Numerical investigation of crack propagation regimes in snow fracture experiments.

A snow slab avalanche releases after failure initiation and crack propagation in a highly porous weak snow layer buried below a cohesive slab. While our knowledge of crack propagation during avalanche formation has greatly improved over the last decades, it still remains unclear how snow mechanical properties affect the dynamics of crack propagation. This is partly due to a lack of non-invasive measurement methods to investigate the micro-mechanical aspects of the process. Using a DEM model, we therefore analyzed the influence of snow cover properties on the dynamics of crack propagation in weak snowpack layers. By focusing on the steady-state crack speed, our results showed two distinct fracture process regimes that depend on slope angle, leading to very different crack propagation speeds. For long experiments on level terrain, weak layer fracture is mainly driven by compressive stresses. Steady-state crack speed mainly depends on slab and weak layer elastic moduli as well as weak layer strength. We suggest a semi-empirical model to predict crack speed, which can be up to 0.6 times the slab shear wave speed. For long experiments on steep slopes, a supershear regime appeared, where the crack propagation speed reached approximately 1.6 times the slab shear wave speed. A detailed micro-mechanical analysis of stresses revealed a fracture principally driven by shear. Overall, our findings provide new insight into the micro-mechanics of dynamic crack propagation in snow, and how these are linked to snow cover properties. Supplementary Information: The online version contains supplementary material available at 10.1007/s10035-024-01423-5.

Prevention of Hypothermia in the Aftermath of Natural Disasters in Areas at Risk of Avalanches, Earthquakes, Tsunamis and Floods.

Throughout history, accidental hypothermia has accompanied natural disasters in cold, temperate, and even subtropical regions. We conducted a non-systematic review of the causes and means of preventing accidental hypothermia after natural disasters caused by avalanches, earthquakes, tsunamis, and floods. Before a disaster occurs, preventive measures are required, such as accurate disaster risk analysis for given areas, hazard mapping and warning, protecting existing structures within hazard zones to the greatest extent possible, building structures outside hazard zones, and organising rapid and effective rescue. After the event, post hoc analyses of failures, and implementation of corrective actions will reduce the risk of accidental hypothermia in future disasters.

Micro-mechanical insights into the dynamics of crack propagation in snow fracture experiments.

Dry-snow slab avalanches result from crack propagation in a highly porous weak layer buried within a stratified and metastable snowpack. While our understanding of slab avalanche mechanisms improved with recent experimental and numerical advances, fundamental micro-mechanical processes remain poorly understood due to a lack of non-invasive monitoring techniques. Using a novel discrete micro-mechanical model, we reproduced crack propagation dynamics observed in field experiments, which employ the propagation saw test. The detailed microscopic analysis of weak layer stresses and bond breaking allowed us to define the crack tip location of closing crack faces, analyze its spatio-temporal characteristics and monitor the evolution of stress concentrations and the fracture process zone both in transient and steady-state regimes. Results highlight the occurrence of a steady state in crack speed and stress conditions for sufficiently long crack propagation distances (> 4 m). Crack propagation without external driving force except gravity is possible due to the local mixed-mode shear-compression stress nature at the crack tip induced by slab bending and weak layer volumetric collapse. Our result shed light into the microscopic origin of dynamic crack propagation in snow slab avalanche release that eventually will improve the evaluation of avalanche release sizes and thus hazard management and forecasting in mountainous regions.

Effects of Climate Change on Avalanche Accidents and Survival.

Avalanches are major natural hazards in snow-covered mountains, threatening people and infrastructure. With ongoing climate change, the frequency and types of snow avalanches may change, affecting the rates of avalanche burial and survival. With a wetter and warmer snow climate, consequences of burial may become more severe. In this review, we assess the potential effects of climate change on the frequency and characteristics of avalanches. We then discuss how these changes might affect the survival rates of subjects buried by avalanches and might influence the responses of search and rescue (SAR) teams and health care providers. While climate change is inevitable, the effects on avalanches remain elusive. The frequency of human triggered avalanches may not change, because this depends largely on the number and behavior of winter recreationists. Blunt trauma and secondary injuries will likely become more frequent as terrain roughness is expected to rise and snow cover to become thinner. Higher snow densities in avalanche debris will likely interfere with the respiration of completely buried victims. Asphyxia and trauma, as causes of avalanche death, may increase. It is unlikely that SAR and health care providers involved in avalanche rescue will have to change their strategies in areas where they are already established. The effects of climate change might foster the expansion of mitigation strategies and the establishment of mountain rescue services in areas subject to increased avalanche hazards caused by changes in snow cover and land use.

Hypoxia and hypercapnia effects on cerebral oxygen saturation in avalanche burial: A pilot human experimental study.

BACKGROUND: A sufficient supply of oxygen is crucial to avoid hypoxic cardiac arrest and brain damage within 30 min in completely-buried avalanche victims. Snow density influences levels of hypoxia and hypercapnia. The goal of this study was to investigate the effects of hypoxia and hypercapnia on cerebral oxygenation (ScO2) in humans breathing into an artificial air pocket. METHODS: Each subject breathed into a closed system (air-tight face mask - plastic tube - snow air-pocket of 4 L) up to 30 min. Each subject performed three tests in different snow densities. ScO2 was measured by a near-infrared spectroscopy (NIRS) device. Measurements included peripheral oxygen saturation (SpO2), end-tidal carbon dioxide (ETCO2), air pocket gases and blood gases. Snow density was assessed via standard methods and micro-computed tomography. Based on predetermined criteria, tests were classified based on whether they were terminated before 30 min and the reason for termination. The categories were: completed tests (30 min), tests terminated before 30 min when SpO2 dropped to ≤75% and tests that were terminated before 30 min by requests of the subjects. General linear models were used to compare termination groups for changes in ScO2, ETCO2, SpO2 and air pocket gases, and a multivariate analysis was used to detect factor independent effects on ScO2. RESULTS: ScO2 was decreased in the group in which the tests were terminated for SpO2 ≤ 75% caused by a decrease in oxygen supply in high snow densities. In the completed tests, an increase in ScO2 occurred despite decreased oxygen supply and decreased carbon dioxide removal. CONCLUSIONS: Our data show that ScO2 determined by NIRS was not always impaired in humans breathing into an artificial air pocket despite decreased oxygen supply and decreased carbon dioxide removal. This may indicate that in medium to low snow densities brain oxygenation can be sufficient, which may reflect the initial stage of the triple H (hypothermia, hypoxia, and hypercapnia) syndrome. In high snow densities, ScO2 showed a significant decrease caused by a critical decrease in oxygen supply. This could lead to a higher risk of hypoxic cardiac arrest and brain damage.

Fiber-bundle model with time-dependent healing mechanisms to simulate progressive failure of snow.

Snow is a heterogeneous material with strain- and/or load-rate-dependent strength. In particular, a transition from ductile-to-brittle failure behavior with increasing load rate is observed. The rate-dependent behavior can partly be explained with the existence of a unique healing mechanism in snow that stems from its high homologous temperature (temperature close to melting point). As soon as broken elements in the ice matrix get in contact, they start sintering and the structure may regain strength. Moreover, the ice matrix is subjected to viscous deformation, inducing a relaxation of local load concentrations and, therefore, further counteracting the damage process. Ideal tools for studying the failure process of heterogeneous materials are the fiber-bundle models (FBMs), which allow investigating the effects of basic microstructural characteristics on the general macroscopic failure behavior. We present an FBM with two concurrent time-dependent healing mechanisms: sintering of broken fibers and relaxation of load inhomogeneities. Sintering compensates damage by creating additional intact, load-supporting fibers which lead to an increase of the bundle strength. However, the character of the failure is not changed by sintering alone. With combined sintering and load relaxation, load is distributed from old stronger fibers to new fibers that carry fewer load. So as we additionally incorporated load redistribution to the FBM, the failure occurred suddenly without decrease of the order parameter-describing the amount of damage in the bundle-and without divergence of the fiber failure rate. Moreover, the b value, i.e., the power-law exponent of frequency-magnitude statistics of fibers breaking in load redistribution steps, at failure converged to b≈2, a value higher than that of a classical FBM without healing (b=3/2). These results indicate that healing, as the combined effect of sintering and load relaxation, changes the type of the phase transition at failure. This change of the phase transition is important for quantifying or predicting the failure (e.g., by monitoring acoustic emissions) of snow or other materials for which healing plays an important role.

Effects of snow properties on humans breathing into an artificial air pocket - an experimental field study.

Breathing under snow, e.g. while buried by a snow avalanche, is possible in the presence of an air pocket, but limited in time as hypoxia and hypercapnia rapidly develop. Snow properties influence levels of hypoxia and hypercapnia, but their effects on ventilation and oxygenation in humans are not fully elucidated yet. We report that in healthy subjects breathing into snow with an artificial air pocket, snow density had a direct influence on ventilation, oxygenation and exhaled CO2. We found that a rapid decline in O2 and increase in CO2 were mainly associated with higher snow densities and led to premature interruption due to critical hypoxia (SpO2 ≤ 75%). However, subjects in the low snow density group demonstrated a higher frequency of test interruptions than expected, due to clinical symptoms related to a rapid CO2 accumulation in the air pocket. Snow properties determine the oxygen support by diffusion from the surrounding snow and the clearance of CO2 by diffusion and absorption. Thus, snow properties are co-responsible for survival during avalanche burial.

A concept for optimizing avalanche rescue strategies using a Monte Carlo simulation approach.

Recent technical and strategical developments have increased the survival chances for avalanche victims. Still hundreds of people, primarily recreationists, get caught and buried by snow avalanches every year. About 100 die each year in the European Alps-and many more worldwide. Refining concepts for avalanche rescue means to optimize the procedures such that the survival chances are maximized in order to save the greatest possible number of lives. Avalanche rescue includes several parameters related to terrain, natural hazards, the people affected by the event, the rescuers, and the applied search and rescue equipment. The numerous parameters and their complex interaction make it unrealistic for a rescuer to take, in the urgency of the situation, the best possible decisions without clearly structured, easily applicable decision support systems. In order to analyse which measures lead to the best possible survival outcome in the complex environment of an avalanche accident, we present a numerical approach, namely a Monte Carlo simulation. We demonstrate the application of Monte Carlo simulations for two typical, yet tricky questions in avalanche rescue: (1) calculating how deep one should probe in the first passage of a probe line depending on search area, and (2) determining for how long resuscitation should be performed on a specific patient while others are still buried. In both cases, we demonstrate that optimized strategies can be calculated with the Monte Carlo method, provided that the necessary input data are available. Our Monte Carlo simulations also suggest that with a strict focus on the "greatest good for the greatest number", today's rescue strategies can be further optimized in the best interest of patients involved in an avalanche accident.

Measuring snow liquid water content with low-cost GPS receivers.

The amount of liquid water in snow characterizes the wetness of a snowpack. Its temporal evolution plays an important role for wet-snow avalanche prediction, as well as the onset of meltwater release and water availability estimations within a river basin. However, it is still a challenge and a not yet satisfyingly solved issue to measure the liquid water content (LWC) in snow with conventional in situ and remote sensing techniques. We propose a new approach based on the attenuation of microwave radiation in the L-band emitted by the satellites of the Global Positioning System (GPS). For this purpose, we performed a continuous low-cost GPS measurement experiment at the Weissfluhjoch test site in Switzerland, during the snow melt period in 2013. As a measure of signal strength, we analyzed the carrier-to-noise power density ratio (C/N0) and developed a procedure to normalize these data. The bulk volumetric LWC was determined based on assumptions for attenuation, reflection and refraction of radiation in wet snow. The onset of melt, as well as daily melt-freeze cycles were clearly detected. The temporal evolution of the LWC was closely related to the meteorological and snow-hydrological data. Due to its non-destructive setup, its cost-efficiency and global availability, this approach has the potential to be implemented in distributed sensor networks for avalanche prediction or basin-wide melt onset measurements.

Upward-looking L-band FMCW radar for snow cover monitoring.

Forecasting snow avalanche danger in mountainous regions is of major importance for the protection of infrastructure in avalanche run-out zones. Inexpensive measurement devices capable of measuring snow height and layer properties in avalanche starting zones may help to improve the quality of risk assessment. We present a low-cost L-band frequency modulated continuous wave radar system (FMCW) in upward-looking configuration. To monitor the snowpack evolution, the radar system was deployed in fall and subsequently was covered by snowfalls. During two winter seasons we recorded reflections from the overlying snowpack. The influence of reflection magnitude and phase to the measured frequency spectra, as well as the influence of signal processing were investigated. We present a method to extract the phase of the reflection coefficients from the phase response of the frequency spectra and their integration into the presentation of the measurement data. The phase information significantly improved the detectability of the temporal evolution of the snow surface reflection. We developed an automated and a semi-automated snow surface tracking algorithm. Results were compared with independently measured snow height from a laser snow-depth sensor and results derived from an upward-looking impulse radar system (upGPR). The semi-automated tracking used the phase information and had an accuracy of about 6 to 8 cm for dry-snow conditions, similar to the accuracy of the upGPR, compared to measurements from the laser snow-depth sensor. The percolation of water was observable in the radargrams. Results suggest that the upward-looking FMCW system may be a valuable alternative to conventional snow-depth sensors for locations, where fixed installations above ground are not feasible.