Automated avalanche hazard indication mapping on state wide scale

Bühler, Y., Bebi, P., Christen, M., Margreth, S., Stoffel, L., Stoffel, A., Marty, C., Schmucki, G., Caviezel, A., Kühne, R., Wohlwend, S., & Bartelt, P. (2022). Automated avalanche hazard indication mapping on state wide scale. Natural Hazards and Earth Science Systems.

The article discusses the development of a computer-based automated procedure for generating avalanche hazard indication maps over large regions based on digital elevation model (DEM) data. Hazard maps are essential for identifying areas with a high risk of avalanches and preventing damage and casualties. However, hazard maps are typically available only for selected areas and can be costly to create for large regions. The procedure involves delineating potential avalanche release areas (PRAs) and using the RAMMS avalanche dynamics model to simulate slides. The hazard indication maps provide information on potential hazard areas outside settled regions but may not include intensity information.

The methodology for this research and development involved data collection, including topographic data, forest inventories, avalanche event registers, hazard maps, and satellite imagery. Automated methods were used to classify the forested areas based on their potential protective effects against avalanches; those providing protection against rare to very rare avalanches and those offering protection against relatively frequent avalanches. The researchers simulated avalanche scenarios with different return periods, ranging from rare (100-300 years) to frequent (10-30 years) events. They also considered both scenarios with and without the protective effects of forests. Researchers validated the simulation results by comparing them with existing hazard maps, event registers, avalanche cadastres, and satellite imagery. Qualitative comparisons were also made with assessments from avalanche experts.

This research showed that the automated procedure was able to generate accurate avalanche hazard maps on a large scale. It also showed the importance of incorporating forest coverage data in the generation of these maps, as it substantially affects the accuracy of slide simulations and the successful identification of hazard zones.

Overall, this research helped me gain a better understanding of how avalanche hazard maps are created using GIS software, how this process can be automated for their production over large regions, and methods for validating their accuracy. I feel that that these modern, automated techniques (when compared to the articles from the early 2000's) are especially important as land is developed in previously uninhabited, avalanche prone areas. Alaska, for example, is geographically huge and would benefit from this type of automated hazard mapping.