首页|Insights into Reservoir-Triggered Landslides Development and Its Influence Factors in the Three Gorges Reservoir Area,China

Insights into Reservoir-Triggered Landslides Development and Its Influence Factors in the Three Gorges Reservoir Area,China

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More than 5 000 landslides or potential landslides have been triggered in the Three Gorg-es Reservoir(TGR)area since the impoundment in 2003.This study aims at investigating the reservoir-induced landslides spatiotemporal and size distribution and its influence factors in the TGR by taking 790 landslides as statistical samples.The landslides exhibit significant regional and sub-regional spatial differences,and numerous landslides occurred at the initial three impoundment stages and the corre-sponding 2-3 cycles of reservoir operations followed,but the landslide frequency decreased dramatical-ly after 2010 from temporal perspective.The relationship between landslide development and topo-graphical,geological as well as hydrological factors were analyzed qualitatively.The reservoir-induced landslides in TGR area exhibit self-organized criticality and the rollover is nearly 2.5 x 104 m2,which could not be attributed to the missing data but the coupled influences imposed by affecting factors.Both the double Pareto and inverse gamma functions are more suitable than the power-law function to present the landslide size characteristics.In term of the fitting precious,the adaptability of the inverse gamma function is better if the landslide inventories are limited.The research results provide founda-tion for the landslide susceptibility maps and hazard risk assessment.

landslidesslope stabilityaffecting factorsThree Gorges Reservoirself-organized crit-icality

Shilin Luo、Da Huang、Jianbing Peng、Zhouzhou Xie、Zhiyu Yang、Roberto Tomás

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Hunan Provincial Key Laboratory for Big Data Smart Application of Natural Disaster Risks Survey of Highway Engineering,Changsha University,Changsha 410022,China

College of Civil Engineering and Geomatics,Chang'an University,Xi'an 710064,China

Hunan Provincial Key Laboratory for Big Data Smart Application of Natural Disaster Risks Survey of Highway Engineering,Changsha 410022,China

School of Civil Engineering,Central South University,Changsha 410075,China

Dpto.de Ingeniería Civil.Escuela Politécnica Superior de Alicante,Universidad de Alicante,Alicante E-03080,Spain

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2024

10.1007/s12583-024-0024-1

地球科学学刊(英文版)
中国地质大学

地球科学学刊(英文版)

CSTPCD
影响因子：0.724
ISSN：1674-487X
年,卷(期)：2024.35(6)