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Snow avalanches, one of the most severe natural hazards in mountainous regions, pose significant risks to human lives, infrastructure, and ecosystems. As climate change accelerates shifts in snowfall and temperature patterns, it is increasingly important to improve our ability to monitor and predict avalanches. This review explores the use of remote sensing technologies in understanding key geomorphological, geobotanical, and meteorological factors that contribute to avalanche formation. The primary objective is to assess how remote sensing can enhance avalanche risk assessment and monitoring systems. A systematic literature review was conducted, focusing on studies published between 2010 and 2025. The analysis involved screening relevant studies on remote sensing, avalanche dynamics, and data processing techniques. Key data sources included satellite platforms such as Sentinel-1, Sentinel-2, TerraSAR-X, and Landsat-8, combined with machine learning, data fusion, and change detection algorithms to process and interpret the data. The review found that remote sensing significantly improves avalanche monitoring by providing continuous, large-scale coverage of snowpack stability and terrain features. Optical and radar imagery enable the detection of crucial parameters like snow cover, slope, and vegetation that influence avalanche risks. However, challenges such as limitations in spatial and temporal resolution and real-time monitoring were identified. Emerging technologies, including microsatellites and hyperspectral imaging, offer potential solutions to these issues. The practical implications of these findings underscore the importance of integrating remote sensing data with ground-based observations for more robust avalanche forecasting. Enhanced real-time monitoring and data fusion techniques will improve disaster management, allowing for quicker response times and more effective policymaking to mitigate risks in avalanche-prone regions.

Understanding crack phenomena in the snowpack and their role in avalanche formation is imperative for hazard prediction and mitigation. Many studies have explored how structural properties of snow contribute to the initial instability of the snowpack, focusing particularly on failure initiation within weak snow layers and the onset of crack propagation. This work addresses the subsequent stage, the effect of slab touchdown after weak-layer failure in mixed-mode loading (compressive anticrack (mode I) and shear (mode II) loading). Our results demonstrate that slab touchdown reduces the energy release rate, which can lead to crack arrest even under static conditions. This challenges the idea that only the dynamic properties of snow layers and spatial snowpack variations govern arrest, emphasizing instead the crucial role of mechanical interactions between the slab, weak layer, and base layer. By integrating these findings into the broader context of snowpack stability analysis, we contribute to a more nuanced understanding of avalanche initiation mechanisms. The analysis is provided in a comprehensive open-source model (https://github.com/2phi/weac, last access: 11 June 2025).

The release process of dry-snow slab avalanches begins with a localized failure within a porous, weak snow layer beneath a cohesive slab. Subsequently, rapid crack propagation may occur within the weak layer, eventually leading to a tensile fracture across the slab, resulting, if the slope is steep enough, in its detachment and sliding. The dynamics of crack propagation is believed to influence the size of the release area. However, the relationship between crack propagation dynamics and avalanche size remains incompletely understood. Notably, crack propagation speeds estimated from avalanche video analysis are almost 1 order of magnitude larger than speeds typically measured in field experiments. To shed more light on this discrepancy and avalanche release processes, we used discrete (DEM: discrete element method) and continuum (MPM: material point method) numerical methods to simulate the so-called propagation saw test (PST). On low-angle terrain, our models showed that the weak layer failed mainly due to a compressive stress peak at the crack tip induced by weak layer collapse and the resulting slab bending. On steep slopes, we observed the emergence of a supershear crack propagation regime: the crack speed becomes higher than the slab shear wave speed. This transition occurs if the crack propagates over a distance larger than the super-critical crack length (approximately 5 m). Above the super-critical crack length, the fracture is mainly driven by the slope-parallel gravitational pull of the slab (tension) and, thus, shear stresses in the weak layer. These findings represent an essential additional piece in the dry-snow slab avalanche formation puzzle.

Liquid water flow in snow is important for snow hydrology, remote sensing, and avalanche formation. Water flow in snow is often dominated by capillary effects, which are responsible for the formation of capillary barriers, capillary flow paths, and capillary rise. Unfortunately, there is little quantitative data on the capillary forces of snow, particularly with respect to capillary rise dynamics. Here, we present the results of 4 capillary rise experiments using neutron radiography. The experiments were performed in 13×13×1 cm3 glass columns with sand-snow and sand-gravel-snow layering mimicking the capillary forces at the soil-snow interface. Images were taken at 10 to 15 s intervals with a pixel size of 92 µm. The experiments provided quantitative results of high resolution liquid water profiles, wetting front progression, flow rates, and parameterization of snow hydraulic properties. The experiments showed that the snow properties influenced the capillary rise height while the hydraulic properties of the transitional layer below the snow influenced the flow rates. The saturated hydraulic conductivity values obtained from the experiments were below the expected values from the literature.

Snow avalanches occur in snow-covered highland mountains and represent one of the most significant natural hazards pertaining to the field of geoscience. Although some insight into the formation of avalanches has been provided, a comprehensive overview or critical review of the latest research is currently lacking. This paper reviews recent advances on the formation process of dry slab avalanches and provides a guiding framework for further research. The formation of avalanches is the consequence of a series of fracture processes in the snowpack, which is usually induced by the failure of a weak layer underlying a snow slab layer. The parameters at each stage of avalanches’ formation are reviewed from theoretical, experimental and simulation perspectives. In terms of the onset of crack propagation, the understanding of the mechanical process has gone through a transition from shear theory, to the anticrack model and supershear. The critical length shows divergent trends with snowpack parameters and slope angles, and there is a lack of consensus in different models. The specific fracture energy is also an essential component in determining fracture propagation. Within cracks’ dynamic propagation, the crack propagation speed includes both the sub-Rayleigh regime and supershear. The crack speed exceeds the shear wave speed in the supershear mode. When the crack propagation reaches a specific distance, the slab undergoes a tensile fracture and the cracking’s arrest. The numerical simulation allows a complete reproduction of the initial failure, the crack’s dynamic propagation and slab fracture. In the future, a unified model is necessary through refining the formative mechanism and integrating it with the avalanche flow. This work offers a comprehensive understanding of the mechanics of the formation and release of avalanches, useful for both modelers and experimentalists.

The formation of avalanche hazards in mountainous regions is largely influenced by slope insolation and albedo. This paper presents a quantitative analysis of how solar radiation, surface reflectivity (albedo), temperature, and snow cover affect avalanche formation depending on slope aspect (north-, south-, east-, and west-facing). This study is based on remote sensing data from MODIS, ERA5-Land, CHIRPS, and a digital terrain model for the winter periods from 2000 to 2024. The results show that north-facing slopes have higher albedo values (up to 0.95) and greater snow cover stability (30–50%), which contributes to increased avalanche risk, especially at temperatures above −5 °C. South-facing slopes are characterized by lower albedo values (around 0.20–0.40) and more intense snowmelt, which reduces the likelihood of avalanches. Regression analysis revealed a strong positive correlation between snow depth and avalanche risk (r = 0.87), as well as a moderate negative correlation between temperature and snow cover stability (r = −0.25). The influence of albedo on avalanche risk was found to be indirect, acting through its impact on the surface energy balance. The resulting avalanche risk map demonstrated high accuracy (overall agreement: 86%; Kappa coefficient: 0.72), highlighting the effectiveness of an integrated approach based on geophysical and climatic parameters. The data obtained can be used to support avalanche safety management and slope assessment in the context of climate change.

This paper studies the influence of meteorological factors on avalanche occurrence in East Kazakhstan using modern data analysis methods. A dataset of 111 avalanche events in nine avalanche-prone areas of the region, recorded between 2012 and 2023, was compiled. Primary data on avalanche dates were obtained from the Department of Emergency Situations of East Kazakhstan Region (DES EKR), and meteorological data were sourced from the Kazhydromet website. Descriptive statistics, correlation analysis, principal component analysis (PCA), as well as K-means clustering and DBSCAN algorithms, were used for the analysis. During the analysis of meteorological conditions preceding avalanches at nine avalanche-prone areas in Eastern Kazakhstan, using PCA (Principal Component Analysis), the main weather factors affecting avalanche formation were determined. Clustering of 111 avalanches using the K-Means method allowed the identification of four scenario types: gradual snow accumulation without wind (33 cases), upper layer thawing due to warming (34), high snow cover (28), and storm impact (16). The DBSCAN method revealed two anomalous cases related to extreme snow depth. Correlation analysis revealed significant relationships between avalanches and meteorological parameters such as air temperature, snow cover depth, wind speed and direction, precipitation, and relative humidity. Correlation analysis revealed both negative and positive relationships between meteorological parameters. Principal component analysis identified the most significant variables affecting avalanche activity, with temperature, snow cover height, and wind making the greatest contributions. Cluster analysis demonstrated that avalanches could occur under different combinations of weather conditions within the same areas, confirming the complex nature of avalanche-forming processes. The results emphasize the need for an integrated approach to avalanche forecasting that accounts for the multi-parametric interactions of meteorological factors, and may contribute to the improvement of avalanche risk monitoring and mitigation systems in mountain regions.

Mountain forests provide natural protection against avalanches. They can both prevent avalanche formation in release zones and reduce avalanche mobility in runout areas. Although the braking effect of forests has been previously explored through global statistical analyses on documented avalanches, little is known about the mechanism of snow detrainment in forests for small and medium avalanches. In this study, we investigate the detrainment and braking of snow avalanches in forested terrain, by performing three-dimensional simulations using the material point method (MPM) and a large-strain elastoplastic snow constitutive model based on critical state soil mechanics. First, the snow internal friction is evaluated using existing field measurements based on the detrainment mass, showing the feasibility of the numerical framework and offering a reference case for further exploration of different snow types. Then, we systematically investigate the influence of snow properties and forest parameters on avalanche characteristics. Our results suggest that for both the cold and warm snow parameterized in our simulations, the detrainment mass decreases with the square of the avalanche front velocity before it reaches a plateau value. Furthermore, the detrainment mass significantly depends on snow properties. It can be as much as 10 times larger for warm snow compared to cold snow. By examining the effect of forest configurations, it is found that forest density and tree diameter have cubic and square relations with the detrainment mass, respectively. The outcomes of this study may contribute to the development of improved formulations of avalanche–forest interaction models in popular operational simulation tools and thus improve hazard assessment for alpine geophysical mass flows in forested terrain.

Earth's snow cover is very dynamic on diurnal timescales. The changes to the snow structure during this metamorphism have wide-ranging impacts on processes such as avalanche formation and on the capacity of surface snow to exchange trace gases with the atmosphere. Here, we investigate the influence of dry metamorphism, which involves fluxes of water vapour, on the chemical reactivity of bromide in the snow. To this end, the heterogeneous reactive loss of ozone in the dark at a concentration of 5×1012–6×1012 molec. cm−3 is investigated in artificial, shock-frozen snow samples doped with 6.2 µM sodium bromide and with varying metamorphism history. The oxidation of bromide in snow is one reaction initiating polar bromine releases and ozone depletion. We find that the heterogeneous reactivity of bromide is completely absent from the air–ice interface in snow after 12 d of temperature gradient metamorphism, and we suggest that the burial of non-volatile bromide salts occurs when the snow matrix is restructuring during metamorphism. Impacts on polar atmospheric chemistry are discussed.

Snow gliding is a key factor for snow-glide avalanche formation and soil erosion. This study considers atmospheric and snow variables, vegetation characteristics, and soil properties and determines their relevance for snow gliding at a test site (Wildkogel, Upper Pinzgau, Austria) during winter 2014/2015. The time-dependent data were collected at a high temporal resolution. In addition to conventional sensors, a “snow melt analyzer” was used. The analysis shows that the soil temperature 10 cm below the surface, the phytomass of mosses, the liquid water content in the snowpack, and the static friction coefficient of the glide shoes had significant influence on snow gliding during the whole winter. In the first period (October to January) the soil moisture at the surface and 1.5 cm below the surface and the length of the slope uphill of the glide shoes affected the snow gliding, too. In the second period (February to May) the soil temperature at the surface, the soil moisture 10 cm below the surface, and the slope angle had additional influence on snow gliding. The role of the vegetation in the snow-glide process is determined by the influence on the static friction coefficient caused by its composition and characteristics and by moss-rich and short-stemmed canopies being seemingly more interconnected with the snowpack. In addition to the soil and snow properties, the topography and the vegetation characteristics, further investigations may be focused on the freezing and melting processes in the uppermost soil layers and at the soil surface.