U.S. Department of the Interior

U.S. Geological Survey

National Water-Quality Assessment Program

Relation of Urbanization to Stream Habitat and 

Geomorphic Characteristics in Nine Metropolitan

Areas of the United States

Scientific Investigations Report 2010–5056
Cover.  Photographs clockwise from top:

Lincoln Creek, Milwaukee, Wisconsin (photograph by Michelle Lutz, U.S. Geological Survey)

Pigeon House Branch, Raleigh, North Carolina (photograph by Elise Giddings, formerly U.S. Geological Survey)

Mill Creek, Salt Lake City, Utah (photograph by Elise Giddings, formerly U.S. Geological Survey)

Center image:

Map showing locations of nine metropolitan areas of the United States sampled as part of the U.S. Geological Survey 

National Water-Quality Assessment Program study on the effects of urbanization on stream ecosystems.
Relation of Urbanization to Stream Habitat and 

Geomorphic Characteristics in Nine Metropolitan 

Areas of the United States

By Faith A. Fitzpatrick and Marie C. Peppler

National Water-Quality Assessment Program

Scientific Investigations Report 2010–5056

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: 2010

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Suggested citation:

Fitzpatrick, F.A., and Peppler, M.C., 2010, Relation of urbanization to stream habitat and geomorphic characteristics in 

nine metropolitan areas of the United States: U.S. Geological Survey Scientific Investigations Report 2010–5056, 29 p.
iii

Foreword

The U.S. Geological Survey (USGS) is committed to providing the Nation with reliable scientific information that helps to 

enhance and protect the overall quality of life and that facilitates effective management of water, biological, energy, and mineral 

resources (http://www.usgs.gov/). Information on the Nation’s water resources is critical to ensuring long-term availability of 

water that is safe for drinking and recreation and is suitable for industry, irrigation, and fish and wildlife. Population growth and 

increasing demands for water make the availability of that water, measured in terms of quantity and quality, even more essential 

to the long-term sustainability of our communities and ecosystems.

The USGS implemented the National Water-Quality Assessment (NAWQA) Program in 1991 to support national, regional, State, 

and local information needs and decisions related to water-quality management and policy (http://water.usgs.gov/nawqa/). 

The NAWQA Program is designed to answer: What is the quality of our Nation’s streams and groundwater? How are conditions 

changing over time? How do natural features and human activities affect the quality of streams and groundwater, and where 

are those effects most pronounced? By combining information on water chemistry, physical characteristics, stream habitat, and 

aquatic life, the NAWQA Program aims to provide science-based insights for current and emerging water issues and priorities. 

From 1991 to 2001, the NAWQA Program completed interdisciplinary assessments and established a baseline understanding of 

water-quality conditions in 51 of the Nation’s river basins and aquifers, referred to as Study Units (http://water.usgs.gov/nawqa/

studies/study_units.html ).

National and regional assessments are ongoing in the second decade (2001–2012) of the NAWQA Program as 42 of the 51 Study 

Units are selectively reassessed. These assessments extend the findings in the Study Units by determining water-quality status 

and trends at sites that have been consistently monitored for more than a decade, and filling critical gaps in characterizing the 

quality of surface water and groundwater. For example, increased emphasis has been placed on assessing the quality of source 

water and finished water associated with many of the Nation’s largest community water systems. During the second decade, 

NAWQA is addressing five national priority topics that build an understanding of how natural features and human activities 

affect water quality, and establish links between sources of contaminants, the transport of those contaminants through the 

hydrologic system, and the potential effects of contaminants on humans and aquatic ecosystems. Included are studies on the 

fate of agricultural chemicals, effects of urbanization on stream ecosystems, bioaccumulation of mercury in stream ecosystems, 

effects of nutrient enrichment on aquatic ecosystems, and transport of contaminants to public-supply wells. In addition, national 

syntheses of information on pesticides, volatile organic compounds (VOCs), nutrients, trace elements, and aquatic ecology are 

continuing. 

The USGS aims to disseminate credible, timely, and relevant science information to address practical and effective waterresource management and strategies that protect and restore water quality. We hope this NAWQA publication will provide you 

with insights and information to meet your needs, and will foster increased citizen awareness and involvement in the protection 

and restoration of our Nation’s waters. 

The USGS recognizes that a national assessment by a single program cannot address all water-resource issues of interest. 

External coordination at all levels is critical for cost-effective management, regulation, and conservation of our Nation’s water 

resources. The NAWQA Program, therefore, depends on advice and information from other agencies—Federal, State, regional, 

interstate, Tribal, and local—as well as nongovernmental organizations, industry, academia, and other stakeholder groups. Your 

assistance and suggestions are greatly appreciated.

Matthew C. Larsen

Associate Director for Water

v

Contents

Foreword ........................................................................................................................................................iii

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

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

Methods...........................................................................................................................................................3

Study Design..........................................................................................................................................3

Urban Indicators and Landscape Characteristics ..........................................................................8

Hydrologic Metrics...............................................................................................................................8

Habitat and Geomorphic Characteristics .........................................................................................9

Data Analyses......................................................................................................................................11

Relations Among Watershed-Scale Urban, Landscape, and Hydrologic Characteristics..............11

Relations Among Reach-Scale Habitat/Geomorphic Characteristics and Watershed-Scale 

Urban, Landscape, and Hydrologic Characteristics ................................................................13

Regional Variations in Relations Among Reach-Scale Habitat/Geomorphic Characteristics 

and Watershed-Scale Total Impervious Surface......................................................................16

Reach-Scale Controls on Habitat and Geomorphic Responses to Urbanization..............................18

Nonlinear Relations of Depositional Bars, Channel Shape, and Streambed Substrate 

with Urbanization............................................................................................................................21

Implications...................................................................................................................................................22

Summary and Conclusions.........................................................................................................................24

Acknowledgments.......................................................................................................................................25

References Cited..........................................................................................................................................25

Figures 

1. Map showing locations of nine metropolitan areas of the United States sampled 

as part of the U.S. Geological Survey National Water-Quality Assessment 

Program study on the effects of urbanization on stream ecosystems ................................3

2. Graphs showing the comparison of urban indicators for nine metropolitan areas 

of the United States......................................................................................................................6

3. Boxplots of urban, landscape, and hydrologic characteristics for nine metropolitan 

areas of the United States...........................................................................................................7

4. Boxplots of selected reach-scale channel controls, channel geometry, streambed 

substrate, low-flow habitat conditions, habitat complexity, and riparian/bank 

characteristics for nine metropolitan areas of the United States......................................10

5–8. Graphs showing—

5. Bankfull channel area, normalized by drainage area, compared to watershed 

total impervious surface for nine metropolitan areas of the United States.............17

6. Percentage of streams with open canopy angle greater than 20 degrees for 

the percentage of watershed total impervious surface (NLCD_IS) groups 

for all nine and selected individual metropolitan areas of the United States .........18

7. Percentage of streams with selected reach-scale channel alterations 

grouped by percentage of watershed total impervious surface (NLCD_IS) 

for combined data from nine metropolitan areas of the United States ....................19
vi

8. Percentage of streams with selected characteristics of channel shape, bar 

formation, and streambed substrate characteristics, grouped by watershed 

total impervious surface (NLCD_IS) for combined data from all nine 

metropolitan areas of the United States........................................................................21

9. Diagram showing generalized hydrologic and habitat/geomorphic relations 

to urbanization.............................................................................................................................22

Tables 

1. Selected urban, landscape, and hydrologic characteristics used to determine 

the relation of urbanization to stream geomorphic and habitat characteristics 

for nine metropolitan areas of the United States ....................................................................4

2. Physiographic region, precipitation occurrence, time period for hydrologic 

data collection, and unusual conditions during habitat sampling for nine 

metropolitan areas of the United States...................................................................................9

3. Spearman rank correlations among selected watershed-scale urban, 

channel-alteration, and land-cover characteristics for combined data 

from nine metropolitan areas of the United States...............................................................12

4. Spearman rank correlations of selected watershed-scale urban and 

channel-alteration characteristics with landscape characteristics for 

combined data from nine metropolitan areas of the United States ...................................12

5. Spearman rank correlations of selected hydrologic characteristics with 

watershed-scale urban, channel-alteration, and landscape characteristics 

for combined data from nine metropolitan areas of the United States .............................13

6. Spearman rank correlations of reach-scale habitat/geomorphic characteristics 

with selected watershed-scale urban, channel-alteration, landscape, and 

hydrologic characteristics for combined data from nine metropolitan areas 

of the United States....................................................................................................................14

7. Results of stepwise linear regression analysis of selected reach-scale 

habitat/geomorphic characteristics with watershed-scale urban, 

channel-alteration, landscape, and hydrologic characteristics for combined 

data from nine metropolitan areas of the United States......................................................15

8. Spearman rank correlations among watershed-scale total impervious surface 

(NLCD_IS) and selected hydrologic and habitat/geomorphic characteristics 

for individual data from nine metropolitan areas in the United States..............................16

9. Spearman rank correlations among reach-scale slope and selected 

habitat/geomorphic characteristics for combined and individual data 

from eight metropolitan areas of the United States..............................................................20

10. Spearman correlations for selected urban indicators, landscape characteristics, 

hydrologic metrics, and habitat characteristics for all streams and streams 

without bedrock outcrops for combined data from nine metropolitan areas 

of the United States....................................................................................................................20
vii

Conversion Factors

SI to Inch/Pound

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

Area

square meter (m2) 0.0002471 acre 

square kilometer (km2) 247.1 acre

square meter (m2) 10.76 square foot (ft2) 

square kilometer (km2) 0.3861 square mile (mi2)

Volume

cubic meter (m3) 264.2 gallon (gal) 

cubic meter (m3) 0.0002642 million gallons (Mgal) 

cubic meter (m3) 35.31 cubic foot (ft3)

cubic meter (m3) 0.0008107 acre-foot (acre-ft) 

Flow rate

meter per second (m/s) 3.281 foot per second (ft/s) 

Hydraulic gradient

meter per kilometer (m/km) 5.27983 foot per mile (ft/mi) 

Inch/Pound to SI

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

meter (m) 3.281 foot (ft)

mile (mi) 1.609 kilometer (km)

Area

square mile (mi2) 2.590 square kilometer (km2)

Flow or precipitation rate

cubic foot per second (ft3/s) 0.02832 cubic meter per second (m3/s)

inch per hour (in/h) 2.54 centimeter per hour (m/h)

Temperature is given in degrees Celsius (°C), which can be converted to degrees Fahrenheit (°F) 

as follows:

°F = (1.8 x °C) + 32

Abstract

The relation of urbanization to stream habitat and 

geomorphic characteristics was examined collectively 

and individually for nine metropolitan areas of the United 

States—Portland, Oregon; Salt Lake City, Utah; Denver, 

Colorado; Dallas–Forth Worth, Texas; Milwaukee–Green Bay, 

Wisconsin; Birmingham, Alabama; Atlanta, Georgia; Raleigh, 

North Carolina; and Boston, Massachusetts. The study was 

part of a larger study conducted by the U.S. Geological Survey 

from 1999 to 2004 to examine the effects of urbanization on 

the physical, chemical, and biological components of stream 

ecosystems. The objectives of the current study were to 

determine how stream habitat and geomorphic characteristics 

relate to different aspects of urbanization across a variety of 

diverse environmental settings and spatial scales. A space-fortime rural-to-urban land-cover gradient approach was used. 

Reach-scale habitat data and geomorphic characteristic data 

were collected once during low flow and included indicators 

of potential habitat degradation such as measures of channel 

geometry and hydraulics, streambed substrate, low-flow 

reach volume (an estimate of base-flow conditions), habitat 

complexity, and riparian/bank conditions. Hydrologic metrics 

included in the analyses were those expected to be altered by 

increases in impervious surfaces, such as high-flow frequency 

and duration, flashiness, and low-flow duration. Other natural 

and human features, such as reach-scale channel engineering, 

geologic setting, and slope, were quantified to identify their 

possible confounding influences on habitat relations with 

watershed-scale urbanization indicators. Habitat and geomorphic characteristics were compared to several watershed-scale 

indicators of urbanization, natural landscape characteristics, 

and hydrologic metrics by use of correlation analyses and 

stepwise linear regression.

Habitat and geomorphic characteristics were related to 

percentages of impervious surfaces only in some metropolitan 

areas and environmental settings. The relations between 

watershed-scale indicators of urbanization and stream habitat 

depended on physiography and climate, hydrology, pre-urban 

channel alterations, reach-scale slope and presence of bedrock, 

and amount of bank stabilization and grade control. Channels 

increased in size with increasing percentages of impervious 

surfaces in southeastern and midwestern metropolitan areas 

regardless of whether the pre-existing land use was forest or 

agriculture. The amount of enlargement depended on annual 

precipitation and frequency of high-flow events. The lack 

of a relation between channel enlargement and increasing 

impervious surfaces in other metropolitan areas was thought 

to be confounded by pre-urbanization hydrologic and channel 

alterations. Direct relations of channel shape and streambed 

substrate to urbanization were variable or lacking, probably 

because the type, amount, and source of sediment are 

dependent on the phase of urbanization. Reach-scale slope 

also was important for determining variations in streambed 

substrate and habitat complexity (percentage of riffles and 

runs). Urbanization-associated changes in reach-scale riparian 

vegetation varied geographically, partially depending on 

pre-existing riparian vegetation characteristics. Bank erosion 

increased in Milwaukee–Green Bay and Boston urban streams, 

and bank erosion also increased with an increase in a streamflow flashiness index. However, potential relations likely were 

confounded by the frequent use of channel stabilization and 

bank protection in urban settings. Low-flow reach volume did 

not decrease with increasing urbanization, but instead was 

related to natural landscape characteristics and possibly other 

unmeasured factors. The presence of intermittent bedrock 

in some sampled reaches likely limited some geomorphic 

responses to urbanization, such as channel bed erosion. 

Results from this study emphasize the importance of including 

a wide range of landscape variables at multiple scales as well 

as detailed information about historical channel alterations, 

such as watershed drainage alterations for stormwater design 

or agriculture, and engineered or natural channel stabilizations 

upstream and downstream from the reach sampled for habitat.

Relation of Urbanization to Stream Habitat and 

Geomorphic Characteristics in Nine Metropolitan 

Areas of the United States 

By Faith A. Fitzpatrick and Marie C. Peppler
2 Relation of Urbanization to Stream Habitat and Geomorphic Characteristics in Nine Metropolitan Areas of the United States 

Introduction 

Stream physical responses to urbanization are dependent 

on temporal changes in hydrologic conditions and sediment 

fluxes associated with increases in impervious surfaces, 

construction practices, and stormwater management (Paul and 

Meyer, 2001; Brabec and others, 2002; Miltner and others, 

2004). Generally, major hydrologic changes associated with 

urbanization include decreases in the duration of floods and 

base flow and increases in total runoff volume, magnitude and 

frequency of floods, and flashiness (Leopold, 1968; Dunne and 

Leopold, 1978; Finkenbine and others, 2000; Konrad, 2003; 

McMahon and others, 2003). Changes in sediment fluxes 

typically are related to phases of urbanization, with increased 

sediment from overland sources during early construction 

and increased channel erosion after build-out (Wolman, 1967; 

Wolman and Schick, 1967; Guy, 1970; Owens and others, 

2000; Chin, 2006). Channel erosion in urban streams may 

contribute more than two-thirds of the total sediment load 

after sediment delivery from construction sites ceases 

(Trimble, 1997). Bedload transport capacity, a major factor 

affecting channel shape, also may increase (Whipple and 

DiLouie, 1981). These physical changes in water/sediment 

fluxes and geomorphic responses associated with urbanization 

have potentially negative effects on habitat conditions 

(Paul and Meyer, 2001; Brabec and others, 2002; Walsh and 

others, 2005). 

Habitat degradation can be assessed in terms of qualitative or quantitative indicators of channel size and shape, 

substrate size and stability, low-flow habitat conditions (such 

as reach volume and maximum depth), habitat complexity and 

cover, and bank/riparian conditions (Barbour and others, 1999; 

Kaufman and others, 1999; Somerville and Pruitt, 2004). 

Channel enlargement, which is an increase in channel size 

through widening or downcutting, and erosion are the most 

commonly measured responses to urbanization in a variety of 

environments worldwide (Guy, 1970; Hammer, 1972; Graf, 

1975; Whipple and DiLouie, 1981; Roberts, 1989; Gregory 

and others, 1992; Booth and Jackson, 1997; Trimble, 1997; 

Doll and others, 2002; Center for Watershed Protection, 2003; 

Fitzpatrick and others, 2005; Leopold and others, 2005; Chin, 

2006). Changes in channel size have been documented in 

watersheds with as little as 10 percent connected impervious 

surface (Booth and Jackson, 1997). In the Seattle, Washington 

area, urbanization-altered hydrology also caused increased 

bank erosion and larger streambed substrate sizes (Booth, 

1991; Finkenbine and others, 2000; Konrad and others, 2005). 

The spatial connectivity of urban land, the timing, phase, 

and location of urbanization, and riparian land use also may 

affect channel size, shape, and substrate conditions (Leopold 

and others, 2005; McBride and Booth, 2005; Chin, 2006; 

Colosimo and Wilcock, 2007). Some urban streams have 

more uniform, less complex habitat structure in the form of 

less riffles and loss of pools (Pizzuto and others, 2000). Local 

geologic setting may have some mitigating effects; urban 

streams with relatively steep slopes and rocky substrates are 

more likely to have good habitat quality and biotic integrity 

than streams with relatively flat slopes and fine-grained 

substrates (Wang and others, 1997; Fitzpatrick and others, 

2005). Geomorphic responses to urbanization are dependent 

on the erodibility of channel bottom and banks, mode of 

sediment transport, local geologic setting, history of channel 

modifications, geomorphic position within the drainage 

network, and geomorphic thresholds (Schumm, 1977; Bledsoe 

and Watson, 2001; Chin, 2006; Fitzpatrick and others, 2006; 

Fitzpatrick and Peppler, 2007). 

This study of the relation of urbanization to stream 

habitat and geomorphic characteristics was part of a larger 

study by the National Water-Quality Assessment (NAWQA) 

Program of the U.S. Geological Survey (USGS) of the effects 

of urbanization on stream ecosystems (Couch and Hamilton, 

2002). The primary objectives of the larger study were to 

(1) examine the physical, chemical, and biological responses 

to urbanization across a range of environmental settings, 

(2) determine the most important landscape features associated with the responses, and (3) describe the physical and 

chemical characteristics associated with biological responses 

(Giddings, and others, 2009). The study was conducted from 

1999 to 2004 in nine metropolitan areas in the United States—

Portland, Oregon; Salt Lake City, Utah; Denver, Colorado; 

Dallas–Forth Worth (hereafter referred to as Dallas), Texas; 

Milwaukee–Green Bay (hereafter referred to as Milwaukee), 

Wisconsin; Birmingham, Alabama; Atlanta, Georgia; Raleigh, 

North Carolina; and Boston, Massachusetts (fig. 1). As many 

as 30 streams in each metropolitan area were characterized for 

hydrology, habitat, water chemistry, fish, macroinvertebrates, 

and algae. The Boston, Birmingham, and Salt Lake City 

studies were conducted in 1999–2000; Atlanta, Denver, and 

Raleigh in 2002–2003; and Dallas, Milwaukee, and Portland 

in 2003–2004. Associations among urbanization, hydrology, 

and habitat were previously examined for Salt Lake City and 

Boston as part of a NAWQA urban-effects pilot study (Short 

and others, 2005). 

The purpose of this report is to describe the relations 

among urbanization and stream habitat and geomorphology 

across a variety of diverse environmental settings. As many as 

30 streams in 9 metropolitan areas in the United States were 

examined. Environmental variables included urban, landscape, 

and reach-scale natural and anthropogenic factors operating 

at several scales that have a high potential for affecting water 

and sediment fluxes and subsequently altering stream physical 

characteristics. Hydrologic metrics that represent flashiness, 

frequency and duration of high-flow events, and duration of 

low-flow events were included. Reach-scale habitat characteristics included commonly measured and representative 

indicators of channel geometry and hydraulics, streambed 

substrate, low-flow habitat conditions, habitat complexity, 

and bank/riparian conditions. Spearman correlation analysis 

and stepwise linear regression were used to determine the 

importance of the various watershed- and reach-scale features 

on habitat and geomorphic characteristics collectively and 

individually for the nine metropolitan areas.
Methods 3

Methods

This study involved collection of urban indicators, 

landscape characteristics, hydrologic metrics, and habitat 

and geomorphic characteristics for about 30 watersheds 

in 9 metropolitan areas. Details on the study design, field 

methods, and data analyses techniques are described in the 

following sections.

Study Design

As many as 30 streams were selected from mainly 

separate watersheds in each of the 9 metropolitan areas using 

a rural-to-urban land-cover gradient design (McMahon and 

Cuffney, 2000; Tate and others, 2005; Falcone and others, 

2007; Sprague and others, 2007). For site selection, a multimetric urban intensity index (UII) was developed with a geographic information system (GIS) from a study-area specific 

combination of mainly watershed-scale urban characteristics 

from census, land-cover, infrastructure, and socioeconomic 

data that highly correlated with population density (Tate and 

others, 2005; Falcone and others, 2007; Cuffney and Falcone, 

2009). A national common urban intensity index (MA_NUII) 

also was developed from standardized values of watershed 

urban land, housing density, and road density (table 1; fig. 2). 

Land cover for the selected streams in the low urban, or 

rural, part of the gradient varied among forest, agriculture, 

and grassland. Four metropolitan areas in the eastern United 

States—Birmingham, Atlanta, Raleigh, and Boston—had 

forested rural portions. The other five metropolitan areas had 

either rural portions of agriculture (Milwaukee), grassland 

(Denver), a mix of agriculture and grassland (Dallas and 

Salt Lake City), or a mix of forest, agriculture, and grassland 

(Portland). The small number of candidate streams in the Salt 

Lake City area required sampling some streams from the same 

watershed. 

Within each metropolitan area, investigators attempted to 

hold watershed- and reach-scale environmental setting, such 

as climate, geology, soils, and topography, relatively constant 

(Tate and others, 2005; Falcone and others, 2007). Collectively, the selected metropolitan areas represented a range 

of environmental settings and hydrologic conditions (table 1; 

fig. 3). Climatic conditions across the metropolitan areas 

ranged from warm and dry to cool and wet. Soils ranged from 

fine (Portland, Dallas, Milwaukee, and Atlanta) to moderately 

coarse (Boston) (U.S. Department of Agriculture, 1994; 

Shirazi, Boersman, and Johnson, 2001; Shirazi and others, 

2001a,b; Falcone and others, 2007). Watershed slopes were 

lowest in Dallas and Milwaukee and highest in Salt Lake City. 

Stream reaches with watersheds of less than 100 square 

kilometers (km2) were preferred for sampling (fig. 3). 

Delineation of drainage areas was problematic in Salt Lake 

City because a large portion of streamflow can be transferred 

among different watersheds using canals located upstream 

from sampling locations (Short and others, 2005). In addition, 

drainage delineation of highly urban watersheds was limited 

by lack of detail about storm sewer networks, which may span 

topographic highs. 

Selected stream reaches for habitat sampling generally 

were meandering and single thread, with perennial flow and 

riffle/pool morphology. Concrete-lined channels were avoided. 

Reaches with riffles were preferred for consistent invertebrate 

and algae sampling.

Figure 1. Locations of nine metropolitan areas of the United States sampled as part of 

the U.S. Geological Survey National Water-Quality Assessment Program study on the 

effects of urbanization on stream ecosystems. Figure 1. Locations of nine metropolitan areas of the United States sampled as part of the 

U.S. Geological Survey National Water-Quality Assessment Program study on the effects 

of urbanization on stream ecosystems. 

Portland

Salt Lake City

Denver

Birmingham

Atlanta

Raleigh

Boston

Milwaukee

Dallas

0 250 500 Miles

0 250 500 Kilometers
4 Relation of Urbanization to Stream Habitat and Geomorphic Characteristics in Nine Metropolitan Areas of the United States 

Table 1. Selected urban, landscape, and hydrologic characteristics used to determine the relation of urbanization to stream 

geomorphic and habitat characteristics for nine metropolitan areas of the United States.—Continued

[Min, Minimum; Max, Maximum; %, percent; m, meter; km2, square kilometer; km, kilometer; >, greater than; °C, degrees Celsius; cm, centimeter; h, hour; 

USDA, U.S. Department of Agriculture; <, less than; m2, square meter; POR, period of record; m/m, meter per meter; m3, cubic meter; m/s, meters per second; 

°, degrees] 

Variable name (unit) Abbreviation Median Min Max

Watershed-scale urban, channel-alteration, and land-cover characteristics

National urban intensity index (rank) MA_NUII 24 0 100

Watershed total urban land (%) NLCD_2 27 0 99

Watershed developed land (%) NLCD22_23_24 17 0 89

Watershed developed open space (%) NLCD_21 8 0 75

Urban patch nearest neighbor mean distance (m) EDM_C2 93 60 450

Watershed total impervious surface (%) NLCD_IS 9 0 55

Population density in 2000 (people/km2) POPDEN00 254 0 2,174

Population change 1990–2000 (%) POP90_00 0.20 –0.19 234

Housing units built prior to 1939 (proportion) PHU_G60 0.07 0.00 0.45

Road area density (km/km2) RDARDEN 3.7 0.0 15.0

Watershed urban land, distance weighted (%) URBANdw 32.2 0.0 99.4

Nearest upstream engineered channel (m) ENG_HYDd >23,000 1 >23,000

Dam density (dams/100 km2) DAMd 2.2 0.0 130.4

Watershed agriculture (%) NLCD_8 10 0 87

Watershed forest (%) NLCD_4 22 0 87

Watershed-scale landscape characteristics 

Drainage area (km2) DA 52 4 184

Mean annual air temperature (°C) MAAT 11 4 19

Mean annual precipitation (cm) MAP 119 38 205

Watershed mean low range permeability (cm/h) PERL 1 0 19

Watershed mean high range sand (%) SNDH 42 0 88

USDA soil texture classification – fine (%) TEXTURE5 29 0 100

Mean watershed elevation (m) MEANELEV 227 31 2,353

Watershed area with slope <1% (proportion) P_FLAT 0.06 0.0 0.77

Watershed slope (m/km) WAT_SLOPE 5.8 1.0 57.8

Basin shape index (unitless) BAS_SHAP_INDX 1.7 1.3 2.9

Drainage density (km/km2) DRAINDEN 0.8 0.0 1.7

Hydrologic metrics

Richards-Baker flashiness index (m2) RB_FLASH 0.084 0.004 0.589

Number of time periods when total rise is greater than or equal to 7 

times the median total rise (count) PERIODR7 20 0 175

Max duration of rising cross-sectional area over POR (h) MAX_DURRISE 10 2 32

Max duration of falling cross-sectional area over POR (h) MAX_DURFALL 14 1 69

Max duration of high cross-sectional area (90th percentile) pulses over 

POR (h) MXH_90 120 24 558

Median duration of high cross-sectional area (90th percentile) pulses 

over POR (h) MDH_90 8 1 286

Max duration of low cross-sectional area (10th percentile) pulses over 

POR (h) MXL_10 103 0 593

Reach-scale channel alterations and geologic setting

Percent of channelized reach length (%) ChannelizedPct 0 0 100

Percent of reach with bank stabilization (%) BankStabPct 0 0 100

Number of grade-control structures (count) GradeControl 1 0 4

Bedrock present in reach (presence or absence) Bedrock 0 0 1
Methods 5

Table 1. Selected urban, landscape, and hydrologic characteristics used to determine the relation of urbanization to stream 

geomorphic and habitat characteristics for nine metropolitan areas of the United States.—Continued

[Min, Minimum; Max, Maximum; %, percent; m, meter; km2, square kilometer; km, kilometer; >, greater than; °C, degrees Celsius; cm, centimeter; h, hour; 

USDA, U.S. Department of Agriculture; <, less than; m2, square meter; POR, period of record; m/m, meter per meter; m3, cubic meter; m/s, meters per second; 

°, degrees] 

Variable name (unit) Abbreviation Median Min Max

Reach-scale channel geometry and hydraulics

Reach slope (%) ReachSlope 0.39 0.01 16.61

Average bankfull channel area (m2) BFArea 12.8 1.2 197.1

Average bankfull channel area/drainage area (m2/km2) BFArea.DA 0.34 0.04 4.47

Average bankfull channel width/depth (ratio) BFWidthDepth 7.7 2.7 26.2

Flow stability index (m/m) FlowStblAvg 0.26 0.06 0.68

Reach-scale streambed substrate

Types of depositional bars present in reach (count) Bar 0 0 3

Dominant substrate size sand, silt and clay (%) DomSubFine 24 0 100

Dominant substrate size sand (%) DomSubSand3 9 0 100

Dominant substrate size cobble (%) DomSubCobble78 18 0 100

Substrate stability (ratio) DomSubStab 1 0.0002 56

Embeddedness (%) EmbedPctAvg 58 4 100

Reach-scale low-flow conditions

Average reach volume (m3) RchVol 265 6 2,535

Average reach volume/drainage area (m3/km2) RchVol.DA 7.1 0.6 41.0

Maximum depth (m) DepthMax 0.7 0.2 2.7

Average velocity (m/s) VelocAvg 0.157 0.000 0.691

Reach-scale habitat complexity

Riffle (%) GCUTypeRiffPct 26 0 78

Pool (%) GCUTypePoolPct 14 0 88

Run (%) GCUTypeRunPct 56 0 100

Reach-scale riparian/bank characteristics

Disturbed land cover within 30-meter buffer (% of transect endpoints) RipLUDis 41 0 100

Open canopy angle (°) OCanAngleAvg 25 0 148

Bank vegetative cover (%) BankVegCovAvg 47 4 100

Presence/absence of bank erosion (%) BankErosPct 50 0 100
6 Relation of Urbanization to Stream Habitat and Geomorphic Characteristics in Nine Metropolitan Areas of the United States 

Figure 2. Comparison of urban indicators for nine metropolitan areas of the United States.

Figure 2. Comparison of urban indicators for nine metropolitan areas of the United States.

0 10 20 30 40 50 0 10 20 30 40 50 0 10 20 30 40 50 60

Watershed total impervious surface (%) (NLCD_IS)

0

20

40

60

80

100

0

20

40

60

80

100

0

20

40

60

80

100

Metropolitan area urban intensity index (MA-NUII)

Atlanta

Birmingham

Boston

Dallas

Denver

Milwaukee

Portland

Raleigh

Salt Lake City

0 15 30 45 60

0

25

50

75

100

Watershed developed land

(%) (NLCD22_23_24)

0 15 30 45 60

0

25

50

75

100

Watershed total urban land (%) 

(NLCD_2)

0 15 30 45 60 0

600

1,200

1,800

2,400

Population density in 2000

(people/km2) (POPDEN00)

Watershed total impervious surface (%) (NLCD_IS)
Methods 7

Figure 3. Boxplots of urban, landscape, and hydrologic characteristics for nine metropolitan areas of the United States. 

(See table 1 for definitions of abbreviations. Boxplots are listed for metropolitan areas from west to east.)

MXH_90

(h)

1 2 3 4 5 6 7 8 9

MXL_10

(h)

1 2 3 4 5 6 7 8 9

PERIODR7

(count)

1 2 3 4 5 6 7 8 9

MAX_DURFALL

(h)

1 2 3 4 5 6 7 8 9

RB_FLASH

(m2)

1 2 3 4 5 6 7 8 9

WAT_SLOPE

(m/km)

1 2 3 4 5 6 7 8 9

TEXTURE5

(%)

1 2 3 4 5 6 7 8 9

MAP

(cm)

1 2 3 4 5 6 7 8 9

1 2 3 4 5 6 7 8 9

DA

(km2)

MAAT

(

o

C)

1 2 3 4 5 6 7 8 9

NLCD_21

(%)

1 2 3 4 5 6 7 8 9

0

20

60 80

40

0

200 20

16

12

8

4

0.6

0.4

0.2

0.0

100

0

60

30

0

400

600

200

0

400

600

200

0

200

150

100

80

40

0

60

40

20

0

50

150

100

50

0

40

NLCD_IS

(%)

1 2 3 4 5 6 7 8 9

Figure 3. Boxplots of urban, landscape, and hydrologic characteristics for nine metropolitan 

areas of the United States. [See table 1 for definitions of abbreviations. Boxplots are listed for 

metropolitan areas from west to east.]

EXPLANATION

1 Portland, OR

2 Salt Lake City, UT

3 Denver, CO

4 Dallas, TX

5 Milwaukee, WI

6 Birmingham, AL

7 Atlanta, GA

8 Raleigh, NC

9 Boston, MA Lower detached

75th percentile

25th percentile

median

Upper adjacent

Lower adjacent

Upper detached
8 Relation of Urbanization to Stream Habitat and Geomorphic Characteristics in Nine Metropolitan Areas of the United States 

Urban Indicators and Landscape 

Characteristics

Urban indicators and landscape characteristics mainly 

were derived from overlays of thematic maps using a GIS 

(Falcone and others, 2007; table 1). Watershed-based landcover and total impervious surface statistics were based on 

the 2001 National Land-Cover Data (NLCD; U.S. Geological 

Survey, 2005, 2006). The four NLCD Level 2 urban landcover categories were based on percentage of total impervious 

surface: less than 20 percent open space, 20 to less than 50 

percent low-intensity development, 50 to less than 80 percent 

medium-intensity development, and 80 percent or greater 

high-intensity development. Developed open space included 

mowed grassy areas associated with large-lot residential 

development, golf courses, lawns, airports, schools, parks, 

and roadsides and medians (James Falcone, U.S. Geological 

Survey, written commun., 2006). The separation of developed 

open space from the group of three developed categories is 

important in determining the intensity of urbanization and the 

potential effects on streams (fig. 2). One landscape pattern 

metric that describes the dispersion of urban patches within 

a watershed (EDM_C2) was included. This EDM_C2 metric 

was derived from FRAGSTATS software calculations of the 

land cover data and is a representation of the connectivity of 

impervious surfaces (Falcone and others, 2007). 

Census data included 2000 population density, change 

in population density from 1990 to 2000, and housing age 

(Falcone and others, 2007). One housing age measure, the 

proportion of houses built prior to 1939 (PHU_G60), was 

selected for this study to represent older urban areas. Road 

density was based on Census 2000 TIGER data. Distance to 

nearest upstream engineered channel (ENG_HYDd), such as 

canals, ditches, and pipelines, was derived from the NHDPlus 

Dataset (Horizon Systems Corporation, 2006; Kelly Ruhl, 

U.S. Geological Survey, written commun., 2007). Density of 

dams in the watershed (DAMd) was derived from the National 

Inventory of Dams (U.S. Army Corps of Engineers, 2006; 

Kelly Ruhl, U.S. Geological Survey, written commun., 2007).

Landscape characteristics included descriptions of 

watershed-scale soils, topography, slope, basin shape, and 

drainage density (table 1; Falcone and others, 2007). Soils data 

were derived from the U.S. Department of Agriculture State 

Soil Geographic (STATSGO) Data Base (U.S. Department 

of Agriculture, 1994; Shirazi, Boersman, and Johnson, 2001; 

Shirazi and others, 2001a,b). Elevation, relief, and watershed 

slopes were calculated from USGS 30-meter (m) National 

Elevation Data (U.S. Geological Survey, 2005). 

Hydrologic Metrics

Hydrologic metrics can provide a direct link between 

urban-caused changes in floods and low-flow characteristics 

and habitat conditions (McMahon and others, 2003; Booth 

and others, 2004). For six of the nine metropolitan areas, 

hydrologic metrics were calculated from hourly records of 

changes in flow cross-sectional area from stage recorders 

(McMahon and others, 2003; Giddings and others, 2009). 

For the other three metropolitan areas (Salt Lake City, 

Birmingham, and Boston), hydrologic metrics were calculated 

from records of hourly changes in stage (McMahon and 

others, 2003). Stage recorders were operated at Salt Lake City, 

Birmingham, Atlanta, and Raleigh for about a year (table 2). 

Stage recorders were operated at Milwaukee and Boston for 

less than a year, but the period included the nonwinter period 

of potential flooding from snowmelt or rainfall. Portland, 

Denver, and Dallas had periods of record that were less than 

a full year. The measured period for Birmingham coincided 

with extreme drought; consequently, several perennial streams 

were intermittent. Records of 10 years or more are recommended to identify site-specific trends over longer periods 

of time (U.S. Water Resources Council, 1981; Konrad and 

Booth, 2002). However, hydrologic metrics calculated from 

short-term hourly stage data were useful for comparisons of 

streamflow variability and flashiness caused by increased 

urbanization (McMahon and others, 2003). 

Based on annual or near annual periods of record for 

hourly stage or cross-sectional area data, 54 hydrologic 

condition metrics were calculated, including indicators of the 

variability in the frequency and duration of high and low flows 

(McMahon and others, 2003; Giddings and others, 2009). 

Frequency metrics included the number of rising or falling 

flows, where the stream rise or fall is equal to or greater than 

three, five, seven, or nine times the median flow rise or fall. 

Duration metrics included median and maximum durations of 

rising or falling high or low flows as well as total duration of 

high and low flows. A flashiness index similar to the RichardsBaker flashiness index was calculated on the basis of daily 

changes in flow cross-sectional area (Baker and others, 2004). 

A low flashiness index typically indicates small shifts in flow 

cross-sectional area, and a high value indicates large shifts in 

flow cross-sectional area.
Methods 9

Habitat and Geomorphic Characteristics 

Field-based reach-scale habitat assessments were conducted once during low flow on wadeable streams (Fitzpatrick 

and others, 1998). Data included qualitative and quantitative 

observations and measurements collected at 11 equidistant 

transects (table 1; fig. 4; Giddings and others, 2009). The 

measured reach was generally 20 times the channel width or a 

minimum of 150 m. A short description of how the habitat and 

geomorphic characteristics were measured and calculated in 

this study follows.

Measurements of channel geometry and hydraulics 

included surveyed low-flow water-surface slope (hereafter 

referred to as reach slope) and bankfull channel dimensions 

(table 1; fig. 4). Morphologic indicators were used to estimate 

bankfull stage and included variations in bank-face slope and 

riparian vegetation, undercut banks, and particle-size changes 

associated with point bars (Fitzpatrick and others, 1998). 

Sampling teams received national and in-house training to 

aid in consistent measurement techniques. Bankfull channel 

dimensions were calculated from riffle and run transects only 

(no pools). A flow-stability index was calculated from the 

ratio of the average depth and bankfull depth. Three point 

observations of dominant streambed substrate size from 

each of the 11 transects were summarized into percentage of 

points with fine (sand sized or smaller), sand, gravel, cobble 

and boulder, or bedrock substrate. A relative bed stability 

index was calculated on the basis of the ratio of the median 

particle size and the critical particle size potentially mobilized 

at bankfull flow (Kaufman and others, 1999). Percentage of 

embedded particles at each transect point was measured to 

the nearest 10 percent. Measurements of low-flow habitat 

conditions included wetted channel dimensions, maximum 

depth, discharge, and velocity. Habitat complexity included 

length-based measurements of riffle, runs, and pools in the 

reach. Habitat-cover data were not included in this analysis 

because many of the small streams had water depths of less 

than 30 centimeter (cm). Measures of bank/riparian conditions 

included percentage of disturbed riparian land cover within 

a 30-m buffer, open canopy angle, percentage of bank-face 

vegetative cover, and presence/absence of bank erosion at 

transect endpoints. Disturbed land cover included cropland, 

pasture, farmsteads, residential, commercial, or transportation. Undisturbed land cover included grassland, shrubs and 

woodland, or wetland. 

After the field surveys, additional information was 

needed about potential reach-scale channel alterations and 

natural controls that might affect habitat conditions and 

geomorphic responses. Using a combination of remarks on 

field forms, notes on field-drawn reach maps, photographs of 

Table 2. Physiographic region, precipitation occurrence, time period for hydrologic data collection, and unusual conditions during 

habitat sampling for nine metropolitan areas of the United States.

Metropolitan 

area

Physiographic provinces 

(Fenneman and Johnson, 

1946)

Precipitation occurrence 

(Falcone and others, 2007)

Noteworthy conditions 

during hydrologic data 

collection

Hydrologic data time 

period (mm/dd/yy)

Portland Pacific Mountain, Pacific 

Border, Cascade–Sierra 

Mountains

Snowmelt in spring, rainfall 

October–April

None 03/01/04–12/01/04

Salt Lake City Rocky Mountain System, 

Middle Rocky Mountains; 

Intermontane Plateaus, 

Basin and Range

Snowmelt in winter/spring is 

major runoff source, 

scattered light thunderstorms in summer

Flow affected by reservoirs, 

interbasin transfers, and 

diversions

04/26/00–03/29/01

Denver Interior Plains, Great Plains; 

Rocky Mountain System, 

Southern Rocky 

Mountains

Snowmelt in spring, rainfall 

April–September

Flow affected by reservoirs, 

interbasin transfers, and 

diversions

05/01/03–09/30/03

Dallas–Fort Worth Atlantic Plain, Coastal Plain Rainfall spring and summer None 10/15/03–02/15/04

Milwaukee–Green 

Bay

Interior Plains, Central 

Lowland

Snowmelt March–May, rainfall May–SeptemberNone 03/16/04–10/30/04

Birmingham Appalachian Highlands; 

Valley and Ridge, 

Plateaus, Piedmont

Rainfall—frontal systems in 

winter, thunderstorms in 

summer/fall

Severe drought 07/08/00–07/28/01

Atlanta Appalachian Highlands, 

Piedmont

Rainfall—frontal systems in 

winter, thunderstorms in 

summer/fall

None 10/01/02–09/30/03

Raleigh Appalachian Highlands, 

Piedmont

Rainfall distributed throughout the yearNone 11/16/02–11/15/03

Boston Appalachian Highlands, 

New England 

Snowmelt March–May, rainfall May–SeptemberDrought 05/02/00–06/22/00, 

09/11/00–12/07/00, 

03/09/01–06/16/01
10 Relation of Urbanization to Stream Habitat and Geomorphic Characteristics in Nine Metropolitan Areas of the United States 

Figure 4. Boxplots of selected reach-scale channel controls, channel geometry, streambed substrate, low-flow habitat 

conditions, habitat complexity, and riparian/bank characteristics for nine metropolitan areas of the United States. (See table 1 

for definitions of abbreviations. Boxplots are listed for metropolitan areas from west to east.)

BankErosPct

(%)

1 2 3 4 5 6 7 8 9

RipLUDis

(%)

1 2 3 4 5 6 7 8 9

GCUTypeRiffPct

(%)

1 2 3 4 5 6 7 8 9

VelocAvg

(m/s)

1 2 3 4 5 6 7 8 9

RchVol.DA

(m3/km2)

1 2 3 4 5 6 7 8 9

DomSubStab

(Log10) (ratio)

1 2 3 4 5 6 7 8 9

DomSubFine

(%)

1 2 3 4 5 6 7 8 9

FlowStblAvg

(m/m)

1 2 3 4 5 6 7 8 9

BFWidthDepth

(ratio)

1 2 3 4 5 6 7 8 9

BFArea.DA

(m2/km2)

1 2 3 4 5 6 7 8 9

ReachSlope

(%)

1 2 3 4 5 6 7 8 9

80

100

40

20

60

0

0.7

0.5

0.6

0.4

0.2

0

0.3

0.1

19

80

80

40

0

40

0

5

25

40

20

150

100

50

80

40

0

0

0

15

5

2

3

1

0

80

40

0

–1

–2

–3

4

1

0

15

2

1

0

BankStabPct

(%)

1 2 3 4 5 6 7 8 9

OCanAngleAvg

(degrees)

1 2 3 4 5 6 7 8 9

Lower detached

75th percentile

25th percentile

median

Upper adjacent

Lower adjacent

Upper detached

Figure 4. Boxplots of selected reach-scale channel controls, channel geometry, streambed substrate, 

low-flow habitat conditions, habitat complexity, and riparian/bank characteristics for nine

metropolitan areas of the United States. [See table 1 for definitions of abbreviations. Boxplots 

are listed for metropolitan areas from west to east.]

EXPLANATION

1 Portland, OR

2 Salt Lake City, UT

3 Denver, CO

4 Dallas, TX

5 Milwaukee, WI

6 Birmingham, AL

7 Atlanta, GA

8 Raleigh, NC

9 Boston, MA
Relations among Watershed-Scale Urban, Landscape, and Hydrologic Characteristics 11

the reach, and aerial photographs, the percentage of the reach 

with bank stabilization or channelization, number of gradecontrol structures (weirs, low-head dams, culverts) within the 

reach and within a distance of one reach length upstream or 

downstream, presence/absence of bedrock cropping out in the 

channel, and presence/absence of depositional bar features 

(lateral, mid, or point bars) were estimated (table 1). The 

degree of confidence in these techniques varied by metropolitan area depending 

on the level of details included on field forms and maps and 

the number of field photos. The calculated values represent 

a minimum for each type of reach-scale modification or 

natural control. 

Data Analyses

The number of sites used for the habitat and geomorphic 

analyses was reduced from 262 to 249 by eliminating 13 sites 

with drainage areas much greater than 200 km2 because a 

large range in watershed sizes can add to the complexity of 

geomorphic settings and possible responses (Ritter and others, 

2002). Omitted sites included nine from Salt Lake City, three 

from Denver, and one from Dallas. Some sites were dropped 

from hydrologic comparisons if more than 30 percent of the 

hydrologic record was missing. Several hydrologic metrics 

were dropped if the data ranges were affected by whether they 

were based on flow cross-sectional area or stage. Bankfull 

channel areas and low-flow reach volumes were normalized by 

drainage area to account for differences in channel size.

Distributions of urban indicators, landscape characteristics, hydrologic metrics, and habitat/geomorphic 

characteristics were examined for the combined dataset and 

for individual metropolitan areas using scatterplots, boxplots, 

and histograms produced with S-Plus (Insightful Corporation, 

2005) collectively for the entire dataset. Relations among 

urban indicators, landscape and hydrologic characteristics, 

and habitat and geomorphic characteristics were examined 

using Spearman rank correlation analysis (Iman and Conover, 

1983) for overall relations as well as for each metropolitan 

area. Univariate linear regressions were performed. Urban 

indicators, landscape characteristics, and hydrologic metrics 

were considered independent variables. Reach slope and 

riparian disturbed land cover also were considered independent variables. All other reach-scale habitat and geomorphic 

characteristics were considered dependent variables. Spearman 

correlation coefficients (rho) with P-values of less than 0.001 

were considered statistically significant for individual correlations. Bonferroni-adjusted coefficients for multiple tests also 

were taken into account. 

Initial analysis of boxplots, scatterplots, and Spearman 

correlations included approximately 250 urban indicators 

and landscape characteristics, approximately 50 hydrologic 

metrics, and approximately 120 habitat/geomorphic characteristics. The final subset of variables used for this study 

was reduced by a combination of eliminating intercorrelated 

characteristics after examination of boxplots, correlation 

tables, and scatterplots. Remaining variables were predictor or 

response factors commonly included in other studies of urban 

stream habitat conditions and determined to be of general 

interest for urban stream studies. 

Stepwise multiple linear regressions (Velleman, 1997) 

were performed on the collective dataset for the selected 

subset of habitat and geomorphic characteristics. Data were 

checked for normal distributions and transformed if necessary 

prior to regression.

The sites were subdivided into four categories of 

watershed-scale total impervious surface (NLCD_IS) representative of rural (less than 6 percent NLCD_IS), urbanizing 

(6 to less than 12 percent NLCD_IS), urban (12 to less than 

18 percent NLCD_IS), and highly urban (greater than or equal 

to 18 percent NLCD_IS) streams. The categorical breaks were 

selected on the basis of past experience, previous literature, 

and maintaining a relatively similar number of sites per 

grouping. Histograms of the categorical data were used to 

explore for potential nonlinear patterns in streambed substrate 

and riparian vegetation characteristics. 

Relations among Watershed-Scale 

Urban, Landscape, and Hydrologic 

Characteristics

Many urban indicators were highly correlated with each 

other in the combined dataset of all nine metropolitan areas 

(rho > 0.92) (table 3; fig. 2). Watershed total impervious surface (NLCD_IS) was used as a surrogate for the highly correlated urban indicators because of its common use in literature 

for research and management and its direct link to infiltration 

and runoff. Although highly correlated, the exact relation 

between the urban intensity index (MA_NUII) and NLCD_IS 

varied somewhat among the metropolitan areas depending 

on regional patterns in the density of urban development 

(Cuffney and Falcone, 2009). In most metropolitan areas, sites 

at the upper end of the urban gradient had 40 to 50 percent 

NLCD_IS except for Birmingham, Atlanta, and Boston, which 

had two or fewer sites above 30 percent NLCD_IS (fig. 2). 

In general, watersheds with about 10 percent NLCD_IS, a 

common percentage above which watersheds are considered 

to be influenced by urban development (Schueler, 1994), 

had about 25 percent watershed total urban land (NLCD_2). 

The relation between NLCD_2 and NLCD_IS improved if 

the proportion from the Level II category of developed open 

space (NLCD_21) was removed from the total urban land. 

Population density change (POP90_00), distance upstream to 

engineered channels (ENG-HYDd), or dam density (DAMd) 

did not relate to NLCD_IS (table 3).

Landscape characteristics were not related to NLCD_IS 

as part of the study design, but correlations among landscape 

characteristics, distance to engineered channels, dam density, 
12 Relation of Urbanization to Stream Habitat and Geomorphic Characteristics in Nine Metropolitan Areas of the United States 

and agricultural land cover for the combined data indicate 

the close association and influence of natural landscape 

characteristics on human activities (tables 3, 4). For example, 

watersheds with high precipitation, low elevation, clayey soils, 

and high percentages of agricultural land had engineered channels near the sampling reach. Previous studies have shown 

that drainage density increases with urbanization (Graf, 1977); 

however, drainage density did not increase with urbanization 

in this study, probably because the scale of the stream network 

data was too coarse to discern changes in the networks of 

ditches and pipes related to stormwater management. Watershed size, drainage density, and basin shape did not correlate 

with urban indicators or other landscape characteristics.

Hydrologic metrics were related to both urban indicators 

and landscape characteristics (table 5). An increase in the 

frequency of high-flow events (PERIODR7) is a common 

feature of urbanized streams regardless of their environmental 

setting. Developed open space had the highest correlation with 

PERIODR7 out of all the urban indicators; mowed grassy 

areas or soil compaction from heavy equipment could have 

unknown aspects of stormwater management (Pitt and others, 

2002). Comparatively, streams with a long MAX-DURFALL 

had a high percentage of clayey surficial deposits and gentle 

watershed slopes, and had relatively high mean annual 

air temperature. 

Table 3. Spearman rank correlations among selected watershed-scale urban, channel-alteration, and land-cover characteristics for 

combined data from nine metropolitan areas of the United States.

[Abbreviations for characteristics are defined in table 1. Statistically significant correlation coefficients with a P ≤ 0.001 and correlation coefficients with an 

absolute value greater than 0.34 are shown in bold] MA_NUII NLCD_2 NLCD_21

EDM_C2

NLCD_IS

POPDEN00

POP90_00

PHU_G60

RDARDEN

URBANdw

ENG_HYDd

DAMd

NLCD_8NLCD_4

MA_NUII 1.00

NLCD_2 0.97 1.00

NLCD_21 0.78 0.84 1.00

EDM_C2 –0.57 –0.57 –0.49 1.00

NLCD_IS 0.95 0.97 0.73 –0.57 1.00

POPDEN00 0.97 0.95 0.74 –0.56 0.94 1.00

POP90_00 –0.15 –0.15 –0.07 0.04 –0.15 –0.14 1.00

PHU_G60 –0.42 –0.44 –0.45 0.32 –0.40 –0.43 –0.37 1.00

RDARDEN 0.96 0.95 0.76 –0.55 0.94 0.95 –0.19 –0.38 1.00

URBANdw 0.93 0.96 0.77 –0.52 0.94 0.92 –0.15 –0.39 0.92 1.00

ENG_HYDd –0.21 –0.22 0.08 0.01 –0.30 –0.26 0.00 0.23 –0.25 –0.29 1.00

DAMd –0.13 –0.06 –0.01 0.08 –0.05 –0.09 –0.17 0.08 –0.07 –0.03 0.16 1.00

NLCD_8 –0.63 –0.58 –0.43 0.26 –0.55 –0.57 0.29 0.19 –0.58 –0.59 0.20 0.10 1.00

NLCD_4 –0.47 –0.56 –0.24 0.33 –0.61 –0.50 0.06 0.24 –0.49 –0.59 0.51 –0.08 0.07 1.00

Table 4. Spearman rank correlations of selected watershedscale urban and channel-alteration characteristics with 

landscape characteristics for combined data from nine 

metropolitan areas of the United States. 

[Abbreviations for characteristics are defined in table 1. Statistically significant correlation coefficients with a P ≤ 0.001 and correlation coefficients with 

an absolute value greater than 0.34 are shown in bold] NLCD_IS ENG_HYDd

DAMd

DA –0.12 0.06 –0.20

MAAT –0.06 0.24 –0.06

MAP –0.27 0.56 0.05

PERL 0.04 –0.19 –0.34

SNDH –0.01 –0.14 –0.49

MEANELEV 0.10 –0.49 0.11

TEXTURE5 –0.18 0.40 0.12

P_FLAT 0.05 0.07 –0.05

WAT_SLOPE –0.05 –0.13 0.07

BAS_SHAP_INDX 0.00 –0.06 –0.11

DRAINDEN –0.14 –0.09 –0.10
Relations Among Reach-Scale Habitat/Geomorphic Characteristics and Watershed-Scale Characteristics 13

Relations Among Reach-Scale Habitat/

Geomorphic Characteristics and 

Watershed-Scale Urban, Landscape, 

and Hydrologic Characteristics

There were no statistically significant correlations among 

habitat characteristics and NLCD_IS for the combined dataset 

of all nine metropolitan areas (table 6). However, streams near 

a large proportion of houses older than 60 years had relatively 

wide channels and coarse-grained substrates. The amount of 

older houses decreased with increasing urbanization in this 

study, indicating that watersheds with high amounts of urban 

land had relatively young residential areas (table 3). These 

combined relations among channel shape and streambed 

substrate for the spatial gradient are supportive of similar 

channel changes measured in temporal studies (Leopold 

and others, 2005; Colosimo and Wilcock, 2007). Reaches 

near engineered channels (ENG_HYDd) had relatively large 

bankfull channel areas. The amount of disturbed land cover 

within the 30-m reach buffer (RipLUDis) was not related to 

any watershed land cover or landscape characteristics.

Watershed-scale landscape characteristics influenced 

channel geometry, streambed substrate, and low-flow reach 

volume (table 6). Mean annual air temperature was a surrogate 

for north-to-south regional differences in environmental 

settings included in this study, in that southern metropolitan 

areas had more fine-grained soil texture, more gentle reach

slopes, larger and deeper channels, less flow stability, and 

finer, more embedded streambed substrates than the northern 

metropolitan areas. Streams with high mean annual precipitation had relatively large bankfull channel areas and low-flow 

reach volumes. Streams with gentle topography had relatively 

low reach slopes, high flow stability, and more run. The 

strength of correlation coefficients among soil texture (PERL, 

SNDH, and TEXTURE5), topographic relief (P_FLAT and 

WAT_SLOPE), and habitat characteristics varied, making it 

useful to examine more than one characteristic reflective of 

surficial deposits and topography. 

The interrelations among landscape characteristics were 

further reflected in the relations among habitat characteristics 

and hydrologic metrics (table 5). The hydrologic metric 

MAX_DURFALL, which correlated with the most landscape 

characteristics, also correlated with the most habitat characteristics. Reach slope had a higher correlation coefficient with 

MAX_DURFALL than did watershed slope, indicating the 

importance of local setting as well as watershed setting for 

hydrologic influences. Streams with high flashiness indexes 

and frequent high-flow events had high percentages of bank 

erosion and fine-grained streambed substrates. Streams with 

longer MXH_90 had wide channels and relatively small 

bankfull channel areas and reach volume (normalized by 

drainage area). 

Table 5. Spearman rank correlations of selected hydrologic characteristics with watershed-scale urban, channelalteration, and landscape characteristics for combined data from nine metropolitan areas of the United States.

[Abbreviations for characteristics are defined in table 1. Number of sites for the subsets ranged from 222 to 249. Statistically significant correlation coefficients with a P ≤ 0.001, with Bonferroni adjustments, are shown in bold]

RB_FLASH PERIODR7 MAX_DURRISE MAX_DURFALL MXH_90 MXL_10

MA_NUII 0.20 0.42 –0.13 0.05 –0.24 –0.06

NLCD_IS 0.20 0.38 –0.17 0.05 –0.24 –0.13

NLCD_21 0.32 0.63 –0.04 0.23 –0.26 –0.09

EDM_C2 –0.30 –0.31 –0.05 –0.16 0.15 –0.06

POP90_00 0.23 0.02 0.16 0.20 –0.14 0.07

PHU_G60 –0.27 –0.36 –0.09 –0.33 0.49 0.08

ENG_HYDd 0.08 0.08 0.11 0.14 0.16 0.21

DAMd 0.04 0.03 –0.11 0.09 0.03 –0.22

DA –0.13 –0.10 0.51 0.22 0.24 0.40

MAAT 0.03 0.29 0.18 0.41 –0.28 0.10

MAP –0.08 0.02 –0.02 –0.16 0.31 0.12

PERL –0.18 –0.05 0.01 –0.37 0.28 0.13

SNDH 0.02 0.02 0.17 –0.21 0.15 0.27

TEXTURE5 0.29 0.33 0.19 0.49 –0.28 0.15

P_FLAT 0.10 –0.14 0.21 0.19 0.08 0.12

WAT_SLOPE –0.17 0.02 –0.22 –0.38 0.20 –0.10

BAS_SHAP_INDX –0.33 –0.35 0.00 –0.26 0.25 0.03

DRAINDEN 0.20 –0.12 –0.17 –0.25 –0.03 –0.22
14 Relation of Urbanization to Stream Habitat and Geomorphic Characteristics in Nine Metropolitan Areas of the United States Table 6. Spearman rank correlations of reach-scale habitat/geomorphic characteristics with selected watershed-scale urban, channel-alteration, landscape, and hydrologic characteristics for combined data from nine metropolitan areas of the United States. [Abbreviations for characteristics are defined in table 1. Statistically significant correlation coefficients with a P ≤ 0.001, with Bonferroni adjustments, are shown in bold]

ReachSlope

BFArea

BFArea.DA

BFWidthDepth

FlowStblAvg

DomSubFine

DomSubCobble78

DomSubStab

EmbedPctAvg

RchVol

RchVol.DA

DepthMax

VelocAvg

GCUTypeRiffPct

GCUTypePoolPct

GCUTypeRunPct

BankVegCovAvg

BankErosPct

MA_NUII 0.07 –0.01 0.10 –0.09 –0.02 0.13 –0.08 –0.03 0.08 0.02 0.20 0.05 0.05 –0.04 0.08 –0.02 –0.10 0.03

NLCD_IS 0.07 –0.11 0.02 –0.07 0.01 0.11 –0.05 –0.01 0.10 –0.07 0.11 –0.01 –0.02 –0.07 0.07 0.01 –0.08 0.08

PHU_G60 0.07 –0.12 –0.24 0.42 0.24 –0.32 0.36 0.32 –0.33 0.06 –0.09 –0.03 –0.04 0.18 –0.09 –0.02 0.02 –0.09

ENG_HYDd –0.27 0.35 0.26 0.05 –0.05 –0.11 –0.09 0.09 –0.09 0.33 0.31 0.23 –0.20 –0.01 0.01 –0.05 –0.10 –0.03

DAMd –0.07 –0.14 0.02 0.08 –0.05 –0.14 0.01 0.08 –0.01 –0.18 0.01 –0.12 –0.36 0.05 0.16 –0.11 –0.03 0.13

DA –0.24 0.38 –0.42 0.12 0.21 –0.05 0.04 0.04 0.19 0.58 –0.28 0.40 0.30 –0.18 –0.29 0.27 –0.01 0.03

MAAT –0.40 0.75 0.66 –0.54 –0.57 0.35 –0.50 –0.31 0.44 0.26 0.28 0.32 –0.11 –0.17 0.07 –0.01 0.07 –0.17

MAP –0.07 0.46 0.33 0.15 –0.10 –0.11 –0.07 0.05 –0.15 0.42 0.42 0.21 –0.01 0.01 –0.02 –0.02 0.10 –0.20

TEXTURE5 –0.42 0.47 0.36 –0.39 –0.25 0.24 –0.49 –0.28 0.32 0.22 0.21 0.31 –0.13 –0.26 –0.04 0.16 –0.12 0.28

P_FLAT –0.43 –0.09 –0.28 0.12 0.37 0.07 –0.03 0.08 0.23 0.15 –0.10 0.13 –0.08 –0.32 –0.24 0.36 0.10 0.15

BAS_SHAP_INDX 0.01 –0.09 –0.27 0.20 0.20 –0.15 0.24 0.14 0.00 0.09 –0.18 0.08 0.09 0.02 –0.10 0.06 0.13 –0.07

DRAINDEN 0.11 –0.18 0.03 0.04 0.10 0.03 0.11 0.08 –0.19 –0.07 0.14 –0.12 0.12 –0.01 0.02 0.03 0.18 0.11

RB_FLASH –0.18 0.02 0.12 –0.27 –0.02 0.36 –0.31 –0.21 0.11 0.07 0.26 0.04 0.01 –0.24 –0.03 0.17 –0.2 0.47

PERIODR7 –0.08 0.19 0.25 –0.3 –0.19 0.33 –0.34 –0.28 0.16 0.11 0.36 0.05 –0.09 –0.14 0.06 0.05 –0.36 0.34

MAX_DURRISE –0.37 0.26 –0.17 –0.13 0.15 0.24 –0.15 –0.25 0.27 0.4 –0.01 0.3 0.08 –0.33 –0.17 0.28 –0.2 0.16

MAXDURFALL –0.52 0.33 0.14 –0.42 –0.15 0.48 –0.48 –0.39 0.47 0.21 0.09 0.25 –0.18 –0.39 –0.03 0.24 –0.26 0.36

MXH_90 0.27 –0.18 –0.41 0.46 0.32 –0.34 0.29 0.23 –0.27 0.09 –0.2 –0.01 0.02 0.11 –0.11 0.01 –0.06 –0.16

MXL_10 –0.11 0.23 –0.14 0 0.19 0.02 –0.02 –0.01 0.02 0.41 0.08 0.33 0.21 –0.12 –0.19 0.15 –0.13 0.06
Relations Among Reach-Scale Habitat/Geomorphic Characteristics and Watershed-Scale Characteristics 15

Results from stepwise linear regression analysis indicate 

that a wide range of watershed- and reach-scale natural and 

human factors influence reach-scale habitat and geomorphic 

characteristics (table 7). Landscape characteristics accounted 

for the most variability in bankfull channel area, flow stability, 

and percentage of cobble in streambed substrate. Precipitation 

Table 7. Results of stepwise linear regression analysis of selected reach-scale habitat/geomorphic characteristics with watershedscale urban, channel-alteration, landscape, and hydrologic characteristics for combined data from nine metropolitan areas of the 

United States. 

[Abbreviations for characteristics are defined in table 1]

Habitat 

characteristics Variables included in linear regression model R2 F-ratio

Standard 

error of the 

residuals

BFArea MAAT 0.54 286 0.28

(log transformed) MAAT, DA 0.63 209 0.25

MAAT, DA, (-)NLCD_21 0.63 138 0.24

MAAT, DA, (-)NLCD_21, MAP 0.65 110 0.24

MAAT, DA, (-)NLCD_21, (-) MAP, NLCD_IS 0.68 105 0.22

MAAT, DA, (-)NLCD_21, (-) MAP, NLCD_IS, EDM_C2 0.69 89 0.22

MAAT, DA, (-)NLCD_21, (-) MAP, NLCD_IS, MXH_90 0.70 85 0.21

FlowStblAvg (-)MAAT 0.31 112 0.10

(-)MAAT, MAX_DURRISE 0.45 91.7 0.09

(-)MAAT, MAX_DURRISE, MXL_10 0.48 69.1 0.09

(-)MAAT, MAX_DURRISE, MXL_10, P_FLAT 0.50 55.0 0.08

(-)MAAT, MAX_DURRISE, MXL_10, P_FLAT, MDH_90 0.51 46.9 0.08

(-)MAAT, MAX_DURRISE, MXL_10, P_FLAT, MDH_90, MAP 0.52 40.8 0.08

DomSubFine (-)ReachSlope 0.23 55.6 0.42

(log transformed) (-)ReachSlope, PERIODR7 0.34 43.7 0.37

(-)ReachSlope, PERIODR7, MAAT 0.38 35.4 0.36

(-)ReachSlope, PERIODR7, MAAT, POP90_00 0.39 24.2 0.36

(-)ReachSlope, PERIODR7, MAAT, POP90_00, (-)MAP 0.42 22.5 0.35

(-)ReachSlope, PERIODR7, MAAT, POP90_00, (-)MAP, (-)ENG_HYDd 0.44 20.4 0.34

DomSubCobble78 SNDH 0.16 37.2 0.41

(log transformed) SNDH, (-)PERIODR7 0.25 29.2 0.39

SNDH, (-)PERIODR7, ReachSlope 0.29 22.1 0.38

SNDH, (-)PERIODR7, ReachSlope, (-)NLCD_21 0.32 18.6 0.37

SNDH, (-)PERIODR7, ReachSlope, (-)NLCD_21, (-)POP90_00 0.36 15.8 0.36

RchVol DA 0.29 102 0.34

(log transformed) DA, MAP 0.42 90.5 0.31

DA, MAP, RB_FLASH 0.45 62.0 0.28

DA, MAP, RB_FLASH, PERL 0.47 49.3 0.27

DA, MAP, RB_FLASH, PERL, MAAT 0.48 41.8 0.27

GCUTypeRunPct (-)ReachSlope 0.17 45.2 23.4

(-)ReachSlope, (-)MAAT 0.21 29.6 22.8

(-)ReachSlope, (-)MAAT, DA 0.24 23.8 22.4

(-)ReachSlope, (-)MAAT, DA, NLCD_8 0.25 18.6 22.3

(-)ReachSlope, (-)MAAT, DA, NLCD_8, PERL 0.28 17.8 21.6

(-)ReachSlope, (-)MAAT, DA, NLCD_8, PERL, PERIODR7 0.30 15.3 21.6

BankErosPct RB_FLASH 0.20 54.7 33.2

RB_FLASH, (-)MAAT 0.23 34.8 32.4

RB_FLASH, (-)MAAT, MAX_DURFALL 0.32 36.2 30.5

RB_FLASH, (-)MAAT, MAX_DURFALL, RipLUDis 0.39 25.1 30.0

RB_FLASH, (-)MAAT, MAX_DURFALL, RipLUDis, POP90_00 0.44 21.4 28.9

RB_FLASH, (-)MAAT, MAX_DURFALL, RipLUDis, POP90_00, SNDH 0.46 19.5 28.3
16 Relation of Urbanization to Stream Habitat and Geomorphic Characteristics in Nine Metropolitan Areas of the United States 

accounted for the most variability in low-flow reach volume 

after accounting for drainage area. Reach slope accounted for 

the most variability for percentage of fine-grained streambed 

substrate and run percentage. The flashiness index accounted 

for the most variability in bank erosion, although the amount 

of variability explained was small. Urban indicators of 

developed open space, impervious surface, urban patch 

distance, and population density change accounted for a small 

amount of variability in bankfull channel area, streambed 

substrate size, and bank erosion.

Regional Variations in Relations Among 

Reach-Scale Habitat/Geomorphic 

Characteristics and Watershed-Scale 

Total Impervious Surface

Relations among reach-scale habitat and geomorphic 

characteristics and NLCD_IS were few and variable for 

individual metropolitan areas (table 8). Relations between 

hydrologic metrics and urbanization did not necessarily 

Table 8. Spearman rank correlations among watershed-scale total impervious surface (NLCD_IS) and selected hydrologic and habitat/

geomorphic characteristics for individual data from nine metropolitan areas in the United States.

[nd, no data. Number of sites for the study unit subsets ranged from 8 to 30. Abbreviations for characteristics are defined in table 1. Statistically significant correlation coefficients with a P ≤ 0.01 are shown in bold]

Portland Salt Lake 

City Denver Dallas–

Fort Worth

Milwaukee–

Green Bay Birmingham Atlanta Raleigh Boston

Hydrologic metrics

RB_FLASH 0.49 –0.07 0.37 0.43 0.35 0.34 0.59 0.38 0.12

PERIODR7 0.59 –0.41 0.29 0.81 0.86 0.70 0.93 0.82 0.39

MAX_DURRISE 0.23 0.11 0.00 –0.19 –0.56 –0.36 0.39 –0.54 0.15

MAX_DURFALL 0.67 0.74 0.40 –0.07 0.00 –0.11 0.22 –0.27 0.05

MXH_90 –0.06 0.36 0.16 –0.54 –0.37 –0.26 –0.61 –0.62 0.27

MDH_90 0.37 –0.36 0.02 0.46 -0.71 –0.62 –0.29 –0.69 0.36

MXL_10 0.37 0.24 –0.10 0.21 –0.36 0.19 –0.26 –0.19 –0.33

Channel geometry and hydraulics

ReachSlope –0.44 –0.53 nd 0.13 –0.16 0.06 –0.27 0.02 –0.20

BFArea –0.09 0.58 0.06 0.25 0.21 0.44 0.12 0.43 0.27

BFArea.DA 0.18 –0.33 0.26 0.06 0.58 0.51 0.09 0.77 –0.05

BFWidthDepth –0.30 0.17 –0.22 0.48 0.08 –0.05 –0.22 –0.52 –0.62

FlowStblAvg 0.04 0.25 –0.48 0.47 –0.02 –0.46 0.19 –0.60 0.34

Bottom substrate

DomSubFine 0.37 0.05 0.07 –0.13 –0.10 –0.16 0.08 0.49 0.48

DomSubCobble78 –0.05 0.35 –0.24 0.15 –0.32 –0.17 –0.08 –0.46 –0.38

DomSubStab –0.26 0.44 nd 0.32 –0.09 0.32 –0.24 –0.33 0.04

EmbedPctAvg 0.49 –0.22 0.09 nd –0.03 0.40 0.18 0.29 0.41

Low-flow habitat conditions

RchVol 0.03 0.70 –0.08 0.51 0.09 –0.03 0.08 –0.28 0.36

RchVol.DA 0.24 0.00 0.07 0.49 0.38 0.17 0.05 0.18 0.19

DepthMax 0.01 0.39 –0.15 0.49 0.22 –0.18 0.14 0.07 0.62

VelocAvg –0.47 0.00 –0.10 0.23 0.19 –0.06 –0.05 –0.27 0.33

Habitat complexity

GCUTypeRiffPct –0.61 –0.41 –0.16 –0.12 0.22 0.05 –0.15 0.02 –0.11

GCUTypePoolPct –0.33 –0.44 0.14 0.33 –0.16 –0.08 0.24 0.11 0.15

GCUTypeRunPct 0.58 0.56 0.11 –0.34 0.03 0.12 0.04 –0.23 0.04

Riparian/bank characteristics

RipLUDis 0.08 0.52 –0.23 –0.06 0.51 0.23 0.24 0.50 0.56

BankVegCovAvg 0.16 0.05 –0.18 0.17 –0.42 –0.18 –0.09 –0.04 –0.50

BankErosPct 0.14 0.18 0.01 0.06 0.19 0.05 0.01 –0.27 0.23
Regional Variations in Relations Among Reach-Scale Habitat/Geomorphic Characteristics and Watershed-Scale Total Impervious Surface 17

extend to habitat and geomorphic characteristics. Out of the 

nine metropolitan areas, Raleigh had the most and strongest 

correlation coefficients for channel geometry and streambed 

substrate with NLCD_IS. A few of the more notable relations 

are discussed in the following paragraphs.

Bankfull channel area (normalized by drainage 

area) increased with increasing NLCD_IS in Milwaukee, 

Birmingham, and Raleigh (fig. 5). Both previously forested 

and agricultural areas had urbanization related channel 

enlargement. Milwaukee, Birmingham, and Raleigh also 

had high correlation coefficients between PERIODR7 and 

NLCD_IS, potentially indicating that the increase in frequency 

of high-flow events may be the hydrologic process responsible 

for the enlarged channels. Raleigh’s channel sizes increased 

at the highest rate of response with increasing NLCD_IS, 

and Milwaukee’s channel sizes increased the least, likely 

due to differences in precipitation amounts and frequency of 

events (figs. 3, 5). Variability in channel sizes also increased 

with increasing impervious surface in these metropolitan 

areas. Atlanta streams showed no channel enlargement with 

increasing urbanization, even though Atlanta is in the same 

physiographic setting as Raleigh and had similar hydrologic 

responses to urbanization (table 8; fig. 5). The lack of association between channel size and urbanization in Atlanta perhaps 

is an artifact that Atlanta streams had larger watershed sizes 

relative to the other metropolitan areas (fig. 3) or that bankfull 

indicators were missing. Dallas-area rural streams had the 

largest channels, which were almost 10 times as large as rural 

channels near Milwaukee and Boston (fig. 5). 

Correlations among bankfull width/depth ratios 

and NLCD_IS were different than for bankfull area for 

Milwaukee, Birmingham, and Raleigh (table 8). Out of the 

three metropolitan areas with bankfull area associations, only 

Raleigh showed an increase in narrow and deep channels 

with increasing urbanization. In addition, Boston channels 

became more narrow and deep with increasing urbanization, 

yet did not increase in size. This finding suggests that a variety 

of geomorphic processes, such as widening, narrowing, or 

deepening, can happen in urban streams depending on water/

sediment fluxes (including bedload), geomorphic setting, 

grade control, and relative erosion resistance of streambed and 

bank materials. In a previous study of Seattle-area streams, 

urban channels were larger and generally were 1–1.5 m wider 

than their rural counterparts (Booth and Jackson, 1997); 

however, the same trends were not observed for regionally 

similar Portland streams, perhaps because of the wide precipitation range for the sampled Portland streams (fig. 3).

Relations between low-flow habitat characteristics and 

NLCD_IS were few, contrary to expected decreases in low 

flow with increasing urbanization (Paul and Meyer, 2001) 

Figure 5. Bankfull channel area, normalized by drainage area, compared to watershed total impervious surface 

for nine metropolitan areas of the United States. [rho, Spearman correlation coefficient]

0 10 20 30 40 50 0 10 20 30 40 50 0 10 20 30 40 50 60

Watershed total impervious surface (%) (NLCD_IS)

0

1

2

3

4

5

0

1

2

3

4

5

0

1

2

3

4

5

Bankfull channel area, normalized by drainage area (m2/km2) (BFArea.DA)

Figure 5. Bankfull channel area, normalized by drainage area, compared to watershed total impervious 

surface for nine metropolitan areas of the United States. [rho, Spearman correlation coefficient.] 

Atlanta

Birmingham

Boston

Dallas

Denver

Milwaukee

Portland

Raleigh

Salt Lake City

rho = 0.18 rho = -0.33 rho = 0.16

rho = 0.06 rho = 0.58 rho = 0.51

rho = 0.09 rho = 0.77 rho = -0.05
18 Relation of Urbanization to Stream Habitat and Geomorphic Characteristics in Nine Metropolitan Areas of the United States 

(table 8). The habitat measurement of reach volume (RchVol) 

and the hydrologic metric used as a surrogate for low flow 

(MXL_10) correlated with each other for the combined dataset 

(table 6), indicating some agreement between the hydrologic 

and habitat measurement techniques, yet neither showed any 

consistent relation with NLCD_IS in the individual metropolitan areas. Only in Salt Lake City and Dallas did urban streams 

have more RchVol than rural streams, yet there was not a 

comparable increase in MXL_10. Augmentation from wastewater discharges should not be an issue for streams in any of 

the metropolitan areas because sampled reaches were chosen 

to be upstream from known discharge points. Urban streams in 

Dallas and Boston had higher maximum low-flow depths than 

rural streams had, again contrary to what is expected from 

urbanization (Center for Watershed Protection, 2003).

Few relations were found among reach-scale riparian/

bank characteristics and NLCD_IS for the individual metropolitan areas (table 8). Only Milwaukee, Raleigh, and Boston 

had increasing RipLUDis with increasing NLCD_IS. The lack 

of correlations in other metropolitan areas may be caused in 

part by sampling streams from different stages of urbanization 

or different rural endpoints. Leopold and others (2005) noted 

that the previously open agricultural riparian zone along the 

Watts Branch in Maryland was lined with trees and brush 

30–40 years after urban development. Temporal changes in 

riparian vegetation along the spatially derived gradient may 

be inferred by grouping streams from the nine metropolitan 

areas into four categories of NLCD_IS—rural (less than 

6 percent), urbanizing (6 to less than 12 percent), urban (12 to 

less than 18 percent), and highly urban (greater than or equal 

to 18 percent), with rural representing the initial stages of 

urban development and highly urban representing old urban 

(fig. 6). The Milwaukee spatial trend in open canopy angle 

shown in the histograms somewhat mirrors the Watts Branch 

findings with streams becoming more shaded and wooded as 

agricultural riparian lands are transformed into unmanaged 

public spaces or floodways in urban settings (fig. 6). Only 

Birmingham shows the expected trend of more open streams 

with the highest percentages of NLCD_IS.

Reach-Scale Controls on Habitat and 

Geomorphic Responses to Urbanization

Reach-scale channel alterations and geology, in some 

cases, may overwhelm or moderate a response caused by 

increases in NLCD_IS. Channel alterations were numerous 

for most of the sampled streams; almost 70 percent of rural 

streams and more than 90 percent of highly urban streams had 

at least one type of channel alteration (fig. 7). On average, 

more than 50 percent of the stream lengths were channelized 

for Salt Lake City, Denver, Milwaukee, and Birmingham, 

indicating a possible mix of ongoing geomorphic adjustments 

from variably aged pre-urban agriculture-related and urban 

channelization. Salt Lake City had more streams with bank 

stabilization (56 percent on average) and a greater number of 

grade-control structures (an average of 1.6 per reach) than any 

Figure 6. Percentage of streams with open canopy angle greater than 20 degrees for the percentage of watershed total 

impervious surface (NLCD_IS) groups for all nine and selected individual metropolitan areas of the United States.

Percentage of streams per NLCD_IS group

NLCD_IS 0 to <6%

NLCD_IS 6 to <12%

NLCD_IS 12 to <18%

NLCD_IS >18%

100

90

80

70

60

50

40

30

20

10

0

Figure 6. Percentage of streams with open canopy angle greater than 20 degrees for the percentage of watershed 

total impervious surface (NLCD_IS) groups for all nine and selected individual metropolitan areas of the United 

States. 

All nine

metropolitan areas 

Denver Milwaukee Birmingham Raleigh
Reach-Scale Controls on Habitat and Geomorphic Responses to Urbanization 19

other metropolitan area. Bank stabilization was 30 percent or 

less, and grade-control structures were one or fewer for the 

rest of the metropolitan areas. Unfortunately, the number of 

sites without channel modifications was inadequate for separate analysis of urbanization effects on unmodified streams. 

Reach slope was measured in eight of the nine metropolitan areas and correlated with many habitat characteristics 

(table 9). Reach slope did not correlate with NLCD_IS and 

was more important than urbanization or watershed slope for 

determining streambed substrate size and habitat complexity; 

these results are similar to results from previous studies in 

Chicago, Illinois, and Milwaukee (Fitzpatrick and others, 

2005; Fitzpatrick and Peppler, 2007; table 6). Reach-scale 

slope is assumed to be most affected by natural or human 

engineered factors, such as geologic setting, geomorphic position within the drainage network, and proximity to grade- or 

base-level controls. In this study, streams with relatively steep 

reach slopes generally had smaller cross-sectional areas and 

wider channels, more coarse and less embedded streambed 

substrates, less depth and reach volume, higher low-flow 

velocity, more riffle substrate, and less run than streams 

with relatively gentle slopes. Five of the eight metropolitan 

areas had significant correlations among reach slope and 

streambed substrate. Seven of the eight metropolitan areas 

had significant correlations between reach slope and riffle 

percentage, indicating that small variations in reach slope have 

a substantial influence on habitat complexity and streambed 

substrate. These findings are important for examining the 

possible confounding reach-scale factors that affect physical 

and biological responses to urbanization, especially responses 

of benthic invertebrates, which are dependent on streambed 

substrate type and sedimentation history (Waters, 1995). The 

amount of riparian disturbance and bank erosion was not 

related to reach slope.

Stream reaches with some outcrops of bedrock typically 

have less bank erosion and incision than alluvial streams, even 

in urban environments with high stream power and steep reach 

slopes (Allen and others, 2002; Fitzpatrick and others, 2006). 

Many streams with drainage areas less than 50 km2, such as 

a large number included in this study, are likely affected by 

local geologic controls. For all of the metropolitan areas in this 

study, at least 20 percent of the sampled reaches had outcrops 

of bedrock (fig. 7). Half of the streams in Birmingham and 

Raleigh had bedrock outcrops. Comparisons of correlations 

from a subset of nonbedrock streams with the full dataset are 

not compelling (table 10); however, correlations were stronger 

among some habitat characteristics and landscape characteristics, hydrologic metrics, or reach slope for a subset of streams 

without bedrock outcrops compared to all streams.

Figure 7. Percentage of streams with selected reach-scale channel alterations grouped by percentage of 

watershed total impervious surface (NLCD_IS) for combined data from nine metropolitan areas of the United 

States. (See table 1 for characteristic abbreviation definitions.)

Figure 7. Percentage of streams with selected reach-scale channel alterations grouped by percentage of watershed

total impervious surface (NLCD_IS) for combined data from nine metropolitan areas of the United States. 

[See table 1 for characteristic abbreviation definitions.]

0

10

20

30

40

50

60

70

Not modified ChannelizedPct

>50% reach length

BankStabPct

>20% reach length

GradeControl>0 Bedrock>0

Percentage of streams per NLCD_IS group

NLCD_IS 0 to <6%

NLCD_IS 6 to <12%

NLCD_IS 12 to <18%

NLCD_IS >18%
20 Relation of Urbanization to Stream Habitat and Geomorphic Characteristics in Nine Metropolitan Areas of the United States 

Table 9. Spearman rank correlations among reach-scale slope and selected habitat/geomorphic characteristics for combined and 

individual data from eight metropolitan areas of the United States. 

[nd, no data. Abbreviations for characteristics are defined in table 1. Number of sites for the study unit subsets ranged from 21 to 30. Statistically significant 

correlation coefficients with a P ≤ 0.01 are shown in bold. Reach slope (ReachSlope) data were not collected for the Denver metropolitan area]

All eight 

areas

Portland Salt Lake 

City

Dallas–

Fort Worth

Milwaukee–

Green Bay

Birmingham Atlanta Raleigh Boston

Channel geometry and hydraulics

BFArea –0.39 –0.06 –0.18 0.04 –0.15 0.09 0.31 –0.05 –0.44

BFWidthDepth 0.33 0.59 0.22 –0.18 0.19 0.13 –0.09 –0.07 –0.06

BFArea.DA –0.16 0.03 –0.05 0.00 –0.04 0.14 0.39 0.22 –0.01

FlowStblAvg 0.00 –0.26 –0.33 –0.33 –0.09 0.08 –0.52 –0.25 –0.17

Bottom substrate

DomSubFine –0.43 –0.43 –0.50 –0.20 –0.43 –0.18 –0.65 –0.28 –0.29

DomSubCobble78 0.43 0.47 0.27 –0.09 0.58 –0.01 0.57 0.33 –0.07

DomSubStab 0.19 0.33 –0.03 –0.20 0.19 0.10 0.29 0.36 –0.52

EmbedPctAvg –0.59 –0.73 –-0.37 nd –0.56 –0.19 –0.67 –0.06 –0.33

Low-flow habitat conditions

RchVol –0.36 –0.40 –0.41 –0.13 –0.16 –0.02 –0.06 –0.28 –0.41

RchVol.DA –0.18 –0.35 –0.25 –0.07 –0.15 0.08 0.13 –0.01 –0.15

DepthMax –0.41 –0.32 –0.36 –0.37 0.03 0.07 –0.12 –0.43 –0.18

VelocAvg 0.28 0.56 0.13 0.61 0.12 0.20 0.25 0.29 0.35

Habitat complexity

GCUTypeRiffPct 0.68 0.81 0.84 0.52 0.51 0.08 0.69 0.61 0.72

GCUTypePoolPct 0.13 0.23 0.11 –0.49 0.30 0.04 0.18 –0.32 –0.16

GCUTypeRunPct –0.49 –0.72 –0.63 0.23 –0.50 –0.19 –0.57 –0.08 –0.65

Riparian/bank characteristics

RipLUDis 0.06 –0.35 –0.40 –0.09 0.13 –0.12 0.25 –0.08 –0.05

BankVegCovAvg –0.26 0.21 –0.30 –0.38 –0.14 –0.28 0.24 0.14 –0.33

BankErosPct –0.22 –0.38 –0.23 –0.15 –0.29 0.15 –0.18 –0.17 –0.11

Table 10. Spearman correlations for selected urban indicators, landscape characteristics, hydrologic metrics, and habitat 

characteristics for all streams and streams without bedrock outcrops for combined data from nine metropolitan areas of the 

United States. 

[Abbreviations for characteristics are defined in table 1. Numbers of sites for the subsets ranged from 177 to 249. Statistically significant correlation coefficients with a P ≤ 0.001 and with Bonferroni adjustments range from the absolute value of 0.32 to 0.37. Correlation coefficients with an 

absolute value greater than 0.37 are shown in bold]

BFArea.DA DomSubFine GCUTypeRunPct BankErosPct

All No bedrock All No bedrock All No bedrock All No bedrock

NLCD_IS 0.02 –0.09 0.11 0.03 0.01 –0.03 0.08 0.07

NLCD_21 0.24 0.11 0.18 0.07 –0.12 –0.10 0.04 0.07

MAAT 0.66 0.67 0.35 0.48 –0.01 0.06 –0.17 –0.17

TEXTURE5 0.36 0.45 0.24 0.27 0.16 0.21 0.28 0.24

RB_FLASH 0.12 0.08 0.36 0.38 0.17 0.29 0.47 0.55

PERIODR7 0.25 0.15 0.33 0.30 0.05 0.16 0.34 0.40

MAX_DURFALL 0.14 0.14 0.48 0.55 0.24 0.33 0.36 0.36

ReachSlope –0.16 –0.23 –0.43 –0.49 –0.49 –0.52 –0.22 –0.22
Nonlinear Relations of Depositional Bars, Channel Shape, and Streambed Substrate with Urbanization 21

Nonlinear Relations of Depositional 

Bars, Channel Shape, and Streambed 

Substrate with Urbanization

 The source and amount of transported sediment affect 

channel shape and streambed substrate size and bed configuration (Leopold and Maddock, 1953; Schumm, 1960; Brierley 

and Fryirs, 2005). Because sediment fluxes temporally vary 

in magnitude and source with urban development, spatial 

patterns in channel shape and streambed substrate should 

not necessarily follow a linear trend along an urban gradient. 

For example, in Watts Branch near Rockville, Maryland, a 

40-year study of channel change showed initial changes within 

the first one to two decades of the channel being overloaded 

with sediment and narrowing, followed in the next two 

decades by channel widening as sediment production from 

construction sites decreased (Leopold and others, 2005). 

Descriptive measures of in-channel storage of sediment, such 

as the development and build-up of lateral and mid-channel 

bars in single-thread meandering channels, can be used as 

indicators of channel change caused by changes in the mode 

or magnitude of sediment loads (Thorne, 1998; Brierley and 

Fryirs, 2005; Colosimo and Wilcock, 2007). Potential indicators of channel change were plotted for the four NLCD_IS 

groups, including channel shape (bankfull width/depth ratio), 

presence/absence of depositional bars, streambed substrate 

size and stability, embeddedness, and bank erosion (fig. 8). 

The initial qualitative measurement of the presence 

or absence of lateral and mid-channel depositional bars, 

although tentative, shows an expected response with increasing urbanization (fig. 8). Rural streams had the fewest bars, 

whereas urbanizing streams with 6 to 12 percent NLCD_IS 

had the most. More than 30 percent of rural streams had 

depositional bars, indicating a possible pre-urban excess of 

sediment or a nearby downstream constriction for bedload 

transport, such as an undersized culvert. The percentage of 

streams with depositional bars decreased slightly with higher 

levels of urbanization. Comparatively, the percentage of wide 

streams (width/depth ratios greater than 10) and the percentage 

of streams with fine-grained streambed substrate increased 

initially with urbanization but then decreased at higher levels 

of urbanization. The percentage of streams with sandy, 

embedded substrates increased with increasing urbanization. 

In general, approximately 50 percent of all the streams, both 

rural and urban, had embedded substrate and evidence of bank 

erosion, indicating potential issues with fine-grained sediment 

deposition and local bank sources for sediment in all landcover settings.

Figure 8. Percentage of streams with selected characteristics of channel shape, bar formation, and streambed 

substrate characteristics, grouped by watershed total impervious surface (NLCD_IS) for combined data from all 

nine metropolitan areas of the United States. (See table 1 for characteristic abbreviation definitions.)

Bar BankErosPct

>50%

BFWidthDepth

>10

DomSubFine

>50%

DomSubSand3

>50%

DomSubStab

<0.1

EmbedPctAvg

>50%

NLCD_IS 0 to <6%

NLCD_IS 6 to <12%

NLCD_IS 12 to <18%

NLCD_IS >18%

0

10

20

30

40

50

60

70

Percentage of sites per NLCD_IS group Figure 8. Percentage of streams with selected characteristics of channel shape, bar formation, and 

streambed substrate characteristics, grouped by watershed total impervious surface (NLCD_IS) for 

combined data from all nine metropolitan areas of the United States. [See table 1 for characteristic abbreviation definitions.]
22 Relation of Urbanization to Stream Habitat and Geomorphic Characteristics in Nine Metropolitan Areas of the United States 

Implications

The regional variability of habitat and geomorphic 

relations to urbanization found in this study facilitated further 

exploration of three issues. First, in order to adequately 

determine the potential rate and direction of geomorphic 

responses, multiple spatial scales of urban, landscape, and 

hydrologic characteristics are needed. Second, the occurrence 

and rate of reach-scale geomorphic responses are controlled 

by reach-scale channel boundary conditions. Third, as the 

amount of urbanization increases, geomorphic responses 

are not always linear, mainly because urban-related changes 

in sediment flux are likely nonlinear with time and spatial 

gradients. Overriding all three issues are influences of historical and ongoing reach- to watershed-scale channel alterations, 

in terms of unmeasured drainage network expansions or 

changes associated with stormwater management 

practices and grade control, bank stabilization, 

habitat improvement, and stream rehabilitation. 

Effects from reach-scale channel controls seem to 

be more important than pre-urban watershed-scale 

land cover (agriculture compared to forest). The 

spatial and temporal complexity of these issues 

has limited the development of simple indicators 

of habitat quality or habitat degradation, such as 

those needed for regional and national assessments 

of habitat conditions and similarly developed for 

biological integrity (H. John Heinz III Center for 

Science, Economics, and the Environment, 2002).

Watershed-scale indicators of urbanization 

generally were highly intercorrelated, including 

impervious surface, the urban intensity index, 

watershed total urban land, population density, 

road-area density, and distance to nearest urban 

land. Use of any of these variables in a spatial 

gradient analysis would have given similar results. 

Some of the unexplained variability in hydrologic 

metrics and habitat/geomorphic characteristics 

may have been more interpretable with additional 

quantitative data on connectivity of impervious 

surfaces, possibly through further analysis of 

land-cover patchiness and road-density data or 

higher resolution GIS data. This assessment would 

have benefited from additional data on drainage 

network changes associated with pre-urban water 

use (irrigation, diversion storage, and interbasin 

transfers) and urban stormwater management (conveyance, connectivity, and detention). Streams in 

metropolitan areas in the semiarid Western United 

States, such as Salt Lake City and Denver, had 

highly regulated systems prior to urbanization from 

agricultural uses. Quantitative data for pre-urban 

channel alterations for the northeastern United 

States are probably equally important because of 

abundant dams and mill ponds that are more than 

100 years old (Walter and Merritts, 2008).

General conclusions for major habitat and geomorphic 

responses and adjustments to urbanization are summarized in 

figure 9 and discussed in the next paragraphs. The diagram in 

figure 9 illustrates expected responses of habitat/geomorphic 

characteristics from this study supplemented with insights 

from previous studies. Dashed lines for some characteristics 

indicate that there is some uncertainty in the relation, either 

through lack of conclusive results in this study or previous 

studies. The magnitude and direction of the relational lines in 

figure 9 are arbitrary and realistically will depend on climatic 

and physiographic setting, as well as pre-urban and urbanrelated watershed-scale human modifications of drainage 

network patterns. The streams are assumed to be alluvial with 

no bedrock or base-level control and are not limited by any 

reach-scale channel modifications, such as bank stabilization, 

grade control, or habitat improvements. 

Figure 9. Generalized hydrologic and habitat/geomorphic relations to 

urbanization. [Relations are based on watershed total impervious surface 

(NLCD_IS) for the nine metropolitan areas across the United States. Solid lines 

are relations typically observed in this study and other studies. Dashed lines 

are potential relations. All relations are dependent on watershed climatic and 

physiographic setting. Channels are assumed to be alluvial, nonbedrock, and 

not influenced by historical or recent changes in stormwater management, 

bank stability, or grade control.]

Watershed total impervious surface (percent)

0 10 20 30 40 50

Frequency of high-flow events

Duration of high-flow events

Streambed sediment size

Channel size

Low flow 

Open canopy angle

Habitat complexity (percentage of riffle)

Channel width/depth ratios

Bank erosion

Figure 9. Generalized hydrologic and habitat or geomorphic relations to urbanization. 

Relations are based on watershed total impervious surface (NLCD_IS) for the nine metropolitan areas across the United States. Solid lines are relations typically observed in this 

study and other studies. Dashed lines are potential relations. All relations are dependent 

on watershed climatic and physiographic setting. Channels are assumed to be alluvial, 

nonbedrock, and not influenced by historical or recent changes in stormwater management, bank stability, or grade control.]
Implications 23

Increased frequency of high-flow events was the most 

widespread change in hydrologic conditions associated with 

urbanization (fig. 9). Duration of high-flow events probably 

decreases with increased urbanization, but this aspect is 

moderated by regional variations in climate and physiography. 

Both our data and the literature suggest unidirectional changes 

in the frequency and duration of high-flow events, both 

spatially and temporally. Low-flow characteristics were not 

related to urbanization. Other studies have shown that base 

flow likely decreases with urbanization (Finkenbine and 

others, 2000), but patterns are likely dependent on watershedscale climate, physiography, and water use (Roesner and 

Bledsoe, 2003), as well as reach-scale geologic and geomorphic setting and hydrologic modifications.

Increased channel size is the most predictable geomorphic response of channels to urbanization (fig. 9), most 

likely because channel size mainly is determined by flow 

characteristics and erosion potential (excess shear stress). 

The results from this study supported previous worldwide 

studies (Hammer, 1972; Graf, 1975; Knight, 1979; Whipple 

and DiLouie, 1981; Roberts, 1989; Gregory and others, 1992; 

Doll and others, 2002; Fitzpatrick and others, 2005; Leopold 

and others, 2005; Chin, 2006). Channel size may increase 

through widening, downcutting, or both, depending on the 

erosion-resistance potential of the banks and channel bottom 

and temporal/spatial variations in sediment-flux type and 

magnitude (Roberts, 1989; Allen and others, 2002; Brierley 

and Fryirs, 2005; Cianfrani and others, 2006). In this study, 

six metropolitan areas—Portland, Dallas, Milwaukee, Birmingham, Atlanta, and Raleigh—had increased frequency of 

high-flow events. Of these six areas, Milwaukee, Birmingham, 

and Raleigh had corresponding increases in channel size, 

indicating that the frequency aspect of floods is an important 

hydrologic factor for channel size; however, additional factors 

were more important indicators of channel size for Portland, 

Dallas, and Atlanta. The lack of increases in channel size 

from urbanization for Portland and Dallas is unexpected, 

given that in previous studies of urbanization effects in Seattle 

and Dallas, there was evidence for channel incision (Booth, 

1990; Allen and others, 2002). It is possible that indicators of 

bankfull stage were difficult to identify in Portland, Dallas, 

and Atlanta. The large range in annual precipitation among 

sampled streams in Portland may be another complicating 

factor. Rural channels near Dallas were large relative to other 

rural channels in this dataset, suggesting that historical land 

use or channel modification may have influenced channel size 

and the ability to determine bankfull indicators more so than 

hydrologic conditions.

Sediment-related habitat characteristics, such as channel 

width/depth ratios, streambed sediment size, and bank erosion, 

likely respond to urbanization in a nonlinear pattern. Previous 

studies in the Eastern United States have generally shown 

that suspended-sediment loads do not follow a linear increase 

with increasing urbanization, but instead peak early in the 

urbanization process when construction and land clearing peak 

(Wolman, 1967; Wolman and Schick, 1967; Guy, 1970; Chin, 

2006; fig. 9). These nonlinear patterns would likely happen 

in previously forested or agricultural watersheds. Typical 

hydrologic responses to urbanization combine to increase the 

potential for excess shear stress, channel erosion, and bedload 

transport (Graf, 1975; Whipple and DiLouie, 1981; Roberts, 

1989; Trimble, 1997; Roesner and Bledsoe, 2003; Rohrer 

and Roesner, 2007; Pomeroy and others, 2008). Exploratory 

results from this study and previous temporal studies in the 

Eastern United States (Leopold and others, 2005; Colosimo 

and Wilcock, 2007) indicate that with increasing amount of 

time since urbanization, channels widen initially and then 

narrow, fine sediment increases and then decreases, and 

depositional bar formation increases then wanes. Spatial and 

temporal fluctuations in source and amount of suspended 

sediment and bedload could cause these varying outcomes for 

channel shape, bar formation, and streambed substrate size. 

Measuring the amount and type of depositional features may 

help explain the relative influences on streambed substrate 

from changes in the sources, sizes, and amounts of transported 

sediment in urban streams.

Whether the channel widens or deepens (or both) during 

enlargement can vary, mainly depending on phase of urbanization and the relative strength of the banks and channel bottom 

(fig. 9). A combination of flow energy (slope) and sediment 

flux, which changes as urbanization increases through time or 

space, affects the balance between erosional and depositional 

processes acting on channel banks and bottoms (Brierley and 

Fryirs, 2005; Cianfrani and others, 2006). Streambed substrate 

size and stability may follow similar trends because they also 

are affected by sediment availability. Local channel boundary 

conditions are highly influential on channel-shape responses, 

including engineered grade control, bank stabilization, and 

riparian vegetation (Hession and others, 2003; Cianfrani and 

others, 2006). The balance between erosional and depositional 

processes is mostly dependent on slope; however, the balance 

may be influenced by nearby upstream or downstream flow 

constrictions, such as culverts, that may reduce bedload 

transport, confounding predictions of channel shape or 

substrate adjustments. 

Embeddedness is generally thought to increase in early 

phases of urbanization but eventually decreases as the amount 

of fine sediment decreases or as streams stabilize in old urban 

areas (May and others, 1997; Finkenbine and others, 2000; 

Scholz and Booth, 2001; Center for Watershed Protection, 

2003). In this study, reach slope was related to embeddedness 

more so than NLCD_IS (table 9), although a relation with 

urbanization is perhaps more apparent if the number of 

streams with more than 50 percent embedded substrate is 

compared to amount of urbanization (fig. 8). Some of the 

variability likely was due to known subjectivity problems 

in measuring embeddedness in different stream types with 

different sizes of substrates (Wang and others, 1996; Sylte and 

Fischenich, 2002; McHugh and Budy, 2005). 

Bank erosion was not correlated with watershed urbanization for the combined dataset (table 6), and few conclusive 

studies exist on urbanization effects on bank erosion (Booth, 
24 Relation of Urbanization to Stream Habitat and Geomorphic Characteristics in Nine Metropolitan Areas of the United States 

1991; Center for Watershed Protection, 2003; Fitzpatrick and 

others, 2005) perhaps because of the many, highly variable 

reach-scale factors that can influence bank erosion, such as 

geology and riparian vegetation (Pizzuto and others, 2000; 

Hession and others, 2003). Bank erosion for the combined 

dataset correlated with flashiness and duration metrics, similar 

to findings by Julian and Torres (2006) that indicated that 

flow variability is important. The amount of observed bank 

erosion is particularly sensitive to grade control, the presence 

of erosion-resistant bedrock, or bank stabilization structures, 

many of which are well hidden by techniques that emphasize 

natural-looking channels. If length of erosion along a transect 

is measured instead of just noting the presence or absence 

of erosion and if bank stabilization is assessed as part of the 

reach-scale habitat assessments, a response between bank 

erosion and urbanization may be seen, such as that seen in 

the Milwaukee study by Fitzpatrick and Peppler (2007). The 

trendline in figure 9 for bank erosion mainly is based on the 

Milwaukee study, which had a steep increase in length of bank 

erosion between 0 and 15 percent NLCD_IS and a continuing 

increase for streams with greater than 15 percent NLCD_IS.

Decreases in habitat complexity from urbanization 

could not be detected in this study, but some evidence from 

other studies suggests that complexity decreases and pool 

depth increases with urbanization (fig. 9; Scholz and Booth, 

2001; Walsh and others, 2005). For streams in this study, the 

measure of habitat complexity (percent riffle, run, pool) was 

primarily related to reach slope, with lesser influences from 

north-south regional differences, watershed size, amount of 

watershed agricultural land, soil permeability, and frequency 

of high-flow events (tables 7, 9). Reach slope should be 

considered as an important independent factor for studying 

effects of land-cover disturbance because changes in reach 

slope are caused by century- to millennial-scale changes in 

climatic conditions and basinwide network development, not 

decadal changes in land cover (Sear and others, 2003). Thus, 

the extra time taken to accurately measure reach watersurface slope provides information for describing the most 

explanatory variable in predicting substrate size and habitat 

complexity. Perhaps a more sensitive measurement for habitat 

complexity would be within-reach variability of velocity/depth 

combinations. Additionally, it may be important to investigate 

habitat complexity in terms of varying flow conditions instead 

of point-in-time low-flow conditions. 

Responses of low flow to urbanization in this study were 

hampered by its confounding relation to stream size. The 

hydrologic metric that was used as a surrogate for low-flow 

conditions, MXL_10, was affected by stream size. No conclusive evidence from other studies shows that reach volume 

decreases with increasing urbanization (Walsh and others, 

2005), potentially because this measurement also is affected 

by channel modifications within the reach. The trend line for 

low flow is flat in figure 9 because reach volume is more likely 

to be affected by other factors than by urbanization.

Finally, the space-for-time approach for determining 

habitat/geomorphic responses to urbanization was adequate 

for showing changes in hydrology and channel size, but it 

may miss subtle and cumulative effects caused by historical 

events and nonlinear temporal trends in sediment sources 

and loads. Temporally, a stream reach may be experiencing 

ongoing geomorphic adjustments from natural and human 

modifications prior to urbanization, including large floods, 

flood control, channel rehabilitation, grade control, and road 

crossings. During the 1990s, channel restoration projects 

increased for small and large streams across the United 

States in urban and rural areas (Cunningham, 2002; Schueler, 

2004; ICF Consulting, 2005). Recent Federal guidelines for 

stream mitigation have further promoted extensive channel 

rehabilitation (U.S. Environmental Protection Agency, 1995; 

U.S. Army Corps of Engineers and others, 2003). Recent 

channel stabilization efforts look much more natural than older 

efforts and can be difficult to detect even after a few years 

because hard structures typically are hidden by vegetation. In 

this study, the possibility of channel modifications was high 

for all streams along the urban gradient; more than 60 percent 

of rural streams had channel modifications, and about 

90 percent of urban streams had modifications. Furthermore, 

geomorphic adjustments within a reach may be the result of 

channel modifications upstream or downstream. Knowledge 

of historical channel modifications within and surrounding 

the reach is an important part of any assessment of habitat 

conditions related to urbanization. 

Summary and Conclusions

Habitat and geomorphic responses to urbanization were 

dependent on regional variations in climatic and physiographic 

conditions, as well as effects from reach-scale channel 

alterations, slope, and geologic setting. Total impervious 

surface was a useful watershed-scale indicator of urbanization, 

although the study would have benefited from more detailed 

data on stormwater management practices and connectivity of 

impervious surfaces. Reach-scale human and natural controls 

on channel-boundary conditions, including amount of channel 

alterations (bank stabilization, channelization, and grade 

control), bedrock/parent material, and reach slope also were 

important. Inclusion of reach slope in analyses was necessary 

for describing reach-scale controls on hydrologic conditions 

and habitat responses, especially for streambed substrate 

and habitat complexity. Hydrologic metrics that described 

various aspects of frequency and duration of high-flow events 

were helpful in describing the continuity between watershed 

urbanization and habitat changes. 

Channel enlargement (channel widening or downcutting) 

and increases in disturbed riparian vegetation only occurred 

in three metropolitan areas in the Midwestern and Eastern 

United States. The frequency of large high-flow events was 

the hydrologic characteristic most closely related with the 

channel enlargement. Streams with pre-urban hydrologic 

alterations from interbasin transfers and diversions or dams 
References Cited 25

and reservoirs, such as the streams found in the semiarid West 

and Northeast, did not show channel enlargement. Changes 

in amounts of disturbed riparian vegetation associated with 

urbanization vary regionally and with the amount of urbanization. The amount of riparian shading may increase along 

previously agricultural streams, or may remain the same or 

decrease along previously forested streams.

Channel shape and streambed substrate size were not 

correlated with watershed urbanization, likely because these 

characteristics are affected by temporal changes in the type 

and source of sediment load associated with phases of urbanization and controls on channel-boundary conditions within 

the sampled reach. Bank erosion increased with an increasing 

index of hydrologic flashiness in Milwaukee and Boston, but 

no trends were observed in other metropolitan areas. Lack of 

observed responses for bank erosion with watershed urbanization may have been caused by the abundance of channel and 

bank stabilizations in urban reaches or simply by the high 

percentage of streams with bank erosion in both rural and 

urban settings. 

Results of this study were inconclusive for responses 

of habitat complexity and low-flow habitat conditions to 

urbanization. Instead, habitat complexity, in terms of percentage of riffle, run, and pool, mainly depended on variations in 

reach slope. Responses of low-flow habitat conditions, such as 

reach volume, likely were masked by precipitation variations, 

within-reach channel modifications, and stream size.

The multitude of within-reach channel modifications, 

such as channelization, bank stabilization, and grade control; 

the presence of bedrock in urban streams from a variety of 

environmental settings; and the importance of reach slope 

emphasize that reach-scale data are needed to adequately 

describe controls on channel-boundary conditions and potential geomorphic responses. This is an especially important 

issue as the popularity of channel rehabilitation continues and 

as bank stabilization and grade control efforts are designed to 

appear natural.

Acknowledgments

The data used in this report were collected, compiled, 

and managed by many USGS scientists and technicians, and a 

study of this magnitude would not have been possible without 

them. Of special note are those USGS scientists who assisted 

with the extra data gathering and analysis needed for this 

report. The authors thank Jeff Steuer and Elise Giddings who 

provided hydrologic metrics and technical insights. We also 

thank those from the nine USGS Water Science Centers who 

provided relevant site photographs and copies of habitat reach 

maps and notes. James Falcone provided extra assistance 

with GIS-derived characteristics. Kelly Ruhl provided data 

on dams and engineered channels. The manuscript benefited 

by technical reviews from Thomas Chapman (Milwaukee 

Metropolitan Sewerage District), Cliff Hupp (USGS), and 

Michael Yurewicz (USGS). 

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Fitzpatrick and Peppler—Relation of Urbanization to Stream Habitat and Geomorphic Characteristics in Metropolitan Areas of the U.S.—Scientific Investigations Report 2010–5056