Abstract
Variations of reservoir water level and seasonal precipitation have reactivated or accelerated many reservoir landslides in the Three Gorges Reservoir area since impoundment in 2003. Updated daily monitoring data since 2017 reveals details about the step-like pattern of annual movement of the Baijiabao landslide, a large creeping landslide with a maximal cumulative surface displacement of 0.2 m over this 2-year period. The spatiotemporal deformation characteristics show that mass movement was greatest in 2017 and boundary cracks exhibit more frequent steps and are more sensitive to hydraulic factors than surface displacement. Acceleration periods are triggered when the reservoir water level falls below 153 m above mean sea level, with most annual movement occurring before the reservoir rises back to that critical level. The rate of daily surface movement is controlled by the daily variation of reservoir water level and by cumulative rainfall during the previous 1 to 7 days. The movement responses vary from different years and movement periods, but the one-factor critical-level model can effectively predict surface movement. The correlation between surface displacement rate and reservoir water level also comprehensively indicates the association between landslide movement and hydraulic factors including rainfall and variation of reservoir water level. Low reservoir level and its drawdown, and heavy or continuous rainfall, increase hydraulic gradients and change stress conditions, which destabilize the Baijiabao landslide and accelerate its surface movement.
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Acknowledgements
We sincerely acknowledge the collaborations with the National Field Observation and Research Station of Landslides in Three Gorges Reservoir Area of Yangtze River in China.
Funding
This work was supported by the National Natural Science Foundation of China (grant numbers 42107181 and 41922055), the National Key R&D Program of China (grant numbers 2018YFC1507200 and 2017YFC1501304), and the China Postdoctoral Science Foundation (grant number 2021M702932).
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Yao, W., Li, C., Guo, Y. et al. Short-term deformation characteristics, displacement prediction, and kinematic mechanism of Baijiabao landslide based on updated monitoring data. Bull Eng Geol Environ 81, 393 (2022). https://doi.org/10.1007/s10064-022-02912-8
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DOI: https://doi.org/10.1007/s10064-022-02912-8