A framework for automated and spatially-distributed modeling with the Agricultural Policy Environmental eXtender (APEX) model

• DOI: 10.1016/j.envsoft.2021.105147
• Publication Date: 2021-07-19T06:30:31Z
• Authors: Feng Pan; Qingyu Feng; Ryan McGehee; Bernard A. Engel; Dennis C. Flanagan; Jingqiu Chen
• Keywords: 2. Zero hunger; 13. Climate action; 0208 environmental biotechnology; 0207 environmental engineering; 02 engineering and technology; 15. Life on land; 6. Clean water

Abstract Agricultural Best Management Practices (BMPs) are popular approaches to reduce nonpoint source (NPS) pollutant losses. Hydrologic models that can simulate impacts of BMPs at the field-scale can help guide the selection of BMPs. Furthermore, high-performance computing techniques have significant potential for scaling spatial simulations and reducing model runtimes. In this study, a parallel modeling framework for the Agricultural Policy Environmental eXtender (APEX) model was developed for large-scale, high-resolution, spatially-distributed model simulations. It provides a tool for conducting BMP evaluations at field-scale with a distributed architecture and automatic model setup of APEX. Sample results demonstrated the capability of the framework for distributed and semi-distributed modeling and illustrated the performance of parallelization. This framework can help provide guidance for decision makers on agricultural BMPs with large-scale water quality assessments and NPS nutrient loading reductions.