Minimization of cost, sediment load, and sensitivity to climate change in a watershed management application

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 nondominated 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. 2013 Elsevier Ltd. All rights reserved.