Minimization of cost,sediment load,and sensitivity to climate change in a watershed management application |
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| Affiliation: | 1. Department of Computer Science, University of Vermont, Burlington, VT 05401, USA;2. Rubenstein School of Environment and Natural Resources, University of Vermont, Burlington, VT 05401, USA;3. Department of Computer Science, University of Vermont, Burlington, VT 05401, USA;1. Center for Green Buildings and Cities, Graduate School of Design, Harvard University, Cambridge, MA 02138, USA;2. Graduate School of Design, Harvard University, Cambridge, MA 02138, USA;1. Crawford School of Public Policy, Australian National University, Australia;2. ISEE Systems, USA;3. Oak Ridge National Lab, USA;4. University of Pittsburgh, USA;5. Independent Game Designer, UK;6. University of Queensland, Australia;7. Alberta Innovates, Canada;8. CSIRO Ecosystem Sciences, Australia;9. Centre for Systems Solutions, Poland;10. Fenner School of Environment and Society, Australian National University, Australia;11. University of Maryland Center for Environmental Science, USA;12. United States Environmental Protection Agency, Office of Research and Development, USA;13. Centre for Tropical Environmental and Sustainability Science, School of Earth and Environmental Sciences, James Cook University, Cairns, Queensland, Australia;14. Research School of Computer Science, Australian National University, Australia;15. University of Maryland, Baltimore City, USA;p. University of Adelaide, Australia;q. Harvard University, USA;1. Department of Civil, Structural and Environmental Engineering, University at Buffalo, Jarvis Hall, Buffalo, NY, United States;2. Department of Industrial and Systems Engineering, University at Buffalo, Bell Hall, Buffalo, NY, United States;3. RENEW Institute, University at Buffalo, Cooke Hall, Buffalo, NY, United States;4. Departamento de Ingeniería Civil y Ambiental, Universidad de Los Andes, Bogotá, Colombia;1. School of Civil Engineering and Transportation, State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou 510641, China;2. Pazhou Lab, Guangzhou 510335, China;3. South China Institute of Environment Sciences, Ministry of Environment Protection of PRC, Guangzhou 510535, China;4. Department of Landscape Architecture, School of Architecture, South China University of Technology, Guangzhou 510641, China |
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| Abstract: | One challenge of climate change adaptation is to design watershed-based stormwater management plans that meet current total maximum daily load targets and also take into consideration anticipated changes in future precipitation patterns. We present a multi-scale, multiobjective framework for generating a diverse family of stormwater best management practice (BMP) plans for entire watersheds. Each of these alternative BMP configurations are non-dominated by any other identified solution with respect to cost of the implementation of the management plan and sediment loading predicted at the outflow of the watershed; those solutions are then pruned with respect to dominance in sensitivity to predicted changes in precipitation patterns. We first use GIS data to automatically precompute a set of cost-optimal BMP configurations for each subwatershed, over its entire range of possible treatment levels. We then formulate each solution as a real-valued vector of treatment levels for the subwatersheds and employ a staged multiobjective optimization approach using differential evolution to generate sets of non-dominated solutions. Finally, selected solutions are mapped back to the corresponding preoptimized BMP configurations for each subwatershed. The integrated method is demonstrated on the Bartlett Brook mixed-used impaired watershed in South Burlington, VT, and patterns in BMP configurations along the non-dominated front are investigated. Watershed managers and other stakeholders could use this approach to assess the relative trade-offs of alternative stormwater BMP configurations. |
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| Keywords: | Multiobjective Differential evolution Robustness to uncertainty Stormwater management Best management practices (BMPs) Total maximum daily load (TMDL) |
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