Due to the impact of climate change, the importance of urban flood analysis is increasing. One of the biggest challenges in urban flood simulations is the complexity of storm sewer networks, which significantly affects both computational time and accuracy. This study aimed to analyze and evaluate the impact of sewer network simplification on the accuracy and computational performance of urban flood prediction by comparing different rainfall runoff methods. Using the hyper-connected solution for urban flood (HC-SURF) model, two rainfall runoff methods, the SWMM Runoff method and the Surface Runoff method, were compared. The sewer network simplification was applied based on manhole catchment areas ranging from 10 m2 to 10,000 m2. The analysis showed that the computation time could be reduced by up to 54.5% through simplification, though some accuracy loss may occur depending on the chosen runoff method. Overall, both methods produced excellent results in terms of mass balance, but the SWMM Runoff method minimized the reduction in analytical performance due to simplification. This study provides important insights into balancing computational efficiency and model accuracy in urban flood analysis.
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