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A framework for automated and spatially-distributed modeling with the Agricultural Policy Environmental eXtender (APEX) model
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 pote...
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Published in: | Environmental modelling & software : with environment data news 2021-10, Vol.144, p.105147, Article 105147 |
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creator | Pan, Feng Feng, Qingyu McGehee, Ryan Engel, Bernard A. Flanagan, Dennis C. Chen, Jingqiu |
description | 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.
•A framework for spatially-distributed modeling of APEX was developed.•Included input database and automated functionality make APEX modeling efficient.•The script is modular and can be readily maintained, modified, and expanded.•Parallelization drastically reduces computational time for spatially-distributed tasks. |
doi_str_mv | 10.1016/j.envsoft.2021.105147 |
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•A framework for spatially-distributed modeling of APEX was developed.•Included input database and automated functionality make APEX modeling efficient.•The script is modular and can be readily maintained, modified, and expanded.•Parallelization drastically reduces computational time for spatially-distributed tasks.</description><subject>Agricultural policy</subject><subject>Agricultural practices</subject><subject>APEX</subject><subject>Apexes</subject><subject>Best management practices</subject><subject>Distributed-modeling</subject><subject>Hydrologic models</subject><subject>Hydrology</subject><subject>Nonpoint source pollution</subject><subject>Nutrient loading</subject><subject>Parallel computing</subject><subject>Parallel processing</subject><subject>Pollutants</subject><subject>Pollution sources</subject><subject>Quality assessment</subject><subject>Simulation</subject><subject>Water quality</subject><subject>Water quality assessments</subject><issn>1364-8152</issn><issn>1873-6726</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNqFUMtKAzEUHUTB-vgEIeBGF1PzmOdKSqkPEHSh4C5kkhubOpPUJNPShf_ulOne1T2ce8653JMkVwRPCSbF3WoKdhOcjlOKKRm4nGTlUTIhVcnSoqTF8YBZkaUVyelpchbCCmM84GyS_M6Q9qKDrfPfSDuPRB9dJyIoJKxCYS2iEW27S5UJ0Zum3286p6A19gttTVyiuAQ0-_JG9m3svWjRm2uN3KGF3RjvbAc2DiR8RrAKPLqZvS0-b8eMi-REizbA5WGeJx8Pi_f5U_ry-vg8n72kkrEypk1WaZHLWrJGC1bUgjS0FE0lBcl0jQsiaaUy0oCkArOyrnUDqqRKacZyDJqdJ9dj7tq7nx5C5CvXezuc5DSvWF5jzPCgykeV9C4ED5qvvemE33GC-b5pvuKHpvm-aT42PfjuRx8ML2wMeB6kAStBGQ8ycuXMPwl_hh-MtQ</recordid><startdate>202110</startdate><enddate>202110</enddate><creator>Pan, Feng</creator><creator>Feng, Qingyu</creator><creator>McGehee, Ryan</creator><creator>Engel, Bernard A.</creator><creator>Flanagan, Dennis C.</creator><creator>Chen, Jingqiu</creator><general>Elsevier Ltd</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7SC</scope><scope>7ST</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0001-9602-4741</orcidid><orcidid>https://orcid.org/0000-0001-7543-125X</orcidid><orcidid>https://orcid.org/0000-0001-7665-7170</orcidid><orcidid>https://orcid.org/0000-0003-0464-9774</orcidid></search><sort><creationdate>202110</creationdate><title>A framework for automated and spatially-distributed modeling with the Agricultural Policy Environmental eXtender (APEX) model</title><author>Pan, Feng ; 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subjects | Agricultural policy Agricultural practices APEX Apexes Best management practices Distributed-modeling Hydrologic models Hydrology Nonpoint source pollution Nutrient loading Parallel computing Parallel processing Pollutants Pollution sources Quality assessment Simulation Water quality Water quality assessments |
title | A framework for automated and spatially-distributed modeling with the Agricultural Policy Environmental eXtender (APEX) model |
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