Development and application of the spatially explicit load enrichment calculation tool (select) to determine potential E. coli loads in watersheds



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According to the USEPA National Section 303(d) List Fact Sheet, bacterial pathogens are the leading cause of water quality impairments in Texas. The automated Spatially Explicit Load Enrichment Calculation Tool (SELECT) uses spatially variable factors such as land use, soil condition, and distance to streams to characterize pathogen sources across a watershed. The results support development of Total Maximum Daily Loads (TMDLs) where bacterial contamination is of concern. SELECT calculates potential E. coli loads by distributing the contributing source populations across suitable habitats, applying a fecal production rate, and then aggregating the potential load to the subwatersheds. SELECT provides a Graphical User Interface (GUI), developed in Visual Basic for Applications (VBA) within ArcGIS 9.X, where project parameters can be adjusted for various pollutant loading scenarios. A new approach for characterizing E. coli loads resulting from on-site wastewater treatment systems (OWTSs) was incorporated into the SELECT methodology. The pollutant connectivity factor (PCF) module was created to identify areas potentially contributing E. coli loads to waterbodies during runoff events by weighting the influence of potential loading, runoff potential, and travel distance. Simulation results indicate livestock and wildlife are potentially contributing large amounts of E. coli in the Lake Granbury Watershed in areas where these contributing sources are not currently monitored for E. coli. The bacterial water quality violations near Lake Granbury are most likely the result of malfunctioning OWTSs and pet waste in the runoff. The automated SELECT was verified by characterizing the potential E. coli loading in the Plum Creek Watershed and comparing to results from a prior study (Teague, 2007). The E. coli potential load for the watershed was lower than the previous study due to major differences in assumptions. Comparing the average ranked PCF estimated by physical properties of the watershed with the statistical clustering of watershed characteristics provided similar groupings. SELECT supports the need to evaluate each contributing source separately to effectively allocate site specific best management practices (BMPs). This approach can be used as a screening step for determining areas where detailed investigation is merited. SELECT in conjunction with PCF and clustering analysis can assist decision makers develop Watershed Protection Plans (WPPs) and determine TMDLs.