Extensive efforts to adaptively manage nutrient pollution rely on Chesapeake Bay Program's (Phase 6) Watershed Model, called Chesapeake Assessment Scenario Tool (CAST), which helps decision-makers plan and track implementation of Best Management Practices (BMPs). We describe mathematical characteristics of CAST and develop a constrained nonlinear BMP-subset model, software, and visualization framework. This represents the first publicly available optimization framework for exploring least-cost strategies of pollutant load control for the United States' largest estuary. The optimization identifies implementation options for a BMP subset modeled with load reduction effectiveness factors, and the web interface facilitates interactive exploration of >30,000 solutions organized by objective, nutrient control level, and for ~200 counties. We assess framework performance and demonstrate modeled cost improvements when comparing optimization-suggested proposals with proposals inspired by jurisdiction plans. Stakeholder feedback highlights the framework's current utility for investigating cost-effective tradeoffs and its usefulness as a foundation for future analysis of restoration strategies.
|Title||Supporting cost-effective watershed management strategies for Chesapeake Bay using a modeling and optimization framework|
|Authors||Daniel E Kaufman, Gary W. Shenk, Gopal Bhatt, Kevin Asplen, Olivia H. Devereux, Jessica Rigelman, J. Hugh Ellis, Benjamin F Hobbs, Darrell J Bosch, George L Van Houtven, Arthur E McGarity, Lewis C. Linker, William P. Ball|
|Publication Subtype||Journal Article|
|Series Title||Environmental Modelling & Software|
|Record Source||USGS Publications Warehouse|
|USGS Organization||VA/WV Water Science Center|