Optimization of Low-Impact Development (LID) Parameters Using SWMM and Response Surface Methodology at the Community Scale

Abstract

The parameters of Low-Impact Development (LID) facilities significantly influence their operational performance and runoff control effectiveness at the site. Despite extensive research on LID effectiveness, limited studies have focused on optimizing design parameters at a community-wide scale, integrating both hydrological and statistical methodologies. A novel approach to optimizing LID design parameters was presented in this study. This study established a community-scale SWMM model, identified the key parameters by the Morris screening method, and determined the reasonable parameter ranges based on runoff control effects. The Response Surface Methodology (RSM) was applied to optimize the key parameters under different return periods and impervious area ratios. The results showed that key LID parameters for runoff volume control were the berm height of the surface layer of sunken greenbelt (SG_Surface_H), the conductivity of the soil layer of sunken greenbelt (SG_Soil_I), the permeability of the pavement layer of permeable pavement (PP_Pavement_I), and the thickness of the storage layer of permeable pavement (PP_Storage_T). The reasonable ranges were 50–265 mm, 5–80 mm/h, 50–140 mm/h, and 100–165 mm, respectively. The key LID parameters for peak flow reduction were SG_Surface_H, SG_Soil_I, PP_Pavement_I, and the berm height of the surface layer of vegetated swale (VS_Surface_H). The reasonable ranges were 50–260 mm, 5–50 mm/h, 50–195 mm/h, and 50–145 mm, respectively. The optimization results of LID parameters showed that for the runoff volume control rate, the optimization strategy involved increasing SG_Surface_H as the return period increased and when the impervious area ratio was large, especially in the rehabilitation of old communities. Meanwhile, the optimal value of SG_Soil_I for runoff volume control was greater than that for peak flow reduction. In contrast, the optimal value of PP_Pavement_I was larger for peak flow reduction. This study provides a significant reference for LID planning and design by emphasizing the optimization of LID design parameters.