Volume 13 Issue 2
Jul.  2022
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Liutong Chen, Zhengtao Yan, Qian Li, Yingjun Xu. Flash Flood Risk Assessment and Driving Factors: A Case Study of the Yantanxi River Basin, Southeastern China[J]. International Journal of Disaster Risk Science, 2022, 13(2): 291-304. doi: 10.1007/s13753-022-00408-3
Citation: Liutong Chen, Zhengtao Yan, Qian Li, Yingjun Xu. Flash Flood Risk Assessment and Driving Factors: A Case Study of the Yantanxi River Basin, Southeastern China[J]. International Journal of Disaster Risk Science, 2022, 13(2): 291-304. doi: 10.1007/s13753-022-00408-3

Flash Flood Risk Assessment and Driving Factors: A Case Study of the Yantanxi River Basin, Southeastern China

doi: 10.1007/s13753-022-00408-3

We would like to thank the editors and reviewers for their comments. We also would like to express our gratitude to Professor Jidong Wu's team at Beijing Normal University, and Professor Tong Jiang's team at Nanjing University of Information Science and Technology for providing data support. This work was supported by the National Key Research and Development Program (2017YFA0604903, 


  • Available Online: 2022-07-06
  • In the context of climate change, the impact of extreme precipitation and its chain effects has intensified in the southeastern coastal region of China, posing a serious threat to the socioeconomic development in the region. This study took tropical cyclones–extreme precipitation–flash floods as an example to carry out a risk assessment of flash floods under climate change in the Yantanxi River Basin, southeastern China. To obtain the flash flood inundation characteristics through hydrologic–hydrodynamic modeling, the study combined representative concentration pathway (RCP) and shared socioeconomic pathway (SSP) scenarios to examine the change of flash flood risk and used the geographical detector to explore the driving factors behind the change. The results show that flash flood risk in the Yantanxi River Basin will significantly increase, and that socioeconomic factors and precipitation are the main driving forces. Under the RCP4.5-SSP2 and RCP8.5-SSP5 scenarios, the risk of flash floods is expected to increase by 88.79% and 95.57%, respectively. The main drivers in the case study area are GDP density (q = 0.85), process rainfall (q = 0.74), asset density (q = 0.68), and population density (q = 0.67). The study highlights the influence of socioeconomic factors on the change of flash flood disaster risk in small river basins. Our findings also provide a reference for regional planning and construction of flood control facilities in flash flood-prone areas, which may help to reduce the risk of flash floods.
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