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Spatial distribution and failure mechanism of water-induced landslides in the reservoir areas of Southwest China 被引量:2

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摘要 Water-induced landslides in hydropower reservoirs pose a great threat to both project operation and human life.This paper examines three large reservoirs in Sichuan Province,China.Field surveys,site monitoring data analyses and numerical simulations are used to analyze the spatial distribution and failure mechanisms of water-induced landslides in reservoir areas.First,the general rules of landslide development in the reservoir area are summarized.The first rule is that most of the landslides have rear edge elevations of 100e500 m above the normal water level of the reservoir,with volumes in the range of 106 e107 m 3.When the volume exceeds a certain amount,the number of sites at which the landscape can withstand landslides is greatly reduced.Landslide hazards mainly occur in the middle section of the reservoir and less in the annex of the dam site and the latter half of the reservoir area.The second rule is that sedimentary rocks such as sandstone are more prone to landslide hazards than other lithologies.Then,the failure mechanism of changes in the water level that reduces the stability of the slope composed of different geomaterials is analyzed by a proposed slope stability framework that considers displacement and is discussed with the monitoring results.Permeability is an essential parameter for understanding the diametrically opposed deformation behavior of landslides experiencing filling-drawdown cycles during operation.This study seeks to provide inspiration to subsequent researchers,as well as guidance to technicians,on landslide prevention and control in reservoir areas.
出处 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2023年第2期442-456,共15页 岩石力学与岩土工程学报(英文版)
基金 We gratefully acknowledge the support of the National Key R&D Program of China(Grant No.2017YFC1501102) the National Nat-ural Science Foundation of China(Grant No.41977229) the Sichuan Youth Science and Technology Innovation Research Team Project(Grant No.2020JDTD0006).
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