Influence of snowpack layering on human-triggered snow slab avalanche release

Dry-snow slab avalanches involve the release of a cohesive slab over an extended plane of weakness. In most fatal avalanches, the triggering of the initial failure occurred by localized rapid near-surface loading by people — followed by fracture propagation. Whereas a limit-equilibrium (LE) approach to snow slope failure only takes into account slab depth, slab density and weak layer strength, it omits properties such as the stiffness of adjacent layers and the fracture propagation process. Nevertheless, LE has been applied with some success to the frequency of skier triggering, suggesting that it is relevant to failure initiation. Since field studies have shown that, for a given slab thickness, stiffer slabs are less likely to be triggered, slab properties influence failure initiation, fracture propagation or both. A highly simplified finite element (FE) model of static skier loading was used to assess the effect of slab and substratum properties on skier-induced stresses in the weak layer. Compared to a uniform slab, the skier-induced stress at the depth of the weak layer varied by a factor of 2 due to layering. In particular, the simplified FE model suggests that while stiffer layers in the slab will reduce the skier-induced stress in the weak layer, stiff layers just below the weak layer can increase the shear stress. These results were incorporated into a modified stability index and compared to stability test results. However, by taking into account snowpack layering the correlation between the modified stability index and stability test results did not improve. While our simulations suggest that less stress penetrates through stiffer slabs and thus fracture initiation is less likely, other studies show that, once initiated, fractures under stiffer slabs have high propagation propensity.     

Comparison of micro-structural snowpack parameters derived from penetration resistance measurements with fracture character observations from compression tests

Compression tests are snow stability tests that are widely used by avalanche professionals and snow researchers to identify potential weak snowpack layers. Describing fracture character in addition to the number of taps required to initiate a fracture improves the interpretation of compression test results, since certain types of fractures, i.e. sudden fractures, are more often associated with skier-triggered avalanches. Digital snowpack penetrometers provide high resolution penetration resistance data of the snow cover with depth. The SnowMicroPen (SMP) was used to measure high resolution penetration resistance profiles in the snowpack next to compression tests. A reliable method to automatically detect the snow surface in the SMP signals was introduced. Furthermore, a method based on the autocorrelation of the penetration resistance signal was developed to identify the failure layers, identified using compression tests, in the penetration resistance profiles. Using field data from 190 penetration resistance measurements, each collected between two compression tests, micro-structural parameters associated with different types of fractures were identified. More than 550 fractures were classified as either Progressive Compression (1.3%), Resistant Planar (12.1%), Sudden Planar (50.4%), Sudden Collapse (26.8%) or non-planar Break (9.4%). Measurement and analysis were focussed on micro-structural properties of the failure layer, the layer adjacent to the failure layer and the slab above the failure layer. Sudden collapse fractures were found to have typical micro-structural snowpack parameters that are generally associated with unstable snow conditions, such as large differences in penetration resistance between the failure layer and the adjacent layer.     

Comparison of micro-structural snowpack parameters derived from penetration resistance measurements with fracture character observations from compression tests

Compression tests are snow stability tests that are widely used by avalanche professionals and snow researchers to identify potential weak snowpack layers. Describing fracture character in addition to the number of taps required to initiate a fracture improves the interpretation of compression test results, since certain types of fractures, i.e. sudden fractures, are more often associated with skier-triggered avalanches. Digital snowpack penetrometers provide high resolution penetration resistance data of the snow cover with depth. The SnowMicroPen (SMP) was used to measure high resolution penetration resistance profiles in the snowpack next to compression tests. A reliable method to automatically detect the snow surface in the SMP signals was introduced. Furthermore, a method based on the autocorrelation of the penetration resistance signal was developed to identify the failure layers, identified using compression tests, in the penetration resistance profiles. Using field data from 190 penetration resistance measurements, each collected between two compression tests, micro-structural parameters associated with different types of fractures were identified. More than 550 fractures were classified as either Progressive Compression (1.3%), Resistant Planar (12.1%), Sudden Planar (50.4%), Sudden Collapse (26.8%) or non-planar Break (9.4%). Measurement and analysis were focussed on micro-structural properties of the failure layer, the layer adjacent to the failure layer and the slab above the failure layer. Sudden collapse fractures were found to have typical micro-structural snowpack parameters that are generally associated with unstable snow conditions, such as large differences in penetration resistance between the failure layer and the adjacent layer.     

The effects of snow variability on slab avalanche release

Dry snow slab avalanches are released by the failure of a weak layer underlying a thick cohesive slab. A model is derived which accounts for spatial variability of this weak layer and for stress redistribution between weak and strong regions. The model is applied to the case of randomly varying shear strength of the weak layer. It is demonstrated that strength variations have a dramatic knockdown effect on slope stability. An equation is derived, which relates the critical load supported by the weak layer to its mean shear strength and shear strength variance, and this equation is used to formulate a slope stability index with fluctuation corrections. The nature of the critical flaw is studied, and precursors to failure are investigated. The effect of time healing of damaged regions due to fast metamorphism is introduced into the model, and it is demonstrated that this has a minimal effect on slope failure strength. The internal stresses in the snowpack are evaluated and discussed, and a failure scenario is developed which accounts for the interplay of snowpack heterogeneity, strain softening and internal stresses.     

Triggering of dry snow slab avalanches: stress versus fracture mechanical approach

This paper analyses the conditions for triggering of dry snow slab avalanches. As suggested by several Authors, we assume as a basic mechanism for avalanche triggering the mode II fracture of the weak layer lying beneath the stiff snow slab, i.e. we assume the presence of super-weak zones in the basal layer. By means of a linear elastic analysis, the shear stresses in the weak layer as well as the strain energy release rate caused by an increment of the super-weak zone are evaluated. Hence we introduce a stress failure criterion as well as an energy one. It is shown that the latter criterion can be seen as an extension of the criterion firstly proposed by McClung [McClung, D.M., 1979. Shear fracture precipitated by strain softening as a mechanism of dry slab avalanche release. Journal of Geophysical Research, 84(B7), 3519-3526.] for dry snow slab avalanche release. Finally we couple the two criteria, showing that the weak layer can fail only in a min–max band of thickness.     

Explanation and limitations of study plot stability indices for forecasting dry snow slab avalanches in surrounding terrain

In the Columbia Mountains of western Canada, some snow avalanche forecasting programs use slab stability indices calculated from study plot measurements near tree-line and find these indices helpful for forecasting dry slab avalanching many kilometers from the study plot. Research in the same mountain range has confirmed the correlation between the indices and avalanche occurrence. Due to spatial variability and scale issues, the explanation for the correlation between the indices, which are based on measurements over a small area, and avalanching many kilometers away has been unclear. The stability indices for natural (spontaneous) avalanches are ratios of shear strength of a weak snowpack layer to the shear stress on the weak layer applied by the overlying slab. The denominator of these ratios is proportional to vertical overburden pressure (load). One time series of overburden and shear strength measurements shows that neither measurement can be extrapolated from one site to another. A second time series shows a substantial difference in the stability index between the two sites, which is likely due to different initial crystal sizes in the weak layer at the two sites. However, different sites exhibit concurrent decreases in the strength–load ratio during snowfall and concurrent increases in the ratio after snowfall. The increases after snowfall are explained by lagged densification of weak layers and pressure sintering between grains. Critical values of stability indices are shown to be less useful than their trends for forecasting natural dry slab avalanches. The potential correlation of study plot stability indices with avalanching in surrounding terrain is also limited by the spatial extent of the weather system that forms the weak snowpack layer.     

Predicting the fracture character of weak layers from snowpack penetrometer signals

Digital penetrometers provide reliable assessments of snow penetration resistance with depth. However, extracting useful information from the signals relating to snow stability has proved to be challenging. In this study, penetrometer profiles were collected in close proximity to compression tests. A scheme for predicting the fracture character of weak layers in the compression tests from the penetrometer signals is presented. When a two-group classification between sudden (Q1) (an indicator of instability) and other fracture character groups was performed, potential failure layers were correctly classified 80% of the time. The variables offering the best discrimination between sudden and other categories were weak layer thickness, average force gradient above the weak layer, and both the average and the maximum force gradient below the weak layer. The effect of introducing randomly selected layers into the prediction scheme was also investigated. When such layers were introduced, the classification rate dropped to 67%, indicating that more effective fracture character prediction occurred when weak layers were manually pre-identified. This suggests that this scheme should be used in conjunction with a weak layer detection model rather than as a stand alone analytical technique for the purpose of critical weak layer identification. The classification rate dropped further to 55% when a more detailed, four-group classification scheme was used.     

Examining spring wet slab and glide avalanche occurrence along the Going-to-the-Sun Road corridor,Glacier National Park,Montana, USA

Wet slab and glide snow avalanches are dangerous and yet can be particularly difficult to predict. Wet slab and glide avalanches are presumably triggered by free water moving through the snowpack and the subsequent interaction with layer or ground interfaces, and typically occur in the spring during warming and subsequent melt periods. In Glacier National Park (GNP), Montana, both types of avalanches can occur in the same year and affect the spring opening operations of the Going-to-the-Sun Road (GTSR).We investigated the timing of wet slab and glide avalanche occurrence along the GTSR from 2003 to 2011 using meteorological and snowpack data from two high-elevation weather stations, one SNOTEL site, and an avalanche database to characterize 55 wet slab and 182 glide avalanches. Daily wet slab and glide avalanche occurrence were combined to represent an avalanche day and were compared to non-avalanche days (no avalanche occurrence) for 60 variables (both direct and derived measurements) using a univariate analysis. A classification tree (CART) was then trained to capture the most important variables for examining specific meteorological and snowpack variables that contribute to these types of wet snow avalanches. The CART was 10-fold cross validated using the data for 2003–2010 seasons and resulted in overall predictive accuracy of 73%. We then used the statistically optimal CART as a predictive model for the spring avalanche season of 2011, which resulted in an overall predictive accuracy of 82% for both avalanche and non-avalanche days, and a predictive accuracy of 91% for avalanche days.The results suggest that the role of air temperature and snowpack settlement appear to be the most important variables in wet slab and glide avalanche occurrence. When applied to the 2011 season, the results of the CART model are encouraging and they enhance our understanding of some of the required meteorological and snowpack conditions for wet slab and glide avalanche occurrence.     

Rutschblock-scale snowpack stability derived from multiple quality-controlled SnowMicroPen measurements

Stability prediction from SnowMicroPen (SMP) profiles would support avalanche forecasting operations, since objective stability information could be gathered more quickly than with standard tests, thereby allowing sampling at higher resolution and over larger spatial scales. Previous studies have related the snow properties derived from the SMP to observed snow properties at Rutschblock (RB) and compression test failure planes. The goals of this study are to show to what extent snowpack stability for artificial triggering, based on RB, can be derived from SMP measurements and how multiple measurements at the RB scale improve the results. Measurements at 36 different sites were used for the development of a classification scheme. Each site included a RB test, a manual profile, and 6 to 10 adjacent SMP measurements, for a total of 262 SMP profiles. A recently improved SMP theory was applied to estimate the micro-structural and mechanical properties of manually defined weak layers and slab layers. SMP signal quality control and different noise treatment methods were taken into consideration in the analysis. The best and most robust predictor of RB stability was the weak layer micro-scale strength. In combination with the SMP-estimated mean density of the slab layer, the total accuracy of predicting RB stability classes was 85% over the entire dataset, and 88% when signals with obvious signal dampening (11% of the dataset) were removed. The total accuracy increased when multiple SMP measurements at the RB scale were used to calculate the mean weak layer strength, when compared to using just one SMP measurement at a site. The analysis was robust to trends and offsets in the absolute SMP force, which was a frequent signal error. However, it was sensitive to dampened or disturbed SMP force micro variance. The sensitivity analysis also showed that the best predictor of instability, the weak layer micro-scale strength, was robust to the choice of SMP signal noise removal method.     

Explanation and limitations of study plot stability indices for forecasting dry snow slab avalanches in surrounding terrain

In the Columbia Mountains of western Canada, some snow avalanche forecasting programs use slab stability indices calculated from study plot measurements near tree-line and find these indices helpful for forecasting dry slab avalanching many kilometers from the study plot. Research in the same mountain range has confirmed the correlation between the indices and avalanche occurrence. Due to spatial variability and scale issues, the explanation for the correlation between the indices, which are based on measurements over a small area, and avalanching many kilometers away has been unclear. The stability indices for natural (spontaneous) avalanches are ratios of shear strength of a weak snowpack layer to the shear stress on the weak layer applied by the overlying slab. The denominator of these ratios is proportional to vertical overburden pressure (load). One time series of overburden and shear strength measurements shows that neither measurement can be extrapolated from one site to another. A second time series shows a substantial difference in the stability index between the two sites, which is likely due to different initial crystal sizes in the weak layer at the two sites. However, different sites exhibit concurrent decreases in the strength–load ratio during snowfall and concurrent increases in the ratio after snowfall. The increases after snowfall are explained by lagged densification of weak layers and pressure sintering between grains. Critical values of stability indices are shown to be less useful than their trends for forecasting natural dry slab avalanches. The potential correlation of study plot stability indices with avalanching in surrounding terrain is also limited by the spatial extent of the weather system that forms the weak snowpack layer.     

Anticrack model for skier triggering of slab avalanches

Skiers caught in a slab avalanche often trigger the avalanche themselves. Preventing those accidents necessitates a better understanding of the factors contributing to the failure of the snowpack under the action of a skier. In the present work, a mathematical model based on the principles of mixed-mode anticracking is proposed for skier triggering. The respective influences of the slope-normal and slope-parallel components of the load exerted by a skier on the prospective fracture plane are taken into account. A criterion for fracture propagation under typical skier loads is derived. It manifests a small number of factors that, combined, multiply the risk of triggering an avalanche. The criterion indicates, contrary to a common perception, that fracture is not more difficult to trigger in gentle slopes than in steep slopes. This major result of the model is confirmed by data obtained from field experiments.     

A field study on failure of storm snow slab avalanches

Storm snow often avalanches before crystals metamorphose into faceted or rounded shapes, which typically occurs within a few days. We call such crystals nonpersistent, to distinguish them from snow crystals that persist within the snowpack for weeks or even months. Nonpersistent crystals can form weak layers or interfaces that are common sources of failure for avalanches. The anticrack fracture model emphasizes collapse and predicts that triggering is almost independent of slope angle, but this prediction has only been tested on persistent weak layers. In this study, dozens of stability tests show that both nonpersistent and persistent crystals collapse during failure, and that slope angle does not affect triggering (although slope angle determines whether collapse leads to an avalanche). Our findings suggest that avalanches in storm snow and persistent weak layers share the same failure mechanism described by the anticrack model, with collapse providing the fracture energy. Manual hardness measurements and near-infrared measurements of grain size sometimes showed thin weak layers of softer and larger crystals in storm snow, but often showed failures at interfaces marked by softer layers above and harder layers below. We suggest collapse often occurs in crystals at the bottom of the slab. Planar crystals such as sectored plates were often found in failure layers, suggesting they are especially prone to collapse.     

Comparison of snow stability tests: Extended column test, rutschblock test and compression test

Several field tests have been proposed in the past for evaluating snow stability. However, few comparative studies have been performed so that presently the advantages and disadvantages of the various tests are partly unclear. During winter 2007–2008 we have collected a dataset of 146 snow profiles, consisting of snow stratigraphy, a rutschblock test (RB), one to two extended column tests (ECT) and in most of the cases also one to two compression tests (CT). Study slopes were classified in regard to stability as either rather stable or rather unstable, based on signs of instability or profile classification. We then studied whether the various tests were able to predict the slope stability class. The CT had an almost perfect probability of detection, but — as the structural stability index (threshold sum) — the CT largely overestimated instability (high proportion of false alarms). Of the small scale tests the ECT was best suited to differentiate between stable and unstable situations. By including the ECT score (number of taps), the number of false alarms was slightly reduced. The performance was similar to the RB which is, however, not independent of the stability classification we used. With two adjoining ECTs it was possible to classify 87% of our test slopes with an accuracy of about 90% into rather stable or rather unstable. Comparing two adjacent stability test results showed that only in about half of the pairs the same weak layer showed up as the most critical one. The snowpack properties (weak layer and slab) that favoured unstable test results for the ECT were associated with whole block releases in the rutschblock test. Thus, the two tests seem to provide similar information possibly related to fracture propagation propensity.     

Measurements of localized dynamic loading in a mountain snow cover

In the majority of fatal avalanches, skiers and snowmobilers apply load to the snow cover which triggers the initial failure in a weak layer. Understanding how the stress due to the dynamic surface load transmits through the snow cover can help people avoid situations where they can trigger avalanches. Capacitive sensors were used to measure this stress within the mountain snow cover. The three main variables affecting stress transmission through the snow cover investigated in this paper are the type of loading, depth and snow cover stratigraphy. At specific depths, snowmobiles added more stress than skiers did, thus increasing the probability of initiating a fracture in a weak layer and releasing a slab avalanche. The increased penetration depth of snowmobiles into the snow cover compared to skiers was the primary reason for this increase in stress. A decrease in stress was observed with increasing depth. A decrease in stress was observed with increased snow cover hardness. Supportive surface layers created a ‘bridging effect’ that spread stress out laterally and decreased the depth to which it penetrated.     

Measuring spatial variations of weak layer and slab properties with regard to snow slope stability

Spatial variations of weak layer and slab properties are believed to affect snow slope stability. To quantify spatial variability at the slope scale, penetration resistance was measured with a high-resolution snow micro-penetrometer (SMP) in a partly randomized grid pattern. The grid design consisted of 46 SMP measurement locations. In addition, a full snow profile and 20 compression tests as well as a Rutschblock test at the snow profile location were performed within the grid. Fifteen slopes of different aspects were sampled of which 11 could be analysed. Weak layer and slab properties were characterised using non-spatial as well as spatial statistics and results were related to slope stability. The geostatistical analysis revealed that in more than half of the cases a range could be determined. Slab layers tended to have more spatial structure than the weak layer. Though some trends are apparent, firm conclusions on the dependence of slope stability on spatial variations were not possible due to the limited range of snow conditions in the dataset, and the fact that the definition of slope stability remains elusive. Based on our limited data set, we can therefore not specify the conditions when spatial variations of weak layer and slab properties are most relevant for snow slab release.     

The energy release rate of mode II fractures in layered snow samples

Before a dry snow slab avalanche is released, a shear failure along a weak layer or an interface has to take place. This shear failure disconnects the overlaying slab from the weak layer. A better understanding of this fracture mechanical process, which is a key process in slab avalanche release, is essential for more accurate snow slope stability models. The purpose of this work was to design and to test an experimental set-up for a mode II fracture test with layered snow samples and to find a method to evaluate the interfacial fracture toughness or alternatively the energy release rate in mode II. Beam-shaped specimens were cut out of the layered snow cover, so that they consisted of two homogeneous snow layers separated by a well defined interface. In the cold laboratory 27 specimens were tested using a simple cantilever beam test. The test method proved to be applicable in the laboratory, although the handling of layered samples was delicate. An energy release rate for snow in mode II was calculated numerically with a finite element (FE) model and analytically using an approach for a deeply cracked cantilever beam. An analytical bilayer approach was not suitable. The critical energy release rate G _c was found to be 0.04 ± 0.02 J m⁻². It was primarily a material property of the weak layer and did not depend on the elastic properties of the two adjacent snow layers. The mixed mode interfacial fracture toughness for a shear fracture along a weak layer estimated from the critical energy release rate was substantially lower than the mode I fracture toughness found for snow of similar density.     

Quantifying changes in weak layer microstructure associated with artificial load changes

Researchers and practitioners have long utilized a variety of penetrometers to investigate the snowpack. Identifying definitive relationships between penetrometer-derived microstructural information and stability has been challenging. The purpose of this study is two-fold: 1. We propose a simple field test to establish relationships between load and penetrometer-derived microstructural estimates, 2. We utilize the SnowMicroPen (SMP) to quantify changes in weak layer residual strength and microstructural dimension associated with an artificial loading event. Our dataset is from Moonlight Basin, Montana and includes three modified loaded-column tests, each paired with 5 SMP profiles. Depth hoar comprised the targeted weak layer. Results indicate that loading caused the residual strength and rupture frequency to decrease significantly. Much like a compression test at a micro-scale, the force required for the SMP to rupture individual structures as well as the micro-scale strength decreased significantly when the slab stress was increased by artificially adding blocks of snow. A decrease in observed rupture frequency within the weak layer (or an increase in the distance between ruptured structures) also occurred after the loading event, probably because some structures within the weak layer had already failed or were so close to failing that the penetrometer could not detect their rupture. Due in part to the large difference in loads, microstructural differences between the natural and loaded columns were significant enough that only one profile would have been necessary to determine a significant difference in residual strength. Artificial removal of slab stress resulted in greater rupture forces and larger microstructures, likely due to elastic rebound.     

Upward-looking ground-penetrating radar for monitoring snowpack stratigraphy

Operational remote monitoring of snowpack stratigraphy, melt water intrusions and their evolution with time for forecasting snowpack stability is not possible to date. Determination of the spatial variability of snowpack conditions on various scales requires a number of point measurements with various methods. These methods are either destructive or do not provide information about the internal structure of the snowpack. The application of a remotely controlled non-destructive sensor system would help to gain a higher spatio-temporal resolution about information of the snowpack. In this study we present results from upward-looking ground-penetrating radar (GPR) surveys from horizontal caves dug in the front wall of snow pits at the bottom of the snowpack. GPR data are compared with vertical profiles of snow hardness and density, obtained in the snow pit. Data were acquired in different areas with varying snow conditions with various GPR impulse systems, frequencies and polarizations. Radar experiments with high frequencies (> 1 GHz) detect internal layers in the snowpack in dry snow, but fail to provide clear reflections at the upper snow-air transition because of attenuation. In wet snow, the radar signals < 1 GHz are capable to penetrate a meter-thick snowpack and detect the snow surface, although the signal is strongly attenuated. Analysis of reflection phases and magnitudes allows interpretation of their physical origin in terms of changes in electrical permittivity. Varying antenna polarization causes a strongly different signal response, likely caused by the snow-pit wall present in our set-up. Forward calculation of density-based reflection coefficients between neighboring layers of varying hardness yields ambiguous results in terms of correspondence with observed radar reflections apart except for interferences of neighboring reflections. Moreover, we identify several pitfalls for future applications. The system set-up used here represents a basis for further developments towards a system, which is capable of improving information on the spatial and temporal snowpack characteristics.     

The effect of surface warming on slab stiffness and the fracture behavior of snow

Surface warming is among the most complex contributory factors that need to be considered when forecasting dry-snow slab avalanches. The aim of the present study is to quantify surface warming with respect to the contributing meteorological processes and to investigate in situ crack propagation propensity under conditions of surface warming. The energy fluxes at the snow surface, partly measured and partly modeled with the snow cover model SNOWPACK, were used to determine the energy input into the snow cover. Stiffness of the near‐surface layers and its changes with daytime warming were derived from penetration resistance measurements with the snow micro-penetrometer (SMP) and related to the energy input. Changes in fracture behavior were assessed with the propagation saw test (PST). An average reduction in stiffness by a factor of about 2 was observed in near-surface snow layers when the cumulative energy input at the surface exceeded 300 kJ m^− 2. At the depth of the weak layer (~ 40 cm) changes were rather small; in particular for the specific fracture energy no trend was detected with warming. Critical cut lengths tended to decrease with decreasing slab stiffness, suggesting that surface warming increases crack propagation propensity. However, the effect seems to be subtle. It is suggested that a pre-existing weakness and significant energy input are required for surface warming to promote instability.     

Refinements of empirical models to forecast the shear strength of persistent weak snow layers: PART B: Layers of surface hoar crystals

Buried layers of surface hoar often release skier-triggered avalanches in the Columbia Mountains of Canada and their shear strength can be used to assess the stability of a slab overlaying these layers. In 2001 Chalmers introduced an Interval Model to calculate the shear strength of layers of surface hoar based on manual snowprofile observations. We refined his model by adjusting the measured shear strength for the normal load and included only data points where the weak layer depth did not exceed 100 cm to better account for skier triggering. Further, we used average and daily loading rates as well as a regression analysis to determine the best estimate of the shear strength change. Our final Forecasting Model used a multivariate regression to calculate the shear strength on days with snowprofile observations and as well as average and daily loading rates to forecast the shear strength on days without manual snowprofile observations. The performance of the model (r²) was 0.71 and 0.63 using average and daily loading rates, respectively. A companion paper, Part A, develops a forecasting model for weak layers of faceted crystals.