Volume 41 Issue 6
Nov.  2022
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Cong Kai, Wei Jie, Yang Yabing, Chen Long, Zhang Tongwei, Li Sheng, Fu Zhou, Zhang Tongwen, Zhang Fanyu. Investigation of the kinematic characteristic of Lijie Beishan landslide through surface displacement monitoring and rainfall response numerical simulation[J]. Bulletin of Geological Science and Technology, 2022, 41(6): 54-65. doi: 10.19509/j.cnki.dzkq.2022.0234
Citation: Cong Kai, Wei Jie, Yang Yabing, Chen Long, Zhang Tongwei, Li Sheng, Fu Zhou, Zhang Tongwen, Zhang Fanyu. Investigation of the kinematic characteristic of Lijie Beishan landslide through surface displacement monitoring and rainfall response numerical simulation[J]. Bulletin of Geological Science and Technology, 2022, 41(6): 54-65. doi: 10.19509/j.cnki.dzkq.2022.0234

Investigation of the kinematic characteristic of Lijie Beishan landslide through surface displacement monitoring and rainfall response numerical simulation

doi: 10.19509/j.cnki.dzkq.2022.0234
  • Received Date: 28 Mar 2022
  • Slope kinematics is normally used to evaluate the temporal and spatial evolution of landslides. The inverse velocity method (INV) is an important tool for predicting the initiation of landslide, but its correlation with the physical and mechanical mechanisms of multiple physical fields inside the landslide need to be further clarified. In this paper, the slope deformation and geological characteristics of the Lijie Beishan landslide in Zhouqu, Gansu Province was investigated. The inverse velocity method, velocity threshold method and numerical simulation based on unsaturated soil theory were used to study the kinematic characteristic of slope. The results showed that after the lowest value of the inverse velocity on June 3, 2021, a stable stage lasted for approximately 60 days and then suddenly accelerated on September 20. The velocity became more than 200 mm/d over 20 days, and the deformation did not converged. There was an obvious acceleration point in the time-dependent inverse velocity curve. The end of the landslide life cycle was obtained by extending the straight line after the onset of the acceleration point. The prediction period was within 8 days compared to the actual instability startup, and the landslide was predicted 130 days in advance. According to the post analysis of the whole time-dependent velocity curve, the multi-level speed thresholds of v1=20 mm/d, v2=60 mm/d, and v3=100 mm/d were set up. Because there were two peaks of velocity, the prediction of landslide triggering was lagging compared to the inverse velocity method. The coupling of slope stresses, deformation and pore water transportation was simulated. The results showed that the inflection point of the time-dependent deformation curve was correlated with the increase in precipitation intensity, and the cumulative precipitation was negatively exponentially correlated with the safety factor. The cumulative deformation obtained by numerical simulation was 2 250 mm, the velocity of deformation was 10-35 mm/d, and the inverse velocity was 0.03-0.12 d/mm, which were close to the actual monitoring data. However, there was still a deviation between the prediction of the inflection point of slope deformation and the actual situation.

     

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