Pi-VAT: A web-based visualization tool for decision support using spatially complex water quality model outputs

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dc.contributor.authorDeval, Chinmayen
dc.contributor.authorBrooks, Erin S.en
dc.contributor.authorDobre, Marianaen
dc.contributor.authorLew, Rogeren
dc.contributor.authorRobichaud, Peter R.en
dc.contributor.authorFowler, Amesen
dc.contributor.authorBoll, Janen
dc.contributor.authorEaston, Zachary M.en
dc.contributor.authorCollick, Amy S.en
dc.date.accessioned2023-05-31T13:29:09Zen
dc.date.available2023-05-31T13:29:09Zen
dc.date.issued2022-04en
dc.description.abstractEffective watershed management and protection of water resources from non-point source pollution require identification, prioritization, and targeting of pollutant source areas. Process-based hydrology and water quality models are powerful heuristic tools for land and water resources managers. However, because of their complexity, such models are often under-utilized as management prioritization and planning tools. In this paper, we present a prioritization, interactive visualization, and analysis tool (Pi-VAT) that is programmed to synthesize multi-scenario, multi-watershed outputs from process-based geospatial models. We demonstrate the utility of Pi VAT to examine simulated hydrologic, sediment, and water quality response at the hillslope/hydrologic response unit (HRU) scale. We apply Pi-VAT to output from multiple watersheds and for multiple management scenarios and treatments from two geospatial models for watershed management: Water Erosion Prediction Project (WEPP) and Soil & Water Assessment Tool (SWAT). Pi-VAT was developed using the Shiny web application framework for the R programming language. In a matter of minutes, Pi-VAT can synthesize overwhelming amounts of output from process-based models into information useful for land and water resources managers. We illustrate the use of Pi-VAT to interactively identify, quantify, and visualize areas that are most susceptible to disturbance under different scenarios and provide a synthesis approach based on land use, soil type, and slope steepness. This approach guides land and water resources managers in prioritizing the areas of the watershed that provide the maximum reduction in pollutant loads while treating the least amount of area. Pi-VAT provides a flexible reactive platform for the development of decision support tools based on process-based models intended for watershed management and research applications.en
dc.description.adminPublic domain – authored by a U.S. government employeeen
dc.description.notesThis work was supported by the AFRI program [grant no201667020-25320/project accession no. 1009827] from the USDA National Institute of Food and Agriculture.en
dc.description.sponsorshipAFRI program [1009827]; USDA National Institute of Food and Agricultureen
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1016/j.jhydrol.2022.127529en
dc.identifier.eissn1879-2707en
dc.identifier.issn0022-1694en
dc.identifier.urihttp://hdl.handle.net/10919/115266en
dc.identifier.volume607en
dc.language.isoenen
dc.publisherElsevieren
dc.rightsPublic Domain (U.S.)en
dc.rights.urihttp://creativecommons.org/publicdomain/mark/1.0/en
dc.subjectDecision-support toolsen
dc.subjectTargeted managementen
dc.subjectPrioritizationen
dc.subjectProcess-based modelsen
dc.subjectWEPPen
dc.subjectSWATen
dc.titlePi-VAT: A web-based visualization tool for decision support using spatially complex water quality model outputsen
dc.title.serialJournal of Hydrologyen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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