Influence mechanism of local terrain features on snow avalanche dynamics

被引:0
作者
Ge, MengLin [1 ]
Li, XingYue [1 ,2 ]
Huang, Yu [1 ,2 ]
Gaume, Johan [3 ,4 ,5 ]
机构
[1] Department of Geotechnical Engineering, College of Civil Engineering, Tongji University, Shanghai
[2] State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai
[3] Institute for Geotechnical Engineering, ETH Zurich, Zurich
[4] WSL Institute for Snow and Avalanche Research, SLF, Flüelastrasse 11, Davos
[5] Climate Change, Extremes, and Natural Hazards in Alpine Regions Research Center, CERC, Davos
关键词
dynamic behavior; local terrain feature; material point method; snow avalanche;
D O I
10.1360/SST-2024-0324
中图分类号
学科分类号
摘要
Snow avalanches pose significant risks, including casualties and economic losses. Mitigating these hazards relies on accurately assessing the dynamic behavior of avalanches on real terrain. However, the complex local features of real terrain and their uncertain influence on avalanche dynamics present significant challenges to accurate evaluations. This study employs the material point method alongside an elastic–plastic constitutive model to investigate avalanches on real terrains through numerical simulations. The avalanche dynamics were analyzed from release to deposition, with a focus on the effects of local terrain features. The results indicate that avalanche flow is more confined to local concave terrain compared to convex terrain. For the concave terrain, the transition from steep to gentle slopes enhances the friction and collisions between the flow and the slope surface, decreasing flow velocity. Conversely, for the convex terrain, the flow velocity can either increase or decrease depending on the interaction between incoming flow characteristics and the downstream slope inclination. Regarding avalanche deposition behavior, the study identifies a critical flow depth inversely related to the slope angle. When the flow depth of the avalanche tail falls below the critical value, deposition begins. Therefore, the critical flow depth serves as the upper limit for evaluating deposition height in the context of this study. Furthermore, the runout distance of avalanches can be predicted using linear regression, incorporating the runout angle and the standard deviation of the slope angle. These two parameters capture cumulative movement distance and terrain roughness, respectively. Terrain with smaller runout angles and higher slope standard deviation tends to result in longer runout distances. The outcomes from this study help better evaluate and mitigate snow avalanches on real terrain. © 2025 Science Press. All rights reserved.
引用
收藏
页码:1043 / 1054
页数:11
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