The danger of dry snow slab avalanches is dependent on the conditions of the snow cover in alpine regions. Whether an avalanche is triggered from its own weight, wind or additional loads as backcountry skiers depends strongly on the conditions of the so-called weak layer. These porous and faceted layers grow as surface and depth hoar and are buried by densified snow layers, the so-called slab. In terms of mechanical properties, the slab has a relative high stiffness and tensile strength, while the weak layers with their low densities are more compliant and prone to collapse. These so-called anti-cracks nucleate in the weak layer and propagate afterwards through the slope until the slab ruptures and the avalanche is released.

Providing an efficient stability assessment of stratified snowpacks demands for a mechanical model that can capture both the anti-crack nucleation and propagation. We present a highly efficient and accurate model based on the weak interface models from fracture mechanics, which is able to render stresses and energy release rates in snow packs in real time. The improved kinematics of the weak layer in combination with an improved derivation of the energy release rate enable one to substitute finite element computations in avalanche mechanics. In particular, the model covers the effect of the layering order on both the extensional and bending stiffness of the slab. It can be used for externally-loaded slopes and for stability tests such as the propagation saw test.

How to cite: Rheinschmidt, F., Weißgraeber, P., and Rosendahl, P. L.: Improved Kinematics in a Weak Interface Model for Stratified Snow Packs, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15698, https://doi.org/10.5194/egusphere-egu23-15698, 2023.

Fracture propagation in the snow-pack can lead to slab avalanches triggering. In the brittle deformation regime, snow can be viewed as a loose cohesive material. As shown in Discrete Element (DEM) simulations, the mechanical response of centimetric snow samples present complex patterns including strong strain-softening and volumetric collapse, with an important sensitiveness to the microstructure. On the other hand, avalanches involve large deformations and can propagate over hundreds or thousands of meters.

To tackle the challenge of modelling this wide variety of spatial scales, a double-scale MPMxDEM approach is proposed.
The MPM (Material Point Method) solver is used to compute the evolution of the flow at large scale and embeds a homogenized numerical constitutive law. Hence, each macroscopic lumping point is associated to its own microstructure, e.g. its own DEM cell, evolving independently. At the micro-scale, a loose assembly of spheres is considered with a cohesive contact law.

The ability of this method to capture the main features of snow mechalical behavior in a more robust manner than empirical analytical constitutive models will be investigated by simulating elemenary laboratory tests like oedometric test and field experiments like the Propagation Saw Test (PST).

How to cite: ozenda, O., Chambon, G., and Richefeu, V.: A multiscale MPMxDEM model for simulating snowpack deformation and failure., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15567, https://doi.org/10.5194/egusphere-egu23-15567, 2023.

The presence of interfacial water at the soil-snow interface is considered one of the important factors controlling glide-snow avalanche release. Suction of water out of the soil has been postulated as a possible mechanism for interfacial water formation in early-winter (also known as “cold”) glide-snow avalanches, where the interfacial water is not due to melt water infiltration from the snow surface. Here, we use two 1D-models, HYDRUS and SNOWPACK, to investigate water transport across the soil-snow interface via capillary action. The results of this modeling demonstrate that, under certain conditions, the snowpack is capable of drawing water from the soil and/or interfacial vegetation layer (e.g. grass). We show that the dynamics and magnitude of water transport are highly dependent on the hydraulic properties of the soil, interface, and snow. For example, capillary rise within the snow increases with decreasing snow grain size and increasing snow density. When considering an initially dry snowpack, the capillary pressure of the water within the soil and vegetation sets an upper bound for the increase in liquid water content within the snow. Additional work is needed to assess the effect of geothermal melting as a competing mechanism for interfacial water generation. However, regardless of how the interfacial water is generated, we show that certain configurations of soil, interface, and snow layers can lead to an increase in liquid water content within the basal snowpack due to capillary action. Thus, we conclude that capillary suction is a possible mechanism for early-winter glide-snow avalanche release.

How to cite: Lombardo, M., Lehmann, P., Fees, A., van Herwijnen, A., and Schweizer, J.: Capillary suction as a mechanism for interfacial water formation in early-winter glide-snow avalanches, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13474, https://doi.org/10.5194/egusphere-egu23-13474, 2023.

Mount Washington, New Hampshire’s east aspect glacial cirques are subject to frequent wind slab avalanche problems due to high winds and ample snowfall in fetch areas above the cirques.  Quantification of these slabs’ location, extent and depth is in integral part of avalanche forecasting and risk assessment. This research used SnowModel, a spatially distributed snow-evolution modeling system, to model wind slab depth maps using Mount Washington Observatory weather station data on a 1-meter grid scale. SnowModel’s SnowTran-3D, a snow redistribution by wind algorithm, is tested for one of the first times in the Eastern United States. Snowpack seasonal evolution and accumulation event-based model performance is calibrated and validated using 15 snow depth maps. These maps were constructed via structure from motion (SfM) analysis photogrammetry. SfM maps were derived from optical imagery collected using an Unmanned Aerial System (UAS) and were able to quantify wind slab depth with a 5cm spatial resolution.

How to cite: Wagner, C., Hunsaker, A., and Jacobs, J.: UAV and SnowModel Estimates of Wind Driven Snow in Eastern USA Avalanche Terrain, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4608, https://doi.org/10.5194/egusphere-egu23-4608, 2023.

Glide-snow avalanches release due to a loss of friction at the snow-soil interface, which can result in large avalanches that endanger infrastructure in alpine regions. It is hypothesized that glide-snow avalanche release is linked to the presence of liquid water at the snow-soil interface, but the driving physical processes are poorly understood and prediction remains difficult. To better understand these driving physical processes, we monitored soil (water content, matric potential, temperature) and snow properties (water content, temperature, weekly snow profiles) across a small slope (40 m x 70 m) at the Dorfberg field site above Davos, Switzerland for the winter seasons 2021/22 and 2022/23. These observations were supplemented with SNOWPACK simulations for 10 release zones across Dorfberg. In addition, SNOWPACK simulations were used to supplement a dataset of more than 900 glide-snow avalanches that were previously (seasons 2009-2023) recorded on Dorfberg using time-lapse photography. Analyses of both SNOWPACK and monitoring data show high spatial variability of soil and snow properties across the monitored slope and across Dorfberg. Spatial variability in soil water content across the monitoring slope was higher during early winter than during spring when melt-freeze cycles and subsequent water infiltration in the soil cause a spatial homogenization. Transferring findings from the field monitoring to the large dataset allowed for the identification of several temporal patterns. For example, we see a positive correlation between mean snowpack density and the number of melt-freeze cycles prior to avalanche release in spring. We see a similar correlation with snow height. Overall, our measurements show that on Dorfberg several diurnal melt-freeze cycles are necessary before glide-snow avalanche release in spring.

How to cite: Fees, A., van Herwijnen, A., Lombardo, M., and Schweizer, J.: Glide-snow avalanches: insights from combining field monitoring, time-lapse photography and SNOWPACK simulations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11880, https://doi.org/10.5194/egusphere-egu23-11880, 2023.

How to cite: Muckenhuber, S., Goelles, T., Schlager, B., Kapper, K. L., Prokop, A., and Schöner, W.: The potential of automotive perception sensors for local snow avalanche monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4989, https://doi.org/10.5194/egusphere-egu23-4989, 2023.

Snow avalanches threaten people and infrastructure in alpine regions. Each winter situations occur that require road closures, which have a major impact on the affected people and economy. The decisions on road safety measures are done by local experts, who decide based on information from the avalanche bulletin, weather forecast and most importantly personal experience. Valuable, detailed information about the snow depth distribution, especially in avalanche release areas is not available in sufficient resolution. To fill this data-gap, we propose a remote-sensing based approach to map, monitor and model the snow depth distribution and its development in avalanche release areas, with high spatial and temporal resolution. The main applied technologies are photogrammetry and LiDAR, both air-borne and ground-based. The newly build up snow database will serve as input to improve the simulation of avalanches and especially the runout distance, which is ultimately crucial for the decision of closing or re-opening a road.

How to cite: Ruttner-Jansen, P., Glaus, J., Wieser, A., and Bühler, Y.: Monitoring and modelling snow avalanches to innovate road safety management in alpine valleys, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13240, https://doi.org/10.5194/egusphere-egu23-13240, 2023.

The unpredictable nature and destructive power of snow avalanches demand reliable, real-time detection systems of the events in mountain regions. Remote detection systems based on seismic and infrasound sensors have been increasingly used to monitor avalanches at a rather low economic cost. The seismo-acoustic wave field generated by avalanches enables the detection of natural avalanches in a large area, independently of the weather and visibility conditions. One approach for the automatization of avalanche detection is the discrimination of seismic and infrasound signals in the continuous recordings by applying machine learning classification methods. In this study, we evaluated the automatic classification of avalanche signals recorded by a seismo-acoustic detection system installed in Davos (Switzerland) since the winter season 2020-2021. We tested three feature extraction methods to classify the signals based on a Random Forest algorithm. The first RF classifier was trained with a set of features extracted from the individual components of the array. This set of features included waveform properties, spectral features and spectrogram attributes. The second classifier used input features extracted from the amplitude, backazimut and apparent slowness time series of the array-processing outputs. In addition, we tested an autoencoder feature extraction method based on a convolutional neural network with long short-term memory. This automated set of input features was used to train another RF classifier using the same labels. We compared the predictive performance of the three classifiers. Our final goal is to develop an effective classification algorithm combining the different methods to automatically detect snow avalanches in near-real time.

How to cite: Pérez-Guillén, C., Seupel, C., Simeon, A., Volpi, M., and van Herwijnen, A.: Automated discrimination of seismo-acoustic avalanche signals, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12211, https://doi.org/10.5194/egusphere-egu23-12211, 2023.

The thickness integrated dense flow avalanche simulation module com1DFA of the open source framework AvaFrame is used for snow avalanche simulations with application in hazard mapping for different mountainous areas. In order to further increase the information value gained from the avalanche simulation results in a global coordinate system, we introduce a thalweg following coordinate system. It allows us to quantitatively compare simulation scenarios and results of different modelling approaches in a new way. It helps to bridge the gap between the modules operating in three-dimensional terrain (com1DFA) versus two-dimensional along the avalanche path, such as the well-known alpha-beta model implemented in module com2AB. One essential step of the analysis procedures (analysis modules in AvaFrame) is the avalanche thalweg generation itself. The thalweg depends on the main flow direction, a property of the avalanche event which is strongly influenced by the terrain the avalanche flow will encounter. So far, the main flow direction is usually derived from observations or avalanche simulations, and the thalweg is generated manually. However, the reproducibility of this method raises an issue, and manually identifying the avalanche thalweg for every slope is unnecessarily time-consuming.

In this work, we use com1DFA simulations in three dimensional terrain. We automatically generate the two-dimensional avalanche thalweg by extracting the centre of mass coordinates at every time step. Projecting the simulation results into this thalweg following coordinate system, we can derive the position of the avalanche front and the local travel angles, from which scalar measures like runout length and runout angle are determined. We combine temporal and spatial information by introducing the thalweg-time and thalweg-altitude diagrams. These offer a different perspective on the simulation results and, at a glance, provide information on the evolution of spatio-temporal flow variables (thickness, velocity) along the avalanche thalweg in a single plot. Additionally, by using a numerical particle-grid method, we can evaluate simulation outputs at a particle level and relate them to the whole avalanche flow. Another advantage of the analysis tools operating in the thalweg coordinate system is the possibility to compare simulation results with field measurements. For example, we present in-flow particle sensors trajectories and corresponding velocities recorded during field experiments to evaluate com1DFA simulation results and thereby help to improve the dense flow module. For different avalanche simulations, we show how these analysis modules provide a new way to summarize the complex spatio-temporal flow variables evolution in three dimensional terrain in a more intuitive two dimensional illustration along the automatically generated thalweg.

How to cite: Dick, O., Tonnel, M., Wirbel, A., Oesterle, F., Fischer, J.-T., and Neuhauser, M.: Analysis of snow avalanche simulation results in a thalweg-following coordinate system, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5687, https://doi.org/10.5194/egusphere-egu23-5687, 2023.