Development of a Grid-Based Pluvial Flooding Analysis Model for Rapid Decision-Making

Urban pluvial flood analysis requires spatial inundation information within operationally useful computation times. This study develops a graphics processing unit (GPU)-accelerated Node–Edge Urban Flood Model (GNE-UFM) that couples SWMM-style runoff generation, structured-grid surface flow, a typed sewer graph, and conservative surface–sewer exchange. The model was evaluated in the Sillim drainage district using the August 2022 observed event and three one-hour rainfall scenarios of 40, 90, and 150 mm, with inputs and output thresholds matched to InfoWorks ICM. For the synthetic scenarios, GNE-UFM achieved CSI values of 0.878–0.904 and wet-union RMSE values of 0.050–0.078 m, while full coupled GPU runs closed the effective runoff mass balance with absolute residuals no larger than 0.0284%. Runtime was comparable to ICM for the lowest-intensity case and became more efficient for the 90 and 150 mm cases, with GNE-UFM maintaining nearly constant RTR as rainfall intensity and inundated area increased.