Shubham Jain, Raghavan Srinivasan, Thomas J Helton, Raghupathy Karthikeyan
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The DSS includes pre-determined watershed-specific inputs that can be readily adjusted within the interface based on user preference and stakeholder recommendations, obviating the necessity for expensive GIS tools and data extraction. To illustrate the applications of TXSELECT, we implemented it in the entire coverage area to identify the potential hotspots and source contributions for <i>Escherichia coli</i> at a regional scale. Median potential <i>E. coli</i> loads were significantly higher in subwatersheds not supporting recreation use. Overall, the large-scale application of SELECT has the potential to aid in prioritizing management measures in watersheds that are less frequently monitored but could have an elevated risk of impairment.</p>","PeriodicalId":15671,"journal":{"name":"Journal of Environmental Science and Health Part A-toxic\\/hazardous Substances & Environmental Engineering","volume":" ","pages":"550-561"},"PeriodicalIF":1.9000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"TXSELECT: a web-based decision support system for regional assessment of potential <i>E. coli</i> loads using a spatially explicit approach.\",\"authors\":\"Shubham Jain, Raghavan Srinivasan, Thomas J Helton, Raghupathy Karthikeyan\",\"doi\":\"10.1080/10934529.2024.2445953\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Bacterial source characterization and allocation are imperative to watershed planning and identifying best management practices. The Spatially Explicit Load Enrichment Calculation Tool (SELECT) has been extensively utilized in watershed protection plans to evaluate the potential bacteria loads and sources in impaired watersheds. However, collecting data, compiling inputs, and spatially mapping sources can be arduous, time-intensive, expensive, and iterative until potential bacteria loads are appropriately allocated to sources based on stakeholder recommendations. We developed a web-based decision support system (DSS), TXSELECT (https://tx.select.tamu.edu), providing a user-friendly interface to run the SELECT model on Texas watersheds. The DSS includes pre-determined watershed-specific inputs that can be readily adjusted within the interface based on user preference and stakeholder recommendations, obviating the necessity for expensive GIS tools and data extraction. To illustrate the applications of TXSELECT, we implemented it in the entire coverage area to identify the potential hotspots and source contributions for <i>Escherichia coli</i> at a regional scale. Median potential <i>E. coli</i> loads were significantly higher in subwatersheds not supporting recreation use. 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TXSELECT: a web-based decision support system for regional assessment of potential E. coli loads using a spatially explicit approach.
Bacterial source characterization and allocation are imperative to watershed planning and identifying best management practices. The Spatially Explicit Load Enrichment Calculation Tool (SELECT) has been extensively utilized in watershed protection plans to evaluate the potential bacteria loads and sources in impaired watersheds. However, collecting data, compiling inputs, and spatially mapping sources can be arduous, time-intensive, expensive, and iterative until potential bacteria loads are appropriately allocated to sources based on stakeholder recommendations. We developed a web-based decision support system (DSS), TXSELECT (https://tx.select.tamu.edu), providing a user-friendly interface to run the SELECT model on Texas watersheds. The DSS includes pre-determined watershed-specific inputs that can be readily adjusted within the interface based on user preference and stakeholder recommendations, obviating the necessity for expensive GIS tools and data extraction. To illustrate the applications of TXSELECT, we implemented it in the entire coverage area to identify the potential hotspots and source contributions for Escherichia coli at a regional scale. Median potential E. coli loads were significantly higher in subwatersheds not supporting recreation use. Overall, the large-scale application of SELECT has the potential to aid in prioritizing management measures in watersheds that are less frequently monitored but could have an elevated risk of impairment.
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