Urban Inundation under Different Rainstorm Scenarios in Lin'an City, China

Int J Environ Res Public Health. 2022 Jun 12;19(12):7210. doi: 10.3390/ijerph19127210.

Abstract

Under the circumstances of global warming and rapid urbanization, damage caused by urban inundation are becoming increasingly severe, attracting the attention of both researchers and governors. The accurate simulation of urban inundation is essential for the prevention of inundation hazards. In this study, a 1D pipe network and a 2D urban inundation coupling model constructed by InfoWorks ICM was used to simulate the inundation conditions in the typical urbanized area in the north of Lin'an. Two historical rainfall events in 2020 were utilized to verify the modeling results. The spatial-temporal variation and the causes of urban inundation under different designed rainfalls were studied. The results were as follows: (1) The constructed model had a good simulation accuracy, the Nash-Sutcliffe efficiency coefficient was higher than 0.82, R2 was higher than 0.87, and the relative error was ±20%. (2) The simulation results of different designed rainfall scenarios indicated that the maximum inundation depth and inundation extent increased with the increase in the return period, rainfall peak position coefficient, and rainfall duration. According to the analysis results, the urban inundation in Lin'an is mainly affected by topography, drainage network (spatial distribution and pipe diameter), and rainfall patterns. The results are supposed to provide technical support and a decision-making reference for the urban management department of Lin'an to design inundation prevention measures.

Keywords: InfoWorks ICM; Lin’an city; designed rainfalls; urban inundation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Cities
  • Floods*
  • Models, Theoretical*
  • Rain
  • Urbanization

Grants and funding

This research was funded by the Zhejiang Provincial Natural Science Foundation of China, grant number: LY19D010004, and the Science and Technology Program of Hangzhou, grant number: 20191203B19.