Benthic Macroinvertebrate Indicators of Strea

Quality of Selected Above-Tidal Streams in th

Houston-Galveston Area Council Service Are

Texas, 1997–98

Water-Resources Investigations Report 01–4010

U.S. Department of the Interior

U.S. Geological Survey
Cover:

Buffalo Bayou west of downtown Houston. (Photograph by J. Bruce Moring, August 1998.)
U.S. Department of the Interior

U.S. Geological Survey

Influence of Stream Habitat and Land Use on 

Benthic Macroinvertebrate Indicators of Stream 

Quality of Selected Above-Tidal Streams in the 

Houston-Galveston Area Council Service Area, 

Texas, 1997–98

By J. Bruce Moring

U.S. GEOLOGICAL SURVEY

Water-Resources Investigations Report 01–4010

In cooperation with the Houston-Galveston Area Council

Austin, Texas

2001
ii

U.S. DEPARTMENT OF THE INTERIOR

Gale A. Norton, Secretary

U.S. GEOLOGICAL SURVEY

Charles G. Groat, Director

Any use of trade, product, or firm names is for 

descriptive purposes only and does not imply 

endorsement by the U.S. Government.

For additional information write to

District Chief

U.S. Geological Survey

8027 Exchange Dr.

Austin, TX 78754–4733

E-mail: dc_tx@usgs.gov

Copies of this report can be purchased from

U.S. Geological Survey

Branch of Information Services

Box 25286

Denver, CO 80225–0286

E-mail: infoservices@usgs.gov
CONTENTS iii

CONTENTS

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

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

Purpose and Scope .................................................................................................................................................... 2

Description of Study Area ........................................................................................................................................ 2

Approach .............................................................................................................................................................................. 4

Reach Selection ........................................................................................................................................................ 4

Assessment Components .......................................................................................................................................... 4

Sampling-Reach Stream Habitat ................................................................................................................... 4

Land Use and Population .............................................................................................................................. 7

Benthic Macroinvertebrate Sampling ............................................................................................................ 7

Data Analysis ............................................................................................................................................................ 7

Influence of Stream Habitat and Land Use on Benthic Macroinvertebrate Indicators of Biological Integrity .................... 8

Relation Between Stream Habitat and Land Use ..................................................................................................... 8

Relation Between Benthic Aquatic Insects and Land Use ....................................................................................... 10

Selection of Reference Reaches ............................................................................................................................... 13

Stream-Habitat and Biological Integrity Scores ....................................................................................................... 15

Multiple-Regression Model to Predict Biological Integrity ..................................................................................... 20

Summary .............................................................................................................................................................................. 21

References Cited .................................................................................................................................................................. 21

FIGURES

1. Map showing data-collection sites in the Houston-Galveston Area Council service area ................................... 3

2. Boxplots showing distribution of selected stream-habitat variables for reaches grouped by dominant 

land use ................................................................................................................................................................. 10

3. Graphs showing relation between population density in above-reach drainage areas and selected 

stream-habitat variables ........................................................................................................................................ 11

4. Boxplots showing distribution of selected benthic aquatic insect variables for reaches grouped by 

dominant land use ................................................................................................................................................. 12

5–10. Graphs showing:

5. Relation between population density in above-reach drainage areas and selected benthic aquatic 

insect variables ........................................................................................................................................... 14

6 Reach structural index and RCE maximum for selected reaches classified by percentile and 

stream-habitat integrity score...................................................................................................................... 15

7. Percent EPT taxa and number of taxa for selected reaches classified by percentile and biological 

integrity score ............................................................................................................................................ 16

8. Hilsenhoff’s biotic index and percent Chironomidae for selected reaches classified by percentile 

and biological integrity score ..................................................................................................................... 17

9. Correlation of stream-habitat integrity score with biological integrity score for selected reaches ........... 19

10. Stream-habitat and biological integrity scores compared to median integrity scores for reference 

sites ............................................................................................................................................................ 20

TABLES

1. Data-collection sites for stream-habitat and benthic macroinvertebrate sampling in the HoustonGalveston Area Council service area .................................................................................................................... 5

2. Stream-habitat and land-use metrics determined for each stream reach .............................................................. 6

3. Benthic macroinvertebrate metrics determined for each stream reach ................................................................. 8

4. Factor loadings from principle components analysis (PCA) greater than 0.7 for reach-habitat variables 

and proportion of variation explained by each principal component ................................................................... 9
iv 

5. Factor loadings from principle components analysis (PCA) greater than 0.7 for land-use variables 

and proportion of variation explained by each principal component .................................................................... 9

6. Factor loadings from principle components analysis (PCA) greater than 0.7 for benthic aquatic insect 

variables and proportion of variation explained by each principal component .................................................... 11

7. Stream-habitat and biological integrity scores for selected reaches ..................................................................... 18
Abstract 1

Influence of Stream Habitat and Land Use on 

Benthic Macroinvertebrate Indicators of Stream 

Quality of Selected Above-Tidal Streams in the 

Houston-Galveston Area Council Service Area, 

Texas, 1997–98

By J. Bruce Moring

Abstract

During 1997–98, the U.S. Geological Survey, in cooperation with the Houston-Galveston 

Area Council, collected stream-habitat and benthic 

macroinvertebrate data for 31 reaches on abovetidal streams in the Council service area near 

Houston, Texas. Stream-habitat, land-use and population, and benthic aquatic insect metrics were 

determined for the 31 reaches. Statistical analyses 

were used to determine the stream-habitat, land-use 

and population, and aquatic insect variables that 

are strongly intercorrelated and that explain the 

greatest amount of variation between the reaches.

Comparison of stream-habitat and biological 

integrity scores computed for each of the 31 

reaches indicated (1) reaches generally had larger 

stream-habitat integrity scores in drainage areas 

that were heavily forested and had fewer people 

per square mile, (2) larger biological integrity 

scores were significantly correlated with larger 

stream-habitat integrity scores, and (3) urban 

reaches generally had more simplified streamhabitat conditions and smaller biological integrity 

scores.

Seven reaches in the study area were selected 

as reference reaches on the basis of high streamhabitat integrity and high biological integrity. The 

reference-reaches median biological integrity score 

was equaled or exceeded by three reaches (one 

on Spring Creek and two on Cypress Creek) that 

are on the State of Texas 303(d) list of threatened 

or impaired waters with respect to aquatic life. 

This indicates that direct measures of biological 

integrity could be used to supplement surrogatebased designations of biological integrity such as 

the State list.

A statistically significant multipleregression model was developed that uses independent variables that can be obtained without fieldintensive studies to predict the biological integrity 

score for a reach. The deviation from the model’s 

predicted score with the score based on biological 

sampling can be used to interpret the degree 

of biological impairment in a reach. Data from 

reaches outside the group of reaches used in this 

study are needed to test the validity of the multipleregression model.

INTRODUCTION

The Houston-Galveston Area Council (H–GAC) 

is the lead agency for the Texas Natural Resource 

Conservation Commission (TNRCC) Texas Clean 

Rivers Program (CRP) for watersheds near Houston, 

Texas. Under this program, H–GAC was required to 

develop (1996) and implement (1997–98) a regional 

water-quality monitoring program. The objective of the 

monitoring program is to provide the data needed to 

assess current water-quality conditions in the CRP river 

basins within the H–GAC service area. The assessment 

will be used to direct future regulatory and management 

actions on stream segments affected by point or 

nonpoint sources of contaminants. The CRP Technical 

Steering Committee for H–GAC determined that 

additional monitoring activities should emphasize 

stream bioassessment methods to evaluate water quality 

in CRP river basins. H–GAC elected to focus on biological assessment through synoptic sampling as the major 

component of its 1997–98 CRP monitoring program. 
2 Influence of Stream Habitat and Land Use on Benthic Macroinvertebrate Indicators of Stream Quality of Selected Above-Tidal

Streams in the Houston-Galveston Area Council Service Area, Texas, 1997–98 

The Texas Clean Rivers Act of 1991 (Texas 

Statute 818) (Texas Natural Resource Conservation 

Commission, 2000) requires the establishment of waterquality standards and the assessment and management 

of water quality. The Act requires the TNRCC to 

(1) assess water quality in the State; (2) investigate the 

effects of nonpoint-source pollution, toxic materials, 

and nutrient loadings; and (3) address discharge permit 

concerns. As a component of the CRP for the 1995–96 

biennium, the TNRCC solicited proposals for “pilot 

projects” to address nonpoint-source pollution concerns 

relating to urban, agricultural, coastal, or geographic 

specific environments.

In response to this initiative, the U.S. Geological 

Survey (USGS), in cooperation with the H–GAC, 

conducted a study in 1997–98 to determine the status 

of in-stream biological resources, including fish and 

macrobenthic community structure and stream-habitat 

conditions. The objectives of this study were to 

(1) conduct an assessment of in-stream biological and 

habitat resources at above-tidal stream sites within the 

H–GAC service area; (2) establish reference-condition 

sites for comparison to non-reference sites; and 

(3) develop a multivariate predictive model for statistical comparisons of sites to determine levels of disturbance of in-stream biological resources. The first 

objective has been completed and documented by 

Moring and others (1998). 

Objectives two and three, the focus of this report, 

were accomplished by (1) determining the streamhabitat, land-use, and (or) biological factors that 

account for the greatest variation between sites in the 

study area; (2) using the selected factors to compute a 

stream-habitat and biological integrity score for each 

site; (3) selecting a network of least-affected reference 

sites to establish a watershed-scale reference condition 

and, using the integrity scores, compare non-reference 

sites with reference sites; and (4) developing a multipleregression model to predict the status of the biological 

resources at sites without extensive biological sampling. Benthic macroinvertebrate data were used to 

compute a biological integrity score because benthic 

macroinvertebrates should provide better site-specific 

information about a site or reach than fish community 

data (Cuffney and others, 1993). Fish mobility tends to 

make determination of accurate species composition 

and relative abundance information more difficult. This 

is particularly true for a synoptic sampling study such as 

this one, designed with only one visit per site. 

Purpose and Scope

This report evaluates the influence of stream 

habitat and land use on benthic macroinvertebrate 

indicators of biological integrity. Specifically, the 

report documents (1) the relation between stream 

habitat and land use, (2) the relation between benthic 

aquatic insects and land use, (3) the selection of 

reference reaches, (4) stream-habitat and biological 

integrity scores for reference and non-reference 

reaches, and (5) a multiple-regression model to 

predict biological integrity scores for reaches without 

biological sampling. 

The evaluation is based on data collected during 

1997–98 for 31 above-tidal reaches of streams in the 

Houston-Galveston area. The data collected consist of 

channel and riparian characteristics of the stream habitat, land-use and human population information, and 

distribution and composition of the benthic macroinvertebrate communities. 

Description of Study Area

The H–GAC service area (fig. 1) consists of the 

15-county Gulf Coast Planning Region that covers 

about 20,100 square kilometers (km2

) and has a population of about 4.3 million people. H–GAC is a regionwide voluntary association of about 150 local governments and agencies that include 15 county governments, 106 cities, 19 school districts, and 10 soil and 

water conservation districts.

The watersheds assigned to H–GAC under the 

CRP include the San Jacinto River Basin, TrinitySan Jacinto Coastal Basin, San Jacinto-Brazos Coastal 

Basin, and Brazos-Colorado Coastal Basin (fig. 1). 

The majority of the study area, including all coastal 

areas, is within the Western Gulf Coastal Plain ecoregion (Omernick, 1987). The Central Plains ecoregion 

extends into the northeastern part of the area, and the 

East Central, South Central, and Blackland Prairie 

ecoregions constitute the extreme northwestern part 

of the area. Natural features in the area include evergreen forests in the San Jacinto River Basin; extensively 

forested wetland corridors along the Trinity, Brazos, 

and Colorado Rivers, coastal bays, and estuaries; and 

non-forested wetlands in the large river floodplains 

and coastal areas. Cropland and pasture are the dominant rural land uses in the study area. Mixed urban, 

commercial, and industrial, particularly petrochemical 

industry along many of the waterways, are the dominant 
INTRODUCTION 3

0 10 20 30 40 MILES

Spring

Cr.

Cypress

Creek

TRINITY

RIVER

BRAZOS

RIVER

SAN BERNARD

RIVER

COLORADO

RIVER

NAVASOTA

RIVER

WEST FORK SAN

 JACINTO RIVER

EAST FORK SAN

 JACINTO RIVER

LAKE 

 CONROE

TRINITY BAY

GALVESTON BAY

GULF OF MEXICO

GULF OF MEXICO

WALKER

GRIMES

MONTGOMERY

SAN

 JACINTO

WALLER

AUSTIN

COLORADO

WHARTON

FORT BEND

HARRIS

LIBERTY

CHAMBERS

GALVESTON BRAZORIA

MATAGORDA

31o

95o30"

96o

95o

94o30"

96o

30"

30o

29o

30o30"

29o

30"

28o

30"

HOUSTON

Buffalo Bayou

Brazos-Colorado 

 Coastal Basin

San Jacinto River Basin

San Jacinto-Brazos 

 Coastal Basin

Trinity-San Jacinto 

 Coastal Basin

Data-collection site—

 Number is Houston-

 Galveston Area Council 

 identification number,

 (referenced in table 1)

EXPLANATION

WFSJ0010

BRAN0011

CANY0017

EFSJ0016

BIGC0015

EFSJ1237

LAKE0012 WILL8325

LAKE1367

WFSJ8000

SPRI0027

WALN0026 SPRI0024

CYPR8800

PANT0040

SPRI8500

LANG0003

WOAK1394

CYPR1329 CYPR1324

SPRI0023

SPRB0022

WFSJ8090 LUCE1280

CANY0020

EFSJ0200

CEDR7500

GREN0034

GARN6180

BUFF4000 BUFF3600 BUFF0005

TEXAS

Study area

LOCATION MAP

Figure 1. Data-collection sites in the Houston-Galveston Area Council service area.
4 Influence of Stream Habitat and Land Use on Benthic Macroinvertebrate Indicators of Stream Quality of Selected Above-Tidal

Streams in the Houston-Galveston Area Council Service Area, Texas, 1997–98 

land uses in and around the greater Houston metropolitan area. 

APPROACH

The selection of watershed-scale reference sites 

or a watershed-scale reference condition can provide a 

more direct and meaningful “point-of-reference” than a 

regional or state-wide criterion if the objective is to 

determine the status of one or more non-reference sites 

in a watershed. A recent development in water-quality 

monitoring is the use of a reference condition based 

on pre-established criteria for a wide range of sites 

rather than relying on a single reference or control site 

(Reynoldson and others, 1997). The reference condition 

is better defined as the best available or best attainable 

condition and is represented by information from a 

number of sites. The reference condition approach is 

useful in watersheds that are characterized by different 

types and intensities of land use and dominated by nonpoint-source conditions where the most reasonable or 

best attainable condition is something less than an ideal, 

non-affected condition. The overall approach in this 

study is to establish a reference condition through the 

selection of a group of reference sites (reaches) to determine the biological integrity of above-tidal, low-order 

streams in the San Jacinto River Basin. Below-tidal 

stream reaches were not included in this study because 

of the distinct differences between freshwater and 

tidal biological communities. In addition, much of the 

interpretation in this report assumes influences of the 

upstream drainage and does not consider the influence 

of fluctuations in salinity that occurs in tidal streams.

A reach-based compositing approach (Gurtz, 

1994) rather than an equal-effort time-based approach 

(Barbour and others, 1997) was chosen as the method of 

sampling. The reach-based approach incorporates a 

stream-habitat component in the selection of a sampling 

location. The establishment of a well marked and monumented reach can allow for more easily repeated 

within-reach sampling at a location to assess trends or 

changes over time.

Reach Selection

H–GAC service-area base maps and geographic 

information system (GIS) coverages were acquired 

that include: (1) ecoregion and/or physiographic provinces; (2) watershed and subwatershed boundaries; 

(3) potential vegetation; (4) land use; (5) TNRCCdesignated stream segments and land-use classifications; and (6) network of current water-quality 

monitoring stations. These map resources and appropriate databases were used to support the selection of 

potential sites and to assist in the screening of these 

potential sites to produce a final group of study sites. 

For this study, a “site” is a sampling reach that is 

defined by the types and frequencies of geomorphic 

channel units or as a multiple of wetted channel width 

(Meador and others, 1993; Moring and others, 1998). 

The majority of sampling reaches are one full meander 

of channel length with a riffle-run-riffle-run or rifflepool-riffle-pool sequence of geomorphic channel units. 

If the reach lacked distinct multiple geomorphic channel units, the reach length was determined as a multiple 

of the wetted channel width. More detail on the selection and establishment of a sampling reach and information on project objectives and approach can be found in 

the report providing all project data (Moring and others, 

1998) or by accessing the project web page at URL 

http://tx.usgs.gov/hgac/index.html 

 Thirty-nine reaches were initially selected for 

physical habitat and benthic macroinvertebrate assessments. Large river reaches on the Colorado, Brazos, 

Navasota, and San Bernard Rivers were not included in 

this study because the drainage areas for these reaches 

extend beyond the H–GAC service area and were 

thought to be less influenced by adjacent land uses, 

upstream drainage area, and bank features than streams 

with smaller drainage areas. Reaches that were thought 

to be tidally influenced and the few sites in the Blackland Prairie ecoregion also were not included in this 

study. Because the number of smaller stream reaches 

outside the San Jacinto River Basin was not sufficient to 

provide adequate sample sizes for meaningful statistical 

analysis, the final selection included 30 reaches in the 

San Jacinto River Basin and 1 in the Trinity River Basin 

(fig. 1, table 1). The reach in the Trinity River Basin, 

Big Creek in the Big Creek Scenic Area, was included 

because its drainage area is heavily forested and largely 

undeveloped, and it is in the same physiographic setting 

as adjacent reaches in the San Jacinto River Basin.

Assessment Components

Sampling-Reach Stream Habitat

A field assessment of channel and riparian characteristics associated with each sampling reach was 

done to determine the geomorphic factors that most 

influence the benthic macroinvertebrate community 
APPROACH 5

Table 1. Data-collection sites for stream-habitat and benthic macroinvertebrate sampling in the HoustonGalveston Area Council service area

[H–GAC, Houston-Galveston Area Council; FM, farm road] 

Site 

(reach name)

H–GAC 

identification no.

(fig. 1)

Downstream reach 

boundary coordinates

Latitude Longitude

Big Creek in Big Creek Scenic Area/Sam Houston National Forest BIGC0015 3030'13" 9505'21"

Branch Creek at FM 1375 bridge BRAN0011 3031'38" 9540'45"

Buffalo Bayou at Eldridge Pkwy. BUFF0005 2946'13" 9537'15"

Buffalo Bayou at West Belt Dr. BUFF3600 2945'43" 9533'27"

Buffalo Bayou at Houston BUFF4000 2945'36" 9524'30"

Caney Creek near Willis CANY0017 3027'21" 9525'28"

Caney Creek near New Caney CANY0020 3008'55" 9511'30"

Cedar Bayou near Crosby CEDR7500 2858'20" 9459'10"

Cypress Creek west of I–45 and north of FM 1960 at Cypresswood CYPR1324 3001'45" 9519'47"

Cypress Creek at Kuykendahl Rd. bridge CYPR1329 3001'19" 9528'38"

Cypress Creek at Grant Rd. CYPR8800 2958'24" 9535'54"

East Fork San Jacinto River at FM 945 EFSJ0016 3035'48" 9511'58"

East Fork San Jacinto River near New Caney EFSJ0200 3008'43" 9507'27"

East Fork San Jacinto River on FM 2025 EFSJ1237 3025'29" 9507'30"

Greens Bayou at Mt. Houston Pkwy. GREN0034 2953'50" 9514'19"

Lake Creek at FM 149 LAKE0012 3016'48" 9542'18"

Lake Creek near Egypt LAKE1367 3015'21" 9534'70"

Langham Creek at Patterson Rd. LANG0003 2948'49" 9537'40"

Luce Bayou above Lake Houston near Huffman LUCE1280 3006'34" 9503'35"

Panther Creek at The Woodlands PANT0040 3009'15" 9528'55"

Spring Branch Creek at State 242/FM 2090 SPRB0022 3013'11" 9514'54"

Spring Creek at Riley Fuzzel SPRI0023 3005'31" 9524'21"

Spring Creek near Tomball SPRI0024 3008'00" 9535'50"

Spring Creek on Robert Cemetery Rd. SPRI0027 3005'12" 9545'46"

Spring Creek at Spring (I–45 bridge) SPRI8500 3006'41" 9526'01"

Walnut Creek near Magnolia WALN0026 3008'36" 9545'12"

West Fork San Jacinto River at State 30 WFSJ0010 3038'47" 9540'29"

West Fork San Jacinto River near Conroe at I–45 WFSJ8000 3014'51" 9527'39"

West Fork San Jacinto River above Lake Houston near Porter WFSJ8090 3005'09" 9517'59"

Willow Creek near Tomball WILL8325 3016'19" 9532'47"

White Oak Bayou at Bingle Rd. WOAK1394 2952'37" 9529'36"

within each reach (table 2). The riparian, channel, and 

environmental index (RCE) (Petersen, 1992) was 

calculated at each site to provide an initial and rapid 

assessment of the physical conditions of small to midsized channel reaches. The RCE consists of 16 scored 

metrics that include adjacent land use, continuity and 

vegetative makeup of the riparian and floodplain zones, 

channel structure, channel sediments, bank undercutting, aquatic vegetation, and type and frequency of geomorphic channel units. The RCE generates a unitless 
6 Influence of Stream Habitat and Land Use on Benthic Macroinvertebrate Indicators of Stream Quality of Selected Above-Tidal

Streams in the Houston-Galveston Area Council Service Area, Texas, 1997–98 

numerical score that can be used to compare physical/biological conditions between different streams 

with the same level of site classification, such as small 

streams in an urban land-use setting or a particular 

physiographic setting. The numerical score is grouped 

into five classifications for use in stream-monitoring 

programs and for comparison to biological indices such 

as the index of biological integrity (IBI) for fish. The 

RCE was computed for the large river sites to provide 

useful site information, particularly channel metrics; 

however, the RCE bank and adjacent land-use metrics 

probably have little meaning for a large river channel 

that can be influenced more by inflows from the 

upstream drainage than by adjacent land uses. The variable, RCE maximum, was calculated as the RCE value 

for each reach divided by the maximum RCE for all 

reaches to standardize this variable. 

In addition to the RCE, several reach-based and 

within-reach, transect-based metrics were made (table 

2). Four channel cross sections extending from the right 

high-bank terrace to the left high-bank terrace were 

established in each reach corresponding to the four geomorphic channel units that were selected, or the cross 

sections were placed at regularly spaced intervals if the 

sampling reach length was based on a multiple of the 

median wetted channel width. The majority of the 

reaches were meandering channels in a low-gradient 

coastal plain, and the selection of geomorphic units generally corresponded to bends in the channel where riffles and/or pools are common and the runs are between 

the bends. Cuffney and others (1993) suggest six or 

more transects per reach, whereas Wang and others 

(1996) recommend a transect every two times the 

median wetted channel width. However, in this study, 

four cross sections in each reach were considered sufficient to characterize channel morphology and, thus, 

variability in stream velocity, depth, and substrate types 

and distribution. Longitudinal reach characteristics 

were normalized by dividing each frequency by the curvilinear reach length to allow for comparisons between 

Table 2. Stream-habitat and land-use metrics determined for each stream reach

[m, meters; m/s, meters per second] 

In channel Bank Riparian zone Land use and 

human population

Linear reach length (m) Median right bank slope RCE (riparian, channel, and 

environmental index)

Percent urban land use

Curvilinear reach length (m) Median left bank slope RCE maximum Percent agricultural land use

Sinuosity Median bank slope Canopy angle (degrees) Percent forest land use

Number of snags Median right bank height (m) Percent wetland

Number of stumps Median left bank height (m) Percent barren land

Number of undercut banks Median bank height (m) Population density

Number of other obstructions Median bank height/width ratio

Reach structural index Median high-bank width (m)

Number of bars

Median width (m)

Median depth (m)

Median velocity (m/s)

Median wetted channel 

width (m)
APPROACH 7

reaches of different lengths. Stream-habitat metrics are 

defined in Moring and others (1998) and at the project 

web page at URL http://tx.usgs.gov/hgac/index.html

A Sokia Leitz Set 4A laser-operated total station 

was used to survey all transects and the entire reach to 

produce many of the reach habitat measures. All survey 

data were stored on-site in a datalogger that was electronically linked to the total station. The data were 

imported into an electronic spreadsheet and sorted and 

computations were made to determine linear reach 

length, curvilinear reach length, bank height, bank 

width, bank slope, wetted channel width, median depth, 

and frequencies of various in-channel structures such as 

woody debris and undercut banks. More details on the 

assessment of reach habitat features are available from 

Moring and others (1998).

Land Use and Population

Land-use and human population data were determined from above-reach polygons using ARC–INFO. 

The drainage area above each reach was delineated, 

and a polygon was established. Total acreage for the 

above-reach polygon was determined, and the percentage of land use within the polygon was determined for 

urban, agricultural, forest, wetland, and barren land use. 

Human population per square mile of the above-reach 

polygon was determined using data from the 1990 

census (U.S. Census Bureau, 2000). These data and 

information were provided by GIS specialists with 

the H–GAC Community and Environmental Planning 

Division.

Benthic Macroinvertebrate Sampling

Three to five benthic macroinvertebrate samples 

collected in each reach from the richest targeted habitat 

(RTH) were composited and placed into a single container. The sample was wet-sieved in the field using a 

425-micrometer (m) mesh 10-inch (in.)-diameter 

sieve, transferred to a sample jar, and fixed with 

10-percent buffered formalin. All samples were transferred from the 10-percent formalin to a 70-percent 

ethanol solution for preservation pending shipment to 

the laboratory for sample processing, identification, and 

enumeration. More details on field collection, processing, identification, and enumeration of the samples are 

presented in Moring and others (1998).

The method of collection was intentionally biased 

towards the collection of benthic aquatic insects 

(Cuffney and others, 1993) and not the collection of 

other macroinvertebrates. The RTH should have the 

greatest number of benthic macroinvertebrate species, 

particularly aquatic insects, and generally consists of a 

coarse substratum such as a cobble bottom or entrained 

woody debris and leaves in a riffle or moderately flowing section of the reach. Each sample was collected 

with a modified surber sampler (Cuffney and others, 

1993) consisting of a rectangular-framed sampler with a 

425-m mesh net and attached 425-m plankton bucket. 

The distribution and composition of benthic 

macroinvertebrate communities in streams respond to 

natural changes in the physical and chemical conditions 

that occur along the longitudinal axis of the river 

(Vannote and others, 1980). Changes in environmental 

variables such as riparian zone condition, water temperature, light penetration, streamflow regimes, and water 

and sediment chemistry all influence the type of benthic 

invertebrate community present at a given location. 

From upstream to downstream along a stream reach, 

changes in the variety of stream habitats (including 

riffles, runs, and pools) influence the type and stability 

of substrates and the stream depths and velocities. 

These changes in stream habitats and their characteristics affect the presence, absence, and relative abundance 

of benthic macroinvertebrate taxa. 

Biological metrics computed from the benthic 

macroinvertebrate data included numbers and percentages of major trophic groups and major taxa, taxa richness, and several diversity and other selected indices 

(table 3).

Data Analysis

All reach data were keyed into an electronic 

spreadsheet, sorted, and reviewed for any errors. 

Data were electronically transferred from the spreadsheet to a statistical software package (STATISTICA, 

1999) for data summary and analysis. Statistical analyses included a principal components analysis (PCA), a 

two-sample student’s t-test, and a multiple regression. 

PCA is a type of community ordination procedure in 

which sampling units are arranged in relation to one 

or more coordinate axes in a way that their relative 

positions to the axes and to one another provide the 

maximum information about their ecological similarities (Ludwig and Reynolds, 1988). The PCA often is 

used to determine which biotic or abiotic variables 

explain the greatest variability between sites, populations of organisms, or individual organisms. Prior to 

using the data in any multivariate statistical analyses, 
8 Influence of Stream Habitat and Land Use on Benthic Macroinvertebrate Indicators of Stream Quality of Selected Above-Tidal

Streams in the Houston-Galveston Area Council Service Area, Texas, 1997–98 

all non-proportional stream-habitat variables were logtransformed as log 10 (x + 1) and proportional land-use 

variables were arcsine transformed (arcsin of the square 

root of the proportion) to reduce the heteroscedasticity 

(or non-normality) of the data (Zar, 1984). All transformed variables were tested for normality using a 

Komolgorov-Smirnov single sample test. A correlation 

matrix was used as the input matrix to extract principal 

components followed by a varimax rotation procedure 

to maximize the variance of factor loadings on each of 

the principal components (STATISTICA, 1999). The 

two-sample student’s t-test is a parametric statistical test 

to determine if two means are the same (Zar, 1984). A 

multiple regression is an expanded version of a simple 

linear regression in which the dependent variable (Yi

) is 

influenced by multiple independent variables (Xi...n). 

Multiple regression often is used in ecological investigations to predict a value for a dependent biotic variable 

using one or more abiotic independent variables. 

INFLUENCE OF STREAM HABITAT AND 

LAND USE ON BENTHIC MACROINVERTEBRATE INDICATORS OF BIOLOGICAL 

INTEGRITY

Stream-habitat and land-use variables that 

explain the greatest variation between the reaches 

were determined and used to select seven reference 

reaches. Stream-habitat and biological integrity scores 

were computed for each of the 31 reaches. A multipleregression model was developed to predict the biological integrity of a site using several, easily determined, 

variables. Because land use in the study area ranges 

from older urban in metropolitan Houston to rural 

forest in the national forests north of Houston, the 

stream-habitat and land-use variables selected were 

highly disparate.

Relation Between Stream Habitat and Land 

Use

A multivariate statistical procedure, PCA was 

used as a “variable reduction” technique to determine 

those stream-habitat and land-use variables that are 

strongly intercorrelated and those variables that explain 

the greatest variation between reaches. Variables with 

PCA factor loadings greater than or equal to 0.7 were 

considered for further analysis. The first PCA indicated 

that among the stream-habitat variables, reach structural 

index, RCE maximum, median bank height/width ratio, 

median high-bank width, median bank height, and 

median wetted channel width all had factor loadings 

greater than 0.7 on one or more of the first three principal components (table 4). The larger the factor loading 

for a given variable, the more among-reach variation 

that variable explains. The first three principal components accounted for 74.1 percent of the variation 

between reaches. Median bank height/width ratio, 

median high-bank width, median bank height, and 

median bank slope were all significantly intercorrelated. Because of problems encountered selecting highbank locations during the reach surveys, these four variables were not used in any additional analyses.

A second PCA was done on the land-use 

variables—urban, agricultural, rangeland, forest, 

wetland, and barren—and population density (number 

of people per square mile). The first three principal 

components accounted for 72.2 percent of the variation 

between reaches (table 5). Percent agricultural, forest, 

and urban land uses and population density in the 

Table 3. Benthic macroinvertebrate metrics determined for each stream reach

[EPT, Ephemeroptera-Plecoptera-Trichoptera]

Numbers of taxa Percentages Indices

Number of taxa Percent EPT taxa EPT taxa richness

Number of filterers Percent Chironomidae Shannon-Weiner diversity index

Number of gatherers Percent Ephemeroptera Hilsenhoff’s biotic index

Number of predators Percent Oligochaeta Margelef’s richness index

Number of scrapers Percent Plecoptera Pielou’s evenness index

Number of shredders Percent filterers Simpson’s heterogeneity index

Percent gatherers

Percent predators

Percent scrapers

Percent shredders
INFLUENCE OF STREAM HABITAT AND LAND USE 9

INFLUENCE OF STREAM HABITAT AND LAND USE

drainage area above each reach all had loadings greater 

than 0.7 on one of the first two principal components. 

Percent rangeland and wetland only slightly exceeded a 

0.7 loading on the third principal component. Rangeland is generally a small part of the land use in the drainage area above each reach and often is difficult to 

separate from agricultural or other cultivation land uses. 

In the low-gradient coastal plains of the study area, the 

majority of wetlands in the drainage area above each 

reach are standing water bodies, such as oxbow lakes, 

that are separated from the fluvial stream corridors for 

much of the year. Therefore, percent rangeland and wetland were not included in subsequent data analyses.

Reaches were grouped by their dominant land 

use, and comparisons were made between the PCAselected stream-habitat and land-use variables (figs. 2 

and 3). Urban and agricultural land uses were combined 

for each reach to compare anthropogenic with nonanthropogenic land-use categories. Median reach structural index was significantly larger for those abovereach drainage areas that were dominated by forest land 

use (median = 157.6, t = -3.2, p <0.05). Median RCE 

maximum also was significantly larger for forest land 

use than for urban-agricultural land use (median = 78.3, 

t = -3.51, p <0.05). The larger medians for the drainage 

areas dominated by forest are an indication of the 

greater structural complexity in the channel, greater 

bank stability, and high integrity of the riparian zone. In 

general, the more forested the drainage area, the less 

disturbed the riparian zone, and the greater the source of 

structural material such as leaves, limbs, and tree logs 

that become habitat for aquatic organisms.

The number of people per square mile in the 

drainage area above each reach was significantly 

negatively correlated (fig. 3) with reach structural index 

(r = -0.37, p <0.05) and RCE maximum (r = -0.63, 

p <0.05). Reaches in drainage areas with more people 

per square mile tend to lack in-channel structural complexity, have less stable banks, be more channelized, 

and lack channel meandering. Reaches on White Oak 

Table 4. Factor loadings from principal components analysis (PCA) greater than 0.7 for stream-habitat variables 

and proportion of variation explained by each principal component 

Table 5. Factor loadings from principal components analysis (PCA) greater than 0.7 for land-use and population 

variables and proportion of variation explained by each principal component 

Stream-habitat variable First principal 

component

Second principal 

component

Third principal 

component

Reach structural index –0.895

RCE maximum –.770

Median bank height/width ratio 0.943

Median high-bank width –0.917

Median bank height –.785

Median wetted channel width –.741

Proportion of variation explained .240 .283 .218

Proportion of total variation explained .741

Land-use and population variable First principal 

component

Second principal 

component

Third principal 

component

Percent agricultural 0.929

Percent forest –.914

Percent urban 0.869

Population density .846

Percent rangeland –0.725

Percent wetland .719

Proportion of variation explained .316 .258 .148

Proportion of total variation explained .722
10 Influence of Stream Habitat and Land Use on Benthic Macroinvertebrate Indicators of Stream Quality of Selected Above-Tidal

Streams in the Houston-Galveston Area Council Service Area, Texas, 1997–98 

Bayou (WOAK1394) and Greens Bayou (GREN0034) 

at Houston are typical of these types of reaches. 

Relation Between Benthic Aquatic Insects and 

Land Use

Non-insect benthic macroinvertebrates are not 

included in any analyses or discussions in this section of 

the report. 

A PCA was done using the transformed benthic 

aquatic insect variables to select those variables that 

explain the greatest variation between the 31 reaches 

and to determine which variables are most intercorrelated. These variables—percent EphemeropteraPlecoptera-Trichoptera (EPT) taxa, percent filterers, 

Hilsenhoff’s biotic index, number of taxa, ShannonWiener diversity index, Margalef's richness index, 

Simpson’s heterogeneity index, percent shredders, 

and percent Oligochaeta—all had factor loadings 

greater than 0.7 on at least one of the first four principal 

components (table 6). The first four principal components accounted for 82.2 percent of the variation 

between reaches. Because the proportional variables, 

Ephemeroptera, Plecoptera, and Trichoptera, were all 

highly positively intercorrelated, percent EPT taxa (sum 

of these three proportional variables) was used in the 

PCA. Percent filterers and percent shredders were not 

used for further analysis because these variables are 

trophic classifications comprised of many of the same 

taxa that make up the variable, percent EPT. Therefore, 

use of these variables and EPT would be somewhat 

redundant. Percent Chironomidae did not have a loading greater than 0.7 after PCA analysis. However, 

because Chironomidae was the dominant group at many 

sites, both in number of taxa and in number of individuals, this variable was selected for further analysis. The 

Shannon-Wiener diversity and Margalef’s richness indices were not used in additional analyses because 

of sample-size bias and other concerns (Ludwig and 

Reynolds, 1988). Percent EPT taxa, Hilsenhoff’s biotic 

DOMINANT LAND USE

-50

0

50

100

150

200

250

300

350

400

URBAN-AGRICULTURAL FOREST

REACH STRUCTURAL INDEX

DOMINANT LAND USE

0

10

20

30

40

50

60

70

80

90

100

110

URBAN-AGRICULTURAL FOREST

RCE MAXIMUM

EXPLANATION

Maximun

75th percentile

Median (50th percentile)

25th percentile

Minimum

Figure 2. Distribution of selected stream-habitat variables for reaches grouped by dominant land use.
INFLUENCE OF STREAM HABITAT AND LAND USE 11

Figure 3. Relation between population density in above-reach drainage areas and selected stream-habitat 

variables.

(NUMBER OF PEOPLE PER SQUARE MILE)

RCE MAXIMUM

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

-200 200 600 1,000 1,400 1,800 2,200 2,600

r = -0.63, p <0.05

95-percent confidence band

B0015

B0011

B0005

B3600

B4000

C0017

C0020

C7500

C1324

C1329

C8800

E0016

E1237 E0200

G0034

L0012

L1367

L0003

L1280

P0040

S0022

S0023

S0024

S0027

S8500

W0026

W0010

W8000

W8090

W8325

W1394

POPULATION DENSITY

(NUMBER OF PEOPLE PER SQUARE MILE)

REACH STRUCTURAL INDEX

B0015

B0011

B0005

B3600

B4000

C0017

C0020

C7500

C1324

C1329

C8800

E0016

E0200

E1237

G0034

L0012

L1367

L0003

L1280

P0040

S0022

S0023

S0024

S0027

S8500

W0026

W0010

W8000

W8090

W8325

W1394

-50

0

50

100

150

200

250

300

350

400

-200 200 600 1,000 1,400 1,800 2,200 2,600

r = -0.37, p <0.05

95-percent confidence band

POPULATION DENSITY

Note: Number shown is first letter 

 and the four numbers of 

 HGAC identification number

Table 6. Factor loadings from principal components analysis (PCA) greater than 0.7 for benthic aquatic insect 

variables and proportion of variation explained by each principal component 

[EPT, Ephemeroptera-Plecoptera-Trichoptera]

Benthic aquatic insect variable First principal 

component

Second principal 

component

Third principal 

component

Fourth principal 

component

Percent EPT taxa –0.904

Percent filterers .722

Hilsenhoff’s biotic index .937

Number of taxa 0.874

Shannon-Weiner diversity index .968

Margelef’s richness index .934

Simpson’s heterogeneity index .856

Percent shredders 0.858

Percent Oligochaeta –0.953

Proportion of variation explained .263 .293 .126 .140

Proportion of total variation explained .822
12 Influence of Stream Habitat and Land Use on Benthic Macroinvertebrate Indicators of Stream Quality of Selected Above-Tidal

Streams in the Houston-Galveston Area Council Service Area, Texas, 1997–98 

index, number of taxa, Simpson’s heterogeneity index, 

and percent Oligochaeta and Chironomidae were 

selected for further analysis. 

The reaches grouped by dominant land use were 

compared for the six selected variables (fig. 4). Percent 

EPT taxa, number of taxa, and Simpson’s heterogeneity 

DOMINANT LAND USE

PERCENT EPT TAXA

-10

10

30

50

70

90

110

URBAN-AGRICULTURAL FOREST

DOMINANT LAND USE

SIMPSON'S HETEROGENEITY INDEX

0.60

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

URBAN-AGRICULTURAL FOREST

DOMINANT LAND USE

NUMBER OF TAXA

10

20

30

40

50

60

70

URBAN-AGRICULTURAL FOREST

DOMINANT LAND USE

HILSENHOFF'S BIOTIC INDEX

1.5

2.5

3.5

4.5

5.5

6.5

7.5

8.5

URBAN-AGRICULTURAL FOREST

EXPLANATION

Maximun

75th percentile

Median (50th percentile)

25th percentile

Minimum

Figure 4. Distribution of selected benthic aquatic insect variables for reaches grouped by dominant land use.
INFLUENCE OF STREAM HABITAT AND LAND USE 13

index all had smaller medians for drainage areas dominated by urban-agricultural land uses than for drainage 

areas dominated by forest land use. However, only 

number of taxa (median = 40.9, t = -5.63, p <0.05) and 

Simpson’s index (median = 0.88, t = -2.92, p <0.05) had 

medians that were significantly larger for drainage areas 

dominated by forest land use. The medians for percent 

Oligochaeta and Chironomidae were larger in urbanagricultural drainage areas, but not significantly larger. 

The median Hilsenhoff’s index was significantly larger 

for drainage areas dominated by urban-agricultural land 

use (median = 5.09, t = 2.48, p <0.05). The Hilsenhoff’s 

index is a community metric that incorporates characteristics of aquatic insect taxonomic diversity with tolerance characteristics; the larger the index, the more 

affected the community (Hilsenhoff, 1987). 

The number of people per square mile was significantly negatively correlated with percent EPT 

taxa (r = -0.45, p <0.05) and number of taxa (r = -0.56, 

p <0.05) (fig. 5). Greater percent EPT taxa and number 

of taxa were associated with those reaches and associated drainage areas that are well forested, have more 

stable riparian zones, and have more in-channel structures such as woody snags and undercut banks. The 

number of people per square mile in the drainage area 

above each reach was significantly positively correlated 

with percent Chironomidae (r = 0.58, p <0.05). Larger 

percentages of chironomids are often associated with 

large river reaches, more lentic or “lake-like” conditions, or in water bodies that have small dissolved oxygen concentrations (Ward, 1992). Comparison of the 

number of people per square mile in the reach drainage 

area with Hilsenhoff’s index, Simpson’s index, and percent Oligochaeta showed no significant correlations.

Selection of Reference Reaches

The six variables that explained the greatest 

variability between reaches as determined by the PCA 

were used in the selection of reference reaches: two 

stream-habitat variables—reach structural index and 

RCE maximum—and four benthic aquatic insect variables—percent EPT taxa, number of taxa, Hilsenhoff’s 

biotic index, and percent Chironomidae. In this report, 

a reference reach is defined as a reach that has high 

stream-habitat integrity as measured by the two streamhabitat variables selected or high biological integrity as 

measured by the status of the aquatic insect taxa. 

Several screening criteria were used to develop a 

pool of potential reference reaches. Reaches with structural index or RCE maximum (fig. 6) or with percent 

EPT taxa or number of taxa (fig. 7) greater than or 

equal to the 90th percentile for these variables were 

selected as potential reference reaches. Reaches with 

percent Chironomidae or Hilsenhoff’s index (fig. 8) 

less than or equal to the 10th percentile for this variable 

also were selected as potential reaches. Sixteen reaches 

met the criteria: BIGC0015, BRAN0011, BUFF0005, 

CANY0017, CANY0020, CYPR1324, CYPR8800, 

EFSJ0016, EFSJ0200, EFSJ1237, LAKE0012, 

DOMINANT LAND USE

PERCENT OLIGOCHAETA

-10

0

10

20

30

40

URBAN-AGRICULTURAL FOREST

DOMINANT LAND USE

PERCENT CHIRONOMIDAE

-10

10

30

50

70

90

110

URBAN-AGRICULTURAL FOREST

Figure 4.—Continued.
14 Influence of Stream Habitat and Land Use on Benthic Macroinvertebrate Indicators of Stream Quality of Selected Above-Tidal

Streams in the Houston-Galveston Area Council Service Area, Texas, 1997–98 

NUMBER OF TAXA

L0003

B0005

W0010

L0012

W0026

S0027

G0034 C1324

C1329

W1394 B3600

B4000

C7500

W8325

C8800

B0011

B0015

E0016

C0017

C0020

S0022

S0023

S0024

P0040

E0200

E1237

L1280

L1367

W8000

S8500 W8090

0

20

40

60

80

-200 200 600 1,000 1,400 1,800 2,200 2,600

r = -0.56, p <0.05

PERCENT EPT TAXA

L0003

B0005

W0010

L0012

W0026

S0027

G0034

C1324

C1329

W1394

B3600

B4000

C7500

W8325

C8800

B0011

B0015

E0016

C0017

C0020

S0022

S0023

S0024

P0040

E0200

E1237

L1280

L1367

W8000

W8090

S8500

0

20

40

60

80

100

-200 200 600 1,000 1,400 1,800 2,200 2,600

r = -0.45, p <0.05

-10

Note: Number shown is first letter 

 and the four numbers of 

 H–GAC identification number

POPULATION DENSITY

(NUMBER OF PEOPLE PER SQUARE MILE)

PERCENT CHIRONOMIDAE

L0003

B0005

W0010

L0012

W0026

S0027

G0034

C1329 C1324

W1394

B3600 B4000

C7500

W8325

C8800

B0015 B0011

E0016

C0017

C0020

S0022

S0023 S0024

P0040

E0200

E1237

L1280

L1367

W8000

W8090

S8500

0

20

40

60

80

100

-200 200 600 1,000 1,400 1,800 2,200 2,600

r = 0.58, p <0.05

Figure 5. Relation between population density in above-reach drainage areas and selected benthic aquatic insect 

variables.
INFLUENCE OF STREAM HABITAT AND LAND USE 15

LAKE1367, LUCE1280, SPRI0027, WFSJ8000, and 

WFSJ8090.

The pool of reaches selected, after screening with 

the stream habitat and aquatic insect variables, were further screened using the percentage of drainage area 

above each reach that is forest land use and the number 

of wastewater outfalls in the drainage area. The greater 

Houston metropolitan area has a relatively large number 

of wastewater discharges partly because of the zoning 

statutes in the area (Todd Running, Houston-Galveston 

Area Council, personal commun., 1999). Those reaches 

with a drainage area that was greater than or equal to 

80-percent forest land use and that had five or fewer 

wastewater outfalls were selected as reference reaches. 

This resulted in six reaches: BIGC0015, BRAN0011, 

EFSJ0016, EFSJ0200, EFSJ1237, and LUCE1280. The 

reach CANY0017 is 61-percent forest land use with five 

wastewater outfalls in its drainage area. Because of its 

location and number of taxa, CANY0017 was selected 

as the seventh reference reach.

Stream-Habitat and Biological Integrity Scores

Stream-habitat and biological integrity scores 

were computed for each of the 31 reaches. The 

90th percentile

75th percentile

50th percentile

25th percentile

10th percentile

90th percentile

75th percentile

50th percentile

25th percentile

10th percentile

RCE MAXIMUM

B0015

B0011

B0005

B3600

B4000

C0017

C0020

C7500

C1324

C1329 E0016

E0200

E1237

G0034

L0012

L1367

L0003

L1280 P0040

S0022

S0023

S0024

S0027

S8500

W0026

W0010

W8000

W8090

W8325

W1394

20

28

36

44

52

60

68

76

84

92

100

108

2

4

5

1

STREAM-HABITAT INTEGRITY SCORE

3

6

REACH STRUCTURAL INDEX

B0015

B0011

B0005

B3600

B4000

C0017

C0020

C7500

C1324

C1329

C8800

E0016

E0200

E1237

G0034

L0012

L1367

L0003

L1280

P0040

S0022

S0023

S0024

S0027

S8500

W0026

W0010

W8000

W8090

W8325

W1394

-50

0

50

100

150

200

250

300

350

400

1

2

3

4

5

6

STREAM-HABITAT INTEGRITY SCORE

Note: Number shown is first letter 

 and the four numbers of 

 H–GAC identification number

C8800

Figure 6. Reach structural index and RCE maximum for selected reaches classified by percentile and streamhabitat integrity score.
16 Influence of Stream Habitat and Land Use on Benthic Macroinvertebrate Indicators of Stream Quality of Selected Above-Tidal

Streams in the Houston-Galveston Area Council Service Area, Texas, 1997–98 

90th percentile

75th percentile

50th percentile

25th percentile

10th percentile

90th percentile

75th percentile

50th percentile

25th percentile

10th percentile

B0015

B0011

B0005

B3600

B4000

C0017

C0020

C7500 C1324

C1329

C8800

E0016

E0200

E1237

G0034

L0012

L1367

L0003

L1280

P0040

S0022

S0023

S0024

S0027

S8500

W0026

W0010

W8000

W8090

W8325

W1394

-8

0

8

16

24

32

40

48

56

64

72

80

88

96

1

2

3

4

5

6

BIOLOGICAL INTEGRITY SCORE

NUMBER OF TAXA

B0015

B0011

B0005

B3600

B4000

C0017

C0020

C7500

C1324

C1329

C8800

E0016

E0200

E1237

G0034

L0012

L1367

L0003

L1280

P0040

S0022

S0023

S0024

S0027

S8500

W0026

W0010

W8000

W8090

W8325

W1394

10

20

30

40

50

60

70

6

5

4

3

2

1

BIOLOGICAL INTEGRITY SCORE

Note: Number shown is first letter 

 and the four numbers of 

 H–GAC identification number

PERCENT EPT TAXA

PCA-selected stream-habitat variables reach structural 

index and RCE maximum were used to compute the 

stream-habitat integrity score; the aquatic insect variables percent EPT taxa, number of taxa, Hilsenhoff’s 

biotic index, and percent Chironomidae were used to 

compute the biological integrity score. Scores for each 

variable were assigned as follows: Scores of 6, 5, and 4 

were assigned to the variables reach structural index, 

RCE maximum, percent EPT taxa, and number of taxa 

that were greater than or equal to the 90th, 75th, or 50th 

percentiles, respectively (figs. 6 and 7). Scores of 3, 2, 

and 1 were assigned to those same variables that 

were between the 50th and 25th percentiles and less 

than or equal to the 25th or 10th percentiles, respectively (figs. 6 and 7). Thus, the greater the percentile, 

the higher the integrity score for these variables. The 

scoring was reversed for the variables Hilsenhoff’s 

biotic index and percent Chironomidae, with greater 

percentiles assigned lower integrity scores (fig. 8).

The integrity scores for the two stream-habitat 

and four biological variables were summed separately 

(table 7). East Fork San Jacinto River on FM 2025 

Figure 7. Percent EPT taxa and number of taxa for selected reaches classified by percentile and biological 

integrity score.
INFLUENCE OF STREAM HABITAT AND LAND USE 17

(EFSJ1237) and Luce Bayou above Lake Houston near 

Huffman (LUCE1280) each had the largest streamhabitat integrity score of 11, and White Oak Bayou at 

Bingle Road (WOAK1394) had the smallest score of 1. 

West Fork San Jacinto River above Lake Houston near 

Porter (WFSJ8090) had the largest biological integrity 

score of 22, and Buffalo Bayou at West Belt Drive 

(BUFF3600), Buffalo Bayou at Houston (BUFF4000), 

and Langham Creek at Patterson Road (LANG0003) 

each had the smallest score of 5. The stream-habitat and 

biological integrity scores (fig. 9) were significantly 

positively correlated (r = 0.58, p = 0.0006).

Median stream-habitat and biological integrity 

scores were computed for the seven reference reaches 

for comparison with all selected reaches (fig. 10). 

The median stream-habitat integrity score for the 

reference reaches is 10. All reaches with stream-habitat 

integrity scores greater than the reference-reaches 

median have relatively well-forested, non-urbanized 

drainage areas. Smaller stream-habitat integrity scores 

10th percentile

90th percentile

90th percentile

10th percentile

75th percentile

50th percentile

25th percentile

25th percentile

50th percentile

75th percentile

HILSENHOFF'S BIOTIC INDEX

B0015

B0011

B0005

B3600

B4000

C0017

C0020

C7500

C1324

C1329

C8800

E0016 E0200

E1237

G0034

L0012 L1367

L0003

L1280

P0040

S0022

S0023

S0024

S0027 S8500

W0026

W0010

W8000

W8090

W8325

W1394

2.0

3.0

4.0

5.0

6.0

7.0

8.0

1

2

3

4

5

6

BIOLOGICAL INTEGRITY SCORE

PERCENT CHIRONOMIDAE

B0015

B0011

B0005

B3600

B4000

C0017

C0020

C7500

C1324 C1329

C8800

E0016

E0200

E1237

G0034

L0012

L1367

L0003

L1280

P0040

S0022

S0023

S0024

S0027

S8500

W0026

W0010

W8000

W8090

W8325

W1394

0

10

20

30

40

50

60

70

80

90

100

1

2

3

4

5

6

BIOLOGICAL INTEGRITY SCORE

Note: Number shown is first letter 

 and the four numbers of 

 H–GAC identification number

Figure 8. Hilsenhoff’s biotic index and percent Chironomidae for selected reaches classified by percentile and 

biological integrity score.
18 Influence of Stream Habitat and Land Use on Benthic Macroinvertebrate Indicators of Stream Quality of Selected Above-Tidal

Streams in the Houston-Galveston Area Council Service Area, Texas, 1997–98 

Table 7. Stream-habitat and biological integrity scores for selected reaches 

[H–GAC, Houston-Galveston Area Council; --, not applicable; FM, farm road]

1

 Threatened or impaired water in Texas (Texas Natural Resource Conservation Commission, 1999).

Site (reach name)

H–GAC

identification

no.

(fig. 1)

 Integrity score 303(d)

listed

segment1

Stream

habitat Biological

Big Creek in Big Creek scenic area/Sam Houston National Forest BIGC0015 8 15 --

Branch Creek at FM 1375 bridge BRAN0011 7 17 --

Buffalo Bayou at Eldridge Pkwy. BUFF0005 10 13 --

Buffalo Bayou at West Belt Dr. BUFF3600 7 5 --

Buffalo Bayou at Houston BUFF4000 2 5 --

Caney Creek near Willis CANY0017 10 15 --

Caney Creek near New Caney CANY0020 10 19 --

Cedar Bayou near Crosby CEDR7500 6 14 --

Cypress Creek west of I–45 and north of FM 1960 at Cypresswood CYPR1324 7 17 yes

Cypress Creek at Kuykendahl Rd. bridge CYPR1329 4 15 yes

Cypress Creek at Grant Rd. CYPR8800 4 10 yes

East Fork San Jacinto River at FM 945 EFSJ0016 7 19 --

East Fork San Jacinto River near New Caney EFSJ0200 10 17 --

East Fork San Jacinto River on FM 2025 EFSJ1237 11 18 --

Greens Bayou at Mt. Houston Pkwy. GREN0034 2 8 yes

Lake Creek at FM 149 LAKE0012 6 19 --

Lake Creek near Egypt LAKE1367 10 18 --

Langham Creek at Patterson Rd. LANG0003 5 5 --

Luce Bayou above Lake Houston near Huffman LUCE1280 11 19 --

Panther Creek at The Woodlands PANT0040 10 19 --

Spring Branch Creek at State 242/FM 2090 SPRB0022 3 12 --

Spring Creek at Riley Fuzzel SPRI0023 6 14 --

Spring Creek near Tomball SPRI0024 8 17 yes

Spring Creek on Robert Cemetery Rd. SPRI0027 10 15 yes

Spring Creek at Spring (I–45 bridge) SPRI8500 6 11 --

Walnut Creek near Magnolia WALN0026 7 17 --

West Fork San Jacinto River at State 30 WFSJ0010 5 10 --

West Fork San Jacinto River near Conroe at I–45 WFSJ8000 10 12 --

West Fork San Jacinto River above Lake Houston near Porter WFSJ8090 6 22 --

Willow Creek near Tomball WILL8325 5 8 --

White Oak Bayou at Bingle Rd. WOAK1394 1 10 yes

were typical of the more urbanized drainage areas such 

as Greens Bayou (GREN0034) and White Oak Bayou 

(WOAK1394). These small scores are consistent with 

reaches that have been channelized for flood control, 

which has greatly simplified the channel. However, 

Buffalo Bayou at Houston (BUFF4000) and Langham 

Creek at Patterson Road (LANG0003), which have 

drainage areas that are urbanized but not extensively 
INFLUENCE OF STREAM HABITAT AND LAND USE 19

channelized, also had relatively small stream-habitat 

integrity scores.

The median biological integrity score computed 

for the seven reference reaches is 17 (fig. 10). The 

larger the structural index of a reach, generally the 

larger the frequency of in-channel woody debris such 

as leaf-packs and woody snags. These types of structures provide an energy base and substrate that can support a benthic aquatic insect community dominated by 

EPT taxa. The EPT in the streams of southeastern 

Texas are dominated by Ephemeroptera (mayflies) and 

Trichoptera (caddisflies) taxa. Many of the urban 

reaches, such as Langham Creek at Patterson Road 

(LANG003), are more susceptible to increased rates of 

runoff during a rainfall event that reduce the number of 

stable structures in the channel. These reaches also have 

less riparian and drainage-area sources to supply the 

stream with coarse organic material such as woody 

snags and leaves. Therefore, a more depauperate (or less 

developed) EPT assemblage in these urban reaches is 

not surprising.

Seven reaches in this study (table 7) are included 

in the State of Texas list of threatened or impaired 

waters, the State 303(d) list (Texas Natural Resource 

Conservation Commission, 1999). These reaches are 

listed as not meeting applicable aquatic-life use 

designations. Included on the 303(d) list are three 

Cypress Creek reaches (CYPR1324, CYPR1329, and 

CYPR8800), one Greens Bayou reach (GREN0034), 

two Spring Creek reaches (SPRI0024 and SPRI0027), 

and one White Oak Bayou reach (WOAK1394). 

Cypress Creek and Spring Creek segments are listed 

for dissolved oxygen concentrations that are sometimes 

lower than the standard established to assure optimum 

conditions for aquatic life. Greens Bayou and White 

Oak Bayou are listed for exceedance of the applicable 

dissolved lead concentration established for the protection of aquatic life. The biological integrity scores for 

CYPR1324 and SPRI0024 equaled the median biological integrity reference-reaches score of 17; and the biological integrity scores for the other five 303(d) sites 

ranged from 8 for GREN0034 to 15 for CYPR1329 and 

SPRI0027. The habitat integrity score for SPRI0027 

equaled the median habitat integrity reference-reaches 

score of 10; and the habitat integrity scores for the other 

six 303(d) sites ranged from 1 for WOAK1394 to 7 for 

CYPR1324. 

The 303(d) listing process often is based solely on 

surrogates, such as dissolved oxygen and lead concentrations, in place of more direct aquatic life measures of 

community status. Studies that use direct measures of 

stream habitat and biological integrity compared to and 

collocated with the more traditional water-chemistry 

measures will help researchers, regulators, and water 

STREAM-HABITAT INTEGRITY SCORE

BIOLOGICAL INTEGRITY SCORE

2

6

10

14

18

22

26

2 4 6 8 10 12

r = .58, p = .0006

Note: Number shown is first letter 

 and the four numbers of 

 H–GAC identification number

B0011

B0015

B0005

B4000 B3600

C0017

C0020

C7500

C1324

C1329

C8800

E0016

E1237

G0034

L0012

E0200

L1367

L0003

P0040 L1280

S0022

S0023

S0024

S0027

S8500

W0026

W0010 W8000

W8090

W8325

W1394

Figure 9. Correlation of stream-habitat integrity score with biological integrity score for selected reaches.
20 Influence of Stream Habitat and Land Use on Benthic Macroinvertebrate Indicators of Stream Quality of Selected Above-Tidal

Streams in the Houston-Galveston Area Council Service Area, Texas, 1997–98 

managers by providing supplemental information that 

could help to support or refute the surrogate-based 

designations.

Multiple-Regression Model to Predict 

Biological Integrity

A multiple-regression model was developed to 

predict a biological integrity score for a reach on the 

basis of the input of several independent variables. 

The independent variables selected for the multipleregression model include percent forest land use in 

drainage area, number of people per square mile in the 

drainage area, and RCE maximum. These independent 

variables were selected because they can be obtained 

without field-intensive studies and can be used to predict the biological integrity of a stream reach without 

actually collecting and processing biological samples. 

The predicted biological integrity score can be compared to an actual score determined from biological 

samples collected from the reach, and the deviation of 

the actual score from the predicted or expected score 

can be used to interpret the degree of impairment to 

reach biota. However, an independent dataset of integrity scores from reaches outside the group of reaches 

used in this study is needed to test the validity of the 

model. Additional above-tidal reaches within the San 

Jacinto River Basin and possibly adjacent river basins 

such as the Trinity and Neches could be selected to test 

the model.

A statistically significant multiple regression 

(r = 0.69, F (3,27) = 8.04, p = 0.0006) was determined 

using percent forest land use, people per square mile, 

BIGC0015

BRAN0011

BUFF0005BUFF3600BUFF4000

CANY0017CANY0020

CEDR7500

CYPR1324CYPR1329CYPR8800

EFSJ0016EFSJ0200EFSJ1237

GREN0034

LAKE0012LAKE1367

LANG0003

LUCE1280

PANT0040

SPRB0022

SPRI0023SPRI0024SPRI0027SPRI8500

WALN0026

WFSJ0010

WFS8000

WFSJ8090

WILL8325

WOAK1394

0

2

4

6

8

10

12

14

16

18

20

22

24

Median score for reference sites (17)

BIOLOGICAL INTEGRITY SCORE

0

2

4

6

8

10

12

14

Median score for reference sites (10)

STREAM-HABITAT INTEGRITY SCORE

Figure 10. Stream-habitat and biological integrity scores compared to median integrity scores for reference sites.
SUMMARY 21

and RCE maximum for each reach as independent 

variables. The biological integrity score was used 

as the dependent variable. The multiple-regression 

equation is:

 Y = 5.73 + 0.065 + 6.32 – 0.002 

 (biolog- (RCE (percent (people 

 ical in- maxi- forest per square

 tegrity) mum) land use) mile)

SUMMARY

During 1997–98 the USGS, in cooperation with 

the H–GAC, collected stream-habitat and benthic macroinvertebrate data for 31 above-tidal sites (reaches) in 

the H–GAC service area near Houston, Texas. The 31 

reaches (30 in the San Jacinto River Basin and 1 in the 

adjacent Trinity River Basin) were screened from a pool 

of 56 reaches. Stream-habitat, land-use and population, 

and benthic aquatic insect metrics were determined for 

the 31 reaches.

A multivariate statistical procedure, principal 

components analysis (PCA), was used to determine the 

stream-habitat, land-use and population, and aquatic 

insect variables that are strongly intercorrelated and that 

explain the greatest variation between reaches. These 

analyses indicated that:

• The variables reach structural index and RCE 

explained a significant proportion of the betweenreach variability.

• Percent forest land use of the above-reach drainage 

area and population density (number of people 

per square mile) of the drainage area explained 

a significant proportion of between-reach 

variability.

• The aquatic insect variables percent EPT taxa, 

Hilsenhoff’s biotic index, number of taxa, 

Simpson’s heterogeneity index, and percent 

Oligochaeta and Chironomidae explained a significant proportion of between-reach variability.

Stream-habitat and biological integrity scores 

were computed for each of the 31 reaches. The PCAselected stream-habitat variables—reach structural 

index and RCE maximum—were used to compute the 

stream-habitat integrity score; the aquatic insect variables—percent EPT taxa, number of taxa, Hilsenhoff’s 

biotic index, and percent Chironomidae—were used to 

compute the biological integrity score. Comparison of 

these indices indicated:

• Reaches generally had larger stream-habitat integrity 

scores in drainage areas that were heavily forested and had fewer people per square mile.

• Larger biological integrity scores were significantly 

correlated with larger stream-habitat integrity 

scores; urban reaches generally had more simplified stream-habitat conditions and smaller biological integrity scores.

• Seven reaches, BIGC0015, BRAN0011, 

CANY0017, EFSJ0016, EFSJ0200, EFSJ1237, 

and LUCE1280, were selected as reference 

reaches on the basis of high stream-habitat 

integrity and high biological integrity. The 

reference-reaches median biological integrity 

score of 17 was equaled by one Cypress Creek 

reach and one Spring Creek reach that are on the 

State of Texas list of threatened or impaired 

waters (the State 303(d) list) for not meeting their 

aquatic life use designation. This indicates that 

direct measures of biological integrity could provide supplemental information to support or 

refute surrogate-based designations such as the 

State 303(d) list.

A statistically significant multiple-regression 

model was developed that uses percent forest land use, 

RCE maximum, and number of people per square mile 

as variables to predict the biological integrity score for 

a reach. Data for these independent variables can be 

obtained without field-intensive studies. The deviation 

of a score based on biological sampling from the predicted score can be used to interpret the degree of 

impairment to a reach’s biota. An independent dataset 

from reaches outside the group of reaches used in this 

study is needed to test the validity of the model.

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District Chief U.S. Geological Survey 8027 Exchange Dr.Austin, TX 78754–4733