Preprints
https://doi.org/10.5194/nhess-2024-202
https://doi.org/10.5194/nhess-2024-202
18 Nov 2024
 | 18 Nov 2024
Status: this preprint is currently under review for the journal NHESS.

Seismic Signal Classification of Snow Avalanches using Distributed Acoustic Sensing in Grasdalen, Western Norway

Franz Kleine, Charlotte Bruland, Andreas Wüstefeld, Volker Oye, and Martin Landrø

Abstract. We show the usage of Distributed Acoustic Sensing for analyzing seismic signals from snow avalanche events. For three winter seasons we continuously recorded seismic data using Distributed Acoustic Sensing (DAS) on a section of a standard telecommunication fiber along a mountain road in Grasdalen, western Norway. Multiple snow avalanche events were registered, alongside various other signals such as road traffic and detonations from remote avalanche triggering. We describe signal characteristics of natural and manually triggered avalanche events 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 avalanche’s approach. The more prominent high-amplitude signals appear to be produced by the snow masses impacting stopping cones or the steep terrain near the road. In one natural avalanche event, we interpret distinct spike signals as likely corresponding to the stopping snow mass, based on similar findings from previous studies using geophones. 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.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Franz Kleine, Charlotte Bruland, Andreas Wüstefeld, Volker Oye, and Martin Landrø

Status: open (until 30 Dec 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Franz Kleine, Charlotte Bruland, Andreas Wüstefeld, Volker Oye, and Martin Landrø
Franz Kleine, Charlotte Bruland, Andreas Wüstefeld, Volker Oye, and Martin Landrø

Viewed

Total article views: 92 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
71 18 3 92 2 1
  • HTML: 71
  • PDF: 18
  • XML: 3
  • Total: 92
  • BibTeX: 2
  • EndNote: 1
Views and downloads (calculated since 18 Nov 2024)
Cumulative views and downloads (calculated since 18 Nov 2024)

Viewed (geographical distribution)

Total article views: 91 (including HTML, PDF, and XML) Thereof 91 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 23 Nov 2024
Download
Short summary
We used a fiber optic cable along a road in western Norway to study snow avalanches signals. Our study shows that avalanches create distinct signals in the 20–50 Hz frequency range, with larger ones having weak early warning signals. However, road traffic interference complicates automatic detection. This research highlights the potential of using existing infrastructure for avalanche monitoring. Further improvements are needed for automated detection.
Altmetrics