posted on 2024-06-03, 23:47authored byChunfeng Luan, Zhaohui Shi, Renjing Zhao, Yiwen CuiYiwen Cui
Under the rapid urbanization and industrialization, the risk of natural disasters in cities is increasingly exposed, especially the issue of rain-induced flood has become increasingly prominent. In view of the rain-induced flood that has occurred in Gongyi City in recent years, a study on the risk of rain-induced flood in Gongyi City has been carried out in order to provide a scientific basis for the city's disaster prevention and mitigation work. Based on the natural disaster risk assessment theory, this paper built a rain-induced flood risk model with the risk of disaster factors, the risk of disaster-pregnant environment, the vulnerability of disaster-bearing bodies and the ability to prevent and reduce disasters as evaluation indicators. Starting from the above, a total of 14 index factors were selected for quantitative analysis, and the SCS model (Soil Conservation Service) and GIS spatial analysis functions were used to finally obtain the comprehensive risk zoning map of rain and flood disasters in Gongyi City. The results show that Mihe Town, Huiguo Town, Zhitian Town and Xiaoyi Sub-District of Gongyi City are more dangerous. The risk of pregnancy in disaster environment in the north, west and east areas include Heluo Town, Xiaoyi Sub-District, Huiguo Town, Zhitian Town and Mihe Town is higher. The disaster-bearing bodies in the western and central parts are more vulnerable, including Huiguo Town, Zhitian Town and Zhanjie Town. The overall disaster prevention and mitigation capacity of the north is strong, including Zhanjie Town and Zijing Sub-District. In general, the overall risk level of rain-induced flood in Gongyi City is relatively higher, and the high-risk areas are mainly distributed in a belt-like structure in the north-central and western regions.
History
Preferred citation
Luan, C., Shi, Z., Zhao, R. & Cui, Y. (2024). Risk Assessment of Rain-Induced Flood in Small Mountain Towns Based on GIS Technology. Yellow River. https://doi.org/10.3969/j.issn.1000-1379.2024.05.009