SWMM-based methodology for block-scale LID-BMPs planning based on site-scale multi-objective optimization： a case study in Tianjin

• Published in: Frontiers of environmental science & engineering Vol. 11; no. 4; pp. 51 - 62
• Main Authors: Xu, Te, Jia, Haifeng, Wang, Zheng, Mao, Xuhui, Xu, Changqing
• Format: Journal Article
• Language: English
• Published: Beijing Higher Education Press 01.08.2017; Springer Nature B.V
• Subjects: algorithms; Best management practices; BMPs; Case studies; China; Construction costs; cost effectiveness; Earth and Environmental Science; Environment; Genetic algorithms; Layouts; LID-BMP chain; LID-BMPs planning; Low Impact Development and Sponge City; Methodology; Multiple objective analysis; NSGA-II; Optimization; planning; Pollutant removal; Pollutants; Pollution index; Pollution load; Research Article; Runoff; Runoff volume; Scenario analysis; Sorting algorithms; Storm runoff; Stormwater; Stormwater management; SWMM; Urban areas; Urban runoff; 块表; 基础设计; 多目标优化方法; 天津市; 网站; 规划开发; Tianjin China; China; LID-BMPs planning; NSGA-II; Scenario analysis; SWMM; Stormwater management; LID-BMP chain
• ISSN: 2095-2201; 2095-221X
• DOI: 10.1007/s11783-017-0934-6

Low impact development type of best management practices （LID-BMPs） aims to mitigate urban stormwater runoffand lessen pollutant loads in an economical and eco-friendly way and has become a global concern in modem urban stormwater management. A new methodology based on stormwater management model （SWMM） for block-scale LID-BMPs planning was developed. This method integrated LID-BMP chain layout optimization in site-scale parcels with scenario analysis in the entire block-scale urban area. Non-dominated sorting genetic algorithm （NSGA-II） was successfully coupled to SWMM through Python to complete the site-scale optimization process. Different LID scenarios of the research area were designed on the basis of the optimized LID-BMP chain layout. A multi-index evaluation that considered runoff quantity indices, pollutant loads, and construction costs simultaneously helped select the cost-effective scenario as the final planning scheme. A case study in Tianjin, China, was conducted to demonstrate the proposed methodology. Results showed that more than 75% control rate of total runoff volume, 22%-46% peak flow reduction efficiency, and more than 32% pollutant removal rate were achieved. The robustness analysis indicated that the selected final planning scheme was considerably robust with varied weight values.