Frontiers in Earth Science (Jan 2023)

A quantitative enhanced assessment for ancient landslide reactivation risk considering cross-time scale joint response mechanism

  • Zixi Yang,
  • Tingchen Wu,
  • Chao E,
  • Chao E,
  • Xiao Xie,
  • Xiao Xie,
  • Leiqi Tan,
  • Leiqi Tan,
  • Leiqi Tan,
  • Xinxi Jiang

DOI
https://doi.org/10.3389/feart.2022.974442
Journal volume & issue
Vol. 10

Abstract

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Ancient landslide has strong concealment and disturbance sensitivity due to its special geotechnical mechanical characteristics, and it is the potential hazard that cannot be ignored in human activities and major engineering planning. The quantitative assessment of ancient landslide reactivation risk has become more necessary for pre-disaster scientific warning. However, because the mechanisms of deformation and damage during the evolution of ancient landslides are quite complex, traditional landslide risk assessment methods only select the single-time scale and relatively stable environmental factors for analysis, lacking consideration of dynamic triggering factors such as rainfall. Focusing on the complexity, a quantitative enhanced assessment for ancient landslide reactivation risk considering cross-time scale joint response mechanism is proposed. First, on the basis of systematic analysis of the implicit genesis mechanism and explicit characterization, an evaluation system of the cross-time scale joint characteristics of ancient landslide reactivation is constructed. Then, XGBoost algorithm and SBAS-InSAR are used to establish the long-time scale developmental evolution mechanism model and the short-time scale dynamical trigger model, respectively. Subsequently, we propose a cross-time scale joint response mechanism. The information entropy weight method is applied to calculate the contribution degree of long-short time scale assessment models for ancient landslide reactivation based on the constraints of quantitative interval thresholds, and the assessment processes of different time scales are dynamically and quantitatively correlated. Finally, the updated optimization of the assessment of ancient landslide reactivation risk is achieved. In this research, experimental analysis was carried out for ancient landslide groups in a geological hazard-prone area in Fengjie County, Chongqing, a typical mountainous region of China. The results of the comparative analysis validate the superiority of the method in this paper. It helps to accurately assess the ancient landslide potential hazard in advance, providing scientific basis and technical support for the risk assessment of mountainous watershed geological hazards and major engineering projects.

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