Volume 12 Issue 5
Dec.  2021
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Weiqi Wang, Wenjie Chen, Guoru Huang. Urban Stormwater Modeling with Local Inertial Approximation Form of Shallow Water Equations: A Comparative Study[J]. International Journal of Disaster Risk Science, 2021, 12(5): 745-763. doi: 10.1007/s13753-021-00368-0
Citation: Weiqi Wang, Wenjie Chen, Guoru Huang. Urban Stormwater Modeling with Local Inertial Approximation Form of Shallow Water Equations: A Comparative Study[J]. International Journal of Disaster Risk Science, 2021, 12(5): 745-763. doi: 10.1007/s13753-021-00368-0

Urban Stormwater Modeling with Local Inertial Approximation Form of Shallow Water Equations: A Comparative Study

doi: 10.1007/s13753-021-00368-0

This work was supported by the National Natural Science Foundation of China (Grant Numbers 51739011 and 51879108).

  • Available Online: 2021-12-25
  • This study focused on the performance and limitations of the local inertial approximation form model (LIM) of the shallow water equations (SWEs) when applied in urban flood modeling. A numerical scheme of the LIM equations was created using finite volume method with a first-order spatiotemporal Roe Riemann solver. A simplified urban stormwater model (SUSM) considering surface and underground dual drainage system was constructed based on LIM and the US Environmental Protection Agency Storm Water Management Model. Moreover, a complete urban stormwater model (USM) based on the SWEs with the same solution algorithm was used as the evaluation benchmark. Numerical results of the SUSM and USM in a highly urbanized area under four rainfall return periods were analyzed and compared. The results reveal that the performance of the SUSM is highly consistent with that of the USM but with an improvement in computational efficiency of approximately 140%. In terms of the accuracy of the model, the SUSM slightly underestimates the water depth and velocity and is less accurate when dealing with supercritical flow in urban stormwater flood modeling. Overall, the SUSM can produce comparable results to USM with higher computational efficiency, which provides a simplified and alternative method for urban flood modeling.
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