ABSTRACT Urban areas are increasingly vulnerable to flooding due to rapid urbanization, inadequate stormwater infrastructure, and the intensifying impacts of climate change. To manage these challenges, reliable hydrological models are essential for mitigating the adverse impacts of hydrometeorological events. In data-scarce regions, the calibration of such models is hindered by limited field data. This study presents a practical methodology for calibrating a 1D–2D Stormwater Management Model (SWMM) for tropical urban catchments through a case study in Udon Thani City, Thailand. An iterative calibration process was applied to address major flooding identified in initial simulations, leading to improved runoff routing that ensured compliance with the 5-year, 1-h design storm of the system. The detailed one-factor-at-a-time (OAT) sensitivity analysis identified Curve Number (CN) and Imperviousness as the most influential parameters, followed by sub-catchment width and slope. The findings underscore the importance of prioritizing these parameters for calibration, particularly in regions with limited data availability. The proposed approach provides a scalable and transferable framework for flood risk assessment and management in similar tropical urban catchments globally. By integrating sensitivity analysis into the planning and optimization of green-grey infrastructure, the study contributes to the development of resilient and sustainable stormwater management strategies in vulnerable urban areas.
Ahmed et al. (Fri,) studied this question.
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