Abstract
Snow avalanches generate seismic signals as many other mass movements. Therefore, detection of avalanches by seismic monitoring systems is highly relevant to assess the avalanche danger level. Apart from estimating the overall activity, information on the location of individual events is also important. We deployed a seismic monitoring system consisting of seven vertical geophones at a site above Davos, Switzerland. During a major snowfall on 2017 March 9 and 10, we visually identified 19 events in the seismic data that we considered as avalanches. For all these events, we calculated the backazimuth angles as well as the apparent velocity of the incoming wavefields using two different array processing techniques: a commonly used beam-forming approach and multiple signal classification (MUSIC). One of the avalanches released directly above the array and the path was well documented in a field survey. We analysed this event in more detail and compared both array processing techniques. Using the MUSIC method we were able to reproduce the avalanche path with reasonable accuracy, whereas the beam-forming method only provided a rough direction. The results obtained using MUSIC suggest that with our seismic array mainly infrasonic waves were recorded during the event. From the remaining 18 events, 15 had a clear path and were classified as avalanches. The other three events were dismissed as falsely classified avalanches. By comparing the results for these 15 avalanches events with our field survey, we were able to map 11 avalanches within a distance of 3 km of the array.
Highlights
Seismic monitoring methods are well suited for the detection of snow avalanches
In this study we used two seismic array processing methods, namely multiple signal classification (MUSIC) and beam-forming, to calculate the backazimuth angles as well as the apparent velocity of incident wavefields generated by snow avalanches
Results obtained with the beam-forming method showed strong variations for the backazimuth angles preventing an unambiguous reconstruction of the avalanche path, while the results obtained with the MUSIC algorithm were more robust
Summary
Seismic monitoring methods are well suited for the detection of snow avalanches. While it is clear that seismic methods can be used to monitor avalanche activity, information about the type, size and location of the avalanche would be an added value. Snow avalanches generate infrasound signals (Bedard 1989) and those signals can be used to detect avalanches Avalanche detection based on one single infrasound sensor is prone to errors (Scott et al 2007). Apart from the increasing robustness of detection, array analysis methods can be used to derive additional information about the avalanche event, such as the velocity of the avalanche front (Havens et al 2014) as well as the direction of the source (Marchetti et al 2015). Apart from the increasing robustness of detection, array analysis methods can be used to derive additional information about the avalanche event, such as the velocity of the avalanche front (Havens et al 2014) as well as the direction of the source (Marchetti et al 2015). Kogelnig et al (2011) combined seismic and infrasound data to identify different avalanche regimes and by combining both data they identified additional characteristics
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