Within the framework of the Interreg projects STRADA and STRADA 2.0, a new model has been developed for semi-automatically delineating avalanche starting zones. It provides support to avalanche experts in estimating the potential risk posed by avalanches. The tool's evolution was described in a recent scientific journal.
Location and size of avalanche starting zones are key factors in assessing the potential danger that avalanches pose to roads, railways or other infrastructure. Does a risk exist, and how great is it? The challenge of estimating size and shape of avalanche starting zones is complex and even today continues to rely largely on the knowledge of experts.
SLF researcher Jochen Veitinger has systematically investigated the characteristics of avalanche starting zones and recorded his findings in a doctoral dissertation. Over the course of 20 years he analysed the data of avalanches which triggered at the SLF test site in Vallée de la Sionne (Arbaz, Valais). It was discovered that one of the factors determining potential slab width is the depth of snow in the starting zone. Since a deep snowpack increasingly buries irregularities such as rocks or ridges, features that can prevent a fracture in a snow layer, their avalanche-averting effects diminish. As a result, cohesive slab avalanches of greater magnitude can form.
In order to capture this smoothing effect the snowpack has on the terrain surface, the researchers took high-resolution snow depth measurements using lasers in a high alpine multiple starting zone over a period of three winters. With the aid of these measurements, a method of linking surface structure to snow depth was developed, reflecting the fact that rough elements increasingly disappear as snow depth increases. Given that the snow is, to a certain extent, very similarly distributed every winter, it was also possible systematically to integrate the smoothing effect.
Against this background the PhD candidate developed a new model which, based on terrain characteristics such as slope gradient, terrain roughness and snow depth, calculates the probability of a particular area of terrain serving as the starting zone of a slab avalanche (Fig. 1). The tool has been implemented in a geographic information system (GIS).The interaction of snow depth and winter terrain surface was integrated in the new algorithm for GIS with the aid of a snow depth-dependent roughness parameter. Potential starting zones can thus be modelled for a variety of snowpack scenarios. A wind-influence parameter has likewise been integrated to accommodate variations in snow deposits arising from shifting wind directions. The tool thus provides additional indicators for estimating the possible size of starting zones both for extreme avalanches (for purposes of danger-zone planning) and in order to assess the hazards posed by smaller-sized, more frequent avalanches, such as those that occur in the vicinity of a transportation corridor, where varying snow and wind conditions can play a crucial role in determining the potential danger. Measured against the outcomes of documented historical avalanche events, the new tool was thus able to deliver better results, particularly in the assessment of frequent avalanches.
2010 - 2016