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 u...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.展开更多
文摘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.
