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Monitoring Yanwan deep-seated toppling deformation with the impact of water-level fluctuation by SAR observations

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Abstract

Reservoir filling in large hydropower stations triggers or accelerates deep-seated toppling deformations (DSTDs). In the absence of large failures, toppling can often last long. It is of great significance to study the mechanism of DSTDs for the prediction of affected areas before filling. Taking Yanwan (YW) DSTDs in Xiluodu Reservoir as a sample, we collected 17 scenes of ALOS/PALSAR-1 images and 45 scenes of ALOS/PARSAR-2 images and used the small baseline subset interferometry synthetic aperture radar (SBAS-InSAR) and time-series offset tracking (TSOT) technologies to analyze the spatiotemporal evolution of YW DSTDs before and after reservoir filling. The correlation between deformation and reservoir filling was analyzed with the fluctuation in the reservoir water level. Before filling, there was no deformation in the area of YW DSTDs. After filling, the maximum deformation rate of YW DSTDs measured by TSOT during the study period was around 1500 mm/year in the line-of-sight (LOS) direction. YW DSTDs showed a fluctuating deformation trend, and the deformation rates of the four filling stages were successively from fast to slow: rapid drawdown of water level period, high water level period, low water level period, and rapid rise of water level period. The soft-hard-interbedded structure provides favorable lithology conditions for toppling. The incision of the Jinsha River and the development of gullies led to the topographic condition of exposure on three sides, shaping a convex slope similar to a triangular cone, which provides advantageous topographic conditions for toppling.

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Funding

This work was supported by the Chinese Geological Survey Project (No. DD20230433), China, Three Gorges Corporation (YMJ(BHT)/(21)036, YMJ(XLD) (19)110).

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Correspondence to Xin Yao.

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The authors declare no competing interests.

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Ren, K., Li, R., Yao, X. et al. Monitoring Yanwan deep-seated toppling deformation with the impact of water-level fluctuation by SAR observations. Landslides 21, 1243–1254 (2024). https://doi.org/10.1007/s10346-024-02220-0

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  • DOI: https://doi.org/10.1007/s10346-024-02220-0

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