April 1978.
Sutherland, R., W. Alley, and F. ^ilis. Draft Users' Guide for Particulate
Transport Model,-PTM. CH2M-H::,L, Portland, Oregon, for the U.S. Geological
Survey, undated (1982?).
U.S. Environmental Protection Agency. Quality Criteria for Water. U.S.
Environmental Protection Agercy. Washington, D.C. 1976.
U.S. Soil Conservation Service. Urban Hydrology for Small Watersheds. Tech.
Releasa No. 55, U.S. Department of Agriculture, Soil Conservation Service,
Washington, D.C., 1^/j.
225
-------
Table A-l. LAKE HILLS - RAIN DATA FOR STUDY PERim
t of
Month periods
Feb/198Ql 6+
March 8
April 7
May 8
June 8
July 3
August 7
September V
October 5
November 17
December 14
Ttl 19802 90(+)
Jan/1981 10
February 7
March 8
April 14
May 10
June 13
July 3
September 10
October 9
November 13
December 19
Ttl 1981 117
Jan/1982 13
Ttl period 220
otal
(In)
3.03+
3.13
3.22
1.21
2.32
0.52
1.31
1.92
1.18
6.52
6.51
30.9(+)
2.08
3.34
2.08
2.78
2.17
2.42
1.93
0 18
4 '.71
5.96
4.59
6.32
38.56
4.65
74.11
rain per stor,n
( m)
avg min max
0.51 0.10 1.44
0.39 0.12 1.05
0.46 0.07 1.32
0.15 0.04 0.50
0.29 0.04 0.72
0.17 0.09 0.28
0.19 0.04 0.63
0.27 0.10 0.57
0.24 0.04 0.74
0.38 0.03 1.55
0.47 0.03 1.28
0.34 0.03 1.55
0.21 0.03 0.48
0.48 0.16 l.OC
0.26 0.07 0.62
0.20 0.04 0.42
0.21 0.03 0.43
0.19 O.OZ 0.43
0.64 0.04 1.25
0 13
0.47 0.03 1.20
0.66 0.07 3.69
0.35 0.03 1.58
0.33 0.03 1.21
0.33 0.02 3.69
0.36 0.04 0.96
0.34 0.02 3.69
duration per storm
(hrs)
avg min max
18.6 3.7 49.5
19.1 6.0 43.1
12.7 0.4 33.7
6.6 0.07 16.0
8.7 0.8 31.1
9.0 3.4 17.3
4.7 0.5 12.4
8.7 3.5 17.7
10.0 2.3 24.4
9.7 1.2 23.4
12.9 0.1 30.0
11. 0 0.07 49.5
9.4 1.0 32.2
19.5 8.0 38.8
12.9 4.8 26.5
8.4 0.9 31.5
6.1 0.8 16.6
5.6 0.1 21.2
6.9 1.7 10.1
12 4 12 4
9.7 1.0 32.0
11.9 1.3 35.8
10.9 0.5 30.1
11.9 0.7 30.3
10.5 0.1 38.3
8.2 2 9 27.9
10.6 0.07 49.5
preceding dry period
(hrs)
avg min max
39.5 9.0 130.4
35.9 6.0 61.4
85.9 7.7 187.5
78.4 7.1 338.9
82.7 7.7 218.8
140.1 55.0 198.8
156.7 12.5 436.4
92.5 18.8 201.3
1-14.9 6.3 230.3
32.0 5.9 116.1
39.6 5.6 136.7
34.4 5.6 436.4
55.3 10.9 209.0
71.2 7.3 315.3
93,8 2). 4 242.4
39.6 6.1 182.5
58.3 8.3 124.3
63.9 7.8 244.5
94.3 53.3 141.4
1150 8 1150 8 0 015
59.5 6.6 434.8
72.3 11.1 433.1
53.9 5.8 186.8
27.3 5.8 70.2
153.4 5.8 1150.8
45.5 7.8 114.8
117.3 5.6 1150.3
avq rain intensity
rW] nin m ,1 x
0.027 C.0?0 0.03")
0.023 0.0'":) 0.053
0.052 0.024 0.168
0.023 O.D08 0.040
0.062 0.005 0.133
0.022 0.016 0.:V6
0.064 0.006 0.142
0.038 0.014 0.089
0.020 0.012 0.030
0.042 0.015 C.091:
O.OJ6 0.008 0.07-1
0.037 0.006 0.163
0.025 0.013 0.058
0.025 0.014 0.044
0.021 0.011 O.OJ3
0.041 0.013 0.1-3
0.040 0.020 0.0-13
0.036 0.015 0.069
0.074 0.024 0.124
- - 00-1
0.054 0.010 0.150
0.045 0.013 0.103
0.033 O.C09 0.076
0.029 0.010 0.075
0.037 0.010 0.13
0.029 0.010 0.073
0.037 0.006 0.18
poi'r 70 '^i'1 ^ i ' n
4 v 9 m ' " i~.ii
0.09 0.02 O.M
0.14 o.o-i o.r:
0.14 0.04 O.n7
0.06 0.02 O.I?
0.13 0.0? rt.-'i
0.0?3 0.04 0.10
0.18 0.02 O.^T
0.13 0.04 0/M
0.08 0.0? 0.12
0.16 0.0' O.'l"'
0.14 0.04 0.30
0.12 0.02 0.53
0.07 0.02 0.16
0.16 0.06 0.36
O.C3 0.04 0.14
0.11 0.04 0.,??
0.15 0.02 0.25
0.11 0.04 0.,?3
0.20 0.06 0.34
0.24 0.02 0.50
0.13 O.OJ 0.5'
0.13 0.0: 0.3J
0.14 0.01 0.33
0.13 C.O' 0.5"1
0.10 0.02 0.13
o . ! ; o.o? o.sq
(1) partial: start 2/15/80
(2) partial year
-------
Table A-2. SURREY DOWNS - RAIN DATA FOR JTIJDY PER [00
* of
storm
Month periods
Mar/1980 11
April 10
May 6
June 7
July 4
August 6
September 7
October 5
November 13
December 13
Ttl 19801 82+
Jan/1981 10
February 5
March 8
April 11
May 11
June 10
July 3
August 1
Sep tercber 7
October 8
November 14
December 19
Ttl 1981 107
Jan/1982 11
Ttl period 200
total
rain
(In)
3.19
3.00
1.35
2.85
0.18
1.39
1.89
1.24
6.79
6.44
28.62+
2.26
3.21
1.96
2.20
1.8i
1.90
1.86
0.24
3.47
6.57
4.62
6.26
36.36
5.5
70.48
rain per storm
(In)
avg m1n max
0.29 0.04 1. 11 "
0.30 0.02 0.28
0.23 0.04 0.60
0.1] 0.08 0.72
0.12 'J.03 0.22
0.23 0.06 0.63
0.27 0.08 0.50
0.25 0.03 0.74
0.52 0.05 1.66
0.50 0.03 1.28
0.35 0.02 1.66
0.23 0.04 0.63
0.64 0.16 1.05
0.25 0.07 0.62
0.20 0.08 0.30
0.17 0.04 0.33
0.19 0.03 0.33
0.62 0.16 1.17
0.24 -
0.50 0.05 1.22
0.82 0.07 4.38
0.33 0.03 1.50
0.33 0.03 1.10
0.34 0.03 4.38
0.50 0.04 1.17
0 ->5 0.02 4.38
duration per storm
(nrs)
avg m1n max
11.5 4.3 29.1
8.9 1.2 30.8
13.5 0.7 30.3
11.2 1.7 31.4
7.6 2.2 13.5
5.7 1.5 17.2
9.4 3.3 17.5
11.7 2.3 25.1
16.4 3.2 56.5
14.8 1.1 31.4
11.1 0.7 56.5
9.5 1.5 32.2
28.3 6.3 71.8
12.3 3.4 26.5
9.9 2.3 26.2
5.4 1.8 8.9
5,4 0,6 18.3
7.3 2.6 10.2
13.4 — —
15.2 0.4 39.8
12.0 1.2 34.1
10.1 1.0 28.5
10.0 0.8 30.6
11.6 0.4 71.8
20.2 3.4 74.7
11.8 0.4 74.7
preceding dry period
(hrs)
avg min max
54.8 5.9 157. 1
60.2 5.6 189.2
98.3 9.9 372.3
8£.2 7.2 194.7
132.8 34.0 196.3
160. C 14.2 354.9
95.3 18.8 199.5
143.1 94.5 184.4
37.4 5.8 111.9
41.5 6.9 137.1
91.2 5.6 354.9
57.9 9.1 208.7
99.1 13.3 317.1
87.7 19.4 266.4
50.1 10.0 180.8
53.3 5.3 125.0
82.4 9.3 287.8
94.3 53.4 141.8
1150.1 — 1150.1
77.8 6.8 386.8
82.8 8.3 432.6
26.5 5.9 167.0
27.7 5.6 59.6
157.4 5.3 1150.1
53.6 7.8 182.0
124.1 5.3 1150.1
avg rain Intensity
( in/hr)
avg m ' n THX
0.027 0.009 0.062
0.037 0.008 0.039
0.021 0.008 0.057
0.049 0.008 0.083
0.016 0.010 0.02?
0.051 0.009 0.078
0.033 0.010 0.064
0.019 0.008 0.029
0.036 0.009 0.103
0.032 0.008 0.071
0.032 0.008 0.103
0.025 0.013 0.041
0.026 0.015 0.040
0.022 0.011 0.0:3
0.034 0.011 0.119
0.033 0.008 3.091
0.048 O.C13 0.092
0.078 0.058 0.115
g 018
0.053 0.022 0.055
0.052 0.013 o.i:a
0.037 0.009 0.089
0.036 0.007 0.062
0.039 0.007 0.128
0.023 0.008 0.058
0.035 0.007 0.128
poilf 30 mln n 1 n
intone i ty ( in/>-r }
3 v ^ TI ^ n ~ i /
0.12 0 02 O.'l
0.15 0.0?
-------
7'ir 1
LaKe Hi 11:5 ctn j Durr^y
for 1 :-eo
Total Duration Pn1n Int.
/3/eo
'/i 3
3/12
;"/''?
.' •' - 'j
"" / 2 ')
'4/5
4/3
4/14
4/13
4/28
4/29
5/20
5/22
5/24
5/26
5/27
6/1
b/1
6/5
6/6
6/16
6/24
6/25
7/4
7/11
7/14
8/2
8/17
8/26
3/27
B/28
8/30
9/1
9/6
9/12
9/13
9/19
9/20
9/29
10/8
10/12
10/24
10/31
1 1 /I
11/2
11/5
1 1/6
Rain
( in)
.19
.76
1 .05
.27
.21
. 1 2
• 52
• 92
-32
1 -32
.07
.07
• 29
.06
• 15
• 50
. 10
-6y
.06
.17
. 17
• 32
72
.06
.09
.28
.15
.09
.63
.04
.17
.26
.04
• 57
.23
.12
.16
.10
.25
-49
. 1 1
.16
-1 1
.74
• 36
• 52
• 35
1 -45
(hrs/
8.0
31 .6
43-1
16.7
20.8
6-5
28.9
21 .0
10.6
33-7
2.2
.4
33-7
2.6
5-4
16.0
6.2
7.8
-9
22.2
8.8
2-4
9-7
.8
3-4
17.3
6.4
? . 0
9-2
.5
1 .2
2.6
5-1
17.7
4.2
4.6
1 1 . T
3-5
14.0
5-5
9.1
15.7
7-3
24.4
10.9
22.3
3-7
55.8
i n / h r I i
. 02
.02
. 02
.02
.0!
.02
.02
.04
• 03
.04
.03
. 18
.01
.02
• 03
.03
.02
.09
.07
.01
. 02
. 1 3
.07
. 10
.03
.02
.02
.05
.07
.08
. 1 4
.10
.01
.03
.05
.03
.01
.0?
.02
.09
.01
.01
.02
.03
.03
.02
-09
.03
nt-;n3l ty
( in/.-.r ,
.06
• 30
. 14
.06
22
.06
.16
.22
. 1 8
.20
.04
. 14
.12
.f-4
. 08
. 12
.04
. 1 3
.10
.02
.14
.28
.22
.10
.01
.08
. 10
.04
•58
.08
.23
.22
.04
. 14
.22
.06
.04
.04
. 16
. 28
. 12
.08
. 10
.10
.14
.14
.24
.24
Hal n
(in)
. 22
.49
1.11
.24
-'9
.04
.40
• 57
. 13
1.18
.25
.03
• 31
.06
-23
.60
.1 1
.67
.72
.24
-13
.36
.65
08
.08
.22
.15
.07
• 63
.03
. I 8
.37
.06
.50
.27
.08
.14
• 09
.38
.43
.19
.12
.16
.74
.29
.60
• 33
1 -59
( h r :i 1
10.9
13. a
29.4
1C. 3
5- ''
4.6
31 .2
8.0
2.7
30.8
2.8
1 .2
30-3
7-5
20.6
16.3
S.3
7-6
14.2
31 -4
8.5
5-2
10.0
1 .7
7-8
13-5
6.8
1 .7
17-2
1 -5
2.3
4.3
6.9
17.5
4.2
3.8
13.4
3-3
15-9
7-4
10.2
14-6
6.2
25.1
13.5
24. 1
3-2
56.5
i i n / n r
.0 I
• 03
. 04
r 2
.04
.r i
.r'i
.07
''' C
.'.'4
. ~'9
. y
. j!
.01
.01
.04
.02
•09
• 05
.01
.02
.07
.07
.05
.01
.02
.02
.04
.04
-05
.08
•09
.01
.03
.Go
.02
.01
.03
.02
.06
.02
.01
.03
.0?
.02
.02
. 10
• 03
in".-'.'.'. /
l n / ' f
.>-
. i •$
:">-,
. j4
. ",''
. i 6
1-.
,- ^
. i 8
. 20
. ' **
' n
. -4
. '', 6
. : ''
r ^
.22
.20
.02
. 1 0
.20
.22
. 1 2
.04
.06
.08
.04
.50
. 12
.24
.13
.02
.03
.30
.04
.04
.04
.30
.24
. 18
. 04
. 10
. 10
. 14
. 1 2
.26
• 30
• -i' . -
- -;
i . '.'.
;-,
' . ' '
' ' '
' . .0
1 . ' J
1 . 6!
2 . '• c
i . ' 2
. _•'-
2.33
•"'4
1 . '" 0
. ^ ~J
• ''' ^
~J '
1 . 07
_ -" •>
1 . '1
.r:"'
1.11
• . oo
1.15
' . 2''
1 .00
1 . 2''
1 .CO
.50
.94
.70
.b"7
1.14
.85
; .50
1.14
1.11
66
1.14
58
1 13
1 .'.6
1 .00
1.24
. 8""
1 ~j^
. '1
-------
Tatle A-3. Haln Data for Lake Hills and Surrey 3ovn3 for 1930 (cont.)
Date
; i /g
1/14
1/17
1/1Q
1/20
1/25
1/27
1/23
1 1/30
12/2
12/3
1 2/10
12/14
12/20
12/21
12/24
.2/25
12/26
12/29
12/30
sun
average
minimum
maximum
Li!
Total
Rain
(in)
. 17
.15
• 03
. 1°
1 .55
. 16
.70
.61
.24
1 .02
.66
.06
.17
.43
.68
.73
1 .28
• 32
• 30
.83
26-94
-40
.03
1-55
'-':'.
Durat i on
(hrs)
11 -7
4-9
1 .2
2.7
23-4
2.7
13-6
17.7
14.0
14.9
31-0
7.2
5-8
11.4
31-4
30.0
17.3
5-9
! 1 -4
28.1
884-9
13-0
.4
55-8
LH Ave.
Rain Int.
(in/.ir)
.01
.03
.03
.07
.07
.06
.05
.03
.02
.07
.02
.01
.03
.04
.02
.02
.07
.05
.03
.03
2.84
.04
.01
.18
Lil Peak
30-- ;n
intensity
(in/hr)
. 12
.03
. C2
.18
.42
1 2
!26
. 18
.06
.28
. 10
.04
. 12
. 14
.14
.20
• 30
.16
.04
.12
9-94
.15
.02
-S8
CD
Total
Rain
(in)
.22
i 2
.05
.21
1 .66
• ' 5
."1
.66
. 20
• 97
• 51
.04
. 1 1
-43
.73
.77
1 .28
• 34
• 30
.84
27.06
.40
-03
1 .66
3D
D iratlor.
(hra)
12.3
9- °-
"j • 5
1 t 2
22.3
c a
17.3
21 .0
18. 1
15.2
31 -4
5-1
5-8
11 -3
24. 1
30.0
18.0
6.6
12.0
23-9
904.7
13-3
1 .2
56-5
SD Ave.
Rain Int.
(in/hr)
.02
.01
.0'
. 0~
. O'7
• 03
.04
. O"7.
.01
.06
.02
.01
. 02
.04
.03
-03
.07
.05
.03
.04
2.37
.03
.01
.10
CD Peak
intensity
( in/hr )
. 1 4
. 1.1
. , •'.
. ! 2
.-If.
. '. 0
.22
. 18
.06
.?""i
. 1 t
.02
.06
. 18
.16
.22
• 30
. 16
.06
.14
9-72
. 1 4
.02
-50
Lii/CD
> t a 1 Pain
Ratio
.-"
1 . 2 -.
'''
\ .'.^
• ':'>
.92
1 . ~>r-
1 . r -
1 . 2?
i . 50
i .55
1 . ~Sj
.93
.95
1 _ Cjfj
.94
1 .00
• 99
•73.C3
1 .07
.08
3.00
: -V ;:
L .j n '. 1 .1
Ratio
. I'7
. "6
.82
• ?'!
• 'J9
' . -* !
' . I'j
1 .<",!
* i '
.96
. ^ >
• 95
. .18
68. 1 1
1 . j''j
.06
3-93
-------
cie A-4.
Date
1 76781
•73
1/17
','13
' / 23
!/27
1/28
2/11
2/17
2/18
3/24
3/28
3/31
4/2
4/5
4/6
4/7
4/10
4/12
4/20
4/21
4/2}
4/27
4/27
5/3
5/7
5/9
5/10
5/14
5/ib
5/19
5/24
5/24
6/4
6/5
6/8
6/9
6/12
6/12
6/15
6/17
6/30
7/6
7/10
7/13
8/31
9/1
9/18
3a:n Data
LH
Ham
; i r. ;
.07
.03
.06
• 09
.48
.06
.60
1 .00
.16
• 58
.21
.14
• 32
-27
.18
• 34
.28
.42
.12
•19
.27
.08
.13
• 35
• 29
-33
.03
• 39
.18
.20
.24
-03
• 36
.03
-43
.40
.08
.28
.21
. 10
• 37
• 33
.64
.04
1 .25
.18
.12
• 45
for Lake '-ilia ^n.1 Currey ZQJT
C'aratijr. Ham I.-.-.. 7'--cl~.
Ihrs, . in/r.r; Intensity
( i n / n r /
far 1581
1 .2
1 .0
4. f^
7 . ~
14.7
2.2
17.0
23- *
8.0
18.8
6.3
9-4
11 .7
16-9
3.8
1-9
20. ~
31 -5
6.7
3- i
16.4
2.4
4.7
14.2
4.4
16.6
1 .0
6.1
4-2
7.2
6.2
.8
14-2
.8
6.2
5-8
4.0
4-2
6.7
5-7
21 .2
6.5
8.8
1 .7
10. 1
12.4
1 .0
13.3
.\jj
.03
.Of.
.04
.02
.03
.03
.01
.03
.02
.05
. 18
.01
.01
.02
.06
.02
.03
.04
.02
.07
.02
.03
.06
.04
.03
.04
.04
.03
.04
.07
.07
.02
.07
.03
.02
.02
-05
.07
.02
. 12
.01
. 12
.03
.04
.04
. 16
.02
.08
.20
.06
.36
.08
.06
.03
.28
.06
.14
.08
.14
.08
.06
.06
. 12
.22
.16
.02
.26
.22
.12
. 10
.04
.20
.04
.16
.16
.06
. 18
. 1 2
.08
.08
.28
.20
.06
• 34
.04
. 18
.26
jtai Duration r.ain Int. 70-
Sain (hrsi ( in/hr I int^r."
i i n ) -, i n /
.01
.02
.02
.04
.02
.04
.04
.03
•03
-03
.02
.03
.01
.07
. 1 2
.01
.01
.01
.02
.01
.03
.05
• 03
• 09
.03
.01
.04
• 03
.02
.04
.01
.02
.04
.05
.06
.08
.09
.05
.0?
.01
.04
.06
.06
. 1 1
.02
. 15
•03
• 05
.04
. 1 1
. 1 1
.38
-09
.63
.91
.16
• 77
.26
.18
.1 1
• 23
.16
.38
.22
-34
• 1 3
.08
. 1 1
.03
.15
• 32
.21
• 49
• 05
• 29
.05
.15
.22
.04
.31
.03
.33
• 31
.05
.23
• 33
. 1 1
.23
.25
• 53
.16
. 17
.24
.06
.45
1 -5
3-1
7-1
5-8
10.5
4-5
15-3
22.7
6.3
25-3
7-9
11.1
3-4
18.0
2-3
3-2
18.4
26.2
1 1 .8
3.6
10- 1
3-0
J-3
9-5
2.3
19-4
4.0
6.7
1 .8
8-9
6.2
4-9
18.3
.7
6.8
5-1
.6
? . c
b.6
6.5
13.3
5-7
9-1
2.6
10.2
13-4
.4
13-3
.04
.05
.04
. 1 4
.04
. 10
. 13
.06
. 4 -1
.03
.06
.04
. 12
. 12
7 o
.79
-•>!
1 .'7
•49
1.11
1 . 07
1 . 27
74
. 10
.04
.06
. Oo
.06
. 1 2
. 14
.26
.04
.20
. 06
.06
. 10
.02
.10
.04
. 14
.12
.08
. 22
.28
.04
.08
.24
.22
.16
-30
.08
. 1 2
.26
. 52
2 T^
2.45
1 .CO
1 . 20
1 .09
1 . T.p
. o'7
.60
1 -34
3-67.
1 -33
1 . 0°
-75
1.16
1 .00
1 . 70
1 .60
1 .22
.64
• 91
1 .6'
1 .^2
1 .21
.25
1 . 'I"7
.75
2. -)C
1 .00
.57
.86
1 .62
. 8'".
1 .42
1.41
1 1 1
. 36
• 25
31
2 . -*3
.31
1 .00
.'5
.79
1 - 7
. il
1.14
u . ^ "
1 . ' 3
1 , ~:2
. 38
1.16
1 . ! 4
. .>-'
• 65
. JQ
j->
2 . -;o
I .00
-------
Pable A-4- Rain Data for Lake Hills and Surrey Downs for 1981 (cont.)
ro
CO
Date
9/ ' 9
9/20
9/25
9/26
9/23
10/1
10/5
1 0/7
10/3
10/27
1 0/28
10/29
10/30
11/11
1 1/13
11/14
11/14
11/16
11/19
1 1/20
1 1/20
1 1/22
11/23
11/30
12/1
12/3
12/4
12/5
12/6
12/9
12/13
12/17
12/18
12/21
12/23
12/24
12/26
12/27
12/28
12/30
sum
average
minimum
maximum
LH
Total
Rain
(in)
.10
t .05
1 .06
1 .43
-42
.76
3-59
.10
.27
.73
. ! 1
.16
.07
1 .56
• 1 4
.05
.45
• 53
.18
-03
.83
.35
.21
.09
.57
.16
1 .21
.22
-05
.84
• 30
.21
• 69
.09
.26
.07
.40
.07
.10
.06
33.23
.38
.03
3.69
LH
Duration
(hrs)
1 .8
32.0
9-1
40.0
11.7
3.5
35-8
6.0
9-5
27.2
1 -3
10.8
2.8
20.7
9-0
.5
32.4
18.0
17.7
1 .8
30.1
5 3
4.8
10.5
16.6
14.1
21 .8
15-5
2.7
30.3
8.9
15.2
19-3
1 .2
1 1 .0
1 .7
23-5
6.7
8.0
2.4
964.1
11 .0
• 5
40.0
LH Ave.
Rain Int.
{ in/hr)
.06
.03
. 12
.04
.04
.09
. 10
.02
.0'
.03
.08
.01
.03
.08
.02
.10
.01
-03
.01
.02
.03
.07
-04
.01
.03
.01
.0^
.01
.02
.03
.03
.01
.04
.08
.02
.Ot
.02
.01
.01
• 03
3-49
-04
.01
.18
LH Peak
30-Ein
intensi ty
(in/hr)
. 1 4
.26
.64
-50
.24
.36
• 52
.10
.16
.14
.10
.10
.06
• 38
.10
.10
.14
.16
.06
.02
.20
.14
.22
• 04
• 30
.08
• 38
.06
.06
.20
.16
.06
.20
.10
.10
.12
.26
.04
.08
.04
13-36
.15
.02
.64
3D
Total
Rain
(in)
.05
.68
. 53
1 . ?2
.43
. 81
4-36
. 14
.24
.74
.10
. J7
-09
1 .50
. 1 i
.10
.36
-51
.20
-03
.86
-49
. 18
.14
.55
.19
1 .10
.17
.05
.78
.36
.29
.79
.08
.27
.09
.45
.06
.04
• 03
31 .56
.36
.03
4.38
3D
Durat ion
(hrs)
: .7
31 -4
1C. 6
33-3
3 - '
'1.7
34.1
5-4
9.7
27.5
1 .2
5-2
3-2
20.2
8.3
2.6
25-4
16.2
16.4
1 .4
28.5
5-5
4.3
16.2
18.6
13-3
17.6
9-6
5-2
30.6
6.1
15-2
19-5
.8
8.6
1 .7
22.2
1 .2
5-3
4.5
923-0
10.5
.4
39-8
S: Ave.
Rain Int.
(i-i/hr)
. "
""'
^
0"
.0
-03
.08
.01
.03
.07
.01
.04
.01
03
.01
.02
.03
.09
.04
.01
.03
.01
.06
.02
.01
.03
.06
.02
.04
.10
.03
.05
.02
.05
.01
.01
3-41
-04
.01
-15
3D Peak
30 -i in
intensi ty
( in/hr)
.04
. ^2
. y-'
. .; ~j
. 4'~
.64
. 1 4
. 10
. 14
.10
.04
.06
.26
.03
1C
. 12
. 1 4
.03
.04
.26
. ?2
. 1 3
. 10
. 24
.12
. 28
.06
.06
.16
.13
.08
. 14
.12
.12
.12
• 34
.06
.04
.04
12.42
. 14
.0?
.64
LH/::,
Rain
Ratio
2 . '. 0
' - ~ ',
' ^ '
*", ~
• ?4
.r;4
1 • ' 3
. ' H ^
1 . '0
? ^'~-t
- 7*3
1 . Cq
1 . 2-"
• '~<'j
1 . ?c
1 -C4
- ~i~j
1 . or,
1 .02
. 7'
1.17
.64
1 . Gi
.34
1 . 1 r.
1 .29
1 .CO
1 .08
• 83
.72
.87
1 .13
• 96
• 78
• 39
1-17
2.50
2.00
102.72
1 -17
-25
3-60
LH / Z u
D 'j r 3 * i o r.
F.a". 10
i
. -u.
• . ; j
1 . '. c
i i -
''3
1 '. -;
2 . '^
Op
1 . '. ?
1 . C2
1 ' 3
' . 3
1 . ^ ' '
1 . ". 6
.Of
r c
. i~.
• CO
1 .' 6
1 . T4
1.61
-52
. ° 'J
1 .46
1 .00
.T3
1 -50
1 .25
1 .00
1 .06
5-53
1 .51
• 53
105.23
1 .20
. 1 ^
6.67
Z Z - L '• '.
Z ' '\ r t
T I.i7 *?
• -
- . " ;-
-. -
. ' ',
i . * n
-1 7
-. ' 1
_ . ' ^
- , '• ^
•~ '<-,
-2 . -"'
Cj
r r
• '-'.'
-j ;j 7
~*
, ' -,
- . " •'"•
-.42
-• "'
-. "_3
- 50
. 1 7
. '" <"'
4 i -7
7 ~
-4. . '^
-. C9
-.75
-.17
-• 37
. V,
3.50
-1 .08
-.33
-.42
-3-17
-! . 17
-28.14
-. *'
-5-16
5-43
-------
Table A-5 • R^in Data for Lake Hills and Surrey Dcr.nj for 10-2
Date
1/10/32
t/15
1/17
1/22
1/25
1/25
1/27
1/27
1/30
sum
average
minimum
maximum
LH
j. 0 ~t Q.1
Rain
( in)
^ c
• 98
.18
1-32
. 12
• 96
.06
.04
• 87
4-88
• 54
• 04
1-32
in
i/ur&tiGfi
(hrs)
24.8
27-9
12.3
35-1
5-3
17-8
2.9
4.2
72.8
203-6
22.6
2.9
72.8
LH Ave.
n£i in i n t .
(in/hrj
.01
.04
.01
.04
.02
• 05
.02
.01
.01
.22
.02
.01
-05
'*(-• «, i n
, w — in i n
intensity
( in/hr )
.12
.14
.10
.18
.06
.12
.04
.02
.12
• 92
. 10
.02
.18
3D
Rain
(i
1 .
1 .
1 .
1 .
5.
1 .
n)
30
10
16
17
13
01
07
04
15
13
57
04
17
-'
( iira
2.1.
OQ
8.
35-
5-
17.
5.
74.
203.
22.
3-
71-
:
c
7
8
7
2
3
8
4
7
6
6
4
7
' in/hr j
.01
.04
.02
• 03
• 03
.06
.01
.01
.02
.22
.02
.01
.06
Inter. Ji ty
; in/hr ''
.1 2
. !6
. i 0
.22
. 10
. 1 4
.04
.02
.34
1 .24
. 14
. ( ^
.- 4
.76
1.17
-------
Table A-b
-------
ro
Co
Runoff
Start
Date
9/20
9/29
10/3
10/12
1G/2C
10/24
10/31
11/1
11/3
11/5
11/6
11/9
1 1/H
1 1/<7
11/19
11/20
11/25
1 1/27
1 1/28
I 1/29
12/1
12/2
12/3
U/10
12/11
12/14
12/20
12/21
12/24
12/25
12/26
12/29
12/30
Sum
Average
Minimum
Maximum
Total
Rain
( Inches)
.38
.43
.19
.12
.03
.16
.74
.29
.60
.33
1 .59
.22
. 12
.05
.21
1 .66
-15
.71
.66
.22
.05
-97
.51
.04
-03
.1 1
-43
.73
.77
1 .28
.34
.30
.84
28.61
-35
.03
1 .66
Rain
Duration
(hrs)
15-9
7.4
10.2
14.6
2.3
6.2
25-1
13.5
?4.1
3 . 2
5o.5
12.8
9-8
5.5
3-2
22.3
5-8
17.8
21 .0
18. 1
7-7
15-2
31 .4
5.1
1 . 1
5.8
11 -3
24-1
30.0
18.0
6.6
12.0
23-9
969-8
11 .8
. 7
56.5
Average
Rain Int.
(in/hr)
.03
.06
.02
.01
.01
• 03
.03
.02
.03
. 1 0
• 03
.02
.01
.01
.07
.07
• 03
.04
.03
.01
.01
.06
.02
.01
.03
.02
.04
• 03
.03
.07
.05
.03
.04
2.71
.03
.01
.10
Peak 30
Min Int.
Total
Discharge
(in/hr)(cubic feet)
.30
.24
.18
.04
.04
.10
.10
.14
. 1 2
. '6
.33
. 14
.04
.04
. 12
.46
.10
.22
.18
.06
.04
.20
.14
.02
.04
.06
.18
.16
.22
• 30
.16
.06
.14
1 1 .02
.13
.02
.50
20300
23700
1C200
4280
1390
7760
43500
20700
41 SCO
20400
1 26000
17200
5330
2510
14200
1 30000
8730
55100
60000
27900
4920
90900
61200
120
515
5050
25100
60400
72000
1 35000
43900
26500
99600
2082642
25398
120
135000
Total
Discharge
(inches }
.06
.C7
.03
.01
.03
.C2
• 1 5
.06
.13
.06
• 3"
.05
.02
.01
.04
.40
.03
.17
.18
.09
.02
.23
.19
.00
.00
.02
.08
. 19
.22
• 42
.14
.08
•31
6.41
.08
.00
.42
Runoff
Duration
(hours)
15-4
6.7
10.4
6.9
1 -9
5.3
24.5
13-3
22. 1
5-4
55-9
12.1
5.2
3-4
5-4
27.8
5-4
17.8
27.2
22.6
7-5
20.7
35- a
.2
-9
6.2
7.8
25.4
35-8
24.1
12.6
15-5
29-8
1 ,021 .3
12.5
.2
55-9
Peak
Di?charge
(c: j)
4.40
~*. . 70
3.44
. 62
.51
1 -53
1 -73
1 .Tr4
2.75
4.40
5-34
2.?7
1 .26
• 37
3.02
7. 17
1 -73
3-16
3-30
1.13
.74
4.40
2.49
.13
.22
.87
2.49
3-02
2.60
5.14
3-30
1 .02
2.88
178.12
2.17
.07
7.17
Runoff
Coefficient
(H\/-rnt io )
. ' 6
. 17
'?
i *
i ^
.15
.20
.22
.21
. 13
.24
.24
. '4
• . 5
.21
.24
. \-^
. :-3
. 3 1
. i^
.2-3
1 *7
.•;i
.05
. 1 4
. i ?
. ,/ 5
• 29
. ^2
.40
-27
• 37
15-18
.19
.01
.64
Runoff/Pain
Duration
( ratio }
r-,^
. "-• 1
i " ")
• t
f ^ ~
• ?'4
. ~'^
. c.
'..'•'"•>
';"?
' , ^
- r
- r
1 J
c
-""
1 . tl?
I . '4
.C4
.52
1 -C"
. O
1 .0^
1.19
1 .34
1 .3!
1 -29
1 -25
87. 13
1 . •>;
.C4
4.91
-------
Table A-btx.
Surrey Downs Runoff Uondltlor.s for 1961
no
OJ
en
Runoff
Gtart
Date (
1/6/81
1/8
1/17
Via
1 /20
1/2;
i /:?
1/27
1/28
2/11
2/13
2/17
2/18
2/24
3/3
3/5
3/15
3/21
3/22
3/23
3/24
3/28
3/31
4/2
4/5
4/6
4/7
4/10
4/12
4/20
4/22
4/23
4/27
4/28
5/3
5/7
5/7
5/9
5/10
5/14
5/18
5/19
5/24
5/24
5/25
6/4
6/5
6/8
6/9
6/10
6/12
6/12
Total
Rain
Inchea J
.05
.04
. 1 1
. 11
.27
.42
• 38
.09
.63
.9'
1 .05
.16
.73
.36
.62
.10
.28
.04
.03
• 34
.26
.18
.11
.23
.16
.38
.22
.34
.13
.08
.11
.08
.15
• 32
.21
.16
• 33
.05
.29
.05
.15
.22
.04
.17
.14
.03
• 33
• 31
.05
.03
-23
• 33
Rain Average Peak 30
Duration Rain Int. fin Int.
(hrs) (
' .5
3-1
7.3
5.8
9-6
32.3
1C. 6
4.5
15-4
22-8
70.0
6.4
25-2
15-7
25-8
4.8
25-5
HA
IU
12.1
7-9
12.0
3-4
17-7
2-3
3-2
18-3
26.2
11.8
3-6
10.0
3-0
3-3
9-4
2.3
6.2
5-7
4-2
6.7
2.0
8.8
6.3
5-0
7-7
5-0
.7
6.7
5-1
.6
1.3
2-5
6.6
Total
"isehar^e Dig
Total Runoff Peax
.:har>/e Duration Diecv!«~ff<3 ~jefi
! i n / h r ) (in/hrJ( cubic feet) ' i n c h e 3 )
.03
.01
.02
.02
.03
.01
.04
.02
.04
.04
.02
.03
.03
.02
.02
.02
.01
NA
!IA
.03
.03
.02
-03
.01
.07
.12
.01
.01
.01
.02
.01
.03
.05
.03
.09
.03
.06
.01
.04
.03
.02
.04
.01
.02
.03
.04
.05
.06
.08
.02
.09
.05
.02
.04
.08
.04
. 10
.12
. 14
.04
.10
. 18
.16
.06
.42
. 10
. 10
.08
.08
NA
MA
.14
.08
.06
.04
.12
.12
• 32
.06
.12
.10
.04
.06
.06
.06
.12
.14
.14
.26
.04
.20
.06
.06
.10
.02
.10
.10
NA
.14
.12
.08
.04
.22
.28
1060
1110
4030
6340
16600
35900
29700
5640
56300
63800
1 4 1 000
1 8000
84000
34300
383CO
8310
23300
;IA
NA
18800
14600
7400
4200
5700
5250
15700
4310
9080
3680
1260
2010
1600
5490
19800
9690
5550
19600
1290
20500
1240
5370
11800
100
7330
7870
378
17600
17500
1930
640
10600
16500
.00
.00
.01
.02
-05
. 1 1
-09
.02
.17
.20
.44
.06
.26
. 1 1
.12
.03
.07
t!A
MA
.CC
.05
.02
.01
.02
.02
.05
.01
.03
.01
.00
.01
.00
.02
.06
-03
.02
.06
.00
.06
.00
.02
.04
.00
.02
.02
.00
.05
.05
.01
.00
.03
.05
fhrs)
1 .4
1 .2
6.6
6.0
9-3
33.2
14.2
4.2
20.7
26.2
72. 1
12.3
31 -3
22.8
19-3
4.5
25.8
"A
MA
11 -7
7.7
10.3
2.5
7.8
2.4
2.3
18.7
17.8
6.4
2.4
3-2
1.5
3-5
10.0
3-2
5-7
4.2
1 .2
5-6
2.2
4.2
5.3
.1
4.3
4.5
.5
6.9
5.6
1 .1
.6
2.8
7.8
(Cf3) ?.V-
11
-51
. 8"
.87
1 -67
2.27
2.60
.80
1 .73
2.74
3-30
1 .83
6 54
1 .63
2 • '. 5
1 .94
2.16
!!A
I:A
1 .94
2.16
1 .02
.80
2. 2^
1 .26
3-44
.42
1 .44
1.10
.51
-51
.62
.80
2.16
1 -94
1.83
4-40
• 51
3-89
.42
.80
1 .53
• 33
1 -53
1 -53
.29
2.16
' -83
1.26
• 33
2.74
4.06
hu, - :'. jtunc
rte:er.- I
-ratio '
.•--
. C1^
. ' 1
. IP,
. 1°
.26
.24
- 19
. 2*i
.22
.41
- V5
'5f.
.29
-'9
.26
.26
"A
MA
. 17
.17
.13
.12
. 08
.10
.13
.06
.08
.0°
.05
.06
.Cb
.11
.19
.14
11
.18
.08
.22
.08
. 1 1
.17
.01
.13
.17
.04
.16
.17
.12
.07
* 4
.15
, f f ' ? t : -i
' .-•>• ;-,
. "-2
• ?"'
rtr
1 . C4
1 .02
1 .C3
i .75
. ^
I 35
1 . 15
' .03
1 .92
1 . 24
1 .46
-75
MC]
• .01
*;A
:;A
.-'6
.38
. 66
.75
. 44
1 .05
. 8^!
1 .02
.63
• 54
.66
• 72
• 5'
1 .05
1 . C6
1 .39
-93
-74
• 20
-83
1 .10
.48
.84
.02
• 36
• 90
.72
1 .02
! .10
1 .8^
. 46
1.12
1 . 18
-------
Table A-6bJcont.) Currey Downs Runoff Conditions
ro
oo
01
o r I 98 1
-C4
6.0
Y / *;
7/U
7/1 ;
3/31
9/18
o/t ~>
9/2V
9/25
")/-'.
9/23
10/1
10/5
10/7
10/8
10/27
10/28
10/29
10/30
1/11
1/13
1/13
1/17
1/'9
11/20
1 1/20
1 1/20
1 1/22
1 1/22
1 1/23
1 1/30
12/1
12/3
12/3
12/4
12/5
12/6
12/9
12/13
12/15
12/17
1 2/18
12/18
12/21
12/24
12/24
12/26
12/27
12/28
Gua
Average
Minimum
Max imum
. 1 6
1.17
.24
.Ct,
-45
.05
. 65
c o
( , 22
.43
.81
4.38
.14
.24
.74
.10
-07
.09
1.50
. 1 1
.10
.51
.13
.07
.03
.86
.03
.49
. 18
.14
• 55
.03
.16
1.10
.17
.05
.78
• 36
.62
.15
.14
•79
.08
.27
.09
.45
.06
.04
35-36
• 34
.03
4.38
C
i r
13-
i''
1 .
30.
10.
39-
9.
9-
33-
5-
Q .
27
1 .
5-
3 -
20
e
2
1 6
6
1
1
28
1
5
4
15
16
7
17
9
5
31
6
13
5
3
19
8
1
22
1
5
1 ,069
10
70
2
a
c
4
]
IT
7
4
6
4
2
4
2
-*
5
6
5
5
0
4
7
j
5
7
6
3
8
0
7
4
0
2
1
2
9
8
3
.8
7
7
5
.2
0
. 1
5
.4
.0
^ i
. 'ji.
.^^
. 1
/-,
.C
• * ^
.05
.06
.13
-03
.03
.03
.08
.01
.03
.07
.01
.0.*
-°3
.02
.07
.02
-03
.02
.09
.04
.01
.03
.04
.02
.06
.02
.01
.03
.06
•05
•03
.04
.04
. 10
• 03
.05
.02
-05
.01
3-91
.04
.01
• 15
. >'J8
.24
.22
i f'
• ' 2
. ",'\
~> ;:>
.26
.40
.4"j
.64
. 14
. 1C
. 1 4
.10
.04
.06
.26
.08
. 1 C
. 14
.06
.08
.C4
.26
.04
.22
. 18
.10
.24
. 0 i
. 12
.28
.06
.06
.16
.18
.28
.06
.08
. 14
. 1 2
.12
.12
.34
.06
.04
13-88
. 1 4
.02
.64
G
10
yi
1 1
12
52
16
1 i
28
->
2
4
27
Q
4
20
6
2
2
'4
~j
1 1
1 1
1 )
21
1
q
26
18
1 1
38
7
1 0
7
,T
24
1
7
4
2 3
3
2
1 , 158
1 I
72
2
c
D
9
p
p
9
-7
9
2
1
7
r;
1
4
-',
4
7
9
i
0
6
1
4
2
4
2
4
3
6
v
7
2
3
2
6
1
8
8
3
5
8
4
2
5
3
7
3
3
8
4
1
1
-r
7
V
7
£
C
1 2
2
2
1
1
4
1
2
^
7
3
1
4
1
5
i
2
2
c:
1
3
•
7
220
2
12
e>;
30
7 o
40
74
'•4
JO
'" 0
^4
-'. "i
" ',
c 6
C2
-. »
' •*
, ',
3;-
1 8
°4
7-'
c°
•16
j ,1
r; ?
44
•1 0
H
9J
34
10
87
60
68
1 4
' 7
18
1 (.•
69
7 ?
•J4
.67
«2
16
2q
CO
.51
-------
Table A-6c.
Surrey Downs Hunoff Conditions for 1
Runoff
Start
Date
1/10/82
1/13
1/15
1/17
1/22
1/25
1/25
1/27
1/27
1/30
2/1
ro
OJ
~j Sum
Average
Minimum
Maximum
Total
Rain
( Inches;
• 30
.05
1.10
.16
1.17
.13
1 .01
.07
.04
.72
-43
5.18
.47
.04
1.17
Rain
Duration
(hrs)
25.0
6.3
28.9
8.9
35-5
5-2
17-4
5.8
3-3
42.4
25-3
204-0
13.5
3-3
42.4
Average Peak 30 Total
lin Int. Kin Int. Discharge Discharge
(in/hr) (in/hr )( cubic feet) ''
.01
.01
.04
.02
• 03
• 03
.06
.01
.01
.02
.02
• 25
.02
.01
.06
. 12
.02
.16
. 10
.22
.10
• H
.04
.02
• 34
.06
1-32
. 1 2
.02
• 34
17800
2700
Q0800
1 3800
91000
11600
96200
1 1400
61 10
56800
49700
449910
-50901
2700
98200
'otal
ar^e
he s )
.05
.01
.28
.04
.28
.04
• 30
-04
.02
.18
.15
1.39
-13
.01
-30
Runoff
Duration
Cr.rs)
21 .2
c .6
34.3
10.7
41 .7
11.2
24.3
1 1 .8
8.6
46.3
31.2
247.4
22.5
5.6
46.8
Vc>
1 .
_^ .
1 .
3.
1 .
3.
4
1
21
1
4
•s)
.73
29
,02
.44
. 16
.63
.72
.62
• 33
.40
.26
.60
• 96
• 29
.40
(Rv-rat : ~j .
.18
. 17
.25
. 2"
.21
. . 2B
• 30
.50
.47
.24
.36
3-26
.30
. 1 7
.50
1 .4;
-------
iiil.5 Runoff Jcr.d 1t Lor:j f:r 1 Slr-0
rxj
Go
OO
Hunrjf?
J t 'j. r t.
»* 'JL j *i ^ J
/i5/2~
2/17
2 / ' 9
2/25
7 / V
, ;
3/10
' ' ' 2
3/19
3/26
3/29
4/5
4/5
4/8
4/11
4/18
4/20
4/29
5/20
5/21
5/22
3/24
5/25
5/26
5/27
6/1
6/1
6/5
6/8
6/16
6/23,
6/24
6/25
7/4
7/11
7/14
8/2
8/17
b/26
8/27
b/28
0/30
8/31
9/1
9/6
9/12
9/13
9/19
9/20
7';Vdl
L \\r .IP 3 i
1 . 44
. i" }
.76
1.05
.27
.21
.12
.07
.45
• 92
.32
1 -35
.07
.07
. 10
•19
.06
• ' ~j
.07
• 50
. 1C
.69
.06
-17
- 17
.12
.04
72
.08
.09
.28
.15
.09
.63
.04
.17
.26
.04
.08
.57
.23
. 12
.16
.10
.25
-'a.n A
i r -i . i j n . ./i x
6.0
31 -4
9.7
4Q . 7
12.9
7. ^
35.6
43-8
16.9
21 .0
6.7
2.3
16.8
20.9
10.7
34.1
2.2
.4
9. :
4.8
2.6
5.4
8.8
16.1
6.3
7.8
• 9
21 .3
8.9
2.2
8.0
9-9
.8
3-5
17.5
6-5
2.0
9-3
• 5
1 .2
2.6
5-0
13-3
17.8
4.2
4.6
.11.4
3-4
13.9
.-j-ir-ien ?•;
' n / •- r ' i
» n / . . i t i i
.02
r 2
.03
.02
.02
02
.02
.01
.02
.0}
.02
.04
.03
.04
.03
. 17
.01
.04
.^2
.03
.01
.03
.02
.09
.07
.01
.02
.15
.01
.07
.10
.03
.02
.02
.05
.07
.08
. 1 4
. 10
.01
.01
.03
.06
.03
.01
• 03
.02
IK: TO
[-,/->, t i c U I
• * 4
. I 2
. 14
.06
-30
.14
.06
.22
.06
.06
. 16
.22
. ' H
.20
.04
. 14
.04
. ' 2
.04
.08
.02
. 12
.04
.18
.10
.02
- 14
. 2y
.02
.22
.10
.04
.08
. 1C
.04
.58
.08
.28
.22
.04
.02
.14
.22
.06
.04
.04
. 16
ToVil
£ L i"* ? 'f* & r • ' i
735CO
31^:0
1 4 1 OC 0
91 20
6950'"
! 4 1000
25600
15300
^;°
37 ='-'0
91 000
173'.C
; 33000
15^0
1660
1 900
1 uljO
035
5850
1240
38100
4070
54900
26 JO
6920
91^0
21000
2700
52400
3630
1570
9870
6090
2770
54400
1210
14300
15900
2100
2?20
56900
14800
3710
4810
3200
17300
™ ri'.'\ \
_ r o
.41
. 1 4
.03
.20
.41
.07
.04
.01
. ;i
. 1 1
.27
.05
30
00
.TO
.01
.03
.00
. 02
.00
. 1 1
.01
. 16
.01
.02
.03
.06
.01
. 15
.01
.00
.03
.02
.01
. 6
.CO
.04
.05
.01
.01
. 16
.04
.01
.01
.01
.05
f -, o j f j
3''.
i i .
5.
24
44 .
1"?.
4.
T
2 .
20.
27.
1 1 .
36 .
i
f! .
4 .
1 .
c
S .
15.
3
9.
23.
4.
3.
!Q.
1 .
1
1 2 .
7.
2.
P.
1
2.
3-
6.
19.
1,
3
9.
2
13
f
p
T
4
7
-i
J
•' ' j
1
i
4
1
^
0
-
~>
•'
3
fi
7
9
3
6
1
f
2
0
0
c
.7
1
.3
8
.2
.3
• 9
-^
.0
.6
0
. 1
.4
.7
?":
c
6 .
0
'
5.
7 .
7 _
2.
4 .
2 .
l .
c •
2 .
^ .
c, .
2.
t .
1
19.
7
5
5
6
h
'"•
4 '
-',
V"7
,; ",
"•4
5 T
-2
6!
72
72
7.7
68
-; T
1 •">
» :
, " S
24
ij ;
.6'
57
-'. ?
T?
17
. 22
. 10
7"
8"
S7
.05
• 54
.65
50
.65
.47
.40
. 10
. PO
. 47
.07
. '">2
.41
.57
•52
_
. ,2
. ' 4
. '•.'.
1 ~i
*'^
. 2 '
,1
'' '•
. : s
. c '
. . i
. ."
,o
i "
• i
2''
. .: '
. 1 "*
. 1 2
1 rj
1 9
' ";
. 2
. 1 7
. ' 0
1 2
.00
. 75
:Q
. 24
. I VJ
. 15
. I i
. 29
. 1 1
. '" ')
. ' "i
)
20
-------
Table A-7a.Lake Hills Runoff Conditions for 1980 (cont.)
Runoff
Start
Date
9/29
I 0/8
10/12
10/24
10/31
11/1
11/3
11/5
1 1 /6
1 1/7
1 1/3
1 1 /P
1/14
1/17
1/19
1/20
1/23
1/25
1/27
1/28
11/30
11/30
12/2
12/3
12/4
12/10
12/14
2/20
12/21
12/22
12/24
12/25
12/26
12/29
12/30
sum
average
min ifflum
maxiaum
Total
Rain
(inches)
.49
. 1 t
. 16
. 17
.74
• 3o
.52
• 35
.77
.43
.24
. 1 7
.15
.03
.19
1 -55
.06
.16
.70
.61
.08
.14
1 .02
.43
.23
.06
.17
-43
.60
.08
.73
1 .28
.32
• 30
• 83
30.10
• 36
.03
1.55
Rain Average Peak 30
Duration Rain Int. Kin Int.
(hrs)
5.
Q.
16.
7-
24.
10.
22
3-
12.
19.
3.
1 1 .
4.
t .
2.
23-
1 .
2.
13.
17.
2.
6.
15-
18.
4 .
7.
5-
1 1 .
l
c
11'.
27.
966.
11 .
.
49-
5
2
0
4
7
6
6
7
4
5
^
3
8
2
7
1
4
7
7
9
1
4
0
7
8
5
9
3
5
i
5
7
8
5
4
7
( ln/hr)
.09
.01
.01
.02
.03
.03
.02
. 10
.06
.02
• 03
02
'03
.03
.07
.07
.04
.06
.05
.03
.04
.02
.07
.02
.05
.01
.03
.04
.04
.01
.02
.07
.05
.03
.03
3-32
.04
.01
.17
Total Total
Discharge Discharge
(in/hr)(cublc feet)
.23
. 1 2
.03
. 10
. 1C
. 1 4
. 14
.24
.22
.20
.24
.12
.03
.02
. 18
.42
. 10
.12
.26
.13
.06
.04
.23
.18
.06
.04
.12
. 14
.14
.06
.20
• 30
.16
.04
.12
11 .28
.13
.02
-58
4.1800
2590
",7=0
8140
C82CC
38700
393CO
1 06000
5y800
27000
15200
9710
730
17400
223000
4400
12600
86400
77600
9410
16200
1 53000
73200
15400
2490
14500
37200
70700
1450
84500
210000
53000
31400
129000
3064825
36406
730
223000
( inches)
.1'
. o i
.02
.02
. 17
. 1 1
. 14
. i :
.31
. 17
.03
.04
.03
.00
.05
.64
.01
.04
.25
.22
• 03
.05
.46
.21
.04
.01
.04
. t 1
.20
.00
.24
.61
.15
.09
• 37
8.86
. 1 1
.00
.64
Piroff P«jax:
Duration Discharge Co
( hours )
6. 1
6.8
15.0
6. 5
23-5
ll.i
17.1
4.3
14.4
20.3
9.8
12.2
3-4
.8
3.4
30.3
1 .2
2.7
17-2
22.8
4.0
3.2
19-4
24.2
10.3
6.3
6.4
11.5
n.6
2.2
33-1
23.0
11 .9
12.8
33.2
961 .5
1 1 .7
.6
53-8
Runoff Runoff/?alT
; f ' i f. 1 ". n t Z u - \ •.!•-, n
(cfs ) (r!v-rat lo) ( rat io )
9
t
2
tr
4
1 1
1 1
6
6
3
1
3
1 r
4
2
< "5
6
l
1
10
5
•3
J
"*•
3
5
5
12
7
1
4
340
4
19
1 9
51
1 2
^
f":
11
56
.20
40
.67
82
.07
.73
.41
.35
. 20
. 56
. 37
.20
.22
.62
.22
.60
. 16
. 17
.33
.07
-96
.92
.29
.92
.80
. 12
.40
• 92
.40
.05
. 10
.50
"' <-" ' ' *
. " ^ "' '.
• ' 2 '*•
' '.
" ' • • =
. 1 1 l.i?
? 6 .76
. ; 2 i.'"
,40 ' . '6
. 4 ", ' '. ':
• 3 3 ' ' :'
.26 ' ' '
. ' j . """,
. 0 7 ". 7
• 26 :
. 4 1- ; :
. ' -'6
. ; ' i . oo
. '. i . 25
. '„' ' 1.2"
T < 1 -, -r
'•29'
.15 l . 2r>
.4:- • . ;•?
• 1 ~! 2.7 '•.
• 1 2 34
.25 t .0-4
. 2 5 '.02
.34 1 . C4
.05 .22
.31 t ."•
.4" !.'<
.45 2 . t 1
. 7r 1.1:
.45 1 .20
18.35 86.::
.22 1 .'.7
.02 . :o
.49 2 . 40
-------
Table A-7K Lake Hills r'un-jf;' Conditions f-j
Runoff
T^.al Pair. Av.'ra^e Peak 30 7ot"aL
'•In ' n P,T I r ct •• • r% n "• *i • n ^ " *• - Mln 7 1 • l"j 1 <> i" 'r *1 r .7 i> H - ^
" _' ' , ^
1/6/51 .07
1/3 .03
1/17 .06
1/18 .09
1/22 .11
1/23 -49
1/26 .16
1/27
1/28
2/11
2/13
2/13
2/15
2/1 V
2/18
3/24
3/29
'4/2
4/2
4/4
4/5
4/5
4/6
4/7
4/10
4/12
4/20
4/21
4/23
4/27
4/28
5/3
5/7
5/11
5/14
5/14
5/18
5/19
5/24
5/24
6/3
6/4
6/5
6/7
6/8
6/9
6/12
6/12
6/15
6/17
6/19
.06
.60
1 .00
.24
.53
.47
.16
-58
.21
.14
-32
.07
.20
.06
. 18
.04
.34
.28
.42
.12
.19
.27
.08
.18
.35
.29
.33
-39
.18
.08
.20
.24
.03
.36
.06
.03
.43
.07
.40
.08
.28
.21
.10
• 37
.02
' r. -, • '
1 .2
1 .0
4.6
6.9
B-5
14.=
5.3
2.
2
17.1
22 .
/
9-6
37-9
22.4
8,
18.
6.
q.
1 1 .
3.
6
1
3
1
20
32
6
3
16
2
4
14
4
16
6
4
7
5
14
4
6
4
5
f.
4
6
5
21
.0
.7
.4
•J
.9
.3
.9
.7
.8
.9
.9
.0
• 3
.7
. 1
-9
.4
.7
.0
.4
.5
. 1
.2
• 3
. 1
• 5
.8
.4
t
• J
.8
.2
.7
.7
.0
.2
.8
.6
.8
.1
i n / h r ; i' i
.06
.03
ioi
.01
• 33
.r.-*
.04
.04
.03
.0'
.02
.02
.03
.03
.02
.03
.02
-03
.04
.05
-04
.13
.01
.01
.02
.06
.02
.03
.04
.03
.07
.02
.06
.04
.12
.03
.04
.04
.03
.01
.04
.07
.02
.07
.02
.07
.03
.02
.02
.20
/« v ' ri-l-
.ce
. ~ 4
.04
.04
.04
. 1 6
.02
.08
.20
.08
.14
.20
.06
• 36
.03
.06
.08
.06
.22
.04
.12
.04
.28
.06
.14
.08
.14
.08
.06
.06
. 12
.22
.16
.26
.22
.16
. 12
. 10
.04
.20
.04
.04
. 16
.08
.16
.06
.18
.12
.08
.08
.04
, „ p Jt, ,. ) / ;
2?CO
310
2" 20
644"
'••'. 0 j
53300
1 1 COO
32rO
75.00
= 0200
1 9900
'.8400
' 1 000
1 0600
46300
1 3000
4700
22300
1940
i 4 TOO
2770
12500
2180
36900
'6300
31400
7340
S3 50
17600
2880
6960
23300
13900
17700
24700
12500
4680
9530
14100
530
20500
1210
260
27700
2050
29100
4190
16200
1 1000
2540
12500
212
To*. <} -
n ^ h c. -j )
.01
.r.O
.01
. 02
r- 1
.01
.22
.26
.06
.17
.15
.03
.13
.04
.01
.06
.01
.04
.01
.04
.01
. 1 1
.05
-09
.02
.02
.05
.01
.02
.07
.04
.05
.07
.04
.01
.03
.04
.00
.Z6
.00
.00
.08
.01
.08
.01
.05
.01
.01
.04
.TO
j r '-i * '. -
\ r 'j - ' T
5-
2.
1 a,.
26.
10.
41 .
26.
7.
' 1 -
7.
3 .
12.
'
6.
^
}.
TT
21 .
31 .
7.
3 .
10.
2.
4.
9-
5-
13.
4.
1 .
"5.
5-
14.
1 .
(,'.
\ .
5.
4.
3.
6.
'->.
20.
n I/ L
\
e
7
i
?
'.
rf
o
6
•<
^
8
o
5
":
8
c
J
1
1
5
i
7
2
5
9
1
3
7
5
9
5
5
8
1
5
4
7
2
2
I
6
9
8
7
3
,._;:
i .
2.
v .
i
4 .
7 .
1 .
').
1 .
6.
y
"7 _
3 ,
2.
2.
2.
1 .
2.
2.
4 .
5.
V
5.
2,
2.
5.
3'
1 .
3
3
3
2
1
S-*
;>
•'C
£6
':-1
. "-i
' 6
; ^
. ?^
i }
7 •'•
. v^
,o2
f- '
. "*,*7
5?
T7
. ' £
1 3
-y)
.72
.02
1s.
.02
>r4
.80
.78
.73
. ;H
,6'j
57
.53
.34
.10
.24
.40
• 92
.22
.84
.40
.61
. 28
.R4
.97
.70
."U
.(2
.'4
. 17
.05
. 16
.06
.35
. n
.08
.2!
.'5
. 17
.15
.07
10
-------
ible A-7h.,cont.)
Ink* till la
.'".4
Runoff Condltlona for 1981
•'1 1
9/20
0 / 2 o
;/27
J/29
9/28
10/1
10/5
10/8
10/27
10/28
10/29
1 " '30
1 1 /3
I/tl
11/13
1/14
11/14
1/15
1/17
1/19
1/20
1/20
1/22
1/23
1/30
12/1
12/1
12/3
12/4
12/5
12/9
12/9
12/13
12/14
12/17
12/18
2/21
12/24
12/24
12/26
12/27
12/28
12/30
sum
verage
Inimua
ax i mum
.'•A
1 . 25
.45
. 10
1 .05
1 .06
. 14
1 . 20
. 14
.42
. 76
3-69
.27
• 73
.1 1
.16
.07
.10
1 .58
. 14
-05
• 31
.14
• 53
. !8
.03
.88
• 35
.21
.09
.0'
.57
.16
1 .21
.22
-03
.84
• 30
• 96
.21
.69
.09
.26
.07
.40
.07
.10
.06
36.05
.34
.02
3-69
K C
8.M
1 . "?
1 \. 1
12.0
1 . 0
i .0
71 -8
i. 1
14. )
8 . •
4.2
11.7
8.5
35-3
9-6
27.0
1-3
10.7
2.8
6.3
20.8
8.8
.S
15.5
2.3
18.3
18.0
1 .8
30.3
5-3
4.8
10.0
1 .2
13.4
14-5
21.6
15-7
.1
30.0
8.8
23.4
15-0
19.2
1.2
10.8
'.7
23.5
7.0
8.3
2.4
1 .048.2
10.0
.1
37.9
.02
.02
. i 2
.04
.06
.03
.01
.15
.03
.04
•'9
.10
.03
. r 3
.09
.02
.03
.02
.08
.02
. 10
.02
.06
.03
.01
.02
.03
.07
.04
.01
.03
.03
.01
.06
.01
.04
.03
.03
.04
.01
.04
.08
.02
.04
.02
.01
.01
.03
4-56
.04
.01
.32
. 2
'.2
. 1
64
. 04
-50
.03
.24
• 36
.52
. 16
.14
. 10
.10
.06
. ~ '
.""3
. 10
.10
.10
. 1 4
. 16
.06
.02
.20
.14
.22
.04
.04
• 30
.08
• 30
.06
.04
.20
.16
• 32
.06
.20
.10
.10
.12
.26
.08
.0;
.08
14-96
.U
.02
.64
4 -'•lOO
•37 ; .0
1 1 5000
5 5 - 0
1 2 1 000
17400
4 ' 000
84 600
490000
4 d' 6 0 .,
52"00
351 0
10200
3060
4 '30
1 39000
1 1 400
3930
28800
1 3 : 00
6C93C
1 1300
760
122000
47400
29600
2170
1440
62900
12400
174000
34700
1190
1 1 5000
29700
1 37000
21800
1 1 1 000
8670
23400
7810
43400
5330
9 ! 60
1080
3525930
33580
90
490000
. '4
. i
r l
. 06
.02
• 35
.04
. 1 2
.24
1 .42
.12
.15
.02
. j3
.01
.01
.55
r. ~x
. j '
.08
.04
. 18
.04
.00
.35
.14
• 09
.01
.00
.18
.04
.50
.10
.00
• 34
.09
.40
.06
•32
.03
.07
.02
.13
.02
.03
.00
10.19
.10
.00
1 .42
i - fL
28.7
1 4. 3
17.0
'5.6
7.2
15.2
14.7
28. 1
19 2
23 4
2.2
11.1
3-5
6. 1
70.7
10.0
1 .5
16.4
5-2
21 .4
'7.6
1 .5
42.0
II .2
10.8
4-3
1 .0
23-2
14.5
23.0
.MA
-9
36.0
10.1
28.8
18.6
24.9
6.4
8.8
4.3
18. 1
7-3
7.6
2.4
1 ,095-4
10.7
. •*,
42.0
i ?
1 .40
20 . 'f.
. rj3
15.00
2.51
6 '3 ."'
1 5 . 60
1 Q . 00
5.40
4 - 03
2.51
.30
2. '0
13-20
2.71
2.5j
3.50
T.3j
4 . V.
1.16
. 1 8
7.27
q . 40
9-53
.65
.80
11 . 60
2.69
13.40
2.26
.70
6.G/
4.^8
10.40
1.16
7-57
2.78
2.97
3.61
6.97
.70
2.02
.20
430.76
4. 10
- 12
20.00
' '•/:
, • !
. ^';
. ','--
. ',' 3
. T;j
. ;^
. 16
. 2 1
.22
. ' =
• ] 3
1 T
• 35
.23
, ^
• 37
.21
.07
i'l
. '-j
. ;'
. 0'.'
. 14
-32
. 2^
.42
.46
.1 1
.40
.29
.41
• j *
.47
.28
.26
.32
.31
.22
.26
.05
22.01
.2'
- ^1
.4 .
i
i . * ^
,
i
' "0
4
^ -
. "3
i . 4 -;
1 . ' -!
"' . 00
' . 06
2. ;7
1 . 17
. j=j
. ---
1 . '/•*
2 • ' 1
2 . ; 6
_ 47
. --..^
1 . ?b
. ':3
1 .06
?!A
1 .29
1 . ^0
1 . '4
1 .23
i . 24
1 . 70
5-33
2.8:
. ~"7
. .04
.91
1 .CO
127.7!
1.2!
->£
5- 77
-------
Table A-7c.
Lake Hills Runoff Conditions for 1982
Runoff
Start
Total Sain Average Peak 3C
Rair Duration Rain Int. Mn Int.
Date (inches)
1/10/92
1/15
1/17
1/22
1/23
1/25
1/25
1/27
1/27
1 /TO
1/30
2/1
sun
average
minimum
maximum
• 35
• 98
.18
-58
.74
.12
-96
.06
.04
.06
.14
.73
4-94
.41
.04
• 98
(nrs)
25-
28.
1 2.
13-
10.
5-
17.
2.
4.
6.
5-
40.
171 .
14.
2.
40.
0
0
9
5
1
2
8
9
0
0
6
6
5
3
9
6
(in/hr) (
.01
.04
.01
.04
.07
.02
• 05
.02
.01
.01
-03
.02
-34
• 03
.01
.07
Tc^al Total
Discharge Discharge '.
in/hr ) (cubic feet) (
. 12
. 14
.10
. 12
. 18
.08
. 1 2
.04
.02
.06
.12
.06
1.16
. 10
.02
.18
25500
106000
20600
64300
1 20000
1 4400
162000
10900
7040
3490
16200
93800
644230
53686
3490
162000
incr. «3 ;
.07
• 31
.06
.19
.35
.04
.47
.03
.02
.01
.05
.27
1 .86
. 16
.01
.47
-u^'j/^; -i,- ,,^a!^
' no jr.! ' of 3 -
2 I
33.
1 1 .
19
16.
i 0 .
23
8.
9.
•"
7
44
21 2
17.
5
44
.7
. 2
.8
.0
. 1
.9
"7
.9
.7
.5
.9
. 4
.3
.7
, s
.4
2
4.
2.
4
e.
2
q
1
4.
1
37.
'3.
b .
. ^
. 0-1
. 'i7
.20
• 97
. 78
• 5 3
. i"o
. 41
• 'j7
~? ^1
• ^6
.7-7
. 1 2
. 41
•97
'7
-------
Table A-8. Lake Hills Dry Weather Wichout Street Cleaning (LHD)
no
-P»
Co
Storm
number
6
8
9
10
1 1
15
16
18
19
21
22
25
26
28+29
30
31
32
114
116
117
118
119
120
Total
Average
Minimum
Maximum
Month
4/14/80
4/18
5/21
5/24
5/27
6/5
6/8
6/24
6/25
7/11
7/14
8/26
8/27
9/1
9/6
9/12
9/13
7/6/81
7/13
8/31
9/1
9/19
9/20
Flow
(cu ft)
8650
132000
11000
5850
4070
6920
9170
52400
3630
9870
6090
1210
30200
56900
14800
3710
4810
48800
126000
19500
3870
7380
87100
653930
28432
1210
132000
Runoff Concentrations (mg/1)
Rain
(in)
Total
Sol.
TKII
COD
Total
Phos .
Lead
Zinc
pH
Spec. Turb.
Ccr.d. (ntu)
( umhos )
1
1
1
8
1
.15
• 33
.19
.15
.10
.18
.17
.72
.08
.28
.15
.04
• 43
.57
• 23
.12
.16
.64
.25
.12
.12
.10
.05
• 33
• 36
.04
.33
87
81
119
87
92
59
195
95
114
85
137
84
190
54
60
24
156
89
79
114
177
274
122
2574
112
24
274
2
1
1
1
1
3
1
1
1
5
2
2
1
33
1
5
.10
• 53
-51
.77
-25
.66
.46
.40
.06
• 8V
.84
• 58
.68
.25
• 98
.67
.56
.04
• 23
.94
.46
• 58
.26
.68
.46
.25
.94
67
13
48
16
31
26
87
41
57
49
43
85
75
30
47
32
39
52
37
100
95
118
54
1241
54
13
118
-27
.19
• 37
.02
.12
.10
.49
.28
.26
.26
-17
• 57
3-61
.08
.27
.15
.10
• 34
.27
.19
• 50
.71
.24
9-55
.42
.02
-3-61
-53
.10
• 38
.15
.12
.12
.56
.19
-38
.23
.20
• 39
• 53
.05
.26
.05
.05
.10
.10
.20
.40
.40
.20
5.69
.25
.05
.56
.12
.08
.14
.1 1
-07
.10
.17
.10
.14
.11
.10
.29
.21
.03
• 13
.1 1
.12
.11
-13
.19
.24
.21
.11
3.17
.14
.07
.29
MA
NA
6.3
6-5
6.0
NA
5.7
5-8
6.2
5-9
5-7
5-3
6.4
6.2
6.0
6.1
6.2
6.3
6.3
6.3
6.4
6.1
6.6
122.3
6.1
5-3
6.6
NA
NA
NA
49
26
NA
22
42
26
51
32
142
31
22
24
34
54
36
37
46
45
43
37
799
42
22
142
it t\
:IA
20
8
13
NA
35
19
15
9
7
26
?9
1 1
16
9
9
8
9
6
16
28
12
305
15
6
35
-------
Table A-9. Lake
, lean in..?
otors
number
•3 »
~ c
c ^
89
90
91
92
93
94
95
96
97
101
102
103
104
105
106
107
108
109
1 10
1 12
113
Total
Average
K iniffium
Maximum
Date
9/2C/8C
3/24/S!
3/23
1/5
4/6
4/7
4/10
0/12
4/20
4/21
4/^3
4/27
5/11
5/14
5/14
5/18
5/24
6/5
6/8
6/9
6/12
6/'2
6/17
6/30
?low
(cu ft)
17300
1 3000
4700
12500
36900
If 300
26000
7340
8350
17600
2880
30300
25400
12500
4680
23700
20500
27700
29'00
4190
16200
1 1000
125GC
21900
402540
16773
2880
36900
Rain
( in i
• 25
.21
.14
. 18
-34
.28
• 36
. 12
• 19
.27
.08
-53
.43
.18
.08
-44
• 36
• 43
.40
.08
.28
.21
• 37
• 33
6.54
.27
.08
• 53
Total
Col .
1 99
71
66
87
135
42
1 17
157
78
76
43
80
23^
161
194
59
97
1 17
73
184
103
108
27
206
2719
1 13
27
239
1
1 .
1 ,
1
i
1
1
1
1
t
4
26
1
4
1 Y * I
71
c<3
7^
73
.'5
.25
.59
.02
.04
.53
.70
. 18
• 90
.46
.60
.62
.64
• 96
.01
.74
• 90
.04
• 50
.00
• 83
. 1 2
.25
.00
•;:;
ir
t- !-/
32
3Q
42
42
27
32
29
50
^6
38
35
67
62
70
27
49
45
36
20
34
76
22
122
1053
44
20
122
T j 1 .'i 1
Fhcj.
.34
.16
. 1 2
.28
.4r<
. 1 5
.23
• 51
.21
. 16
. 12
.25
.26
. 22
'.Yl
. 13
• i ?
• 54
.25
. 10
.28
. 18
. 1 1
1 .18
6.94
.28
. 10
1 .18
I-r; id
-39
. 10
. 10
i n
. 2 "
r ^
• j j
. 10
10
.20
. 10
. 10
.20
. 10
. 30
.30
1 l~*
.20
.20
. 10
. 10
. 20
.20
- . *J
•50
4-14
. 17
• 05
• 50
Z i r, o
i ^
. r °
. 1 C1
1 f~
1 ~*
^ r-
r,cA
. ' 2
1 r.
. 06
.r T
^ "7
. 12
1 ^
. 1 4
1 i
1 s_
13
.OT
15
1 ;
. 10
.07
.26
2.77
. 1 2
.06
.25
j_ ' •
5 . -,
f . 2
*-'' . 5
5 • ^
5-5
6 . '
7.0
*"/ • T
^ -]
5 -2
c , 9
5-4
6 . 4
6 • ^
b.4
- , ^
XA
6 , !
6 - i
6 .4
c; q
6 . 1
i.c.
5-4
139.6
6. 1
S.7
7.0
-------
Table A-10. Lake Hills Wet Weather Without Street -leaning (LI:'./"
Stor3 Month
number
50
51
54
55
56
57
56
59
61
62
127
1 29
150
131
132
133
134
135+136
137
140
141
148
149
150
151
152
153
154
155
156
158
159
Iital
Average
Minimum
Maximum
11/27/SO
1 1/23
12/4
12/14
12/20
12/21
12/24
12/24
12/26
12/29
10/8/81
10/28
10/29
10/30
11/11
11/13
11/17
1 1/20
11/30
12/3
12/4
12/9
12/13
12/14
12/17
12/18
12/21
12/23
12/28
1/10/82
1/15
1/17
Flow
(cu ft)
864CC
103200
13900
14500
37200
70700
23700
57500
53000
158000
42600
12500
5640
3060
189000
1 1400
60900
199000
3610
12400
209000
111000
29700
132000
21800
111000
8670
23400
0160
25500
106000
20600
1966040
61439
3060
209000
Rain
(in)
.70
• S3
.23
.17
-43
.60
. 26
.44
• 32
1.11
.27
.20
.07
.07
1.58
.14
• 53
1 -44
.12
.16
'1-43
.84
• 30
• 96
.21
.69
.09
.26
.10
.35
.98
.18
16.06
.50
.07
1.58
Runoff
otal T
Sol.
83
f,6
62
152
109
113
120 1 .
93
68
60
81
47
64
88
53
50
33
46
34
119 1 •
108
95
61
62
45
51
51
33
58 1.
227 1 .
78
82
2492 20.
78
33
227 1 .
Concent
x;i
90
25
78
70
70
76
12
70
59
53
25
61
78
90
73
64
28
38
50
32
92
42
25
50
31
48
48
31
37
37
48
67
98
66
25
37
rations
CCC
23
2?
27
77
36
33
45
55
23
22
29
23
29
36
33
41
22
30
29
38
'30
20
26
21
17
19
24
20
39
77
25
33
1031
32
17
77
'-.a/I }
Total
Fhos.
.15
• 13
. 12
• 31
.24
.21
.22
.14
.12
.10
.10
.13
.18
.15
.21
. 16
.12
.12
.12
.12
:i3
.09
.15
.1 1
.07
.08
.08
.07
.12
-34
.1 1
.12
4.62
.14
.07
• 34
.10
-05
.10
• 30
.20
.10
.20
. 10
.10
.10
.10
.05
.20
.05
.10
.10
.10
.05
-05
.10
.10
.05
.10
.10
.10
.10
.10
.05
.05
.40
.10
.10
3.60
.11
.05
.40
Zinc
.16
.07
.08
.22
.10
-14
. 14
. 1 1
•13
• 15
.05
.08
.08
• 13
.07
.09
.08
.07
.15
.08
• 05
• 03
.07
.05
.06
.09
.03
.04
.08
• 15
.08
.06
3-00
-09
.03
.22
5-9
5-9
5.17
6.1
5-5
5-6
7. 1
7.0
6.0
7. 1
HA
6.7
7.0
6.6
7.1
6.8
6-9
7.0
6.9
6.7
6.8
6.7
6.8
6-9
6.7
6.3
6.9
7.1
6.7
6.8
7-0
204.7
6.6
5-5
7.1
Cond .
f ur.hoa )
27
29
2-7
2'
31
44
76
53
:;A
22
32
30
42
34
4Q
45
85
46
42
25
48
55
35
34
23
70
69
31
43
1235
40
22
85
Turb .
I n t u )
13
• 5
i 9
33
14
3
1 A
3
7
q
1 4
1 2
9
13
6
6
10
7
7
7
9
e
12
32
14
15
526
16
6
82
-------
Table A-11. Lake .--.:11?
37
38
^ o
- >
40 + 4 I
42
43
45
46
47
48
49
63
66
67
69
70+71
72
73+74
76
77+78
Total
Average
M in imum
Maximum
1C/U/80
10/12
10/24
1C/31
11/1
51/3
1 1/8
11/14
11/19
1 1 /20
11/23
1/17/81
1/23
1/26
1/28
2/1 1
2/13
2/13
?/17
2/18
2590
6730
•1 1 4 :
582CO
337CO
47500
422CO
9710
17400
223000
17100
8460
53000
1 1000
75000
90200
1 9900
1 1 3200
10600
51080
903760
45188
2590
223000
. i 1
. 1 o
i ~
.74
.'.6
-52
-41
-15
-19
1-55
.22
.15
-48
.16
.60
1 .00
.24
1 .01
.16
.58
8-96
-45
. 1 1
1 -55
163
2^
1 33
1C6
188
85
68
125
.',42
92
72
142
161
81
69
QO
66
218
74
;IA
2412
127
27
442
"T Zi ~
1 . ' 2
.^e
1 .46
.62
.67
-73
1 .38
1 .04
-95
70
• 95
-25
-25
.ij4
-25
1 .26
.73
1 .40
20.45
1 .02
.25
3.80
•-T ;j
22
30
41
63
35
•7 ;T
S3
V3
32
22
45
57
24
i ^
43
27
33
31
56
860
43
13
83
.20
. 33
.21
.30
. 16
. 14
. 17
.0-2
.29
.52
.51
.28
,27
.0''.
.22
. 13
.45
.15
• 34
5-°3
.7.0
.03
• 92
. 23
-2?
. 1 3
• 31
. 10
. 1C
- 15
•25
1C
• 15
. 20
;c
r;C
• - J
. 10
. U
. 10
-30
• 15
-29
3-64
. 18
-05
-31
. ' 6
. 1 3
.13
i o
-23
.07
. l '
1 6
f ~j
. i 1
1 h
. 1C
.O"7
• >5
. C"7
. C 6
. 1 2
. ~ 7
. 12
2.25
. 1 t
-05
.23
5-6
5 -7
-------
T«
9-.;.-=
1
21
22
23
25
26
27
25
3C
31
32
33
34
35
81
82
83
84
85
86
88
89
90
91
92
93
94
95
97
98
99
100
101
104
105
106
107
108
109
1 10
1 12
113
114
115
1 16
117
'19
120
121
122
Total
Average
M inimum
Maximum
itii A-IZ.
la-.i
3/12/30
7/ ' l
"VI 4
a/ 17
3/26
8/27
8/23
9 ' 1
9/6
9/12
9/13
9/19
9/20
9/29
3/3/81
3/5
3/15
3/23
3/24
3/28
4/2
4/5
4/6
4/7
4/10
4/12
4/20
4/22
4/27
5/3
5/7
5/7
5/10
5/19
5/24
6/5
0/8
6/9
6/12
6/12
6/17
6/30
7/6
7/10
7/13
8/31
9/18
9/20
9/25
9/26
5UT--V 0
1 3800C
3550
IC700
DI50
31 sec
2670
3450
25600
31 4CC
1 1 9CC
1970
5020
2870
203CO
23700
383CO
8310
23300
18800
14 600
7400
5^00
5250
15700
4310
8070
3680
1260
2010
25300
9690
5550
19600
20500
11800
16500
17300
17500
2160
10600
17100
8880
11500
26400
6230
69800
6340
18800
38200
33900
103000
950420
18636
1260
103000
•-•ir.j D- 7 V
, -n
1 .27
- 1 }
. 22
• 1 5
-63
.C8
. 1 °
-37
• 50
.27
.03
H
-09
.38
.43
.62
.10
.28
• 34
.26
.18
.23
.16
• 38
.22
.30
.13
.08
.1 1
-47
.21
.16
• 33
.29
.22
.31
• 33
-31
.05
.23
• 33
.23
.25
• 53
.16
1.17
.24
.50
.68
• 50
1.65
17.56
.34
.05
1.65
^ i ~ -, ^ r » '
(ur
Col .
142
127
624
106
266
1 44
58
90
-72
90
82
163
115
64
83
92
82
76
62
1 °1
58
147
49
67
117
MA
128
72
104
136
188
87
69
75
140
87
NA
131
285
31
324
113
149
78
198
336
136
116
158
6613
135
31
624
10:":" Jrn^e
1 .26
1 -29
.25
2.91
3-42
1 .90
.84
.63
1.23
.25
1 .02
.90
1 .43
• 92
.57
.84
1 .06
.78
.67
.25
1 .71
1 .01
1.15
.25
.70
1 .06
1IA
.73
.31
1.46
1.46
1.54
.84
.90
.76
1.57
.76
NA
1.01
2,10
.67
4.26
1.15
1.76
.84
3.10
3-92
1.29
1 .06
1 .18
62.13
1 .27
< . 5
4.26
n -. r -i : ; o n a
'5^
37
1 52
129
1 02
TT
29
47
24
43
56
76
42
27
33
82
^4
72
37
100
d5
45
21
27
46
ilA
46
33
95
82
61
40
79
45
66
52
NA
51
98
30
149
59
10?
82
131
58
57
50
3006
61
21
152
3«t/ 1 .'
?hoa .
.77
• 29
. i 5
.84
.95
1.17
.09
.12
.31
.1 '
.12
. 21
.36
. 18
. 14
.16
.22
.16
.22
. 12
• 51
.17
• 55
.07
.20
.26
*IA
.15
.19
.29
.31
• 36
.20
-19
.20
.30
.20
NA
.27
.61
.17
1 -19
.24
.28
.17
.68
.89
.20
.22
-32
15.76
.32
.07
1 .19
-.»*
. 21
. ' 0
.62
-51
.49
.20
.05
.22
.05
.05
.10
.2*;
.13
.10
.10
.10
.10
. 1C
.05
.20
.10
.20
.05
. 10
.20
'^A
.10
.20
.10
.20
.20
.10
.10
.10
.20
.10
ilA
. 10
.40
.10
.40
.10
.20
.10
.20
• 50
.20
.10
.20
9-02
.18
< . 1
.82
line
' n
. 1 2
• 77
• 30
.22
. 1 !
.C1
• 29
.09
.15
.10
.16
. i '
.03
.09
.12
-09
.10
.09
.15
.10
. 1 4
.C3
.07
.10
MA
.08
.08
.15
.17
. 1 ~
.09
.1 1
.12
.17
.10
NA
.12
.23
.09
.26
.14
.17
.12
.26
.28
.1;
.15
.12
7.04
. 14
.07
• 37
?'H
6 . 7
•5.0
6.2
7 , 4
6 . ^
6.6
6.3
6.0
6.8
6.6
5.5
5-3
6. 1
5-3
5-5
6.2
6.1
6.2
6.5
6.6
6.2
5-5
5-9
6. 1
6.1
5-9
5-3
5-2
6.3
6.1
5-9
6.1
6.1
HA
6. 1
5.8
6.5
6-3
6.6
6.5
5-2
6.2
6.3
6.4
6.5
5-9
6.4
6.2
6.8
'-£95 - 6
' 6.2
5-2
7.4
Corvl .
35
32
''2
70
2";
42
69
54
29
27
42
34
23
56
25
33
69
tiA
26
39
35
25
25
31
t!A
38
16
46
23
30
25
60
32
38
30
69
47
42
29
27
1738
38
16
95
12
6
31
5
1 4
19
12
19
26
27
20
17
9
6
13
24
20
36
11
28
'2
20
6
22
31
8
4
1 1
796
16
4
41
-------
Table A-13- Surrey Downs Dry Weather V/ith Street Cleaninr
Runoff Concentrations
•'r .-/I)
Storm
number
3
4+5
7
8
Total
Average
M inimurn
Maximum
Date
4/5/80
4/8
4/14
4/18
Flow
(cu ft)
22600
48900
8590
78800
158890
39723
8590
78800
Rain
(
1
2
1
in)
.43
.79
.18
. 18
.58
• 65
.18
. 18
Total
Go lid 3
1 1 2
132
196
43
483
121
43
196
1
2
4
1
2
m r/M
-Lf.lt
.06
.60
.74
• 50
.90
o '/
- c- J
• 50
• 74
CO
r
>
'£
u~
>
1
1 S
D
0
9
4
5
8
T o t a
Phon
. 2
.2
C.
. 1
1 1
1
-
^
4
o
r
'^
P
40 . 2rJ
1
5
r
j
4
. 1
. r.
0
9
-------
Table A-14. Surrey Downs Wet Weather Without Street Cleaning
Runoff Concentrations !a;
Storm
number
37
38
39
40
4-2
43
44
45
46
47
48
49
50
51
52
53
55
56
58
59
60
61
62
63
64
65
69
70
72 to 78
79
155
156
158
159
Total
Average
Minimun
Maximum
Eate
10/8/80
10/12
10/24
10/31
11/1
11/3
11/6
11/8
11/14
11/19
11/20
11/25
11/27
11/28
12/2
12/3
12/14
12/20
12/24
12/24
12/25
12/26
12/29
1/17/81
1/20
1/21
1/28
2/11
2/13
2/24
12/28
1/10/82
1/15
1/17
Flow
(cu ft)
102CC
4230
7760
48500
20700
41600
87500
36000
5330
14200
134000
8730
55100
87900
88000
51200
5050
25100
16600
50500
135000
49900
127000
10400
16600
35900
59100
63800
249600
34300
2460
17800
90800
13800
1704710
50139
2460
249600
Rain
(in)
• 19
. 12
.16
.74
• 29
.60
1.18
-43
.12
.21
1 .66
.15
.71
.86
• 97
.46
. 1 1
-43
.26
• 51
1 .28
-34
1.14
.22
.27
.42
.63
.91
2.20
.36
.04
.30
1 .10
.16
19-53
.57
.04
2.20
Total
Solids
174
52
140
57
100
95
93
64
250
73
60
29
49
C1.
J ,'
68
71
100
95
98
60
76
83
91
125
98
91
68
80
125
75
46
274
102
127
3242
95
29
274
TK'i
1 .96
MA
1 .06
.64
1 .09
.78
.62
.62
1 .40
1-23
1.12
.87
.56
1 .26
.73
• C5
.87
.70
.88
.25
.70
.64
• 5^
1 .01
.25
.78
.25
.64
-98
.64
NA
1-93
.73
.74
26.74
.84
<-5
1.96
rr-p
39
26
102
51
46
32
51
35
50
41
30
31
29
34
42
26
69
58
62
20
27
20
19
47
52
4fa
20
52
47
38
NA
110
38
33
1425
43
19
110
Tote":
F'".3:i .
-f.f.
• ^ ' j
• 17
.24
.15
. 18
.'6
.08
.14
• 23
.17
.15
.26
.1 1
.10
.17
.08
.24
.18
.16
.oq
• 13
.21
.09
• 37
.07
.02
.00
.16
.20
.17
NA
• 38
.17
.09
5-49
.17
.00
-38
lea^
.25
.07
.15
• 09
. 14
.06
.10
.10
.20
.10
.10
.10
.05
.10
.10
.10
.20
.10
.10
.20
.05
• 05
-05
.20
.10
. 10
.10
.10
.16
.10
NA
.40
.10
.10
4-02
.12
<. 1
.40
Zir.c
. ir-
.08
. 15
. 10
. 10
.07
. 13
.13
.31
.12
.17
. 1 1
.08
.08
.15
.08
.14
.12
.21
.09
. 1 1
-23
-09
.15
. 10
.07
.05
.10
.09
.09
MA
.20
.10
.08
4- 08
.12
.05
.31
pH
NA
6. 1
C.5
6.5
5-7
6.3
;FA
6.2
6.0
5-9
5-8
5-9
5-8
6.6
6.2
6.8
6.2
6.4
5-9
7.0
7-0
7.0
NA
6.4
6.4
6.1
6.0
6.1
6.1
6.2
7-0
6.7
6.8
6.9
196.5
6.3
5-7
7.0
r. ce~ .
C\r,i .
( UC-KC3 ,
48
6l
-U
2?
?6
27
4"1
37
46
26
30
2b
31
46
15
50
*1
21
37
43
52
62
59
57
27
33
32
29
64
41
52
102
1 1 1
73
1559
46
23
i 1 1
Turb .
3',
7
22
12
' 2
1C
' ~I.
1 1
1=!
1 6
16
i 3
7
"
\ 7
(-,
-i "I
2\
2r.
6
3
5
q
2C>
23
17
10
17
15
17
10
67
1 Q
7
531
16
c;
67
-------
Table A-15- Surrey Downs Wet Weather
Cleaning (C3CW;
Runoff Concentrations
Stori
n um b e r
123
1 24+1 25
126
1 27
1 23
1 29
131
132
133
137
138+139
ro 1 40
en i 41
0 148
1 49
150
151
152
153
154
Total
Average
Minimum
Maximum
Date
10/1/81
10/5
10/7
10/8
10/27
10/28
10/30
11/11
11/13
1 1 /30
12/1
12/3
12/4
12/9
12/13
12/14
12/17
12/19
12/21
12/23
Flow
(cu ft)
52100
401000
13300
19200 '
39500
9170
4230
Q8900
6030
7360
37130
13500
1 1 6000
72800
22400
81 100
22400
83100
3980
17100
1 125300
56265
3980
401000
H.ui n
fin)
. 81
4.38
. 14
.24
.74
. 17
.09
1 .50
. 1 1
. H
-55
.19
1 .27
.78
.36
.87
.29
.79
.08
.27
13.77
-69
.08
4-38
Total
Ccli.ls
95
144
116
88
72
75
Q3
76
69
1 10
83
140
1 10
1 14
79
97
133
64
194
73
2030
102
64
194
™Y.~.',
77;
1 .02
.90
• 56
.61
.62
1 .80
.64
.76
1 -32
.76
.66
.64
.48
.62
.62
-59
.48
• 95
.56
15.32
.77
.48
1 .80
COD
28
34
24
30
36
29
27
33
44
69
36
48
17
23
35
35
27
21
53
33
687
34
17
69
Total
Phos.
. 15
.23
.08
.10
. 16
.15
.28
.17
. 1 6
.27
. 13
.13
. 1 2
.09
. 14
.15
.13
.08
.20
.12
3.08
. 15
.08
.28
Le~.d
. 10
. 17
. 10
. 10
.05
.10
.05
. 10
. 10
. 20
19
. 10
. 10
.05
. 10
. 10
. 1C
. 10
.20
.05
2. 16
. 1 1
-05
.20
" inc
08
. 1C
.07
.07
• 09
• 1 3
.'5
.08
. 16
. : 4
. 1 2
. 1 0
.03
. 06
. 10
.08
. 1 1
. 08
. 14
.0"?
2.00
. 10
.06
. 16
6
6
7
7
6
6
7
6
T
7
6
6
6
6
6
7
6
•-I
f.
1 30
6
6
7
o!:
. "j
. 'j
3
r^
. !
, r.
. "5
. D
. 2
.0
• o
.8
;.A
. Q
. 3
p
.0
. Q
.6
•?
.5
. q
7
• J
.3
47
44
-------
Table A-16. Lake Hills Dry Weather Without Street Cleaning (L:.T
Runoff Yields (1 h / a c r e / s t, o r T-. }
Gtorm
number
6
e
g
1C
1 1
15
16
18
i g
21
22
25
26
28+29
30
31
32
1 U
1 16
1 17
1 18
1 19
120
Total
Average
Minimum
Maximum
Month
4/14/80
4/18
5/21
5/24
5/27
6/5
6/8
6/24
6/25
\j 1 i— j
7/1 1
7/14
8/26
8/27
9/1
Q/6
9/1l
9/13
7/6/81
7/13
8/31
9/1
9/19
9/20
Flow
(cu ft)
8650
132000
11000
5850
4070
6920
9170
52400
3630
^ ^ ~s w
9870
6090
1210
30200
56900
14800
3710
4810
48800
1 26000
19500
3870
7380
37100
653930
28432
1210
132000
Rain
(in)S
.15
1-33
-19
.15
. lO
.18
.17
.72
.08
.28
.15
.04
.43
• 57
.23
.12
.16
.64
1 .25
.12
.12
.10
1 .05
8.33
• 36
.04
1 -33
Total
ol ids
.46
6.55
.80
• 31
.23
.25
1 .10
3-05
. 25
* *— J
.51
• 51
.06
3-51
1 .86
• 54
.05
.46
2.66
6.10
1.36
• 42
1 .24
6.51
3P 82
1 .69
.05
6.55
TKJi
.01 1
.043
.010
.003
.001
.003
.008
.045
.002
.005
.003
.003
.031
.009
.009
.002
.002
.031
.095
.071
.OOC
.012
.067
.470
.020
.001
.095
COD
.^<5
1 .03
• 32
.06
.08
. 1 1
.49
1.32
• 1 3
• 30
.16
.06
1 .38
1 .05
-43
.07
.11
1 -55
2.86
1 .19
.23
• 53
2.88
16.70
.73
.06
2.38
Total
Pho~.
. G0 1 4
.0154
.0025
.0001
.C003
. 0004
.0028
.0090
.OCC6
.0016
.0006
.0004
.0668
.0027
.0024
.0003
.0003
.0102
.0208
.0023
. 00 1 2
.0032
.01 23
.ireo
.."069
.0001
.0668
Lead
.00?'-:
.0081
.002'.:
.0005
.0003
.0005
.0031
.0061
.0005
.0014
.0007
.0003
.0098
.0017
.GO 2 4
.0001
;C01
.GO"' 0
.0077
.0024
.000 a
.0013
.0107
.0680
.0030
.0001
.0107
0 •' f <-•
r rr {
i"'^-;
• oc r '?
• r •
r, '"/,'.'
.0004
. 00 1 0
. r. •; 1 1
r c/.^
err 7
r r-. ~- ,t
.".^02
. '^G"7^
. 0026
.001 2
.0002
.0004
-0033
.01 00
. C 0 2 7)
.0006
. r.O'"'"1
. 0'0r'°
.0462
.Gr20
. T C 2
.0100
-------
Table A-17. Lake liilln Dry
;her With Street Clo-'irinr !"'„>'',
Runoff Yield:; < i b/;,,; r-/— - f" /'
.vtorm
number
34
85
86
89
90
91
92
93
94
95
96
97
101
102
103
104
105
106
107
108
109
1 10
1 12
1 13
Total
Average
Mi n irnum
Maximum
Date
9/20/80
3/24/81
3/28
4/5
4/6
4/7
4/10
4/'2
4/20
4/21
4/23
4/27
5/11
5/14
5/14
5/18
5/24
6/5
6/8
6/9
6/12
6/12
6/17
6/30
Flow
(cu ft)
173CO
1 3000
4700
12500
36900
1 6300
26000
7340
8350
17600
2880
30300
25400
12500
4680
23700
20500
27700
29100
4190
16200
11000
12500
21900
402540
1 6773
2880
36900
Rain
Cn)
-25
.21
.14
.18
• 34
.28
• 36
.12
.19
.27
.08
.
. ! 8
.08
.44
.36
• 43
.40
.08
.28
.21
• 37
• 33
6.54
.27
.08
.53
Total
Col H:i
2.1 1
• 57
.19
.67
3-C5
.42
1 .86
.71
.40
.82
.08
1 .48
3-72
1.23
• 56
.86
1 .22
1 .98
1 .30
.47
1 .02
.73
.21
2.76
28.40
1.18
.08
3-72
TK"
.018
.007
.002
.006
.026
.002
.009
.004
.005
.006
.001
.022
.014
.01 1
.005
.009
.008
.033
.018
.004
.009
.007
.004
-054
.235
.012
.00!
.054
COL'
7 1
. 26
. 1 1
.":'2
• "j
.27
• 52
.13
-25
•>'*-'
-07
.66
1 .05
. 48
.20
• 39
.62
.76
.64
• 05
• 34
.51
.17
1 .64
1C.r)7
.46
-05
1 .64
,0111
, 001 ^
-------
Table A-18. Lake Hi] Is Wet Weather Without Street Cleaning (LH'w)
Runoff
no
-------
ro
Ln
-p.
"able A-19- Lake Hills Wet Weather With Street Cleaning (CLrlV)
Runoff Yields (Ib /acre/stor-)
Storm
number
37
38
39
40+41
42
43
45
46
47
48
49
63
66
67
69
70-:71
72
73+74
76
77+78
Total
Average
Minimum
Maximum
Month
10/8/80
10/12
10/24
10/31
11/1
11/3
11/8
11/14
11/19
1 1/20
11/23
1/17/81
1/23
1/26
1/28
2/11
2/13
2/13
2/17
2/18
Flow
(cu ft)
2590
6780
8140
58200
38700
47500
42200
9710
17400
223000
17100
8460
53000
1 1 000
75000
90200
19900
1 13200
10600
51080
903760
45188
2590
223000
Rain
(in)
.1 1
.16
.17
.74
.36
• 52
.41
.15
• 19
1 .55
.22
.15
.48
.16
.60
1 .00
.24
1 .01
.16
.58
8.96
.45
. 1 1
1.55
Total
Solids
.27
.11
.69
3-78
4-46
2.47
1.76
.74
4.71
12.56
• 75
.74
5-23
• 55
3-17
4-97
.80
15-11
.48
.00
63-35
3-17
.00
15-11
TKN
.006
.003
.006
.031
.035
.018
.017
.004
.020
.142
.010
.004
.031
.002
.01 1
.035
.003
.087
.005
.044
• 517
.026
.002
.142
COD
.12
.09
.40
1 .45
1 -50
1 .02
.93
• 50
.41
4-42
.23
.23
1 .86
.16
.61
2 . 37
• 33
2.29
.20
1 .74
20.66
1 .04
• 09
4-42
Total
Phoc .
-0004
. 0008
. G0 1 9
.0075
. 007 1
.0047
-OC3C
.CC1G
.C0°8
• 0396
.0054.
.0026
.00Q1
. 00 1 M
.001 2
.01 22
. 00 1 6
.031 2
. 00 1 0
.0106
. 1 5^2
.0077
.0004
.03 "C
-------
Currey Do win-- Try V.-ntMer Witho-it Gt.reet Cleaning (ODD)
• ' - - r~.
.-, , ] - 1 . p p
1
,; |
^ t '
, • ;
25
27
2S
30
31
J2
<3
M
J S
81
82
83
84
05
86
up
8T
no
91
')2
93
0,4
95
97
°8
rn
100
101
104
1 or,
106
07
103
1 no
1 l5
1 12
13
14
15
16
17
19
20
21
22
Tol^l
Avernj'e
f. i n in-.um
Mnx i IT. urn
Pr\ * ^
V12/W
3/26
7/11
7/14
8/17
8/26
Q/27
8/23
9/1
9/6
9/12
9/1?
9/10
°/20
9/29
3/3/01
3/5
3/15
3/23
3/24
3/28
'4/2
4/5
4/5
4/7
4/10
4/12
4/20
4/22
4/27
5/3
5/7
5/7
5/10
5/19
5/24
6/5
G/S
6/9
6/12
6/12
6/17
6/30
7/6
7/10
7/13
8/31
9/18
9/20
9/25
9/26
Flow
(cu ft)
i of-rvo
.qi-,',0
1 0700
6 1 r-0
31 'VO
'2670
Si '-0
23600
"S 1 4 CO
1 1 900
1 °70
5020
2870
20 '00
23700
3STOO
8310
25300
1 8800
14600
7400
5700
5250
15700
4310
8070
3680
1260
2010
25300
Q690
5550
1Q600
20^00
11800
16500
17300
17500
21 60
10600
17100
8880
1 1500
26400
6230
69800
6340
18000
38200
33900
103000
950420
18635-69
1260
1 08000
R n i n
(in)
1 .2^
-19
. 22
• 1 5
.63
.0"
. 18
• 37
.50
.27
.08
.14
.on
• 38
.43
.62
. 10
.28
.34
.26
.18
.23
.16
• 38
.22
• 30
- '< 3
.08
.1 1
.47
.21
.16
• 33
.29
.22
•31
• 33
.31
• 05
.23
• 33
• 23
.25
• 53
.16
1 .17
.24
• 50
.68
• 58
1.65
17.56
• 34
• 05
1.65
Tot.'il
1-nlidR
4.95
1 .29
1 .00
• 51
1 3 . 00
• 1 9
1 .47
2.23
1.19
• 70
• 09
• 30
. 1 S
2.23
1 .79
1 .61
.45
1 .40
1 .01
-73
• 30
.71
.20
1.51
.14
• 35
.28
HA
17
1-19
.66
.19
2.41
1 .17
• 53
.81
1-59
1 .00
NA
• 91
3-19
.18
2.44
i .05
.61
3-57
.82
4-14
3-40
2.58
10.66
84.25
1 .72
• 09
13-00
•uneff Yields (lb/i.cre/storm)
TKN COD Total
Fhos .
.040
.007
.009
.001
.061
.006
.01 1
.013
.014
.010
.000
.003
.002
.01 9
.014
.014
.005
.01 6
.010
.006
.001
.006
.003
.012
.001
.004
.003
NA
.001
.013
.009
.005
.020
.01 1
.007
.008
.018
.009
NA
.007
.024
.004
.032
.020
.007
.038
.013
.048
.032
.024
.080
.720
.015
.000
.080
1 .63
.44
.48
• 15
3-17
.22
.56
.54
.60
.37
.03
.14
.11
1 .01
.65
.68
.18
1.25
.42
• 69
.16
.37
.15
.46
.06
.14
.11
NA
.06
• 55
.60
.30
.78
• 54
.51
.49
• 75
.60
NA
• 35
1 .10
.17
1.12
1 .02
.42
1 .46
• 34
1 .61
1 -45
1 .27
3-37
33-75
.69
.03
3-37
.00° 2
.0018
.0020
.0006
.C'75
.0017
.0065
.0014
.0025
.0024
.0001
.0004
.0004
.0048
.0028
• 0035
.0009
.0034
.0020
.0021
.0006
.0019
.0006
.0057
.0002
.001 1
.0006
NA
.0002
.0031
.0018
.0011
.0046
.0027
.0015
.0022
.0034
.0023
NA
.0019
.0068
.0010
.0090
.0042
.0011
.0078
.0023
.01 10
.0050
.0049
.0215
.17S3
.0036
.0001
.0215
Lead
.0071
.0020
.0015
.0004
.0171
.0009
.0027
.0031
.0010
.0017
.0001
.0002
.0002
.0032
.0020
.0025
.0005
.0015
.0012
.0010
.0002
.0007
.0003
.0021
.0001
. 0005
.0005
MA
.0001
.0033
.0006
.0007
.0026
.0013
.0008
'.0011
.0023
.0011
NA
.0007
.0045
.0006
.0030
.0017
.0008
.0046
.0008
.0062
.0050
.0022
.0135
.1119
.0023
.0001
.0171
Zinc
.0055
.0012
.001 1
.0005
.0077
.0 )05
.0012
.0017
.0017
.0023
.0001
.0005
.0002
. 0021
.0017
.0020
.0005
.0018
.0011
.0010
. 000'4
.0006
.0003
.0015
.0002
.0004.
.0002
NA
.0001
.0013
.0009
.0006
.0017
.0012
.0008
.0013
.0019
.0011
NA
.0008
.0026
.0005
.0020
.0024
.0007
.0056
.001 1
.0034
.0039
.0034
.0079
.0832
.0017
.0001
.0079
255
-------
Table A-21 . Surrey Downs Dry Weather With Street Cleaning (C:JCD.'
Runoff Yields (Ib/acre/otorrr,)
Storm
number
3
4+5
7
8
Total
Average
Min irnum
Maximum
Date
4/5/80
4/8
4/H
4/18
Flow
(cu ft)
22600
48900
8590
78800
1 58890
39723
8590
78800
Pain
(in)
.43
• 79
.18
1 .18
2-58
.65
.18
1.18
Total
TKN
COD
Solids
1 .
4.
1 .
2.
9.
2.
1 .
4-
66
23
10
22
21
30
10
23
.016
.019
.015
.026
.076
.019
.015
.026
• 74
1 .25
• 30
.77
3-07
-77
.30
1 .25
Total
Phos.
.0037
.007?
.0033
.0050
-01 97
.0049
• 0033
.0077
L.-^d
.004C
.OC64
.001 ?
-002G
.01 4?
.0037
.0019
.0064
-------
Table A-22. Surrey Downs Wet Weather
Street Cleaning
Runoff Yields (Ib/acre/atorn1
CtO T3
number
37
38
39
40
42
43
44
45
46
47
48
49
50
51
52
53
55
56
58
59
60
61
62
63
64
65
69
70
12 to 78
79
155
156
158
159
Total
Average
Minimum
Maximum
Sate
10/8/80
10/12
10/24
10/3i
11/1
11/3
11/6
11/8
11/14
11/19
11/20
11/25
11/27
11/28
12/2
12/3
12/14
12/20
12/24
12/24
12/25
12/26
12/29
1/17/81
1/20
1/21
1/28
2/11
2/13
2/24
12/28
1/10/82
1/15
1/17
Flow
(cu ft)
10200
4280
7760
48500
20700
41 600
87500
36000
5330
14200
134000
8730
55100
87900
88000
51 200
5050
25100
16600
50500
135000
49900
1 270CO
10400
16600
35900
59100
63800
249600
34300
k460
17800
90800
13800
1704710
50139
2460
249600
Rain
(in)
-19
.12
.16
• 74
.29
.60
1 .18
• 43
.12
.21
1 .66
.15
-71
.86
.97
.46
.11
.43
.26
• 51
1 .28
• 34
1.14
.22
.27
.42
.63
• 91
2.20
.36
.04
• 30
1.10
.16
19-53
• 57
.04
2.20
Total
Solids
1.16
• 15
.71
1 .81
1-36
2.59
5-33
1 -51
.87
.68
5-27
-17
1 -77
3-05
3-92
2-38
.33
1.56
1 .07
1 -98
6.72
2.71
7-57
.85
1 .07
2.14
2.63
3-34
20.44
1 .68
.07
3-19
6.07
1.15
97-30
2.86
.07
20.44
TKI;
.013
NA
.005
.020
.015
-021,
.036
.015
.005
.011
.098
.005
.020
.073
.042
.008
.003
.012
.010
.003
.062
.021
.047
.007
.003
.018
.010
.027
.160
.014
SA
.023
.043
.007
.861
.027
.003
.160
CCD
.26
.07
• 52
1 .62
.62
.87
2.92
.83
.17
• 38
2.63
.18
I .05
1.96
2.42
.87
• 23
• 95
.67
.66
2-39
.65
1.58
• 32
• 57
1 -13
.77
2.17
7.6L
.85
NA
1 .28
2.26
.30
41 .86
1 .27
-07
7.68
Total
Phos.
.0024
.0005
.0012
.0048
.0024
.0044
.OC 4 6
-0033
.0008
.0016
.0132
.0015
.0040
.0058
.0098
.0028
. 0008
.0030
.0017
.0029
.01 18
.0069
.0077
.0025
.0008
.0004
.0001
.0067
.0327
.0038
NA
.0044
.0101
.0008
.1601
.0049
.0001
.0327
I.
-------
Table A-23- Surrey Downs Wet 'weather With Street Cleqr.inr (o:'.rV,'<
Runoff Yields (1 b/ac re/3f o rrr.
Storm
number
123
1 24+125
1 26
1 27
1 28
1 29
131
132
133
137
138+139
140
141
148
149
150
151
152
1 53
1 54
Total
Average
Mini mum
Maximum
Date
10/1/81
10/5
10/7
10/8
10/27
10/28
10/30
11/11
11/13
11/30
12/1
12/3
12/4
12/9
12/13
12/14
12/17
12/19
12/21
12/23
Flow
(cu ft)
5 2 ",00
401000
18300
19200
39500
9170
4230
93900
6030
7360
37130
13500
1 1 6000
72800
22400
81 100
22400
83100
3980
17100
1 125300
56265
3980
401000
Rain
(in)
.81
4-38
. 14
-24
-74
.17
-09
1 .50
. 1 1
.1£
• 55
.".9
1 .27
.78
-36
.87
.29
.79
.08
.27
13.77
.69
.08
4.38
Total
Solids
3.24
37.82
1 -39
1.11
1 .86
.45
.27
4-92
.27
.53
2.02
1 .24
8.36
5-44
1.16
5.15
1 -95
3-48
• 51
.82
81 .99
4. 10
.27
37-82
TK:I
.025
.268
.01 1
.007
.016
.004
.005
.041
.003
.006
.018
.006
.049
.023
.009
.033
.009
.026
.002
.006
.S67
.028
.002
.268
COL
.96
8.93
.29
. 33
.93
.17
.07
2. 14
. 17
.33
.88
.42
1 .2Q
1 -34
• 51
1 .86
.40
1.14
. 14
.37
22.72
1.14
.07
8.^3
T rj t • i i
F'.O"..
.0051
.0604
.0009
.CGI 2
.0040
r r-.t'-f
. ^ . j j
.00.08
.011 0
.0006
.<~.01 3
.00/13
.Cr ! 1
^ ' ^ ' * '
.0'M3
-C0?0
.0''r'0
. 00 ' 9
. 0 0 4 6
.0005
. on i 3
.1235
.0062
.0005
.0604
-------
ro
en
20
16.
fe
8
FIGURE A- 1
NUMBER OF RRIN5 PER MONTH
™^™
WE'.1
SURREY DOWNS
V
M^ ^
\ /
\
DRY
01*234567
1
'
t '
//
//
vl
8 9
\
\
\
\
v
\
\
\
\V-j
» / *
i j
V
WET
1 1
10 11 12 12
A
A/
/ /"V. 1
• -.' '\ i
^ \i /
'! /
^ r
u
DRY \
1 1 1
iJ 15 16 17* 18 IS
A
/ ^
:? ^,
/ ':
/
s /
.•'
WET
20 21 11 23
MONTH OF STUDY
-------
FIGURE A-2
RfllN VOLUME PER STORM EVENT
ro
01
O
0 1 2 3 4 5 6 7 8 9 Iff 11* 1
9 2ff 21 27 23 24
MONTH OF STUDY
-------
Q- 1
FIGURE A-3
STORM DURRTIONS
0 1
2'3' 4'5' ft1 7'B1 S1 IB II1 12 13"
MONTH OF STUDY
23 2i
-------
1200
FIGURE A-4
INTEREVENT PERIOD
O1 1 ' 2 ' 3 ' 4 ' 5 ' 6 7 8 ' 9 ' 10 11' 12 13
MONTH Of STUDY
2l 27 23 24
-------
no
en
FIGURE A-5
RVERRGE RRIN INTENSITY
23 24
MONTH OF STUDY
-------
FIGURE A-6
PERK RflIN INTENSITY
\.s
V-
H-
• •^
1
«—•
Z
0' 1 2 3 4 5' 6 7 8 9 10 11 12 13
MONTH OF STUDY
23 24
-------
FIGURE A-7
K LfiKE HILL5 flND SURREY DONN5 RRIN QUERIES
£ 1.5
x
z
1
*~* at
z B
cr
-.5
in
o „» i
/—5 1 « <
-2
»*•
3
Lfl
-3.5
« •
-3.5 -3 -2.5 -2 -1.5 -1 -.Z 0 ' .5
NfiTURflL LOS OF L3KE HILL RRIN QUfiNHf (LN X INQ.ESJ
1.5
-------
i -
a;
2
O
a
o
4.5J
4 _
o
•"• 3 '
L— v • •
-1 -.5 '0 .51 1.5 2 2.5 3 3.5 4
NflTURflL LOG Of- LFKE HILLS RfllN DURRTION (LN X HOURS)
4.5
-------
FIGURE A-9
1 LflKE HILLS flND SURREY DOWNS PERK RflIN INT
x
V 3.5__U
5 3
o
a
2 .
1.!
1 .
.5.
5 3
U3
• * « «
• *
« * • • V
« « »
•
«
.5 1 1.5 2 2.5 3 3.5
NES. NRTURflL LOG LflKE HILLS PR. RflIN INT. f-LN X IN/HR)
-------
(NJ
LT.
15.
10.
FIGURE A- 1 0
LflKE HILLS - Wei Season
-------
FIGURE A- 1 1
SURREY DONN5 - Net Season
-------
FIGURE A- 1 2
30
25.
a
20.
15.
10.
LflKE HILLS - Dry Season
J
~*
"~
—
—
—
-
-
<
i
/
/
/
i;
3.
•
1
11
lie
L
i-""
{'
|/
j7
*. /
ilH
i.]
e
T
/
/
./
/
'
/
/
/
.:
2
Q
7
/'
/
/
/
/
/
/
/
.:
5
1
!
'.i
p
\
!r'
3
7
/
/
/
/
/
/
/
'
[
H
0
T
/
/
C
*i
1
0
7
/
/
/
/
/
/
.f
1
tf-J
0
7
/
/
/
~t
r
0.8
£
0.5
)
P
1
/
x
/
/
/
.e
3
1-
>
/
/
/
/
/'
1.
1
^-EVENTS
1INFP.LL Q-RUNOFF
( -
-------
FIGURE A- 1 3
SURREY DONNS - Dry Season
Q-RUNOFF
-------
FIGURE A- 1 4
no
-j
SURREY DOWNS RUNOFF (percent by month)
JULT
flUGUST
SEPTEMBER
OCTOBER
FEERUfiRT
JflNURRY
DECEMBER
NOVEMBER
-------
rsj
•-j
OJ
FIGURE A- 1 5
SURREY DOWNS BflSE FLOWS (percent by month)
MRRCH
flPRIL
MflY
JUNE
JULY
flUGUST
SEPTEMBER
OCTOBER
FEBRUfiRT
JflNUflRT
DECEMBER
NOVEMBER
-------
FIG'J'rlE A-16
55
H 50__
* 45__
5
£ 40-_
§ 3S—
a 30
u
2 2S_
H
a 20 —
3
H is_
t 10_
if"
ai c
jp 5 —
SI
n
V
-
™*
r
^_
§
^
~
—
^
— .
-_-1
—
—
«i
—
i»
if
£
jj
^
3
*
1
0
-
j
1
fin
II 1
0. 15
— '
P
C
!
\
*
'i
i
£
i
D
'1
R 11 n
I ri~! B-i B-i ' S~l n ETl I era r-i
10.2510.3 0. 35 I '). 4 U . 4 rj . ;- j ': . ~> ~> >., . ^
||-LflKE HILLS Q-SURRET DOHNS
-------
FIGURE A- 1 7
ZINC
ro
—i
LTI
-LflfcE HILLS
Q-5URRE
-------
FIGURE A- 1 a
CHEMICRL OXYGEN DEMfiND
-------
no
—j
FIGURE A-19
TOTHL UELDRHL NITROGEN
<0.5 I 0.5
HILLS Q-SURRET DOHNS
-------
r\J
~o
30
5
50
40.
30.
\-
10.
-------
FIGURE A--21
30
PH
20.
BS!
5.0
5.2:
b. 0
KILL5 Q-SURRET D(M4S
-------
•X)
'.TO
O
FIGURE A-22
SPECIFIC CONDUCTRNCE
HILLS Q-SURftET DOWNS
-------
ro
DO
FIGURE A-23
TURBIDITY
< 5 5 10
U*E HILLS Q-SURRET DOWNS
-------
00
ro
09
08
o /
06
OS
0 1
I °09
£ oofl
•o
J 007
006
005
003
0.02
Surrey Downs £
Lake Hills *
20 30 40 50 60 fO 80 90 95
Percent Less Irtan Concentration
98 99 995 998
FIGURE A~24 Fraquency Distribution of Lead Concentration
-------
Surrey Downs •
Lake Hills *
ro
CD
OJ
1 0.07
OOP
0.05
O.O4
0.03
0.02
20 30 40 50 60 70 80
Percent Less than Concentration
98 99 99 •> 99 8
FIGURE A ~ 2 5 Frequency Distribution of Zinc Concentration
-------
Surrey Downs
Ldke Hills
80
70
60
20 30 40 ',0 60 70 80
Percent Less then Concentration
98 99 99 5 9y f
FIGURE A~26 Frequency Distribution of COD Concentration
-------
rsj
oo
1
= 0.!*
£ 0.8
^ 0.7
(-
0.6
Surrey Downs
Lake Hills
0.2
20 30 40 50 60 70 80
Percent Less than Concentration
FIGURE A— 27 Frequency Distribution of TKN Concentration
-------
4 0
30
Suridy Downs
Lake Hills
IN)
CO
cr>
006
005
004
003
20 30 40 50 60 70 80 90
Percent Leas than Cofi~entratlor
FIGURE A~28 Frequency Distribution of TP Concentration
-------
Surrey Downs
Lake Hills
IN3
CO
20
20 30 40 50 60 70 80
Percent Less than Values
FIGURE A — 29 Frequency Ditttrlbutlon of Specific Conductance Values
98 99 995 998
-------
200
Surro> Df ".s
Lake hills
po
oo
oo
60
bO
5 30
*•••
20 30 40 50 60 70 80
Percent Less than Values
FIGURU A~30 Fr»quancy DlvVrlbutlon of Turbidity Values
-------
("O
oo
FIGURE A-31
SURREY DOWNS TOTflL SOLIDS BY SEflSON
3(5(5
25fl
5 2a
N
in
2 ISfLU
d
vn
ct
j**
.
*
A «
0 .25
9 dry season
* wet season
.5
.75 1
RflIN, INCHES
1.25
1.5
1.75
-------
.5.
.4.
.3.
a
-------
FIGURE A-33
SURREY DOWN5 ZINC BY SEflSON
.35__
.3.
• *A
.05 I...
A •
0 ' .25
dry season
, wet season
.5
.75 1
RflIN, INCHES
1.25
1.5
1.75
-------
FIGURE A-34
SURREY DOWNS COD BT SEflSON
150
lOfl
75.
50.
25.
A A
V*'j; .*
/'A
A. • A •
• A A A
.25
o dry season
A wet se^r.on
.5 .75 1
RfllN, INCHES
1.25
1.5 1.75
-------
ro
>O
to
FIGURE A-35
SURREY DOWNS TK.N BY 5ERSON
4.5 r
i
4 __;
3.5
3 ,
2.E
0 0
0 00 0 A
0
0 .25
a dry season
4 wet season
*f ' I
"'t.; i
-i-'
.75 1
RfllN, INCHES
1.25
1.5
1.75
-------
FIGURE A-36
SURREY DOWNS TOTflL PHOSPHOROUS BY SEflSON
1.25
.71
fc
S -
OL-
*f
.25
e dry season
A wet season
.5
.75 1
RfllN, INCHES
1.25
1.5 1.75
-------
FIGURE A-37
SURREY DOWN5 PH BY 5ER50N
7.5
6.1
£
a.
A A
A
A A A A A A
A A A
• A A A A
A A
• • 9 « A A
> • A* ® A A
A A A •
« e» • A
A««»AA««« A
A* e «• « A
A* e • A
• A » A 2 •
9 » A
A
5.!
.25
.5
dry season
wet season
.75 1
RflIN, INCHES
1.25
J.5 1.75
-------
FIGURE A-38
SURREY DOWNS CONDUCTIVITY BY 5ER50N
150
5 12D—
90.
S 60.
LJ
t—t
U_
30
A
« 9 C
_ A A -
'". A
0 .25
e dry season
A'wet season
.5
.75 1
RflIN, INCHES
1.25
1.5 1.75
-------
FIGURE A-39
100
80.
60.
40.
SURREY DOWNS TURBIDITY BY SEflSON
20..
e .25
e dry season
A wet season
.5
A A
A *
£
.75 1
RRIN, INCHES
1.25
1.5
1.75
-------
FIGURE A-40
fNJ
k£-
ro
LRKE HILLS TOTflL SOLIDS BY SERSON
300
25D
20D
in
° 1C?
•— lot
o
in
50.
0
Ac
0 e
• * , A
« -- * *
A A
e A
.25
e dry season
A wet season
.5
1.25
1.5 1.75
RfllN, INCHtS
-------
FIGURE A-41
LfiKE HILLS LEflD 3Y 5ERSON
f\5
\0
-O
.3.
f
.2.
.1.
-A «• 00 AC 99
* A
e 9
• A
A A « -tt
0 .25
0 dry season
A wet season
,5 .75 1
RfUN, INCHES
A AA
1.25
1.5
1.75
-------
o
o
FIGURE A-42
LflKE HILLS ZINC BY SEflSON
,35__
.IS
.1-
.854—
0
* .
A A A
• A A
• * A
A » A* •
A #
*A • A A*
'A*/
0 ' .25
0 dry season
A wet season
.5
.75
1
1.25 ' 1.5
RflIN, INCHES
1.75
-------
OJ
O
FIGURE A-43
LflKE HILLS COD BY SEflSON
150
125-_
IQfl •
75.
A* A
0 a • •
A
A
A
A* A
0 ' .25
e dry season
A wet season
.5
.75 1
RflIN, INCHES
1.25
1.5
1.75
-------
FIGURE A-44
LflKE HILLS TKN BT 5ER50N
4.5
3.25_ A
o
ro
2.:
i.i
7C
• / •>
A e
* w* •. • .
A •« * 9 • *
-«PA . * 8 *^ *
AA * • •
—£
0 ' .25
e dry season
A wet season
A «A
.5
A
A
A •
A
AA *
,75
1
1.25
1.5 1.75
RflIN, INCHES
-------
FIGURE A-45
CO
o
LflKE HILLS TOTRL PHOSPHOROUS BT 5ERSON
1. 25_- a
*7£
• A
A •
A
AA
0 ' .25
e dry season
A wet season
.5
1 .75 1
RflIN, INCHES
1.25
1.5
1.75
-------
7.5
FIGURE A-46
LRKE HILLS PH BY 5ER50N
OO
o
12
»—I
5
£
A A A A
•A A A A •
A A A
A A A
A t\ A
A
• A
0O
• •
• »
• •*»
O0 A •
e A a
A
A
*» A
AA
A
A A
• A
0 .25
e dry season
A wet season
.5
.75 1
RfllN,- INCHES
1.25
3.5
1.75
-------
FIGURE A-4T
LRKE HILLS CONDUCTIVITY BY SERSON
150
5
3t
90
13
Ul
u
30
.25
e dry season
* wet season
,5 .75 1
RflIN, INCHES
1.25
1.5
1.75
-------
OJ
o
FIGURE A-48
LflKE HILLS TURBIDITY BY SEflSON
100
6f
20_
• •
:.
.25
.5
« dry season
A wet season
1 .75 1
RflIN, INCHES
1.25
1.5 1.75
-------
.- :\ , ' s i:
roin dei'iing re il e) (microns)
A-1 12 A.-) 4 .'.'61 36}
A-1 15 6.9 7 268 327
A-1 1 9 11-0 11 423 -60 323 474
A-170 1i .6 >60 312 463
A-174 2.0 >60 270 441
A-179 4.2 >60 384 473
A-185 -6 >60 233 599
A-312 .4 >60 382 752
A-319 6.3 >60 503 488
A-325 1.0 >60 442 934
A-329 2.9 >60 400 564
A-335 .8 >60 329 720
A-341 -4 >60 374 716
A-349 5-4 >60 405 968
A-353 7-4 >60 379 896
A-356 q.2 >60 372 782
A-362 12.4 >60 356 774
A-366 .8 >60 282 1006
A-372 1.7 >60 314 842
A-381 4-9 >60 597 514
A-386 8.9 >60 361 790
A-395 2.3 >60 341 850
A-400 5.3 >60 315 496
A-402 1.0 >60 594 936
A-418 .6 >60 422 832
A-429 2.6 >60 430 7^4
A-440 .4 >60 304 700
A-454 7.2 >60 343 800
A-459 1.0 >60 226 914
A-475 3-7 >60 443 580
A-481 7-5 >60 501 593
A-490 2.8 >60 432 748
A-494 3-6 >60 350 760
A-499 1.0 >60 279 872
307
-------
VM e B-1. Surrey Downs Gtreot Dirt Load i nps ', cont
(Dry season, no r-treet. ~.i r;\-.i r.r}
3 a in p 1 o
D n t e
fc ;"
(', I ^ r
6/30
7/0
7/14
7/1 7
7/20
7 / 2 3
6/4
8/7
8/1 2
6/1 4
fc/'l 8
8/21
S/25
8/2E
q/2
9/4
9/8
9/1 1
9/H
9/15
J I ' ,x
°/1 3
^ 1 ' '—
9/23
Count
Average
,"•' iniwum
"vix inum
0 an pie
Ident .
A -500
:\_
A-530
A-534
A-^4'i
A-548
A -553
A -5^3
A-S^Q
A-^6S
A-567
A-575
A-579
A-501
A-586
A-586
A-593
G-594
n.ivs f-
iTot ^i,
r r
;
1 2
i
f}
^
~it
1
\ ^
r?
/4
32
3s
~;9
43
45
1
~j
c
1 1
14
15
18
1
74
45
-GUI
,M •
3 i n
p
_ ,>,
7
. i
_ c~l
o
. 0
. o
. 0
_ o
, o
. {
3
. 1
. 1
.5
.6
-4
• 5
. A
.3
.4
.4
.0
10
4
- 4-
• 9
Days from
laot
cl ean i np
>GO
>6C
>60
> h 0
>60
> f- 0
><50
>oO
>00
>60
>60
>^0
>60
> 60
>60
>fO
>60
>60
>60
>60
>60
>60
>60
>60
>60
>60
74
>30
4
>60
Load i ng
(it/curb-
mile)
368
669
409
38?
562
348
315
540
385
446
568
500
£93
416
503
516
546
282
498
435
450
506
275
872
277
74
3Q9
21 9
872
Median
si ze
(microns )
732
610
4^4
610
61 1
403
648
559
489
484
457
454
477
520
479
445
415
421
613
468
429
444
440
44~5
447
682
74
575
28°
1006
>08
-------
'i;rrey l''owns Street Dirt Loadings
( W o t ,• e a son, no street cleaning)
Gar.rle Days from Loadir?; Kediar
luen4,. last si£n. (ib/curb- size
rain mile) (microns)
10/2/80 A-189 2.4 526 50?
10/7 A-196 7-5 389 561
10/9 A-198 -9 406 442
10/14 A-206 6.1 336 500
10/16 A-2C8 8.2 339 408
10/21 A-213 13-2 371 963
10/23 A-218 15-2 342 514
10/28 A-221 20.1 369 444
10/30 A-227 22.2 379 450
11/18 A-236 8.8 244 1592
12/9 A-244 4-9 475 1228
1/6/81 A-249 5-3 346 1609
1/8 A-252 7-1 333 1600
1/13 A-259 12.3 406 870
1/15 A-263 14-3 371 888
1/20 A-267 19-1 447 1708
1/27 A-271 3-4 556 1220
1/29 A-276 .3 290 1064
2/5 A-284 7.1 • 681 802
2/10 A-289 12.5 471 724
2/17 A-291 .6 278 1190
2/19 A-295 2.7 330 930
2/26 A-304 1.1 425 888
Count 23-0 23 23
Average 8.5 387 917
Minimuc .3 244 408
Maximum 22.2 681 1708
309
-------
(11- /curl -
rail" )
4/18
^-42
u-44
S-45
3-47
F.-49
3-51
3-52
S-54
5-56
S-58
S-59
S-61
S-63
S-65
S-66
S-68
S-70
S-72
G-75
S-76
S-7Q
S-80
S-81
S-84
S-86
S-87
8-88
S-90
S-92
S-95
G . 4
1 . 1
1 . 1
1 .6
1 .6
1 .7
3-7
1 .2
1 .2
3- 2
3-2
5-2
5-2
2.2
2.2
S29
4°3
7.
7.
Q .
9.
1 1 .
1 1 .
14.
14-
16.
16.
18.
18.
21 .
21 .
2.
3-6
3. 6
2.0
2.0
9-0
9-0
1 1 .0
1 1 .0
14.0
14.0
1 .6
1 .6
3-t)
3-6
5-0
2.9
545
695
442
713
41 2
32fe
2G5
303
317
295
386
371
323
424
332
333
353
406
315
472
423
437
427
384
444
29C
304
305
375
257
235
252
237
245
281
295
336
352
352
320
251
249
328
315
302
364
41 5
45^
423
483
471
415
391
441
391
408
329
376
346
357
333
327
309
361
349
300
325
341
335
314
365
372
391
371
356
324
308
334
343
341
386
302
415
366
368
354
330
310
-------
'able D-7- Surrey Downs Street Dirt Load ir:g3(c°nt •
(Dry season1, with street cleaning)
Sample
Date
6/30
7/2
7/2
7/7
7/7
7/9
7/9
9/24/01
o/OQ
9/29
9/30
9/30
Count
Average
Ki nitnum
Max imum
Sample
Ident.
3-97
S-100
3-101
S-103
S-105
S-107
S-109
S-598
S-5Q9
S-600
S-602
S-603
Days from
last sign.
rain
3-0
7.0
7.0
12. C
12.0
14.0
14.0
2.6
.2
.4
1 .2
1 .4
60.0
7
.2
21 .2
Days fron
j ast
clea ilng
. 1
1 .9
.1
4-9
. 1
1 -9
.1
1 .0
3-9
. 1
• 9
.1
60.0
1 .2
•1
4-9
Loading
(Ib/curb-
mile)
306
363
364
295
285
353
345
253
139
177
164
180
60
347
139
713
Median
size
(microns)
301
323
282
322
304
327
339
531
862
444
734
421
60
377
276
862
311
-------
i rt Lo"id i n/'"
. fet i1 1 o.°. n i np)
2 'I- ;• 1 ,->
I'M t .^
10/2/2-1
10/2
1 0/[>
1 c,")
10/1 ?
10/12
10/16
10/16
1 0/1 '1
10/20
10/20
10/21
10/21
10/2"
10/26
1 1/2
11/2
11/5
11/5
1 1/6
1 1/9
11/16
1 1/16
11/19
1 1/20
1 1/24
11/24
11/25
12/4
12/7
12/7
1 2/1 1
1 2/1 1
12/14
1?/14
1 2/16
12/16
12/21
12/21
12/23
12/23
Count
Average
M i n imum
n.-i.x i mum
2'-.np] p
Id nn t .
'2-L>Oc.
2-t.iCe
2-607
S-612
2-6! \
S-612
2-613
2-6 1 6
S-617
S-621
S-622
2-623
G-624
S-625
3-626
S-629
S-630
S-632
S-633
S-635
S-637
S-639
S-640
S-642
S-645
S-646
S-648
S-649
S-651
S-652
S-653
S-657
S-659
S-660
S-661
S-662
S-663
S-665
S-666
S-667
S-668
>),v:- from
1 n r t :; i f n .
r n i n
.4
.7
3-4
•7
• I
3.4
3-6
7-4
7-7
10.4
11 .4
11.6
12.4
12.6
14-4
17.6
5-3
5-5
8.3
8.6
9-3
12.3
1 .0
1 .2
1 .7
2.8
1
1 .2
2.0
2.2
1 .2
1 -3
.8
• 9
. 7
-9
.6
.8
1 .8
2.0
^. 8
4-0
41 .0
4-9
.4
17-6
Pny:-' from
] MPt
c 1 e M n i n c
1 -9
.2
3-0
1 . 2
1 .q
.i
1 .9
.2
2.9
3-9
. 1
.8
. 1
1 -9
2.9
2.9
.1
2-9
.1
.8
3.8
10.8
. 1
2.9
• 9
3-9
.1
.8
.1
2.9
.1
3-9
.1
2.9
.1
1 .9
.1
4.9
.1
1.9
.1
41 .0
1 .8
.1
10.8
Load ir,f
(Ib/curb-
mile )
1^6
195
228
127
129
122
204
177
229
245
193
202
158
160
193
122
123
156
1SO
166
106
239
117
135
116
78
88
92
92
86
94
98
127
101
108
119
127
172
178
167
110
41
H6
78
245
Median
pi zp
(microns)
751
4^0
36 f
462
448
38^
316
327
303
378
338
345
274
355
438
491
419
454
410
407
794
1831
729
466
563
775
548
575
985
725
528
740
404
539
489
641
528
466
475
572
518
41
537
274
1831
312
-------
.' r--^. ("\irrcy i-cvr.. - 10fHh Ft. Street Dirt Loadings
(Fry sen:? *» 1676
9/30 A-186 .6 591
3/5/81 A-313 1.4 273 1246
3/10 A-320 6.3 509 978
^/17 A-326 1.2 394 1493
3/19 A-330 3.0 318 1312
3/25 A-339 .4 253 1460
3/30 A-350 5-5 265 1622
^/1 A-352 7.4 385 2182
313
-------
Table fl-5- Surrey Downs - 100th St. Street Dirt Loadings
(Dry season, no street cleaning) (cont. >
Sanple
Date
4/G
4/9
4/13
4/15
4/20
4/24
5/4
5/12
5/20
5/29
6/2
6/4
6/16
6/23
6/26
7/2
7/6
7/9
7/14
7/17
7/20
7/27
8/6
8/18
8/27
9/2
9/9
9/15
9/23
Count
Average
Minimum
Maximum
Sample
Ident .
A-360
A-369
A-374
A-379
A-3S5
A-397
A-420
A-443
/-457
A-477
A-482
A-485
A-495
A-502
A-510
A-518
A-521
A-526
A-531
A-535
A-537
A-543
A- 5 50
A-561
A-569
A-574
A-582
A-589
A-596
Days from
last sign.
rain
12.3
1 . 1
1 .e
3-9
8.8
2.4
.8
1 .2
1 .0
4-5
7.6
9-7
3-7
4-9
7.8
1 .5
5-7
2.4
1 .0
3-8
7-0
13-9
24-0
36.1
44-8
1 -4
8.5
14-3
1 .6
77-0
8.7
.4
44.8
Loading
!lb/ourb-
mile;
323
336
238
209
203
3H
331
320
252
399
368
273
506
330
308
543
240
311
283
218
340
318
295
557
281
199
266
300
157
77
409
157
1336
Med ian
size
[microns)
1392
1582
956
1092
1410
1866
1 184
1320
1674
1450
1466
2040
1 540
1996
1150
1286
992
1319
669
71 2
901
913
1163
1395
1503
1650
1412
1360
1240
1334
66y
2182
314
-------
•-•Me r-6. furrey Downs - 108th "t. Street Dirt Leadings
(Wot season, no street cleaning)
10/2/80
1 0/7
10/9
10/14
1 0/16
1 0/21
10/23
1 0/28
4 r\ I "7 r\
. ^ f ^\J
11/18
1/8/S1
1/13
1/15
1 /20
1/27
1/29
2/5
2/10
2/17
2/19
2/26
10/9
10/19
11 A
11/19
1 1/24
1 2/3
Count
Average
Minimum
Maximum
Garaple
Ident.
A-190
A-197
A-199
A-205
A-2QQ
A-21 2
A-217
A-222
A-235
A-253
A-260
A-262
A-268
A-272
A-275
A-283
A-290
A-292
A-296
A-303
A-609
A-618
A-634
A-643
A-647
A-655
f rcm
3 i gn.
rain
2.4
7.6
. Q
5-7
7-9
12.8
14-9
19-9
21 .9
8.8
7.1
12.3
14-3
19-3
3-4
• 3
7.1
12.3
.7
2.7
1 .1
.6
10.6
8.5
8
1
2.3
27-0
7-7
• 3
21 .9
Load ing
(Ib/curb-
mile)
382
378
432
374
400
27S
239
386
453
163
243
267
288
209
175
138
308
239
365
300
255
153
205
472
128
128
123
27
277
123
472
fled ian
size
'microns)
1730
1874
1264
1548
1584
1990
1258
21 56
1764
1916
1340
1034
1408
1318
1 148
890
1468
1328
1096
956
1310
808
981
1952
1344
1869
964
27
1418
808
2156
315
-------
I~?
Road Htree
t Dirt
street cleaning)
Days from
n s i sign. (
r 9 i r.
2.0
11.1
14-2
7.0
14.0
20. 1
27.0
34.9
4-4
2.6
9-6
2.2
1 -4
3-0
• 4
5-5
.8
1 -9
2.4
.8
4-7
7.6
4.6
6.0
1 -5
• 4
3-8
10.0
14.0
24.0
35-9
44-9
1-5
9-5
1 .6
35.0
9-58
.4
44-9
Load ing
Ib/curb-
mil e )
394
454
351
721
710
637
417
509
261
336
266
232
266
462
1 1 2
225
420
200
258
184
195
313
109
145
282
21 1
206
185
149
432
268
431
206
170
147
35
3iO
109
721
hed ian
size
( r. i c r o n s )
491
582
339
697
402
410
376
425
284
431
421
652
634
482
682
784
776
904
1352
836
967
645
694
497
21 1 7
1715
625
786
528
418
636
517
91 7
999
626
35
704
284
21 17
316
-------
Loadings >
Cample
10/2/SC
1 0/9
10/14
10/21
10/28
11/18
1/3/81
1/15
1 /20
1/27
2/5
2/20
2/26
10/19
1 1 /6
11/19
1 2/8
Count
Average
Minimum
Maximum
Downs -
eason, t
C a TT.pl e
Ident .
A-1Q1
A-200
A-2C7
A-21 4
A-223
A-257
A-254
A-264
A-269
A-273
A-285
A-2Q8
A-305
A-61 9
A-636
A-644
A-656
West. w o o d i: o^ e s
ic street clean
Days from
last sign. (
rain
2.5
,9
5-9
12.9
19.9
8.6
7.2
14-4
19.3
3-5
7-3
3-6
1 .2
10.6
9-5
1 .8
2-3
17.0
7.7
.Q
19-9
Road 3t
ir.r)
Load ing
Ib/curt-
mile)
517
538
318
270
519
906
125
462
206
229
515
240
229
368
283
241
182
17
362
125
906
reel Dirt
ived ian
si ze
(microns)
422
1084
866
934
67,'
>6370
990
1898
>6370
2858
1216
1142
1146
349
595
1543
1789
17
>12CO
0
>6370
317
-------
C i rr. i • 1 ^
Pa!,e
4/22/60
4/24
5/7
5/14
5/16
6/3
6/12
6/19
6/24
7/1
7/8
7/10
7/17
7/22
7/25
7/20
7/31
8/6
8/8
8/1T
8/15
8/19
8/22
8/25
8/29
9/4
9/9
7/7/81
7/10
7/14
7/16
7/21
7/27
8/4
8/7
8/12
8/14
8/19
8/21
8/25
8/28
9/2
9/4
9/8
9/11
9/14
9/18
9/23
9/29
Count
Average
M in imum
[laxiiriim
Cample
Ident .
A-31
A-35
A-43
A-55
A-62
A-71
A-79
A-89
A-93
A-99
A- 106
A-1 1 1
A-1 1 4
A-1 1 8
A-121
\-125
A-245(?)
A-132
A-1 36
A-1 37
A-143
A-1 46
A-147
A-151
A-1 54
A-1 56
A-1 60
A-524
A-528
A-529
A-533
A-539
A-542
A-547
A-552
A-554
A-557
A-562
A-564
A-566
A-572
A-573
A-578
A-580
A-585
A-587
A-592
A- 595
A-601
C'iy:i from
last si p,n .
rain
2.3
4-3
17.3
24-3
26.3
1 .4
10.3
2.7
7.7
6.0
13-0
15-2
5-7
10.6
13-6
•6.6
19-7
24-7
26.7
30.6
33-8
1 -3
4-3
6.3
1 .1
1.3
2.4
.4
3-4
• 9
3-0
8.2
14.0
22.0
24-8
29-8
31 .8
36.8
39-0
43-0
46. 1
1.3
3-6
7-4
10.4
13.4
17.4
1 -5
• 5
49-0
14
.4
46.1
rr. i 1 e )
434
444
705
671
467
451
544
721
552
774
577
6b4
558
673
920
358
731
627
753
801
711
552
497
478
350
386
428
156
138
132
196
261
331
302
297
273
243
219
299
241
326
157
235
271
271
287
350
207
206
49
443
132
920
F'ed ian
size
(fEicrons)
734
749
573
626
679
710
525
494
637
419
583
492
556
472
413
430
434
416
382
392
386
402
529
434
588
592
607
384
310
464
346
323
335
393
377
327
404
511
386
407
388
530
380
362
355
381
364
525
599
49
472
310
749
318
-------
:-10. Lake Hill.? Street Dili Loadings
(Vet season, no street cleaning)
"ample
Count
Average
Minimum
Maximum
Sample
I dent.
1 0/9/S1
10/16
1 C/1 9
10/26
1 1 /4
11/16
1 1/25
1 2/1
1 2/8
1 2/1 1
1 /I 4/82
A-60S
A-614
A-620
A- 627
A-631
A-641
A-650a
A-650
A-654
A -6 5 8
A-570
Bays fron
_ast sign.
rain
.6
7.5
10.7
17-6
7.5
1 .6
2.0
9-1
2.0
. q
3-0
11 .0
5-7
.6
17.6
Load ing
(Ib/curb-
mile)
233
218
241
319
249
338
201
344
238
257
1065
11
337
201
1065
size
(microns)
480
406
451
1012
1190
1010
1840
3690
1742
1606
1 1
1262
406
3690
319
-------
n ; I
3/11
3/13
3/16
3/13
3/13
3/20
3/20
3/24
3/24
3/25
3/25
3/27
3/27
V30
V~o
4/3
4/3
4/6
4/6
,|/9
4/^
4/10
4/13
4 /1 ?
4/15
4 /' 1 5
4/17
4/17
. 1
. R
474
2-1 (L^
2-184
p-T.Ofl
2 — ^O'"1
2- ^1 0
2-31 1
3-31 i:
3-~M6
S-^17
S-318
3-321
3-~,_'2
3-323
3-324
3-327
3-328
3-332
2-333
;-;_ •; 54
3-336
S-337
3-338
3-344
3-M6
3-347
3-343
3-^5
3-v>7
S-359
3-361
3-^65
3-367
3-^70
S-371
S-376
3-377
S-'778
3-382
3-384
R. 1
R. ^
5-6
5 • a
' . 5
.6
2.4
2.6
5-4
5-6
7-4
7.6
9-4
• 5
2-3
2 . 5
4-3
4-5
.8
1 .0
.2
• 3
2.2
2.4
5. 2
5- ?
-3
. 5
3-3
3-5
. 7
. q
1 .7
1 .4
1 .6
3-4
3-6
5.4
5-6
2 . }
. (.1
2.9
. 1
1 .8
. 1
1 .8
. 1
2 • 9
. T
1 • 9
. 1
1 .8
.1
l -9
. 1
1 -9
. 1
3-8
.1
,9
. i
1 -9
. 1
2-9
. 1
2.Q
. i
2-9
. 1
2.9
.0
• 9
2.9
.0
1 -9
.0
1 -9
.1
2b5
311
2'^
213
12S
172
1Q7
207
223
21 1
246
201
235
150
185
168
22^
233
374
144
134
143
167
166
267
141
159
136
150
156
1 1 1
130
135
164
170
195
156
21 1
21 1
T?C
324
257
237
484
308
276
24 1
26C
2-13
225
238
247
300
200
241
246
210
335
237
550
293
260
232
321
454
329
284
3^4
303
415
343
;29
>°0
301
312
263
262
263
320
-------
with street
4 '' J '
4 '21
-I/?7!
4/.:^
4/24
4/24
4 ' J7
4/"0
4 / : ^
S/ 1
5/1
S / 4
5/4
5/b
5/5
5/8
5/8
5/12
5/12
5/13
5/13
5/15
5/15
5/18
5/21
5/21
5/22
5/22
5/29
6/1
6/1
6/4
6/5
6/5
6/11
6/1 1
6/15
6/17
6/17
6/23
6/23
6/?4
6/24
6/26
6/26
6/29
6/29
7/1
7/1
Count
Average
i'i ni™ua
Kax imum
:j-;-"37
• •• ~ o o
O~ ,. ^l
,-- vl°
S-VTI
P--VD4
P-^b
t-3lr^
Jf— 401
n-403
?-41 2
S-4 1 5
0-417
S-41 ^
3-423
S-430
S-433
S-4-37
3-442
S-444
S-445
S-447
G-449
S-451
S-453
G-460
S-461
S-462
S-468
S-.<76
3-479
S-480
S-s84
S-486
3-43S
S-489
3-491
S-i93
S-4%
S-497
S-501
S-503
S-504
3-50'5
S-50<)
S-51 i
S-512
S--13
S-51 5
S-51 6
9-4
9-6
. 0
1 . 1
1 .9
2. \
4-9
.9
1 . i
2.9
3-2
.5
.7
2.5
2.7
• 5
.7
1 .2
1 .4
1 .2
1 .4
4.2
4.4
7.2
1 -9
2.0
2.7
2.Q
4.5
6.5
6.7
9-5
10.5
10.7
2-9
3-1
2.4
4.4
4-6
4.8
5-0
5-8
6.0
7.8
8.0
10.8
11 .0
.4
.6
97.0
4
.2
11 .0
3-9
, 1
1 -9
. 1
. q
.1
2-9
1-9
.1
'.9
.2
2-9
. I
1-9
.1
1 -9
.1
3-9
.1
• 9
.0
1-9
.1
2.9
2.9
.0
.7
.1
6.9
9-9
.0
2.9
3-9
.1
1.9
.1
2.9
1.9
.0
5.9
.0
• 9
.1
1.9
.0
2.9
.0
1.9
.0
97.0
1 .4
.0
9-9
101
1?S
117
115
110
154
1 so
103
109
130
107
62
175
227
184
132
134
158
155
I7b
189
99
122
161
123
128
115
133
188
198
209
88
130
125
290
174
237
15G
265
205
165
210
202
167
158
201
196
111
121
97
182
62
380
4R4
301
352
127
364
308
301
450
34 P
31 5
260
376
208
368
240
396
284
275
270
2%
265
324
256
376
400
326
306
262
340
282
324
474
365
294
465
304
285
276
332
422
280
346
240
289
291
319
298
402
344
97
318
210
550
321
-------
10/1 /
1 0
<0
/ i
10/10
1 0/1 ^
10/13
10/17
0/17
10/22
10/22
10/24
10/27
10/29
10/29
11/5
11/5
1 1/10
1 1/12
i/; 2
1/17
1/17
1/19
1/19
1/24
1/26
1 1/26
12/5
12/15
1/5/81
1/5
1/7
1/7
1/9
1/9
1/12
1/12
1/14
1/19
1 /19
1/21
1/28
1/30
1/30
2/2
3-202
S-^O7)
3-204
3-210
3-21 1
S-21 5
3-21 6
S-21 9
3-220
3-224
3-225
S-228
3-229
3-230
3-231
S-232
3-233
3-234
3-238
3-239
S-240
3-241
3-242
S-243
3-246
3-247
S-248
3-250
3-251
S-255
3-256
S-257
S-258
S-2C1
S-265
S-266
3-270
S-274
S-277
S-278
S-279
1 .4
1 .6
3.4
3 • 6
6.4
6.6
10.4
10.6
1'..4
13.6
17-4
17.6
22 . 4
22.6
24-4
27.6
2Q.4
29.6
1 -5
1 .7
1 -7
3-4
3-6
8.4
8.7
10.5
10.6
2.7
4-5
4-6
.7
10.7
4-5
4-6
6-5
6.7
8.5
8.7
12.5
12.7
14-5
19-5
19-6
21 .7
4.2
1 .0
1 .2
4-0
1 .8
. 1
1 -9
. 1
2-9
, 1
1 .8
. 1
3-0
. 1
3-9
1
4
.9
.6
.0
1 -9
. 1
6.9
.1
.0
1 .8
. 1
2.9
.1
1 -9
.0
. 1
1 -9
.1
2. 1
.0
9
0
4-9
.1
1 -9
2.9
.1
1 -9
6.9
.0
.1
1.9
1 -9
2.9
V'-o \ an
r, i z F>
( n i c r o n r )
220
239
22^-
200
244
2^0
216
214
124
148
182
1 QQ
198
21 1
212
201
250
235
167
123
130
150
148
161
147
1 10
112
112
108
121
159
145
261
210
144
179
270
197 '
242
214
187
1 94
191
162
138
109
310
185
^29
341
v, 1
279
28 i
2qQ
351
272
665
342
316
255
349
•MO
257
300
341
297
964
465
626
629
413
720
48S
>6370
473
461
755
491
679
464
455
316
592
375
421
340
348
314
4Q1
444
325
321
733
608
275
479
322
-------
'able B-1C. T.-ike Hills Street
(Wet season, with
Dirt LoadingBfcont
Si/rcpu c j. s t
Parple
Pate
••i ' --,
•"i / «
>- / '4
-,'4
2/'6
2/9
2 ,' 0
2/18
2/18
2/20
2/20
2/2?
2/2?
2/25
2/27
2/27
Count
Aver ape
M '. r, i mum
Maximum
Sample
Ident .
;T-280
S-281
?-2<-2
3-286
^ _ p Q 7
r>_ -^i QC^
S-29?
8-294
8-2^7
s-2Qq
t. -?CO
0-301
S-302
5-3C6
3-307
Days from
last sign.
rain
4-2
6.0
6 . 2
8.0
1 1 .0
1 1 .2
1 .4
1 .£
.q
1 .6
3-9
4- 1
.&
2-5
2.7
63-0
8.7
• 7
29-6
Days fron:
] qpt
clear, a ng
.1
1 -9
. 1
1-9
4.9
. 1
4-7
.1
1 .9
.1
2-9
.1
2.0
3-9
.1
63.0
1 .6
.0
6.9
Load inf
( lb/ curb-
mile)
";oo
190
.?15
277
274
186
277
195
298
224
269
194
166
190
436
63
200
108
436
Kedia.i
si ze
(microns )
256
2QO
229
326
384
336
427
424
339
304
264
293
355
324
264
62
>405
229
>6370
323
-------
(Ib/curl -
A-34;/ 1.4 ^0 335
A-;*54 2.0 255 4C6
A--68 1 .0 300 399
A-380 4.7 407 417
4/23 A-~92 1.2 401 6°6
^/1 A-414 3-1 294 411
5/S A-436 .7 225 413
5/28 -\-474 3-2 268 ^32
6/5 A-487 11.1 116 866
6/12 A-4-92 .3 286 403
6/25 A-507 7.1 429 41^5
7/2 A-517 1.5 162 236
7/10 A-527 3-0 115 382
7/16 A-532 2.8 V?1 401
7/23 A-540 10.0 162 395
'f/26 A-545 H.9 216 510
8/6 A-549 23-9 198 319
8/13 A-556 30.9 196 524
8/20 A-563 37-9 191 422
8/27 A-568 43-9 180 412
9/3 A-577 2.4 270 366
9/10 A-584 9-4 214 279
P/17 A-591 16.4 233 248
Count 23.0 23 23
Average 3-1 273 447
Minimum .3 115 236
Maximum 43-9 429 866
324
-------
;-• L7~14- 148th Avr. ?K Street Dirt Loadings
(Wet season, no street cleaning)
cample Sample Days from Loading Median
Tite Ident. last si^n. (ib/curb- size
r&in mile) (microns)
10/1/81 A-604 2.2 234 329
10/16 A-615 1-6 124 439
11/10 A-638 13-4 174 548
12/17 A-664 1.8 487 446
1/14/81 A-669 2.8 1588 1135
Count 5.0 5 5
Average 5-6 521 579
Minimum 1.8 124 329
Kaxirr.um 13-4 1588 1135
325
-------
Table B-14a STREET DIRT QUALITY: SURREY DOWNS -
Particle Size (Microns)
CO
no
mg/kg
date COD
3/3 - 5/25/80
5/26 - 7/14
7/14 - 9/15
9/15 - 11/24
11/24 - 2/2/81
2/2 - 4/13
4/13 - 7/2
7/3 - 9/18
9/23 - 11/20
11/24 - 1/16/82
mean
standard deviation
stand, dev./mean
mg/kg
date TKN
3/3 - 5/26/80
5/26 - 7/14
7/14 - 9/15
9/15 - 11/24
11/24 - 2/2/81
2/2 - 4/13
4/3 - 7/2
7/3 - 9/18
9/23 - 11/20
11/24 - 1/1G/82
mean
standard deviation
stand, dev./mean
<63
120,000
156,000
177,000
185,000
157,500
188,000
198,000
239,000
186,000
182,000
179,000
31,000
0.17
602
2770
3100
2890
2175
2950
3950
4620
3055
3130
2920
1050
0.36
63-
125
129,000
124,000
167,000
141,000
112,000
131,000
166,000
217,000
140,000
135,000
146,000
30,200
0.21
2280
2400
2290
1570
1710
2080
3710
5350
2180
1880
2550
1150
0.45
125-
250
76,600
88,900
122,000
93,500
97,100
86,600
128,000
185,000
88,000
79,200
103,400
32,300
0.31
196
1310
2070
2520
1200
1260
2400
3800
1180
900
1680
1030
0.61
250-
500
41,400
43,500
97,300
98,300
103,000
80,700
145,000
182,000
86,400
65,400
94,300
43,200
0.46
182
1110
1310
1420
1050
1260
i930
3010
1040
430
1270
780
0.62
500-
1000
59,000
43,500
116,000
125,000
202,000
174,000
167,000
196,000
107,000
82,600
127, /OO
56,100
0.44
182
545
1270
1615
1830
1660
1950
3140
1270
770
1420
830
0.59
1000-
?000
15:, ooo
269,000
19?, 000
/22,000
275,000
184,000
161,000
240,000
156,000
55,200
190,200
6-1,400
0.39
910
QS<5
1420
1940
2330
1700
1880
2685
1490
915
1620
610
0.37
2QOO-
6150
113,000
90,000
171,000
?63,00n
221 ,'^n
177,'o'^n
171,000
233,000
171,000
6-1,700
167,800
63,?00
0.33
1°,9
636
1040
1730
1600
1230
1750
1390
1560
1044
1?30
506
0.41
• f, ~> "-, o
3 1 ". .'""I
» '
11 VV;1
°17,nnn
?15,V'T
6? 1 //in
7R?
3^10
?s^o
1470
P10
o. .,?
-------
Table B-14& STREET DIRT QUALITY: SURREY DOWNS - MAIN B<\SIN (cnnt.'
Particle Size (Microns)
mg/kq
date Total Phos
3/1 - 5/26/80
5/26 - 7/14
7/14 - 9/15
9/15 - 11/24
11/24- 2/2/81
2/2 - 4/13
4/13 - 7/2
7/3 - 9/18
9/23 - 11/20
11/24 - 1/16/82
mean
standard deviation
s tand . de v . /mean
'63
835
893
240
889
476
887
934
1080
1065
971
830
265
0.32
63-
125
597
571
429
649
273
665
625
887
723
627
605
165
0.27
125-
250
319
366
517
499
329
525
472
703
475
425
465
113
0.24
250-
500
331
313
396
430
420
443
412
595
432
375
415
77
0.19
500-
1000
419
347
393
569
627
356
546
569
504
385
480
117
0.24
1000-
2000
553
605
975
807
629
749
621
728
552
651
690
131
0.19
2000-
63SO
689
763
1030
755
641
772
813
654
618
690
750
133
0.13
- 6350
7Q°,
616
971
93'
73'
600
730
61?
697
686
740
127
0.17
mg/kg
date Lead
3/3 - 5/26/30
5/26 - 7/14
7/14 - 9/15
9/15 - 11/24
11/24 - 2/2/81
2/2 - 4/13
4/13 - 7/2
7/3 - 9/18
9/23 - 11/20
11/24 - 1/16/82
mean
standard deviation
stand. dev./mean
1400
1600
1800
1500
1100
1100
1200
1500
1500
1500
1420
?25
0.16
1100
1400
1600
1400
1100
680
1100
1400
1200
1100
1210
255
0.21
985
1200
1400
1200
970
720
920
1200
1000
910
1050
200
0.19
600
810
905
820
1100
470
670
990
1100
930
840
210
0.25
550
470
1200
440
520
355
430
1200
1000
620
680
330
0.48
280
340
540
280
400
230
330
790
790
220
420
216
0.51
190
180
240
130
585
150
210
330
130
210
235
136
0.58
180
110
92
?00
900
120
640
58
182
350
'80
276
0.98
-------
Table B-14a. STREET DIRT QUALITY: SURREY DOWNS - MAIN BASIN (cont.)
OJ
fX)
CD
mq/kg
date Zinc
3/3 - 5/26/80
5/26 - 7/14
7/14 - 9/14
9/15 - 11/24
11/24 - 2/2/81
2/2 - 4/13
4/13 - 7/2
7/3 - 9/18
9/23 - 11/20
11/24 - 1/16/82
mean
standard deviation
s tand . dev . /mean
< 63
287
270
379
412
252
259
292
371
340
308
317
55
0.18
Par
63-
12!')
224
247
288
354
239
188
239
295
264
232
257
46
0.18
tide Size1
125-
250
189
228
230
248
199
125
220
246
196
185
207
37
0.18
(Microns)
250-
500
131
178
154
194
121
126
182
210
182
135
168
29
0.17
500-
1000
152
168
170
133
151
120
135
194
213
154
159
28
0.18
1000-
2000
102
117
98
137
147
116
101
181
118
99
122
27
0.22
2000-
6350
327
87
67
82
120
72
75
88
85
97
110
78
0.71
^ "i 5 0
85
80
74
10?
176
6n
64
75
116
150
99
33
0.38
-------
Table 8-15 STREET DIRT QUALITY SURREY DOWNS - 108th AVEN'IE
Particle Size (Microns)
CO
ro
mg/kg
date COD
3/3 - 5/26/80
5/26 - 7/11
7/14 - 9/15
9/15 - 11/24
11/24 - 2/2/81
2/2 - 4/13
4/13 - 7/2
7/3 - 9/18
9/23 - 11/20
11/24 - 1/16/82
mean
standard deviation
stand, dev./mean
mg/kg
date TKN
3/3 - 5/26/80
5/26 - 7/14
7/14 - 9/15
9/15 - 11/24
11/24 - 2/2/81
2/2 - 4/13
4/13 - 7/2
7/3 - 9/18
9/23 - 11/20
11/24 - 1/16/82
mean
standard deviation
stand . dev . /mean
<63
122,000
139,000
128,000
.. 140,0v,0
179,000
141,000
148,000
142,000
149,000
189,000
147,700
20,900
0.14
1680
1440
300
1640
2583
1735
1980
1930
2020
2710
1800
663
0.37
63-
125
92,500
21,200
262,000
69,600
132,000
86,700
88,200
81,400
90,600
118,000
104,200
62,700
0.60
665
2100
882
859
1760
1060
1230
1150
1090
1440
1220
436
0.36
125-
250
48,700
42,000
37,450
36,600
105,000
57,300
51,300
35,200
61,400
59,700
53,500
20,600
0.38
315
889
341
451
2550
545
595
2480
580
902
965
840
0.87
250-
500
47,200
26,000
28,400
27,400
62,800
36,800
33,900
26,400
27,600
45,100
36,200
12,100
0.34
266
470
236
293
713
367
296
453
327
653
407
164
0.40
500-
1000
28,500
16,000
25,200
29,300
84,700
40,500
23,200
20,200
37,800
62,000
37,200
21,000
0.57
245
833
221
276
743
A33
291
208
654
668
457
243
0.53
1000-
2000
23,600
20,400
20,100
24,100
85,800
36,900
11,600
24,900
63,900
58,200
36,900
24,200
0.65
168
105
207
150
868
442
244
209
442
565
340
239
0.70
2000-
6350
53,800
204,000
19,400
23,600
85,100
47,600
19,100
14,600
70,700
13,700
55,200
58,000
1.05
133
147
67
120
720
348
285
164
439
515
29*
211
0.72
-6350
7.3,000
?13,ono
18,400
17,^00
151,000
33,400
Id, 000
13,800
65,400
95,700
69,600
67,300
0.97
98
140
281
96
1340
245
223
145
532
409
351
375
1.07
-------
Table B-15 STREET DIRT DUALITY SURREY DO'-INS - 108th AVEN'IE (cont.)
Particle Size (Microns)
CO
o
mg/kg
date TP
3/3 - 5/26/80
5/26 - 7/14
7/14 - 9/15
9/15 - 11/24
11/24 - 2/2/81
2/2 - 4/13
4/13 - 7/2
7/3 - 9/18
9/23 - 11/20
11/24 - 1/16/32
mean
standard deviation
stand, dev./mean
<53
661
539
686
672
417
706
666
748
840
972
691
151
0.22
63-
125
40?
1080
473
472
360
461
389
463
455
502
506
207
0.41
125-
250
287
316
236
314
369
389
320
334
413
354
333
51
0.15
250-
500
275
316
182
325
393
306
204
268
:C5
382
304
73
0.24
500-
1000
393
367
193
384
446
418
402
295
440
461
380
81
0.21
1000-
2000
576
601
365
673
67^
672
680
6G2
573
767
619
108
0.17
2000-
6350
630
531
332
766
664
726
712
625
475
883
639
154
0.24
-6350
62B
470
135
791
610
767
617
624
731
739
616
179
0.29
mq/kg
date Lead
3/3 - 5/26750"
5/26 - 7/14
7/14 - 9/15
9/15 - 11/24
11/24 - 2/2/81
2/2 - 4/13
4/13 - 7/2
7/3 - 9/18
9/23 - 11/20
11/24 - 1/16/82
mean
standard deviation
stand. dev./Tean
2000
2250
1600
2200
1100
1100
1500
1700
1300
1500
1630
416
0.26
1900
2100
1600
1800
850
945
1100
1600
1100
1100
1410
442
0.31
1600
2100
1800
1500
870
840
1300
1300
1000
1200
1350
407
0.30
980
1100
770
1200
900
570
920
1100
800
720
910
196
0.22
1000
500
700
610
590
350
320
930
259
400
566
253
0.45
350
320
400
200
300
140
165
190
139
170
237
96
0.40
130
190
92
88
230
140
210
95
87
76
131
37
0.42
55
52
48
42
230
280
30
30
65
77
91
88
0.97
-------
Table B-15 STREET DIRT QUALITY SURREY DOWNS - 108th AVENUE (cont.)
Particle Size (Microns)
CO
CO
mg/kg
date Zinc
3/3 - 5/26/80
5/26 - 7/14
7/14 - 9/15
9/15 - 11/24
11/24 - 2/2/81
2/2 - 4/13
4/13 - 7/2
7/3 - 9/18
9/23 - 11/20
11/24 - 1/16/82
mean
standard deviation
s tand . dev . /mean
<63
262
296
233
332
257
250
249
264
310
283
274
31
0.11
63-
125
233
260
192
210
172
180
179
192
228
226
207
29
0.14
125-
250
191
188
131
197
176
131
120
151
164
142
159
28
0.18
250-
500
137
114
109
156
128
99
91
124
122
111
119
19
0.16
500-
1000
123
229
89
151
122
109
92
170
115
101
130
43
0.33
1000-
2000
112
103
110
105
118
254
171
90
99
111
127
50
0.39
2000-
6350
69
75
62
77
106
?83
82
89
76
79
99
65
0.66
>'o350
70
50
53
108
98
861
61
56
62
64
148
251
1.7
-------
Table B-16 STREET DIRT DUALITY: SURREY DOWNS - Wd'-:TWOOn
Particle Size (Microns)
mq/kq
date COD
5/26 - 7/14/80
7/14 - 9/15
9/15 - 11/24
11/24 - 2/2/81
2/2 - 4/13
4/13 - 7/2
7/3 - 9/18
9/23 - 11/20
mean
standard deviation
stand, dev./mean
mq/kq
date TKN
5/26 - 7/14
7/14 - 9/15
9/15 - 11/24
11/24 - 2/2/81
2/2 - 4/13
4/13 - 7/2
7/3 - 9/18
9/23 - 11/20
mean
standard deviation
s tand . dev . /mean
<63
132,000
166,000
173,000
168,000
208,000
242,000
249,000
175,000
189,000
40,400
0.21
2680
2990
2780
2130
3270
4550
4930
3160
3310
953
0.29
63-
125
159,000
164,000
162,000
144,000
212,000
226,000
274,000
167,000
188,500
44,500
0.24
2290
3290
2290
1710
2940
4740
6000
3295
3320
1420
0.43
125-
250
124,000
205,000
87,000
165,000
143,000
169,000
232,000
114,000
154,900
48,000
0.31
1200
1900
1370
1400
2130
3450
4830
1810
2260
1260
0.56
250-
500
146,000
193,000
80,000
175,000
166,000
178,000
185,000
91,900
151,900
43,100
0.28
575
1140
1250
1550
2040
2350
3190
1290
1670
822
0.49
500-
1000
155,000
161,000
160,000
152,000
215,000
173,000
198,000
169,000
172,900
22,300
0.13
2480
1470
1760
1680
1490
2240
2580
1830
1940
43L
0.22
10DO-
2000
348,000
259,000
183,000
367,000
339,000
170,000
252,000
282,000
275,100
73,900
0.27
2900
1770
1980
2280
2230
3530
2730
2^40
2470
563
0.23
?000-
6350
~h4,0< .0
7)5,000
3fi",000
367,000
214,000
124,000
245,000
320,000
293,900
95,000
0.32
653
1Q90
2340
6160
1 7 30
1590
1820
3110
2420
1660
0.63
63^0
4V/ ,.'.',0
J9c nOO
36 l! 000
7 33, ''no
457,000
117,01,0
161, one
640,000
373,900
?34,?00
0.62
437
408
?050
21QO
?4nn
773
1170
48SO
17RQ
1470
0.83
-------
Table B-16. STREET DIRT QUALITY: SURREY DOWNS - WESTWOOD HOMES ROAD (cont.;
Particle Size (Micronc)
OJ
CJ
mq/kg
date TP
5/26 - 7/14
7/14 - 9/15
9/15 - 11/24
11/24 - 2/2/81
2/2 - 4/13
4/13 - 7/2
7/3 - 9/18
9/23 - 11/20
mean
standard deviation
stand, dev./mean
mg/kg
date Lead
5/26 - 7/14
7/15 - 9/15
9/15 - 11/24
11/24 - 2/2/81
2/2 - 4/13
4/13 - 7/2
7/3 - 9/18
9/23 - 11/20
mean
standard deviation
stand . dev . /mean
< 63
855
489
810
619
771
875
1010
1060
810
189
0.23
375
400
390
440
415
600
560
340
440
92
0.21
63-
125
853
359
652
436
570
758
994
846
684
220
0.32
321
320
300
350
350
380
400
250
334
47
0.14
125-
250
393
511
—
389
410
584
509
520
474
76
0.16
250
260
205
230
210
370
300
160
248
64
0.26
250-
500
1250
346
341
572
352
417
529
391
525
305
0.58
140
215
140
190
160
180
210
190
173
29
0.16
500-
1000
424
470
718
772
4?4
403
497
521
529
140
0.26
580
89
75
200
75
94
83
115
164
173
1.1
1000-
?ono
573
627
642
519
567
538
610
584
581
43
0.07
1900
59
60
170
89
52
145
71
318
641
2.0
2000-
6350
740
657
609
546
569
668
658
654
638
61
0.10
55
34
35
160
50
27
37
30
54
44
0.82
6 ISO
R29
780
r.PS
• t ' i ~~\
45',
653
69°,
499
619
146
0.24
32
23.
52
360
80
39
24
62
84
113
1.35
-------
Table 3-16.
Street Dirt Quality: Surrey Downs
Homes Rrl. fcon't)
Particle Size (Micron:;)
OJ
p.
mq/kq
Date Zinc
5/26-7/14
7/14-9/15
9/15-11/24
11/24-2/2/81
2/2-4/13
4/13-7/2
7/3-9/18
9/23-11/20
mean
standard dev.
stand, dev. /mean
-63
177
152
169
162
160
209
228
177
179
26
0.15
63
-125
158
112
127
121
130
155
177
139
140
2?
0.16
125
-250
96
75
92
102
99
126
115
82
98
17
0.17
750
-500
69
88
71
87
87
79
89
68
80
9.2
0.11
500
-looo
94
58
66
88
66
74
72
81
75
12
0.16
inoo
_'X)00
195
81
76
100
U5
67
88
108
99
?6
0.26
20^0
-6350
P,5
IS
&3
108
m
63
63
64
74
30
0.41
^ -J -, )
C T
\ '^
1\
1 f, 1
1 ''6
oo
c r
7^
qc,
51
n.6o
-------
Table B-17.
Street Dirt Quality: Lake Hills
CO
CO
CJ1
Particle Size
mg/kg
Date COD
3/3-5/26/80
5/26-7/14
7/14-9/i5
9/15-11/24
11/24-2/2/81
2/2 - 4/13
4/13-7/1
7/3-9/18
9/23-11/20
11/24-1/16-82
N=10
mean
standard dev.
stand, dev. /mean
mg/kg
Date TKN
3/3-5/26/80
5/26-7/14
7/14-9/15
9/15-11/24
11/24-2/2/81
2/2-4/13
4/13-7/1
7/3-9/18
9/23-11/20
11/24-1/16/82
mean
standard dev.
ta nd . dev . /mean
<63
310,000
201,000
231,000
249,000
134,000
190,000
206,500
274,000
240,000
242,000
232,800
39,400
0.17
4170
3420
3230
3750
2750
2600
3540
4440
3965
3165
3500
590
0.17
63
-125
322,000
152,000
147,000
174,000
131,000
99,500
159,000
246,000
164,000
176,000
177,100
63,200
0.36
3760
3560
3100
3120
1770
1590
3270
5040
2730
3560
3150
990
0.31
125
-250
98,800
129,000
130,000
122,000
83,800
79,400
88,700
137,000
105,000
152,000
112,600
24,900
0.22
2600
1870
2160
1950
974
1040
2380
3070
1490
1520
1910
670
0.35
250
-500
62,200
111,000
150,000
98,700
98,800
57,500
97,000
149,000
82 , 800
106,500
101,400
30,900
0.30
1660
1750
2270
1550
962
806
1620
2820
1375
1240
1610
590
0.37
(Microns)
500
-1000
199,000
175,000
316,000
253,000
156,500
101,000
120,000
296,000
191,000
301,000
210,800
77,000
0.37
2420
2180
3160
I960
1325
1060
2010
4225
2330
2680
2340
900
0.38
1000
-2000
154,000
171,000
244,010
176,000
154,000
151,000
251,000
344,000
366,000
385,000
239,600
93,900
0.39
2380
833
2610
1750
1420
1790
2890
1440
2410
3590
2110
820
0.39
2000
-6350
171,000
234.010
330,000
1 96 , 000
161,000
132,000
230,000
426,000
269,010
453,000
266,000
105,500
0.40
504
2020
2470
1270
1310
2240
2700
1510
22UO
3960
2010
950
0.47
• 6351
11, '•
-------
Co
CO
CTi
Table B-17.
Street Dirt Quality: Lake Hills (con't.)
Particle Gize (Microns)
mg/kg
date TP
3/3-5/26/80
5/26-7/14
7/14-9/15
9/15-11/24
11/24-2/2/81
2/2-4/13
4/13-7/1
7/3-9/18
9/23-11/20
11/24-1/16/62
mean
stand, deviation
stand, dev./mean
tng/kg
date Pb
3/3-5/26/80
5/26-7/14
7/14-9/15
9/15-11/24
11/24-2/2/81
2/2-4/13
4/13-7/1
7/3-9/18
9/23-11/20
11/24-1/16/82
lean
;tand. deviation
stand, dev./mean
'63
1060
950
614
921
738
876
832
1103
1390
938
942
213
0.23
2600
2300
1600
2100
1700
1500
1350
2300
2100
1400
1895
439
0.23
63
125
1370
718
444
730
500
634
656
904
842
615
741
261
0.35
2300
2300
1900
1900
1500
1300
1700
2300
2000
1400
1860
378
0.20
125
250
663
443
522
522
393
480
450
795
649
533
545
123
0.22
1800
2000
1800
1800
1200
1100
1800
2200
1700
1100
1650
384
0.23
250
500
522
340
251
425
467
499
221
546
652
439
436
134
0.31
1600
1800
]400
1500
670
970
1100
1700
1400
1000
1310
364
0.28
500
1000
650
557
135
537
600
537
550
913
623
598
570
189
0.33
820
750
UOO
1000
540
770
840
1600
710
530
866
313
0.36
1000
2000
744
661
1230
620
646
702
752
866
607
793
763
183
0.24
360
700
800
820
520
470
690
850
240
870
632
222
0.35
20^0
6351
621
6°/J
1220
642
636
793
709
743
613
732
740
179
0.24
3.10
260
210
200
280
250
170
1100
150
515
347
284
0.82
'I, 3 51
c - j
411
1 n 1 r
?'< -
53"i
656
fT'O
li''1]
6r
85'J
750
2Y)
0.32
130
140
130
160
503
110
130
100
240
420
210
140
0.67
-------
OJ
LO
Table B-17.
Street Dirt Quality: Lake Hills (cont.'
Particle Size (Microns)
mg/kg
Date Zinc
3/3-5/26
5/26-7/14
7/14-9/15
9/15-11/24
11/24-2/2/81
2/2-4/13
4/13-7/1
7/13-9/18
9/23-11/20
11/24-1/16/82
mean
stand, deviation
s tand . dev . /mean
<63
502
314
339
438
310
342
316
420
416
333
373
66
0.18
63
-125
347
320
370
382
249
234
322
383
400
267
327
60
0.18
125
-250
282
255
335
277
272
192
246
343
320
216
274
49
0.13
250
-500
270
196
225
236
182
144
219
281
283
165
220
49
0.22
500
-1000
179
145
254
183
155
143
164
197
136
168
177
32
0.18
1000
-2000
147
j.27
141
159
175
130
146
179
128
440
177
94
0.53
2000
-6350
90
97
145
103
143
89
91
283
135
151
133
59
0.44
-5350
79
75
121
109
231
63
77
93
1°,9
277
137
32
0.60
-------
Table B-18.
Street Dirt Quality - 148th Ave.
Particle Size (Micr"nc)
mg/kg COD
4/13-7/1/Sl
9/23-11/20
N=2 mean
mg/kg TKN
4/13-7/1/81
9/23-11/20
mean
mg/kg TP
4/13-7/1/81
9/23-11/20
mean
rnqj/kc^ Lead
4/13-7/1/81
9/23-11/20
mean
mq/kq Zinc
4/13-7/1/81
9/23-11/20
mean
,63
153,000
167,000
160,000
1750
1530
1640
603
878
740
2400
3500
2900
437
531
480
63-125
83,600
102,000
93,800
993
941
967
319
614
470
2400
3000
2700
317
379
350
125-250
52,100
40,300
46,200
601
432
517
427
387
410
2200
2300
2250
208
251
230
250-500
45,500
36,600
41,100
419
520
470
245
384
315
2UOO
2500
2250
170
273
220
500-1000
66,900
138,000
102,000
986
1030
1010
3b7
456
410
1300
2000
1650
141
186
160
1000-2000
77,300
209,000
143,000
727
1270
1000
624
499
560
320
545
430
102
205
150
2r.iOn_ P,:5Q
09 ir/j
267,000
1 73 , 000
1030
1060
1050
755
491
620
150
170
150
73.5
94.1
84
C ")'r
! r 7 , ' '
2^'J>/:/
'9V>V.
'i 1 9
572
500
5? 3
50 5
450
89
535
310
54 . 3
93.3
74
-------
FIGURE B-1
CO
CO
SURREY DOWNS-WE5TWOOD HOME5 RD DIRT RCCUM
1000r
-I I I I I I I I I I I I II I II I II II 111 L J I I I I I I I I I I I I I I I i I
10
20 30
RCCUMULflTION (Days)
40
50
-------
FIGURE B-2
SURREY DOWNS-.108th ST. STREET DIRT flCCl'M
] 400.
E
_O
3
U
\
U
_D
in
o
in
d
40
200_-
0 R I I I I I I I I I I I I I I I I I I I I I I I I I I
10
I II I I I I I
20 30
RCCUMULRTION (Days)
40
-------
CO
-e.
FIGURE B-3
LfiKE HILL5-WITHOUT STREET CLEflNING
1200
e.
i
.a
w
-O
in
o
in
oc
o
0
10
0 H I I I I M I I I I I I I I I I I I | I I I II I I I I I I I I I I I I I I I I I I I
20 30
RCCUMULRTION (Doys)
40
50
-------
FIGURE B-4
LRKE HILLS-HITH STREET CLERNING
500
400
'a)
E
1
-D 1
L
3 30D_J
X,
U1
-O 1
in
2 20QJ
o
|
a: i
i-
£ 1CO_
0
3
E B Q
t-
M
^" QA 0 B
l~* A A A
15 ^ A
1 - . ej . J
^ n ft0 , n^^., ^r-
s n w o r ^ f A ^ ^ O n E Q L V j f ' tJ ' j O i ,
.-|— n r- 1 1'J WL-L.-DC-CJO'^'li1-1 ji^-1 L / ^J - "-* -J ^ f7)
1 0___-— *-- A- A---'- A 0 "
f ? Q A Q Fl •
L? A
HA A
%B i Q 1 A H
«Q Q @ |A A Q
— B
— Q
o 4 5
RCCUMULRTION (Days)
-------
FIGURE B-5
148th five. 5.E. STREET DIRT RCCUMUlflTI0r
1600.
14Dfl=_
£
-O
U
w
~ 800_E
un
a
o
in
60
40
200.
cz—or
— a
a-*
*#S
.Q ti
^ B
0 B i i i i i i i i
_LL
dry season, no cleaning
0 ET 1
10
I I I I I I I I I
I I I I I I 1 I I
23 30
fCCUMULRTION (Days)
50
-------
FIGURE B-6
WET SERSC'N PflRTICLE SIZE DISTRIBUTION
UJ
M
UJ
t — i
g 20
Q_
Z
i — i
un 1C
Q 15
t— <
— i
o
to
i
£ 10
°
.
o
i- 5
LU
LJ
a;
LU
Q_
0
— WB
gjiji^
Hf"
-
a
,
j
-
A
<63
_
iilll
[§l!n
Sllil
Ji;
^
i
—
3
4
63-
.—
1
tlmi
SL
MS
n
K*|
icj
ilml
1'
2-
—
J
-
*
125-
~
1
^
3
4
250-
.— 1
I
1
i
i
I
1
1
1
1
11
1
11
Ml'
-,
i
3
&
500-
1
1
If:
1
HI
|1
ill
fjjjl
JJM
_l
p
1
~1
z
—
3
4
1000-
1
il
1
8
|S
1
ii">
fi
~
m
*l|(
i
§}| .
y
p.-
"~|
'
3
4
2000-
K«
|
L
i
-,
.^
>6370/u
[T]- 108th
LH
-------
3500
FIGURE B-7
KN CONC. BY PflRTICLE SIZE (mg/kg)
^ 3 A
I 13 A
I t 3 A
i i 1 4
63- 125-
Q}- 108-th
25Q-
500-
1000-
2000-
>6350y
- 148-th
-------
UJ
-C»
en
FIGURE B-8
TOTRL PH05. CONC. BY PRRTICLE SIZE
1000
90
63- I 125-
jTj- 108th
2 3
250-
(mg/kg)
500- 1003- 2000- >6350/u
ra-LH m-1 48-th
-------
-p.
—t
ZINC CONC.
500
F«GURE B-9
3Y PflRTICLE SIZE (Mg/kg)
1134
n
! 1 3 4
n
I 2 3 -I !
63- 125-
[TJ-108ih
25(3-
500-
-L 3 4
1000-
"' I lit
2000- i >6350/u
-------
FIGURE B-10
.URRtFY DOWNS WflSHOFF BY
900
800_
70CL
f 600L
f
^ 50CL
-Q
o
••*•
40
30
o
3T
in
cr
m 20C
10Q_
A
Q
A "
O O
g> A
O ^ A
^° *
O
O
A A
A
a
LOAD INC; ir.CRr.AS>:
3 3.5' 4 4.5 5
0 Su ; i" (.•'/ Downs
o
A
5.5 6 6.5 7 7.5 8 8.5 9
RUNOFF VOLUME Mn+10 Inches)
9.5 10
1C.5 11
A 108th St.
B Westwood Homos R-l.
-------
FIGURE B- 1 1
LflKE HILLS & 148th flVE WflSHOFF Bv RuNCFF
700
6
J3
60C
50
400_
30C
xf
O
i:
1/1
ct
20
IOC
LOADING DLCRLASi;
NO WASIiOFF
3.5 4 4.5 5
0 o
o
a o
o
o
...Q.
LOADING INCREASE
5.5 6
6.5 7 ' 7.5 8 8.5 9
9.5 10
Lake Hills RUNOFF VOLUME Mn+10 Inches)
148th Avo. S.L.
-------
FIGURE B- 1 2
SURREY DOWNS RUNOFF VS
7.5
E
I
_D
U
X
_Q
c
a:
o
cr
a
i—*
in
6.7_
6.3_
5.9_
5.5.
5.1
4. 1
4.3
O
8
o o
A o o n fe
LORD
O 0* °
A
o
a
B
4 5
Surrey Do.vns
678
RUNOFF (10+In Inches)
11
-------
FIGURE B- 1 3
C-J
LTJ
LflKE HILLS & 148th RUNOFF VS RE5IDURL LORD
5.9
5.
•p 5.;
u
N,
O
-------
FIGURE B-14
Co
Ln
SURREY DONN5 PERK RRIN INT V5 RE:
Pi
n i
6.9
fll r
^_ O.
16-
3 6-
2 6.
c
C 5.
in 5.
a
i—i
c 5'
in
_j 5.
a:
t—
P 4.
in
UJ
a;
4.3
B
e
a
o
A
0
O
o
0
O
e
e
A
B
6.4 6.8 7.2 7.6 8 8.4
PEflK 30-MIN. RRIN INTENSITY (10+ln
Surrey Downs
108th St.
Homes Rd.
o
A
8.8
9.2
9.6
-------
FIGURE B-1 5
LRKE HILLS & 148th PEflK RRIN V5 RESIDURI
6.9
2-
a
vn 4>S-
^ 4.3
0
— Q B °
O O
P3 0 0
— ~- t-.
V)
B ©
• *"^ ©
0
00
&
0
0 0
0
0 0 © e
G
&
6.6 6.9 7.2 7.5 7.8 8.1 8.4 8.7 9 9.3
. Lake Hills PEflK 30-MIN. RRIN INTENSITY (10+1 n inches/hour)
B 148th Ave. S.E.
9.6
-------
FIGURE B- 1 6
L
55
50
OJ
•j: 45
E
1
-Q
^ 40
u
-° 35
£ 30
Q
" .
>\.$/^^''*^-'--~^*^ ...... - -- ' "" ""
^^^r1''^ '"""" *°
5 '10 15 20 25 30 35 40
INITIRL STREET LORDING (1b/curb/m11e)
45
50 55
-------
FIGURE B-17
CO
Ol
en
LflKE hi ILLS STORM WR5HOFF: 63-125 microns
45
e
i
J3
L
3
U
X
.£)
d
a:
o
UJ
UJ
ce
in
cc
a
i—*
in
LU
10 15 20 25 30 35
INITIflL STREET LORDING (Ib/cu. b-mlle)
40
45
-------
FIGURE B-18
CO
ui
en
LRKE HILLS STORM NR5HOFF: 125-250 micron
75 . . . . .
E
I
-Q
L
U
X.
-0
LD
Z
cr
o
UJ
LU
U1
_J
cr
o
in
LU
CkT
70_
65_
60_
55_
50_
45_
40_
35_
30_
25_J
20_
15.
10_
5 .
0
/
-V-
Wo ''
Q)
X
' / ' x-
/ //'/ x .x-'
/ e-. » ,..'•
/ // •' X ^
Q3' 'O
Q) O •'
"V
/
o
0 '5 '10 15 20 25 30 35 40 45 50 55 60
INITIflL STREET LORDING (Ib/curb-mlie)
65 70 75
-------
FIGURE B-19
OJ
c_n
LflKE
100
HILLS STORM WflSHOFF: 250-500 microns
E
I
JO
3
U
t_D
(X
o
UJ
UJ
tki
in
-------
FIGURE B-20
UJ
en
30
.RKE HILLS STORM WflSHOFF : 500
103
mcrons
90
80_.
JD
70.
50.
Q
cr
UJ
40
£ 30.
i—
in
o^ 20.
Q
f—I
uj 10.
a;
GO
^ ° e0 °
V-
\S'r-
10 20 30 40 50 60 70 80
INITIflL STREET LORDING (1b/curb-mMe)
90
-------
FIGURE B-2 1
cn
.O
LRKE HILLS STORM HflSHQFF:1000-2000 micron
60
55_
QJ
~ 50
£
1
-P 45
L ^v ..ox
r"\/ /-V ,A" ^ V ^0
-^ *v" \" _%
S. ' v . Cj t\ ' ,,v
"fu rx°'" * ^ oCl^-5*'
c-'." r? (0° • ,-T^'
.- " ^ x ° rv-. " ' °
,0 1°
c,VVO^
/ O, - -T\^>
/' \"xl t
»a'-Q
i,v>
/ / •'•
//
••' x '
X n /-'
f ^"^
s'
° ° "°" '"
I
0"
,
a 0 o
/ / 0 0 Q
/ - ox , e
/ ' / J*nf> ^
— / / d**3* «'
/''/''-' ''"
^£-r- ]
_
0 '5 1(3
15 '20 ' 25
INITIRL STREET LORDING (Ib/curb-mlle)
50
55
60
-------
LRKE
60
I-IUURE B-22
HILLS STORM WflSHOFF:2000-6350 micron
E
I
-O
L.
U
•x
-O
Q
d
O
UJ
a;
h-
ui
cr.
55.
50_
45.
40-
35.
30_
25.
2G_
15_
10_
5 .
0
or
O
ft: £
> $
~~i <,'
o
o
•« *
O
O
10 15 20 25 30 35 40 45 50 55
INITIflL STREET LORD Ob/curb-m I le)
-------
FIGURE B-23
Lfl
!25
12CL
11 5_
U H0_
- 105_
f 10DH
-o 95
b 90~
v! 85_^
-° 80
- 75
LO 70
= 65__!
g 60
3 55
L_ 50
Mi 45
£ 40_J
in 35
_i 30
S? 25
Q 20
>—i •"j —
en 1 <;
LU J; —
a: 10_
5 _
0 «
KE HILLS STORM NflSHOFF : >63:3 m cm-
/ - ,<•• •' •:, - ^ }
~ W ?f £/ :>' :f .^- ^' -vc .-c-:' .-^ •:•'•'
si f /• S ..v ,..v ,,•
iy ; v- ^ ta- ,- -
~ o/ ^? ^" "" r -;-'"
G ~> ^
1.M /
/
1 / /
0 i'.
/
0
•; Q / ••' .. .i V
/ / / ••• ,- v.i-'A''"
-//.' •,-
/ /'' . ,•
/ >' ' / °- Q . ,.7,:M'.Ol :\..
/, •• ' .?«-'• ' ' -'
--j * / • / _. -~
5^x^v< • ..---"'
_ij*>/e^-. ',•-.--
^T f i 'II 1 1 1 1 1
0 ' 5 10 15 20 25 30 35 40 4o 50 5S1 60 65 70 75 80 85 9d 95 1 001 dsi 1011512
INITIRL STREET LORDING (Ib/curb-mllei
-------
FIGURE B-24
SURREY DOWNS TOTflL SOLIDS - NET SLh.iC
330
25
20C
2 isf
o
a:
0
• A
• 0
.25
O Dirty :-^ t
A ( I ",in S» r
.75 1
RflIN, INCHES
1.25
J
1.7C
-------
FIGURE B-25
SURREY DOWNS TOTflt SOLIDS - DRY 5ER50I
303
251
H» «-
t
in
o
in
cr
20fl
J5
o 10flL_,_« •
^« **>
i «
• o
50.
0 L
* I.irtv SLroet:
A C1 f a n S t r c e t:
.75 1
RfllN, INCHES
1.25 '1.5
1.75
-------
en
-p.
FIGURE B-26
LflKE HILLS TOTflL SOLIDS • WET 5E.R50N
300
250
2oa,
in
ci
- 150 •
_
o
in
a.
»—
o
lOfl
53,
& «
A A
9 A
0 ' .25
o Dirty Streets
4 C1 c-an Streets
.5
.75 1
RPIN, INCHES
1.25
1.:
1.75
-------
FIGURE B-27
LflKE HILLS TOTflL 50LID5 - DRY 5ER50M
303
250-4—
28d
in
C3 i cm A
-« 15fl 1
o
in
100
50.
A A
• A
.25 .5
• Dirty Streets
A Clean Streets
.75 1
RRIN, INCHES
1.25
1.5
1.75
-------
cr.
a-
UJ
.4.
.3-
.2.
FIGURE 8-28
SURREY DOWNS LEFlD
- WET 5ER50
• e e s A
A *»
• A A
.25
.5
0 Dirty
A Clf-an
f f r c - < :• t
i; tract
.75 1
RRIN, INCHES
1.25
1.5
1.75
-------
.6
FIGURE B-29
SURREY GOWNS LERD - DRY 5ER5QN
.5.
.4.
OJ
£71
.3.
.2.
0 A
.1.
.25 .5
• Dirty Streets
A Clean Streets
.75 1
RfUN, INCHES
1,25
1.5
1.75
-------
CO
en
UJ
z;
a
ct
Ui
.4.
.3.
.2.
FIGURE B-30
LFIK.E HILLS LEflD - WET SEfiSON
-« A
AS JD
eee A • «
L.
a
I \ I
.25 .5 .7^
.25
3) D ' r t y S t r c t; t n
A C I •-• a n Streets
1
1.25
i.5
INCHES
-------
FIGURE B-31
LflKE HILLS LEflD - DRY SEflSON
to
CT>
•-D
Q
ft
.3—U- A
.2-
A AA A A
.1.
0
* 0
0
• • A a
! j
' .25 ' .5
• Dirty Streets
A Clean Streets
.75 ' 1
RfllN, INCHES
i I I
1 ' 1.25 1.5
1.75
-------
FIGURE B-32
WET 5ER50N TOTflL SOLIDS LORDS VS.
14
RUNOFF
n:
o
\—
in
\
UJ
C£
LJ
CE
\
in
CD
O
O
13.
12.
11.
S 9
o
in
cr
(—
o
dirty c
Surrc-y Down:;
Lake Hills
9 10 11
FLOW (LN OF CUBIC FEET)
12
13
-------
FIGURE B-33
DRY 5ER50N TOTflL SOLIDS LORDS VS. RUNOFF
13
CK
o
I—
in
\
UJ
a;
LJ
cc
in
CD
12.
11.
10.
in
o
in
cr
o
8
dirty clean
_Surrey Downs
Lake Hills
8
9 10
FLOW (LN OF CUBIC FEET)
11
12
-------
WET 5En50N LERD YIELDS VS. RUNG!
I
_SuL'roy Df)wnr,
Lake- Hill:,
in
x,
UJ
ce:
u
^
in
CD
o
d 2
a
cr
UJ
9 '10 '11
FLOW (LN OF CUBIC FEET)
12
-------
FIGURE B-35
DRY SEflSON LERD YIELDS VS. RUNOFr
6 _
XL
on
P 5
in
X.
LU
o:
u
\ 4
in
fQ
^^ O —
CJ
3 2
a
en
UJ
~* 1
C
dirty c 1 o a n
Surrey Downs • *
Lc-.ke Hills • "
A
»«
• * * •
^ «
* *
* • . * *
• • • • A
*^ 4 •• - *
" '*" . *
• * • " • • •
. ' *
..'..'
"" . ' *"*
' * *• * "
. • .
• ^
%
9 • **
*
•
8
9 10
FLOW (LN OF CUBIC FEET)
11
12
-------
3 TOTflL KJELDflHL NITROGEN WH5HOF
Lu
V
o
o
:n
in
ct
in
LU
LD
in
cr
cr
i—
o
IELD
4.!
4 .
3.:
3 .
2.:
2 .
0 L
.05 .1 .15 .2 .25 .3
RUNOFF VOLUME (Inches)
35
.4
.45
-------
FIGURE B-37
COD STREET HR5HOFF/RUNOFF YIELD RflTIG
25
22.
g 20.
t
o
Q£
t
O
in
tu
UJ
a:
I—
l/l
§
LJ
17.
12.
10.
7.
e
§
*. %
e
0 o
' .05 .1 .15 .2 .25 .3
RUNOFF VOLUME (Inches)
.4
.45
-------
o
»—*
i—
cr
a
_j
UJ
u_
o
z
ID
on
o
IE
in
en
LU
in
a
in
o
50
45_
40.
35.
30_
20_
15.
10.
5 .
0
FIGURE B-33
PHGSPHORUS HRSHOFF/RUNOFF RflTIQ
.05
.1
15 .2 .25 .3
RUNOFF VOLUME (Inches)
.35
.4
.45
-------
8
2 7
t—
-
t 5
o
or ,
x 4
o
? 3
j.
uj 2
in
5 '
M
0
FIGURE B-39
ZINC WflSHOFF/RUNOFF YIELD
a
o e
o
e o
.05
o o
.15 .2 .25 .3
RUNOFF VOLUME (Inches)
.35
.45
-------
FIGURE B-40
a
LU
in
o
cr
o
U-
o
z
C£
o
in
in
o
a
LU
a;
a;
in
350
25
1G
50.
TOTflL SOLIDS YIELDS: DRY
o
<*
A O A
A
o Calibration
A Lake 11 i 11 n c 1 <_• a n i n • j i j n 1
i I
0 50 100 150 200 250 300 350 400 450 500 550 600 650
LflKE HILLS STORM RUNOFF TOTflL SOLIDS TIELDS Ob/storm)
-------
e
O
I/I
^
_£)
in
a
in
o
-------
CO
•x
o
- 350
E
LJ
2
O
1/1
*—t
_J
O
3QC
25£
oc 20C
h-
o
fe 15C
3C
a;
o
(—
1/1
in
O
a
LU
1/1
IOC
50.
FIGURE B-42
TOTflL SOLIDS CONC,
DRY
SEflSON
0 Q
0 Calibration
A Lake Hills cleaning only
20 40 60 80 100 120 140 ' 160 180 200 220
LflKE HILLS STORM RUNOFF TOTflL SOLIDS CONC. (mg/1)
-------
00
c»
U
o
U
300
25
200
g 15C
o;
o
in
10
z
o
a
in
FIGURE B-43
TOTRL SOLIDS CONC.
NET SEflSON
B o
a 0 P
s V •
Q A
A
• f
o Calibration
o Surrey Downs cleaning only
A Lake Hills cleaning only
50 100 150 200 250 300 350
LflKE HILLS STORM RUNOFF CONC. (mg/1J
400
450
-------
Table C-l.
Street Cleaning Effects on Street Loads for
Other Bellevue Sites (Ib/curb-mile)
GO
oo
ro
Site and Date
2nd Ave.
4/30/81
5/9?
120th
4/30
5/22
Kelsey Cr. Pky.
4/30
5/22
118th
4/30
5/22
Stoneridge
5/5
SE 30th St.
5/5
Bellevue Way
5/5
Bellevue North
5/6
before or
after
cleaning
before
after
before
after
before
after
before
after
before
al ter
before
after
before
after
before
after
before
after
before
after
before
after
before
<63
78.2
61.1
22?
114
28.2
30.1
23.9
37.4
16.3
36.4
42.6
22.0
11.8
43.0
5.2
21.7
25.6
38.1
351
249
31.0
30.8
39.2
63
-125
50.5
42.2
149
142
48.3
53.0
36.4
43.5
21.0
28.0
31.0
17.2
7 .1.
23.0
3.9
14.8
31.2
29.6
439
203
50.5
40.5
25.1
Particle Size
125 250
-250 -500
87.6
70.3
305
129
96.6
101
74.6
76.0
43.8
43.9
47.5
26.7
8.4
28.7
5.5
16.9
47.5
47.1
773
18fl
81.0
6l.l
33.4
137
106
483
148
202
182
143
108
69.;
51.5
48.0
33.8
15.5
35.1
11.1
22.4
66.6
59.0
1050
174
110
78.5
33.3
(Microns)
500
-1000
135
97.1
378
,115
219
145
154
83.8
75.0
35.8
39.3
28.0
39.3
44.4
29.0
33.2
64.1
50.2
826
195
130
85.2
34.6
1000
-2000
77.4
40.5
242
51.2
106
38.4
54.5
32.7
67.2
14.4
20.9
9.5
54.0
38.3
38.6
24.4
34.5
21.5
420
160
106
62.1
12.1
2000
-6350
If-. 7
O.4
446
74.9
65.6
14.4
20.1
9.5
57.3
13.7
17.1
5.3
53.6
24.9
39.0
14.6
24.5
9.2
242
62.3
112
52.3
8.6
-6350
46.7
14.2
".30
5.7
27.2
1.7
3.3
1.0
21.5
24.3
' 5.2
l.b
9.3
2.7
10.5
4.7
14.6
5.4
82.9
52.1
22.2
3.6
2.9
total
solids
689
452
•"•50
73^
793
565
509
392
371
243
252
144
200
210
143
153
509
260
4180
1230
643
414
195
fotil
VI II 1r>
ppriP-U
3J«
72
29
?3
33
43
-20
-/
16
69
36
--
-------
Table C-2
Redistribution of Street Dirt due to Street Cleaning
Site: 115-llOth Ave. SE (SD2)
4/14/82 tests
(10-3
loadings)
Before
0-10"
10"-20"
20"-4'
4'-8'
8'-15'
0-15'
After
0-10"
10 "-20"
20"-4'
co 4'_8'
2 8'-15'
0-15'
Removed
0-10"
10"-20"
20"-4'
4'-8'
8 '-15'
>6350
0.29
0.8
0.06
0.006
C.003
0.03
2.3
0.01
0.006
0.02
0.26
-1.50
0.05
0.00
-0.02
2000-6350
0.48
4.5
1.0
0.18
0.05
0.03
5.8
1.0
0.08
0.13
0.45
-1.30
0.00
0.10
-0.08
Particle
1000-2000
0.39
2.1
0.58
0.17
0.08
0.08
3.3
0.84
0.14
0.10
0.31
-1.20
-0.26
0.03
-0.02
Size (Microns)
500-1000
0.58
2.3
0.80
0.26
0.16
0.18
6.5
1.3
0.34
0.18
0.40
-4.2
-0.5
-0.08
-0.02
250-500
1.2
2.3
0.59
0.15
0.10
0.48
8.2
1.2
0.28
0.12
0.72
-5.9
-0.6
-0.13
-0.02
125-250
1.1
1.6
0.26
0.04
0.03
0.71
5.5
0.63
0.11
0.04
0.39
-3.9
-0.37
-0.07
-0.01
63-125
0.50
0.8
0.14
0.03
0.02
0.45
2.7
0.28
0.06
0.02
0.05
-1.9
-0.14
-0.03
0.00
total
< 63 so 1 ids
0.13
0.4
0.10
0.03
0.02
0.26
1.3
0.21
0.06
0.03
-0.08
-0.9
-0.11
-0.03
-0.01
4.7
14.8
3.6
0.9
0.4
2.1
(165
curb
2.2
35.7
5.5
1.1
0.6
3.5
(230
curb
2.5
-20.
-1.9
-0.2
-0.2
1.5
lb/
mi le)
lb/
mile)
9
% Removed
0-10" 90% 94%
10"-20" -190 -29
20"-4' 83 0.00
4'-8' 0.00 0.56
8'-15' -600 -160
0-15'
79%
-57
-45
18
-25
69%
-180
-62
-31
-13
60%
-260
-100
-87
-20
35%
-240
-140
-180
-33
10%
-240
-100
-100
0.00
-44%
-225
-110
-100
-50
54%
-140
-53
-21
-47
-70
Notes: (lawn mowed between before & after sunny/dry, good street condition)
-------
UJ
oo
Table C-2 (con't.)
Redistriuution of Street Dirt due to Street Cleaning
Site: 405-llOth Ave. SE (SDl)
4/14/82 tests
Before
0-10"
10"-20"
20"-4'
4'-8'
8'-l 5'
0-151
After
0-10"
10"-20"
20 "-4 '
4 '-8'
8'-l 5'
0-15'
> 6350
1.03
0.29
0.57
0.006
0.003
0.32
1.11
0.14
0.006
0.02
2000-6350
1.6
1.8
2.2
0.29
0.08
1.27
0.84
0.42
0.33
0.22
rcti. UJ.(- L
-------
Table C-3.
Street Cleaning Test Results During Special Tymco Test Period
Initial Load (Ib/curb-mile)
Particle Size (Microns)
Surrey Downs
Date
Mobil
Tymco
Modified
Tymco
9/8
9/14
9/17
9/22
9/10
9/15
9/21
9/23
9/10
9/14
9/21
9/23
>6350
8.0
5.0
1.4
8.6
2.5
2.1
6.9
3.0
5.1
6.0
2.1
3.5
2000
-6350
11.7
18.2
6.3
16.3
7.8
14.1
17.1
18.8
16.2
15.8
6.3
6.7
Surrey Downs
Date
Mobil
Tymco
Modified
Tynco
9/8
9/14
9/17
9/22
9/10
9/15
9/21
9/23
9/10
9/14
9/21
9/23
1.3
3.9
3.1
2.1
1.7
0.7
0.5
2.2
7.7
0.3
0.6
0.8
14.4
12.2
6.3
9.7
5.3
8.0
6.5
8.1
10.1
7.3
3.1
4.9
1000
-2000
37.6
29.3
11.6
25.7
14.4
25.6
30.1
46.8
46.5
37.0
15.5
9.0
Residual
38.9
23.7
12.7
22.1
9.1
9.7
12.5
24.0
24.6
13.6
9.9
5.8
500
-1000
99.1
59.4
19.0
50.7
34.5
49.3
66.5
110.4
121.5
60.7
24.5
16.0
Load (
99.4
55.4
24.5
42.7
23.1
19.7
23.3
52.6
54.5
22.1
14.2
10.3
250
-500
114.4
58.9
14.4
62.1
32.3
52.9
67.2
113.8
171.5
54.2
32.5
21.7
Ib/curb-mile)
114
63.4
23.2
48.5
19.7
25.8
21.7
48.0
61.1
18.2
17.5
12.0
125
-250
87.8
40.5
10.2
52.8
14.8
39.5
44.0
73.7
142.8
32.3
29.3
19.8
82.3
42.5
16.7
39.9
15.7
24.8
18.0
37.7
48.5
12.7
18.3
11.9
63
-125
54.4
24.1
7.8
38.0
5.8
29.9
26.9
39.9
88.7
16.0
24.7
15.8
52.7
25.2
10.8
30.1
11.2
19.1
13.8
26.9
38.2
8.8
15.6
9.8
37
-63
26.1
10.5
4.7
15.2
2.3
10.6
10.1
16.6
39.7
8.3
9.7
8.3
24.8
11.2
5.1
14.3
6.9
10.3
6.6
13.8
20.4
5.3
8.0
5.8
•=37
6.9
6.2
5.2
8.8
1.6
13.7
8.4
11.9
19.7
6.9
7.3
6.8
20.9
9.0
5.5
10.5
5.8
10.3
5.1
9.3
18.2
6.4
7.7
5.1
TS
456
252
81
278
116
238
277
435
652
239
152
108
449
243
108
220
99
129
ill
223
283
95
95
66
-------
T'1:^ L.-J, (Cont.)
Street Cleaning lest Results During Special Tymco Test Period
Initial Load (Ib/curb-mile)
Particle Size ^Microns)
C/J
00
en
Surrey Downs
Date
SE 30th
Mobil
Tymco
Modified
Tymco
SE 30th
Mob i 1
Tymco
Modified
Tymco
9/1
9/16
9/27
9/30
10/5
9/2
9/16
9/27
10/1
10/4
9/16
9/29
9/30
10/4
9/1
9/16
9/27
9/30
10/5
9/2
9/16
9/27
10/1
10/4
9/16
9/29
9/30
10/4
>6350
141
17.1
1.2
9.2
5.5
37.6
47.3
18.2
11.2
3.1
17.1
6.8
7.8
15.5
85.9
22.3
14.3
8.4
5.3
7.0
11.7
6.9
2.0
1.9
6.2
1.4
6.8
1.4
2000
-5350
251
80.4
32.2
33.9
21.5
84.0
135
72.7
27.1
28.3
48.9
37.6
31.5
33.4
231
45.3
128
36.2
23.1
31.5
38.2
29.2
12.4
20.4
18.3
'3.9
20.3
18.4
1000 500 250
-2000 -1000 -500
28C
146
83.5
68.0
34.4
152
141
120
38.4
51.0
127
64.9
73.3
62.4
239
97.5
75.0
68.0
39.7
113
64.1
84.8
28.9
38.0
66.6
33.0
70.3
42.1
532
321
125
138
54.2
259
222
226
60.5
70.2
201
117
133
125
Residual
413
208
146
126
62.5
153
87.9
149
42.1
47.1
61.5
43.7
83.9
70.5
740
390
137
174
55.5
403
314
288
70.0
83.0
222
131
205
125
125
-250
667
384
119
185
48.7
400
358
245
72.1
81.4
192
102
186
94.8
63
-125
284
302
73.9
141
27.3
245
200
151
43.6
48.9
134
47.5
90.0
63.5
37
-63
66.7
98.1
20.8
55.1
8.8
80.6
76.3
47.8
16.9
13.6
44.8
n.7
22.4
18.9
•37
20.8
91.8
6.9
19.3
5.2
37.8
85.0
14.5
9.4
5.1
24.0
4.7
5.8
8.0
TS
2986
1339
600
822
261
1699
157S
912
349
385
1009
523
755
547
Load (Ib/curb-mile)
635
237
228
144
65.3
216
93.9
13(5
37.5
45.3
74.4
39.6
55.0
59.5
824
218
221
121
54.5
223
105
127
35.9
46.1
76.2
30.9
37.8
48.6
488
169
125
69.7
32.4
145
93.2
84.6
27.7
34.7
74.5
16.7
26.2
35.0
137
60.2
46.3
24.2
13.0
58.0
41.5
34.7
11.0
12.7
34.7
c.l
9.5
11.8
23.1
67.0
24.4
11.3
8.1
43.9
34.1
13.0
7.1
6.6
33.5
2.7
6.?
7,&
3077
1123
909
610
104
991
570
664
205
2?2
446
187
316
295
-------
FIGURE C- 1
E
I
_Q
L
U
jQ
O
o
Ul
01
OH
Street Cleaner Performance
50
so
40
\
6370
c r o n
Surrey Downs (Mobil)
Lake Hills (Mobil
M: Modified Tymco (Surrey Downsj
T: Tymco (Surrey Downs;
20 30 40
Initial Load (Ib/curb-mIle)
-------
FIGURE C-2
LO
00
Street Cleaner Performance'
70
60.
O '• S u r L <:y Downn(t-'/j 1
A.' Lake II i 1 1 :: (M:>M 1 )
M: Modifier! Tymco (Surrey Downr.)
L: Tymco (Suiroy D'lwnf;)
'000-63/0
20 30 40 50
Inl-tlol Load Ob/curb-ml le)
70
-------
FIGURE C-3
oo
UD
Street Cleaner Performance:
90
1000-2000
01
e
f
u
o
o
o
-o
in
o>
80.
70.
0 '• Surrey Downs (Mobil)
A: Lake Hills (Mohil)
•H-. Modified Tymco (Surrey Down
T: Tymco (Surrey Downs)
40 50 60
Load (Ib/curb-mlle)
70
80
90
-------
CO
^o
o
_O
U
V.
_Q
C
O
o
-
U)
0)
o;
Sir
150
14fl
i3a
120.
11
10
90
80
70
60
50
40
30
20
FIGURE C-4
eet Cleaner Performance: 5QG-1GGQ
0! Surrey Downs (Mobil)
A: Lake Hills (Mobil)
M-. Modified Tymco (Surrey Downs)
T: Tymco (Surrey Downs)
10 20
40 50 60 70 80 90 100 110 120 130 140 150
Initial Load (1b/curb-mI 1e)
-------
FIGURE C-5
5treet Cleaner Performance-' 250-500 [j
160
151U— A
140_I_ M
T
130.
Surrey Downs (Mobil)
Lake Hills (Mobil)
Modified Tymco (Surrey Downs)
Tymco (Surrey Downs)
01
E
f
U
0
o
o
tJ
"w
CI
eg
0
10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160
Inl-Mol Lood Hb/curb-mlle)
-------
FIGURE C-6
Street Cleaner Performance: 125-25Q
f
f
u
~o
a
o
o
-
w
01
a;
130
11
IOC
90_
80.
70.
60.
50_
40.
30.
20.
10.
0
: Surrey Downs (Mobil)
A: Lake Hills (Mobil)
M; Modified Tymco (Surrey Downs)
T: Tymco (Surrey Downs)
0
10 20 30 40 50 60 70 80 90 100 110 120 130
Initial Load (Ib/curb-mlle)
-------
FIGURE C-7
Street Cleaner Performance:
u
V.
-O
"O
o
O
o
-
ut
4)
63-125
> • Surrey Downs
•' Lake Kills
-------
FIGURE C-8
Street Cleaner Performance
<63 M i crons
80
70_
3 60.
0: Surrey Downs (Mobil)
*: Lake Hills (Mobil)
_M: Modified Tymco (Surrey Downs)
T; Tymco (Surrey Downs)
40
50
,•£>>•-
60
70
80
Inl-tlol Lood (lb/curb-mlle)
-------
FIGURE C-9
Surrey Downs Greater Than 6350 Microns
3456
Initial Load (Ib/curb-mMe)
-------
E
I
.£)
L
3
U
\
JO
- 10
a
o
o
-o
in
OJ
01
0
FIGURE C-1 0
Surrey Douns 2000 to 6350 Microns
6 8 ' 10 12 14 16 18
Inl-Uol Load (Ib/curb-mlle)
20
-------
FIGURE C- 1 1
Surrey Douns 1000 to 2000 Microns
10 20 30
Inl-tlal Load Ub/curn-ml le)
-------
OJ
'O
00
U 10
E
_£>
L
-o
f}
O
c
-o
w
(V
FIGURE C-12
Surrey Downs 500 to 1000 Micron
o
10
40 50 60 70 80 90
Inl-tlo) Load (1 b/curb-m I 1 e)
100 110
120
-------
FIGURE C- 1 3
Surrey DONHS 250 to 5QG Microns
40
63 80 100 120 140
:nltlol Load Mb/curb-mM e)
160 183
-------
E
u
_o
-o
o
o
o
U
TJ
FIGURE C- 1 4
Surrey Douns 125 to 250 Microns
10 20 30 40 53 60 70 80 90 100 110 120 130 140 150
Initial Load (1b/curb-ml1e)
-------
O
FIGURE C- 1 5
Surrey Downs 63 to 125 Microns
10
20 3C 40
Initial Load (Ib/curb-mMe)
50
-------
o
'o
FIGURE C-1 6
Surrey Downs 37 to 63 Microns
10 15 20 25 30
Initial Load (1b/curb-mIIe)
35
40
-------
FIGURE C-1 7
Surrey Downs Less Than 37 Microns
o
10 15
Inl-tlol Load (lb/curb-m! 1e)
20
25
-------
FIGURE C-18
Surrey Douns 2 to 10 Microns
.2 .3 .4 .5
Inl-tlo) Load (Ib/curb-m M e)
-------
FIGURE C- 1 9
Surrey Downs Less Than 2 Microns
0
.1
.2 .3
Inl-tlol Load (1b/curb-m!le)
.4
.5
-------
FIGURE C-20
5.E. 30th Greater Than 6350 Microns
E
I
_D
U
X
_D
-a
o
_j
'c
T)
01
60 90
Initial Lood ()b/curb-mI 1e)
120
150
-------
FIGURE C-2 1
S.E. 30th 2000 -to 6350 Microns
20 40 60 80 100 120 140 160 180 200 220 240 260
Initial Load (1b/curb-mI1e)
-------
o
00
FIGURE C-22
5.E. 30th 1000 to 2000 Micron
100 150 200
Initial Load (1 b/curb-m Mel
250
300
-------
0
FIGURE C-23
5.E. 30th 500 to 1000 Microns
50 100 150 200 250 300 350 400 450 500 550
Inl-tlol Lood nb/curb-mtle)
-------
750
FIGURE C-24
5.E. 30th 250 to 500 Microns
50 100 150 200 250 300 350 400 450 500 550 600 650 700 750
Inl-tlol Load (Ib/curb-mMe)
-------
FIGURE C-25
5.E. 30th 125 to 25Q Microns
_o
u
TJ
c
o
o
-6
IV
ct:
850
800J_
100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850
Initial Load (Ib/curb-mMe)
-------
0
FIGURE C-26
5.E. 30th 63 to 125 mcrons
50 100 150 200 250 3QO 350
Initial Load Hb/curb-mlle)
400
450 530
-------
E
J3
U
V.
J3
"O
o
o
Q
-
W
01
ct:
FIGURE C-27
S.E. 3Qth 37 to 63 Microns
40 60 80 100
Inl-tlol Load (Ib/curb-mMe)
123
140
-------
FIGURE C-28
5.E. 30ih Less Than 37 Microns
10 20
30 40 50 60 70
Inl-tlol Load Hb/curb-m I 1 e)
80
90
100
-------
FIGURE C-29
5.E. 30th 2 io 10 Microns
2345
Inltlol Loed Hb/curb-mMe)
-------
0
0
FIGURE C-30
5.E. 30-th Less Than 2 Microns
Initial Lood llb/curb-mlle)
-------
Table D-1 . Surrey Down." Catchbaoin Sediment Loading Observations fcubic fee*,}
Dec 17-26 Aug 8-14 Jan 30 Peb 26-Apr 21-24.Jun l6-17Jul 17-21Aug 17-24 Jan 18- Xir. 1
Tlumber
1979
19UO
1981
Mar 1 '
506
507
^09
510
526
-,21
528
529
531
532
533
534
535
536
538
539
540
54?
543
544
546
547
550
551
554
555
557
558
559
560
561
562
565
566
567
568
570
572
573
574
575
578
580
998
Total
Max iraum
Average
Count
.00
.40
.04
.23
.30
.29
.08
.06
.64
.00
.03
.80
.18
.26
.20
.21
.49
.09
.32
.21
.03
.10
.68
.24
.10
.15
.25
• 31
.79
.64
.47
.71
.34
1.13
• 37
.60
.58
• 34
.49
.20
.20
2.36
.17
.60
17
2.36
.38
44
• 05
.12
.02
.24
.13
.12
.04
.21
1 .44
.00
.14
2.20
.08
.03
.08
.08
•65
-15
1 .01
1 .21
.17
• 13
.85
• 34
.17
.16
• 31
-92
1 .06
.64
1 .10
3-56
.00
.37
• 19
.15
.12
.17
2.46
.27
2.34
2.15
2.48
.60
29
3.56
.65
44
.00
1 .81
2.23
t .23
2. 36
6.74
.19
3-24
2.02
.30
1.15
8.69
4-33
4.80
1 .71
1 1 .04
6.63
.00
1.9-
1.49
• 37
2.05
2.72
2.41
4.53
1 .70
2.81
4-13
5-36
3-81
1 .61
3-85
4-32
6.63
NA
1 .08
.00
6.52
2.32
.20
1 .72
1 .72
2.41
3.03
127
1 1 .04
2.96
43
.00
1 .81
2.05
1 .42
2.10
6.56
.47
3-99
2-34
.21
3.02
9.CI
-••54
4-85
1 -31
11.24
6.4'-'
.09
1 .92
1 -52
• 37
1.51
2.86
2.04
4.25
2.01
2.96
4-28
5-41
3-50
2.08
HA
.00
6.27
• 30
1 .14
.58
3.18
2.46
• 39
1 .09
.43
• 33
3-24
116
1 1 .24
2.69
43
.CO
1 .81
2.41
T.'53
2.42
7.16
-5C
3.69
2.50
.12
1.15
9.01
.1.28
4. 65
1 .87
t.52
''•" 1!
.
•< 9-)
1 .48
.03
1 .61
2.75
2.21
2.14
.09
.22
.13
.79
3.81
.09
.14
.44
-58
.04
.24
.00
1.51
.12
08
.04
.47
2.05
.15
75
9.01
1 .71
44
.41
2.61
3-14
1 .42
2.28
6.56
.00
3-6j
2.-'0
-30
1.15
8.81
4-33
4-85
2.10
7.7r
6.fi
. ; •
1.^2
' . - 1
• 37
1 .68
2.69
2.38
3.06
.71
• 37
.76
1 .72
3-81
.00
.86
1 .42
1 .61
.00
.84
.77
• 03
.86
.08
.12
.86
2.15
1-35
90
8.81
2.05
44
.00
1 .61
2.63
1 .62
2. 10
6.44
• 31
3-36
1 .95
• 39
1 .56
9-17
3-37
4.88
2.50
6-94
6-73
.06
1 .67
1 .27
• 37
2.08
2.99
2.72
3-50
-77
.47
1 .07
1 .06
3-49
.19
1 .8S
1 . 47
1 -25
.00
1 -57
.15
.17
• 37
• 55
• 23
• 39
2.18
1 .41
89
9-17
2.02
44
.09
2.01
2.71
1.56
2.10
6.86
• 39
3-63
2.18
.15
1 .01
9.01
4.46
1.85
2.10
2.05
1 .56
1 .06
1 .98
1 .36
-54
1 .35
2.86
2.04
3-57
.93
• 56
1 .40
2.51
3-50
• 03
1 .28
1.67
1 .61
.22
1 -35
.12
. 10
.62
.00
.70
.64
.00
1.65
3\
9.01
1 .84
44
1.56
3-41
4.02
1 .70
2.75
7.16
.97
1.14
2.66
.'5
1 .30
9-41
4.33
4-72
.32
5-34
.97
.00
1 .57
1 .97
.54
2.69
3.06
2.21
3-74
1.39
1 .87
3.4^.
S.2S
4.45
.66
MA
5-61
6.27
.22
-99
• T8
1.34
2.09
.20
.31
.86
2.31
2.85
108
9.4t
2.52
43
.00
. 12
.02
.24
- 13
. 12
.00
.06
.64
.00
.03
.80
.08
.03
.08
.00
-49
.00
.32
.21
.03
.10
.68
O •
.10
• 09
.22
.15
.79
-6-1
.00
.14
.00
•77
.00
• 15
.00
• 03
.12
.00
.04
• 39
.00
.15
8
.80
. 18
44
t c r
3.4l'
4-02
1 .70
2.76
7.16
• 97
3-99
2.V,
.3?
3-C2
9.4'
4.54
4.33
2 . -0
1 1 . 24
6.66
1 .06
1 .03
1 -97
.C4
2.6Q
7-06
2.72
4.53
2.0!
2.36
4.28
5-41
4.45
2.08
3-35
5-3!
6.63
• 37
1 -57
.77
6.52
2.46
.55
2.34
;.76
:.' . 43
.5-24
'50
1 1 .24
3.4T
14
- -r
1 .""5
2.14
1 .23
1 .:A
5.72
/ T
") - ^
2.01
. 13
1 . ', 1
7-75
7.72
7 . 7ri
i -75
c . 5-1
-t f —
j • *
. i •)
1 - 53
1 .74
• 31
1 . ^ >
2 . M
1 .84
2.i^
••3
1 . Z^
' -87
2.66
3.07
.69
1 -75
1 .->2
2.36
.17
.89
• 70
1 .43
1 -31
.22
-7S
1 .1C
1 .56
' .65
82
7-35
1 .86
44
-------
Table D-2. Surrey Downs Inlet CecUment Loading Observations 'cubic fee1",;
Deo 13-26 Aug 9-14 Jan 30 Feb 26-Apr 2l-24o'un 16-17Jul 17-21 Am? 17-24
Number 1979 1980 19^1 Mar 11
oo
.'* i n L m MTI
502
503
505
508
511
513
514
516
517
518
520
524
525
530
537
541
545
548
549
552
553
556
569
571
579
581
999
Total
Maximum
Average
Count
•J3
:;A
.04
.42
.CO
.15
• 15
.06
.03
.03
NA
• 45
.00
.10
.77
.36
.26
1 .01
• 32
1 .02
.22
.45
1 .04
• 35
1 .62
.12
• 03
9
t .62
-36
25
• 38
.15
. 12
• 98
.07
• 03
.09
• 03
.03
.24
.09
.36
.00
.07
1 .29
.85
-49
2.02
1 .29
1 .87
• 32
.06
3-64
• 35
2.70
.07
.10
18
3.64
• 65
27
• 03
. 1b
.12
1.15
1.58
.00
.27
.81
.03
.12
.42
1 . : i
.00
.06
4.95
1 .06
1.23
1.51
1 .49
3-06
3-03
4.08
18.93
1 .40
• 31
.30
3-33
51
18.93
1 .87
27
.20
.09
.00
1.34
1-34
.06
• 15
• 69
. 12
.18
-45
1.23
.00
.04
5-46
1 .27
1 .5o
4-94
1.32
2.89
2.87
4.1 1
18.98
1-57
• 39
-32
3-40
55
10.98
2.04
27
.44
.:?
.15
1 -57
1 .51
-15
.24
.69
.06
.24
.60
1 .47
.00
.10
6.03
1 .27
1 .72
5-64
1.97
2.72
1 .44
4-20
19-24
.00
.50
.16
3-40
56
19-24
2.06
27
.49
.21
-CO
1 .43
1.75
.15
.15
.69
.22
• 33
• 30
1 .47
.00
.07
5- 65
1.36
1-39
5-71
1 .81
2.89
2.23
4-26
18.72
• 52
• 31
.16
3-23
56
18.72
2.06
27
-35
. 10
1?
1 .43
1 .68
• 36
-15
.69
.16
.39
.60
1 .47
.01
.00
6.18
1-51
1 -55
5-95
1 .42
2.58
2.07
4.20
18.46
.70
• 35
.23
3-50
56
10.46
2 . 08
27
.00
.05
-72
1 -57
1 -5'
.21
-15
.69
.22
.37
• 30
2.07
.00
.07
6.11
1 .58
1-39
5-86
1 .81
.07
2.23
1 .26
18.7?
.87
• 39
.16
• 34
48
18.72
1.79
27
5.22
. 77
1 .40
t il ">
J • J1-
7.22
.70
. to
.69
.22
. 18
.45
1 .02
.00
.07
6. 18
1 .21
.42
6. ^
1 . 29
4. >>
2 . S7
2.76
8.58
.8^
.19
.40
.24
57
8.58
2.12
27
.00
. 00
.CO
.-12
. '~ ^
.00
r,q
.03
• 05
r7
.00
.76
.',0
00
."~>
• 3o
.26
1 .01
.7<^
. 07
T -1
. ^ C
06
1 .04
.00
. n
.07
.03
5
1 .04
.20
27
5-22
1 -f
* . 4 0
~* i ">
S ' s -
7. 22
. "*/,
C ^
.8'
.22
. j'(
r "*
2 . '".i
.01
. ! 0
6 . 1 •!
I . = •<
1 . 7 j
^.^'.
\ . "1 7
4 . C8
1 . 0 '.
4.2s
1 '') . 2 4
1 .57
? 70
.40
3-50
80
19-24
2.96
27
~ <
' *
. C"
t . '•' '
1 '•*=.
. i •')
. .'' .?
c ^
. I i
', i
. i -
1 I -.'
4 . "'•
1 . !•:.
1.1'
4 . 7-1
1.4'
2.1 =
i ri ~>
2 . ••;
14.0';
.71
.7<>
. 21
1 . i'i
4r>
14.0?
1 .67
27
-------
Table D-3- Surrey Downs Man Hole Sediment Loading Observation (cubic fe;t)
Dec 13-26 Aug 8-14
Itumber 1979 1980
504
512
515
519
521
522
523
577
Total
Maximum
Average
Count
HA
NA
NA
NA
NA
NA
NA
10.03
10
10.03
10.03
1
.13
.00
NA
.00
.00
.00
.00
15-18
15
15-18
2.19
7
Jan 30
1 981
.00
• 39
.00
.00
4.02
.16
-63
15-32
21
15-32
2.56
8
Peb 26-Apr 21-24Jun 16-IVJ'il t?-21Aug 17-24 Jan 18- "iniouT. .'"ax Lr= JBI Av«r-i,?-i
Mar 1 1 Feb 5
.00
.00
.00
.00
.00
.32
• 38
15.32
16
15-32
2.00
8
.00
.79
.00
.00
.00
.16
.00
13-99
15
13-99
1 .87
8
.00
.00
.00
.00
.00
.00
.00
15.31
15
15-31
1.91
8
.00
.00
;JA
.00
.00
.00
.50
25.86
26
25-83
3.77
7
.00
.00
.00
.00
.00
.00
.00
15-32
15
15-32
1.91
8
1 962
MA
NA
.00
.00
.00
• 57
.00
20.08
21
20.08
3-44
6
.CO
.cc
"A
NA
NA
.00
.CO
10.03
10
10.03
2.01
5
•'3
-79
."A
'iA
:;A
_ c; -
• 63
25 . 38
28
25. ?3
5-60
5
.02
. 17
'in
"iA
:;A
. 1 9
•6.27
17
1 6 . 27
3-36
C,
-------
Klllo -'atchbas ir
LcH.Jir. *? Observations f cubic
Dec 4-12 Jul 23-Jan
liua'jer 1979 Aug b
1980
!*ir 2- A-r 2.1-.J'in 19-26Jul 14-56
Acr i >ay 5
-C.
ro
o
;c5
5C6
510
51 1
= i j
514
516
517
519
520
521
524
526
528
543
544
"45
546
547
548
550
551
552
553
554
555
556
560
561
564
565
566
5b8
570
571
573
574
576
577
578
579
580
582
584
588
589
591
593
596
.39
.40
.22
. 1 2
• 3°
o9
.00
.04
• 37
1 .04
1.16
1.14
• 58
1 .60
.00
.02
.00
.04
.00
.20
.00
.00
.00
.00
.00
.00
.04
.08
.04
.08
.00
.21
.08
.00
.04
.04
.08
.08
.07
.02
1 .41
NA
-39
.08
-40
.04
. 12
• 39
.20
• 96
.60
1 .08
.20
. 12
.73
.00
• 58
. 18
-42
1.35
.76
-58
1.14
-04
.04
• 39
.00
1 .28
.04
.08
.00
.00
.04
.00
.00
.00
.28
.19
1 .58
.00
.63
. 12
-04
-29
.08
.08
.19
.07
. 17
• 35
• 03
• 39
.04
.12
. t 1
.08
-39
.12
2.93
2.C1
2.76
.36
4 . 28
.82
.00
.81
1 -39
2.66
1 .62
2.93
2.43
4.83
.00
.00
.00
.00
.00
2.12
.00
•31
.00
.04
HA
.08
.08
. 16
.54
2.46
.00
.17
.00
.00
-51
.46
.04
.89
.13
.40
.14
1 .24
1 -54
-29
.71
. 18
.00
• 35
.00
1 .
2.
2 .
4.
1 .
1
2
1
3
2
5
1
2
1
.00
21
T7
.60
.47
.02
. 27
.93
.69
.20
.35
.43
• 32
•52
.00
.00
.00
.00
.85
.77
.00
.CO
.00
.00
NA
.00
.00
.00
-85
.10
• 09
.42
.08
.08
• 55
.04
.00
.16
.17
• 34
NA
NA
NA
HA
NA
NA
.03
.78
.00
6.38
2.4!
2 . °S
".60
1.67
1.41
.27
1.12
1 .76
2-62
1 .74
3.62
2.12
4.15
NA
NA
NA
NA
NA
NA
NA
NA
;;A
NA
NA
NA
NA
NA
HA
NA
NA
i!A
NA
NA
MA
NA
NA
NA
NA
NA
-50
1 .28
1 -93
.29
.48
.32
.46
.31
.20
1 .
c •
3 •
4-
1 .
1 .
3-
4.
2.
5-
1 .
2,
1
2
1
1
2
54
C 1
20
80
32
41
00
73
68
32
16
19
51
06
.00
.00
.00
."A
,20
.28
.00
.00
.00
.00
.00
.00
.00
.36
• 23
.49
.00
• 34
.39
.00
• 55
.46
.19
.16
.17
• 34
• 57
.28
. 12
• 50
MA
NA
.66
.78
.00
1 .
2.
7
4.
2.
1 .
1 .
2.
1 .
3-
2.
5.
2.
2.
1
1
2
20
21
54
24
32
20
00
39
61
41
'9
qo
55
29
00
00
00
CO
90
CO
00
35
.00
.00
NA
,08
.00
.28
.63
,30
.09
.38
.03
.20
.33
.46
.08
.66
. 1 7
.54
.06
.31
.04
.21
.51
-50
.46
.43
.08
1 • ~"'
2 . "~'j
t _ 2Q
.C8
8.32
2.59
• 1 9
1.12
1.^9
2^62
1 .35
3-62
2.CQ
5.75
.00
.00
. 12
.00
1 .71
1 .96
.04
.15
.00
.15
NA
.27
. 12
.08
.46
2.49
.09
.34
.77
.20
. c 5
.46
.0^
1.15
.20
.Si
N£
NA
2.31
.42
.00
.07
HA
. 53
.00
i tr
2.^1
7 . 4 h,
! . 40
4.47
1 .61
r p
1.31
2 . o
2 ^ 2
r. i"e
4. C7
2.51
7.57
.00
.00
. 1 2
. t 2
.00
1 .96
. CO
. 7°
.CO
.00
.CO
1 2
.CO
. 16
1 .04
2.49
.09
• 34
.77
.00
. 73
.46
. 15
1 -35
. 10
.67
1 .98
1.11
1 .35
. ?°i
. .10
. 2S
.73
. 3'1
. 39
. "* "i
.4 :
. 2 ?
. " -J
. ' 2
=, -'
. 4
i .•)
. 4 J
1.16
. 76
c p
1 ' 4
, r
•- r:
CO
r:C,
.CO
. CO
.CO
.'.0
.CO
.CO
CO
. CO
. on
.00
. JO
.00
. oo
.00
. 00
.00
. on
.00
.00
.no
. 00
.00
.00
.•"'O
.CO
.00
.00
.00
.00
.31
.00
4.5"'
2 . /(
2.4^
77
.20
• 5s
. 46
.6""
1 .P8
1.71
.SO
.71
.77
. 7H
. 1 4
I .C4
1 • 5'
.27
-------
Table D-4. Lake Hillo CatohDaain Sedioent Loading Observations (cubic feet) (cont.)
Dec 4-12 ,Iul 23-Jan 27-29 Mar 2- Apr 24-Jun 1 9-'6Jul 14-16 Au£ 27-Jan 20-27
Hunber 1979 Aug 6 1981 A or t May 5 2ep 3 1932
1980
597
598
599
601
607
607
608
609
612
614
£16
618
619
621
623
625
627
629
630
631
632
634
Total
Maximum
Average
Count
.77
.00
.20
.08
.12
.08
•37
.26
-29
:IA
.56
.00
-04
.04
.04
.00
.04
.04
.04
.04
.19
.08
15
1 .60
.22
69
• 96
.04
.48
.19
.19
.20
.37
.19
• 54
:;A
.15
.00
.20
.28
.04
.04
.04
.08
.08
.19
• 39
.12
21
1 .58
.30
70
.69
.20
.64
.C3
.00
.20
.37
1.23
2-39
2.4'
1 .61
.00
.79
.12
.00
.08
.20
.08
.12
.00
• 58
.77
55
4-83
.79
70
.77
.00
.44
.08
.00
.48
• 37
1.12
2.50
2-52
1 -68
.00
• 79
-52
.00
.00
.20
• 31
.41
.00
.69
• 96
53
5.52
.83
64
-77
.20
.44
.00
.23
.60
.48
.00
2.86
2.52
1 .61
.00
• 98
KA
HA
NA
MA
HA
NA
.00
• 58
HA
53
6.38
1 -39
38
• 58
.CO
1 .04
.27
.00
.CO
.CO
t .50
2.14
2.66
1 .68
.20
1 .38
.51
.00
.12
.20
.70
2.89
.00
.77
• 96
67
5.06
• 98
68
.46
.CO
.28
.C8
.CO
.CO
.26
1 .08
1 -96
2.55
1 .68
.08
.71
.16
.00
-40
.04
.74
2.76
.19
.89
.62
64
5.29
-91
70
• 58
.08
• 96
.CO
.04
.CO
.44
1 .38
2.50
2.6';
1.50
.00
• 5!
.12
.00
.00
.00
1 .09
3-09
• 96
.96
• 77
70
8.32
1.05
67
.77
.CO
1 .C4
C ^
.00
.20
.18
-37
2.68
2.66
1 .i8
.00
1 .38
.71
.00
.00
.78
• 31
2.68
.00
.89
1 .16
72
7.57
1 .01
71
.46
-CC
.2C
.CO
.CO
-CO
.CC
.00
.29
.00
.15
.00
.04
.00
.CO
.00
.00
.00
.00
.00
. IP
.00
9
1 .16
.1 1
71
• 9"i
. 20
• .C4
2"!
.2'
.60
.48
1 .50
2.86
2.66
t .68
.20
1 .38
.71
.04
.40
.78
1 .09
3-09
.PC
.96
1 .16
96
a. 32
' -35
71
^1
. 06
tT Q
. "r|
.06
.20
3'
.79
t .96
2-56
1 -35
-C3
.75
. 71
.01
.08
. 1P
.42
1 .51
.15
.66
. 68
55
4-54
.T1
71
-------
Table D-5-
ilills Inlet Sedicent Loading Observations (cubic feet)
Dec ^-12 Jul 23-Jan 27-29 Xar 2- Apr 24-Jun 1 9-26Jul M-'6
:!unber 1979 Aug 6 1981 Apr 1 May 5
1980
'•'in:T.uri "'ax : - j- .-'.•/•-• ri*/-?
502
507
508
509
512
515
515
522
525
527
529
531
532
536
542
549
557
559
562
563
567
569
572
575
577
578
580
585
537
590
592
594
602
604
606
610
613
615
617
620
622
624
626
620
633
Total
Maximum
Average
Count
• C4
.09
.CO
.00
-03
.00
cc
• o;
.10
• 13
.00
.00
.00
.00
.29
• 38
.13
.00
• 03
.02
• 03
.07
• 03
-03
.07
.02
MA
.07
1.54
• 03
.77
-79
.28
.08
.06
.00
NA
.60
• 03
.20
.12
.08
.24
.12
.16
7
1.54
. 16
43
. 14
.09
.10
.03
, -\
— -r
• <-> >
.07
.07
-34
.67
-03
.07
.07
.00
.84
• 38
.10
.17
.10
.27
.03
.17
.07
.00
.07
. 1 7
^03
.03
1.16
• 55
• 96
1 .77
1.19
.27
.14
.00
NA
.60
.09
.78
1-39
.78
.40
.98
.79
16
1 .77
.37
44
.00
.47
.03
.00
• 30
.CO
.00
.00
.10
.13
.17
.00
.00
.00
1 .80
• 30
.03
.00
.00
. 2^*
. CL
.03
.00
.00
.13
.40
1 -24
.20
2.43
.87
2.47
5-H
3-30
.08
.14
.00
.77
.78
-44
.38
1 -99
1 . iO
1 .27
2.22
1.95
32
5- '4
.70
45
.07
-31
.00
.00
.30
.07
.00
.00
.10
.20
.'0
.18
.00
.07
1.59
.'d
.24
.07
.00
.20
.00
.10
.00
KA
.17
• 34
NA
tIA
HA
NA
2.66
5.42
3-57
.08
.27
.03
.70
• 90
.22
.98
1.39
1-37
.84
2.54
1.95
27
5.42
.63
/,0
.07
.41
.00
.30
.1 7
.00
.00
.00
.27
« T
- 1 J
.07
-32
.00
.07
1 .67
"A
NA
:;A
NA
HA
HA
MA
NA
NA
:;A
NA
1 .28
.13
2.70
• 96
3-24
5.49
3-57
.11
.06
.00
• 58
1.05
.38
• 98
NA
NA
HA
NA
1 -95
26
3-49
.86
30
.07
:IA
.CO
.00
.30
.00
.00
.17
.10
.20
.07
.13
.00
00
I .46
.45
.17
MA
.0?
.20
.00
.17
.07
.00
.17
.34
1 .28
.20
2.12
.82
3-24
5.49
3.77
.27
-05
.00
.70
.90
.38
1 .26
2.19
1-57
.84
2.73
2.34
34
5-49
.80
43
.14
.00
.00
.00
. *0
.00
.00
.10
.37
.24
.00
.32
.00
.10
1 -33
• 30
.24
RA
.00
-37
-30
-03
.00
::A
.13
.54
1 .31
.17
1 .58
.32
2.66
.55
4.09
. 1 1
. 1 1
.00
.66
.81
.44
1 .10
1.43
I 61
.79
2.58
2. 'B
23
4.39
.65
43
. -7
.22
.13
.07
• 30
. 17
.00
. 17
.27
.20
.17
.36
-03
-34
1 .67
.45
.03
MA
.03
.20
.00
.17
-03
.00
.20
.51
;IA
.20
1 .93
1 .09
NA
5-50
3-77
.19
.41
.CO
.58
.46
.53
1 .26
1 .70
1 .17
.84
2.73
1.95
31
5-50
.74
42
.cc
.22
.03
. CO
• 77
.CO
.00
.13
.07
* ,•'''
^ ^
. 1 5
.CO
. 1C
1 .04
.0°.
.00
. ^"'0
.00
.CO
.00
.17
.00
.00
. 10
.67
1.11
.00
2.70
.68
3-47
5.10
4. 17
HA
.05
.00
-35
1 -05
.11
-39
.60
1 .37
.34
2.01
2.54
31
5-10
.71
44
. ~C
.CO
-CO
.00
.".-}
. cc
r ^
.CO
. C'7
' 5
.CO
.CC
.CO
-<"0
. 9Q
.ce
r r-
. f C
.cc
.^0
.CO
.03
.00
• 'J'J
.0-
.02
.03
.00
1 .16
-OT
-77
.5=)
.28
.08
-05
.00
.35
.60
-03
.20
.12
.08
.s"4
. 12
.16
6
1 .16
* o
15
. U
.4 '
. 1 *
i ' "
1°^
1 -7
r~'j
. 1 7
• ^ '
. 6^
. 1 7
-I £
. C"
. M
'. .:'0
.45
. 2 -
. 1^
. 'C
T-f
7 •"
. IT
.0"
. C^
.20
.-J7
1 -31
.20
n ~''~i
\ .C9
5-47
5-50
4. 17
.27
.41
.03
.77
1 .05
• 53
1 .26
2. 10
1 .61
1 .27
2.QT
2.54
41
5.^0
• 92
45
. C~^
. 5 '
. ~_ '
. " '
. ?-
r i
~ i
. ;~
. T "
•) C
-•C1:
1 :.
n
C ~*
4 7 l~
1
. '2
- c
r ~i
• -|
• 0
. ' '
. C ^
. j '
1 H
*"*
I . C4
. l -*>
2.02
- 73
2-0
3.92
?.G8
1
- !}
.00
.f2
-35
. y<
.1'8
1 . ""-3
1 . 16
.7h
2.10
1 .75
:o
3-12
.M
45
-------
Table D-6. Lake Hills >ian llole Sediment Loading Observations (cubic feet)
Minimum ."'axinur. Average
Number
503
504
523
530
533
534
535
537
538
539
540
541
579
581
583
Total
Maximum
Average
Count
1979
.00
.40
2.51
5-67
1 .89
NA
5.66
.13
.25
1.26
NA
NA
1 -41
5-65
KA
25
5.67
2.26
1 1
Aug 6
1980
.00
.13
1.26
1 .42
1 .01
.00
• 71
• 38
• 25
1 .26
.00
-29
• 35
-71
NA
8
1 .42
• 55
14
1981
14.28
.00
1-13
.14
3-52
.00
8.13
.25
• 50
6.28
.00
9.62
.14
5-51
HA
50
14.28
3-54
14
Apr 1
15.83
-
2.14
.28
4-15
.00
7.71
.00
.00
1.26
HA
11 .06
NA
"A
NA
42
15.83
3-86
11
May 5
14.40
1.39
2.14
-99
1.76
.00
7.49
.00
.13
1.63
.00
10.58
-50
3-96
NA
45
14.40
3.21
14
10.17
.40
4-65
4.82
4.77
.00
7.70
.00
.00
1 .88
.00
9-62
• 57
4.10
1.63
50
10.17
3-35
15
14.70
.00
3-02
.00
3-02
.03
8.34
.1^
-38
2.01
.00
10.29
1 .06
4-95
3.27
51
14.70
3.41
15
Sep 3
13-01
.00
2.77
.00
4-52
• 35
7-71
.00
.00
1 .89
NA
9-62
tIA
4.81
1.63
46
13-01
3-56
13
1982
9.61
.26
3-39
3-20
2.26
.00
9-33
i .26
.63
1 .43
.00
12.10
1 .88
2.64
6.66
55
12.10
3-64
15
.00
-00
1 -13
.00
1 .01
.00
-71
.00
.00
1 .26
.00
.29
-14
-71
1.63
7
1.63
-46
15
15-83
1 "*Q
4.55
5-67
4.77
-35
9-33
1 .26
• 63
6.23
.00
12.10
1 .98
5-65
6.66
76
15-83
5-10
15
10.22
-29
2.56
1 .54
2-cr>
.04
6.1?
.•74
. 24
2-10
.00
9-'5
.84
4.04
3-30
45
10.22
2-99
15
-------
Table 0-7. RELATIVE CATCHBA3IN SEDIMENT DUALITY (LAKE HILLS)
S.ampl ing
CB0 Date
Total
(1) (2) So1ids«)
mg constituent/kg total solids
COD TKN Phos Ph Zr
524
535
578
626
616
592
616
626
524
528
535
549
564
578
582
592
616
626
524
528
535
549
563
578
582
3-20-80
3-20-80
3-20-80
3-20-80
3-20-80
12-27-79
12-27-79
12-27-79
12-27-79
12-28-79
12-27-79
12-28-79
12-28-79
12-28-79
12-28-79
12-27-79
12-27-79
12-27-79
12-27-79
12-28-79
12-27-79
12-28-79
12-28-79
12-28-79
12-28-79
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
'
19.1
70.5
5.31
13.8
26.?
X 91 mq/1
X 88 mg/1
X 124 mg/1
X 85 mg/1
X 111 mq/1
X 272 mg/1
X 34 mg/1
X 49 mg/1
X 158 mg/1
X 150 mg/1
54.0
13.6
40.6
46.2
427
79.5
63.7
60.7
28.8
59.7
42,400
15,700
267,000
34,100
14,500
263,786
306,818
193,548
?82,353
729,730
897,059
6,7,069
663,265
559,620
133,833
5115
213
585
439
312
55.1
315
1020
892
412
1440
55.6
11,200
4630
2130
5495
11,136
9677
55,647
19,820
11,176
35,000
10,204
35,443
4667
794
342
878
1020
778
56.0
353
1470
2010
560
199
28.4
2170
905
282
3571
1500
1758
7506
2901
25,092
2412
1592
4367
900
12.8
1.7
24.9
31.4
13.0
18.9
5.1
11.6
24.6
8.45
880
15.5
2930
1880
604
879
795
564
1588
1261
404
2647
1633
2848
800
580
236
278
262
149
13.0
407
507
465
479
318
37.9
595
906
226
13,077
511
637
212
946
801
971
17S6
797
247
166
159
146
93.0
53.5
37.0
123
211
104
120
(1) sediment sample
(2) supernatant sample
.124
-------
Table 0-7. RELATIVE CATCHBASIN SEDIMENT QUALITY (SURREY DOWNS)
CB#
510
548
559
531
534
508
510
524
548
566
526
531
534
559
578
508
510
524
548
566
526
531
534
559
578
Samoling
Date
3-19-80
3-19-80
3-19-80
3-19-80
3-19-80
2-4-80
2-4-80
2-4-80
2-4-80
2-4-80
2-14-80
2-14-80
2-14-80
2-14-80
2-14-80
2-4-80
2-4-80
2-4-80
2-4-80
2-4-80
2-14-80
2-14-80
2-14-80
2-14-80
2-14-80
(1) (2)
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Total
Solids^}
y.29
19.2
56.6
5.75
5.99
87 mg/1
40 mg/1
114 mg/1
116 mg/1
100 mg/1
1470 mg/1
144 mg/1
399 mg/1
215 mg/1
4160 mg/1
8.08
27.4
50.7
44.1
73.0
70.5
4.60
16.25
75.4
26.0
mg constituent/kg total solids
COO TKN Phos Pb Zn
269,000
121,000
92,700
489,000
445,000
206,897
500,000
175,439
189,655
110,000
42,178
145,833
107,769
144,186
293,269
'190,000
• 26,400
63,300
112,000
39,900
24,300
456,000
492,000
24,300
108,000
9710
3960
7910
12,200
27,500
9655
14,000
12,281
12,069
5600
1109
4375
12,807
2605
7356
13,500
3890
1790
1040
154
10,200
6380
4510
880
809
2020
411
168
2124
3720
632
3875
2737
629
280
255
451
814
605
73,798
1510
321
292
199
250
54.3
515
136
23.9
129
507C
806
1325
5153
2890
345
1500
263
517
400
6258
694
326
1209
1346
2080
1490
349
299
90.6
517
3510
954
477
790
540
137
245
1195
1000
919
. 19?«i
298
371
500
2544
576
241
465
685
682
472
153
108
117
177
725
317
107
365
(1) Sediment sample
(2) Supernatant sample
425
-------
APPENDIX E
SAMPLING PROCEDURE
STORMWATER SAMPLING
This appendix describes th? procedures and techniques used during the
Bellevue urban runoff study for collecting composite flow and proportional
stormwater runoff samples. The sampled basins (Surrey Downs and Lake Hills)
are described in Section 3 of this report.
The equipment installed at each site for flow-weighted composite
stormwater monitoring consists of a Manning composite sampler (S-3000), a
Manning flowmeter with an ultrasonic stage sensor (UF-1100) and a 12 volt
power converter- The samplers were factory modified for priority pollutant
sampling. All surfaces contacting the sample are either glass or Teflon.
Special cleaning procedures were developed for collecting priority pollutant
samples. These special procedures are described by METRO in their report.
The sampler is triggered at predetermined increments of flow by the
flowmeter. These flow increments need to be small enough so small runoff
events will be adequately represented by enough samples. Conversely, the
sample container should be large enough so that large events do not cause the
sample volume to exceed the storage capacity. A 30 to 50 gallon (110 to 190
liter) polypropylene reservoir with a five gallon (19 liter) glass inner
reservoir for priority pollutant analysis has been found to be adequate. In
addition, the increment of flow selected for subsampling should not be so
small that during peak flows the cycling capacity of the sampler is exceeded.
For instance, in the case where the peak flow is expected to be less than ten
cubic feet per second (cfs) (280 liters/second), a sampling increment of 600
cubic feet (17,000 liters) would produce one subsample per minute at ten cfs
(280 liters/second). It is necessary to determine the cycle time of the
sampler in the field. At the Bellevue sites, it was expected that maximum
flows would not exceed ten cfs (280 liters/second) and the sampler cycle time
was 40-45 seconds. Flow increments of 300 and 500 cubic feet (8500 and 14,000
liters) were therefore used. At 300 cubic foot (8500 liter) subsawpling
increments, peak flows would cause the cycle time to be exceeded., This
increment was used to obtain more subsamples when small events were expected.
The flow has exceeded ten cfs (280 liters/second) at the Lake HDIs site on
several occasions , briefly exceeding the cycling capacity of the sampler
during the peak flors.
The flowmeters use an ultrasonic transducer to sense relative stage.
Stage is converted to discharge by a programmed microprocessor in the.
flowmeter and presented on a circular flow chart as a percentage of maximum
rated flow. The microprocessor is programmed from a stage/discharge rating
426
-------
developed by the USGS (Ebbert, Pools, and Payne, 1983). These ratings are
described in their report. Weekly or daily flow charts are selected based on
weather predictions, with daily charts preferred for runoff events. The
flowraeter totals the flow in 100 cubic foot (2800 liter) increments and
criggers the sampler at the selected flow increment.
The subsarnple volume is adjustable up to a maximum of about A50 ml. To
ensure adequate samples from small events, the subsample volume is adjusted
to near maximum. The intake hose for the sampler is securely attached to the
bottom of the concrete drain pipe with two anchor bolts. Profiles of
suspended solids as a function of depth in the pipe during flow have
indicated that solids are evenly distributed, due to the turbulent flow, so
that no correction factor is necessary.
The samplers can be used with 12 volt batteries as a power source.
However, the motorcycle batteries supplied with the samplers are inadequate.
A 12 volt power converter was used in conjunction with a large capacity (90
amp-hour, or greater) bactery.
Calibration of the flowrneters required the use of an artificial stage
target set at zero and 100 percent of rated flow. Comparisons of discharge
records obtained from the flowmeters and discharge records from the USGS
equipment and the Manning flowmeters indicated that the Manning flowmeters
were somewhat less accurate. For this reason, the USGS flow data were used
whenever possible. The flowmeters are adequate for triggering the sampler and
for providing a back-up record of flow.
Entries on a station log were made at each visit to the stations,
describing all maintenance and calibration activities.
Storm samples were removed from the samplers as soon as possible after
storms, typically within two or three hours. Samples are kept on ice until
processed. A storm processing log was kept for each storm. Conductivity, pH,
and turbidity were measured at the City of Bellevue water quality
laboratories. Subsamples were preserved and sent to a contract lab in Seattle
(Am Test, Inc.) for the chemical analyses. Analytical methods are in
accordance with "Methods for Chemical Analysis of Water and Wastes,"
EPA-600/4-79-020. These constituent analyses and the rainfall/runoff data
were used to calculate mass loads for storm events.
It was possible with this sampling arrangement to obtain representative
storm samples for 80 to 100 percent of the runoff events. When sampling
failures occurred during a runoff event, partial samples representative of a
part of the storm were usually collected. Analyses of the sample volumes and
the hydrography determined the times of sampling. The flow charts had event
markers for each sample pulse; however, with short sampling increments,
individual event marks were not always discernible.
A quality control program for chemical analysis of runoff samples and
street dirt samples was completed. The USGS national laboratory processed
duplicates of samples sent to the contract lab. Discussion of the QC program
Is included in the USGS report. ;
-------
STKKKT SUKMCE PARTICULATb SAMPLING AND EXPERIMENTAL DESIGN
Ihe sampling procedures described in this appendix were mostly developed
in a previous study: "Demonstration of Nonpoint Pollution Abatement inrough
Improved Street Cleaning Practices," (Pitt, 1979).
Equipment Selection and Sampling Effectiveness
As part of the Bellevue experimental design efforts, various vacujm,
hose and gulper attachment combinations were tested. Relative air flows and
suction pressures in the hosf. were monitored for different test set-ups. Both
one and tvo vacuum configurations and 1.5 inch (38 mm) hoses in lengths
varying from 10 to 35 feet (3 to 11 meters) were tested, alon- with a
Vacu-Max unit. The standard "reference" system was two vacuums a.^.d a 35 foot
(11 meter) hose. The best suction and higher air velocities were observed
with trfo vacuums and short hose lengths (10 feet, or 3 meters), but the short
hose length would require that the vacuums be dismounted from the truck at
each subsampling location. This would require a substantial incrpaee in time
and labor. The longer hose, with the two vacuums, was judged adequate, and
resulted in great cost and time savings.
Twelve street dirt sampling effectiveness testt were conducted
throughout the project for several weather and street surface conditions. The
street dirt sampling effectiveness tests were conducted in an area about ten
feet (3 meters) along the curb to the street's center line. This area was
completely vacuumed using a single pass of the standard sampling equipment.
The sample was removed from the vacuum canisters and stored for later
processing. The same area was then immediately vacuumed a second time using
the same procedures. Again, the second vacuumed sample was removed for
storage. The sama area was finally sprayed with a water spray and wet
vacuumed to remove all runoff. The wetting and wet vacuuming were repeated
again, if necessary, ur.til the street surface was thoroughly cleaned. This
sampling indicated the street surface loadings that remained on the street
after the normal single pass sample collection. This is not an indication of
how much more material would wash off the street during rain events when
compared with the street sampling. Very few rain events would be as effective
in cleaning the street as the spraying and wet vacuuming procedures used in
these tests. These tests were iLainly used to confirm that the singla pass dry
vacuum procedures removed more material than the rain events and the
mechanical street cleaning equipment.
Table E-l summarizes the results of these tests. The initial street
surface loads varied over a wide range of conditions (from 100 to 1500
Ibs/curb-mile, or 28 to 430 g/curb-meter). Tests were also conducted with wet
and dry street surface moisture conditions and on streets having good to
moderately rough textures. The first dry vacuum sample collected about 40 to
85 percent of the total absolute street, surface load. The percent recovery
was slightly better for the higher street surface loads and somewhat less for
the more damp street surfaces. The sample recovery with the first dry vacuum
pass was much greater for the larger particle sizes than for the smaller
428
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Table E-l SAMPLING EFFECTIVENESS TEST RESULTS
Percent of absolute street loading
date
9/5/80
1/16/81
3/15/81
4/16/81
7/29/81
1/2S/82
2/3/82
7/29/80
2/3/81
3/24/81
7/24/81
1/20/82
1/29/82
2/4/82
total
removed by
solir's total
test street street loading solids
area moisture texture (Ib/curb-mi) (%)
Surrey
Downs
dry
wet
dry
dry
wet
wet
Lake
Hills dry
dry
wet
dry
wet
wet
wet
smooth
smooth
smooth
si . rough
si. rough
smooth
si. rough
smooth
smooth
si. rough
si . rough
smooth
smooth
534
451
223
419
1460
432
400
13/u
117
225
171
1080
297
551
75%
79
69
64
72
69
53
85
42
46
77
48
74
54
COD
59%
84
51
44
72
23
26
80
35
37
80
51
64
34
TKN
85%
58
37
41
53
20
19
93
29
17
71
50
49
34
first dry vacuuming
T Phos
47%
57
39
41
40
53
47
81
37
29
61
60
:-7
34
Leaa
50%
57
45
41
61
38
18
64
34
23
67
39
43
23
Remain ing
total solids
loading
Zinc (Ib/curb-rri )
57%
54
40
36
61
37
32
69
30
23
66
46
47
25
134
95
136
151
409
133
188
206
"9
122
39
562
77
253
-------
I'.irt K. lc si.'.rs. Almost all ru the Lir>;iT material was remo.cd with the first
v.iruuni pass, hut smaller fractions of the finer material were removed. This
u; and one wet to remove more than 90 pel:ent of the different
,ml lut.ir.Ls trom the street surface.
Tabh> K-l also shows the total solids remaining on the street surface
alter a single dry vacuuming. These remaining loading values correspond to
tl.c particulate material that was traced within the texture of thf street
surface. It is obvious that the sampling equipment was more effective than
the rains and tic street cleaning equipment in removing street surface
pa^ticulates: at no time was the street surface loading undetectable. The
lowest measured street surface loadings during this study was about 100
Ibs/curb-mile (28 p./curb-meter). The highest observed street surface loading
values were about 1500 Ibs/curb-mile (430 g/curb-tneter), with typical values
around 400 Ibs/curb-mile (110 g/curb-meter). These values represent the
particulate loadings above the non-recoverable loadings. The unrecovered base
particulate loading values shown in Table E-l can be considered as a
measuring datum that changes for different conditions.
These tests were extremely time consuming to conduct; or.ly 14 tests were
conducted throughout the program period, representing different conditions.
The most important conditions affectirg sampling efficiency were assumed to
be street moisture and texcure conditions. These two factors were considered
in a two-level factorial analysis. The 14 data points corresponding to
remaining total solid loadings on the street were separated into four
categories corresponding to the four possible street moisture/texture
conditions. A factorial analysis was then conducted to determine if either or
both of these factors were important in determining the residual loading
value. The calculations showed that the street texture was the most important
factor, with street moisture being of less importance. The calculated loading
values for smooth textured streets were about 1?5 Ibs/curb-mile (38
g/curb-meter) while it was about twice this value (270 Ibs/curb-mile, or 76
g/curb-metar) for rough-textured streets. The variations for the loadings due
to street textures depended on the texture conditions. The variation was
quite small for the smooth streets (about 65 Ibs/curb-mile, or 18
g/curb-meter) while it was much greater for the rough-textured streets (about
200 Ibs/curb-mili, or 580 g/curb-meter). These variations were large because
the sampling effectiveness studies were conducted for a variety of separate
test and street conditions. These were all small area tests and do not
consider average conditions which actually occurred in the large-scale
sampling prograns.
It is expected that the datum levels slowly fluctuated when averaged
throughout tie whole study basins. The expected fluctuation of the datum is
estimated to be about ten or 15 percent in each sampling period, •>ll within
the 25 percent sampling error based upon the variations in observed loadings.
Most of the analyses considered relative changes in street surface loadings
(comparing the initial to residual loads for street cleaning and rainfall
events and the change in street surface loading values witl time).
430
-------
Tho loading values r>* a .mi red (luring this study are considered reasonable
when ccnp.-ired with the loadings observed at other locations, is described in
Section 1. Because the major variation was associated with the constant
street textures, sampling efficiency corrections were not necessary. If there
was a large fluctuation in sampliii; effectiveness associated with season,
then it nay have been worthwhile to orrect the street surface loading values
to absolute conditions. However, thif would have required many tnore sampling
effectiveness tests. Again, the datum variation was less than the sampling
errors associated with the number of subsamples obtained. Therefore, the
sampling procedures were quite appropriate when considered with the other
errors in the sampling program. The selected sampling procedures are
sensitive to variations in loadings over large test areas which are much
larger tnan the residual loading variations.
Equipment Description
A pick-up truck was used to carry the equipment components, consisting
of a generator, tools, fire extinguisher, vacuum hose and wand, and two
wet-dry vacuum units during sample collection. The truck had varning lights,
including a roof-top flasher unit. It operated with its headlights and
warning lights on during the entire period of sample collection. The sampler
and hose tender both wore orange, nigh visibility vests. Both the truck and
the street cleaner used to clean the test areas were equipped with radios
(city KM radios), so that the sampling team could contact the street cleaner
operator when necessary.
Two industrial vacuum cleaners (2-hp, or 1.5 kilowatts, each) with one
secondary filter and a primary dacron filter bag were used. The vacuum units
were heavy duty and made of stainless steel to reduce contamination of the
samples. The two 2-hp (1.5 kilowatt) vacuums were used together by using a
wye connector at the end of the hose. This combination extended the useful
length of the 1,5 inch (38 mm) hose to 35 feet (11 meters) and increased the
suction. A wand and a <^ulper attachment were also used. The generator used to
power the vacuum units was of sufficient power (3600 watt, heavy duty,
low-RPM) to handle the electrical current load drawn by the vacuun units. The
gulper attached to the end of the wand, was triangular in shape and about six
inches (150 mm) across.
Sampling Procedure
Because the street surfaces were more likely to be dry during daylight
hours (necessary for good sample collection), collection did not begin
before sunrise nor continue after sunset, unless additional personnel were
available for traffic control. Two people were required for sampling at all
times: one acting as the sampler, the other acting as the vacuum hose tender
and traffic controller. This lessened individual responsibility and enabled
both persons to be more aware of traffic conditions.
Before each day of sampling, the equipment was checked to siake sure that
the generator's oil and gasoline levels were adequate, and that the vacuum
431
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hose, wand and gulper were
-------
the subsample strip, thfi sampler loosened it by scraping a shoe along the
subs.imple path (being certain that street construction material was not
removed from the subsample path unless it was very loose). Scraping caked-on
mud was done after an initial vacuum pass. After scraping was completed, the
strip was revacuumed. A rough street surface was sampled most easily by
pulling (not pushing) the wand and gulper toward the curb. Smooth and busy
streets were usually sampled with a pushing action.
An important aspect of the sample collection was the speed at which the
g-ilper was moved across the street. A very rapid movement significantly
decreased the amount of material collected; too slow a movement required more
time than was necessary. The correct movement rate depended on the roughness
of the street and the amount of material on it. When sampling a street that
had a heavy loading of particulates, or a rough surface, tho wand was pulled
at a velocity of less than one foot (0.3 meter) per second. In areas of lower
loading and smoother streets, the wand was pushed at a velocity of two to
three feet (0.6 to 0,9 meter) per second. The best indication of the correct
collection speed was given by visually examining how well the street was
being cleaned in the sampling strip and by listening to the collected
material rattle up the wand and through the vacuum hose. The objective was to
remove everything that was lying on the street that could be removed by a
significant rainstorm. It was quite common to leave a visually cleaner strip
on the street where the subsample was collected, even on streets that
appeared to be clean.
In all cases of subsample collection, the sampler and hose tender
continuously watched for oncoming vehicles. While working near the curb out
of the traffic lane (typically an area of high loadings), the sampler
visually monitored the performance of the vacuum sampler. In the street, he
constantly watched traffic and monitored the collection process by listening
to particles moving up the wand. A large break in traffic was required to
collect dust and dirt from street cracks in the traffic lanes, because the
sampler had to watch the gulper to make sure that all of the loose material
in the cracks was removed.
The hose tender also always watched for traffic. In addition, he played
out hose to the sampler as needed and kept the hose as straight as possible
to prevent kinking. If a kink developed, sampling stopped until the hose
tender straightened the hose.
When moving from one subsample location to another, the hose, wand and
guiper were securely placed in the truck. The hose was placed away from the
generator's hot muffler to prevent hose damage. The generator and vacuum
units were left on and in the truck during the entire subsample collection
period. This helped dry damp samples and reduced the strain on the vacuum and
generator motors.
The length of time it took to collect the subsample varied with the
number of subsamples and the test area. For the first phase of this study,
the test areas required the following sampling effort:
433
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Th-M' AKFA N,j. Of.- SAMPLING
SAMPLES PERIOD
Surrey Downs - tn Un basin lb 0.5-1.0 hr.
fair-good asphalt, concrete
gutters
Surrey Downs - lUSth Ave. 9 0.5 hr.
poor asphalt, no curbs
Surrey Downs - Westwood Homes Rd. \'i 0.5 hr.
good asphalt
Lake Hills 60 2-2.5 hr.
fair-good asphalt
In the Surrey Downs main basin and on 108th Avenue, two curb-to-curb passes
were made at each of the 16 sampling locations due to relatively low
particulate loadings. In Lake Hills, subsamples were collected by a half pass
(from the crown to the curb of the street). Tb^.se modifications were
necessary because several hundred grams of sample material were needed for
the laboratory tests and 1:00 much sample is difficult to sieve. An after
street cleaning subsample was not collected from exactly the same location as
the before street cleaning subsample (taken from the same general area), but
at least a few feet (one neter) apart.
A field-data record sheet kept for each sample contained:
o Subsample numbers
o Dates and time of the collection period
o Any unusual conditions or sampling techniques.
A tally of subsample locations where the street cleaner was unable to operate
next to the curb because of parked vehicles was kept, allowing analysis of
the effect of parked cars on street cleaning performance.
Sample Transfer
After all subsamples for a test area were collected, the hose and wye
connection were cleaned if necessary. The translucent hose allowed visual
inspection for trapped material or excessive dirt in the hose.
The vacuums were either emptied at the last station or at a more
convenient location. To en:pty the vacuums, the top motor units were removed
and placed out of the way of traffic. The vacuum units were then disconnected
and lifted out of the truck. The secondary, coarse vacuum filters were
removed from the vacuum can and were carefully brushed with a small whisk
broom into a-plastic bucket. The primary dacron filter bags were kept in the
vacuum can and shaken carefully to knock off most of the filtered material.
The hose inlet was blocked with a leg or knee, and the primary filter bag was
held onto the vacuum drum with arms and chest. The dust inside the can was
allowed to settle for a rew minutes, then the primary filter was removed and
brushed carefully into the sample can with the whisk broom. Any dirt from the
434
-------
Cop part of the bwg where it was bent over the top of the vacuum was also
carefully removed and placed into the sample jar.
After the filters were removed and cleaned, one person picked up the
vacuum can and poured it into the bucket, while the other person carefully
brushed the inside of the vacuum can with a soft three- to four-inch (76 to
H>2 mm) paint brush to remove the collected sample. In order to prevent
excessive dust losses, the emptying and brushing was done in areas protected
from the wind. To prevent inhaling the sample dust, both the sampler and the
hose tender wore mouth and nose dust filters while removing the samples from
the vacuums. Samples were then transferred to one quart (0.9 liter) Mason
jars for storage until analysis.
To reassemble the vacuum cans, the primary dacron filter bag was
inserted into the top of the vacuum can with the filters' elastic edge bent
over the top of the can. The secondary, coarse filter was placed into the can
and reassembled on the truck. The motor heads were then carefully replaced on
the vacuum cans, making sure that the filters were on correctly and the extra
electrical cord was wrapped around the handles of the vacuum units. The
vacuum hoses and wand were attached so that the unit was ready for the next
sample collection.
The storage jars were labeled with the date, the test area's name, and
an indication of whether the sample was taken before or after the street
cleaning test or if it was an accumulation (or other type of) sample.
Finally, the sample jars were transported to the laboratory for logging-in
and analysis or storage.
Variability Test Procedures
Variability tests were conducted seasonally in each test area to
determine how many subsample locations were necessary to collect a suitable
representative sample. About 50 individual locations were sampled in each
test basin during each of four variability test phases. The first test phase
data were eliminated because the samples were collected using the initial
sampling equipment that was later replaced; and because the samples wt..
biased by sand applications on the roads due to an unusual snowstorm. The
individual samples were weighed and their variabilities were calculated. The
formula used to determine the number of subsamples needed is as follows:
2 2
N = 4sVl/
where:
N = number of subsamples needed
s = standard deviation
L = allowable error
This formula was used to balance the sampling effort for the different test
phases and for each test basin. In most cases, an allowable error of about 25
435
-------
p.'roMiL ot the b.iniple mo .in vai.ic resulted in a reasonable sampling effort.
The samples h.id to be obtained in a relatively short period of tlme
(.pii'UT.ih] y within about two hours). This allowed samples to be collected
immediately before and after each street cleanirg operation. Because of the
freqvent rains in the Bellevue area, a short sampling time was also needed to
prevent samples from being rejected frequently due to rain interferences.
These samples also enabled various portions of the watershed to be
compared with each other. Bellevue street cleaning equipment could not
operate on 108 th Avenue and Westwood Homes Road in the Surrey Downs basin
because, of streets and gutters in poor condition or private ownership.
Therefore, the Surrey Downs basin had to be subdivided into these three
subsections, each requiring individual sampling. No major loading vari.'j lions
were found in the Lake Hills area.
A single vacuum was used to collect the experimental design, \d.th each
sample consisting of one curb-to-curb pass. The samples were then emptied
from the vacuum canister into a bucket lined with a plastic bag. The bag was
then wired shut, labelled and stored for liter weighing in the laboratory.
Information describing each subsample location was also obtained. This
information included the sampling date and location, the presence and type of
gutters, the street condition, slope, and width, the parking density, and the
traffic density and speed. Information concerning the adjacent area was also
obtained. This included the landscaping practices adjacent to the street, the
presence of leaves on the street, and the adj:cent land-use (socio-economic
condition, single- or multiple-residential family units, commercial areas,
vacant lots, schools, churches, or other areas). Each information sheet also
included the. individual sample loadings expressed in Ibs/curb-mile. This
information is discussed in Section 7.
DRIVING LANE TEST
Periodic street surface particulate samples were collected from only the
driving lanes immediately after a collection of a regular full street-width
sample. These samples were collected from the center lane of the street to
the edge of the parking lane. These samples were processed in a similar
manner as the regular street surface particulate samples but no chemical
analyses were performed. These samples, which were collected several times
during the second project year, helped determine the presence of street
surface particulates available for street cleaning. The data can also be used
to indicate the importance of parked cars and necessary parking controls for
street cleaning improvements.
ACROSS THE STREET TESTS
Several special tests were conducted to determine the redistribution of
street surface particulates across the street during street cleaning
operations. T>o adjacent sections of street, about ten feet (3 meters) along
the curb, were selected for each test. Several strips parallel to the curb
were marked in each section. Each strip in one section (the furthest in the
436
-------
direct'-n of travel) was individually sampled prior to street cleaning. After
the sampling was completed, the street clo.aner made a single pass over both
of the sections. The street cleaner started about one block up the street to
eliminate startup effects and broom streakings. After ;he street dried off,
the strips in the other section were then individually sampled. The
corresponding sample weights in strips in both sections were compared to
determine how much of the material was removed by the street cleaner or
pushed out into the middle of the street and not removed. The samples were
analyzed in a manner similar to the other street surface particulate samples,
but no chemical analyses were conducted.
CATCHBASIN INVENTORY ANU SAMPLING
All catchbasins, manholes, and inlets were inventoried by the Bellevue
survey crew at the beginning of the project. Recorded information included
catchbasin number, elevations (top of grate, bottom of catchment, and all
pipe inverts), size, type, and length of each pipe. The Survey Division then
mapped the drainage systems.
The first sediment inventory was conducted during December, 1979. At
that time, the catchbasin dimensions were measured. The sediment depth was
measured by pushing a tape measure or a measuring stick into the sediment
until it hit the bottom of the catchbasin, A second sediment inventory during
July and August, 1980, was also conducted. The procedure was changed when it
was discovered that a rock may be struck on occasion instead of the bottom of
the catchbasin, resulting in a false depth value. The final measurements were
made from the top of the grate to the top of the sediment; a simple
measuiement that did not require lifting the grate. The catchbasin depth was
known and the sedimc-nt depth was then calculated. Pipe sediment and standing
water were also observed through the grate.
The sediment inventory was conducted about twice yearly during the
project. Spot checks were also made in about ten percent of the catchbasins
after several significant rains.
Sediment samples were also taken during the inventories. Five
catchbasins and five pipe sediment samples were taken in each area during
each sampling. Samples were originally obtained using a scooper, pouring
excess water off before transferring to a sample container. Finally they were
obtained with a coring device. Excess water was pumped out of the top of the
corer before pulling the sample out. Usually three to five cores were taken
in various spots in each catchbadin sampled in order to obtain enough sample.
Pipe sediment samples were also scooped or scraped out of the pipe. Samples
were weighed, dried, and sieved into size fractions. Some of the sample
fractions were then combined into three samples for chemical analyses: <63
microns, 63-500 microns, >500 microns.
Ten sediment and ten supernatant samples were taken from each study area
in February, 1980, and another five sediment samples were taken from each
area in March, 1980, for chemical analysis (Total Solids, Chemical Oxygen
Demand, Kjeldahl Nitrogen, Total Phosphorus, Lead, and Zinc).
437
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APPENDIX F
STREET DIRT SAMPLE PREPARATION AND DATA HANDLING
INTRODUCTION
This appendix summarizes the street surface particulate handling
procedures used in Bellevue. These procedurp^ w.=re used after the samples
were collected and before Lhey are sent to the laboratory for analysis. This
appendix also briefly describes the preliminary calculations and organization
of the data needed before detailed data analysis. Recommended procedures for
obtaining street surface particulate samples were described in Appendix E.
Originally, these techniques were described in the report "Demonstration of
Nonpoint Pollution Abatement Through Improved Street Cleaning Practices"
(Pitt, EPA-600-2/79-161, U.S. Environmental Protection Agency, August 1979).
Modifications of these techniques for the Bellevue Urban Runoff project have
been discussed and approved by EPA project officers during field visits. The
scope of this appendix is limited to the discussion of the day to day sample
handling practices necessary to prepare the samples for subsequent laboratory
analysis.
SAMPLE DESCRIPTION
Specific information collection tecuniques were employed for consistency
and proven ease of data collection. Table F-l is an example of a checksheet
that can be used during the experimental design of street surface sampling
activities. These activities require about 50 to 100 individual street
surface sampling strips to be cleaned. All of the samples are then
individually weighed. This results in STL indication of street surface
particulate loading variations over the study area. The characteristics on
this checksheet are noted for each individual sample and are stored for
future reference. This information is extremely useful in determining the
causes for extreme loading values observed at any specific sampling location.
The information in Table F-l can then be summarized on a percentage basis to
describe the specific test area characteristics. The most important test area
characteristics include the street surface and curb-street interface
conditions.
INFORMATION TO BE NOTED DURING STREET CLEANING OPERATIONS AND SAMPLE
COLLECTION
It is Important that the street cleaning equipment operator fill out a
simple form every time the test areas are cleaned. Table F-2 is an example of
a form that is used to confirm street cleaning activities and to note unusual
438
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-l. SAMPLE AREA DESCRIPTION
STUDT AREA:
LOCATION:
MTZ:
FHOTO KUXBKR:
H 'I Aci I <- \
M
SAXPLZ INTOIXATIOS:
I.D. Number:
Weight* (grami):
Loading* (Ib/curb-aile):
GUTTERS:
Number: 1 , (5> 3 ,
Type:
Shape:
Mediae atrip:
STREET: -_
Material: e oner gt_t^Cji phi It-^othtrt
Condition: poorfjTijO tood
Vidth: < 20 ft^20_iojl>''11, > 40 ft
CURB/STREET INTERFACE:
Condition: poor , (£fif) gi^od
CDtB T7PE (at
locition): rolled,
Type: paved drivevay, dirt driveway, corner,
curb f«T, other**
TRAJFIC:
Deniity: dihi^ coderate, heavy
Average Speed: < 25 aph,
PAJIKING:
Deniity: none,1
SDRSOUND1NG AREA:
Land uae type:
to 40 nph), > 40 »ph
.
>oderate, heavy
lov incoae/old/alnjle fanily
mediun incoae/nev/ainglt fanily
*>-ltiple family
cotonercial
vacant land
•chooli
other**
g vegetation:
Vegetation dentity:
Leavec on atreet:
Topography:
deciduoua
•parte
tparat,
other:
AJIEA ADJACENT TO CURJ XKD SIDEWALK:
Surface type: (""graa>>
paved
unimproved (dirt, rocka)
other:
COMMENTS:
*Tbia information ia to be recorded after laboratory analyaea have
been conducted.
439
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l'U.- K-2. INFORMATION FOR STREET CLEANING TESTS
STODT
DATE:
EQDIPKEN7: .
Onit nanber or n«oe : V^.O X3 M A 3
Adjusted ti ijecified _
for thi« tut: (Teip no , other*
TIKE:
St«rt of teit:
End of test: /
HOPPER CONTENT:
Impty before teft? CjeT) no> "'her*
Estimated volume or weight
»fter test: V 2— (JuT yd«6y poundi
COMMENTS:**
OPERATORS SIGNATURE:
•Explain "other" under COMMENTS
"Note «ny unutuil condition* (e.g., vind, r»in, cooitruction, ftreet
•Ltintenance, tpilli)
440
-------
conditions. The important parameters are the dates and times of street
cleaning and an indication of weather conditions that may_jadversely affect
the street cleaning operation. V
Similarly, the street surface partirulate sampling crew must also fill
out a simple form for each sample collected. Table F-3 is an example form
which notes the important information necessary to resolve future likely
disputes and inconsistencies with times, dates, weights and sample numbers.
The time at the start of the collection and at the end of the collection is
noted. Subsamples collected where the street cleaner was unable to operate
next to the curb were noted on the sampler log. This results in an indication
of the parked car densities in the study area.
When the samples are transferred from the vacuum collection equipment to
the storage canisters, the date and test area is written on the can, along
with the type of sample. When the sample is returned to the laboratory, each
sample is given an identification number which is also written on the can and
on the sample checklist.
PHYSICAL ANALYSIS
The sample description information written on the test area sample
checklist at che laboratory is also noted on a sample inventory sheet. Table
F-4 is an example of this sheet and shows the chronological inventorying of
each sample immediately after collection. The samples are then prepared for
particle size and chemical analysis.
Most street surface samples are quite dry and do not experience chemical
or biological degradation, over short storage periods, of the constituents
typically monitored. In many cases, street surface particulates can lie
exposed on the road surface for up to three months before rains wash them
into the receiving waters. During this time, they may be intermittently
moistened and subjected to a wide range of temperatures. Although the
laboratory storage times should be kept to a minimum, they are likely to be
several months long due to the necessity of compositing samples over testing
time periods, as described later in this section.
For physical analysis, the samples are transferred from their storage
containers to well-labelled drying pans. These pans are then placed in a low
temperature drying oven for several hours at 70-75 degrees F (21-24 degrees
C). Again, this heating does not typically affect the chemical
characteristics of the samples, except for the more volatile phosphorus and
mercury compounds that may be analyzed in street surface particulates. If,
through special tests, appreciable quantities of certain constituents of
importance are lost during sample drying, then subsampling of the complete
sample mixture for analysis for those specific compounds may be necessary.
However, because of the heterogeneity of the street surface particulates,
obtaining a representative subsample from the whole sample is extremely
difficult and can introduce significant errors. Table F-5 is an example of
the data form used when drying the samples. The gross and net weights of the
samples are noted and the percent moisture is calculated. Again, this
441
-------
!> . STREET SAMPLING CHECKLIST (for use during
field program)
SAX7LE:
I.D. nuaiber: __
Type: before itreet cleaned, after afreet cleaned,C^ccv»uia:ion_J^)
STUDY AJL1A:
H
DATE:
TIME:
-3:
At itart of aampling:
At end of sampling:
SDB-SAKPLE
SHIP TALLY:
Jf
tti
ITS
if
** 5
-W5
XT
Check off the
ouabert a> tbe
atrip lanplei
are collected
(tach itrip ia
aaiuaed to be
located betveen
the curb and the
center line; i.e.
half itripi).
riaj location!
where parked
cara interfered.
PAMINC INTERf ER£NCE:
Totjl number of ftrip
(*nplei collected:
Stripi vherc parked
c»r» interfered:
Parked car dentity
(percent):
SAMPLE WEIGHTS:*
Croat vet veight (grami):
Tare veight (grtau):
Mtt vet veight (graaa):
115V
COMXENTS:
SAMPLING TEAM KEMEHS:
*Thia information ia to be recorded after laboratory analyiea have been
conducted.
442
-------
P-4.SAMPLE INVENTORY SHEET
SAMPLE
ID
NUMBER
>\9
5-?o
A-91
S^l
S-rz.
S-4n
DATE
COLLECTED
inl&o
3/k
3/(*
3/| •*-
3/14
3//4
TIME
COLLECTED
0^30 -?
0^30
0?CrO->
09trD
0^3O^
/ 0^-0
osiro-j
0^ 6^0
0^30-^
O?30
I(J-LTO^
I03o
STUDY
AREA
!Mi4A.U>
VvM^aW
\0\M*-y
W\'d i k
WN'cloW
Ufpty
NET WET
WEIGHT CT
UN ',EIVED
SAMPLE
(graai)
nw5.
1^3
3^0
inr
IZgD
n>r
COMMENTS
Vz 5 V^
tl
II
I/
II
'/
443
-------
r- .MOISTURE CONTENT DATA S11EET
SAMPLE
ID
NUMBER
DRYING
PAN
NUMBER
TARE
WEIGHT
CROSS
WET
WEIGHT
(grtmi)
CROSS
DRY
WEIGHT
(gruni)
NET
WET
WEIGHT
NET
DRT
WEIGHT
MOISTURE
CONTENT
(perctat
A
5"
A?
£-30
A 3
2-9
S-34-
730
)o/4
L
I, SI
z
Noce: d - b - •»
e • c - «
d •• c
- x ioor
d
444
-------
complete information must be noted for each sample in order to resolve
problems Lh.it may later occur due to misplacing or mislabelling samples.
After adequate drying, the samples are passed through a set of
mechanical, stainless steel sieves for size separation. The sieve sizes being
used are b3, 125, 250, 500, 1,000, 2,000 microns, and I/A inch C.6,370
microns). If the sample contains large amounts of coarse material it may h?
necessary tc pass the sample through a I/A inch (6,370 micron) coarse sieve
made of hardware cloth attached to a wooden (25 by 100 mm) frame, about two
feet (600 mm) square. Samples less than 63 microns are retained on the pan on
the bottom of the sieve stack. Table F-6 is a worksheet showing the
calculations for this sieve analysis. The gross weight of each sieve plus
associated retained sample is noted along with the tare weight of the sieve.
A top loading precision balance is required for the weighing. The net dry
weight of this sample is then shown and totaled. The percentage of sample in
each eize fraction is also calculated and presented on this sheet along with
the pounds per curb—mile (or g/curb-meter) loading factor (the calculation
for this will be described later). It is important to note that detailed
sample descriptions are presented on this sheet. Specifical1y, the sample
number, date and test area are written in along with the total net raw sample
weight as shown on the initial sample inventory sheet. This weight is then
compared with the total net weight for the sample. The net raw wet weight is
not as precise as the total of the sieved dry weights (because of the sample
drying and different scales typically used) but there should usually be less
than a five percent difference. If a large discrepancy exists between these
two weight values, then the sample should be rechecked by observing the notes
from the sample drying, inventory and test area checksheet along with any
other information available. In addition, the percent sample should add up
close to 100 percent.
CALCULATION OF STREET LOADING VALUES
The calculation to convert the quantity of sample expressed ir, grams to
a representative street loading value expressed in pounds per curb-mile (or
g/curb-meter) varies, depending upon the sampling technique and equipment.
The
width cleanr with each subsample strip is slightly wider than the gulper
width, beca se of material being drawn into the sides of the gulper. The
actual cleaning width can be measured directly on the street when sampling a
moderately dirty street surface.
A variety of subsampling procedures may be necessary depending upon
special circumstances. At least 200 grams of sample are necessary for the
mechanical sieving analyses. Therefore, if the streets to be sampled are very
clean, then multiple adjacent subsampling strips may be necessary. In other
circumstances, traffic hazards may prohibit sampling from curb to curb, and
curb to crown subsampling strips may be necessary. Table F-7 shows the
equivalent number of full strips for these various subsampling schemes, along
with the number of subsampling full width strips necessary to make one
445
-------
l1 . PARTICLE SUE ANALYSIS DATA SHEIT
STUDY ARF.\:
DA IT SAXFLED:
DATI AJiALYTED: 3 / 3 °
SXKH.E
ID number :
Nee r*v weight (gr»a»):
- 4
SIEVE
SIZE
(aicront )
) 6370
2000 -»
1000-»
5000)
| OTTO
250-^
125-0
63 'i
\T-S"
<63
TOTAL
TARE
WEIGHT
(jr»a«)
*
0
4%-L
AA1
A-bA
403
3Ti
tt
3>)
—
CROSS
DRY
w E; en T
(graai )
b
•r*
s^^
57J
4ST
Cr 7~J A
/\ "7 ^T
3^
"5^5-
—
NET
DRY
WEIGHT
(grtmi )
c
3>
fo
rz.t
JT)
'0|
5T5
2,0
A
4^
AKOUNT OF
SAXPLE
REMAINING
ON SIEVE
(percent
of total
net dry
weight)
d
?„>
1^*5
^.3
lO^Co
ZIJ
10.4
t\ (. Z
o.
32-r
13-0
z.c
31)
COKXEKT3
y^^V \*««s
•Se« eqoitioc 1 to convert net dry weight per staple (fr«a
-------
; Ic F-7. EQUIVALENT NUMBER OF FULL STRIPS FOR VARIOUS SUB-SAILING
SCHEMES
SUBSAMPLING
STRIPS
12 half-strips
3 double-strips
10 half-strips
14 half-strips
16 half-strips
4 double-strips
18 half-strips
20 half-strips
5 double-strips
30 half-strips
40 half-strips
10 double-strips
EQUIVALENT NUMBER
OF FULL (CURfl-TO-CURS STRIPS)
6 full-strips
5 full-strips
7 full-strips
8 full-strips
9 full-strips
10 full-strips
15 full-strips
20 full-strips
50 half-strips
25 full-strips
447
-------
curb-null1 (.IK'O eurb-melers ) .
Sl'MMAKIKS OF KAIN KVF.NIS
It is very important to keep careful records of the precipitation events
occurring during the nroject period. Tables F-8 and F-9 together are an
example ot a complete rain record. Table F-8 summarizes the total amount of
rain that has occurred on each day during the project period. Monthly totals
are also ^hcwn or. Table F-8. This table is used to determine the antecedent
dry conditions before any sample and it also shows the variability of
precipitation within storm periods. Table F-9 presents more detail for each
of the stOirn/3 that occurred during the sampling program. This summary also
shows which scorms were monitored at the runoff monitoring stations and which
rains are considered significant.
A signalicant rain event is one that is capable of removing most
(greater than 9C percent) of the street surface particulates from the street.
Some of the smaller significant rains, however, may not be capable of totally
moving all of the street surface particulates through the storm sewerage
system and into the receiving waters. A storm of about 0.2 inch (5 mm) total
(occurring over several hours and during periods of moderate to heavy
traffic) can move most of the street surface particulates from the street and
into the drainage system. Therefore, rains of this magnitude, or greater, are
typically considered significant. If the street surface material is very
coarse, caked with large quantities of debris (mud or leaves), or in very
poor condition, a much greater quantity of rain may be necessary. In
addition, if the rains occur at nighttime, or at other periods of very low
traffic activity, then more rain would be necessary to remove most of the
street surface oarticulates. Traffic volume is an important consideration
because of the ability of the vehicles to loosen particulates from the road
surface. The rain then only has to transport material to the curb and along
the curb to the storm drainage inlet. The smaller rains, however, are
probably not sufficient to move the material through the stonn drainage
system into the receiving water. Therefore, this particulate material would
accumulate in the sewerage system to be flushed out by later larger storms.
Storms of about 0.5 inch (13 mm) total, occurring within several hours, are
usually capable of removing all of the street surface material and moving it
all the way through the storm sewerage system and into the receiving water,
irrespective of traffic conditions. However, larger rains cm result in
significant erosion yields from the surrounding land areas. This erosion
material is washed onto the street surfaces and into the stonn sewerage
system. In some cases, the street surface loadings after storms can be
greater than the loadings before storms, because of this erosion. In areas of
the semi-arid west, rains of about one inch (25 mm) or more, can create much
greater erosion yields for many constituents in urban areas than the street
surface runoff yields. However; in areas of the Midwest, much greater rain
quantities are necessary before significant erosion yields contribute to the
urban runoff flow.
Table F-9 also shows the time of the beginning and the ending of the
rain event. These values are compared to the times of beginning and ending of
448
-------
r,iLlc K- 8. DAILY RAIN RECORD SUMMARY
WATER YLUl
RAIN GAUGE:
5cW? I.
DAY
1
2
1
it
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
TOTAL
OCT
l4ft>
air
O.S4
0.07.
I.U?
0.0 1
O-OT
£>Br>|
234
NOV
A4SO
0-01
r-sz.
D.r>)
o.oT-
o*o~3
(0-0"?-
0-JK
o-OT
0-4 I
O-T.-L
o^lO
?«•»/
DEC
\q§o
0.44
0.13
I- 5*7
Mc
o^?-
o,2r
C»t3-
W\
JA>»
^91
0> 0\
o-o i
o.oi
0.dT
<9
O£>\
Q.Ol
fc.tT
MON
MAR
H8I
o=23
0.05"
0-?£-
o-r^-
o-?q
n-oi
a 03
o.oi
OoOl
0»l^
O"0(
IcSJ
TH
APR
11^1
0.30
CP.^f
o»\ 1
0C01
0»\^
l»4sr
MAY
H?l
0-cz
O-oc
5.oA
0.03.
o-oi
O.IS
JUN
>^«l
CaOl
Ood
JUL
!
-------
F-o. SUMMARY OF RAIN EVENTS DURING FIELD ACTIVITIES ***
DAT!
RAIN
1ECXK
a^-Vff
\-t-t\r
H /H
\fl/?i
^*
TIKI
SUIN
JECAJI
os3o
D^'S"
0^30
oiy)
war
DATt
LAIN
IKDED
H,'l>
\Viy
^A-|
^T
V.'S
TIKE
IAIN
1KDED
V?lTO
T^JO
cM*r
-2-3 iy
\T^r
DDJUTIO)!
(bcurt)
\T-5-~
t5~^
0.3
\A.Sr
t -0
TOTAL
mcip-
TTATIOK
(iochci)
€><^
6. or
0.0)
0.34
U-Z4
ATZRjkCI
irrmsiTT
(inc'dti/
hour)
o, o3
e>0cro3
o »oi
0^ OT_
Oo-L|
rixx
IKTIHSITT
(incbti/
hour)
0. \ A
o, 03
o.oi
0005-
0^40
.
UAS TEE
I7TKT
XOIIITOLED*
(jPtt/Do)
r
^
/j
r
A-1
WAS TIE
mrr
ticNin-
OUTT"
(yt«/no
y
/y
A^
/
Y
•"Monitored" requirti <11 raio «nd runoff Be««urr»ento bttvttn «dj»c«nt icttit >urf*c« i»pl«i.
TIic ti»e iloci the r*in toded mnd the "«fter" itrett lurfact scaplt ihould b* Itn tb«o on«
d*7, in «o»t
**"Siinif ir«nt" •• dtfintd in the tizt.
*"ME*ch nin ~IT«DC" i« i*p«r»t«d by at lt»t 6 hour* of no precipitation. Several adjacent
rain tTenti ar* u«u«llj grouped togtther to *ake a coaplct* aonitortd *di ;« »«t". See tbe
aboTe definition of tbe "monitored" criteria tbat define* a complete data act.
450
-------
runoff to obtain lag values and are necessary in order to calculate the
accumulation periods for street surface: samples taken near a rain event.
VKLPAKAT10N OF LOADING SUMMARIES
Simple summary forms are necessary to display the straet surface loading
results for accumulation and test samples. Tables F-10 and F-ll are examples
of completed summary forms. Table F-10 shows the size distribution and
loadings for a street surface accumulation sample. Information shown on this
table include a complete sample description along with the climatic
conditions during the time of sampling and for the last rain event. The
median particle size is also shown or; this table. Table F-1J is similar, but
a pair of street cleaning test samples are presented side by side with the
loading en fference calculated and expressed as the street cleaning
effectiveness. The amount removed, expressed in pounds per curb-mile (or
g/curb-meter) is stressed, brt the percentage removed of the before loading
is also presented as a normalized value. The times of street cleaning and
sampling are also shown on these forms in order to calculate accumulation
periods and to confirm the test scheduling.
SAMPLE COMPOSITING FOR CHEMICAL ANALYSIS
Before any additional preliminary calculations of street surface
particulate characteristics are possible, chemical laboratory analyses must
also be performed. The most cost effective procedure is to physically
composite similar samples before chemical analysis. After mechanical sieving,
the different particle sizes are stored in separate plastic bags or bottles
as appropriate and replaced in their original storage containers. The
compositing involves combining equal quantities (typically five or ten grams)
of each size fraction of all samples collected in a single study area over a
short period of time. Equal quantities from each bag from the same particle
size, but different samples, are combined to obtain a composite sample
representing a single particle size for all samples in the compositing time
period ana test area. Leftover samples are replaced in the cans and saved.
Equal sample quantities must be composited because we are interested in
obtaining a time averaged chemical analysis of the material. The time phases
for compositing should be based upon major seasonal differences and street
cleaning practices conducted within the areas. Table F-12 is an example of
how the time periods could be identified. This table shows six different time
phases for three different study areas. The time periods range from a short
two weeks for special leaf removal tests up to six weeks. A total of eight
size ranges, times six time periods, times three test areas, or 144 samples,
will be prepared for chemical analyses. This will result in chemical
descriptions of specific particle sizes within time and area subunits. It is
much more important to analyze different particle sizes for the different
chemical constituents than analyzing each separate sample. The chemical
concentrations vary substantially within each particle size. This variation
is shown to be much greater than either seasonal or aerial variations. In
addition, it is very difficult to subsample a complete sample to obtain a
451
-------
o F-io. STREET SURFACE LOADING - RESULTS OF TESTS
1—CH^&V
STUDY AiEJk:
SAKPLE CODE: A~ 104
Dl^TE SAKPLED: \
TIKE SAKPLED: I (J
Hog
VZATHES DOKIPG SAKPLIHC: (TTTFppartly cloudy, cloudy
viody, moderately «ind
ANTECEDENT CONDITIONS
Tint tince Ult ivepc (d*y>):
L«it rain:
date :
precipitatioo (iocbci):
duiatioo (boura):
int«oiity ( iocbci/hour) :
cine aince laac raio (dayi):
Tint lioce lait significant rain (dayi/:
. O A
TOTAL HET CRT UIICHT:
SIEVE
SIZE
(•icrona)
>6370
2000 - 6370
1000 - 2000
500 - 1000
250 - 500
125 - 250
63 - 125
<63
TOTAL
AMOUNT OF
SAKPLE
KEKAININC
ON SIEVE
(jrua )
'2.1-4 f
131. T
xsy. 1
|0^,-1-
A 7-0. •">
Xfcfo.Y
\ t5". lo
A-o-'J-
134(4
(percent of
total ntt
dry veight)
I."?
1**- I
a-.o
if »9
14-fc
•3.0
,OP,I
AMODKT Of
SAKPLE PASSING
SIEVT. (ptrctot
of total ntt
dry vti(ht)
[(TO. 1
i %-.a
'3~Ir>5~~
(r> ? » 4
C.1.4
|~5. (^
•3 o U
FAtTICLI«
LOAD IMC DCT
(Ibi |xr
curb ail*)
ir- i
i -^ -3,
^?-/o 1
1/C,
|-3T-
'i-t, ."7-
-------
-p*
U1
oo
STUDY A1U:
LOCATION:
tun innua:
Tin IAWLID:
Ilr««l cU«*«4:
iqoinoirr OUT tor
1 r«
1 Ov-~*-<
Mook
57 1 (p ( 'f-L-
OU AVD/OI HAMK:
imciotrr COHDITIOIIS:
CvJJ-t~ Ti» .i.e. lot ~»t U.r.): '
U.i r.i.
..,.: -57(r79-^-
/CnTD ...ci.il.U.. .o
X5"-5"
1Z»3
lb.1
G.4
100, '
AKOOITT Or
futruc rASSMC
SltVl (p.rc.nt
drr w*iibt)
lao-l
IV'1
l/.c.
^r. i
^lol
AS~»t
Z3.-3
t.4
FAITICU
LOADIIIC HT
(Ib. ^r
^-3
s~a.5~~
)OI
5"i*5-
ni
Ko^
n-k
49. t-
"9-^1
NZDIAH MIT1CLI lilt l.icro.. ): '^i.°l *^
jLTTta STicrr UAS ctEAnD
UMFLE I.D. mnoEa
AMOOMT OF
SAMPLE
IEMAIII1MC
OM SIEVE
(p«rc«ot of
total Mt
dry w«iftht)
I--L
&*L
11.1
6. A
^U>
Z3U0
i^.r
fe.4?
«?^-"2-
Amurr or
ujfn.i rtjsiKC
S1IVI (p.rc.nt
Of tOt«t B«t
4ry ««i(bt)
9^.-L
9^0
^•4
7^-5-
^/. 1
4^-4
O-t.A
fc.1
.
fAITICU
LOAD I 1C DIT
(Ui p«r
t.ik .il<)
S--8-
4.0. k
S5-.1-
30-T-
102
Jo»
f/.fc
3^J'
Ate,
KIDU« FAIT1CLI till (.lcrx») "Z.S~^-
STIECT CUAIIIK
ErrECTlTCMUS
AXOUWT 1LHOTID IT
ITUIT CLJLAKU
(Ib. ^r
»tl> «il.)
3.r
136^
4-sr.o
O-T.^
g-9
5^
34
15-. i
•l^o-
of total
«t
35-
-z~^~
•JT-
3*-
nOIAI M1TIC1.I III! l.icr«i»l "3 4"^-
-------
Table F-12. STREET CLEANING SCHEDULE
ivt Day Work U*«k
I.D. Code
(or
»po*ile Staple
KUHici or JTterr CLUU«I«CS Kti*c THE WIQ
Study Locf (
Study Lo<;«tigg Stiidj^^gc^tioa g;udT Location
0
&
-------
representative five or ten yrams. The extreme heterogeneity of the samples
makes this impossible withr-ut having to mill all of the sample and then
remove the small quantity necessary for chemical analysis. It is much easier
to select a representative five or ten grams from each particle size because
of the reduced physical and chemical variation within that size range. Each
composited sample is typically made up of five to 20 subsamples. These
composited samples are then placed in small sample containers that are
thoroughly labeled and sent to the laboratory for chemical analysis. Tht
laboratory will have to mill the coarser samples before they are analyzed.
Care should be taken to design a chemical analysis program that will key in
on the most important constituents and those that are least affected uy the
required collection, storage and handling techniques. If special chemical
analyses, such as priority pollutants, are necessary, then special samples
should be collected and handled specifically for those analyses.
After the chemical analysis results are obtained from the laboratory,
the chemical strength (concentrations expressed in micrograms of constituent
per gram of total solids) should be summarized as shown on Table F-13. Table
F-14 presents an example of the loading caJculations for each of these
constituents for an individual sample. Each sample collected within the time
frame and for the specific test area should be identified for each composite
analysis and the appropriate concentration factors used. Table F-14 also
shows an example calculation to obtain the appropriate street surface
loadings.
SUMMARY
This appendix describes the laboratory handling of the street dirt
material before it is sent to a laboratory for chemical analysis. The
preliminary data calculations and summarizing formats are also briefly
described. After these stages are completed, more detailed data analyses need
to be performed. These analyses include the determination of the accumulation
and deposition rates of the various street surface particulate
contaminants,and various measures of street cleaning effectiveness. Initial
and residual street surface loadings for different street cleaning
frequencies, and residual loadings as a function of initial loadings for
different study area characteristics also need to be identified, j..- addition,
as runoff monitoring will also be conducted simultaneously with street
cleaning, the effects of streec cleaning on runoff water quality will also be
addressed in the final project .report.
455
-------
Table F-13. CHEX:CAL COKPOSITION OF STREET DIRT SAMPLE
SIEVE
SIZE
(microns)
l>6370
2000 - 6370
1000 - 2000
500 - 1000
250 - 500
125 - 250
63 - 125
<63
Pb
1- '
<\^
^ratn of total solids^
Zn
C,%'
-ve
\30
^ rro
OPO.
4
7^%-
i>
2-6"
X^
T-5~
•7-1
3 '-?
5^
s
^Kro
Sin?
^rcro
\~IMO
1 4^'D
I^LTO
1^1 LfV
'2_
17,0
Cr
VfT
(T^r
i>4
iSr?-
14-3
1 ¥5-
•Z-4
S-4
vs
W6K
^6u
Illk
!04k
^4K
I-ZK
)i3U
O>K
en
en
Study Area:
Compo.it- Dates
Note.:
-------
Table- F-14.STREET LOADING CALCULATIONS FOR CHEMICAL COMPOSITION
SIEVE
- IIZZ
(•icrooa)
>6,170
2000 - 6170
1000 - 2000
500 - 1000
1
250 - 500
i
STREET LOADING (Ibi Btr curb »ilt)
•olid.
W
\T>\
Ib4
W.?
i ^JfT\
I D L/
125 - 250i |T,^
[
1
« - 1" ,0k
<63 j
Total
I
W
k 1
Pb*
0.0t>3
0.017.
OolS"
O.I4
O.ST-
0/ST-
0.3C?
o.,r
i.g
Zn«
O. W33
O.OJO
0.014
O.Olta
0.053
O.ObO
0-053
O-Oj (0
o.rr
COD*
ll
,(.
Z3
?.r
^
^
»30
p*
O.ai>
O.P>,
O.O'fT-
0.03?
(90CX?5~"
0. ^7^
u,fV7-
0,047-
0.*-
OPO •
0.0013
fl-oua-
0. U"D^|
L9«(TO(^
6X^045"
O.tWSir
O.OD4/
o.unr
o.ozr
i«
0.034-
O.W
0./5-
0.0^
e?.7,s~
0^3
0.22-
Oo,r
/.-z-
Ai*
0.00,,
0.**
QtU^lL
a.o»u>
o, WAG
O.VO-LO
Wl
O..JLO
Cu«
(9.01733
*«^
O.^a-4
0o-W
0,0 n
0.0/5T
0,0,,
OP cn")f.c
>r,57
Cr»
O.OT4J
0.01^-
0,^9
ao,T_
0.07.9
0.^
0.0,0
a.,37
OcO
V
9-
;z.
/r
fc.
ifc.
^
/z.
r
^-> ,
9 c
•Calculation:
cbcaical £ - (total aolida) z [cooc«ntr«tioo of I) x
(lb§/curb-«il«) (Iba/curb-nil*) (•icro(roi>/|ra> total aolida)
**For total aolidg amount a** Table 10.
>icro|raaal
Sa»plt Cod. and
S«plt Data:
Taat
Hot..:
ot Sfaplt:
-------
..I'i'FMUX ,;
OK IKhAN Kl'.V'.'F IMLMTANTS
Yhi-rf I.'vo N'fii r:inv stiulies in the past that h.-ye >->:amined dif.rrent
sinirci'^ iv_ arban njimit pollutants. These ref>.• rences have bjen reviewed as
,\H t <>:' this sti'.l-, and tin- results are summarized in this section.
Mp-iticanr Mb an runol'l pollutants are defined as having a potential
rei.-oi.vim' W.-U-T impact. Xost of these potential problem pollutants are
iue;it i t iod by siyiiiic,,nt concent rat ion increases in the receiving waters or
sed imeiu;. , as i-t>rrr,>a red Lo areas nut affected by urban runoff. Others
i! isi-usst'd lie not or io- s.l y toxic and present in urban runoff, but their
conrent i .) t i OP.S in the njnoff may not create significant water rroblec,s.
Sediment ace urnv. i ;i t i on and bioaccuir.ula t i on of trese <_oxic '.x>l lutant s , however,
ni.,y be h.'iza.' O-^us .
Tile import;;nt sourcet> of these pollutants are ""elated to various uses
and processes. These inr iudv_ natural sources, s-ich as rock weathering t.o
proauct soil (and s-oiubi !•( ty produces of Lhe 'najor roc1', components),
>'.rou inwater in^ i 11 rat i on , volcanoes and forest fires. Automobile-related
pv.enti.il soiirci. •; usually affect the ro?d dust and dirt more importantly than
Dthe:' particular components of the runoff sysem. The road dust and dirt
quality is aitected by -'ehicle fluid dr'ps and spills (gasoline, oils, etc.)
and i;asol;ao rocibusLi on, ?long wiuh various vehicle wear, loca] soil erosion
and pavrvntiit wear products. Urban "agricultural" practices potentially
affecting jrban n-.noft irclude landscaping (vegetation litter, fertilizer and
pes:icidi- v.st < and animal wastes. i-Kscellancous sources of urban runoff
p., 1 .utanLs include fireworks, wildlife and possible sanitary wasttwater
1.111 i 11 r.s 11 on . ^recipitation and atmospheric fallout are both affected by
urban luno'rt pollurant retuspens ion after initial deposition. Pesticide use
in ar urban area can contribute significant quantities of various toxic
materials to urban runoff. Many manufacturing and industrial activities,
including the combustion of fuels, also affects urban runoff quality.
Therefore, it is extremely difficult to identify a small number of activities
th-\t contributes most of the significant urban runoff pollutants.
Natural weathering and erosion products of rocks contribute the majority
of the hardness c.nd iron in u^ban runoff pollutants. Roar1 dust and associdted
automobile rse activities (gasoliae exhaust product?) contribute most of the
lead in urban runoff. Road dust, contaminated by tirt wear products,
contributes most of the zinc to urban runoff. In certain situations, paint
c'.ipping can al;;r> be a major source of lead J.n urban areas. Urban
agr .culturai activities can be a major source of cadmium. Electroolating and
ore processing activities can also contribute much cadmium. Most of the
mercury released into the environment comes from the chlor-alkali and pulp
458
-------
.Ki.i i\-,\ or industries. M.ir.v ;>>:lut,int sources ,ire specific to a particular
.it--.i .11.d on-i;oinr. rutivitit's. For exnmplo, iron oxides are associated with
vol.iiiu-, i.per.it i'V.is ard strontium, used in the production of flares and
tiieuoiks, would probably be found on the streets in greater quantities
ground holid.ws, or .it the scenes of traffic accidents. The relative
i-c-i-i ribution i.t each of these potential urban runoff sources is, therefore,
hijjhlv variable, depending on specific site conditions and ssasons.
Uil.MlCAL iM/ALl TV OF ROCKS AND SOILS
Almost nrlf of tne lithosphere (the earth's crust) id oxygen and about
J i percent iri silica. Approxinately eight percent is aluminum and five
percent is iron. Elements comprising between two percent and four percent of
the lithosphere include calcium, sodium, potassium and magnesium. Because of
the great abund.i >e of these ma.erials in the lithosphere, urban runoff
contributes only a relatively small additional quantity of these elements to
receiving waters. This is especially iuportant to remember for iron, which
••as been analyzed in many urban runoff studi°s. Iron can cause detrimental
effects in receiving waters, but these effects .»re mostly associated with its
dissolved form. A reduction of the pH subrtantially increases abundance of
dissolved iron.
Arsenic is mair.ly concentrated in iron and manganese oxides, shales,
clays, cediinentary r-cvc and phosphorites. Mercury is concentrated mostly in
confide ores, shales and clays. Lead is fairly uniformly distributed, but can
be concentrated in clayey sediments and sulfide deposits. Cadmium can also be
concentrated in shales, clays and phosphorites (Durum 1974).
JTKftT DUST AND DIRT POLLl'TAJ!! SOURCES
Most of tv
-------
r.iost notable ot these he.ivy n.-tals is lead. Solomon and Natusch (1977)
studied automobile exhaust Articulates in conjunction with a comprehensive
study ot lead in the Chr.mrai>;n-Urbana , Illinois, area. They found that the
exhaust participates existed in two distinct morphological forms. The
smallest participates were almost perfectly spherical, having diameters in
the range of 0.1 to U.5 microns. These small particles consisted almost
entirely of PbBrCl at the time of emission. Because they are snail, they are
expected to remain airborne for considerable distances and can be deposited
ir the lungs when inhaled. They concluded that the small particles are formed
by condensation ot HbBrCl vapor onto small nucleating centers which are
probably introduced into the engine with the filtered engine air.
Solomon and Natusch (1977) found that the second major form of
automobile exhaust particulates were rather large, being roughly 10 to 20
microns in diameter. These typically had irregular shapes, with somewhat
smooth surfaces. Thev found that the elemental compositions of these
irregular particles way quite variable, being predominantly iron, calcium,
lead, chlorine and bromine. They found that individual particles did contain
aluminum, zinc, sulfur, phosphorus and some carbon, chromium, potassium,
sodium, nickel and thallium. Many of the»e elements (bromine, carbon,
chlorine, chromium, potassium, sodium, nickel , phosphorus, lead, sulfur, and
thallium) are most likely condensed, or adsorbed, onto the surfaces of these
larger particles during passage through the exhaust system. Tbey believed
that these large particles originate in the engine or exhaust system because
of their very high iron content. They found that 50 to 70 percent of the
emitted lead is associa-ed with these large particles, which would be
deposited within a few meters of the emission point onto the roadway because
of their aerodynamic properties.
Solomon and Natusch (1977) also examined urban particulates near
roadways and homes in urban areas. They found that soil lead concentrations
were higher near the roads and houses. This indicated the capability of road
dust and peeling paint to contaminate nearby soils. The lead content of the
soils ranged from 130 to about 1,200 mg/kg. Koeppe (1977), as part of another
element of this Champaign-Urbana lead study, found that lead was tightly
bound to various soil components. However, the lead did not remain in one
location, but it was transported both downward into the soil profile and to
adjacent areas through both natural and man-assisted processes.
URBAN AGRICULTURAL SOURCES OF URBAN RUNOFF POLLUTANTS
Vegetative litter can be a significant pollutant component in almost all
source areas. The leaf fall on streecs in Bellevue is an important street
surface pollutant in the fall months. Animal feces can contribute important
quantities of nutrients and bacteria to the urban area, mostly affecting
vacant land and landscaped areas where they tend to accumulate. Fertilizer
and pesticide use is mostly associated with landscaped areas, but large
amounts of pesticides are sometimes used to control plant growths in
impervious areas. Fertilizer may be used in large quantities for road
maintenance operations. Koeppe (1977) found that significant levels of
plant-available le£d may be released during decomposition of plant tissue
460
-------
cor.tainim; le.ui. Therefore, it may ht difficult to permanently immobilize the
soil lead by returning polluted plant residues to the soil. These polluted
plants are mostly associated with vegetative areas close to the road that
IvA-e been shown to accumulate large amounts of lead in their foliage. The
cjcveraent of lead during plant decomposition may be the cause for the downward
movement of lead.
ATMOSPHERIC RESUSPENS ION, TRANSPORTATION AND REDEPOSITION OF URBAN RUNOFF
POLLUTAiNTS
Atmospheric processes affecting urban runoff pollutants include dry
dustfall and precipitation quality. These two elements have beer monitored in
many urban and rural areas. In many instances, however, the samples were
combined a? a bulk precipitation sample before processing. Automatic
precipitation sampling equipment currently available can automatically
distinguish between dry periods of fallout and precipitation. These devices
cover and uncover appropriate collection jars exposed to the atmosphere. As
part of the Nationwide Urban Runoft and Atmospheric Deposition Programs of
the EPA, much of this information is currently being collected. The USGS
report (Ebbert, Poole, and Payne, 1983) discusses the Bellevue atmospheric
deposition rates.
One must be very careful in interpreting this information, however,
because of the ability of r^any polluted dust and dirt particles to be
resuspended and tnen redeposited within the urban area. In many cases, the
measured atmospheric deposition measurements include material that was
previously residing and measured in other urban runoff pollutant source
areas. Therefore, mass balances and determinations of urban runoff deposition
and accumulation from different source areas can be highly misleading, unless
transfer of material between source areas and the effective yield of this
material to the receiving water is considered.
Dustfall and precipitation affect all of the major urban runoff source
areas in an urban area. Dustfall, however, is typically not a major pollutant
source but is mostly a mechanism for pollutant transport. Most of the
dustfall monitored in an urban area is resuspended particulate matter from
street surfaces or wind erosion products from vacant areas. Foint source
pollutant emissions can ao.so significantly contribute to dustfall pollution.
The bulk of the dustfall, however, Is contributed by the other major
pollutant sources. Barkdoll, et al (1977) stated that urban runoff
contaminants may be mo Jed by man's activities or the wind. Wind-transported
materials are commonly called "dustfall". Dustfall includes sedimentation,
coagulation with subsequent sedimentation and impaction. Dustfall is normally
measured by collecting dry samples, excluding rainfall and snowfall. If
rainout and washout are included, one has a measure of total atmospheric
fallout. This total atmospheric fallout is sometines called "bulk
precipitation". Rainout removes contaminants fron, the atmosphere by
condensation processes in clouds, while washout is the removal of
contaminants by the falling rain. Therefore, precipitation can include
natural contamination associated with condensation nuclei in addition to
collecting atmospheric pollutants as the rain or snow falls. In some areas,
461
-------
the contaminant contribution by dry deposition is small, compared to the
contribution by precipitation (haL^quist 1978). However, in heavily urbanized
are,;.-., du.-slfall can contribute more of an annual load than the wet
precipitation, especially when dustfall includes resusp^nded materials.
Kain water quality has been reported by several researchers. As
expected, tne non-urban area rain quality can be substantially better than
urban rain quality. Many of th<° important heavy metals, however, have not
been detected in rain in many areas of the country. The roost important heavy
metals in rain in urban areas are lead and zinc, both oeing present in nin
up to several hundred ug/1. The concentrations of lead and zinc in non-urban
areas is typically less than 50 ug/1. Iron is also present in relatively high
concentrations in rain (about 30 to 40 ug/1).
The concentrations of various important urban runoff pollutants in dry
dustfall has also been studied. Urban, rural and oceanic dry dustfall samples
contain more than 5,000 mg iron/kg total solids. Zinc and lead are the next
most predominant constituents of dustfall in urban areas. These can be
several thousand mg/kg dry dustfall. Spring, et al (1978) monitored dry
dustfall ne<:r a major freeway in Los Angeles, California. Based on a series
of samples collected over several months, they found that lead concentrations
on and near the freeway can be about J.OOO mg/kg, but as low as about 50C
mg/kg 5UO feet (150 meters) away. In contrast the chromium concentrations of
the dustfall did not vary substantially between the two locations and
approached oceanic dustfall chromium concentrations.
Much of the monitored atmospheric dustfall and precipitation would not
reach thvi urban runoff receiving waters. The percentage of dry atmospheric
deposition retained in a rural watershed was extensively monitored and
modelled in Oakridge, Tennessee (Barkdoll, et al, 1977). They found that
about 98 percent of the dry atmospheric deposition lead was retained in the
watershed, along with about 95 percent of the cadmium, 85 percent of the
copper, 60 percent of the chromium and magnesium and 75 percent of the zinc
and mercury. Therefore, if the dry deposition rates were added directly to
the yields from other urban runoff pollutant sources, the resultant urban
runoff loads would be very heavily over-estimated.
Chemical oxygen demand (COD) is the largest component in bulk
precipitation, followed by total dissolved solids (TDS) and suspended solids
(SS). Betson (1978), in a study in Knoxville, Kentucky, found that almost all
of the pollutants in the urban runoff streamflow outputs could easily be
accounted for by bulk precipitation deposition alone. Betson concluded that
bulk precipitation is an important component for some of the constituents in
urban runoff but the transport and resuspension of particulates from other
areas in the watershed are overriding factors.
RhSUSPENSION OF SOURCE AREA PARTICULATES
Rubin (1976) stated that resuspended ur^an particulates are returned to
the earth's surface and water bodies in four main ways: gravitational
settli-.g, impaction, precipitation and washout. Gravitational settling, as
462
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dry deposition, returns most of the particles. This not only involves the
settling or relatively large fly ash and soil particles, but also the
settling ot smaller particles that collide and coagulate. Rubin stated that
particles that are less than 0.1 micron in diameter move randomly in the air
and collide often with otl.er particles. These small particles car. then grow
rapidly by this coagulatio.i process. These small particles woul^. soon tx:
totally depleted in the air if they were not constantly replenished.
Particles in the U.I to 1.1) micron range are also removed primarily by
coagulation. These larger particles grow more olowly t'uHii ttie smaller
particles because they move less rapidly in elie air, a'-3 somewhat less
numerous and, Therefore, collide less often with other particles. T=ir;icles
with diameters larger than one micron have appreciable settling velocities.
Those particles about ten microns in diameter can settle rapidly, although
they ojn be kept airborne for extended periods of time and large distances by
atmospheric turbulence. The seccnd important particulate removal process from
the atmosphere is impaction. Impaction of particles near the earth's surface
can occur on vegetation, rocks and building surfaces. The third form of
particulate removal from the atmosphere is precipitation, in the form of rain
and snow. This is the rainout process described earlier where the
particulates are removed in the cloud-forming process. The fourth important
removal process is washout of the p-~.rticulates below uhe clouds during the
precipitation event. Therefore, it is easy to see that r^entrained particles
(especially from street surfaces, other paved surfaces, rooftops and from
soil erosion) in urban oreas can be readily redeposiL°.d through these various
processes, either close to the points of origin or at so-ne distance downwind.
Pitt (1979) monitored roadside concentrations of particuJates. He found
that on a number basis, the downwind roadside particulate concentrations were
about 10 percent greater than upwind conditions. About 80 percent of the
concentration increases, by number, were associated with particles in the 0.5
to 1.0 micron size range. However, about 90 percent of the particle
concentration increases by weight were associated with particles greater than
ten microns. He found that the rate of particulate resuspension from street
surfaces increases when the streets are cleaned at long intervals and varie^
widely for different street and traffic conditions. The resuspension rate was
calculated based upon observed long-term accumulation conditions on street
surfaces from many different study area conditions and varied from about one
to ii Ibs/Ciirb-mile/day (0.3 to 3.4 g/curb-meter/day).
Murphy (1975) described a Chicago study where airborne particulate
material within the city was microscopically examined, along with street
surface particulates. The particulates (mostly limestone and quartz) from
both of these areas were found to be similar in nature indicating that the
airborne particulates were :nost likely resuspended street surface
particulates. PEUCo (1977) found that the reeutrained portion of the
traffic-related particulate emissions (by weight) is an order of magnitude
greater than the direct emissions accounted for by vehicle exhaust and tire
wear. They also found that particulate resuspensions from a street are
directly proportional to the traffic volume and that the suspended
particulate concentrations near the streets are associated with relatively
large particle sizes. The medium particle size found, by weight, was about 15
microns, with about 22 percent of the particulates occurring at sizes greater
453
-------
tl.an 'H mu-'ons. 1'hrse relatively large particle sizes resulted in
Mi'T-t .int 1 a 1 | .,ir t i en lat e t, ill. Hit near the road . They found t'aat about 15
1'eiv'eiit ot resuspended pa r t i cu 1.11 es t;e area. They found, through
multi-elemental analyses, that the settled outdoor dust collected at or near
the curb was contaminated by automobile activity and originated from the
streets. Soil sunples taken near buildings that were painted with lead base
paint were conta;ni na ted by lead from chipping paint.
464
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APPENDIX H
REACTIONS AND FATES OF IMPORTANT URBAN RUNOFF POLLUTANTS
Tlr'.s section of the report summarizes information from the literature on
chemical reactions, solubilities and fates of important urban runoff
pollutants. Rubin (1976) discussed the forms and reactions that may occur for
heavy metals. Metals in natural waters may be soluble, colloidal or
suspended. Soluble metals are defined as being less than one micron in size,
whiie suspended metals are greater than 100 microns in size. Colloidal metals
are intermediate in size. Using these definitions, settleable materials are
also included in the suspended size fraction. Rubin further stated that the
suspended and co loidal particles may consist of individual or mixed metals
in the form of their hydroxides, oxides, silicates, sulfides or as other
compounds. They may also consist of clay, silica or organic matter to which
metals are bound by adsorption or ion exchange or as a complex. The soluble
metals may be un-ionized organo-metallic chelates, organic ions, or complexes
of these chelates or ions. Because of various reactions within the water,
(physical, chemical or biological) there may be dynamic interactions among
the various particle sizes and chemical forms. When incoming metals react
with receiving .vater bodies, several types of potential interactions can take
place. The pH and Eh (oxidation redaction potential, redox potential or ORP)
are very important in controlling solubility and agglomeration and,
therefore, sedimentation of a metal. The pH of the water system also affects
the bonding of the metals to insoluble carriers which influences adsorption,
ion exchange and co-precipitation.
The oxidation reduction potential can also radically affect the ionic
form of the metal. Iron and manganese are the most responsive metals to Eh
exchanges with lower redox potentials favoring the divalent (+2) iron and
manganese valence states. These valence states are also much more soluble
than the more oxidized (+3) states. Redox potential and pH will both affect
the stability of certain transition metal chelates (Rubin 1976).
The presence of inorganic ions can form complexes with the metals that
can increase the solubility of the metals. As an example, as salinity is
increased, more manganese becomes dissolved rather than suspended. The
opposite can happen with other complexes, where metal carbonates and sulfides
typically have limited solubilities. Organic conplexing agents in natural
waters include humic and fulvic acids. These can form stable metal humics and
fulvics that are soluble in fiesh waters. Adsorption and ion exchange can
also bind metals to insoluble particulates, especially in flowing waters with
large quantities of clay and soil. Much of the material that the metals
interact with involve organic materials that originated from aquatic
organisms. Other aquatic organism effects on meual solubilities include
465
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changes in pK and Eh by various biochemical processes. These in turn affect
soluble metal concentrations and metal accumulations in sediments. Aquatic
organisms can also concentrate many metals in their tissues
(bioaccumulation).
Rubin (197b) also discussed the importance of oxidation reduction
reactions at the sediment-water interface. This interface can have a large Eh
gradient depending upon the mixing, diffusion and the extent of biological
activity, intense redox activity nan occur at the sediment-water interface
because of deposition and accumulation of organic matte.'.: diffusion of oxygen
down into the sediment interstitial waters can then create a large redox
gradient. Organic sedirents generally contain ]arge quantifies of reduced
uaterial, especially sulfides. Since most heavy metal sulfides tend to h?
rather insoluble, it IG clear that interactions in the heterogeneous sulfide
systems can be an important process where trace metals are retained or
released from the soluble phase (Rubin 1976).
Gambrell and Patrick (1977) stated that metals are present in soils and
sediments in many chemical forms that differ greatly in their
bioavailability. Gome metals are bound within the crystalline structure of
the sediments and soils and are e-jentially unavailable to biota. However,
metals dissolved in soil solutions, or in interstitial or surface waters, are
considered readily available to Mota. Also, metals weakly adsorbed to the
solid mineral or organic colloidal phase by ionic exchange mechanisms are
also readily available. Between the unavailable and readily available metals
forms are a ~\. jter of forms that are potentially available. As discussed
previously, .ae potential solubility, and therefore availability, of various
metal form.: are strongly dependent upon the pH and oxidation reduction
conditions and, of course, the specific chemical compound. In reduced
sediment conditions, the formation of stable and insoluble metal sulfide
precipitates is important in limiting the mobility and bioavailability of
most metals. Humic materials in reduced environments are characterized by
large molecular weights and greater structural complexity. These
characteristics increase the metal retention capacity and the metal bonding
stability of insoluble humic materials. If these reduced sediments are
subjected to an oxidizing environment, such as being aerated by dredging,
scouring during high flows or by benthic organism activities, many of these
insoluble organics are more likely to become soluble. This is especially true
for copper, lead and cadmium complexes. As an example, Gambrell and Patrick
found that as the redox potential was increased from strongly reducing to
well oxidized levels, insoluble organic bound cadmium was transferred to more
available soluble and exchangable forms. They also stated that a reduction in
metal availability by the formation of insoluble organic complexes in reduced
sediments, may be offset uo some extent by an increase in soluble or organic
acids which maintain some metals in solution as soluble organic complexes.
These various Eh and pH mechanisms affect various metal complexes
differently. As an example, lead solubility is enhanced by low pH levels but
is little affected by changes in oxidation reduction conditions.
Cailahan, et al (1979), described the importance of various
environmental processes for the aquatic fates of some urban runoff heavy
metals and organic priority pollutants. Photolysis (the breakdown of
466
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compounds in the presence of sunlight) and volatilization (the transfer of
material from the water into the air as a gas or vapor) are not nearly as
important as the other mechanisms for heavy metals. Chemical speciation (the
formation of chemical compounds) is very important in determining the
solubilities of the specific metals. Sorption (adsorption is the attachment
of the material on to the outside of a solid and absorption is the attachment
of the material within a solid) is very important for many heavy metals.
Sorption can typically be the controlling mechanism affecting the mobility
and the precipitation of most heavy metals. Bioaccuiaulation (the uptake of
the material into organic tissue) can also occur for many heavy metals.
Biotransformatioa (the change of chemical form of the metal by organic
processes) is very important for some metals, especially mercury, arsenic and
lead. In many cases, the discharge of mercury, arsenic or lead compounds in
forms that are unavailable can be accumulated in aquatic sediments. They are
then exposed to various benthic organisms that can biotransform the material
through metabolization to methylated forms of the material which can be
highly toxic and soluble. Various organic priority pollutants are also found
in urban runoff, mainly various phenols, polyc.yclic aromatic hydrocarbons
(PAHs) and phthalate esters. Photolysis may be an important fate process for
phenols and PAHs but is probably not important for the phthalate esters.
Oxidation or hydrolysis may be important for some phenols. Volatilization may
be important for some phenols and PAHs. Sorption is an important fate process
for most of the materials, except for phenols. Bioaccumulation,
biotransforination and biodegradation are important processes for many of
these orranic iLaterials.
467
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-1 f
\
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