Long-term three-dimensional deformation monitoring and risk assessment of the Guba landslide, Tibetan Plateau

Abstract High-elevation and long-runout landslides are among the most destructive mountain hazards. In this study, we present the first identification of a high-elevation and long-runout landslide, referred to as the Guba landslide, located near the Jinsha River Bridge, using interferometric synthetic aperture radar (InSAR) technology. This landslide poses a significant threat to the construction and future safe operation of both the Jinsha River Bridge and the Yebatan hydropower station. Therefore, deformation monitoring and risk assessment based on comprehensive remote sensing and numerical simulation are urgently required. We processed SAR imagery acquired from four satellite platforms between July 2007 and September 2023 to derive surface displacements of the Guba landslide. A topography-constrained model integrating multi-track SAR observations was employed to retrieve the three-dimensional deformation field and determine the optimal sliding direction for each pixel, enabling estimation of the potential slip surface. Furthermore, a Tikhonov regularization method was applied to reconstruct a nearly 16-year displacement time series along the sliding direction. To assess potential hazards, numerical simulations were conducted to estimate the extent and impact of possible landslide failures. Results show that the Guba landslide is a large-scale rockslide with an area of approximately 0.17 km 2 , a maximum slip surface depth of 94 mm and an estimated volume of 0.84×10 7 m 3 . The cumulative displacement of the landslide between 2007 and 2023 reached 1.37 m, and it is currently in an initial accelerated sub-phase. Numerical simulation results suggest that once failed, the landslide mass could move rapidly along the valley, forming a debris dam approximately 40–50 m high and 200 m wide across the Jinsha River, which poses a severe risk to both the bridge and the hydropower station. In addition, local seasonal deformation oscillations were observed, potentially driven by the coupled effects of precipitation and near-surface temperature. Further wavelet analysis revealed a time lag of approximately 39 days between deformation, rainfall, and near-surface temperature. These findings offer critical insights into the mitigation and management of the Guba landslide, supporting the safe implementation of major infrastructure projects. Moreover, the approach provides a novel framework for investigating high-elevation and long-runout landslides in inaccessible mountainous regions.

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Publication Details

Journal
Science China Earth Sciences
Published
2025-09-04
DOI
https://doi.org/10.1007/s11430-024-1654-6
Citations
3
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
7.27
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article

Long-term three-dimensional deformation monitoring and risk assessment of the Guba landslide, Tibetan Plateau

Jianbing Peng, Liangwen Jiang, Zhenhong Li, Chuang Song et al.
3 citations
Science China Earth Sciences
Landslides and related hazards
7.27
article

Long-term three-dimensional deformation monitoring and risk assessment of the Guba landslide, Tibetan Plateau

Jianbing Peng, Liangwen Jiang, Zhenhong Li, Chuang Song, Wu Zhu, Y. Liu, Qiang Xu, Bo Chen, Jiantao Du, Mingtao Ding
article en
3 citations

Abstract

Abstract High-elevation and long-runout landslides are among the most destructive mountain hazards. In this study, we present the first identification of a high-elevation and long-runout landslide, referred to as the Guba landslide, located near the Jinsha River Bridge, using interferometric synthetic aperture radar (InSAR) technology. This landslide poses a significant threat to the construction and future safe operation of both the Jinsha River Bridge and the Yebatan hydropower station. Therefore, deformation monitoring and risk assessment based on comprehensive remote sensing and numerical simulation are urgently required. We processed SAR imagery acquired from four satellite platforms between July 2007 and September 2023 to derive surface displacements of the Guba landslide. A topography-constrained model integrating multi-track SAR observations was employed to retrieve the three-dimensional deformation field and determine the optimal sliding direction for each pixel, enabling estimation of the potential slip surface. Furthermore, a Tikhonov regularization method was applied to reconstruct a nearly 16-year displacement time series along the sliding direction. To assess potential hazards, numerical simulations were conducted to estimate the extent and impact of possible landslide failures. Results show that the Guba landslide is a large-scale rockslide with an area of approximately 0.17 km 2 , a maximum slip surface depth of 94 mm and an estimated volume of 0.84×10 7 m 3 . The cumulative displacement of the landslide between 2007 and 2023 reached 1.37 m, and it is currently in an initial accelerated sub-phase. Numerical simulation results suggest that once failed, the landslide mass could move rapidly along the valley, forming a debris dam approximately 40–50 m high and 200 m wide across the Jinsha River, which poses a severe risk to both the bridge and the hydropower station. In addition, local seasonal deformation oscillations were observed, potentially driven by the coupled effects of precipitation and near-surface temperature. Further wavelet analysis revealed a time lag of approximately 39 days between deformation, rainfall, and near-surface temperature. These findings offer critical insights into the mitigation and management of the Guba landslide, supporting the safe implementation of major infrastructure projects. Moreover, the approach provides a novel framework for investigating high-elevation and long-runout landslides in inaccessible mountainous regions.

Science China Earth SciencesVol. 68(10)
Ministry of Education of the People's Republic of China (CN), Ministry of Natural Resources (CN), Chang'an University (CN), Chengdu University of Technology (CN), Ministry of Natural Resources (RW), China Railway Group (China) (CN), China Railway Eryuan Engineering Group Co.
Openalex Percentile: Top 3%
Landslides and related hazards
7.27
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