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Linking a storm water management model to a novel two-dimensional model for urban pluvial flood modeling

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journal contribution
posted on 27.05.2020, 11:17 by Yuhan Yang, Leifeng Sun, Ruonan Li, Jie Yin, Dapeng YuDapeng Yu
This article describes a new method of urban pluvial flood modeling by coupling the 1D storm water management model (SWMM) and the 2D flood inundation model (ECNU Flood-Urban). The SWMM modeling results (the overflow of the manholes) are used as the input boundary condition of the ECNU Flood-Urban model to simulate the rainfall–runoff processes in an urban environment. The analysis is applied to the central business district of East Nanjing Road in downtown Shanghai, considering 5-, 10-, 20-, 50-, and 100-year return period rainfall scenarios. The results show that node overflow, water depth, and inundation area increase proportionately with the growing return periods. Water depths are mostly predicted to be shallow and surface flows generally occur in the urban road network due to its low-lying nature. The simulation result of the coupled model proves to be reliable and suggests that urban surface water flooding could be accurately simulated by using this methodology. Adaptation measures (upgrading of the urban drainage system) can then be targeted at specific locations with significant overflow and flooding.


This study was supported by the National Key Research and Development Program of China (Grant Nos.: 2018YFC1508803, 2017YFE0107400, 2017YFE0100700), the National Natural Science Foundation of China (Grant Nos.: 41871164, 51761135024), the National Social Science Fund of China (Grant No.: 18ZDA105), the Humanities and Social Sciences Project of the Ministry of Education of China (Grant No.: 17YJAZH111), the Key Project of Soft Science Research of Shanghai (Grant No.: 19692108100), and the Fundamental Research Funds for the Central Universities (Grant Nos.: 2018ECNU-QKT001, 2017ECNU-KXK013).



  • Social Sciences and Humanities


  • Geography and Environment

Published in

International Journal of Disaster Risk Science






508 - 518


Springer Science and Business Media LLC


VoR (Version of Record)

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© The Authors

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Prof Dapeng Yu. Deposit date: 26 May 2020