Development of a Web-Based Decision Support System for Watershed-Scale Agricultural Conservation Management in the United States

An automated Web-based decision support tool, Agricultural Integrated Management System (AIMS) is developed to evaluate the impacts of agricultural and channel conservation management practices within any watershed in the United States. AIMS offers a user-friendly Web-GIS framework, enabling convenient interaction with geospatial data layers, automated input data preparation for AnnAGNPS model and visualizing watershed simulation results on any device with internet access. AIMS uses the watershed-scale simulation tool of the USDA Agricultural Research Service (ARS), the Annualized Agricultural Non-Point Source Pollution (AnnAGNPS) model to estimate the runoff, sediment, nutrients, and pesticides that may originate from agricultural areas and impact water quality in rivers, streams, and other water bodies. Running the AnnAGNPS model requires various datasets including topographic, soil, land use and land cover, climate, management data. The topographic data consists of concentrated flows (reaches) and sub-catchments (cells) which are delineated for the entire United States using TopAGNPS, a topographic parameterization program for AnnAGNPS. Soil data is obtained from NRCS Soil Data Access service and processed to produce aggregated data for AnnAGNPS. Historical climate data is derived from the North American Land Data Assimilation System Phase 2 (NLDAS-2) obtained from Hydrology Data Rods. Where NLDAS-2 is unavailable or incomplete, the climate data is supplemented using Daily Surface Weather and Climatological Summaries (DAYMET). The land use data includes the spatial information about the land cover (such as crops) and the management data includes the agricultural operation (such as scheduling of tillage, planting, fertilization, harvesting etc.) performed in the region. The assimilation of the management data to AIMS is currently underway. This presentation summarizes the development of the AIMS framework, dataset preparation for the models, and displays the capabilities of AIMS.