Posters and Spotlights
PyAGNPS: A Python Toolbox for Watershed Modeling with AnnAGNPS
Start Date
30-4-2025 11:30 AM
Document Type
Event
Description
Poster Presenter: Luc Rébillout
Research Team: Luc Rébillout, Yavuz Ozeren, Mohammad Al-Hamdan, & Ronald Bingner
Abstract: The National Center for Computational Hydroscience and Engineering (NCCHE) hasdeveloped the Agricultural Integrated Management System (AIMS) to provide aweb-based, user-friendly platform for watershed modeling with automated datapreparation for the continental United States (CONUS). For watershed simulations,AIMS utilizes Annualized Agricultural Non-Point Source model (AnnAGNPS) ofUSDA-ARS. The Python toolbox, pyAGNPS was developed to aggregate and processdata from diverse sources and to facilitate input data preparation for AnnAGNPS.pyAGNPS automatically downloads digital elevation models (DEMs) and usesTopAGNPS to delineate and generate the input les for AnnAGNPS. The toolboxautomatically aggregates land-use, land-cover, and soil data to each AnnAGNPScell (unit catchment). It also processes climate data from various sources such asNLDAS-2, CMIP5 and CMIP6.pyAGNPS has successfully been implemented to delineate the entire CONUS at a30 m resolution, populating a PostgreSQL database with the datasets necessary forAnnAGNPS runs. Within the framework of AIMS, pyAGNPS uses this database toprepare the 'ready-to-run' AnnAGNPS input les for any sub-watershed withinCONUS, streamlining the traditionally cumbersome input assembly process. Bysimplifying the input le assembly process for AnnAGNPS simulations, pyAGNPSsignicantly enhances the eciency of watershed modeling.
Relational Format
poster
Recommended Citation
Rébillout, Luc, "PyAGNPS: A Python Toolbox for Watershed Modeling with AnnAGNPS" (2025). Showcase of Research and Scholarly Activity. 48.
https://egrove.olemiss.edu/ored_showcase/2025/posters/48
PyAGNPS: A Python Toolbox for Watershed Modeling with AnnAGNPS
Poster Presenter: Luc Rébillout
Research Team: Luc Rébillout, Yavuz Ozeren, Mohammad Al-Hamdan, & Ronald Bingner
Abstract: The National Center for Computational Hydroscience and Engineering (NCCHE) hasdeveloped the Agricultural Integrated Management System (AIMS) to provide aweb-based, user-friendly platform for watershed modeling with automated datapreparation for the continental United States (CONUS). For watershed simulations,AIMS utilizes Annualized Agricultural Non-Point Source model (AnnAGNPS) ofUSDA-ARS. The Python toolbox, pyAGNPS was developed to aggregate and processdata from diverse sources and to facilitate input data preparation for AnnAGNPS.pyAGNPS automatically downloads digital elevation models (DEMs) and usesTopAGNPS to delineate and generate the input les for AnnAGNPS. The toolboxautomatically aggregates land-use, land-cover, and soil data to each AnnAGNPScell (unit catchment). It also processes climate data from various sources such asNLDAS-2, CMIP5 and CMIP6.pyAGNPS has successfully been implemented to delineate the entire CONUS at a30 m resolution, populating a PostgreSQL database with the datasets necessary forAnnAGNPS runs. Within the framework of AIMS, pyAGNPS uses this database toprepare the 'ready-to-run' AnnAGNPS input les for any sub-watershed withinCONUS, streamlining the traditionally cumbersome input assembly process. Bysimplifying the input le assembly process for AnnAGNPS simulations, pyAGNPSsignicantly enhances the eciency of watershed modeling.