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This study represents a pioneering effort to analyze the impact of avalanches descending into Morskie Oko from Marchwiczny Gully, the most active avalanche path around the lake. It focuses on catastrophic avalanches that descended from the analyzed gully, as reported in the literature from the 1900s until now. However, only the data collected in recent years, our field studies, combined with modern LIDAR data and GIS-based modeling, allowed us to perform a detailed analysis. The GIS-based approach effectively uses spatial data to address snow avalanche modeling challenges. Although the study area lies within Tatra National Park, no official services carry out systematic avalanche monitoring or measurements. The impact of hazardous events, such as snow avalanches, on the most famous Polish mountain lake, Morskie Oko, has been poorly described in the literature and has yet to be discovered. Therefore, to analyze the selected avalanche parameters, we mainly used our ground and additional aerial photographs taken by local mountain services and related field measurements. Our analysis resulted in figurative estimates of the extent and volume of avalanche snow and its weight, both on the surface of the ice sheet and the part of the avalanche that did not reach the lake's shore and remained on the slope of Marchwiczny Gully. For example, the values for the mighty avalanche on February 3, 2023, are 23,500 m3 and 4,700 tons on the ice surface and 20,000 m3 and 4,000 tons on the slope. It was determined that avalanches that descend onto the studied lake's surface result in its shallowing. This process occurs because of sedimentation of slope material carried by avalanches, especially during the final phase of ice cover melting. When openings appear in the solid ice cover in spring, floating ice can migrate, driven by wind pressure, and deposit avalanche material in various parts of the lake bottom. Thus, avalanches contributed to the gradual disappearance of the lake. [ABSTRACT FROM AUTHOR]

Snow avalanches are a major natural hazard threatening human life and infrastructure in mountainous areas. They have a sudden onset and involve the rapid transport of large masses of snow and ice down on steep slopes. Thus, it is essential for risk management activities to understand avalanche activity, frequency and triggers. In this study, the dendrogeomorphic method was used to analyse an avalanche path in the Țarcu Mountains (the Southern Carpathians) in order to reconstruct the spatio-temporal activity of past snow avalanches. The reconstruction was based on the dating of growth disturbances caused by the mechanical impact of snow avalanches on trees. A total of 186 increment cores were analysed, resulting in the identification of 374 growth disturbances, including traumatic resin ducts, reaction wood, growth suppression and scars. In a chronology spanning 101 years in Picea abies, 13 events with It between 10-20% and 6 events with It between 20-40% were reconstructed over the period 1965-2021. The frequency of snow avalanche events was calculated, resulting in an average of 17.7 years. The climatic parameters were analysed for the event years exhibiting the strongest signal. The occurrence of avalanches was associated with warmer weather and rainy days. Event year 2010 is evidenced by a tragic incident in which two individuals lost their lives in the vicinity of the Țarcu weather station. Eleven events are synchronous with those analysed in other avalanche paths, while the event year 2005 is synchronous in nine other avalanche paths. [ABSTRACT FROM AUTHOR]

Most of the available models for estimating the snow avalanche impact pressures are 2D in nature. In this work, a 3D non-Newtonian Navier-Stokes equations–based simulation model is developed. For transient comparison, snow avalanche impact pressures were measured on an instrumented obstacle of 1 m height and 0.65 m width for high-density moist snow. This experimental setup was developed and installed on a 61-m-long facility at a research station near Manali, Himachal Pradesh, India. Based on experimentations and simulations carried out in the current work, the measured and simulated avalanche impact pressures were correlated, which can be used to estimate the avalanche impact pressures on the structures for the dense flow of avalanches. The root mean square error between the currently proposed model and the measured data is nearly 10.74, which is significantly less than the existing models for the estimation of the avalanche impact pressures on the obstacles. Further, the effective drag coefficient $C_d^'$ C d ′ for the avalanche flow and the instrumented obstacle, which takes into account the combined effects of the fluid, solid, granular, and compressibility effects of the flowing snow, is found in the range of 3.97 to 8.54, which is in agreement with published studies. [ABSTRACT FROM AUTHOR]

The purpose of the study was to date the powerful snow avalanches occurred in the avalanche catchment area in the river Korgon basin (Northwestern Altai) by the dendrochronological method. The paper presents the results of the analysis of a number of dendrochronological indicators of avalanches: the age of trees, the relation between widths of annual rings from opposite sides of the trunk, the presence of reactive (compressional) wood and traumatic resin canals, the dates of death and formation of wounds in trees, the presence of clearing effects (a sharp increase in growth) in three avalanche catchments, as well as a complex dendrochronological index of the avalanche activity. The dates of releases of the powerful avalanches were established down to 1570. It has been found that against the background of increasing amount of winter precipitation in these catchments, there are different trends in occurrence of the avalanches, which is determined by their morphological properties. In the avalanche areas with steeper slopes, due to repeated unloading of the avalanche centers in winter, the probability of releasing of powerful avalanches decreases. For the same reason, the powerful avalanches do not release during the years of maximum snow accumulation. The trends in the avalanche activity in the region under consideration had been obtained for the first time. The dendrochronological index of the avalanche activity, which is the ratio of the number of the tree growth failures to the number of the examined trees, is a good indicator of a release of a powerful avalanche even at a value of 0.85, provided that the number of examined trees in the lower part of the transit zone and in the zone of accumulation is 25–35 units. The results of this study may be used to predict the territorial differentiation of changes in the avalanche activity due to climate change. In connection with the recreational development of the Altai territory, they may also be of practical importance.

The article proposes a methodological approach to quantifying direct economic damage from unfavorable and hazardous natural processes and phenomena for railways—an element of the critical infrastructure of the Russian Federation. The methodology is based on a normative approach to assessing the replacement cost of railway lines, which varies depending on the cost of construction in the orographic and climatic conditions of a particular region. The results are presented in the context of municipalities, which makes it possible to better take into account intraregional differences and facilitates their comparison with parameters characterizing natural hazards (floods, hazardous slope-related and geocryological processes, etc.). The calculations showed that the maximum cost of replacing railway lines in the event of natural threats for the country as a whole is about RUB 11 trln in 2021 prices, or approximately 8.4% of Russia's GDP for this year. The first ten regions in terms of the maximum amount of probable damage—Irkutsk, Amur, and Sverdlovsk oblasts; Khabarovsk, Zabaykalsky, Krasnoyarsk, Altai, Krasnodar, and Primorsky krais; and the Republic of Buryatia—account for over 40% of the total replacement cost. It is in these regions that measures to protect the fixed assets of railway transport are particularly important. The obtained data can be used in studies of natural and man-made risk: by comparing them with parameters characterizing the impact of hazardous natural processes and phenomena, it is possible to predict the risk and probable damage to railway infrastructure facilities in certain territories. Using the example of snow avalanches and permafrost degradation due to climate change in the Russian Arctic, the possibilities of this type of assessment are demonstrated. [ABSTRACT FROM AUTHOR]

The performed dendrochronological analysis of the radial growth of coniferous trees in the avalanche paths of the Chuya River basin (Central Altai) has enabled to define the patterns of avalanche activity in the studied starting zones and the frequency of high-magnitude snow avalanches. It is shown that a tree-ring complex indicator is driving in detection of avalanche activity in specific avalanche paths. We suggest calling it the dendrochronological index of avalanche activity. In some cases, the applied dendrochronological method has helped to identify the cause (factor) of avalanching in the area under study.

Most of the available models for estimating the snow avalanche impact pressures are 2D in nature. In this work, a 3D non-Newtonian Navier-Stokes equations–based simulation model is developed. For transient comparison, snow avalanche impact pressures were measured on an instrumented obstacle of 1 m height and 0.65 m width for high-density moist snow. This experimental setup was developed and installed on a 61-m-long facility at a research station near Manali, Himachal Pradesh, India. Based on experimentations and simulations carried out in the current work, the measured and simulated avalanche impact pressures were correlated, which can be used to estimate the avalanche impact pressures on the structures for the dense flow of avalanches. The root mean square error between the currently proposed model and the measured data is nearly 10.74, which is significantly less than the existing models for the estimation of the avalanche impact pressures on the obstacles. Further, the effective drag coefficient [Formula: see text] for the avalanche flow and the instrumented obstacle, which takes into account the combined effects of the fluid, solid, granular, and compressibility effects of the flowing snow, is found in the range of 3.97 to 8.54, which is in agreement with published studies.

Snow avalanches constitute a dangerous natural hazard in snow-clad mountain regions. Spaceborne synthetic aperture radar (SAR) has emerged as an effective tool for monitoring avalanche activity also in remote areas due to its all-weather capabilities and sensitivity to the presence of avalanche debris. The objective of this study was the application of a novel polarimetric change detection approach to the task of identifying avalanche debris candidate areas and characterizing the impact of factors, such as avalanche size and topography, on its performance. We applied polarimetric change vectors (PCVs) for change detection between pairs of Sentinel-1 SAR images acquired over the Swiss Alps during a two-month period characterized by episodes of exceptionally high avalanche activity. PCV were classified using a two-step mixture analysis of their magnitude and direction components. Candidates for avalanche debris were matched against a reference database of $>$ 16 000 avalanche outlines. The detected changes were largely attributed to snow processes, such as transitions from dry to wet snow and vice versa, as well as the occurrence of avalanches. 23% of all reference avalanche polygons could be matched to retrieved avalanche debris patches. The matching rate strongly depended on avalanche size, reaching $>$ 33% for very large (size 4) avalanches and, to a lesser degree, on the orientation of the avalanche relative to the look direction of the sensor. Apart from constituting a standalone approach for detecting avalanche debris candidate areas, the PCV method has potential for integration into automatic avalanche detection workflows based on machine learning methods.

The rapid deglaciation in the Upper Indus Basin (UIB) significantly impacts local landscapes, watersheds, and basin-wide hydrology. While creating new opportunities, such as emerging landscapes and hydrological changes, deglaciation simultaneously heightens the risk of glacio-hydrological hazards in adjacent and downstream regions. With limited available land for agriculture and settlements, communities around glaciers expand human activities toward newly formed floodplains and deglaciating valleys, necessitating a comprehensive understanding of associated risks and vulnerabilities. This study employs Geographical Information System (GIS) and Remote Sensing products for a multicriteria hazards susceptibility assessment in the Shigar Valley, located in the downstream of major Himalayan glaciers - the Baltoro (63 km) and Biafo (67 km) glaciers. The research reveals that 28.3% of the valley is highly susceptible to multiple hazards, emphasizing the urgency of informed decision-making in the region. Only 0.03% area lies in the very low susceptible category, 9.7% in the low susceptible, 60.6% in the moderately susceptible, and 1.04% in the very highly susceptible categories. These findings highlight the need for proactive measures, adaptive strategies, and sustainable development in the Shigar Valley to mitigate the escalating risks posed by deglaciation and changing hydrological patterns. [ABSTRACT FROM AUTHOR]

The intense snow activity in the medium and high altitude of the Cantabrian division mountains produces an accumulation of significant thickness of snow that unchains forceful avalanches that put human lives and infrastructure at risk. For this work, a general analysis is carried out through GIS of the conditions for the triggering of avalanches in the Somiedo valley, southwest part of the Principality of Asturias. It is added to this analysis the information observed during the fieldwork, photo-interpretation, interviews and historical sources, in order to realize the damage caused by these processes to the vegetation and infrastructure, especially on the AS-227, between the villages of Caunedo and Santa Maria del Puerto. Cartography of the valley's environment is also provided: maps of vegetation, susceptibility and risk on the road. In addition, the development of AR in different media is proposed to host this cartography and in order to allow the viewer a more interactive and academic analysis on the study of avalanche risk. [ABSTRACT FROM AUTHOR]

Snow avalanches are thought to influence large wood dynamics within mountain streams, but studies that explicitly quantify their impact are minimal. In three headwater catchments of the Frying Pan River, Colorado, USA, we found that wood loads in stream reaches intersected by avalanche pathways ranged from 220 to 8,500 m3/ha and were significantly greater than in non‐avalanched reaches. Inter‐catchment differences in the number of avalanche occurrences were not reflected in control reach wood loads, suggesting that elevated loads may be restricted to the general vicinity of the avalanche pathway. However, the sizable wood volumes in avalanche reaches generated notable geomorphic impacts, indicating that avalanches can create hotspots of in‐stream geomorphic complexity and influence the overall habitat mosaic of the stream ecosystem. Loads in avalanche reaches were moreover significantly greater than literature values for similar streams and recruitment processes, emphasizing the importance of snow avalanches as a wood recruitment mechanism. Plain Language Summary: Snow avalanches are thought to contribute downed, dead wood to mountain streams, but the volume and mobility of supplied wood is unknown. Because downed wood is important for many stream processes (such as habitat creation and sediment storage), an increased understanding of the importance of avalanches for wood supply has notable implications for management of mountain watersheds and their ecosystems. Here we study several streams within the Frying Pan River Basin in Colorado, USA, where avalanche paths commonly intersect the streams that flow along steep mountain valley bottoms. We find that the volume of wood within the length of stream intersected by snow avalanches that occurred in Winter 2019 is substantially greater than the wood volumes outside those reaches. We additionally discover that in‐stream wood volumes within the avalanche areas in this study are significantly greater than values reported by other studies for similar streams and recruitment processes. Overall, our work further emphasizes that avalanches are important suppliers of wood to mountain streams and calls for future studies to continue to expand understanding of how snow avalanches impact mountain stream ecosystems. Key Points: In‐stream wood loads supplied by avalanches are on the order of 102–103 m3/ha within avalanche‐impacted reachesAvalanche‐derived wood may have low mobility but generate hotspots of geomorphic complexityLoads in avalanche reaches are significantly larger than literature values for comparable streams and recruitment mechanisms [ABSTRACT FROM AUTHOR]

The article deals with the experience of using an unmanned aerial vehicle (DJI Matrice 300 RTK) and Agisoft Metashape software to obtain the characteristics of avalanches that descended in late March in the Shukur and Kotyrbulak tracts (Pioneer avalanche) in the Ile Alatau mountains. UAVs can perform observations in remote and dangerous areas, quickly reach the scene, and capture high-quality images and video. In Agisoft Metashape, data processing is performed to create digital elevation maps, 3D models and obtain various geometric data. The resulting data can be used to analyze and predict avalanche processes, as well as to develop measures to reduce the risk of such processes in the future. [ABSTRACT FROM AUTHOR]

Greenland's peripheral glaciers are losing mass at an accelerated rate and are contributing significantly to sea level rise, but only a few direct observations are available. Here, we use the unique combination of high-resolution remote sensing data and direct mass balance observations to separate and quantify the contribution of a singular avalanche event to the mass balance of Freya Glacier (74.38° N, 20.82 W), a small (5.5 km², 2021) mountain glacier in Northeast Greenland. Elevation changes calculated from repeated photogrammetric surveys on 11th -18th August 2013 and on 28th - 31st July 2021 range from -11 m to 18 m, with a glacier-wide mean of 1.56 + 0.10 m (0.85 + 0.20 m w.e.). Somewhat surprisingly, the geodetic mass balance over the full period of 8 years (2013/14 - 2020/21) is slighly positive, (0.25 + 0.21 m w.e.). A main imprint of the near decadal mass balance stems from the exceptional (2.5 standard deviations above average) winter mass balance of 2017/18 with 1.85 + 0.05 m w.e., when in addition to above average precipitation, snow avalanches affected more than one third of the glacier surface and contributed at least 0.31 m w.e. (17%) to the total winter mass balance of 2017/18. We estimate the contribution of avalanches to the accumulated mass balance 2013/14 - 2020/21 as 0.55 m w.e. Without this avalanche event the 8-year mass balance would have been slightly negative, -0.30 m w.e. instead of 0.25 m w.e. Due to a gap in valid observations caused by high accumulation rates and the COVID-19 pandemic the recently reported glacier-wide annual mass balance values now turn out to have a negative bias and demand a thorough reanalysis. Finally, we speculate that the projected future warming increases the likelihood of extreme snowfall events for individual years and thus, may increase the contribution of snow avalanches to the mass balance of mountain glaciers in NE Greenland. [ABSTRACT FROM AUTHOR]

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Abstract Snow avalanches can repeatedly occur along the same track under different snowpack and meteorological conditions during the snow season in areas of snow avalanche activity. The snowfall, air temperature, and snow cover can change dramatically in a warming climate, causing significant changes in the snow avalanche risk. But how the risk of snow avalanche activity during the snow season will change under a warming climate remains an open question. Based on the observed meteorological and snowpack data from 1968 to 2021 and the snow avalanche activity data during the 2011–2021 snow seasons along a transportation corridor in the central Tianshan Mountains that has a typical continental snow climate, we analyzed the temporal distribution of the snow avalanche activity and the impacts of climate change on it. The results indicate that the frequency of the snow avalanche activity is characterized by a Gaussian bimodal distribution, resulting from interactions between the snowfall, air temperature, and snowpack evolution. In addition, the active period of wet snow avalanches triggered by temperature surges and high solar radiation has gradually moved forward from the second half to the first half of March with climate warming. The frequency and size of snowfall-triggered snow avalanches showed only a slight and insignificant increase. These findings are important for rationally arranging snow avalanche relief resources to improve the risk management of snow avalanche disasters, and highlight the necessity to immediately design risk mitigation strategies and disaster risk policies to improve our adaptation to climate change.

In this article, we study snow avalanche activity during the snow seasons of 2017–2020 using four automatic time-lapse cameras strategically positioned along the southwestern slope of Tasiapik Valley, near the village of Umiujaq, in Nunavik (northern Québec, Canada). Over the three snow seasons, cameras helped to detect evidence of 130 avalanche events, scattered over seventy-eight distinct avalanche days. The evolution of weather conditions prior to each avalanche release was detailed according to data from a nearby weather station. Moreover, the time of release, the release type, the surface texture, and whether rocky material was present in the deposits were documented from the photographs. To explore relationships between weather data and avalanche releases, conditional inference tree (CIT) analysis was conducted. Results of the CIT analysis showed that there are different weather patterns associated with avalanche releases depending on the season, and significant thresholds values were defined. In winter, the avalanche probability was greater when three-day snowfall total exceeded 10 cm. In spring, the avalanche probability was greater when cumulative melting degree-days were less than forty-six and when daily minimum air temperature was greater than 2°C. Moreover, cornice failures were found to be a major component of the avalanche dynamic in Tasiapik Valley, mainly because of the slope’s morphology. They have also been the cause of the three largest volume and longest runout avalanches observed by cameras in this study, highlighting potential risks for local communities. The probability of observing cornice failures is enhanced on days when maximum air temperature is greater than −8°C in winter conditions, whereas in spring conditions it is enhanced by daily maximum air temperature greater than 2.5°C. This study represents a necessary first step toward avalanche forecasting based on weather data in Nunavik. Efforts should be continued given the expected higher frequency of natural hazards in northern regions as a consequence of recent climate changes.

Snow avalanches can repeatedly occur along the same track under different snowpack and meteorological conditions during the snow season in areas of snow avalanche activity. The snowfall, air temperature, and snow cover can change dramatically in a warming climate, causing significant changes in the snow avalanche risk. But how the risk of snow avalanche activity during the snow season will change under a warming climate remains an open question. Based on the observed meteorological and snowpack data from 1968 to 2021 and the snow avalanche activity data during the 2011–2021 snow seasons along a transportation corridor in the central Tianshan Mountains that has a typical continental snow climate, we analyzed the temporal distribution of the snow avalanche activity and the impacts of climate change on it. The results indicate that the frequency of the snow avalanche activity is characterized by a Gaussian bimodal distribution, resulting from interactions between the snowfall, air temperature, and snowpack evolution. In addition, the active period of wet snow avalanches triggered by temperature surges and high solar radiation has gradually moved forward from the second half to the first half of March with climate warming. The frequency and size of snowfall-triggered snow avalanches showed only a slight and insignificant increase. These findings are important for rationally arranging snow avalanche relief resources to improve the risk management of snow avalanche disasters, and highlight the necessity to immediately design risk mitigation strategies and disaster risk policies to improve our adaptation to climate change. [ABSTRACT FROM AUTHOR]

Snow avalanches are a major component of the mountain cryosphere that frequently create road obstructions. Deposit characteristics determine the extent of damage to the road infrastructures and the period of disruption of the road network, but the factors controlling snow‐deposit volumes remain largely unknown. This study investigates the influence of meteorological and snowpack conditions on snow‐avalanche deposits and road‐network vulnerability based on 1986 deposit volumes from 182 paths located in two regions of the French Alps between 2003 and 2017: the Guil and Haute‐Maurienne valleys. During the period, 195 avalanches impacted the road network in these areas, leading to major disruptions. In the Haute‐Maurienne, correlations between deposit volumes and meteorological and snowpack conditions are high in winter. However, the relationships differ with path elevation and orientation. Results do not show any significant relationship between volumes and meteorological or snowpack conditions for the spring season. Focusing on deposits that disturbed the road network in winter and spring reveals a distinct influence of meteorological and snow variables compared to the overall dataset, with snowfall intensity as the predominant control variable of deposit volumes leading to road cuts. When the same analysis is conducted by considering Guil valley separately or by aggregating the Haute‐Maurienne with Guil valley area data, results do not show any significant relationship, highlighting the specific local nature of relations between deposit volumes and meteorological and snowpack conditions. [ABSTRACT FROM AUTHOR]

The falling of snow avalanches is frequent in the Bunderitsa valley in Pirin Mountains, Bulgaria. These events have high effects on forest structure and dynamics and importance for tourist activities. The studying of the effects of avalanches requires good data on the frequency and magnitude of events. However, the lack of historical data hinders very much this analysis. In our study we analyzed the types of damages on trees on Bosnian pine and Macedonian pine caused by avalanches and the most frequent responses of trees. We found that avalanches mostly cause tree breakages, partial uprooting, strong tilting of stems, visible wounding. The most frequent reactions in tree rings are: 1) sharp growth suppressions; 2) production of reaction wood, frequently accompanied by narrow tree rings on the opposite side; 3) lack of tree rings (missing rings); Trees often produced resin ducts and resin spills. However, these responses were not good indicators of the year of damage because pines in general form many resign ducts and often the response is not specific to a given year. [ABSTRACT FROM AUTHOR]

Dilute gas-particle mixtures in which the particles are carried by the turbulent fluid are found in various geophysical contexts, from cold snow avalanches to hot pyroclastic density currents. Though previous studies suggest that such mixtures have maximum particle concentrations of a few volume percent, the dependence of this maximum concentration on the Reynolds number is unclear. We addressed this issue through laboratory experiments in a vertical pipe, where dilute gas-particle mixtures were created by injecting a turbulent air flow from below. Nearly monodisperse mixtures of glass beads of different grain sizes (77 to 1,550 μm) were used with varying bulk concentrations from 0.025 to 8 vol. %. To create quasi-static mixtures, the mean air velocity matched the terminal settling velocity for the grain sizes investigated. The maximum Reynolds numbers of the mixtures were ~104–106. The air pressure indicated full support of the particle weight at concentrations down to 0.025 vol. %. Above a critical particle concentration, at which all the particles were suspended, subsequent additional particles were not maintained in the mixture and led to the formation of clusters that settled downward in the pipe to form a dense fluidized bed. Maximum mean particle concentrations of the dilute mixtures increased from ~1 to ~2.8 vol. % and reached a plateau at increasing mixture Reynolds number. These results give insights into the maximum particle concentrations of geophysical turbulent gas-particle mixtures and may serve to constrain observations as well as the input and output data of models.

In this article, we study snow avalanche activity during the snow seasons of 2017–2020 using four automatic time-lapse cameras strategically positioned along the southwestern slope of Tasiapik Valley, near the village of Umiujaq, in Nunavik (northern Québec, Canada). Over the three snow seasons, cameras helped to detect evidence of 130 avalanche events, scattered over seventy-eight distinct avalanche days. The evolution of weather conditions prior to each avalanche release was detailed according to data from a nearby weather station. Moreover, the time of release, the release type, the surface texture, and whether rocky material was present in the deposits were documented from the photographs. To explore relationships between weather data and avalanche releases, conditional inference tree (CIT) analysis was conducted. Results of the CIT analysis showed that there are different weather patterns associated with avalanche releases depending on the season, and significant thresholds values were defined. In winter, the avalanche probability was greater when three-day snowfall total exceeded 10 cm. In spring, the avalanche probability was greater when cumulative melting degree-days were less than forty-six and when daily minimum air temperature was greater than 2°C. Moreover, cornice failures were found to be a major component of the avalanche dynamic in Tasiapik Valley, mainly because of the slope's morphology. They have also been the cause of the three largest volume and longest runout avalanches observed by cameras in this study, highlighting potential risks for local communities. The probability of observing cornice failures is enhanced on days when maximum air temperature is greater than −8°C in winter conditions, whereas in spring conditions it is enhanced by daily maximum air temperature greater than 2.5°C. This study represents a necessary first step toward avalanche forecasting based on weather data in Nunavik. Efforts should be continued given the expected higher frequency of natural hazards in northern regions as a consequence of recent climate changes. [ABSTRACT FROM AUTHOR]

The present study addresses, for the first time, the problem of spatio-temporal reconstruction of geomorphic processes using tree-rings in the Sâmbăta Valley (Romanian Carpathians). The dendrogeomorphic analysis was conducted in two different sites, one affected by snow avalanches and the other by rockfall. A total number of 130 Picea Abies were sampled in the two sites. The results yield 13 major snow avalanches between 1950 and 2020 and a return period of 3.3 years. The winters with the highest activity index were 1988, 1997 and 2012. The rockfall reconstruction highlights several years of intense activity: 1952, 1955, 2003 and 2012. Thus, the results of the present study provide evidence of active geomorphic processes in the studied area, indicating that tourists are highly exposed to geomorphic hazards, as both sites interfere with popular hiking trails. (Because Sâmbăta Valley is one of the most intensely frequented by tourists in the Făgăraș Mountains, it is a need for warning signs to be installed on the exposed trails.

The possibility of assessing the avalanche hazard in the North Caucasus mountains with the use of the data of modern Era-Interim, SCSR, and NCEP-NCAR reanalyses is considered. The data have been previously compared with the materials of weather stations (average seasonal values of the surface temperature and precipitation). The avalanche hazard was estimated with the use of a correlation matrix, which is based on a relationship between the avalanche hazard characteristic and the standard deviations of the seasonal values of temperature and precipitation. The synoptic processes that increase the probability of catastrophic avalanches were identified. The anomalously high avalanche hazard was shown to form at a negative anomaly of air temperature at land surface and in higher air layers at an integral moisture content of the atmosphere close to the norm. [ABSTRACT FROM AUTHOR]

We reconstruct snow-avalanche (SA) activity along three adjacent avalanche paths in the northern part of the Rodna Mountains (Eastern Carpathians, Romania) using tree-ring analyses. We sampled a total of 238 disturbed Norway spruce (Picea abies (L.) Karst.) trees and used the growth anomalies found in tree rings to obtain an avalanche chronology at the subregional scale spanning the 1979–2019 period. Multiple regression analysis of weather data covering the tree-ring-based reconstructed avalanche winters provided three distinct synoptic patterns favoring SA activity: (i) in January, when destabilization of the snow cover occurs during warm periods; (ii) in April, when destabilization of the snow cover is due to the combined effect caused by the warm days and the ones with heavy rainfall; and (iii) in November, during cold periods with snowfalls and strong winds. This study based on the tree-ring approach coupled with multiple regression analysis contributes to a better understanding of the snow-avalanche regime at both local and subregional scale. It also provides the basis for further research to decipher the linkage between the synoptic conditions favoring the naturally released avalanches at a regional scale. [ABSTRACT FROM AUTHOR]

The possibility of using the data of modern ERA-Interim, CFSR and NCEP-NCAR re-analyses to assess an avalanche danger in the mountains of the North Caucasus is considered. Previously, the mean seasonal values of the surface air temperature and seasonal precipitation amounts obtained from the reanalysis archives were compared with the data of meteorological stations. The mean temperature of the cold period (November–March) was best reproduced by the ERA-Interim reanalysis: the correlation coefficients amounted to 0.8–0.9, and the average deviation from the station data ±1.7 °C. The accuracy of measurements of precipitation is lower, but the magnitude of the errors does not exceed the limits of inter-seasonal variability. To estimate the avalanche hazard, a correlation matrix was used based on the relationship of the avalanche hazard indicator with the standard deviations of seasonal values of temperature and precipitation. The ERA-Interim reanalysis reproduces the avalanche danger in the North Caucasus most adequately (71% of coincidences with the actually observed events). Synoptic processes which may promote formation of catastrophic avalanches in the North Caucasus were also determined. The most typical situation is the position of a high-level cyclone over the Eastern Europe, accompanied by the invasion of cold air masses from Scandinavia that activates cyclogenesis in the Mediterranean. It was found that the extreme avalanche hazards occurred at negative anomalies of mean seasonal air temperature near the ground and in the middle troposphere (about 1.5–2 °C) when the integral water content of the atmosphere was close to the norm.

For the first time, a qualitative and quantitative evaluation of the effectiveness of anti-avalanche measures was carried out for the territory of the «Krasnaya Polyana» ski resort, located in the Western Caucasus on the Aibga ridge. The following materials were used for this work: the results of field survey in 2019, which made it possible to map the resort's infrastructure exposed to possible snow avalanches and protected by existing preventive (anti-avalanche) measures, experience of similar studies from other regions as well as identification of the avalanche release zones by means of digital elevation model and analysis of remote sensing data, archive data on the snow avalanches regime at the site, and numerical modeling of the snow avalanches with different starting conditions. Modeling of the avalanches was performed in the RAMMS program basing on three scenarios: 1) taking account of the successful operation of existing anti-avalanche measures; 2) with regard for the failures in the work of existing anti-avalanche measures that were recorded earlier during the operation of the resort; 3) without considering any anti-avalanche measures, which corresponded to the conditions at the stage of the territorial planning of the resort. Differences in the impact of simulated avalanches on the resort infrastructure were interpreted as «high», «medium» and «low» effectiveness of existing antiavalanche measures. It was found that the dynamical characteristics of the local avalanches (run-out distance, volume, velocity, and pressure) had different importance for different types of the infrastructure with regard to the effectiveness of anti-avalanche measures. Under existing conditions of the relief, climate and vegetation of the investigated territory the artificial triggering (at the ski resort it is mainly made by the Gazex systems) is the most efficient. Snow-retaining structures often do not perform their functions, while dams and avalanche cutters can be successful only in combination with the properly functioning artificial triggering. It was found that there are areas where the run-out distance of artificially controlled avalanches is smaller than that of possible natural avalanches, and these areas can still be dangerous for the infrastructure of the resort due to the high values of the avalanche speed and pressure.

Snow avalanches are one of the most devastating natural hazards in the highlands that often cause human casualties and economic losses. The complex process of modeling terrain susceptibility requires the application of modern methods and software. The prediction of avalanches in this study is based on the use of geographic information systems (GIS), remote sensing, and multicriteria analysis—analytic hierarchy process (AHP) on the territory of the Šar Mountains (Serbia). Five indicators (lithological, geomorphological, hydrological, vegetation, and climatic) were processed, where 14 criteria were analyzed. The results showed that approximately 20% of the investigated area is highly susceptible to avalanches and that 24% of the area has a medium susceptibility. Based on the results, settlements where avalanche protection measures should be applied have been singled out. The obtained data can will help local self-governments, emergency management services, and mountaineering services to mitigate human and material losses from the snow avalanches. This is the first research in the Republic of Serbia that deals with GIS-AHP spatial modeling of snow avalanches, and methodology and criteria used in this study can be tested in other high mountainous regions. [ABSTRACT FROM AUTHOR]

Snow avalanches are a prevalent threat in mountain territories. Large-scale mapping of avalanche prone terrain is a prerequisite for land-use planning where historical information about past events is lacunar. To this aim, the most common approach is the identification of Potential Release Areas (PRAs) followed by numerical avalanche simulations. Existing methods for identifying PRAs rely on terrain analysis. Despite their efficiency, they suffer from i) a lack of systematic validation on the basis of adapted metrics and past observations over large areas and ii) a limited ability to distinguish PRAs corresponding to individual avalanche paths. The latter may preclude performing numerical simulations corresponding to individual avalanche events, questioning the realism of resulting hazard assessments. In this paper, a method that well identifies individual snow avalanche PRAs based on terrain parameters and watershed delineation is developed, and confusion matrices and accuracy scores computed both in terms of PRA numbers and areas are proposed to test and evaluate it. Confrontation to an extensive cadastre of past avalanche limits from different massifs of the French Alps used as ground truth leads to high accuracy rates, between 89.8% and 93.5% in numbers and 96.2% and 97.1% in areas. This shows the applicability of the method to the French Alps context. A sensitivity study is performed, highlighting the most important steps to reach high accuracy in PRA detection, among which the strong role of watershed delineation to identify the right number of individual PRAs. Outlooks for further progresses are discussed. Notably, the proposed data and evaluation framework could be used for additional developments of the method, and to benchmark existing and/or new PRA detection methods. [ABSTRACT FROM AUTHOR]

In the winter months of 2018–2020 the Kola Branch of the Unified Geophysical Service RAS conducted experiments on the joint registration of avalanches in the Khibiny mountain range using seismic and infrasonic sensors during work on the forced descent of the snow mass. The aim of the experiments is to assess the possibility of avalanche detection using the geophysical methods. The lack of representative statistics on the frequency and regularity of avalanches is the reason for the relevance of developing methods of their remote registration. The difficulty of registering avalanches is due to their occurrence often in hard-to-reach areas and in poor visibility conditions. To record signals generated by avalanches, different configurations of infrasound panels consisting of three spatially separated sensors (MPA 201 or Hyperion IFS-4000 microbarographs) and a portable seismic station Guralp CMG-6TD were used. As a result of the experiments, infrasound recordings were obtained at different distances from the avalanche source. The infrasound group recordings collected from the experiments were processed using an automatic detector implementing amplitude and cross-correlation signal detection methods. The spectral composition of the recordings and their characteristic appearance were analyzed. Avalanche-induced signals are characterized by long duration and changes in azimuth to the source. The dominant frequencies of the signal lie in the region of 1–10 Hz. Conclusions are made about the insufficient sensitivity of the seismic method when the seismometer is located at a distance of the first kilometers from the avalanche source, as well as the high applicability of the infrasound method for recording the facts of avalanches. The results obtained will make it possible to develop a methodology for automatic detection of signals generated by avalanches using the data of infrasound registration. This is the necessary basis for building a system for continuous monitoring of avalanche activity.

Knowledge about frequency and location of snow avalanche activity is essential for forecasting and mapping of snow avalanche hazard. Traditional field monitoring of avalanche activity has limitations, especially when surveying large and remote areas. In recent years, avalanche detection in Sentinel-1 radar satellite imagery has been developed to improve monitoring. However, the current state-of-the-art detection algorithms, based on radar signal processing techniques, are still much less accurate than human experts. To reduce this gap, we propose a deep learning architecture for detecting avalanches in Sentinel-1 radar images. We trained a neural network on 6345 manually labeled avalanches from 117 Sentinel-1 images, each one consisting of six channels that include backscatter and topographical information. Then, we tested our trained model on a new synthetic aperture radar image. Comparing to the manual labeling (the gold standard), we achieved an F1 score above 66%, whereas the state-of-the-art detection algorithm sits at an F1 score of only 38%. A visual inspection of the results generated by our deep learning model shows that only small avalanches are undetected, whereas some avalanches that were originally not labeled by the human expert are discovered.

Avalanche risk changes through time due to climate, landscape and socio-environmental transformations. These drivers exhibit space-time variations as function of local peculiarities that may alter local avalanche risk trajectories. Here, we use an integrative methodology to track the co-evolution of the socio-economic, land cover and climatic drivers of avalanche risk and its components in three upper basins of the French Alps: the Upper Maurienne valley, the Guil valley and the municipality of Valloire. The analysis, based on data from 1860 to 2017, focuses on avalanche-prone terrain defined as the maximal extension of avalanches potentially occurring on all paths of the French avalanche cadaster. Avalanche occurrence numbers have likely increased over the last decades, more strongly at higher elevation. By contrast, a quasi-complete afforestation of avalanche-prone areas took place in the Guil valley, whereas, in the Upper Maurienne and Valloire, afforestation remains incomplete. This suggests a significant increase of protection from avalanches for people downslope due to the presence of forests in the Guil valley only. In parallel, recent expansion of urban areas in avalanche-prone terrain is prominent in the Upper Maurienne, and more modest and controlled in the Guil valley and in Valloire. Hence, overall, avalanche risk for buildings and their inhabitants have locally slightly decreased over the study period in the Guil valley, remained rather stationary in Valloire and has rather strongly increased in the Upper Maurienne. This demonstrates the crucial role of local dynamics in avalanche risk evolution. Our results help in understanding the complex patterns resulting in mountain risks changing faster than ever and very differently from one location to another, which may, in turn, contribute to the development of improved disaster risk reduction strategies. [ABSTRACT FROM AUTHOR]

Climate variability has probably affected the frequency and distribution of debris flows and snow avalanches throughout the Holocene. In this paper, we reconstruct the Holocene history of debris flows and snow avalanches by investigating outcrops in colluvial fans surrounding lake Anestølsvatnet in western Norway and sediment cores penetrating the lake-floor deposits. We made a detailed map of the surface deposits around the lake. The formation of a large end moraine that dams the lake was radiocarbon dated to 10,200-10,800 cal. yr BP, and correlates to the Erdalen event, a Preboreal glacial oscillation. There are colluvial fans and debris-flow paths and snow-avalanche paths eroded on the steep slopes around the lake. On the western slopes, the fans are dominated by snow avalanches, and on the eastern slopes by debris-flow activity. Three of the lake cores were taken distal to the largest avalanche fan on the western slope, Storeskreda ('Storeskreda' means 'the big landslide'). Clasts > 2 mm in the lake sediments are interpreted as traces of snow avalanches and sorted sand layers as being derived from debris flows. Loss-on-ignition and magnetic susceptibility measurements document an increased silt content in the lake sediments after c. 6000 cal. yr BP, probably due to the reappearance of local glaciers in the area. Our combined data from the onshore outcrops/pits and lake sediments shows almost continuous snowavalanche activity and debris-flow activity throughout the last 10,000 years. However, there may have been an increase in the snow-avalanche activity over the last 5000 years. [ABSTRACT FROM AUTHOR]

Finger-like debris are sometimes observed in the deposition area of snow avalanches. Particle segregation within the flow is a key factor for finger formation during debris flow; however, investigation of the particle size distribution in snow avalanche debris led to a contrasting conclusion. A novel hypothesis is proposed herein for explaining finger formation by constructing a model in which debris continue to flow or get deposited depending on the distribution of velocity and random kinetic energy within the flow. [ABSTRACT FROM AUTHOR]

Avalanche danger forecasts are of great importance for ensuring the safety of residentsand tourists in mountainous areas. All methods for forecasting snow avalanches used in the work of the snow avalanche service in Kazakhstan were developed in the 80s of the XX century. They are in need of significant modernization. In the laboratory of natural hazards of the Institute of Geography and Water Safety, work is underway to study advanced scientific methods for assessing and forecasting avalanche danger. In the winter period from December 2020 to April 2021, an experiment was carried out to assess the level of avalanche danger in the vicinity of the city of Almaty and to issue a weekly avalanche bulletin. The main objective of the project is to adapt the experience of the Swiss Institute for Snow and Avalanches (SLF) for the conditions of Kazakhstan. In the course of work, the meteorological information received from meteorological stations of international exchange was analyzed. The level of avalanche danger was assessed on an international five-point scale. The expert assessment was carried out taking into account the recommendations of the SLF institute and a specially trained neural network. European Center Weather Forecast Mathematical Models (ECMWF) were used to increase the lead time of avalanche warnings. The results of the assessment of the level of avalanche danger were published as a weekly avalanche bulletin on the website of the Institute of Geography and Water Safety, as well as on the Telegram social network.. This method is recommended to be used in the operational work of the Kazhydromet and the Kazselezashchita. [ABSTRACT FROM AUTHOR]

Slope processes are active in the rolling plateau landscapes of Nunavik, Northern Québec, Canada. There are a few short but very steep escarpments in this region. On January 1st, 1999 a powerful snow avalanche struck Kangiqsualujjuaq, one of the 14 Inuit villages in Nunavik. Nine people died and 25 were injured. This village and its surrounding are located within a glacial valley, in a periglacial environment. There is significant population growth, as well as in the other villages in Nunavik. As early as 1999-2000, there was a significant spatial reorganization of the village's infrastructures to avoid the impact of other snow-avalanche events. The main objective of this paper is to examine the village expansion in response to snow-avalanche process and population growth, within an area constrained with permafrost thawing and steep slopes. From naturalist geomorphologic methods, written sources such as archive documents and aerial photographs, the results show that slopes above Kangiqsualujjuaq are prone to release snow avalanches during blizzards from uncommon directions, and that the newly built housing may be at risk in some places, due to the conjunction of snow avalanches and permafrost thawing.

Snow avalanches are a common phenomenon in Parâng Mountains (Southern Carpathians, Romania) perturbing tourism activities and associated infrastructures, damaging forests, and causing fatalities. Its past history is an es­sential information to gather while assessing the hazard zonation areas. Usually, in Romania snow–avalanche activ­ity occurring in forested areas are neither monitored, nor recorded by historical archives. In these areas, environ­mental archives such as tree rings may provide useful information about the past avalanche activity. The purpose of the present study is to reconstruct snow–avalanche history with tree rings along a path located below Cârja Peak (2405 m a.s.l.), an area where past snow–avalanche activity still remains underestimated. In this sense, 57 Norway spruce (Picea abies (L.) Karst.) trees showing clear signs of disturbance by snow avalanches were sampled and the growth anomalies associated with the mechanical impact produced by snow avalanches on trees were identified within their rings and served to reconstruct past events. The reconstructed chronology covers the period 1994–2018 showing the occurrence of a minimum of 11 major events, with an average return period of 2.1 years. Tree–ring records provided the most consistent avalanche event chronology in the study area. Although the lim­ited extension of the chronology back in time, a better understanding of snow–avalanche history which may be gained through dendro­chronological reconstructions represent nonetheless useful and pertinent information to consider before the imple­mentation and development of infrastructure in this mountain avalanche–prone area.

Snow avalanches are critical events due to the sudden instability of snow in mountain regions. Seismically induced snow avalanches, due to a particular type of trigger perturbing snow-covered slopes, are occasional events in geodynamically active mountain regions around the world, which can lead to large anomalous avalanches. The seismic trigger of an avalanche is either simultaneous or delayed. In Italy, the Alps, and particularly the Apennines, feature large areas expected to be affected by seismically induced snow avalanches. In this work, the avalanches’ distribution in Central Italy (i.e., Abruzzo region) and its connection with moderate–high seismicity were investigated. With regional and historical analyses, we investigated the connection between avalanches and seismicity. We revealed two main events of seismically induced avalanches (April 6–9, 2009, western Gran Sasso-Assergi area, and January 18, 2017, Gran Sasso massif) characterized by an anomalous distribution of avalanches. A specific and detailed analysis focused on the northeast Mt. Siella slope, where well-documented and constrained events occurred on January 18, 2017 in the Gran Sasso area, affecting a tourist facility. This involves geomorphological and photogeological multitemporal investigations. Moreover, the Rigopiano avalanche was analyzed through 3D numerical modeling and stability analysis of the snow to investigate the possible seismic trigger. We found the avalanche was consistent with delayed seismically induced avalanche cases. This combination contributed to a more general assessment of the seismically induced avalanches in the Central Apennines area (i.e., Abruzzo region) and provided new examples of seismically induced avalanches at both the regional and detailed scales, which are largely consistent with the world distribution.

Snow avalanches are among the most important disturbances in mountain ecosystems. The effects of avalanches on the endemic Pinus heldreichii and Pinus peuce forests in the Pirin Mountains in Bulgaria are poorly understood. These forests are among the few remaining old-growth forests with preserved natural dynamics in Europe. However, the ongoing development of tourist infrastructure at the borders of some of the best-preserved Pinus heldreichii and Pinus peuce forests close to Bansko ski resort leads to increased tourist pressure. Many backcountry skiers and snowboarders venture beyond the resort boundaries, practicing their activities in these forests and avalanche tracks and couloirs within them. The objective of our study was to collect tree-ring cores from Pinus peuce and Pinus heldreichii trees affected by avalanches and verify the specific types of damages and tree responses characteristic for the species and region. Then using the collected data, we aimed at reconstructing the years in which specific areas were affected by avalanches and in this way obtain data on the magnitude of larger events. Our study shows that large magnitude avalanches (LMA) in the vicinity of Bansko ski resort in the Pirin Mountains in Bulgaria occurred dozens of times in the 20th century. On average the period between LMAs ranged between 9 and 20 years with the shortest period between two such events in one couloir being 2 years. Avalanches affected forests high on the couloir banks and left traces in the tree rings related to the mechanical impact that snow avalanches had on the surviving trees. In the studied tree-ring cores of Pinus peuce and Pinus heldreichii the most informative types of responses were sharp growth suppressions, including missing rings, followed by reaction wood and in less cases visible scars and callus tissue. Our data for frequent large avalanches shows that is necessary to address the avalanche risk with high priority especially for the Palashica couloir, which directly threatens the lower parts of the ski runs as well as other facilities in Bansko ski resort. [ABSTRACT FROM AUTHOR]

This paper presents a snow avalanche hazard map of the most avalanche-prone mountain range in the Czech Republic, the Krkonoše Mountains. The map was prepared using historical records of 1132 avalanches which occurred over the last 54 years and state-of-the-art modelling of avalanche propagation and the spatial distribution of potential avalanche source areas. The map provides not only reliable and easy to understand information for the Mountain Rescue Service of the Czech Republic and mountain tourists, but also for land use managers to identify areas where new avalanche paths may develop under favourable conditions, including the total removal of forest cover.

The calibration of the dry friction and turbulent friction coefficients is necessary for computer simulation of avalanches. The method of back calculation based on data on actual avalanches is used for this purpose. The article presents the results of the calibration of the Eglit’s and RAMMS models for Ile Alatau range condi‑ tions. The range is located in Kazakhstan. The data on six avalanches in the same avalanche site were used. Five avalanches were dry, and one avalanche was wet. Avalanches volume varied from 2000 to 12000 m3. Maximum speed avalanches were between 15 and 30 m/s, the flow height – from 3 to 10 m. Series of back calculations with different values of the friction coefficients was made to obtain the calibrated coeffi‑ cients. The calibrated coefficients were chosen under condition of the best fit with real avalanches. The cal‑ ibrated coefficients were following. For the Eglit’s model for dry avalanches of the volume 2000–5000 m3 μ = 0.46÷0.48, k = 0.005–0.006, and the volume 8000–12000 m3 μ = 0.38÷0.42, k = 0.002÷0.003. For RAMMS model for dry avalanches of the volume of 2000–5000 m3 μ (dry friction coefficient) = 0.35÷0.4, ξ (viscous friction coefficient) = 1500÷2000 m/s2, and the volume 8,000–12,000 m3 μ = 0.3÷0.35, ξ = 2000÷3000 m/s2. For wet avalanches of the volume 12,000 m3 μ = 0.35, ξ = 1500 m/s2. The work on the calibration will be con‑ tinued to obtain the friction coefficients for the Eglit’s and RAMMS models. The additional data on real ava‑ lanches will be needed for this purpose.

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