To address the challenge of optimizing the spatial layout of Low Impact Development (LIDLow Impact Development (LID)) facilities in small-scale areas, this study established a Storm Water Management Model (SWMM) for a pilot sponge citySponge city community in Nanchang City as the primary study area, with an additional area selected for validation. Sensitivity analysis and calibration of model parameters were performed using standardized methods. Furthermore, a method for quantifying the distribution uniformityUniformity of LIDLow Impact Development (LID) facilities was proposed. The Non-dominated Sorting Genetic Algorithm II (NSGA-IINSGA-II algorithm) was subsequently employed to optimize the LIDLow Impact Development (LID) facility layout. The results indicate a positive correlation between runoff reduction and LIDLow Impact Development (LID) construction costs across different rainfall return periods. Notably, for a 10-year return period rainfall event, a greater runoff reduction was achieved for the same cost compared to higher return periods. Further analysis revealed that dispersed LIDLow Impact Development (LID) layouts exhibited high distribution uniformityUniformity but incurred higher costs, while clustered layouts provided advantages in balancing runoff management and cost. Centralized layouts have lower costs but limited runoff management effectiveness. Additionally, carbon emissionsCarbon emissions from permeable pavement constitute the primary source of total emissions, and total life-cycle carbon emissionsCarbon emissions are positively correlated with runoff reduction. Considering factors such as cost-effectiveness, LIDLow Impact Development (LID) layout type, and ecological benefits, the optimal implementation strategy for the primary study community was determined to comprise 1.17% green roofs, 3.79% sunken green spaces, and 3.76% permeable pavements. These findings offer technical support for LIDLow Impact Development (LID) implementation in similar areas.