Dynamic process analysis of the Xinmo landslide via seismic signal and numerical simulation

被引:0
|
作者
Wenbin Chang
Qiang Xu
Xiujun Dong
Yu Zhuang
Aiguo Xing
Quan Wang
Xiangzhao Kong
机构
[1] Shanghai Jiao Tong University,State Key Laboratory of Ocean Engineering
[2] Chengdu University of Technology,State Key Laboratory of Geohazards Prevention and Geoenvironment Protection
来源
Landslides | 2022年 / 19卷
关键词
Xinmo landslide; Landslide seismology; Dynamic analysis; Runout behavior; DAN3D;
D O I
暂无
中图分类号
学科分类号
摘要
On 24 June 2017, a rockslide-debris avalanche occurred in Xinmo Village, Maoxian County, Sichuan Province, China. The displaced materials traveled approximately 2.6 km and caused 83 casualties. Combined with the field investigation, seismic signal, and numerical simulation, the dynamic process and deposit characteristics of the Xinmo landslide were analyzed. Based on the Arias intensity and Hibert time–frequency analysis of the seismic signal, the Xinmo landslide is determined to have a total duration of 120 s and with three-stage dynamic processes, namely, the initial accelerating stage (50 s), erosion impact stage (50 s), and accumulation stage (20 s). Then, taking the field investigation results, the total duration, and kinetic parameters inverted from the seismic signal as criteria, the DAN3D (Dynamic Analysis of Landslides) was employed to reconstruct the dynamic process of the Xinmo landslide. The results show that the erosion and deposit depth distributions obtained from the simulation are in agreement with the pre- and post-landslide DEM (digital elevation model) data and field results. Further, the three-stage dynamic processes (40 s, 60 s, 20 s) obtained from the numerical simulation are also close to the seismic analysis results. In this study, the results of the field investigation and seismic analysis provide a more detailed set of inversion criteria for the numerical simulation work, which contributes to reconstructing the dynamic processes of the Xinmo landslide more accurately. Based on the approach of multi-source data collaboration in this paper, those landslides that lack direct observation data can be better understood and the numerical parameters used for landslide dynamics inversion are better calibrated, which can be applied to predict the runout behavior and disaster scope of potential landslides in the immediate area.
引用
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页码:1463 / 1478
页数:15
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