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Addressing the spatial disconnect between national‐scale total maximum daily loads and localized land management decisions
Author(s) -
Amin M. G. Mostofa,
Veith Tamie L.,
Shortle James S.,
Karsten Heather D.,
Kleinman Peter J. A.
Publication year - 2020
Publication title -
journal of environmental quality
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.888
H-Index - 171
eISSN - 1537-2537
pISSN - 0047-2425
DOI - 10.1002/jeq2.20051
Subject(s) - environmental science , watershed , total maximum daily load , soil and water assessment tool , water framework directive , swat model , clean water act , environmental resource management , watershed management , land use , computer science , water resource management , hydrology (agriculture) , water quality , engineering , civil engineering , ecology , cartography , geography , drainage basin , geotechnical engineering , machine learning , streamflow , biology
Regulatory watershed mitigation programs typically emphasize widespread adoption of best management practices (BMPs) to meet total maximum daily load (TMDL) goals. To comply with the Chesapeake Bay TMDL, jurisdictions must develop watershed implementation plans (WIPs) to determine the number and type of BMPs to implement. However, the spatial resolution of the bay‐level model used to determine these load reduction goals is so coarse that the regulatory plan cannot consider heterogeneity in local conditions, which affects BMP effectiveness. Using the Topo‐SWAT modification of the Soil and Water Assessment Tool (SWAT), we simulated two BMP adoption scenarios in the Spring Creek watershed in central Pennsylvania to determine if leveraging fine‐scale spatial heterogeneity to place BMPs could achieve the same (or better) nutrient and sediment reduction at a lower cost than the state‐level WIP BMP adoption recommendations. Topo‐SWAT was initialized with detailed land use and management practice information, systematically calibrated, and validated against 12 yr of observed data. After determining individual BMP cost effectiveness, results were ranked to design a cost‐effective BMP adoption scenario that achieved equal or greater load reduction as the WIP scenario for 74% of the cost using eight management‐based BMPs: no‐till, manure injection, cover cropping, riparian buffers, land retirement, manure application timing, wetland restoration, and nitrogen management (15% less N input). Because watersheds of this size typically represent the smallest modeling unit in the Chesapeake Bay Model, results demonstrate the potential to use watershed models with finer inference scales to improve recommendations for BMP implementation under the Chesapeake Bay TMDL.