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.