Prompt Quantitative Risk Assessment for Rain-Induced Landslides
Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 149, Issue 5
Abstract
An extreme rainstorm can cause thousands of landslides and kill hundreds of people. In the changing climate, fatal rainstorms become more frequent and intense. The current landslide emergency management evaluates hazard intensities but lacks key information on likely consequences. This study presents a novel prompt quantitative risk assessment method for rain-induced landslides. The proposed method automatically generates a one-page risk assessment report within minutes to support effective risk communication, resource allocation, and emergency response. The propagation of uncertainties is quantified in a scientific probabilistic framework. The proposed method is tested using 83 major rainstorms during 1995–2016 in Hong Kong. The method accurately predicts the number of affected buildings and the number of potential fatalities and identifies rainstorms that can trigger fatal landslides. The proposed method contributes to the advancement of landslide emergency management from hazard-informed to risk-informed, which will significantly enhance societal resilience and facilitate climate change adaptation.
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Data Availability Statement
All the datasets and base maps of Hong Kong in this study are provided and owned by HKSARG and can be accessed from DATA.GOV.HK or through the links in Table 1. Alternative sources are also provided in Table 1 to facilitate the application of the proposed method to other regions. The computer codes of PoLA are available on GitHub (https://github.com/JianH-coding/PoLA).
Acknowledgments
This work was supported by the National Key Research and Development Program of the Ministry of Science and Technology of China (Project No. 2021YFC3001000), the Science and Technology Plan of Shenzhen, China (Project No. JCYJ20180507183854827), the Research Grants Council of the Hong Kong Special Administrative Region Government (Project Nos. 16203720 and AoE/E-603/18), and the Project of Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone (HZQB-KCZYB-2020083). The authors would also like to thank the Government of Hong Kong Special Administrative Region for providing all the datasets.
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Published In
Journal of Geotechnical and Geoenvironmental Engineering
Volume 149 • Issue 5 • May 2023
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© 2023 American Society of Civil Engineers.
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Received: Apr 18, 2022
Accepted: Nov 22, 2022
Published online: Mar 1, 2023
Published in print: May 1, 2023
Discussion open until: Aug 1, 2023
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