Optimal selection and placement of BMPs and LID practices with a rainfall-runoff model

A decision support tool, which links a hydrologic/water quality model (L-THIA-LID 2.1) with optimization algorithms (AMALGAM) using a computational efficiency framework (MLSOPT), was developed to optimally implement BMPs and LID practices to reduce runoff and pollutant loads. The decision support tool was applied in the Crooked Creek watershed, Indiana, USA. For initial expenditures on practices, the environmental benefits increased rapidly as expenditures increased. However, beyond certain expenditure levels, additional spending did not result in noticeable additional environmental impacts. Compared to random placement of practices, the optimization strategy provided 3.9-7.7 times the level of runoff/pollutant load reductions for the same expenditures. To obtain the same environmental benefits, costs of random practices placement were 4.2-14.5 times the optimized practice placement cost. The decision support tool is capable of supporting decision makers in optimally selecting and placing BMPs and LID practices to obtain maximum environmental benefits with minimum costs. (C) 2016 Elsevier Ltd. All rights reserved.