Displays

Highly-porous cohesive granular materials such as snow possess complex modes of failure. Apart from classical failure modes, they show microstructural failure and fragmentation associated with densification within a local, narrow zone. Therefore cracks may form and propagate even under compressive load (‘anticracks’,’compaction bands’). Such failure modes are of importance in a range of geophysical contexts. For instance, they may control the release of snow slab avalanches and influence fracturing of porous rock formations. In the snow context, specific failure mechanisms of the ice matrix and their interplay with the microstructure geometry of snow are still poorly understood. Recently, X-ray computed tomography images have provided insights into snow microstructure and capability of directly simulating its elastic response by the finite element method (FEM). However, apart from thermodynamically driven healing processes the inelastic post-peak behaviour of the microstructure is controlled by localized damage, large deformations and internal contacts. As a result of the well-known limitations of FEM to capture these processes we use Peridynamics (PD) as a non-local continuum method to approach the problem. Due to its formulation, (micro)cracks and damage are emergent features of the problem solution that do not need to be known or located in advance. Furthermore, the Lagrangian character of the governing equations makes the method suitable for simulating large deformations. In this contribution we perform confined uniaxial compression simulations of snow microstructures within a peridynamic framework. Computed tomography images of snow specimen serve as a simulation data base. The obtained results show a novel insight into local failure of snow and allow a better comprehension of the underlying failure mechanisms. This study contributes to improve non-local macroscopic constitutive models for snow for future applications.

How to cite: Ritter, J., Löwe, H., and Zaiser, M.: Microstructural insights into the compressive failure of snow based on a peridynamic framework, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22435, https://doi.org/10.5194/egusphere-egu2020-22435, 2020.

The mechanical response of snow depends on its microstructural geometry. Parameters such as porosity and orientation (degree of anisotropy) are examples of microstructural parameters that can affect snow mechanical properties. Numerical simulations of snow microstructure obtained from X-ray computer tomography have aided researchers in investigating the elastic response and strength of snow. However, we lack insight into the post-peak and plastic response of snow, which in most previous studies have been oversimplified assuming (quasi-)brittle behavior. We propose studying both the elastic and post-peak behavior using the material point method (MPM), a hybrid Eulerian-Lagrangian continuum numerical method. A major advantage of MPM compared to the (classical) finite element method (FEM) is its ability to handle large deformation processes. Moreover, as a continuum method, it is significantly less computational expensive than the discrete element method (DEM). We independently study the influence of the microstructural parameters on macroscopic quantities, such as elastic modulus, strength, energy release rate and plasticity index, in mixed-mode shear-compression loading simulations. This is accomplished by using the leveled gaussian random field (GRF) approach to generate snow samples with desired microstructural properties. The ice matrix of the microstructure is modeled in the elastoplastic framework with a strain-softening Drucker-Prager failure criterion. Based on the relationships discovered through these numerical experiments, we aim to develop a microstructure-based homogenized constitutive snow model. This study will contribute to improve large-scale snow mechanical models with applications in the simulation of e.g. snow slab avalanche release, avalanche dynamics and snow-tire interaction.

How to cite: Blatny, L., Löwe, H., Wang, S., Jiang, C., and Gaume, J.: Microstructure-based modeling of snow using the material point method and finite strain elastoplasticity, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10203, https://doi.org/10.5194/egusphere-egu2020-10203, 2020.

Improving the prediction of snow avalanches requires a detailed understanding of the fracture behavior of snow, which is intimately linked to the mechanical properties of the snow layers (strength, elasticity of the weak and slab layer). While the basic concepts of avalanche release are conceptually relatively well understood, understanding crack propagation and fracture propensity remains a great challenge. About 15 years ago, the propagation saw test (PST) was developed. The PST is a fracture mechanical field test that provides information on crack propagation propensity in weak snowpack layers. It has become a valuable research tool to investigate processes and mechanical parameters involved in crack propagation.

Here, we use the discrete element method (DEM) to numerically simulate PST and therefore analyze fracture dynamics based on micromechanical approach. Using cohesive and non-cohesive ballistic deposition, we numerically reproduce the basic required layers for dry-snow avalanche: a highly porous and brittle weak layer covered by a dense cohesive slab.

The results of these numerical PTSs reproduce the main dynamics of crack propagation observed in the field. We developed different indicators to define the crack tip and therefore derive the crack velocity. Our results show that crack propagation on flat terrain reaches a stationary velocity if the snow column in long enough. The length of the snow column to reach stationary crack velocity depends on snowpack parameters. On sloped terrain our results show a transition in the local failure mode, this transition can be visualized from the crack tip morphology and from the main stress component.

Overall, our results lay the foundation for a comprehensive study on the influence of the snowpack mechanical properties on these fundamental processes for avalanche release.

How to cite: Bobillier, G., van Herwijnen, A., Bergfeld, B., Gaume, J., and Schweizer, J.: Micromechanical modeling of crack propagation in weak snow layer , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18483, https://doi.org/10.5194/egusphere-egu2020-18483, 2020.

Dry snow slab avalanche release depends heavily on the stratification of the snow cover and the mechanical properties of the individual snow layers. This does not only concern the depth and condition of the weak-layer but also the ordering and properties of all snow layers above it.

In order to allow for a quick stability assessment of stratified snow covers, we present an analytical model for snow cover deformations, weak-layer stresses and energy release rates of cracks within the weak-layer for arbitrarily layered snowpacks. In particular, the model covers the impact of the layering order on both the extensional and bending stiffness of the slab. It can be used for skier-loaded slopes and for stability tests such as the propagation saw test. The model is highly efficient and readily allows for parameter studies and implementation into other toolchains.

Recognizing weak-layer collapse as an integral part of the fracture process prior to the release of slab avalanches is crucial and explains phenomena such as whumpf sounds and remote triggering of avalanches from low angle terrain. Finite fracture mechanics introduces a new conceptual understanding of crack nucleation. It provides a coupled stress and energy failure criterion for anticrack formation in persistent weak-layers.

Incorporating this physically sound mixed-mode failure criterion, the model allows for the prediction of skier-loads that layered snowpacks can sustain before weak-layer failure triggering is expected that can lead to avalanche release. Our analysis covers the impact of the layering order on weak-layer stresses and critical skier-loads.

How to cite: Rosendahl, P. L. and Weißgraeber, P.: A comprehensive elastic and fracture model for stratified snowpacks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2409, https://doi.org/10.5194/egusphere-egu2020-2409, 2020.

For a snow avalanche to release, a weak layer has to be buried below a cohesive snow slab. The slab-weak layer configuration must not only allow failure initiation but also crack propagation across a slope. While in the past failure initiation was extensively studied, research focusing on the onset and dynamics of crack propagation only started with the introduction of the Propagation Saw Test (PST), a meter scale fracture mechanical field test. Since then, various studies used particle tracking analysis of high-speed video recordings of PST experiments to gain insight into crack propagation processes and to measure crack propagation speeds. At the slope scale, a few crack speed estimates have been obtained from seismic sensors, videos or visual observation. However, due to experimental limitations, these latter studies can only provide rather crude crack speed estimates and direct comparisons to PST measurements are still missing. Sure, performing experiments in avalanche terrain is challenging and limited for security reasons, but crack propagation occurs also in slopes not sufficiently steep to release an avalanche. This phenomena is called a whumpf. Since crack propagation in whumpfs is presumably similar to that in avalanches, we developed instrumentation to measure crack speeds on artificially triggered whumpfs. We designed small wireless time synchronized accelerometers with a sampling rate of 400 Hz that can be placed on the snowpack. These measure the downward acceleration of the slab when a crack in the weak layer below passes by. Though triggering whumpfs is difficult and unpredictable, we performed a successful experiment with seven sensors placed over a distance of 25 m. Our experiment revealed a crack speed around 50 ms^-1. In addition, we obtained very similar crack speed measurements from a 5.3 m long PST carried out close-by (42 ms^-1) and a video-based speed estimate of an avalanche triggered two days later (42 – 55 ms^-1). Our unique whumpf measurement is the first slope scale speed value that can be directly compared to results obtained with other speed measurement techniques. The similarity between the measured speeds suggests that the one-dimensional crack propagation in PSTs is also similar to the 2-dimensional crack propagation in Whumpfs and real avalanches. PSTs are therefore well suited to investigate crack propagation processes of dry snow slab avalanches.

How to cite: Bergfeld, B., van Herwijnen, A., Bobillier, G., and Schweizer, J.: Measuring slope-scale crack propagation in weak snowpack layers, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8369, https://doi.org/10.5194/egusphere-egu2020-8369, 2020.

Dry-snow slab avalanche release can be separated in four distinct phases : (i) failure initiation in a weak snow layer buried below a cohesive snow slab, (ii) onset, (iii) dynamics of crack propagation in the weak layer and eventually (iv) slab release. While a lot has been done to study the first two phases, less is known about dynamic crack propagation and slab release, especially at slope scale. 

In this study, we used the Material Point Method and elastoplasticity to simulate the dynamics of 20 m long centered Propagation Saw Tests (PST). We improved the recent constitutive snow model of Gaume et al. (2018) by developing a new softening law based on the total plastic deformation (volumetric and deviatoric parts) to remove artifacts observed in failure modes.

Interestingly, several regimes of propagations are observed depending on slope angle Θ. For slope angles smaller than the friction angle (Θ < Φ), crack propagates faster in the downslope direction than upslope. The propagation speed increases with slope angle and appears closely related to the bending mechanism which sustains the propagation. For slope angles higher than the friction angle (Θ > Φ), a sharp transition is observed once the crack reaches a critical length l_f. We interpret this transition as a change from slab bending to slab tension due to the increasing load in the downslope direction. An estimation of l_f is proposed using a basic analytical shear model with residual friction similar to the one developped by McClung in 1979. In this case, the crack propagation speed seems to be mostly related to the P-wave speed in the slab. In this study, we explain the gap between propagation speeds based on 2 m PSTs and some observations of avalanche triggering. Finally, our results show the relevance of shear models which appear sufficient to describe slab avalanche release on steep terrain.

How to cite: Trottet, B., van Herwijnen, A., Wang, S., Jiang, C., Teran, J., and Gaume, J.: Sharp transition in modes of dynamic crack propagation in dry-snow slab avalanche release, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20604, https://doi.org/10.5194/egusphere-egu2020-20604, 2020.

Strong earthquakes often trigger snow avalanches, sometimes with observable delays. Most existing models assume that snow slab avalanches happen simulatenously during or immediatly after their triggering. Therefore, they cannot explain the plausibility of delayed avalanches that are released minutes to hours after a quake. Resolving this shortcoming is critical for improving safety, as emphasized by deadly delayed avalanches in Western Himalaya and, most recently, by the devastating Rigopiano avalanche in Italy’s Abruzzo region, which occurred more than 30 min after the last in a series of major quakes on 18 January 2017. This work establishes the basic mechanism of delays in earthquake-induced avalanche release using a novel analytical model that yields failure scenarios consistent with the Western Himalaya and Rigopiano cases. The mechanism arises from the interplay between creep, strain softening and strain-rate sensitivity of snow, which drive the growth of a basal shear fracture. Our results imply that earthquake-delayed avalanches are rare, yet possible, and could lead to significant damade, especially in long milder slopes. The generality of the model formulation opens a new avenue for exploring other questions related to natural slab avalanche release.

How to cite: Puzrin, A. M., Faug, T., and Einav, I.: Can earthquakes lead to delayed avalanche release ?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22530, https://doi.org/10.5194/egusphere-egu2020-22530, 2020.

Since most dry slab avalanches occur during or immediately following loading by snowfall or wind deposition, it is important to understand changes in the mechanical properties of the snowpack in the minutes and hours following loading. To investigate these temporal changes we conducted a series of 15 Propagation Saw Test (PST) experiments on a flat, uniform site. The existing snowpack at our site contained a layer of surface hoar buried 2 cm below the snow surface. We used a 5 mm sieve to add 10 cm of snow into a 120 cm by 30 cm cardboard frame and completely isolated our blocks. We then conducted PSTs on the buried surface hoar layer from 4 – 453 minutes after adding the sieved snow. We sprayed dye on the side of our tests and filmed them with a high speed camera at 3000 frames per second. Immediately following our tests we measured the density of the sieved snow, and we collected three SnowMicroPen (SMP) profiles along the length of each PST. In one case we collected SMP data at 10 cm increments along our beam prior to conducing our PST to better assess vertical and lateral variations in slab properties induced by sieving. We utilize Digital Image Correlation analyses of the high speed videos to assess the slab elastic modulus (E), the weak layer specific fracture energy (wf), and the crack propagation speed (c) of each test. All our tests fully propagated to the end of the PST columns. Critical cut lengths (rc) ranged between 1.5 and 9 cm, with rc generally increasing over time, in line with the gradual stiffening of the slab observed in the SMP measurements. Our results provide additional information about the temporal changes of mechanical properties immediately following loading, and will better inform modeling efforts attempting to assess these changes.

How to cite: Birkland, K. W., Bergfeld, B., and van Herwijnen, A.: Changes in the mechanical properties of snow relevant to crack propagation in the hours and minutes following loading, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22491, https://doi.org/10.5194/egusphere-egu2020-22491, 2020.

Numerical snow cover models are increasingly used in operational avalanche forecasting. While these models can provide snow stratigraphy and some snow instability information, their full potential is not yet exploited in forecasting. We investigated, how well the snow cover model Alpine3D simulated spatial and temporal variations in snow instability. Therefore, simulations were performed in highly varying complex terrain for the winter season 2016-2017 in the region of Davos, Switzerland for an area of about 21 km x 21 km. Alpine3D was forced with data from several automatic weather stations within the region, which were interpolated to a resolution of 100 m. To reproduce observed spatial variability, we scaled precipitation input with snow height measurements derived with airborne laser scanning. For comparison, we also simulated the snowpack without scaling. The simulation with scaling precipitation showed significantly higher spatial variability in modeled snow instability than the simulation without scaling. However, when information was aggregated to aspect and elevation dependent information for the whole region, as it is done for operational forecasting, this variability vanished and scaling precipitation seems unnecessary. At the beginning of the season and towards the end, snow instability depended on aspect, while in the winter months December to March, differences between different aspects were small. The simulations with scaling precipitation revealed a strong influence of snow depth on snow instability, although the various snow instability criteria provided inconsistent results. Simulated profiles, which were classified as rather favourable were rated as rather unstable and vice versa. A comparison to traditional snow profiles shows that snow stratigraphy was reproduced well, but assessing snow instability from stratigraphy alone is not feasible.

How to cite: Richter, B., van Herwijnen, A., Rotach, M. W., and Schweizer, J.: Simulating snow instability in complex terrain, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19589, https://doi.org/10.5194/egusphere-egu2020-19589, 2020.

Numerical snow cover models enable simulating present or future snow stratigraphy based on meteorological input data from automatic weather stations, numerical weather prediction or climate models. To assess avalanche danger for short-term forecasts or with respect to long-term trends induced by a warming climate, the modeled vertical layering of the snowpack has to be interpreted in terms of mechanical instability. In recent years, improvements in our understanding of dry-snow slab avalanche formation have led to the introduction of new metrics describing the fracture processes leading to avalanche release. Even though these instability metrics have been implemented into the detailed snow cover model SNOWPACK, validated threshold values that discriminate rather stable from rather unstable snow conditions are not readily available. To overcome this issue, we compared a comprehensive dataset of almost 600 manual snow profiles with simulations. The manual profiles were observed in the region of Davos over 17 different winters and include stability tests such as the Rutschblock test as well as observations of signs of instability. To simulate snow stratigraphy at the locations of the manual profiles, we obtained meteorological input data by interpolating measurements from a network of automatic weather stations. By matching simulated snow layers with the layers from traditional snow profiles, we established a method to detect potential weak layers in the simulated profiles and determine the degree of instability. To this end, thresholds for failure initiation (skier stability index) and crack propagation criteria (critical crack length) were calibrated using the observed stability test results and signs of instability incorporated in the manual observations. The resulting instability criteria are an important step towards exploiting numerical snow cover models for snow instability assessment.

How to cite: Mayer, S., van Herwijnen, A., Bavay, M., Richter, B., and Schweizer, J.: Comparing simulated and manual snow profiles to derive thresholds for modeled snow instability metrics, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18898, https://doi.org/10.5194/egusphere-egu2020-18898, 2020.

Windthrow is an important disturbance agent in forest ecosystems and is expected to become more frequent and severe under climate change. Windthrow creates large amounts of surface roughness from downed trees, root plates and stumps. In mountain forests, these elements increase the surface roughness and provide a considerable protective effect against snow avalanches during the first years following a disturbance event. However, if large volumes of snow covers the surface roughness elements, a windthrow area may become prone to avalanche release. Snow accumulation produces terrain smoothing, which is an important factor in avalanche formation.

To assess the effect of snow accumulation on surface roughness in windthrow areas, we quantified terrain smoothing using a vector ruggedness measure and corresponding snow heights, based on digital surface models from summer and winter terrain produced from repetitive UAV flights. Additionally, the snowpack structure was examined using a digital snow micro penetrometer (SMP) to quantify the heterogeneity of snow stratigraphy and to monitor a possible development of weak snow layers over distances greater than 10-20 m, which may contribute to slab avalanche formation. Four study plots were selected to characterize different conditions: i) undisturbed forest, windthrow area with ii) high and iii) low surface roughness, and iv) an open meadow control plot. We then quantified how surface roughness is smoothed depending on the snow height, and at the same time characterized the snowpack structure and the extent of potential weak layers.

We found that increasing snow height leads to decreasing surface roughness, which can produce local release areas. We expect that with continuous increase of snow height, these release areas expand in size; however, further analyses of the snowpack structure will provide deeper insights in potential weak layer formation. Critical conditions for avalanche releases in windthrow areas may thus be defined based on scenarios for snow height and close-range sensing-based roughness data.

How to cite: Brožová, N., Baggio, T., Teich, M., Bast, A., and Bebi, P.: Potential avalanche release in windthrow areas: the effect of snow height and terrain roughness, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8922, https://doi.org/10.5194/egusphere-egu2020-8922, 2020.

Recently, a method applying the Hough Transform was used to obtain the numerical parameters of the shape of the SON section of the spectrograms  of the seismic signals generated by snow avalanches at the experimental site of Vallée de la Sion (VdlS, Valais, Switzerland) (SFL, Davos). The avalanches were of different size and type (powder-snow, transitional and wet-snow) descending along the same path and recorded at two different locations 690 m of distance between them on the path. This helped us to estimate the evolution of the avalanche speed along the path from the starting zone to the run-out zone. We obtained different spectrogram definition parameters according to the type of avalanche.

We apply the same methodology to the seismic signals generated by avalanches at the Ryggfonn experimental site (NGI, Oslo). The avalanches were dry/mixed and dry/dense and occurred in the period (2004-2008). They were recorded in a site along the path. The instrumental conditions, characteristics of the raw data, and the data processing were like those of VdLS. However, the topographic characteristics of the site were different. At the Ryggfonn site, the distance between the starting zone and the sensor was 1640 m (985 in VdlS) and the vertical drop was 800 m (700 m in VdLS).

We present and compare the results obtained to validate a possible application of the method used to VdlS to other places and topographic conditions.

This research was funded by the CHARMA (CGL2013–40828–R) and the PROMONTEC projects (CGL2017-84720-R) of the Spanish Ministry of Economy, Industry and Competitiveness (MINEICO-FEDER) and RISKNAT group (2014GR/1243).

How to cite: Suriñach, E. and Flores-Márquez, E. L.: Comparison of the application of the Hough Transform method (characterization of the SON section in seismic spectrograms) at two different sites (VdlS and Ryggfonn) to study the evolution of avalanches., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8540, https://doi.org/10.5194/egusphere-egu2020-8540, 2020.

Snow avalanches and slush flows are often released at the stratovolcano of Mt. Fuji, which is the highest mountain of Japan (3776 m a.s.l.). These flows represent a major natural hazard as they may attain run-out distances up to 4 km, destroy parts of the forest, and sometimes damage infrastructure. We detected large dimension flows released in the winter seasons of 2014, 2016 and 2018 using the local seismic network installed to monitor the volcanic activity of Mt. Fuji. The maximum detection distance of the seismic network is approximately 15 km for the largest avalanche size class 4–5 (Canadian avalanche classification).  Using data from several seismic sensors, we applied the automated approach of amplitude source location (ASL) based on the decay of the seismic amplitudes with distance to localize and track the avalanche flow paths. We also conducted numerical simulations with Titan2D to reconstruct the avalanche trajectories and thus to assess the precision of the seismic tracking as a function of time, showing mean location errors ranging between 85 and 271 m. The average front speeds estimated from the seismic tracking, which ranged from 27 to 51 m s⁻¹, are consistent with the numerically predicted speeds. In addition, we correlated the source amplitudes and the estimated seismic energies with the approximate run-out distances of the avalanches deduced from the ASL method. The obtained scaling relationships can be useful to empirically classify the flow size. An important task in the near future will be to develop highly effective methods for automatically detecting and tracking avalanche events in the seismic data in near-real time. One approach for the automatization of avalanche detection is the discrimination of seismic sources in the continuous recordings by applying machine learning classification methods. We expect that the precision of the flow tracking could be improved through adaptive weighting of the signals from different stations according to the source–receiver distances and angles.

How to cite: Pérez-Guillén, C., Tsunematsu, K., Nishimura, K., and Issler, D.: Seismic localization and dynamical characterization of snow avalanches and slush flows of Mt. Fuji, Japan, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13407, https://doi.org/10.5194/egusphere-egu2020-13407, 2020.

Aeolian transport of particles occurs in many geophysical contexts such as wind-blown sand or snow drift and is governed by a myriad of physical mechanisms. Most of drifting particle are transported within de saltation layer and has been largely studied for cohesionless particles whether for snow or for sand. Thus, the theoretical description of aeolian transport has been greatly improved for the last decades. In contrast cohesive particles-air system have received much less attention and there remain many important physical issues to be addressed.  

        In the present study, the characteristics of drifting cohesive snow phenomena is investigated experimentally Several wind tunnel experiments were carried out in the Cryopsheric Environment simulator at Shinjo (Sato et al., 2001). Spatial distribution of wind velocity and the mass flux of drifting snow were measured simultaneously by an ultrasonic anemometer and a snow particle counter. The SPC measures the size of each particle passing through a sampling area. The size is classified into 32 classes between 50 and 500µm. Compacted snow was sifted on the floor. Then snow bed is left for a determined duration time to become cohesive by sintering.Two kinds of snow beds with different compression hardness were used (“hard snow” with a compression hardness of about 60 kPa and “semi hard snow” with a compression hardness of about 30 kPa). Wind tunnel velocity varied from 7 m/s to 15 m/s. Moreover steady snow drifting can be produced by seeding snow particles at a constant rate at the upwind of the test section. The results are compared with those obtained for loose surfaces. It was shown that :

- on hard snow cover, aerodynamic entrainment does not occur and saltating particles from the seeder just rebounded without splashing particles composing the snow surface (Kosugi et al.,2004). b, the inverse of the gradient of the mass flux decay with height is proportional to the friction velocity. The mass flux profiles exhibit a focus point. It is also confirmed (Kosugi et al., 2008) that the saltation height increased with increasing particle diameter throughout the full range of investigated wind tunnel velocity. Such characteristics are not observed for cohesionless snow particles (Sugiura et al.,1998)

-on semi hard snow cover, the inter-particle cohesion makes the transport unsteady and spatially inhomogeneous. A steady state is never obtained. It makes experimental protocol and experiments repeatability tricky. Without seeder, the same trends are observed compared to the previous experiments on hard snow. With seeder, the drifting snow flux dramatically increases, even for low wind speed, leading to snow cover vanish.

How to cite: Ralaiarisoa, J.-L. V., Naaim-Bouvet, F., Kosugi, K., Nemoto, M., Ito, Y., Valance, A., Ould El Moctar, A., and Dupont, P.: Saltation layer of cohesive drifting snow observed in a wind tunnel, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13993, https://doi.org/10.5194/egusphere-egu2020-13993, 2020.

The wind-driven saltation of sediments, such as snow and sand, is responsible for a wide range of geophysical processes. Blowing-snow, in particular, affects snow surface properties and drives snow redistribution in alpine terrain. As such, it is of fundamental importance for avalanche mechanics. One of the most important controls on initiation and development of snow saltation is the surface cohesion induced by ice particle sintering. Although inter-particle cohesion is known to limit the number of grains lifted from the surface through aerodynamic entrainment and granular splash, the role of cohesion in the development of saltation from onset to steady state is still poorly understood. Using a numerical model based on the discrete element method, we show that saltation over cohesive beds sustains itself at wind speeds one order of magnitude smaller than those necessary to initiate it, giving rise to hysteresis in which the occurrence of transport depends on the history of the wind. Our results further suggest that saltation over cohesive beds requires much longer distances to saturate, thereby increasing the size of the smallest stable bed forms.

How to cite: Comola, F., Gaume, J., Kok, J., and Lehning, M.: The role of surface cohesion in wind-driven snow transport, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22679, https://doi.org/10.5194/egusphere-egu2020-22679, 2020.