Urban storm water drainage system optimization using a sustainability index and LID/BMPs

Abstract

• A new comprehensive sustainability index for urban stormwater drainage systems was developed. • The developed sustainability index applied to the western part of Tehran stormwater drainage. Results showed that the study area suffers from significant performance degradation. • Two multi-objective optimization models, with the objectives of maximizing sustainability and minimizing costs, were introduced to rehabilitate the stormwater drainage system. • The effects of considering channels rehabilitation along with BMPs implication were studied. • Results showed that rehabilitating the stormwater networks by BMPs implication and rehabilitating the channels would result in more cost-effective solutions. Urban stormwater drainage systems (USDSs) play an essential role in protecting cities from excessive rainfalls and urban floods. To quantify the performance of the USDSs, a new sustainability index is proposed based on reliability, resiliency, and vulnerability indices. These performance indices evaluate different aspects of a USDS with a comprehensive view of the system's level of service. Using the proposed sustainability index, two USDS design/rehabilitation optimization models are introduced and compared to see which one offers a more sustainable solution and lower implementation cost. The first model ( Case I ) applies Best Management Practices (BMPs) to an existing USDS to improve sustainability with minimum costs. The second model rehabilitates the channel sizes along with using BMPs. A part of the Tehran Stormwater Drainage System (TSDS) is chosen as the study area to evaluate the proposed methodology. Optimization models are developed by linking the NSGA-II optimization algorithm with the EPA SWMM model. The best solutions are extracted from both cases’ Pareto fronts and compared using the Nash bargaining method. Results showed that designing/rehabilitating USDSs by optimizing the BMPs size and channel size would result in a higher sustainability index and lower costs.