Addressing the spatial disconnect between national-scale total maximum daily loads and localized land management decisions

M. G.Mostofa Amin, Tamie L. Veith, James S. Shortle, Heather D. Karsten, Peter J.A. Kleinman

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)613-627
Number of pages15
JournalJournal of Environmental Quality
Issue number3
StatePublished - May 1 2020

All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Water Science and Technology
  • Waste Management and Disposal
  • Pollution
  • Management, Monitoring, Policy and Law


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