Acta Geographica Sinica ›› 2023, Vol. 78 ›› Issue (5): 1059-1073.doi: 10.11821/dlxb202305001

• Research on Natural Disasters •     Next Articles

Regionalization of flash floods in China

CHEN Yuehong1(), XU Congcong1, ZHANG Xiaoxiang1(), ZHANG Ruojing1, MA Qiang2, LIU Changjun2, REN Liliang1, SHI Kaixin1   

  1. 1. College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
    2. Research Center on Flood and Drought Disaster Reduction, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
  • Received:2022-08-29 Revised:2023-02-12 Online:2023-05-25 Published:2023-05-27
  • Contact: ZHANG Xiaoxiang E-mail:chenyh@lreis.ac.cn;xiaoxiang@hhu.edu.cn
  • Supported by:
    National Key R&D Program of China(2019YFC1510601);Key R&D Program of Guangxi Province(2019AB20003);Water Resources Science Technology Program of Hunan Province(XSKJ2019081-17)

Abstract:

According to the Ministry of Water Resources of the People's Republic of China, the number of casualties in flash flood disasters accounts for nearly 70% of flood disaster casualties in recent years and flash flood has become one of the major natural disasters causing casualties in China. Flash flood regionalization is fundamental for implementing the local measures of the flash flood prevention and mitigation according to local conditions. Using results from existing flash flood relevant physiographical regionalization schemes, and in accordance with the principles of comprehensive, dominant factors, the relative consistency within units, the relative difference between units, the integrity of spatial distribution and the hierarchical divisions, this paper firstly constructs an index system of the flash flood trigger factors and its underlying surface environment for the flash flood regionalization in China. In the combination of top-down and bottom-up regionalization, the hybrid self-organizing-map-based spatial clustering algorithm is then built. Finally, nine homogeneous regions at the first-grade and thirty-three subregions at the second-grade are delineated for flash floods in China. The historical flash flood events and the Geodetector method are adopted to evaluate the developed regionalization schemes. Results show that the first-grade and the second-grade flash flood regionalization schemes in China can respectively provide the determinant power of 66.4% and 75.4% for the spatial distribution of historical flash flood events in the whole country, indicating the developed flash flood regionalization has a good spatial consistency with the distribution of historical flash flood events with different densities. The developed flash flood regionalization not only effectively delineates the regional differentiation pattern of flash floods, but also provides a scientific basis for the implementation of localized flash flood prevention and mitigation measures in China, which benefits for the sound development of flash flood disasters prevention and management in China.

Key words: regionalization, flash flood disaster, short-duration heavy rainfall, underlying surface, machine learning, China