Data-driven mapping of avalanche release areas: a case study in South Tyrol, Italy

Abstract

Avalanche hazard and risk mapping is of utmost importance in mountain areas in Europe and elsewhere. Advanced methods have been developed to describe several aspects of avalanche hazard assessment, such as the dynamics of snow avalanches or the intensity of snowfall to assume as a reference meteorological forcing. However, relatively little research has been conducted on the identification of potential avalanche release areas. In this paper, we present a probabilistic assessment of potential avalanche release areas in the Italian Autonomous Province of Bolzano, eastern Alps, using the Weights of Evidence and Logistic Regression methods with commonly available GIS datasets. We show that a data-driven statistical model performs better than simple, although widely adopted, screening criteria that were proposed in the past, although the complexity of observed release areas is only partly captured by the model. In the best case, the model enables predicting about 70 % of avalanches in the 20 % of area classified at highest hazard. Based on our results, we suggest that probabilistic identification of potential release areas could provide a useful aid in the screening of sites for subsequent, more detailed hazard assessment.