Study on warning rainfall threshold for rainfall-induced collapses and landslide geological hazards in Zhuhai City, Guangdong Province

Zhuhai City experiences abundant rainfall, which often triggers sudden geological hazards such as landslides and collapses.This paper conducts a comprehensive analysis of 342 landslide and collapse events that occurred in Zhuhai City between 2013 and 2021, along with their associated rainfall charac...

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Bibliographic Details
Main Authors: Xinxiong ZENG, Jia LIU, Bo LAI, Fengshun ZHAO, Shan JIANG
Format: Article
Language:zho
Published: Editorial Office of The Chinese Journal of Geological Hazard and Control 2024-10-01
Series:Zhongguo dizhi zaihai yu fangzhi xuebao
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Online Access:https://www.zgdzzhyfzxb.com/en/article/doi/10.16031/j.cnki.issn.1003-8035.202406005
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Summary:Zhuhai City experiences abundant rainfall, which often triggers sudden geological hazards such as landslides and collapses.This paper conducts a comprehensive analysis of 342 landslide and collapse events that occurred in Zhuhai City between 2013 and 2021, along with their associated rainfall characteristics. The study concludes that the occurrence of landslides and collapses in Zhuhai City is closely related to the daily rainfall and the cumulative rainfall over of the previous four days, classifying these events as typical rainfall-induced collapses and landslides.By analyzing the relationship between hazard occurrence and rainfall, an E-D early warning model based on effective rainfall thresholds was established. The model was tested using 153 collapse and landslide geological disasters from 2021 to 2023 in Zhuhai, resulting in an early warning accuracy of 91.5%.A single early warning test on May 12, 2022, showed a hit rate of 94.7%, a missed report rate of 5.3%, and a false alarm rate of 16.2% for the first, second, and third-level warning zones. The E-D early warning rainfall threshold model established in this study is suitable for the actual conditions in Zhuhai and can provide technical support for improving threshold models in early warning systems. It also offers a reference method for studying early warning techniques for collapse and landslide hazards in similar granite regions.
ISSN:1003-8035