Coupled SWMM-MOEA/D for multi-objective optimization of low impact development in urban stormwater systems

Abstract

The escalating challenge of unsustainable urban development worldwide has precipitated changes in land usage, contributing to increased impermeability of the urban landscape. This phenomenon exacerbates urban runoff, a critical environmental concern. In response, Low Impact Development (LID) techniques, recognized for their environmental efficacy, have emerged as pivotal in mitigating urban runoff. However, transforming the hydrological dynamics of urban watersheds into a more sustainable state necessitates substantial financial commitments from relevant authorities. Consequently, strategic LID planning becomes essential to maximize effectiveness while minimizing costs. This research introduces a novel, hybrid modeling strategy that integrates the Storm Water Management Model (SWMM) with the Multi-Objective Evolutionary Algorithm by Decomposition (MOEA/D) optimization algorithm. This approach aims to concurrently minimize runoff volume, peak flow rate, and implementation expenses. Focusing on a segment of Tehran Municipality’s urban stormwater system in District 11, the study evaluates four distinct LID scenarios. These scenarios encompass various configurations of Rain Barrels (RB), Bioretention Cells (BC), Green Roofs (GR), and Porous Pavements (PP). Utilizing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method for comparative analysis, the study results identify the most efficacious scenario, S2_1, including RB and BC, which achieves a 19.34% reduction in runoff volume and a 46.53 % decrease in peak flow rate, all at the implementation cost of 123,169 USD. A close second, scenario S3_1 incorporating RB and PP, demonstrates a 17 % and 46.55 % reduction in runoff volume and peak flow at an expenditure of 107,017 USD, respectively. The proposed SWMM-MOEA/D model, in conjunction with TOPSIS, presents a valuable tool for LID planning and optimization, offering decision-makers and relevant entities a pragmatic approach to address the challenges of urban runoff management.