EGU24-15088, updated on 09 Mar 2024
https://doi.org/10.5194/egusphere-egu24-15088
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Snow depth distribution measurements using low cost LiDAR sensors

Pia Ruttner-Jansen1,2,3, Julia Glaus1,2,4, Annelies Voordendag3, Andreas Wieser3, and Yves Bühler1,2
Pia Ruttner-Jansen et al.
  • 1WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland, (pia.ruttner@slf.ch)
  • 2Climate Change, Extremes, and Natural Hazards in Alpine Regions Research Center CERC, Davos Dorf, Switzerland
  • 3Institute of Geodesy and Photogrammetry, ETH Zurich, Zurich, Switzerland
  • 4Institute for Geotechnical Engineering, ETH Zurich, Zurich, Switzerland

Redistribution of snow by wind is an important factor influencing the avalanche danger. However, it is challenging to get detailed information on variations of snow depth in avalanche release areas with sufficiently high spatiotemporal resolution. We have developed a distributed measurement system containing two low cost LiDAR sensors, cameras and meteorological sensors. In autumn 2023 we have deployed this system at a first test site, in the area of a frequently released avalanche. Two stations equipped with the sensors cover an area of around 20'000 m² and provide the snow depth distribution once per hour with a spatial resolution on the cm to m-level. The (near) real time data transmission to a local server allows for an up-to-date assessment of the conditions in the slope. First analyses show the small temporal changes of average snow depth from epoch to epoch for small areas (1m²), including some local avalanche events. We will present first results obtained from the unique dataset resulting from acquisition at high spatio-temporal resolution over the entire winter season 2023/2024, focusing particularly on the snow depth variations before and after avalanche events. In the future, the newly built up snow depth database and the additionally recorded meteorological parameters will be used to model, predict and evaluate the snow depth redistribution on a slope scale level. The data collected directly within the release areas will improve the process understanding of avalanche formation and forecasting, and will thus contribute to better protection of people and infrastructure.

How to cite: Ruttner-Jansen, P., Glaus, J., Voordendag, A., Wieser, A., and Bühler, Y.: Snow depth distribution measurements using low cost LiDAR sensors, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15088, https://doi.org/10.5194/egusphere-egu24-15088, 2024.