Screening to Identify and Prevent Urban Storm Water Problems:
Estimating Impervious Area Accurately and Inexpensively
Sandra Bird, Jim Harrison, Linda Exum, Stephen Alberty and Christine Perkins
Biographical Sketches
\a&
Sandra Bird is an Environmental Engineer with the EPA Office of Research and Development in
Athens, GA. Her research interests include forecasting impacts of land use and land cover
changes on aquatic resources, and modeling the off-site drift from agricultural pesticide use.
Jim Harrison, the presenting author, has been an Environmental Scientist with EPA's Region 4 in
Atlanta, GA for 18 years. His responsibilities include developing biological and nutrient criteria,
monitoring, data management, and water quality indicators for geographic planning and
community-based projects.
Linda Exum is a Geographer with the EPA Office of Research and Development in Athens, GA
and has worked for EPA for 25 years. Her research interests include analysis of land use and
land cover change and interpretation of aerial photography.
Stephen Alberty is a Software Development Specialist with the Computer Sciences Corporation,
Athens, Georgia.
Christine Perkins is a Software Development Specialist with the Computer Sciences Corporation,
Athens, Georgia.
Abstract
Complete identification and eventual prevention of urban water quality problems pose
significant monitoring, "smart growth" and water quality management challenges. Uncontrolled
increase of impervious surface area (roads, buildings, and parking lots) causes detrimental
hydrologic changes, stream channel erosion, habitat degradation and severe impairment of
aquatic communities. Existing aerial photography (digital orthophoto quarter quadrangles -
DOQQ's), sampled statistically using desktop GIS tools, was used to evaluate impervious area
estimates based on readily available landscape data including: categorized land-cover data
(National Land Cover Data - NLCD); block-level census data; and road networks. Models
linking the photo interpretation and wide area estimation techniques provided: 1) cheap estimates
of impervious cover with known accuracy at the watershed and sub-watershed scales; 2) a
comprehensive state-wide ranking of Georgia waters likely impaired or threatened by urban
storm water; and 3) characterization of change in imperviousness over time. Multiple data
source estimation of imperviousness provides improved accuracy compared to the use of land-
use/land- cover alone, especially for the 5-10% impervious range where prevention of storm
water problems is critical. Estimated imperviousness change from 1993 to 1999 revealed 51
Georgia watersheds defined by 12-digit hydrological unit codes (HUCs) with substantial
impervious area increases (class changes) during this short, 6-year period. For 1999, 92 HUCs
were estimated to be more than 10% impervious with potentially detrimental aquatic impacts,
and 137 in the 5 to 10% range with detrimental aquatic impacts likely with future growth unless
preventive actions are taken. Similar analyses will be expanded to the 8 Southeastern states of
EPA Region 4. These screening results can guide in-situ monitoring to confirm problems, aid
listing of impaired waters under Section 303(d) of the Clean Water Act and total maximum daily
load (TMDL) development, provide reliable scientific information to energize sound local

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planning and land-use decisions, and promote protection and restoration of urban streams.
Background/Introduction
Urban and suburban development threatens surface water quality in many areas of the
United States (USEPA 2000). This threat is rapidly increasing as the U.S. population grows.
Along with increased development comes increased impervious surface-areas preventing
infiltration of water into the underlying soil. Roadways, parking lots and rooftops account for
the majority of impervious area. Hydrologic (Poff et al. 1997; Richteret al. 1996) and physical
stresses (Gaff 2001), as well as chemical contamination, must be addressed to protect and restore
urban water resources. Screening techniques are needed to assess imperviousness and related
urban stresses to allow comprehensive identification of water quality problem areas as part of
systematic water quality monitoring strategies (Harrison 1998).
The pace of urban growth in the Southeastern United States is unprecedented. A recent
National Geographic map (Mitchell and Leen 2001) illustrates this extremely rapid
urban/suburban expansion using Department of Defense "city lights" data from two time periods,
1993 and the "present." Huge areas of "sprawl" growth are particularly evident throughout the
Southeast and are most heavily concentrated in the area between Atlanta, GA and Raleigh, NC.
Based on National Resources Inventory data, land in developed uses increased by over 25% in
Georgia between 1992 and 1997 (USDA 2000).
Rapid growth is expected to continue. Preliminary forecasts expect urban land in the
study area to increase from 20 million acres in 1992 to roughly 52-55 million acres in 2020, and
to 72-81 million acres in 2040 (Southern Forest Resource Assessment 2001 draft). This urban
expansion will likely come at the expense of both agricultural and forest areas. Regions likely to
be most affected by future growth are the Piedmont, the Lower Atlantic and Gulf Coastal Plains
and the Southern Appalachians.
Fundamental social and economic forces govern conversion of land from uses of less
value to uses of greater value. Production of wealth drives much economic activity and growth.
In the Willamette River Basin (Oregon, USA), the dollar value of developed land relative to its
dollar value for dry land (non-irrigated) agriculture was 59 times for land prepared for homes,
253 times for land with single family homes, up to 552 times for land in commercial use, and 390
to 2535 times for industrial use (Hulse and Ribe 2001). This tremendous increase in land
valuation places intense economic pressure promoting development of land to urban use
whenever the demand exists.
Urban growth produces many stresses on water quality. Some of these stresses include:
lack of maintenance of sanitary sewer infrastructure, e.g. combined sewer overflows, sanitary
sewer overflows, sewer leaks and faulty septic systems; extensive hydrologic alteration of
watersheds, e.g., excessive runoff from impervious surfaces; riparian area destruction or
degradation; polluted runoff from impervious areas and managed landscapes; sedimentation from
construction activities; inadequate control of point sources; and illicit discharges (Harrison et al.
2001). In addition to extremely deleterious ecological and water quality impacts, flooding is also
an often devastating result of the urban hydrologic alteration (Inman 2000; Inman 1995), a stress
that is only sporadically regulated at the local level.
Increased imperviousness causes a well-known cascade of damaging results to streams
(Wolman 1967). Detrimental hydrologic changes cause more frequent, higher peak flows and
lower base flows. Altered flow regimes also increase stream bank erosion and channel
enlargement producing significant sedimentation from the stream channel itself. The resulting
unstable channel often evidences highly degraded aquatic habitat, largely due to unstable
substrates. Due to lowered base flows, streams do not have the resilience to recover from
drought conditions. The end result of these stresses is usually severe biological impairment and
poor aquatic community integrity. Other stresses often compound hydrologic impacts from
imperviousness. Summer stream temperatures may be elevated due to runoff from pavement and

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structures, placing additional stress on the biological communities. Riparian alterations regularly
exacerbate stream channel erosion and increase stream temperatures further. Additional habitat
degradation often ensues from reduced input of large woody debris (LWD), and from increased
stream crossings by roads, sewers and other structures that create barriers to fish movement.
Impervious surfaces channel pollutants directly into waterways, preventing processing of these
pollutants in soils. Higher pollutant loads, particularly oils, other petroleum products and metals
are typically associated with roadways, while biocides (pesticides and herbicides) are generally
associated with managed landscapes (Center for Watershed Protection 1998b).
Recent research has consistently shown strong relationships between the percentage of
impervious cover in a watershed and the health of the receiving stream. Booth and Jackson
(1994) suggest that 10% impervious watershed area "typically yields demonstrable loss of
aquatic system function," and that lower levels may be significant to sensitive waters. In a
review of research on impervious cover, Schueler (1994) concluded that, despite a range of
different criteria for stream health, use of widely varying methods and a range of geographic
conditions, stream degradation consistently occurred at relatively low levels of imperviousness
(10% or greater). May et al. (1997) found that indicators of stream health in the Pudget Sound
Lowlands declined most rapidly from 5 to 10 % impervious cover. A recent survey of Maryland
streams (Boward et al. 1999) found that brook trout (Salvelinus fontinalis), a species very
sensitive to water temperature, were not present in any streams where the watershed was greater
than 2% impervious cover.
Stream response to imperviousness likely varies due to local soils, geology, slope and
land management practices. Absent more specific local models, Schueler's (1994) three
imperviousness classes of impact provide a useful initial guide to stream quality in the
Southeastern US:
Sensitive streams have 0 tol0% imperviousness and typically have
good water quality, good habitat structure, and diverse biological
communities if riparian zones are intact and other stresses are
absent.
Impacted streams have 10 to 25% imperviousness and show clear
signs of degradation and only fair in-stream biological diversity.
Non-supporting streams have >25% impervious, a highly
unstable channel and poor biological condition supporting only
pollutant-tolerant fish and insects.
Although there are strong relationships between impervious cover and stream health, the
utility of imperviousness as an indicator of potential stream degradation remains a function of the
ease and accuracy for estimating it. A number of approaches have been used for measuring and
estimating impervious cover. While ground based surveys can be extremely accurate, these
surveys are typically prohibitively expensive. Readily available, high-resolution satellite
imagery facilitates rapidly expanding use of remote sensing techniques for impervious cover
estimation. The National Land Cover Data (NLCD circa 1993), developed for the Multi
Resolution Land Characteristics Consortium, provides nationally consistent land-use/land-cover
at 30-meter resolution. The NLCD identifies three urban area classes: high-intensity
commercial/industrial, high-density residential and low-density residential (Vogelmann et al.
2001). A number of relationships between population density and impervious cover have also
been developed (Stankowski (1972); Graham et al. (1974); Hicks and Woods (2000)). City
planners often use land-use zoning for rapid estimates of total impervious area. Both population
density and land-use zoning based estimation methods provide a means for projecting increase in
impervious cover in a watershed, using either population growth or build-out scenarios as the
forcing function (Arnold 1996). Population density is available nationally from the U.S. Census
Bureau, but comprehensive land-use zoning data are not available throughout the Southeast.
In this study, aerial photography (digital orthophoto quarter quadrangles - DOQQs),
5

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sampled statistically using desktop GIS tools, was used to evaluate impervious area estimates
based on available landscape data including categorized land cover data (National Land Cover
Data - NLCD), block level census data, and road networks. Wide area estimation techniques,
were used to identify Georgia watersheds or hydrologic unit codes (HUCs) that may currently be
impaired due to urbanization plus those that are likely to show degradation in the near future
based on the current status and rate of growth of impervious cover. [Note: Hydrologic units
.established by the USGS (8, 11 and 12/14 digit HUCs ) are widely available and are often used
as surrogates for watersheds. However, many HUCs are not true watersheds (Omernik and
Bailey 1997), and this must be recognized when using HUCs for water quality or landscape
analyses.] These screening results presented herein can guide in-situ monitoring to confirm
problems, aid listing of impaired waters under Section 303(d) of the Clean Water Act and total
maximum daily load (TMDL) development, provide sound information to energize local decision
makers and promote protection and restoration of urban streams.
Materials and Methods
Test Data Set Development
An impervious cover test data set for 56, 14-digit HUCs in Frederick County, MD was
developed using DOQQs from the U.S. Geological Survey (USGS) taken in 1989. DOQQs are
computer-generated versions of aerial photographs that have been ortho-rectified so they
represent true map distances and are available for any area of the country (USGS, 1996). The
DOQQs have aim2 resolution and their analysis provides a high level of accuracy in the
determination of impervious cover at a sub-watershed scale . A point-sampling method on a 200
m regular grid was used to evaluate the impervious area; a detailed description of the
methodology and quality assurance assessment is provided in Bird, et al. (2000). The DOQQ
sampling yielded an average of approximately 800 sample points per 14-digit HUC-with a total
of 43,816 points in the study area. Quality assurance objectives for these data were to obtain a
measure of the percent total impervious area (%TIA) within +/- 1 for watersheds with a %TLA of
less than 10% of the total watershed area and within 10% of the %TLA for watersheds with a %
TLA greater than 10%.
A second set of test data was developed for 13 12-digit HUCs around and just North of
Atlanta, GA for two separate time periods. Two sets of digital aerial photography existed for the
study area. The first, taken in 1993, was a black and white (gray-scale) set of DOQQs similar to
those used in the Frederick County evaluation. The second set of DOQQs, taken in 1999, was
color-infrared. The color-infrared photography covered the same geographic location and was
also created by the USGS. These data allowed us to evaluate the ability to do wide area
estimates of the change in impervious cover over relatively short time periods. A 200 m regular
grid was used for sampling and the analysis method was the same as used in the Frederick
County, MD study and described in Bird, et al. (2000). There were a total of 23,176 points
sampled averaging 1783 points per 12-digit HUC.
The greatest potential introduction of error identified in the quality assurance assessment
was from an individual analyst's interpretation of the images. In order to control this error,
sampling points overlaid on the DOQQs were characterized by two independent analysts as
either pervious or impervious. A third individual served as a quality assurance checker. The
quality assurance checker imported the results of the first two analysts into a program that
compared the two grids on a point-by-point basis. Points with discrepancies in categorization of
results by the first two analysts were reviewed by the quality assurance checker who made the
final determination of assignment of categories. The black and white aerial photography for the
Atlanta area were of poor quality relative to the color-infrared photography during the study time
period, and were expected to have a higher interpretation error rate.
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Impervious cover is not a single homogenous quantity. Generally, paved surfaces and
buildings fall unambiguously under the definition of impervious surfaces. However, ambiguity
can exist even for these categories since there is now isolated use of pervious paving materials,
allowing some infiltration. Other areas, such as dirt and gravel roads and parking lots, railroad
yards, and quarry areas that may not be coated with manmade impervious materials are in many
instances so heavily compacted as to be functionally impervious. Actual surface material in
these latter cases is often hard to determine from the aerial photography. These features were
categorized as impervious in the interpretation of the photography in our study.
Wide Area Estimation Techniques for Impervious Surfaces
Two different approaches were used to estimate impervious surfaces over a large area,
i.e., 1624 12-digit HUCs wholly contained within Georgia. First, three different data types-
population density from block-level census data, commercial/industrial and quarrying/mining
land-cover category from the National Land Cover Data, NLCD, (Vogelman, et al. 2001), and
interstates and major US highway coverage-were combined to estimate impervious cover.
Population density served as an indicator of impervious cover generated by residential
development. This residential contribution was estimated from a relationship developed by
Hicks and Woods (2000) between population density and %TIA. The two NLCD categories
provide information on contributions from major manufacturing, commercial and quarrying
areas, which can be more reliably detected by satellite imagery. These areas were assumed to be
90% impervious (the NLCD defines the commercial/manufacturing category as 80% or greater
impervious cover in a 30 m cell). The highway coverages provided information on impervious
cover contributed by major highways (interstate and other US highways) that aren't necessarily
related to local residential development. The highway contribution was calculated based on the
length of the roadways and number of lanes, assuming a 12 ft lane width.
Second, for purposes of comparison, simple class-based imperviousness assumptions
were applied to the National Land Cover Data (1993) for 1624 Georgia 12-digit HUCs using the
ATTILA landscape factor extension tool for ArcView (Ebert and Wade 2000). Imperviousness
cover assumptions were: High-Intensity Commercial/Industrial - 90%, High-Density Residential
- 60%, Low-Density Residential -40%, and Other Grasses (primarily parks and golf courses) -
10% (Center for Watershed Protection 1998b).
Evaluation of Estimation Methods
The accuracy of wide area estimates of impervious cover based on combining the Hicks
and Woods (2000) population-density method results with estimates of industrial and commercial
contributions from the NLCD and contributions from highways (Interstates and other major U.S.
highways) were compared to the data sampled from two different areas - Frederick County, MD
and selected watersheds in Georgia in a region North of Atlanta. Figure 1 compares the
estimated impervious cover to the measured values for Frederick County. The straight line
indicates a one-to-one match between the estimated and measured values. Overall, this technique
underestimated impervious cover by 0.8% TLA, with an average absolute error of 1.4% TLA.
This estimate was obtained without fitting to the test data set. For Frederick County as a whole,
the residential area calculated from population density contributed 65% of the imperviousness,
commercial/industrial land cover from the NLCD contributed 25%, the major highways
contributed 6%, and quarrying and mining contributed 4%. Fifty-six percent of the points
categorized as impervious from the aerial photography interpretation were in grid cells .
categorized as agricultural class in the NLCD, indicating limitations of using satellite land cover
alone to estimate imperviousness (Bird et al 2001). Many of these points fell in very low density
residential areas which fell below the threshold for categorization as developed by the NLCD
6

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criteria.
An additional set of test DOQQ measurements were made for thirteen watersheds in
midtown and north Atlanta and the Etowah River basin north of Atlanta. Impervious cover was
evaluated at two time periods, 1993 and 1999. Since the NLCD is based on 1993 data, the 1993
set of aerial photography was excellent for evaluating the estimation methods. The two time
windows were informative for change detection since two of the North Atlanta watersheds
doubled in impervious cover during this time period. Table 1 shows the results of estimated and
measured impervious cover in the 13 watersheds. Results for 1993 estimated and measured
values are shown in Figure 2. Both the NLCD only and the multiple data source (MDS)
approach provided reasonable estimates for urbanized watersheds. For low impervious area
watersheds, the MDS approach underestimated the impervious area somewhat, as seen in the
Frederick County results. The NLCD only method underestimates impervious area even more
significantly than the MDS method. The NLCD does not identify low-density residential
development areas where lots are typically greater than lA acre with impervious area under 30%
in a 30 m x 30 m grid cell. Since the MDS method relied on updated population data for the
1999 estimates, but only 1993 commercial/industrial area land cover contribution, there was a
greater underestimate for 1999 using MDS method. By contrast, the MDS approach appeared to
slightly overestimate the imperviousness in the very-developed mid-town Atlanta watersheds.
Table 1. Percent Total Impervious Area (%TLA) Results from North Georgia Watersheds
HUC number
DOQQ 1993
NLCD 1993
Multiple Data Sc(urces-1993
DOQQ
1999 Multiple Data Sources-1999
031300011204
52.1
44.9
54.9
49.1
58.1
031300011202
35.8
31.6
36.6
32.3
38.0
031300011201
33.8
31.8
41.0
34.1
44.8
031300011002
8.6
6.5
9.7
15.8
13.8
031300011001
6.1
3.4
6.2
9.5
7.9
031300010907
21.0
20.7
24.6
24.4
27.6
031300010906
10.5
11.3
14.9
22.4
23.9
031501040301
1.6
1.9
1.6
2.0
1.7
031501040302
3.4
1.9
1.7
5.1
1.9
031501040303
3.7
1.9
2.5
5.5
2.9
031501040304
3.6
2.0
3.6
7.9
4.4
031501040305
5.4
2.0
3.8
8.4
4.9
031501040306
2.0
1.8
1.7
3.9
1.7
Application to Georgia
Impervious cover was estimated for 1624 12-digit watersheds (HUCs) wholly contained
within the state of Georgia, using both the simple NLCD-only approach and the multiple data
source (MDS) approach. The use of NLDC data with the ATTILA landscape factor extension
tool provided a very rapid analysis and identified most of the potentially degraded watersheds
(Table 2). The NLCD-only method identified 69 watersheds as having over 10% TIA whereas
the MDS approach identified 80. The NLCD-only method under-estimated the number of
watersheds in the at-risk, 5 to 10 % TIA, range. For 1993, the MDS approach identified 117
HUCs in the 5 to 10% impervious class versus 76 for the NLCD only approach-35% fewer.
Thus, the NLCD-only approach appears to have limitations for identifying
imperviousness in the 5 to 10% range. This range, particularly in areas with significant growth,
likely incorporates the most critical areas where prevention of storm water problems might be
most effective. Figure 3, for 1993, identifies the specific Georgia HUCs categorized by MDS as
of concern (i.e. great than 5 %TLA) that were not identified by the NLCD-only. It is important to

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remember that the MDS approach may underestimate these HUCs somewhat as well.
Table 2. Evaluation of Impervious Cover Status of Georgia watersheds/HUC's.
NLCD Data Onlj (1993) (Number of
Impervious (Jover Class (% [TIA)
watersheds) Multiple Data Sources (1993) (Number of watersheds)	Multiple
Data Sources (1999) (Number of watersheds) Change (1993-1999) from lower to higher class
High Growth > 0.2 % TIA/yr (1^
umber of watersheds)
0-5
1479
1427
1395
-32
12
5 - 10
76
117
137
+32
19
10-25
58
62
67
+ 12
36
>25
11
18
25
+7
13
Between 1993 and 1999, we estimated that a total of 51 HUCs changed to a higher risk
impervious cover category. Figure 4 shows that the majority of these watersheds were in the
Atlanta area. The largest change was 32 HUCs moving from the 0 to 5% class to the 5 to 10%
class. Appreciable imperviousness changes were also evident in the higher impervious classes
with 12 HUCs moving from the 5 to 10% range to the 10 to 25% range and 7 HUCs from the 10
to 25% to the >25% ranges. For 1999, we estimated that there were a total of 229 HUCs of
concern, i.e. HUCs that are currently impaired or likely to be in the near future (14% of 1624):
92 (-6%) for likely existing impairment (imperviousness above 10%), and 137 (-8%) for
impairment in the near future (5 to 10% impervious range) if appropriate planning and
management is not undertaken. Since there is likely an underestimate of impervious area for
1999 using the MDS approach, even more watersheds than we estimated are likely changing
categories. The expected result is increasing storm water stress on the streams in these areas.
Conclusions and Recommendations
Monitoring and Priority Storm Water Management Areas
This study demonstrates the utility of using inexpensive landscape screening tools to
identify areas for priority monitoring for urban or urbanizing watersheds. The use of the NLCD
only with the ATTILA tool identifies most watersheds that are likely suffering impairment from
urbanization and allows a very rapid assessment. Unfortunately, this tool is not as useful in
identifying watersheds whose condition may be in a borderline category and vulnerable to
impairment in the near future. The statistical approach to air photo interpretation of
imperviousness supplies an essential, cost-effective, independent accuracy assessment for both
the MDS and the NLCD only approaches and allows their use for wide areas with known
accuracy. The promising pilot results of the multiple data source (MDS) approach in identifying
watersheds vulnerable to degradation from increasing impervious area for Georgia improve on
the NLCD only approach and encourage application of the MDS approach to all eight of the
Southeastern states of EPA Region 4. These analyses are now underway, to the extent that
comparable watershed/HUC mapping is available for the other states, through cooperative efforts
of EPA/ORD-Athens and EPA Region 4-Atlanta. Results of these analyses will be provided to
state water quality agencies to aid their water quality monitoring efforts.
Accurate, inexpensive impervious area estimates constitute an important landscape
screening tool for designing water quality monitoring programs. State monitoring programs have
limited resources, and thus cannot sample everywhere. Scientifically sound landscape screening
processes provide workable, defensible methods to: extrapolate condition estimates to waters
lacking in-stream data; identify suspected problem areas (likely impaired waters); identify
candidate reference areas (least impaired waters); target additional monitoring to confirm
problems; target prevention activities to specific threatened areas; prioritize TMDL development
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and restoration planning efforts; and, evaluate landscape stresses and causes of water quality
problems for large areas (Harrison et al 2000).
Some urban streams are listed as impaired through Section 303(d) of the Clean Water
Act and are subject to TMDL development. However, many are not yet listed, primarily due to a
lack of systematic monitoring approaches to identify urban water quality problems. Specific
recommendations for the results presented here are:
1)	HUCs with imperviousness exceeding 10% that are not already listed under
the 303(d) impaired waters listing process should be monitored to ascertain if they
are in fact impaired;
2)	Jurisdictions encompassing HUCs within the imperviousness range 5 to 10%
should undertake proactive storm water management actions to prevent water quality
degradation; and,
3)	Jurisdictions encompassing HUCs with imperviousness exceeding 10% and
confirmed impairment should quickly adopt effective storm water management
ordinances and provide necessary funding to address existing problems and institute
expanded prevention activities.
Further Research
Additional research will be needed to account for differences in sensitivity to hydrologic
storm water stress in different areas. A number of geographic frameworks should be tested to
evaluate the variation in response to hydrologic stress from impervious areas including:
ecoregions and subecoregions (McMahon and others 2001); hydrologic landscapes (Winter
2001); and average hydrologic response (Woodruff and Hewlett 1970). In addition, the USGS is
undertaking a series of "urban gradient" studies that will gather both landscape and in-stream
data for a variety of urban areas around the nation. These efforts could provide valuable
information to help understand variations in response to imperviousness and other urban stresses.
Since some impervious areas are not directly connected to streams and other waters, work is also
needed to incorporate cost-effective estimates of effective impervious area into storm water
planning (Sutherland 1995 and Alley and Veenhuis 1983).
Tools to estimate impervious area and in-stream response attack just one of many
stresses associated with urban expansion (Karr 1999). Practical screening tools are also needed
for nutrient and upland sediment loading (Jones and others 2001, and Wickham and others 2002),
bacterial contamination (Mallin and others 2000) and for pesticide/herbicide contamination.
Approaches for Storm Water Management
The known severity and growing extent of urban storm water problems strongly argues
for comprehensive local approaches to storm water management, including both prevention of
problems in growing areas and restoration/retrofit of existing problem areas (Center for
Watershed Protection 1998a & b). Current approaches to municipal/county storm water
permitting, including the new round of MS 4 permits that now include smaller urban areas, have
traditionally focused on chemical monitoring rather than the impacts of storm water volumes
coming from impervious surfaces. While there are a growing number of examples of local
governments who are tackling storm water management head on, such as Griffin, GA and
Charlotte, NC, effective, adequately funded local storm water programs are the exception rather
than the rule.
Some large cities are initiating storm water management, and known problems will be
very expensive to solve. Atlanta, with a metropolitan population of over 3 million, has begun
this process. The Metro Atlanta Urban Watershed Initiative and other local watershed studies
revealed that most area streams are already degraded (MAUWI 1998). The Clean Water
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Initiative of the Metro Atlanta Chamber of Commerce led to the creation of the North Metro
Atlanta Water Authority-a coalition of local governments focusing on integrated planning for
water supply, waste water treatment and storm water management. Storm water management
needs for the next 20 years are estimated at over $10 billion for the Atlanta metro area (Clean
Water Initiative 2000). Early products of the Authority, required by the enabling legislation,
include model storm water ordinances to be implemented and funded through individual local
governments. Effective development practices that protect water quality are perhaps the most
critical element for storm water management, and should be adopted by all local governments
(Nichols and others 1997 and 1999).
Storm water utilities are one increasingly attractive option to fund and to focus planning
and implementation to prevent and correct storm water problems. About 350 municipal
governments in the United States have begun fee-based storm water utilities, most within the past
10 years (Walker 2001). Other options to explore for balanced, equitable funding include
supplemental road use fees (which might be collected through gas tax mechanisms) since roads
comprise roughly 2/3 of the impervious area in many urban watersheds, and bonds for low
interest loans and grants. Additional continued private and government support for pilot storm
water efforts remains essential while long term funding for effective planning, implementation
and maintenance is structured.
Prevention and Restoration
Prevention is critical. Stream channels de-stablized by excessive urban storm water
runoff from impervious surfaces continue to erode for many decades (or longer) (Hammer 1972),
have little potential to recover naturally and can be restored only with great difficulty and
expense (Rosgen 1994). Combining storm water management options, e.g., reduction of
impervious surfaces through smart design, watershed retrofits using infiltration, extended
detention and on site practices, with geomorphic stream channel restoration can help many urban
streams regain some of their natural integrity. Successful restoration should follow the sequence
of 1) hydrology, 2) channel and habitat, 3) riparian zones and 4) aquatic biological communities
(National Research Council 1992, and Brosnan and others 1999). Total Maximum Daily Load
(TMDL) implementation should consider using this same sequence. Restoration should be
pursued to the maximum extent possible, but will be expensive.
A three to four fold increase of urban area in the Southeast over the next 40 years need
not result in the widespread destruction of our streams, a resource vital to every community's
quality of life. If we get serious now about the importance of imperviousness, we can avoid
totally unnecessary storm water degradation of streams, and put those waters already impacted
back on the road to recovery.
Disclaimer
This paper has been reviewed in accordance with the U.S. Environmental Protection
Agency's peer and administrative review policies and approved for presentation and publication.
Mention of trade names or commercial products does not constitute endorsement or
recommendation for use.
References
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Arnold, C.L. 1996. Helping communities make watershed-based land use decisions: three

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0
0	5	10	15	20	25
Measured Impervious Cover (%)
Figure 1. Impervious cover for 56 Frederick County, MD watersheds measured from aerial
photographs and estimated from multiple data sources (MDS), including U.S. Census population
density, manufacturing and industrial areas from derived satellite imagery and major highway
networks from U.S. Department of Transportation. The straight line would be the one-to-one
match of measured data and the estimated.
60
g 50
<1>
O 40
3
O
"I 30
CL
E
S 20
03
E
w 10
LLI lu
0
0 10 20 30 40 50 60
Measured Impervious Cover (%)
Figure 2. Impervious cover for 13 North Georgia HUCs measured from 1993 aerial photographs
and estimated from multiple data sources (MDS), including U.S. Census population density,
manufacturing and industrial areas from derived satellite imagery, and major highway networks
from U.S. Department of Transportation along with estimates based on National Land Cover
Data only (NLCD). The straight line would be a one-to-one match of measured and the
estimated.

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April 2002
20
Figure 3. Estimated 1993 Percent Impervious Area for 1624 Georgia 12-digit HUCs. Fifty-two
(52) HUCs identified as at-risk (5-10% impervious) or potentially degraded (>10% impervious)
using Multiple Data Sources (MDS), but not identified using the land cover data alone, are cross
hatched.
i L

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Figure 4. Estimated 1999 Percent Impervious Area in 1624 Georgia 12-digit HUCs. The 51
HUCs which changed to a higher risk impervious class between 1993 and 1999 are cross
hatched.
(C

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