Articles | Volume 23, issue 1
https://doi.org/10.5194/nhess-23-293-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-23-293-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Temporal evolution of crack propagation characteristics in a weak snowpack layer: conditions of crack arrest and sustained propagation
WSL Institute for Snow and Avalanche Research SLF, Davos,
Switzerland
Alec van Herwijnen
WSL Institute for Snow and Avalanche Research SLF, Davos,
Switzerland
Grégoire Bobillier
WSL Institute for Snow and Avalanche Research SLF, Davos,
Switzerland
Philipp L. Rosendahl
Institute of Structural Mechanics and Design, Technical University of Darmstadt, Darmstadt, Germany
Philipp Weißgraeber
Chair of Lightweight Design, University of Rostock, Rostock, Germany
Valentin Adam
Institute of Structural Mechanics and Design, Technical University of Darmstadt, Darmstadt, Germany
WSL Institute for Snow and Avalanche Research SLF, Davos,
Switzerland
Jürg Dual
Institute for Mechanical Systems, ETH Zurich, Zurich, Switzerland
Jürg Schweizer
WSL Institute for Snow and Avalanche Research SLF, Davos,
Switzerland
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Avalanche formation depends on crack propagation in weak snow layers, but the conditions that stop a crack remain unclear. We show that slab touchdown reduces the energy driving crack growth, which can halt propagation even under static conditions. This suggests that crack arrest is influenced not only by snowpack variability or dynamics but also by mechanical interactions within the snowpack. Our findings refine avalanche prediction models and improve hazard assessment.
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To release a slab avalanche, a crack in a weak snow layer beneath a cohesive slab has to propagate. Information on that is essential for assessing avalanche risk. In the field, information can be gathered with the propagation saw test (PST). However, there are different standards on how to cut the PST. In this study, we experimentally investigate the effect of these different column geometries and provide models to correct for imprecise field test geometry effects on the critical cut length.
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Our study investigates the initiation of snow slab avalanches. Combining experimental data with numerical simulations, we show that on gentle slopes, cracks form and propagate due to compressive fractures within a weak layer. On steeper slopes, crack velocity can increase dramatically after approximately 5 m due to a fracture mode transition from compression to shear. Understanding these dynamics provides a crucial missing piece in the puzzle of dry-snow slab avalanche formation.
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To release a slab avalanche, a crack in a weak snow layer beneath a cohesive slab has to propagate. Information on that is essential for assessing avalanche risk. In the field, information can be gathered with the propagation saw test (PST). However, there are different standards on how to cut the PST. In this study, we experimentally investigate the effect of these different column geometries and provide models to correct for imprecise field test geometry effects on the critical cut length.
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Philipp Weißgraeber and Philipp L. Rosendahl
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The work presents a mathematical model that calculates the behavior of layered snow covers in response to loadings. The information is necessary to predict the formation of snow slab avalanches. While sophisticated computer simulations may achieve the same goal, they can require weeks to run. By using mathematical simplifications commonly used by structural engineers, the present model can provide hazard assessments in milliseconds, even for snowpacks with many layers of different types of snow.
Stephanie Mayer, Alec van Herwijnen, Frank Techel, and Jürg Schweizer
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Information on snow instability is crucial for avalanche forecasting. We introduce a novel machine-learning-based method to assess snow instability from snow stratigraphy simulated with the snow cover model SNOWPACK. To develop the model, we compared observed and simulated snow profiles. Our model provides a probability of instability for every layer of a simulated snow profile, which allows detection of the weakest layer and assessment of its degree of instability with one single index.
Cristina Pérez-Guillén, Frank Techel, Martin Hendrick, Michele Volpi, Alec van Herwijnen, Tasko Olevski, Guillaume Obozinski, Fernando Pérez-Cruz, and Jürg Schweizer
Nat. Hazards Earth Syst. Sci., 22, 2031–2056, https://doi.org/10.5194/nhess-22-2031-2022, https://doi.org/10.5194/nhess-22-2031-2022, 2022
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A fully data-driven approach to predicting the danger level for dry-snow avalanche conditions in Switzerland was developed. Two classifiers were trained using a large database of meteorological data, snow cover simulations, and danger levels. The models performed well throughout the Swiss Alps, reaching a performance similar to the current experience-based avalanche forecasts. This approach shows the potential to be a valuable supplementary decision support tool for assessing avalanche hazard.
Achille Capelli, Franziska Koch, Patrick Henkel, Markus Lamm, Florian Appel, Christoph Marty, and Jürg Schweizer
The Cryosphere, 16, 505–531, https://doi.org/10.5194/tc-16-505-2022, https://doi.org/10.5194/tc-16-505-2022, 2022
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Antoine Guillemot, Alec van Herwijnen, Eric Larose, Stephanie Mayer, and Laurent Baillet
The Cryosphere, 15, 5805–5817, https://doi.org/10.5194/tc-15-5805-2021, https://doi.org/10.5194/tc-15-5805-2021, 2021
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Ambient noise correlation is a broadly used method in seismology to monitor tiny changes in subsurface properties. Some environmental forcings may influence this method, including snow. During one winter season, we studied this snow effect on seismic velocity of the medium, recorded by a pair of seismic sensors. We detected and modeled a measurable effect during early snowfalls: the fresh new snow layer modifies rigidity and density of the medium, thus decreasing the recorded seismic velocity.
Nora Helbig, Michael Schirmer, Jan Magnusson, Flavia Mäder, Alec van Herwijnen, Louis Quéno, Yves Bühler, Jeff S. Deems, and Simon Gascoin
The Cryosphere, 15, 4607–4624, https://doi.org/10.5194/tc-15-4607-2021, https://doi.org/10.5194/tc-15-4607-2021, 2021
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The snow cover spatial variability in mountains changes considerably over the course of a snow season. In applications such as weather, climate and hydrological predictions the fractional snow-covered area is therefore an essential parameter characterizing how much of the ground surface in a grid cell is currently covered by snow. We present a seasonal algorithm and a spatiotemporal evaluation suggesting that the algorithm can be applied in other geographic regions by any snow model application.
Bastian Bergfeld, Alec van Herwijnen, Benjamin Reuter, Grégoire Bobillier, Jürg Dual, and Jürg Schweizer
The Cryosphere, 15, 3539–3553, https://doi.org/10.5194/tc-15-3539-2021, https://doi.org/10.5194/tc-15-3539-2021, 2021
Short summary
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The modern picture of the snow slab avalanche release process involves a
dynamic crack propagation phasein which a whole slope becomes detached. The present work contains the first field methodology which provides the temporal and spatial resolution necessary to study this phase. We demonstrate the versatile capabilities and accuracy of our method by revealing intricate dynamics and present how to determine relevant characteristics of crack propagation such as crack speed.
Jürg Schweizer, Christoph Mitterer, Benjamin Reuter, and Frank Techel
The Cryosphere, 15, 3293–3315, https://doi.org/10.5194/tc-15-3293-2021, https://doi.org/10.5194/tc-15-3293-2021, 2021
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Snow avalanches threaten people and infrastructure in snow-covered mountain regions. To mitigate the effects of avalanches, warnings are issued by public forecasting services. Presently, the five danger levels are described in qualitative terms. We aim to characterize the avalanche danger levels based on expert field observations of snow instability. Our findings contribute to an evidence-based description of danger levels and to improve consistency and accuracy of avalanche forecasts.
Michaela Wenner, Clément Hibert, Alec van Herwijnen, Lorenz Meier, and Fabian Walter
Nat. Hazards Earth Syst. Sci., 21, 339–361, https://doi.org/10.5194/nhess-21-339-2021, https://doi.org/10.5194/nhess-21-339-2021, 2021
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Mass movements constitute a risk to property and human life. In this study we use machine learning to automatically detect and classify slope failure events using ground vibrations. We explore the influence of non-ideal though commonly encountered conditions: poor network coverage, small number of events, and low signal-to-noise ratios. Our approach enables us to detect the occurrence of rare events of high interest in a large data set of more than a million windowed seismic signals.
Bettina Richter, Alec van Herwijnen, Mathias W. Rotach, and Jürg Schweizer
Nat. Hazards Earth Syst. Sci., 20, 2873–2888, https://doi.org/10.5194/nhess-20-2873-2020, https://doi.org/10.5194/nhess-20-2873-2020, 2020
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We investigated the sensitivity of modeled snow instability to uncertainties in meteorological input, typically found in complex terrain. The formation of the weak layer was very robust due to the long dry period, indicated by a widespread avalanche problem. Once a weak layer has formed, precipitation mostly determined slab and weak layer properties and hence snow instability. When spatially assessing snow instability for avalanche forecasting, accurate precipitation patterns have to be known.
Frank Techel, Karsten Müller, and Jürg Schweizer
The Cryosphere, 14, 3503–3521, https://doi.org/10.5194/tc-14-3503-2020, https://doi.org/10.5194/tc-14-3503-2020, 2020
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Exploring a large data set of snow stability tests and avalanche observations, we quantitatively describe the three key elements that characterize avalanche danger: snowpack stability, the frequency distribution of snowpack stability, and avalanche size. The findings will aid in refining the definitions of the avalanche danger scale and in fostering its consistent usage.
Louis Quéno, Charles Fierz, Alec van Herwijnen, Dylan Longridge, and Nander Wever
The Cryosphere, 14, 3449–3464, https://doi.org/10.5194/tc-14-3449-2020, https://doi.org/10.5194/tc-14-3449-2020, 2020
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Deep ice layers may form in the snowpack due to preferential water flow with impacts on the snowpack mechanical, hydrological and thermodynamical properties. We studied their formation and evolution at a high-altitude alpine site, combining a comprehensive observation dataset at a daily frequency (with traditional snowpack observations, penetration resistance and radar measurements) and detailed snowpack modeling, including a new parameterization of ice formation in the 1-D SNOWPACK model.
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Short summary
For a slab avalanche to release, the snowpack must facilitate crack propagation over large distances. Field measurements on crack propagation at this scale are very scarce. We performed a series of experiments, up to 10 m long, over a period of 10 weeks. Beside the temporal evolution of the mechanical properties of the snowpack, we found that crack speeds were highest for tests resulting in full propagation. Based on these findings, an index for self-sustained crack propagation is proposed.
For a slab avalanche to release, the snowpack must facilitate crack propagation over large...
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