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Development of a Web-Based Agricultural Integrated Management System (AIMS) for Watershed Management: A case study for the Johnson Creek-Long Creek Watershed in Panola County, Mississippi
Proceedings of the 2020 Mississippi Water Resources Conference
Year: 2020 Authors: Pophet N., Ozeren Y., Bingner R., Yasarer L., Smith P., Ramalingam V., Yafei J.
The National Center for Computational Hydroscience and Engineering (NCCHE) and the USDA-ARS-National Sedimentation Laboratory have developed a web-based Agricultural Integrated Management System (AIMS) to provide a powerful watershed conservation management planning tool in easy to use technology. This technology provides modeling capabilities with automated data preparation from seamless geospatial data for use in evaluating runoff, sediment, and agro-pollutant loadings for any watershed in the U.S. via a Web-browser. The ultimate goal of AIMS is to provide capabilities such as (i) viewing and interacting with geospatial layers, (ii) acquiring information describing features from geospatial layers for a user-defined area, (iii) launching modeling tools for topographic landscape analysis (TopAGNPS) and agricultural watershed simulations (AnnAGNPS), and (iv) accessing various Decision Support tools to allow users to compare various simulated conservation planning scenarios. The beta version of AIMS is currently available and can be accessed via the address "aims.ncche.olemiss.edu." In order to evaluate AIMS for adequate input data preparation required for AnnAGNPS watershed simulations, a case study was performed on the Johnson Creek-Long Creek HUC 12 Watershed (155.85 km2) located in northwest Mississippi. The input parameters required for use with the AnnAGNPS model includes soil, climate, land use, and crop data, which can be automatically prepared through AIMS. Soil information was prepared by AIMS from the USDA-NRCS Soil Survey Geographic (SSURGO) Database. The climate generator-GEM6 was used to generate climate data. Land use and crop data were obtained from the USGS 2016 National Land Cover Database (NLCD) and the USDA 2018 Crop Data Layer (CDL), respectively. The performance of the AIMS system to adequately describe this watershed was evaluated by comparing the observed runoff at an in-stream measuring station with the AIMS-AnnAGNPS simulated results.