Stephan Harvey

Avalanche terrain maps are becoming increasingly common for large areas due to the availability of high-resolution and high-quality digital elevation models (DEM). Many of these maps use the Avalanche Terrain Exposure Scale (ATES) classification system, which categorizes terrain from simple to extreme, often using simple runout models such as the statistical alpha-beta model to identify potential runout areas. The current automated ATES classification models do not include avalanche dynamics models such as RAMMS, SAMOS or r.avaflow. Since 2018, Classified Avalanche Terrain (CAT) and Avalanche Terrain Hazard (ATH) maps have been introduced in Switzerland, delineating avalanche terrain into potential release areas and runout zones for size class 3 avalanches determined with the numerical avalanche simulation model RAMMS. While these maps have been very well received by recreationists and are widely used in Switzerland, the experience gained over the last years has shown that there is still room for improvements. Specifically, (i) potential release areas were not always well classified, (ii) runout zones may be too long for typical skier-triggered avalanches, and (ii) the ATH map, combining various factors, is complex and the information can be ambiguous. Therefore, we present updated versions of the CAT and ATH maps addressing these issues and allowing users to better assess avalanche risk and plan backcountry trips. These revised maps provide refined representations of potential release areas and improved mapping of avalanche runout zones driven by a new version of RAMMS::EXTENDED. Validation in different regions, focusing on size 3 avalanches, confirm the improved accuracy in delineating potential avalanche runout zones. Additionally, a new iteration of the ATH map simplifies the complexity of avalanche terrain by categorizing the terrain into easy-to-understand classifications that provide a concise overview, which also incorporates the ATES system. The new maps are generated using various layers provided by the RAMMS output, which can also support automatic risk assessment at cruxes. All that is required to produce these new maps is a high-quality elevation model at 5-m resolution, and a reliable map layer for the protective forest cover.

Those traveling in the winter backcountry expose themselves to avalanche danger, where the interplay of triggering probability and potential consequences of being caught determines the individual risk. To assess the risk, the focus is on the sections particularly exposed to avalanche danger, so-called cruxes. At a crux, the probability of triggering as well as the possible consequences of an avalanche are estimated by assessing the stability of the snowpack (failure initiation and crack propagation) and the characteristics of the terrain. In general, there are different approaches, ranging from pre-tour planning to on-site decision-making, which are applicable for beginners as well as experts. However, navigating the multitude of information, observations and assessment tools is a challenge. This requires a comprehensive view and a structured yet flexible approach. To address this issue, we introduce the RiskCheck framework, which systematically focuses on key issues related to avalanche triggering probability and the consequences of an avalanche, culminating in a graphical risk analysis. This modular framework allows flexibility and continuous refinement to adapt to further information and observations. On the one hand, we propose an automated to semi-automated application of the Risk- Check that uses digital avalanche terrain maps and up-to-date information from the avalanche bulletin as a starting point, with subsequent refinement and adaptation by the user following a Bayesian approach. On the other hand, we show how simple rules of thumb and process-oriented approaches can facilitate risk assessment in the field using the same framework. The integration of both automated and manual procedures provides an approach to backcountry risk assessment that considers the inherent uncertainty associated with the problem. The proposed framework ensures consistency across different information sources and application scenarios which also allows a smooth transition from automated to manual application. In summary, the RiskCheck provides a versatile tool to assess avalanche risk by promoting risk-based decisions with a universal approach (probability ´ consequences) based on the current state of knowledge on avalanche release.

Assessing snowpack stability is crucial for determining the avalanche danger level. In this context, the propagation saw test is a valuable tool, though its results can be difficult to interpret. This paper aims to provide practical guidance for interpreting PST results by establishing direct connections between test outcomes and interpretable parameters. Despite nearly two decades of use, a definitive guide for PST interpretation is still lacking, with outcomes categorized as no propagation, crack arrest, or full propagation. We address the influence of factors such as slope angle and slab geometry on critical cut length and introduce an analytical model for real-time assessment. Utilizing data from 271 PSTs, we offer an interpretation tool to enhance comparability across different terrains and conditions.

The snow-covered winter surface differs significantly from its snow-free equivalent due to the smoothing caused by progressive snow accumulation and erosion. This smoothing effect becomes more pronounced as the absolute snow depth increases. However, variations in accumulation, settling and redistribution occur in complex mountain terrain. The spatial variability of snow depth plays a crucial role in the formation and dynamics of snow avalanches. Surface shape and roughness serve as established metrics to assess the effect of snow on terrain. In this study, we investigate snow surface smoothing within the release areas of typical skier-triggered avalanches observed in the vicinity of Davos, Switzerland. We analyze therelease areas of nearly 2000 avalanches of class size 2 to 3, using high spatial resolution (0.5 m) annual snow depth maps recorded during the peak of winter over 6 years and covering an area of 275 km2. These avalanche release areas are grouped according to their main terrain shape. Within each group, the influence of snow depth on surface shape and roughness is assessed. Finally, we investigate the effect of different DEM resolutions on the terrain smoothing factor and analyze the intra-annual consistency of the terrain smoothing. For the first time, we assess the role of snow depth on surface shape and surface roughness in avalanche release areas over a large sample size and a large area. We find strong agreement in the intra-annual terrain smoothing behavior despite significant differences in mean snow depths observed over the study period, ranging from 0.73 m in 2023 to 2.2 m in 2019.

For travelling in the backcountry, good planning is crucial. Besides the current weather and avalanche forecast, terrain characteristics must be assessed to identify cruxes in terms of avalanche risk. Nowadays, support is given by slope angle layers and Geographic Information System (GIS) based avalanche terrain maps. When planning a backcountry tour, it is important to draw the route yourself on a detailed map, consider relevant terrain characteristics and define cruxes. To assist in this task, we developed an automatic crux detector. The method automatically identifies potential cruxes from digital avalanche terrain maps and assesses the terrain at these locations in terms of avalanche triggering and the consequences of being caught. In addition, the various associated terrain characteristics are presented. With this information, an initial risk assessment can already be made during the planning phase. Further, this function improves map reading skills in terms of avalanche risk when drawing routes, and it can analyze downloaded GPS tracks to verify the quality of the route and possibly improve it. The automatic crux detection is implemented in the White Risk application. This streamlines the planning process, which finally contributes to safer backcountry tours. In the future, we plan to link the detected potential cruxes to current snow cover conditions.

Das Tourenplanungsmodul auf der Plattform White Risk wurde überarbeitet und ist noch enger mit der gleichnamigen App verknüpft. Es stehen neue Layer und interessante Anwendungsmöglichkeiten bereit - etwa die automatische Erkennung von potenziellen Schlüsselstellen.

Die Auseinandersetzung mit dem Gelände ist für Tourengeher bei der Beurteilung des Lawinenrisikos das A und 0. Doch die Interpretation des Geländes auf der topografischen Karte ist nicht einfach. Zwei neue Karten bieten Hilfe.

Terrain characteristics are one of the main factors contributing to avalanche formation. Hence, terrain assessment is crucial for planning and decision making when travelling in the backcountry. So far, terrain is mainly interpreted manually from topographic maps and by observations in the field. Recent support for interpreting avalanche terrain is given by slope angle layers derived from digital elevation models or the Avalanche Terrain Exposure Scale (ATES) for classifying avalanche terrain manually. We developed avalanche terrain maps by combining terrain characteristics of avalanches with the avalanche simulation model RAMMS::EXTENDED and with fall simulations, all based on a high resolution digital elevation model. The focus was on mapping terrain of size class 3 avalanches, which typically threaten backcountry recreationists. We propose a Geographic Information System (GIS) based methodology for a fully automatic classification of the avalanche terrain taking into account: a) potential avalanche release areas, b) remote triggering of avalanches, c) possible runout zones, and d) the potential of being seriously injured or deeply buried by small or medium-sized avalanches. To considered all these aspects several simulations were performed where from we created two different avalanche terrain maps for the entire Swiss Alps and the Jura. One map classifies the avalanche terrain thematically into: i) potential release areas, ii) areas with remote triggering potential, and iii) the runout zones of size 3 avalanches. The second map provides continuous values illustrating how serious or dangerous the terrain is in terms of avalanche release and the consequences of being caught. These maps assist the interpretation of avalanche terrain for travelling in the backcountry. Although they focus on Switzerland, the methods can also be applied to other mountain areas worldwide.

Das ganzheitliche Beurteilungssystem 3×3 ist bei Ski- und Snowboardtouren etabliert. Während bei den ersten beiden Filtern „Planung” und „Beurteilung vor Ort” schwierige Entscheidungen hinausgeschoben werden können, ist beim dritten Filter „Beurteilung im Einzelhang” Endstation. Hier gibt es nur noch „Go” oder „No go”. Beim Entscheid im Einzelhang fehlte bislang ein Ratgeber, um die richtigen Fragen zu stellen und systematisch vorzugehen. Das neue Merkblatt „Achtung Lawinen” schafft Abhilfe.

The holistic assessment and decision framework «3 x 3» is well established for ski and snowboard tours. Whereas difficult decisions can be postponed in the first two filters, «planning» and «local evaluation», a final decision is necessary in the third filter «individual slope». At that point, we can only decide 'to go' or 'not to go'. So far, an approach asking the right questions and answering them systematically was missing. The latest edition of the popular leaflet «Caution Avalanches» now includes a risk-based scheme for decision making at the individual slope. Three elements of avalanche risk assessment are considered: the avalanche triggering probability, the consequences of being caught and the behaviour, i.e. measures to reduce the risk. Three colours (blue, pink and orange) corresponding to the three elements guide the user through the decision-making process. In a first step, important questions have to be asked related to each of these topics. The answers can then visually be combined with the help of a diagram to estimate the avalanche risk. The scheme suggests an explicit decision 'go' or 'no go' and helps not to forget anything essential. In addition to the established methods, such as the «graphical reduction method» or thinking in «avalanche problems», the presented tool is an aid to reflect important factors for making decisions at the individual slope. It especially applies to slopes steeper than 30° and to slopes that are either not obviously critical or unproblematic. We demonstrate how to apply this risk-based approach to make better decisions at the individual slope.

Initialbruch und Bruchfortpflanzung, das sind die Schlüsselbegriffe zum Verständnis von Schneebrettlawinen, den gefährlichsten Skifahrerlawinen. Wie sie "funktionieren" und welche Rolle dabei die typischen "Lawinenprobleme" spielen, schildern Stephan Harvey und Jürg Schweizer vom Schweizer Lawinenforschungsinstitut SLF.

«Learning by doing» is an obvious credo for every instructor. In avalanche education, however, trying out everything yourself can be dangerous. Furthermore, learning about avalanches requires some theoretical background, which has to be taught. Avalanche instructors tend to explain a lot without the participants having to deal seriously with the topic. Using cooperative ways of learning, the learning attention and the learning success can be increased distinctly. The idea behind this form of learning consists of the following: a) Give tasks and stimulate participants to think; b) Discuss in different forms of groups and exchange knowledge and ideas, and c) Present answers and results to understand the content. Based on the content of the leaflet «Caution Avalanches», we put together a training-kit for cooperative learning. The kit is especially designed for teaching in the field and includes topics such as interpreting the avalanche danger scale, typical avalanche situations, graphical reduction method, trip planning, decision making, human factors. Guides and instructors of avalanche courses as well as participants have had good experience of working with this kit and appreciate the diverse way of learning.

Planning ski tours with accurate topographic maps is today a standard procedure. When a specific avalanche-prone slope has to be evaluated, the perception of the terrain from the map varies due to subjective interpretation. The question arises: How do experienced backcountry skiers assess avalanche terrain from a map? To gain a better understanding, we conducted a survey among 26 experts. They were asked to evaluate 24 avalanche-prone locations considering a given avalanche situation. First, they had to delineate the slope area they considered relevant for assessing the terrain. Second, they had to rate the hazard in terms of avalanche triggering probability and the consequences of being caught. The participants were also encouraged to describe their assessment in qualitative terms. Depending on the specific location, the assessments among the participants varied, whereas the agreement between the qualitative explanations was higher. The criteria most frequently mentioned to rate the terrain were slope angle, slope size, terrain traps, homogeneity of the slope and proximity to ridges. The results confirm that assessing avalanche terrain from a map is not a straightforward task. Nevertheless, the survey helps quantifying subjective expert knowledge. For instance, the data can be useful for designing algorithms to classify potential avalanche terrain, as it provides a set of well-studied terrain situations.

Glide-snow avalanched are notoriously difficult to predict, in part because we still do not fully understand the physical processes governing their release. Previous research has highlighted the presence of a wet basal layer as a prerequisite for glide-snow avalanche release. Different processes are believed to contribute to the formation of this basal layer in winter and in spring, since in winter the snowpack is usually cold and dry, while in spring it is warm and wet. We compared glide-snow avalanche activity to meteorological parameters of nearby weather stations for two winter seasons, the winter of 2008–2009 and the winter of 2011–2012. During both these winters, glide-snow avalanche activity was high in the Swiss Alps, posing a particular challenge to avalanche forecasting services. We used univariate and multivariate statistical methods to analyse the data for cold temperature events in winter and warm temperature events in spring, separately. For cold temperature events the minimum air temperature and the amount of new snow prior to avalanche release were the most significant variables, while for warm temperature events the most significant variables were air temperature, snow surface temperature derived from outgoing longwave radiation and decrease in snow height. Our results support the hypothesis that different processes result in the formation of glide-snow avalanches in winter and in spring. While the limited data set does not allow us to draw general conclusions, our results clearly indicate that treating cold and warm temperature events separately is of paramount importance to develop a widely applicable glide-snow avalanche forecasting model.