Numerical Experiments on Low Impact Development for Urban Resilience Index

Abstract

Low impact development (LID) has become one of the strategies that effectively mitigate the impacts of climate change. In addition to the ability to reduce nonpoint source (NPS) pollution caused by flash floods from the surface runoff, LID has also been applied to control water quantity under extreme rainfall events. Due to the fact that studies about LID configuration optimization tended to control water quantity and gradually ignored the main functions of water quality treatment, this study aims to consider water quantity and quality to estimate the benefits and optimal configuration of LID by Non-Dominated Genetic Algorithm (NSGA-II). In addition, regarding to the outlet peak flow, hydrologic footprint residence (HFR) was considered to be the water quantity indicator due to the ability to represent the dynamics of flow changes, and the modified quality indicator (Mass Emission First Flush ratio, MEFF30) was corrected to represent the pollutant transport process in a large catchment area. The results show that the flood and MEFF30 reduction rate of LID are inversely proportional to rainfall duration and intensity. The benefit of pollutant reduction, which can still be maintained by 20% and 15% under a big return period and the long duration was about three times than the quantity control. Taking the cost into account, although the rain barrel had the best effect of reduction per unit area, green roofs and permeable pavements had a higher unit cost reduction rate due to the lower costs. The upper and middle reaches of the open channel and the confluence of rainwater sewers should be the optimal LID configuration to achieve the benefits of both flood and pollution reduction.