A new framework for the optimal management of urban runoff with low-impact development stormwater control measures considering service-performance reduction

Abstract

Abstract This paper presents a comprehensive framework for the quantitative management of urban runoff. The framework assesses the response of urban catchments to design rainfall events and identifies low-impact development (LID) stormwater control measures (SCMs) for runoff control and flood mitigation. This research's method determines the optimal areas in which to deploy SCMs to control runoff in urban catchments. The optimization method relies on a three-objective simulation-optimization model that (1) minimizes the volume of runoff at the catchment outlet and at flooding nodes, (2) minimizes the implementation and maintenance costs of LID SCMs, and (3) minimizes the service-performance reduction of LID SCMs. The storm water management model (SWMM) is applied for runoff simulation and is coupled with the multi-objective antlion optimization algorithm (MOALOA). The simulation-optimization method is exemplified with an application to District 6 of Tehran's municipality (Iran). The performance of the simulation-optimization method is compared with that of the multi-objective non-dominated sorting genetic algorithm II (NSGAII), and, after confirming the superior capacity of the MOALOA, the latter algorithm is applied to District 6 of Tehran municipality, Iran. The identified optimal LID SCMs are ranked with the technique for order of preference by similarity to ideal solution (TOPSIS) method that reveals the preferences of the runoff managers concerning SCMs choices. The most desirable solution herein found shows the optimal LID SCMs provide a significant reduction in runoff volume at the catchment outlet and flooding nodes.