Seismic signal characterization of snow avalanches using distributed acoustic sensing in Grasdalen, western Norway

Abstract. We show the use of distributed acoustic sensing for analyzing seismic signals from snow avalanches. For three winter seasons, we continuously recorded seismic data using distributed acoustic sensing (DAS) on a standard telecommunication fiber along a mountain road in Grasdalen, western Norway. Multiple snow avalanches were registered, alongside various other signals such as road traffic and detonations from remote avalanche triggering. We describe the signal characteristics of natural and manually triggered avalanches and present a comparison with other observed signals in both time and frequency domain. Our frequency analysis shows that avalanche signals are most visible between 20–50 Hz. For larger avalanches, we observe weak low-frequency precursor signals, which correspond to the avalanches approaching towards the fiber. The more prominent high-amplitude signals appear to be produced by the snow masses impacting the stopping cones or the steep terrain near the road. For a smaller, naturally released avalanche, we observe impulsive signals, interpreted as the snow mass stopping. These results agree with earlier studies that used geophone measurements. Automatic detection, tested with simple STA/LTA thresholds in the 20–50 Hz range, presents challenges due to false positives from road traffic. Further refinement and testing are required to improve detection reliability in this complex environment. Our study represents an initial exploration into the application of distributed acoustic sensing for snow avalanche detection, showcasing its potential as an effective monitoring tool for long road networks in mountainous regions.