Quantitative risk assessment of the Shilongmen reservoir landslide in the Three Gorges area of China
Many landslides have been triggered by the fluctuation of reservoir water level in the Three Gorges Reservoir area (TGRA) of China. The current research lacks the quantitative risk assessment framework for reservoir landslides. In this study, the risk associated with the Shilongmen reservoir landsli...
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Veröffentlicht in: | Bulletin of engineering geology and the environment 2023-06, Vol.82 (6), Article 214 |
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Sprache: | eng |
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Zusammenfassung: | Many landslides have been triggered by the fluctuation of reservoir water level in the Three Gorges Reservoir area (TGRA) of China. The current research lacks the quantitative risk assessment framework for reservoir landslides. In this study, the risk associated with the Shilongmen reservoir landslide in TGRA is assessed by considering two hazard scenarios corresponding to the deformation and failure phases. The former is modeled via fully coupled finite element analyses, which take into account the reservoir water level and rainfall as triggering factors of landslide displacements; the latter, via the limit equilibrium method and Monte Carlo method, analyzes the failure probability under different conditions induced by the annual reservoir regulation and the return period of rainfall events. The vulnerability is quantitatively modeled as a function of both landslide intensity and the resilience of the elements at risk (EAR). In the deformation scenario, the expected monetary loss is estimated by multiplying the monetary value of the buildings for their vulnerability, and the corresponding risk map displays the potential economic losses to the EAR. In the failure scenario, direct (landslide) and indirect (tsunamis) risks are considered because the rapid decline of reservoir water level and heavy rainfall can cause the landslide rapidly sliding into the Yangtze River. Bearing in mind that there are several unstable slopes in the same geo-environmental context in the TGRA, the proposed research framework could provide a reference for government risk management strategies. |
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ISSN: | 1435-9529 1435-9537 |
DOI: | 10.1007/s10064-023-03242-z |