Regional Landslide Hazard Assessment Using Extreme Value Analysis and a Probabilistic Physically Based Approach

Hyuck-Jin Park, Kang-Min Kim, In-Tak Hwang and Jung-Hyun Lee
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Hyuck-Jin Park: Department of Energy Resources and Geosystem Engineering, Sejong University, Seoul 05006, Korea
Kang-Min Kim: Department of Geography, Kyung Hee University, Seoul 02453, Korea
In-Tak Hwang: Department of Energy Resources and Geosystem Engineering, Sejong University, Seoul 05006, Korea
Jung-Hyun Lee: Department of Energy Resources and Geosystem Engineering, Sejong University, Seoul 05006, Korea

Sustainability, 2022, vol. 14, issue 5, 1-17

Abstract: The accurate assessment of landslide hazards is important in order to reduce the casualties and damage caused by landslides. Landslide hazard assessment combines the evaluation of spatial and temporal probabilities. Although various statistical approaches have been used to estimate spatial probability, these methods only evaluate the statistical relationships between factors that have triggered landslides in the past rather than the slope failure process. Therefore, a physically based approach with probabilistic analysis was adopted here to estimate the spatial distribution of landslide probability. Meanwhile, few studies have addressed temporal probability because historical records of landslides are not available for most areas of the world. Therefore, an indirect approach based on rainfall frequency and using extreme value analysis and the Gumbel distribution is proposed and used in this study. In addition, to incorporate the nonstationary characteristics of rainfall data, an expanding window approach was used to evaluate changes in the mean annual maximum rainfall and the location and scale parameters of the Gumbel distribution. Using this approach, the temporal probabilities of future landslides were estimated and integrated with spatial probabilities to assess and map landslide hazards.

Keywords: temporal probability; spatial probability; landslide hazard; physically based model; extreme value analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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