Location: Water Management and Systems Research
Project Number: 3012-13660-009-08-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 15, 2016
End Date: Sep 14, 2019
(1) Maintain and enhance a library of Java-based science modules for continued development of the Agricultural Ecosystem Services (AgES) watershed scale model. (2) Develop and maintain a hybrid simulation-optimization framework that uses AgES and multi-objective evolutionary algorithms (MOEA) for assessing synergies and tradeoffs between agricultural production and ecosystem services over a range of spatial scales. (3) Continue development and implementation of AgEs auxiliary tools for land unit delineation, parameterization/calibration, sensitivity/uncertainty analysis, and spatial-temporal output visualization. (4) Continue development and evaluation of web-based data provisioning capabilities for soil, land use/cover, and DEM data with linkage to AgES model input files. (5) Enhance and help maintain software applications for deploying AgES to a cloud infrastructure to enable scalable model applications to large data sets.
The AgES model currently has essential core Java-based modules taken from the WEPS, WEPP, RZWQM2, SWAT and J2K-SN models. These modules will be further verified and new modules added (e.g., infiltration, water table tracking, conservation effects, and crop growth) to further improve AgES robustness and applicability. Existing software applications for data provisioning and cloud computing will be augmented as needed during this process. ARS scientists will evaluate the AgES model with experimental data from Colorado and Midwest watersheds for water quantity and quality outcomes and tradeoffs between agricultural production and ecosystem services. A newly developed hybrid simulation-optimization framework that uses AgES and multi-objective evolutionary algorithms (MOEA) will be used to facilitate the evaluation process. Additional tools developed by ARS scientists for land unit delineation, parameterization, sensitivity/uncertainty analysis, output visualization, and scaling will also be fully implemented. The final package will be delivered to customers and stakeholders, i.e., water conservancy districts, county conservation districts, university faculty, international research collaborators, and other researchers and educators conducting research to improve environmental models and ecosystem service assessment.