Characterization and detection of avalanche signals using a seismo-acoustic array

Seismic and infrasound monitoring systems have been used for remote detection and characterization of avalanches and their dynamics. Recent studies have shown that seismic and infrasound methods are very complementary. Infrasound signals from avalanches are relatively easy to detect automatically but only contain partial information about the avalanche. Seismic signals, on the other hand, are more difficult to detect automatically but contain more information about the entire avalanche. To exploit the advantages of both wave types, we installed a combined seismo-acoustic array consisting of five seismometers and five infrasound sensors at our field site in Dischma valley above Davos. Additionally, we obtained ground-truth data on avalanches from several automatic cameras, field surveys and drone flights.

Results from data collected over two winter seasons show that both dry- and wet-snow avalanche were detected by our system, and highlight differences in seismic and infrasound wave characteristics depending on the avalanche type and size. Specifically, detection distance increased with avalanche size for both wave types. Furthermore, differences in seismic and infrasound signal characteristics were generally more pronounced for wet-snow avalanches than for dry-snow avalanches. Using array techniques we localized the avalanche paths and extracted seismic and infrasound waveform features. We also trained a machine learning model to automatically identify signals generated by avalanches, with promising results. Overall, our results indicate that combining seismic and infrasound wave characteristics can improve the remote detection and characterization of avalanches.