Optimizing Low Impact Development (LID) Methods in Urban Runoff Quantitative and Qualitative Control with Considering the Effects of Climate Change Using Multi-Objective Optimization Algorithms

Quantitative and qualitative management of urban runoff in part of Karaj city has been investigated using optimization of Low Impact Development (LID) methods under base period and climate change conditions. CanESM2 was employed with the base period (1985-2005) and future period (2020-2040) under the RCP2.6 and RCP8.5 scenarios to investigate climate change impacts. Hydraulic and hydrological modeling was performed by Storm Water Management Model (SWMM) and was combined with Multi-objective Particle Swarm Optimization Algorithm (MOPSO) and Non-dominated Sorting Genetic Algorithm (NSGA-II). Thirty-seven sub-catchments and five types of LIDS are introduced to the algorithms. Eight scenarios were defined to compare and evaluate the algorithms. Under the base period conditions, by applying NSGA-II and MOPSO algorithms, the flood volume in the catchment will decrease by 21.2% and 20.3%, total suspended solids (TSS) will increase by 59.1% and 58.4%, total nitrogen (TN) will increase by 16.6% and 12.7%, and lead (Pb) concentration will increase by 29.7% and 28.7%, respectively. Solution of the algorithms under climate change conditions gave similar flood values as the base conditions. In RCP2.6 scenario, TSS will decrease by 59.5% and 55.2%, respectively, and in RCP8.5 scenario, TSS will decrease by 59.6% and 55.8%, respectively. In RCP2.6 scenario, TN will decrease by 17.4% and 13.4%, respectively, and in RCP8.5 scenario, TN will decrease by 17.6% and 13.5%, respectively. Pb in RCP2.6 scenario will decrease by 30.1% and 29.7%, respectively, and in RCP8.5 scenario, Pb will decrease by 30.9% and 30.4%, respectively.