Background
Rapid urbanization expands impervious surfaces and intensifies urban flood risk. Permeable pavement is a proven LID measure — but where and how much to deploy under fixed budget and area constraints is a separate multi-objective optimization problem.
Method
- Automated geospatial processing (OSM + Copernicus DEM) builds EPA SWMM for 18 Seocho-gu sub-catchments
- Scenario sweep across 0–100% coverage under a 10-year design storm
- XGBoost surrogate (R² = 0.79) replaces expensive SWMM runs
- NSGA-II multi-objective optimization delivers the Pareto front (runoff reduction vs installation area)
- SHAP quantifies per-sub-catchment influence
Key Results
- Baseline runoff 614,298 m³, 24.8% reduction at full coverage
- Diminishing-return pattern: first 30% delivers 73% of full-coverage benefit
- Cost-effective sweet spot: 30–50%
- Pareto front: 14.7–22.7% runoff reduction / 3.8–63.5% installation area
- Naegok-dong identified as priority investment site (largest catchment area)
Significance
This study provides a reproducible, scalable, and interpretable methodology for LID spatial optimization in dense urban watersheds — a decision-support tool that bridges quantitative recommendation and qualitative policy choice.