Implications of spatially distributed rainfall design events on urban hydrological response across advection scenarios

Urban catchments face high flood risks caused by heavy rainfall, largely because of altered hydrology and high imperviousness. Estimating the runoff response to such rainfall events is crucial for effective stormwater management. This study utilizes modified python version of the Short Term Ensemble Prediction System (pySTEPS) to generate stochastic design storms, mimicking spatiotemporal properties of an observed thunderstorm over an urban catchment in southern Finland. The model is parametrized using weather radar data with altered rain field advections. Simulated rainfall ensembles are fed into a storm water management model (SWMM) to assess the hydrological response across advection scenarios. Results show notable differences in rainfall accumulations depending on orientation of rainfall structures and varying advection magnitude. Changes in advection properties translate to increased peak stormwater flows and urban flooding risk for slowly moving rain structures and for rain structures with an elongated shape along the direction they are advancing. The presented approach gives insight to the effects of spatial variability of heavy rainfall on runoff generation across advection scenarios.