The evolution of the Samaoding paleolandslide river blocking event at the upstream reaches of the Jinsha River, Tibetan Plateau

Bao, Yiding; Zhai, Shijie; Chen, Jianping; Xu, Peng; Sun, Xiaohui; Zhan, Jiewei; Zhang, Wen; Zhou, Xin

doi:10.1016/j.geomorph.2019.106970

Cited by 61 publications

(27 citation statements)

References 85 publications

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“…First, the landslide dam remnants on the right bank of the river are removed on the basis of borehole data and the morphology of the residual dam. Then, according to the morphology of the trailing edge and the slopes along the Jinsha River, the ground surface in the sliding area is restored to the natural angle of repose (Bao et al 2020). Landslide dam relics on the left bank were not taken into account in the restoration of the terrain in this study, because the volume is relatively small compared to the entire landslide mass.…”

Section: Landslide Runout Model and Parametersmentioning

confidence: 99%

Combined numerical investigation of the Gangda paleolandslide runout and associated dam breach flood propagation in the upper Jinsha River, SE Tibetan Plateau

et al. 2022

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A large paleolandslide occurred opposite the Gangda village in the upper Jinsha River, SE Tibetan Plateau. Field geological investigations and remote sensing indicated that the Gangda paleolandslide once blocked the Jinsha River. Evidence of river blocking, including landslide dam relics, upstream lacustrine sediments, and downstream outburst sediments, has been well preserved. To understand the river-blocking event including landslide, dam breach, and associated outburst flooding, optically stimulated luminescence (OSL) dating and numerical simulations were performed in this study. OSL dating results showed that the paleolandslide dam was formed at 5.4 ± 0.5 ka BP and breached at 3.4 ± 0.3 ka BP, indicating that the dam lasted approximately 2000 years. The discrete element method was used to simulate the dynamics of the Gangda rock landslide based on the restored topography, while a fluid-solid coupling model was performed to simulate the landslide dam breaching and flooding. The fluid-solid coupling model can simultaneously reflect the process of landslide-dam collapse and the propagation of outburst flood. The simulated results indicate that the whole landslide process lasted about 60 s with a peak velocity of 38 m/s. It is significant that the simulated morphology of the residual landslide dam and downstream outburst sediments is consistent with the field observations. The combined numerical investigation in this paper provided new insights into the research of landscape evolution and helped to understand the chain disaster of landslide, dam breach, and flooding.

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Section: Landslide Runout Model and Parametersmentioning

confidence: 99%

Combined numerical investigation of the Gangda paleolandslide runout and associated dam breach flood propagation in the upper Jinsha River, SE Tibetan Plateau

et al. 2022

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“…Landslide is a kind of natural hazard in the mountainous regions, threatening human life and property [1][2][3][4]. Over the past decades, the huge catastrophe ability of landslides attracted many researchers to devote themselves to assessing landslide susceptibilities [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

GIS-Based Landslide Susceptibility Mapping Using Information, Frequency Ratio, and Artificial Neural Network Methods in Qinghai Province, Northwestern China

Wang

Chen

2021

Advances in Civil Engineering

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Landslides are one of the nature hazards causing a lot of casualties and property losses in the world. Over the last decades, many researchers have made contributions in landslide susceptibility maps using qualitative and quantitative methods. Parameters of DEM, geology, etc. are selected to analyze the mechanism of landslides. The quality of data is essential in the landslide studies, and more credible results can be obtained if the data is adequate and accurate from the wide range of parameters. The aim of this study is to evaluate the landslide susceptibility of Huangyuan County of Qinghai. Through field investigations, 100 landslide disaster locations in the study area were selected, and 11 influencing factors including elevation, slope, aspect, plane curvature, profile curvature, road distance, river distance, fault distance, stratum rock property, vegetation coverage index, and terrain humidity index were selected as the influencing factors of landslide disaster based on GIS. In this paper, the information method (IM) model, frequency ratio (FR) model, and artificial neural network (ANN) model are used to evaluate the susceptibility of geological hazards, and the receiver operating characteristic (ROC) curve of disaster points at different levels is used to test the evaluation accuracy of three models. The results show that factors that have great influence on landslides are associated with witness, and the terrain humidity index has the highest weight in the occurrences of landslide. The values of AUC indicate that the ANN model is the best evaluation model suitable for the study area and can be extremely useful for landslide hazard mitigation strategies. Based on the calculation of ANN model, three valley areas are determined with high landslide susceptibility, and necessary reinforcement measures should be taken.

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“…The Three Gorges Reservoir area (TGRA) is significantly affected by catastrophic landslides, and the colluvial landslides often occur in this area due to reservoir water level changes [11]. Since June 2003 when the Three Gorges Pro-ject was completed, around 2619 landslides have failed due to the fluctuation of the reservoir water level, and 670 mountains are under unstable status [5][6][7][12][13][14][15][16][17][18][19][20]. Therefore, it is important to study the failure mechanism to provide guideline for the risk assessment of the landslides.…”

Section: Introductionmentioning

confidence: 99%

Failure Mechanism of Colluvial Landslide Influenced by the Water Level Change in the Three Gorges Reservoir Area

et al. 2021

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The stability of the reservoir bank landslide is affected by a variety of external factors, and the fluctuation of reservoir water level is one of the important influencing factors. The Erdaohe landslide is a typically colluvial landslide in the Three Gorges Reservoir area with periodic reservoir water level fluctuations. According to landslide displacement data, the displacement of the Erdaohe landslide exhibits the significantly stepwise feature. Its failure mechanism was analyzed using strength reduction method by the FLAC3D package in the case of reservoir water level changes. The results indicate that the hydrodynamic pressure has an important impact on the initialization of the landslide failure. When reservoir water level rises rapidly or maintains constant at the lower level, the landslide stability would be higher. When the reservoir water level decreases rapidly or maintains constant at the higher level, the landslide stability will be smaller. When the reservoir water level was in the lowest elevation, the factor of safety (FS) reached the minimum value of 1.11. Findings in this paper can provide guidelines for the risk assessment of colluvial landslides.

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The evolution of the Samaoding paleolandslide river blocking event at the upstream reaches of the Jinsha River, Tibetan Plateau

Cited by 61 publications

References 85 publications

Combined numerical investigation of the Gangda paleolandslide runout and associated dam breach flood propagation in the upper Jinsha River, SE Tibetan Plateau

Combined numerical investigation of the Gangda paleolandslide runout and associated dam breach flood propagation in the upper Jinsha River, SE Tibetan Plateau

GIS-Based Landslide Susceptibility Mapping Using Information, Frequency Ratio, and Artificial Neural Network Methods in Qinghai Province, Northwestern China

Failure Mechanism of Colluvial Landslide Influenced by the Water Level Change in the Three Gorges Reservoir Area

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