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Evaluation of slope stability with respect to snowpack spatial variability
Author(s) -
Gaume J.,
Schweizer J.,
Herwijnen A.,
Chambon G.,
Reuter B.,
Eckert N.,
Naaim M.
Publication year - 2014
Publication title -
journal of geophysical research: earth surface
Language(s) - English
Resource type - Journals
eISSN - 2169-9011
pISSN - 2169-9003
DOI - 10.1002/2014jf003193
Subject(s) - snowpack , snow , spatial variability , slab , elasticity (physics) , geotechnical engineering , smoothing , geology , stability (learning theory) , slope stability , environmental science , materials science , mathematics , statistics , computer science , geomorphology , geophysics , machine learning , composite material
The evaluation of avalanche release conditions constitutes a great challenge for risk assessment in mountainous areas. The spatial variability of snowpack properties has an important impact on snow slope stability and thus on avalanche formation, since it strongly influences failure initiation and crack propagation in weak snow layers. Hence, the determination of the link between these spatial variations and slope stability is very important, in particular, for avalanche public forecasting. In this study, a statistical‐mechanical model of the slab‐weak layer (WL) system relying on stochastic finite element simulations is used to investigate snowpack stability and avalanche release probability for spontaneously releasing avalanches. This model accounts, in particular, for the spatial variations of WL shear strength and stress redistribution by elasticity of the slab. We show how avalanche release probability can be computed from release depth distributions, which allows us to study the influence of WL spatial variations and slab properties on slope stability. The importance of smoothing effects by slab elasticity is verified and the crucial impact of spatial variation characteristics on the so‐called knock‐down effect on slope stability is revisited using this model. Finally, critical length values are computed from the simulations as a function of the various model parameters and are compared to field data obtained with propagation saw tests.