U.S. Department of the Interior

U.S. Geological Survey

Open-File Report 2011–1052

In cooperation with the Wisconsin Department of Natural Resources

Characterizing the Size Distribution of Particles in Urban 

Stormwater by Use of Fixed-Point Sample-Collection Methods

Characterizing the Size Distribution of 

Particles in Urban Stormwater by Use of 

Fixed-Point Sample-Collection Methods

By William R. Selbig and Roger T. Bannerman

In cooperation with the Wisconsin Department of Natural Resources

Open-File Report 2011–1052

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2011

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Suggested citation:

Selbig, W.R., and Bannerman, R.T., 2011, Characterizing the size distribution of particles in urban stormwater by use 

of fixed-point sample-collection methods: U.S. Geological Survey Open-File Report 2011–1052, 14 p..
iii

Contents

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

Description of Source Study Areas ............................................................................................................2

Methods...........................................................................................................................................................2

Runoff-Sample Collection....................................................................................................................2

Determination of Particle-Size Distribution......................................................................................2

Characterization of Particle-Size Distributions ........................................................................................3

Comparison of Particles by Percent..................................................................................................3

Comparison of Particles by Mass ....................................................................................................10

Limitations and Suggestions for Future Research .................................................................................10

Summary and Conclusions ........................................................................................................................10

References....................................................................................................................................................13

Figures

1. Distribution of particle size for individual samples and resulting median 

value, Madison, Wis., study area. A, Parking lot. B, Institutional roof. 

C, Collector street. D, Feeder street. E, Arterial street. F, Mixed-use area.........................5

2. Comparison of the distribution of particles measured from six source 

areas as part of the Madison, Wis., study to that reported by Driscoll (1986) ...................9

3. Median percent contribution of total mass for particles in sediment 

from stormwater runoff, Madison, Wis., study area. A, Greater than 

32 micrometers. B, Less than 32 micrometers.......................................................................11

Tables

1. Source areas and land use sampled for distribution of particles 

in urban stormwater.....................................................................................................................2

2. Summary statistics of particle size distributions represented as percent 

finer than the corresponding particle size ...............................................................................4

3. Comparison of median particle size in stormwater runoff from previous studies.............8

4. Comparison of similarity or difference in the percentage of sand 

in samples from six source areas in Madison, Wis. using Dunn’s procedure ...................9

5. Summary statistics of particle-size distributions, Madison, Wis., study area, 

represented as a concentration...............................................................................................12
iv

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

foot (ft) 0.3048 meter (m)

micrometer (μm) 0.00003937 inch (in)

Mass

gram (g) 0.03527 ounce, avoirdupois (oz)

Volume

liter (L) 0.2642 gallon (gal)

milliliter (mL) 0.03381 fluid ounce (fl. oz)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32

Concentrations of sediment are given in milligrams per liter (mg/L).

Conversion Factors
Abstract

The distribution of particles in runoff was characterized 

from six types of urban source areas (parking lot, feeder 

street, collector street, arterial street, rooftop, and mixed 

use) around Madison, Wis. The lowest median particle sizes 

were found at the mixed-use and parking-lot study areas 

(42 and 54 micrometers (μm), respectively), followed by 

the collector street (70 μm). Similar median particle sizes of 

approximately 95 μm were found for both the arterial street 

and institutional roof study areas. The largest median particle 

size, nearly 200 μm, was measured in feeder street samples. 

Variability in median particle size and distribution was considerable between source areas. Variability was also evident 

in comparisons with similar source area types from previous 

studies. Much of the variability can be attributed to use of 

different analytical techniques, sample-collection methods, 

and reporting between researchers. Results from this study 

further document the difficulty of deriving a single particlesize distribution that is representative of stormwater runoff 

generated from more than one source area. 

Introduction

Sediments in stormwater runoff from urban areas, and 

metals and hydrocarbons associated with these sediments, are 

a substantial source of contamination to receiving waters and 

associated toxic effects to aquatic organisms. Water-quality 

data from 10 Wisconsin storm sewers showed that 74 percent 

of the total metal load was associated with particulate matter, whereas 26 percent of the metal load was in the dissolved 

form (Bannerman and others, 1996). In addition, greater than 

86 percent of all polycyclic aromatic hydrocarbons detected 

in samples from a municipal maintenance garage and storage 

facility in Milwaukee were particulate associated, whereas 

less than 14 percent were in dissolved form (Corsi and others, 

1999). These data suggest that treatment options for urban 

stormwater should include specific plans to target sediment 

as the primary source of contamination to receiving streams. 

Watershed managers in urban areas need information to 

help choose the most effective means to reduce sedimentassociated contaminants in urban runoff. Numerous structural 

best management practices (BMPs) provide some level of 

sediment control and are readily available. However, because 

many of these devices rely on settling of solids, their effectiveness is largely dependent on the range of particle sizes in 

stormwater runoff. Variation of particle sizes can be attributed 

to a combination of site conditions such as vehicular activity, 

soil type, overhead tree canopy, wind patterns, and rainfallrunoff characteristics. In order to select the most appropriate 

BMP for sediment control, characterization of particles found 

in stormwater runoff becomes increasingly important. Data 

are currently lacking in this area. In Wisconsin, many control devices are selected and sized according to a generalized 

particle-size distribution from historical datasets collected 

as part of the Nationwide Urban Runoff Program (NURP) 

(U.S. Environmental Protection Agency, 1982). Few particlesize data are available for specific source areas and land uses. 

In 2005, the U.S. Geological Survey (USGS), in cooperation with the Wisconsin Department of Natural Resources 

(WDNR) and in collaboration with the Root River Municipal 

Stormwater Permit Group, began a study to help municipalities reduce the uncertainty in their stormwater-management 

planning by improving the characterization of particle-size 

distributions in urban stormwater runoff from specific sourcearea and land-use categories. This information can then be 

used to assist watershed managers and engineers in designing 

the most appropriate control devices for reduction of sediment in urban stormwater runoff. The primary objective of 

this report is to summarize particle-size distributions collected 

from six urban source areas in or near Madison, Wis., during 

the study and to compare these data to distributions from other 

published studies. 

Characterizing the Size Distribution of Particles in Urban 

Stormwater by Use of Fixed-Point Sample-Collection 

Methods

By William R. Selbig and Roger T. Bannerman
2 Characterizing the Size Distribution of Particles in Urban Stormwater by Use of Fixed-Point Sample-Collection Methods

Description of Source Study Areas

This study characterized distribution of particles in stormwater runoff from six types of urban source areas (table1). 

Selection was based on the prevalence of the specific types of 

source areas within urban watersheds. Data from source area 

types with multiple sampling sites were synthesized to represent their respective source area type. For example, data from 

three different commercial parking lots were compiled into 

a single dataset representing all parking lots. Street type was 

categorized by traffic volume as a feeder, collector, or arterial. 

A summary of the geographic setting and physical description 

for each study area can be found in Selbig and Bannerman 

(2009).

Methods

Runoff-Sample Collection

An automated monitoring station was used to measure 

flow and collect samples near the basin outlet of each source 

area or land use monitored in this study. Each monitoring 

station was equipped with automated stormwater-quality 

samplers and instruments to measure discharge. Measurement, 

control, and storage of data were done by way of electronic 

dataloggers. Precipitation data were collected by use of a 

tipping-bucket rain gage calibrated to 0.01 in. Discharge was 

measured by use of a probe with two different sensor systems 

mounted to the bottom of each pipe. Each probe contained a 

pressure transducer to measure water level and a pair of ultrasonic transducers to measure velocity. A fifth-order polynomial 

was used to relate water level to cross-sectional area for each 

pipe configuration. Instantaneous pipe discharge was then 

computed by multiplying the cross-sectional area of the pipe 

by the associated mean velocity. Storm-runoff volumes were 

computed by summing the 1-minute-interval instantaneous 

discharge during the sampled storm. 

Sample collection was activated by a rise in water level 

in the pipe during a precipitation event. Once the water-level 

threshold was exceeded, typically a depth of 0.15 ft from 

the pipe floor, the volume of water passing the station was 

measured and accumulated at 1-minute increments until a 

volumetric threshold was reached. At that point, the sampler 

collected a discrete water sample and the volumetric counter was reset. The process was repeated until the water level 

receded below the threshold. Samples representing less than 

80 percent of the storm-hydrograph were precluded from data 

analyses. The intake nozzle of the sampler orifice was fixed 

approximately 0.5 in. above the pipe floor. The location of the 

fixed-point sample intake was chosen to accommodate a range 

of flow conditions. Subsamples, 1 L in volume, were transferred through the sample tubing into a 10-L glass jar. These 

flow-weighted samples were collected and composited into 

a single water sample, then split and processed for analysis. 

Because each discrete sample was composited into a single 

event sample, the resulting concentrations and distributions 

represent the event mean.

A Teflon churn splitter was used to composite and split 

samples into smaller, 4-L plastic containers for particlesize distribution analysis. Processed samples were kept in a 

refrigerator at 4°C until delivered to the analytical laboratory, 

usually within 48 hours after runoff cessation. Because each 

discrete sample was composited into a single event sample, the 

resulting distributions represent the event mean distribution. 

Samples were analyzed at the Wisconsin State Laboratory of 

Hygiene (WSLH), in Madison.

Determination of Particle-Size Distribution

Upon receipt of the sample, WSLH would determine the 

total mass after correcting for the weight of the container. It 

was assumed that sample density approximated that of pure 

water so the units of mass could be directly related to units 

of volume; for example, 1 mL of water is equal to 1 g. Water 

density corrections are required when the suspended-sediment 

concentration exceeds 8,000 mg/L (ASTM International, 

2009). None of the samples evaluated as part of this study 

approached that magnitude of solids concentration. The 

sample was then wet sieved through a series of stacked nylonmesh sieves, which separated the solid-phase material from 

the sample into five separate particle-size fractions: ≥500, 

250 - <500, 125 - <250, 63 - <125, and 32 - <63 μm. Material retained on each sieve was transferred into a clean, tared, 

heat-tolerant container and dried overnight at 105 degrees C. 

Transfer of material from each sieve into the container was 

done by use of deionized water. The mass of dried material 

recovered from each sieve was measured and recorded. This 

process was repeated for each of the five size fractions. The 

total mass for each fraction was then divided by the volume of 

the original sample to achieve a mass concentration. Particles 

less than 32 μm were quantified by use of a Coulter counter 

(Beckman Coulter, 2010) into five separate particle-size fractions: 14 - <32, 8 - <14, 5 - <8, 2 - <5, and <2 μm. 

Table 1. Source areas and land use sampled for distribution of 

particles in urban stormwater.

Source area Land use Number of sites

Parking lot Commercial 3

Streets Residential, Commercial 3

Rooftop Institutional 1

Mixed Use Commercial (strip mall) 1
Characterization of Particle-Size Distributions 3

Characterization of Particle-Size 

Distributions

Comparison of Particles by Percent

The distribution of particles in urban stormwater is commonly reported in terms of the percentage of all particles in a 

water sample that are finer (by mass) than a specific particle 

size. Table 2 details summary statistics for each particle-size 

fraction measured in sampled precipitation events at the eight 

study locations. Data from each of the three parking lots were 

synthesized to represent a single parking-lot source area. 

Tests for normality by use of the Shapiro-Wilk test (Helsel 

and Hirsch, 1992) showed that most of the data used to create 

table 2 did not fit a normal or log-normal distribution, indicating skewness and variability. The degree of variability is most 

apparent in figures 1A–1F, which illustrate particle-size distributions from all samples within each source area that were 

analyzed as part of this study. Given the degree of variability 

and lack of normality in the data, the median distribution was 

chosen as the most appropriate representation of particles from 

each study area because the median is a better representation 

of the population center in highly skewed datasets than the 

mean (Ott and Longnecker, 2001). A commonly reported metric for the distribution of particles in stormwater is the median 

particle size (d50). Because all particles measured as part of 

this study were categorized into separate size fractions—for 

example, the 63- through 125-μm fraction—the median particle size was estimated by using figures 1A–1F. Mixed-use 

and parking-lot study areas had the lowest median values 

(42 and 54 μm, respectively), followed by the collector street 

(70 μm). Both the arterial street and institutional roof study 

areas had similar median particle sizes of approximately 

95 μm. Finally, the feeder street study area showed the 

largest median particle size of nearly 200 μm.

Median particle-size distributions from each source area 

were compared to data from other studies that characterized 

particle sizes in urban stormwater (table 3). The majority of 

these studies focused on particles entrained in runoff originating from streets, particularly highways. A wide range in 

median particle size was found both amongst and between 

urban source areas and land uses. The d50 for highways ranged 

from 570 to less than 3 μm. On the basis of the estimates 

from figures 1A–1F, median particle size from the parking lot, 

arterial street, and mixed-use study areas (54, 95, and 42 μm, 

respectively) compared favorably to values from the literature presented in table 3. Several studies, in addition to those 

listed in table 3, reported the distribution of particles in terms 

other than a median particle size. Results of these studies 

suggest substantial variability in data can inhibit the development of a single particle-size distribution that is representative 

of stormwater runoff generated from a single source area or 

land use. Numerous studies reported the majority of particles 

in stormwater trended toward the fine end of the distribution range, with approximately 80 percent less than 44 μm 

(Kobringer, 1984; Driscoll, 1986; Ball and Abustan, 1995). Yet, 

other studies suggest a coarser distribution, where the majority of particles were sand (>63 μm) (Sansalone and others, 

1998; Selbig and Bannerman, 2007; Kim and Sansalone, 2008, 

Horwatich and others, in press). Figure 2 illustrates median 

particle-size distributions derived from samples collected as 

part of this study. Although median particle sizes vary between 

source areas, they are larger than those reported from similar 

studies done in the mid-1980s.

By use of the Kruskal-Wallis test (Helsel and Hirsch, 

1992), all samples collected as part of this study were evaluated 

to determine whether the percentage of sand within each source 

area came from the same general population. If the test affirmed 

the null hypothesis that all distributions were from the same 

general population, then a single distribution could be assumed 

for all source areas. Results of the test rejected the null hypothesis, indicating at least one of the source areas had a significantly 

different percentage of sand (5-percent significance level) than 

the others. An additional test was done by means of Dunn’s 

procedure (Dunn, 1964) on multiple pairwise comparisons to 

identify where significant differences in median particle-size 

distribution between source areas occur and to distinguish those 

differences by sorting each source area into similar groups. 

Results of the test are summarized in table 4. Three distinct 

groups are presented in table 4 that identify, qualitatively, if a 

difference in the percent sand from sample populations within 

a source area is different than other source areas. Overlap 

between groups depicts no difference. For example, the collector street was not statistically different than any other source 

area (table 4). The parking lot was not statistically different than 

mixed use, collector street, or arterial street study areas but was 

statistically different than the institutional roof and feeder street 

(table 4). Results of the Kruskal-Wallis test and Dunn’s procedure suggest no single particle-size distribution can be applied 

to all source areas. 

Researchers often employ different analytical techniques, 

such as laser diffraction, optical sensors, settling rates, or wet/

dry sieving when determining the distribution of particles in 

stormwater (table 3). Much of the inconsistency can be attributed to the lack of analytical equipment capable of covering 

the wide range of particle sizes found in urban stormwater. 

Therefore, each method has the propensity to produce methodspecific results. Similarly, selection of the particle-size fraction 

or range of fractions (upper and lower) used by each researcher 

to characterize the distribution is inconsistent. Furthermore, 

sample-collection methods vary widely. As a result, much of the 

variability evident in table 3 may be attributed to differences in 

analytical method or sample-collection method, or both. 
4 Characterizing the Size Distribution of Particles in Urban Stormwater by Use of Fixed-Point Sample-Collection Methods

Table 2. Summary statistics of particle size distributions represented as percent finer than the corresponding particle size. All values, 

with the exception of the number of observations, are expressed as a percent. 

[No., number; <, less than]

Source Area Statistic

Particle size, in micrometers

500 250 125 63 32 14 8 5 2

PARKING LOTa

No. of observations 94 94 94 94 94 94 94 94 94

Minimum 43 12 4 2 1 1 1 <1 <1

Maximum 100 100 99 97 95 93 85 71 37

Median 95 80 69 54 38 26 22 18 10

Mean 87 74 63 51 38 30 25 21 11

Standard deviation 16 23 25 24 22 19 17 14 8

INSTITUTIONAL

 ROOF

No. of observations 41 41 41 41 41 41 41 41 41

Minimum 40 32 21 14 6 6 6 <1 1

Maximum 100 100 90 77 68 67 64 55 34

Median 100 79 59 36 23 22 19 16 11

Mean 90 76 58 36 24 22 20 18 12

Standard deviation 17 18 19 15 13 12 12 11 7

COLLEC

TOR

STREET

No. of observations 21 21 21 21 21 21 21 21 21

Minimum 79 47 14 7 4 4 4 1 <1

Maximum 100 100 96 94 86 82 67 63 59

Median 96 85 68 47 30 26 19 17 10

Mean 93 83 66 48 35 32 27 23 15

Standard deviation 7 13 23 26 25 23 21 18 15

FEEDER

STREET

No. of observations 21 21 21 21 21 21 21 21 21

Minimum 36 10 6 3 2 2 2 2 1

Maximum 99 97 93 80 66 60 48 42 33

Median 74 55 41 26 18 16 13 9 6

Mean 73 53 39 28 20 17 14 12 8

Standard deviation 15 23 23 20 16 14 11 10 8

ARTERIAL

STREET

No. of observations 48 48 48 48 48 48 48 48 48

Minimum 37 10 1 1 <1 <1 <1 <1 <1

Maximum 100 100 96 90 84 71 55 39 35

Median 99 85 60 35 21 17 13 10 5

Mean 95 79 56 39 28 21 17 13 8

Standard deviation 10 23 27 25 22 17 13 10 7

MIXED USE

No. of observations 20 20 20 20 20 20 20 20 20

Minimum 82 66 49 31 17 16 13 9 4

Maximum 100 97 94 83 76 71 59 45 33

Median 96 91 84 63 42 38 32 26 14

Mean 95 88 78 58 42 38 31 25 15

Standard deviation 4 8 13 17 18 17 14 11 7

a

 compilation of all three parking lot study sites
Characterization of Particle-Size Distributions 5

0

10

20

30

40

50

60

70

80

90

100

2 5 8 14 32 63 125 250 500

Percent finer than corresponding size

Particle size, in micrometers

Individual Sample

Median

EXPLANATION

Figure 1. Distribution of particle size for individual samples and resulting median value, Madison, Wis., 

study area. A, Parking lot. B, Institutional roof. C, Collector street. D, Feeder street. E, Arterial street. 

F, Mixed-use area.

A

B

2 5 8 14 32 63 125 250 500

0

10

20

30

40

50

60

70

80

90

100

Percent finer than corresponding size

Particle size, in micrometers

Individual Sample

Median

EXPLANATION
6 Characterizing the Size Distribution of Particles in Urban Stormwater by Use of Fixed-Point Sample-Collection Methods

0

10

20

30

40

50

60

70

80

90

100

2 5 8 14 32 63 125 250 500

Percent finer than corresponding size

Particle size, in micrometers

Individual Sample

Median

EXPLANATION

0

10

20

30

40

50

60

70

80

90

100

2 5 8 14 32 63 125 250 500

Percent finer than corresponding size

Particle size, in micrometers

Individual Sample

Median

EXPLANATION

C

D

Figure 1. Continued.
Characterization of Particle-Size Distributions 7

Figure 1. Continued.

E

F

0

10

20

30

40

50

60

70

80

90

100

2 5 8 14 32 63 125 250 500

Percent finer than corresponding size

Particle size, in micrometers

Individual Sample

Median

EXPLANATION

0

10

20

30

40

50

60

70

80

90

100

2 5 8 14 32 63 125 250 500

Percent finer than corresponding size

Particle size, in micrometers

Individual Sample

Median

EXPLANATION
8 Characterizing the Size Distribution of Particles in Urban Stormwater by Use of Fixed-Point Sample-Collection Methods

Table 3. Comparison of median particle size in stormwater runoff from previous studies. 

[A, autosampler; G, grab; ST, settling tank; B, bedload sampler]

Source area 

or land use

Number 

of samples

Sample 

method Analytical method d50(μm) Source

Highways 13 A Particle analyzer 570 Sansalone and others (1998)

Highways 8 G, ST Wet sieve (>75μm);

particle analyzer (<75μm)

136 Kim and Sansalone (2008)

Highways 172 G Particle analyzer 2.7 – 7.1 Li and others (2006)

Highways 9 A Wet sieve <50 Furumai and others (2002)

Highways 14 A Visual accumulation tube 340 Horwatich and others (2010)

Highways 8 A Particle analyzer 15.9 Andral and others (1999)

Highways 7 A Particle analyzer 4–6 Westerlund and Viklander (2006)

Arterial streets 12 G Particle analyzer <100 Drapper and others (2000)

Arterial streets 48 A Wet sieve (>32μm);

particle analyzer (<23μm)

95b Present study

Collector streets 21 A Wet sieve (>32μm);

particle analyzer (<23μm)

70b Present study

Feeder streets 21 A Wet sieve (>32μm);

particle analyzer (<23μm)

200b Present study

Parking lot 18 A Particle analyzer 46 Fowler and others (2009)

Parking lot 94 A Wet sieve (>32μm);

particle analyzer (<23μm)

54b Present study

Institutional roof 41 A Wet sieve (>32μm);

particle analyzer (<23μm)

95b Present study

Residential 46 A, B Particle analyzer 9 Burton and Pitt (2002)

Residential 68 A Wet sieve (>32μm);

particle analyzer (<32μm)

250b Selbig and Bannerman (2007)

Mixed use 20 A Wet sieve (>32μm);

particle analyzer (<32μm)

42b Present study

Mixed use 4 A Particle analyzer 31 Anta and others (2006)

b estimate
Characterization of Particle-Size Distributions 9

Table 4. Comparison of similarity or difference in the percentage of sand in samples from six source areas 

in Madison, Wis. using Dunn’s procedure.

Source Area Observations Sum of ranks Mean of ranks Groups

Mixed Use 20 1614 81 A

Parking Lots 94 9613 102 A B

Collector Streets 21 2366 113 A B C

Arterial Streets 48 6586 137 B C

Institutional Roof 41 6271 153 C

Feeder Streets 21 3685 175 C

Figure 2. Comparison of the distribution of particles measured from six source areas as part of the 

Madison, Wis., study to that reported by Driscoll (1986).

0

10

20

30

40

50

60

70

80

90

100

1 10 100 1,000

Percent finer than corresponding size

Particle size, in micrometers

Driscoll, 1986

Parking

Institutional Roof

Collector Street

Feeder Street

Arterial Street

Mixed Use

EXPLANATION
10 Characterizing the Size Distribution of Particles in Urban Stormwater by Use of Fixed-Point Sample-Collection Methods

Comparison of Particles by Mass

Figures 3A and 3B illustrate the median values of percent 

total mass contributed by each particle-size fraction from each 

study area. The values in figures 3A and 3B have been scaled 

to equal 100 percent. Particles less than 32 μm in figure 3A

were further subdivided into smaller particle-size fractions 

for greater resolution (fig. 3B). Feeder street samples had the 

greatest percentage of total mass from sand-size particles 

(>63 μm) compared to samples from other source areas, and 

nearly 30 percent came from particles greater than 500 μm. 

Less than 10 percent was attributed to that fraction for all 

other source areas. The majority of particle mass in four out of 

the six source areas was dominated by silt and clay particles 

that are less than 32 μm in size (fig.3A). This finding is similar 

to that of Li and others (2005) who found 30–60 percent of 

the particle mass in particles smaller than 50 μm. The remaining two source areas, institutional roof and feeder street, had 

a greater presence of sand-size particles, with the majority of 

mass in the 63–125 and > 500-μm particle fractions, respectively. For particles less than 32 μm, 30 to 50 percent of the 

mass was in particles less than 2 μm for all source areas 

(fig. 3B). 

Although normalizing the mass of each particle-size fraction as a percentage of the total mass allows for comparison 

of the distribution of particles amongst and between source 

areas, it says little about the magnitude of the mass within 

each particle-size fraction. Table 5 details summary statistics 

of concentration, in milligrams per liter, for all source areas 

monitored as part of this study. The feeder and arterial street 

study areas had the highest median values of total concentration, followed by the collector street, mixed use, parking lot, 

and finally, institutional roof. Despite having one of the coarsest distributions of particle size, institutional roof samples 

had the lowest median value of total concentration (table 5). 

This could be due, in part, to the presence of organic material. 

Organic particles generally have less mass than inorganic particles given equal size (Butler and others, 1996). The disparity 

between particle-size distribution and total concentration for 

institutional roof samples could also be an indication of the 

lack of source material. In a study of contaminant concentrations from source areas in Marquette, Mich., institutional roofs 

had the lowest concentrations of suspended solids (Steuer and 

others, 1997). Given the absence of fine particles, the presence 

of only a few large particles could result in not only a low total 

concentration but also a coarse distribution. Knowledge of 

the specific gravity of sediments in each sample would have 

provided additional information on the relative abundance of 

inorganic and organic fractions. 

Limitations and Suggestions for Future 

Research

This study summarized particle-size distributions in 

stormwater runoff from selected urban source areas and land 

uses. Collection of water-quality samples was done by use 

of automated water-quality samplers with a sample intake 

orifice fixed near the pipe floor. In an urban environment, the 

energy required to transport sediment in a pipe via increased 

flow can change rapidly such that sediment moving as bedload 

can quickly be carried as suspended load, and vice versa. The 

location of the sampler intake can be critical, depending on the 

degree of sediment stratification in the storm sewer pipe. Thus, 

resulting concentration data and particle-size distributions 

resulting from a fixed-point configuration could be biased 

towards larger particles that tend to accumulate near the bottom of a pipe or other conveyance. 

Recognition of stratification of solids in urban stormwater has led to recent improvements in sampling technology 

(Smith, 2002; Kayhanian and others, 2005; DeGroot and 

others, 2009; Selbig and Bannerman, 2011). These improvements are an attempt to collect a water-quality sample that 

is more representative of the entire water column rather than 

from a single, fixed point. Field data from one such technology, known as the Depth-Integrated Sampler Arm (DISA), 

show that particle-size distributions in water-quality samples 

collected from multiple points spaced vertically throughout the 

water column were generally finer than those collected near 

the bottom of a storm sewer (Selbig and Bannerman, 2011). 

If use of the DISA results in a more accurate representation of 

the average sediment distribution and concentration in a water 

column, then particle-size distributions presented as part of 

this study would likely require modification to mitigate the 

effect of sediment bias inherent with a fixed-point sampler.

Summary and Conclusions 

The U.S Geological Survey, in cooperation with the 

Wisconsin Department of Natural Resources (WDNR) and in 

collaboration with the Root River Municipal Stormwater Permit Group monitored eight urban source areas representing six 

types of source areas in or near Madison, Wis. in an effort to 

improve characterization of particle-size distributions in urban 

stormwater by use of fixed-point sample collection methods. 

The types of source areas were parking lot, feeder street, 

collector street, arterial street, rooftop, and mixed use. This 

information can then be used by environmental managers and 

engineers when selecting the most appropriate control devices 

for the removal of solids from urban stormwater. 

Mixed-use and parking-lot study areas had the lowest 

median particle sizes (42 and 54 μm, respectively), followed 

by the collector street study area (70 μm). Both arterial street 

and institutional roof study areas had similar median particle 
Summary and Conclusions 11

Figure 3. Median percent contribution of total mass for particles in sediment from stormwater runoff, Madison, Wis., 

study area. A, Greater than 32 micrometers. B, Less than 32 micrometers.

0%

20%

40%

60%

80%

100%

Parking Lot Institutional roof Collector Feeder Arterial Mixed use

Percent of total mass

Source area

≥500

<32

32 to<63

63 to <125

125 to <250

250 to <500

Particle-size fraction,

in micrometers

EXPLANATION

A

B

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Parking lot Institutional roof Collector Feeder Arterial Mixed use

Percent of total mass

Source area

<2

2 − <5

5 − <8

8 − <14

Particle-size fraction,

in micrometers

EXPLANATION

14 − <32
12 Characterizing the Size Distribution of Particles in Urban Stormwater by Use of Fixed-Point Sample-Collection Methods

Table 5. Summary statistics of particle-size distributions, Madison, Wis., study area, represented as a concentration. All values, with 

the exception of the number of observations, are in milligrams per liter.

[No., number; <, less than]

Source 

Area Statistic

Particle size, in micrometers

>500 250–500 125–250 63–125 32–63 14–32 8–14 5–8 2–5 <2 Total 

concentration

PARKING LOTa

No. of observations 94 94 94 94 94 94 94 94 94 94 94

Minimum <1 <1 <1 <1 <1 0 0 0 0 0.5 4.4

Maximum 2,030 2,150 581 89 256 32 68 78 78 41 4,952

Median <1 2.1 3.0 4.8 4.8 2.6 1.7 1.8 3.8 3.6 41

Mean 63 64 24 10 11 4.7 4.0 4.1 6.8 6.9 199

Standard deviation 276 287 79 16 28 5.8 8.0 9.1 11 8.4 640

INSTITUTIONAL

 ROOF

No. of observations 41 41 41 41 41 41 41 41 41 41 41

Minimum <1 <1 <1 <1 <1 0 0 0 0 0.5 3.0

Maximum 29 25 53 56 38 13 11 4.4 18 20 240

Median <1 1.2 1.6 2.0 1.1 0.1 0.1 0.1 0.6 0.5 10

Mean 2.2 2.5 3.8 4.7 2.6 0.6 0.5 0.3 1.3 1.7 20

Standard deviation 5.1 4.2 8.5 9.5 6.0 2.0 1.7 0.7 2.9 3.2 38

COLLEC

TOR

STREET

No. of observations 21 21 21 21 21 21 21 21 21 21 21

Minimum <1 <1 <1 <1 <1 0 0 0 0.3 0.5 9.6

Maximum 38 138 111 179 246 33 88 60 2 59 731

Median 6.2 7.3 20 16 7.7 1.3 1.5 1.6 2.2 8.0 83

Mean 9.1 17 29 30 24 5.3 9.9 7.5 8.8 11 151

Standard deviation 10 30 32 39 51 8.6 20 13 12 12 166

FEEDER

STREET

No. of observations 21 21 21 21 21 21 21 21 21 21 21

Minimum <1 1.3 2.3 4.1 3.9 0.2 0.7 0.4 0.8 2.2 40

Maximum 3,050 3,190 889 125 108 86 75 59 153 87 7,470

Median 41 22 32 26 14 1.8 3.7 2.4 5.9 10 165

Mean 391 362 116 37 26 11 14 9.0 17 21 1,004

Standard deviation 853 809 230 32 27 22 22 14 32 21 1,991

ARTERIAL

STREET

No. of observations 48 48 48 48 48 48 48 48 48 48 48

Minimum <1 <1 <1.5 <1 1.5 0 0 0 0 0.5 14

Maximum 1,240 2,074 5,073 150 75 47 100 125 158 63 5,110

Median <1 4.6 19 14 9.7 4.4 2.3 1.9 3.3 5.6 109

Mean 31 99 160 24 15 7.6 6.6 6.2 9.4 7.6 365

Standard deviation 177 326 722 27 15 9.4 15 18 23 9.7 831

MIXED USE

No. of observations 20 20 20 20 20 20 20 20 20 20 20

Minimum <1 <1 <1 1.6 1.4 0.2 0.2 0.2 0.4 1.3 8.0

Maximum 39 51 52 84 75 35 37 37 76 57 346

Median 2.5 2.5 6.4 11 7.6 2.2 2.8 2.6 4.6 7.5 48

Mean 6.2 7.4 11 19 16 5.5 9.0 7.5 12 12 105

Standard deviation 11 12 13 22 19 8.3 11 9.5 17 13 109

a

 compilation of all three parking lot study sites
References 13

sizes of approximately 95 μm. Finally, the feeder street study 

area showed the largest median particle size of nearly 200 μm. 

Median particle sizes measured as part of this study were 

somewhat comparable to those reported in previous studies 

from similar source areas. The majority of particle mass in 

four out of six source areas was silt and clay particles that are 

less than 32 μm in size. 

Distributions of particles ranging from <2 to >500 μm 

were highly variable both within and between source areas. 

Results of this study suggest substantial variability in data 

can inhibit the development of a single particle-size distribution that is representative of stormwater runoff generated 

from a single source area or land use. Continued development 

of improved sample collection methods, such as the depthintegrated sample arm, may reduce variability in particle-size 

distributions by mitigating the effect of sediment bias inherent 

with a fixed-point sampler.

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