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Conference Paper

Avalanche detection using existing telecommunication infrastructure and Distributed Acoustic Sensing

Authors

Edme,  Pascal
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Paitz,  Patrick
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Walter,  Fabian
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

van Herwijnen,  Alec
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Fichtner,  Andreas
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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Citation

Edme, P., Paitz, P., Walter, F., van Herwijnen, A., Fichtner, A. (2023): Avalanche detection using existing telecommunication infrastructure and Distributed Acoustic Sensing, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-4714


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5021122
Abstract
We demonstrate the detectability of snow avalanches using Distributed Acoustic Sensing (DAS) with existing fiber-optic telecommunication cables. To achieve this, during winter 2021/2022, we interrogated a ~10 km long dark fiber that follows the avalanche-prone Flüelapass road in the Swiss Alps. In addition to other signals like traffic and earthquakes, the DAS data contain clear recordings of numerous snow avalanches, even though many of them did not reach the sensing cable itself, as revealed with automatic cameras and images taken by drone. The spatial resolution of the detection is of the order of few tens of meters. Avalanche signals can produce strong strain fluctuations exceeding 3 μm/m/s and they exhibit specific characteristics in terms of frequency content and apparent velocities which, we believe, can be used to discriminate them from other types of events. Our results open new perspectives for cost-effective, near-real-time avalanche monitoring over long distances using pre-installed fiber-optic infrastructure.