Enhancing Road Drainage Systems for Extreme Storms: Integration of a High-Precision Flow Diversion Module into SWMM Code

Autor: Yuting Ren, Zhiyu Shao, Qi Zhang, Wang Feng, Lei Xu, Huafeng Gong, Scott Yost, Lei Chen, Hongxiang Chai
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: International Journal of Disaster Risk Science, Vol 15, Iss 5, Pp 789-802 (2024)
Druh dokumentu: article
ISSN: 2095-0055
2192-6395
DOI: 10.1007/s13753-024-00594-2
Popis: 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.
Databáze: Directory of Open Access Journals
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