Enhancing Road Drainage Systems for Extreme Storms: Integration of a High-Precision Flow Diversion Module into SWMM Code - Yuting Ren; Zhiyu Shao; Qi Zhang; Wang Feng; Lei Xu; Huafeng Gong; Scott Yost; Lei Chen; Hongxiang Chai (International Journal of Disaster Risk Science)
Abstract Urban road networks function as surface passage for floodwater transport during extreme storm events to reduce potential risks in the city. However, precise estimation of these flow rates presents a significant challenge. This difficulty primarily stems from the intricate three-dimensional flow fields at road intersections, which the traditional one-dimensional models, such as Storm Water Management Model (SWMM), fail to precisely capture. The two-dimensional and three-dimensional hydraulic models are overly complex and computationally intensive and thus not particularly efficient. This study addresses these issues by integrating a semiempirical flow diversion formula into the SWMM source code. The semiempirical formula, derived from hydraulic experiments and computational fluid dynamics simulations, captures the flow dynamics at T-shaped intersections. The modified SWMM’s performance was evaluated against experimental data, and the original SWMM, the two-dimensional MIKE21, and the three-dimensional FLUENT models. The results indicate that the modified SWMM matches the precision of the two-dimensional MIKE21, while significantly reducing computational time. Compared to MIKE21, this study achieved a Nash-Sutcliffe efficiency of 0.9729 and a root mean square error of 0.042, with computational time reduced by 99%. The modified SWMM is suitable for real-sized urban road networks. It provides a high-precision tool for urban road drainage system computation that is crucial for effective stormwater management.