Influence mechanism of local terrain features on snow avalanche dynamics

<p indent="0mm">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.

Authors

Publication Details

Journal
Scientia Sinica Technologica
Published
2025-03-07
DOI
https://doi.org/10.1360/sst-2024-0324
Citations
2
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
4.84
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article

Influence mechanism of local terrain features on snow avalanche dynamics

Min Ge, Johan Gaume, Li Xingyue, Yu Huang
2 citations
Scientia Sinica Technologica
Landslides and related hazards
4.84
article

Influence mechanism of local terrain features on snow avalanche dynamics

Min Ge, Johan Gaume, Li Xingyue, Yu Huang
article en
2 citations

Abstract

<p indent="0mm">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.

Scientia Sinica TechnologicaVol. 55(6)
Openalex Percentile: Top 7%
Landslides and related hazards
4.84
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