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Snow avalanche hazard mapping has a long tradition in the European Alps. Hazard maps delineate areas of potential avalanche danger and are only available for selected areas where people and significant infrastructure are endangered. They have been created over generations, at specific sites, mainly based on avalanche activity in the past. For a large part of the area (90 % in the case of the canton of Grisons) only strongly generalized hazard indication maps are available (SilvaProtect), not showing impact information such as pressure. This is a problem when new territory with no or an incomplete historical record is to be developed. It is an even larger problem when trying to predict the effects of climate change at the state scale, where the historical record may no longer be valid. To close this gap, we develop an automated approach to generate spatially coherent hazard indication mapping based on a digital elevation model for the canton of Grisons (7105 km2) in the Swiss Alps. We calculate eight different scenarios with return periods ranging from frequent to very rare as well as with and without taking the protective effects of the forest into account, resulting in a total of approximately 2 million individual avalanche simulations. This approach combines the automated delineation of potential release areas, the calculation of release depths and the numerical simulation of the avalanche dynamics. We find that between 47 % (most frequent scenario) and 67 % (most extreme scenario) of the cantonal area can be affected by avalanches. Without forest, approximately 20 % more area would be endangered. This procedure can be applied worldwide, where high-spatial-resolution digital elevation models, detailed information on the forest and data on the snow climate are available, enabling reproducible hazard indication mapping also in regions where no avalanche hazard maps yet exist. This is invaluable for climate change studies. The simulation results are validated with official hazard maps, by assessments of avalanche experts, and by existing avalanche cadastres derived from manual mapping and mapping based on satellite datasets. The results for the canton of Grisons are now operationally applied in the daily hazard assessment work of the authorities. Based on these experiences, the proposed approach can be applied for further mountain regions.

Snow avalanche hazard is threatening people and infrastructure in all alpine regions with seasonal or permanent snow cover around the globe. Coping with this hazard is a big challenge and during the past centuries, different strategies were developed. Today, in Switzerland, experienced avalanche engineers produce hazard maps with a very high reliability based on avalanche database information, terrain analysis, climatological data sets and numerical modeling of the flow dynamics for selected avalanche tracks that might affect settlements. However, for regions outside the considered settlement areas such area-wide hazard maps are not available mainly because of the too high cost, in Switzerland and in most mountain regions around the world. Therefore, hazard indication maps, even though they are less reliable and less detailed, are often the only spatial planning tool available. To produce meaningful and cost-effective avalanche hazard indication maps over large regions (regional to national scale), automated release area delineation has to be combined with volume estimations and state-of-the-art numerical avalanche simulations.In this paper we validate existing potential release area (PRA) delineation algorithms, published in peer-reviewed journals, that are based on digital terrain models and their derivatives such as slope angle, aspect, roughness and curvature. For validation, we apply avalanche data from three different ski resorts in the vicinity of Davos, Switzerland, where experienced ski-patrol staff have mapped most avalanches in detail for many years. After calculating the best fit input parameters for every tested algorithm, we compare their performance based on the reference data sets. Because all tested algorithms do not provide meaningful delineation between individual PRAs, we propose a new algorithm based on object-based image analysis (OBIA). In combination with an automatic procedure to estimate the average release depth (d0), defining the avalanche release volume, this algorithm enables the numerical simulation of thousands of avalanches over large regions applying the well-established avalanche dynamics model RAMMS. We demonstrate this for the region of Davos for two hazard scenarios, frequent (10–30-year return period) and extreme (100–300-year return period). This approach opens the door for large-scale avalanche hazard indication mapping in all regions where high-quality and high-resolution digital terrain models and snow data are available.

Mining activities in cold regions are vulnerable to snow avalanches. Unlike operational facilities, which can be constructed in secure locations outside the reach of avalanches, access roads are often susceptible to being cut, leading to mine closures and significant financial losses. In this paper we discuss the application of avalanche runout modelling to predict the operational risk to mining roads, a long-standing problem for mines in high-altitude, snowy regions. We study the 35 km long road located in the "Cajón del rio Blanco" valley in the central Andes, which is operated by the Codelco Andina copper mine. In winter and early spring, this road is threatened by over 100 avalanche paths. If the release and snow cover conditions can be accurately specified, we find that avalanche dynamics modelling is able to represent runout, and safe traffic zones can be identified. We apply a detailed, physics-based snow cover model to calculate snow temperature, density and moisture content in three-dimensional terrain. This information is used to determine the initial and boundary conditions of the avalanche dynamics model. Of particular importance is the assessment of the current snow conditions along the avalanche tracks, which define the mass and thermal energy entrainment rates and therefore the possibility of avalanche growth and long runout distances.