Deformation characteristics and reactivation mechanisms of the Outang ancient landslide in the Three Gorges Reservoir, China

Luo, Shilin; Huang, Da

doi:10.1007/s10064-020-01838-3

Cited by 34 publications

(7 citation statements)

References 37 publications

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“…To further confirm the slip surface position, we compared the results regarding deep-seated deformation at this section of the landslide. Figure 4b depicts that the nearby inclinometer has detected the slip surface at a depth of ∼24 m (Luo & Huang, 2020), which validates the identification that the slip surface was revealed by our borehole deployment. The depth discrepancy is considered acceptable considering the complex microrelief and difference in stratigraphy.…”

Section: Identification Of Driving the Accelerated Movementsupporting

confidence: 79%

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Subsurface Multi‐Physical Monitoring of a Reservoir Landslide With the Fiber‐Optic Nerve System

Zhu

Wang

et al. 2022

Geophysical Research Letters

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Reservoir landslides are typical geohazards with sophisticated thermo‐hydro‐mechanical interactions. However, direct observations of subsurface multi‐physical processes in bank slopes remain rare. Herein we present the design, implementation and evaluation of an innovative fiber‐optic nerve system based on weak‐reflection fiber Bragg grating to monitor a giant landslide located in the Three Gorges Reservoir region, China. The system is capable of measuring and imaging spatiotemporal distributions of temperature, moisture and strain along boreholes in near real‐time. Such visual profiles offer unique insights into the subsurface thermo‐hydro‐mechanical link between external conditions and geotechnical deformation, making it possible to decipher the substantial trigger of accelerated movements. Multi‐physical responses at depths of interest also enable us to better understand the evolution mechanism of reservoir landslides. Fiber‐optic nerve sensing can synergize with remote sensing and surface‐based technologies to build a space‐sky‐ground‐subsurface integrated monitoring system for landslides.

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Section: Identification Of Driving the Accelerated Movementsupporting

confidence: 79%

“…(a) Strain in Borehole FOS1. (b) Displacement measured by the probe inclinometer I5 adjacent to Borehole FOS1 (adapted from Luo & Huang, 2020). (c) Surface displacement recorded by GNSS.…”

Section: Identification Of Driving the Accelerated Movementmentioning

confidence: 99%

Subsurface Multi‐Physical Monitoring of a Reservoir Landslide With the Fiber‐Optic Nerve System

Zhu

Wang

et al. 2022

Geophysical Research Letters

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“…According to the second and third phase of survey and prevention works of geological disasters in the TGR, the number of dual-structure landslides account for near 80% of the total landslide events (Tang, 2013). Generally, the dual-structure landslides can be divided into three parts: deposit (mobilized materials), bedding and DBI (means interface between deposit and bedding) (Caballero et al, 2002;Yang, 2019;Chen et al, 2005;Igwe, 2015;Luo and Huang, 2020). The dual-structure landslide stability was often assessed once the relatively larger slope deformation was monitored by in situ instruments and signs of activity were observed.…”

Section: Introductionmentioning

confidence: 99%

Influence of permeability on the stability of dual-structure landslide with different deposit-bedding interface morphology: The case of the three Gorges Reservoir area, China

Luo

Huang

Peng

et al. 2022

Engineering Geology

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“…Current research on reservoir landslides mainly focuses on soil landslides with more severe deformation, such as Shuping landslide (Song et al, 2018), Xintan landslide (Chen et al, 2021). There are many research methods including the extraction of field monitoring data and field investigations to analyze the response of landslide deformation to changes in the reservoir water level (Yao et al, 2019;Luo and Huang 2020;Yi et al, 2022). On this basis, some scholars have established an physical landslide model to analyze the deformation process of the landslide, measure the change in the pore water pressure in the slope as the reservoir water level rises and falls, and understand the deformation mechanism of the landslide (He et al, 2018;.…”

Section: Introductionmentioning

confidence: 99%

Influencing factors, deformation mechanism and failure process prediction for reservoir rock landslides: Tanjiahe landslide, three gorges reservoir area

Chen

Zhang²,

Wang³

et al. 2022

Front. Earth Sci.

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Compared with terrestrial rock landslides, reservoir rock landslides are also affected by the rise and fall of the reservoir water level, and these landslides are more threatening. High-speed debris flows may form once they lose stability, and once they enter the water a surge is formed. This endangers the safe operation of reservoirs. This study explored the deformation characteristics and influencing factors of the Tanjiahe reservoir rock landslide in the Three Gorges Reservoir using field investigations, GPS surface displacement monitoring, and groundwater level monitoring. The discrete element system MatDEM was used to simulate failure motion, and predict the hazard area affected by the Tanjiahe landslide. The results show that within the reservoir water variation section (145-175 m), the Tanjiahe landslide mass was composed of surface soil (156-175 m) with low permeability and deep cataclastic rock (145-156 m) with high permeability. Due to the difference in permeability between the deep and surface layers, the response of landslide deformation to water level rise is not obvious. The high-level (175 m) operation of the reservoir and the decline in the reservoir water level (175-145 m) are key factors affecting the landslide deformation. Rainfall had a positive effect on landslide deformation. Under their combined action, the stability of the front gentle antisliding section of the landslide decreases, and the displacement of the middle and rear steeper sliding section increases under the driving force, which may lead to slope failure. The simulation results show that the upper part of the Tanjiahe landslide slides first and pushes the lower part to move, which is a typical of thrust load-caused failure. The speed of the sliding mass has three stages: rapid rise, rapid decline, and slow decline. The higher the slope angle, the higher the acceleration of the sliding mass in the direction parallel to the slope surface, the higher the speed peak value and the faster the sliding mass speed reaches the peak value. During the failure process, energy is transferred between sliding mass through collisions. Landslides can easily lead to debris flow. The maximum height of the first wave generated when the debris flow entered the water is 5.95 m, and the wave height that propagated to the

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Deformation characteristics and reactivation mechanisms of the Outang ancient landslide in the Three Gorges Reservoir, China

Cited by 34 publications

References 37 publications

Subsurface Multi‐Physical Monitoring of a Reservoir Landslide With the Fiber‐Optic Nerve System

Subsurface Multi‐Physical Monitoring of a Reservoir Landslide With the Fiber‐Optic Nerve System

Influence of permeability on the stability of dual-structure landslide with different deposit-bedding interface morphology: The case of the three Gorges Reservoir area, China

Influencing factors, deformation mechanism and failure process prediction for reservoir rock landslides: Tanjiahe landslide, three gorges reservoir area

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