This study conducts watershed analysis using biological and geo-spatial techniques. Incorporating landscape features with biological attributes has been shown to be an effective method of monitoring environmental quality within watersheds. In situ biomonitoring using the Asiatic Clam, Corbicula fluminea, habitat suitability, and water quality data were evaluated for their potential to describe ecological conditions in agricultural and urban areas within the Upper Trinity River watershed. These data were analyzed with GIS to identify effects of land use on ecological conditions. C. fluminea downstream of point source effluents was effective detecting in-stream toxicity. Ambient toxicity appears to have improved in the Trinity, although urban influences limit aspects of aquatic life. No association between habitat quality and land use was identified.

With the advent of national storm water regulations, municipalities with populations greater than 100,000 are required to obtain National Pollutant Discharge Elimination System Permits (NPDES) for storm water discharges. In addition to the sampling required for the permit process, the City of Fort Worth contracted with the University of North Texas' Institute of Applied Sciences to conduct acute toxicity testing using Pimephales prcmelas and Ceriodaphnia dubia on storm water samples received from the Dallas/Fort Worth Metroplex. A Toxicity Identification Evaluation (TIE) was performed on four samples that exhibited acute toxicity to C. dubia. High levels of metals as well as diazinon were some of the probable toxicants found.

A method was developed for extending a fine-scaled forest gap model to a watershed-scaled landscape, using the Eastern Cross Timbers ecoregion as a case study for the method. A topographic wetness index calculated from digital elevation data was used as a measure of hydrologic across the modeled landscape, and the gap model modified to have with a topographically-based hydrologic input parameter. The model was parameterized by terrain type units that were defined using combinations of USDA soil series and classes of the topographic wetness index. A number of issues regarding the sources, grid resolutions, and processing methods of the digital elevation data are addressed in this application of the topographic wetness index. Three different grid sizes, 5, 10, and 29 meter, from both LiDAR-derived and contour-derived elevation grids were used, and the grids were processed using both single-directional flow algorithm and bi-directional flow algorithm. The result of these different grids were compared and analyzed in context of their application in defining terrain types for the forest gap model. Refinements were made in the timescale of gap model’s weather model, converting it into a daily weather generator, in order to incorporate the effects of the new topographic/hydrologic input parameter. The precipitation …