Articles | Volume 25, issue 4
https://doi.org/10.5194/nhess-25-1315-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-25-1315-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
03 Apr 2025
Research article | Highlight paper |
| 03 Apr 2025
| 03 Apr 2025
Monitoring snow depth variations in an avalanche release area using low-cost lidar and optical sensors
WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, 7260, Switzerland
Climate Change, Extremes, and Natural Hazards in Alpine Regions Research Center (CERC), Davos Dorf, 7260, Switzerland
Institute of Geodesy and Photogrammetry, ETH Zurich, Zurich, 8092, Switzerland
Annelies Voordendag
Institute of Geodesy and Photogrammetry, ETH Zurich, Zurich, 8092, Switzerland
Thierry Hartmann
WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, 7260, Switzerland
Julia Glaus
WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, 7260, Switzerland
Climate Change, Extremes, and Natural Hazards in Alpine Regions Research Center (CERC), Davos Dorf, 7260, Switzerland
Institute for Geotechnical Engineering, ETH Zurich, Zurich, 8092, Switzerland
Andreas Wieser
Institute of Geodesy and Photogrammetry, ETH Zurich, Zurich, 8092, Switzerland
Yves Bühler
WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, 7260, Switzerland
Climate Change, Extremes, and Natural Hazards in Alpine Regions Research Center (CERC), Davos Dorf, 7260, Switzerland
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Elisabeth D. Hafner, Patrick Barton, Rodrigo Caye Daudt, Jan Dirk Wegner, Konrad Schindler, and Yves Bühler
The Cryosphere, 16, 3517–3530, https://doi.org/10.5194/tc-16-3517-2022, https://doi.org/10.5194/tc-16-3517-2022, 2022
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Aubrey Miller, Pascal Sirguey, Simon Morris, Perry Bartelt, Nicolas Cullen, Todd Redpath, Kevin Thompson, and Yves Bühler
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Natural hazard modelers simulate mass movements to better anticipate the risk to people and infrastructure. These simulations require accurate digital elevation models. We test the sensitivity of a well-established snow avalanche model (RAMMS) to the source and spatial resolution of the elevation model. We find key differences in the digital representation of terrain greatly affect the simulated avalanche results, with implications for hazard planning.
Adrian Ringenbach, Elia Stihl, Yves Bühler, Peter Bebi, Perry Bartelt, Andreas Rigling, Marc Christen, Guang Lu, Andreas Stoffel, Martin Kistler, Sandro Degonda, Kevin Simmler, Daniel Mader, and Andrin Caviezel
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Forests have a recognized braking effect on rockfalls. The impact of lying deadwood, however, is mainly neglected. We conducted 1 : 1-scale rockfall experiments in three different states of a spruce forest to fill this knowledge gap: the original forest, the forest including lying deadwood and the cleared area. The deposition points clearly show that deadwood has a protective effect. We reproduced those experimental results numerically, considering three-dimensional cones to be deadwood.
Yves Bühler, Peter Bebi, Marc Christen, Stefan Margreth, Lukas Stoffel, Andreas Stoffel, Christoph Marty, Gregor Schmucki, Andrin Caviezel, Roderick Kühne, Stephan Wohlwend, and Perry Bartelt
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A. B. Voordendag, B. Goger, C. Klug, R. Prinz, M. Rutzinger, and G. Kaser
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 1093–1099, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1093-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1093-2022, 2022
Animesh K. Gain, Yves Bühler, Pascal Haegeli, Daniela Molinari, Mario Parise, David J. Peres, Joaquim G. Pinto, Kai Schröter, Ricardo M. Trigo, María Carmen Llasat, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 22, 985–993, https://doi.org/10.5194/nhess-22-985-2022, https://doi.org/10.5194/nhess-22-985-2022, 2022
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Natalie Brožová, Tommaso Baggio, Vincenzo D'Agostino, Yves Bühler, and Peter Bebi
Nat. Hazards Earth Syst. Sci., 21, 3539–3562, https://doi.org/10.5194/nhess-21-3539-2021, https://doi.org/10.5194/nhess-21-3539-2021, 2021
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Surface roughness plays a great role in natural hazard processes but is not always well implemented in natural hazard modelling. The results of our study show how surface roughness can be useful in representing vegetation and ground structures, which are currently underrated. By including surface roughness in natural hazard modelling, we could better illustrate the processes and thus improve hazard mapping, which is crucial for infrastructure and settlement planning in mountainous areas.
L. H. Hansen, R. van Son, A. Wieser, and E. Kjems
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W4-2021, 43–48, https://doi.org/10.5194/isprs-archives-XLVI-4-W4-2021-43-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W4-2021-43-2021, 2021
Nora Helbig, Michael Schirmer, Jan Magnusson, Flavia Mäder, Alec van Herwijnen, Louis Quéno, Yves Bühler, Jeff S. Deems, and Simon Gascoin
The Cryosphere, 15, 4607–4624, https://doi.org/10.5194/tc-15-4607-2021, https://doi.org/10.5194/tc-15-4607-2021, 2021
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The snow cover spatial variability in mountains changes considerably over the course of a snow season. In applications such as weather, climate and hydrological predictions the fractional snow-covered area is therefore an essential parameter characterizing how much of the ground surface in a grid cell is currently covered by snow. We present a seasonal algorithm and a spatiotemporal evaluation suggesting that the algorithm can be applied in other geographic regions by any snow model application.
Annelies Voordendag, Marion Réveillet, Shelley MacDonell, and Stef Lhermitte
The Cryosphere, 15, 4241–4259, https://doi.org/10.5194/tc-15-4241-2021, https://doi.org/10.5194/tc-15-4241-2021, 2021
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The sensitivity of two snow models (SNOWPACK and SnowModel) to various parameterizations and atmospheric forcing biases is assessed in the semi-arid Andes of Chile in winter 2017. Models show that sublimation is a main driver of ablation and that its relative contribution to total ablation is highly sensitive to the selected albedo parameterization and snow roughness length. The forcing and parameterizations are more important than the model choice, despite differences in physical complexity.
A. B. Voordendag, B. Goger, C. Klug, R. Prinz, M. Rutzinger, and G. Kaser
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2021, 153–160, https://doi.org/10.5194/isprs-annals-V-2-2021-153-2021, https://doi.org/10.5194/isprs-annals-V-2-2021-153-2021, 2021
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Editorial statement
This paper demonstrates a significant technological advance, from measurements of snow depth at a point at high temporal resolution, to mapping snow depth at the 100m scale with high temporal resolution. It has important applications in snow hydrology, snow avalanche research, and climate monitoring. The approach and design are described in detail and will be useful for other researchers looking to apply this approach. The paper is clear and well written, with important details included.
This paper demonstrates a significant technological advance, from measurements of snow depth at...
Short summary
Snow depth variations caused by wind are an important factor in avalanche danger, but detailed and up-to-date information is rarely available. We propose a monitoring system, using lidar and optical sensors, to measure the snow depth distribution at high spatial and temporal resolution. First results show that we can quantify snow depth changes with an accuracy on the low decimeter level, or better, and can identify events such as avalanches or displacement of snow during periods of strong winds.
Snow depth variations caused by wind are an important factor in avalanche danger, but detailed...
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