期刊
COLD REGIONS SCIENCE AND TECHNOLOGY
卷 218, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.coldregions.2023.104056
关键词
Wet snow; Slab avalanches; Blade hardness; Shear strength; Liquid water content
The formation of wet-snow slab avalanches is related to the liquid water content and strength of the snow layers. However, current studies disagree on this relationship and there is limited understanding of snow layers with a saturation level of θ=7% and above.
The rapid weakening of snow layers that accumulate infiltrating liquid water is a well-known, but poorly quantified, mechanism for wet-snow slab avalanche formation. Therefore, quantifying this mechanical process is a crucial part of forecasting these snow avalanches accurately. Currently, studies do not agree on how snow strength should change as a function of volumetric liquid water content (theta) and whether this relationship differs between snow types. Furthermore, strength measurements taken at or above theta=7% in snow are rare, so there is limited understanding at this end of the theta continuum. These levels of saturation can occur in the snow immediately above hydraulic barriers and are considered important for wet-snow slab avalanches to initiate. To address this knowledge gap, a blade hardness gauge (BHG, a.k.a. thin blade penetrometer) and SLF snow sensor were used to take 349 targeted paired measurements of strength and theta, respectively, in the snow above 19 manually wetted hydraulic (capillary) barriers. Using a multiple regression analysis, we developed an expression for the blade hardness of manually wetted snow as a function of theta, crystal form, and blade hardness prior to wetting (R-2=0.85). To understand these results in terms of a common measure of snow strength, we also performed a comparison of the BHG and a shear frame in dry snow. The two instruments are highly linearly correlated (R-2=0.94), allowing us to interpret our regression in terms of shear strength when compressive stress is low. Our results demonstrate that short-term (< 2 h) changes in snow strength due to increasing theta can differ between snow layers. These differences can be empirically modelled using easily measured dry snow properties (i.e. crystal form and blade hardness), which could allow avalanche forecasters to be more selective when identifying failure layers in advance of a wetting event.
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