Decennial infrasonic array analysis of snow-avalanche activity in Aosta Valley: New perspectives for supporting avalanche forecasting

Snow avalanches rank among the deadliest natural hazards in mountain environments worldwide. Forecasting is mostly based on measuring meteorological forcing, aiming at assessing the probability of event triggering in a certain area. To make forecast models as accurate as possible, information on avalanche occurrence is critical. However, real-time avalanche detection is still challenging and generally limited to radar or visual surveillance of one or a few known avalanche paths; here the need for novel monitoring solutions. In the last decades, infrasound has proven to be a promising tool for real-time detection of avalanches. However, many difficulties still exist, mostly connected to the discrimination of the infrasonic signals from avalanches among the signals radiated by other natural or anthropic sources.

Here we present the analysis of more than 10 years of infrasonic array data recorded at an altitude of $\sim$2000 m in Aosta Valley (Itay). We develop an algorithm aimed at detecting snow-avalanche events based on recorded infrasound and calibrated on two avalanche sequences that occurred in the site. The identified avalanche infrasonic signals are compared with reports of the Regional Avalanche Cadastre and with local snow-depth data to test the accuracy of our algorithm. Results reveal a good performance and suggest the use of infrasound as a supporting tool for early-warning purposes, as it could provide avalanche detection in near real-time also when visual surveillance is prevented.