Hydrological Impacts of Urban Expansion and Rainfall Spatial Distribution in Urban Subcatchments: A Scenario-Based Assessment Using EPA-SWMM Model

Urban expansion significantly alters the hydrological response of cities, particularly in steep-slope regions where the increase in impervious surfaces intensifies surface runoff and contributes to drainage system overload. This study evaluates the combined impacts of land cover change and rainfall spatial distribution on four urban subcatchments in Medellín, Colombia, using the EPA-SWMM model. Seven synthetic and real rainfall scenarios were developed by combining two spatial patterns, typical uniform rainfall (SP1) and rainfall concentrated in the lower subcatchment (SP2), with three levels of accumulated rainfall (R1, R2, and R3), along with a real event (SP3) derived from radar and gauge observations. Land use scenarios for the years 2012, 2018, and 2024 were derived from satellite imagery and reflect distinct urbanization trajectories in each subcatchment. Model simulations were evaluated using four key performance metrics: peak flow, runoff volume, runoff coefficient, and the percentage of overloaded nodes in the urban drainage network. Results show that SP2 scenarios produce significantly higher impacts for the same rainfall accumulation, particularly in subcatchments with greater imperviousness in the lower and flatter areas. Furthermore, increases in the metrics were more pronounced for moderate-magnitude events (R1 and R2) compared to extreme events (R3 and SP3), which showed relatively stable behavior across the years studied. A ternary diagram was used to classify total runoff into three components: infiltration, runoff from permeable areas, and runoff from impervious areas, highlighting the influence of land cover on runoff generation and the differential behavior among subcatchments. Overall, the study demonstrates the importance of accounting for both rainfall spatiality and urban expansion in hydrological impact assessments and supports the use of scenario-based modeling as a decision-making tool in urban water management, particularly in small, steep tropical urban catchments where intense rainfall and rapid runoff generation significantly increase the risk of flash flooding and infrastructure vulnerability.