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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]

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]

Natural disturbances, such as avalanches, snow breakage, insect outbreaks, windthrow or fires shape mountain forests globally. However, in many regions over the past centuries human activities have strongly influenced forest dynamics, especially following natural disturbances, thus limiting our understanding of natural ecological processes, particularly in densely-settled regions. In this contribution we briefly review the current understanding of changes in forest cover, forest structure, and disturbance regimes in the mountain forests across the European Alps over the past millennia. We also quantify changes in forest cover across the entire Alps based on inventory data over the past century. Finally, using the Swiss Alps as an example, we analyze in-depth changes in forest cover and forest structure and their effect on patterns of fire and wind disturbances, based on digital historic maps from 1880, modern forest cover maps, inventory data on current forest structure, topographical data, and spatially explicit data on disturbances. This multifaceted approach presents a long-term and detailed picture of the dynamics of mountain forest ecosystems in the Alps. During pre-industrial times, natural disturbances were reduced by fire suppression and land-use, which included extraction of large amounts of biomass that decreased total forest cover. More recently, forest cover has increased again across the entire Alps (on average +4% per decade over the past 25–115 years). Live tree volume (+10% per decade) and dead tree volume (mean +59% per decade) have increased over the last 15–40 years in all regions for which data were available. In the Swiss Alps secondary forests that established after 1880 constitute approximately 43% of the forest cover. Compared to forests established previously, post-1880 forests are situated primarily on steep slopes (>30°), have lower biomass, a more aggregated forest structure (primarily stem-exclusion stage), and have been more strongly affected by fires, but less affected by wind disturbance in the 20th century. More broadly, an increase in growing stock and expanding forest areas since the mid-19th century have - along with climatic changes - contributed to an increasing frequency and size of disturbances in the Alps. Although many areas remain intensively managed, the extent, structure, and dynamics of the forests of the Alps reflect natural drivers more strongly today than at any time in the past millennium. [ABSTRACT FROM AUTHOR]

One of the purposes of dendrogeomorphic studies is to provide long and continuous reconstructions of mass movements and to detect climate-induced trends in process activity. The development of regional chronologies—in which information from different sites are aggregated—is often needed to identify process–climate relations and to overcome local-scale specificities, sparse data available for individual sites and to extract a signal that is common to a larger region and possibly driven by past climate fluctuations or large-scale environmental changes. Yet, such chronologies are scarce and consensus neither exists on how to compile local data at the regional scale nor on the methods to be used to extract a common signal. In the case of snow avalanches, existing regional tree-ring studies typically included less than ten paths, and they discriminated years of high/low avalanche activity based on a regional index representing the proportion of disturbed trees in any given year. However, such an index does not account for potential non-stationarities in local tree-ring reconstructions such as e.g., time-varying sample size, decreasing dendrogeomorphic potential of trees after the occurrence of an extremely large, devastating avalanche or socio-environmental changes. Here we combine a dendrogeomorphic approach to reconstruct snow avalanche events in 11 paths located in the Goms valley (Swiss Alps) with an innovative statistical modelling approach. For each path, we compute reconstructions using a 4-step procedure to disentangle potential effects of snow avalanches from disturbance pulses in trees caused by climatic or other exogenous factors. We then process the regional dataset (spanning the period 1766–2014) within a Bayesian hierarchical spatio-temporal framework specifically designed to homogenise time series of avalanche events by i) removing trends related to the decreasing number of living trees back in time and ii) inferring robust trends in mean annual/regional avalanche activity in time and space. This contribution has the merit to introduce a methodological approach allowing rigorous extraction of common, average avalanche signals from snow avalanche paths characterized by heterogeneous process activity. Despite its stringency, we show that 11 avalanche paths may not suffice to yield a signal that is independent from the selection of couloirs. As a result, the approach also does not highlight a clear climatic control of snow avalanche activity but rather points to a complex, yet combined impact of afforestation and management strategies on reconstructed avalanches. • Regional snow avalanche chronologies can inform about process-climate relations. • We provide a 294-yr, dendrogeomorphic chronology covering 11 paths in the Goms valley. • Hierarchical Bayesian modelling was used to regionalize avalanche chronologies. • More avalanche paths are needed to overcome local non-stationarities. [ABSTRACT FROM AUTHOR]

Avalanche occurrences are unambiguous indicators of unstable snow conditions. Information on past and current avalanche activity is therefore crucial for avalanche forecasting. To continuously assess avalanche activity, automatic detection systems are required. In recent years, technological and signal processing advances have led to the development of operational infrasound avalanche detection systems. We evaluated the detection performance of four operationally running infrasound detection systems installed at three different sites in the Swiss Alps during two entire winter seasons. To this end, we collected a comprehensive data set of avalanche activity using a network of automatic cameras and supplementary field observations by local observers. The events automatically identified by the systems were then compared to the data set of visually observed avalanches. Only 3% of the 839 observed avalanches were associated with automatic detections and 21% of the automatic detections were confirmed by field observations. However, the majority of observed avalanches were small and most automatic detections occurred during periods of poor visibility. Furthermore, the probability of detection (POD) increased with avalanche size, decreased with distance, and varied with avalanche type. Dry-snow avalanches were generally better detected than wet-snow and mixed-type avalanches. Large avalanches (on the order of 300 m wide and 1000 m long) within a distance of 3 km from the array were typically well detected (POD ≈ 90%). The false alarm ratio was estimated to 13–30%. • Snow avalanche size, type and distance affect detection rates of infrasound systems. • Large avalanches within 3 km have a high probability of detection (≈ 90%). • Results suggest higher detection rates for dry-snow than for wet-snow avalanches. [ABSTRACT FROM AUTHOR]

In full-scale snow avalanche test sites, structures such as pylons, plates, or dams have been used to measure impact forces and pressures from avalanches. Impact pressures are of extreme importance when dealing with issues such as hazard mapping and the design of buildings exposed to avalanches. In this paper, we present the force measurements recorded for five selected avalanches that occurred at the Seehore test site in Aosta Valley (NW Italian Alps). The five avalanches were small to medium-sized and cover a wide range in terms of snow characteristics and flow dynamics. Our aim was to analyze the force and pressure measurements with respect to the avalanche characteristics. We measured pressures in the range of 2 to 30 kPa. Though without exhaustive measurements of the avalanche flows, we found indications of different flow regimes. For example, we could appreciate some differences in the vertical profile of the pressures recorded for wet dense avalanches and powder ones. Being aware of the fact that more complete measurements are necessary to fully describe the avalanche flows, we think that the data of the five avalanches triggered at the Seehore test site might add some useful information to the ongoing scientific discussion on avalanche flow regimes and impact pressure. [ABSTRACT FROM AUTHOR]