Articles | Volume 22, issue 6
https://doi.org/10.5194/nhess-22-1825-2022
© Author(s) 2022. 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-22-1825-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Jun 2022
Research article |
| 02 Jun 2022
| 02 Jun 2022
Automated avalanche hazard indication mapping on a statewide scale
WSL Institute for Snow and Avalanche Research SLF, 7260 Davos Dorf, Switzerland
Climate Change, Extremes and Natural Hazards in Alpine Regions
Research Center CERC, 7260 Davos Dorf, Switzerland
Peter Bebi
WSL Institute for Snow and Avalanche Research SLF, 7260 Davos Dorf, Switzerland
Climate Change, Extremes and Natural Hazards in Alpine Regions
Research Center CERC, 7260 Davos Dorf, Switzerland
Marc Christen
WSL Institute for Snow and Avalanche Research SLF, 7260 Davos Dorf, Switzerland
Climate Change, Extremes and Natural Hazards in Alpine Regions
Research Center CERC, 7260 Davos Dorf, Switzerland
Stefan Margreth
WSL Institute for Snow and Avalanche Research SLF, 7260 Davos Dorf, Switzerland
Lukas Stoffel
WSL Institute for Snow and Avalanche Research SLF, 7260 Davos Dorf, Switzerland
Andreas Stoffel
WSL Institute for Snow and Avalanche Research SLF, 7260 Davos Dorf, Switzerland
Climate Change, Extremes and Natural Hazards in Alpine Regions
Research Center CERC, 7260 Davos Dorf, Switzerland
Christoph Marty
WSL Institute for Snow and Avalanche Research SLF, 7260 Davos Dorf, Switzerland
Gregor Schmucki
WSL Institute for Snow and Avalanche Research SLF, 7260 Davos Dorf, Switzerland
Climate Change, Extremes and Natural Hazards in Alpine Regions
Research Center CERC, 7260 Davos Dorf, Switzerland
Andrin Caviezel
WSL Institute for Snow and Avalanche Research SLF, 7260 Davos Dorf, Switzerland
Climate Change, Extremes and Natural Hazards in Alpine Regions
Research Center CERC, 7260 Davos Dorf, Switzerland
Roderick Kühne
Department of Forest and Natural Hazards (AWN), Canton Grisons, 7000 Chur, Switzerland
Stephan Wohlwend
Office for Civil Protection, Government of Liechtenstein, 9490 Vaduz, Liechtenstein
Perry Bartelt
WSL Institute for Snow and Avalanche Research SLF, 7260 Davos Dorf, Switzerland
Climate Change, Extremes and Natural Hazards in Alpine Regions
Research Center CERC, 7260 Davos Dorf, Switzerland
Related authors
Feiko Bernard van Zadelhoff, Yves Bühler, and Michael Bründl
EGUsphere, https://doi.org/10.5194/egusphere-2026-4604, https://doi.org/10.5194/egusphere-2026-4604, 2026
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
Debris flows are a major hazard in mountainous areas, causing millions of francs in damage in Switzerland every year. Therefore, the Swiss national railway company aims to identify dangerous areas along their infrastructure. We perform this analysis by identifying critical areas using machine learning and detailed simulation modelling of debris flow events caused by extreme rainfall. The results are a valuable baseline to plan mitigation measures and be better prepared for the future.
Jan Kleinn, Dörte Aller, Yves Bühler, Julia Glaus, Adrian Peter, and Nils Hählen
EGUsphere, https://doi.org/10.5194/egusphere-2026-3799, https://doi.org/10.5194/egusphere-2026-3799, 2026
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
We have demonstrated that it is possible to apply an approach to hazard and risk modelling of avalanches, which is commonly used for seismic risks and other hazards. This approach provides more differentiated results and additional information compared to the current approach used in Switzerland for hazard assessment. The applicability of the approach has been demonstrated with an avalanche model commonly used in Switzerland and can be applied to other avalanche models.
Pia Ruttner, Nora Helbig, Annelies Voordendag, Andreas Wieser, and Yves Bühler
The Cryosphere, 20, 4185–4208, https://doi.org/10.5194/tc-20-4185-2026, https://doi.org/10.5194/tc-20-4185-2026, 2026
Short summary
Short summary
The spatial variability of snow depth distribution in avalanche release areas is key for avalanche forecasting but is strongly influenced by the interaction of wind with the terrain. We generate maps of high resolution snow depth changes during three snowfall events by using low-cost terrestrial laser scanner measurements and compare them to the results of selected snow depth distribution models. We show that basic terrain derivations have the highest correlations to our measurement results.
Elizabeth Fischer, Gabriel J. Wolken, Yves Bühler, Marc Christen, and Rick Lader
EGUsphere, https://doi.org/10.5194/egusphere-2026-1345, https://doi.org/10.5194/egusphere-2026-1345, 2026
Short summary
Short summary
Snow avalanches are a major hazard in Southeast Alaska, where limited data and climate change complicate risk planning. We created the first regional hazard maps using past and projected climate conditions. Results show hazard decreasing at lower elevations as rain replaces snow but increasing at high elevations due to more snow and longer avalanche runouts. These maps provide an important tool for informed land-use and infrastructure planning as Alaska’s landscapes adapt to a changing climate.
Julia Glaus, Jan Kleinn, Lukas Stoffel, Pia Ruttner, Katreen Wikstrom Jones, Johan Gaume, and Yves Bühler
EGUsphere, https://doi.org/10.5194/egusphere-2026-999, https://doi.org/10.5194/egusphere-2026-999, 2026
Short summary
Short summary
Snow avalanches threaten roads, ski areas, and communities in mountain regions. We present a practical method to create daily maps showing where avalanches are likely to travel and how strong they may be. By combining weather data, snow measurements, and computer simulations, our approach supports safer decisions on road closures and avalanche control and helps protect people and infrastructure.
Jaeyoung Lim, Elisabeth Hafner-Aeschbacher, Florian Achermann, Rik Girod, David Rohr, Nicholas Lawrance, Yves Bühler, and Roland Siegwart
Nat. Hazards Earth Syst. Sci., 26, 411–431, https://doi.org/10.5194/nhess-26-411-2026, https://doi.org/10.5194/nhess-26-411-2026, 2026
Short summary
Short summary
As avalanches occur in remote and potentially dangerous locations, data relevant to avalanche monitoring is difficult to obtain. Uncrewed fixed-wing aerial vehicles are promising platforms for gathering aerial imagery to map avalanche activity over a large area. In this work, we present an unmanned aerial system (UAS) capable of autonomously navigating and mapping avalanches in steep mountainous terrain. We expect our work to enable efficient large-scale autonomous avalanche monitoring.
Julia Glaus, Katreen Wikstrom Jones, Perry Bartelt, Marc Christen, Lukas Stoffel, Johan Gaume, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 25, 2399–2419, https://doi.org/10.5194/nhess-25-2399-2025, https://doi.org/10.5194/nhess-25-2399-2025, 2025
Short summary
Short summary
This study assesses RAMMS::EXTENDED's predictive power in estimating avalanche runout distances critical for mountain road safety. Leveraging meteorological data and sensitivity analyses, it offers meaningful predictions, aiding near real-time hazard assessments and future model refinement for improved decision-making.
Pia Ruttner, Annelies Voordendag, Thierry Hartmann, Julia Glaus, Andreas Wieser, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 25, 1315–1330, https://doi.org/10.5194/nhess-25-1315-2025, https://doi.org/10.5194/nhess-25-1315-2025, 2025
Short summary
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.
John Sykes, Pascal Haegeli, Roger Atkins, Patrick Mair, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 25, 1255–1292, https://doi.org/10.5194/nhess-25-1255-2025, https://doi.org/10.5194/nhess-25-1255-2025, 2025
Short summary
Short summary
We model the decision-making of professional ski guides and develop decision support tools to assist with determining appropriate terrain based on current conditions. Our approach compares a manually constructed Bayesian network with machine learning classification models. The models accurately capture the real-world decision-making outcomes in 85–93 % of cases. Our conclusions focus on strengths and weaknesses of each model and discuss ramifications for practical applications in ski guiding.
Jan Magnusson, Yves Bühler, Louis Quéno, Bertrand Cluzet, Giulia Mazzotti, Clare Webster, Rebecca Mott, and Tobias Jonas
Earth Syst. Sci. Data, 17, 703–717, https://doi.org/10.5194/essd-17-703-2025, https://doi.org/10.5194/essd-17-703-2025, 2025
Short summary
Short summary
In this study, we present a dataset for the Dischma catchment in eastern Switzerland, which represents a typical high-alpine watershed in the European Alps. Accurate monitoring and reliable forecasting of snow and water resources in such basins are crucial for a wide range of applications. Our dataset is valuable for improving physics-based snow, land surface, and hydrological models, with potential applications in similar high-alpine catchments.
Andrea Manconi, Yves Bühler, Andreas Stoffel, Johan Gaume, Qiaoping Zhang, and Valentyn Tolpekin
Nat. Hazards Earth Syst. Sci., 24, 3833–3839, https://doi.org/10.5194/nhess-24-3833-2024, https://doi.org/10.5194/nhess-24-3833-2024, 2024
Short summary
Short summary
Our research reveals the power of high-resolution satellite synthetic-aperture radar (SAR) imagery for slope deformation monitoring. Using ICEYE data over the Brienz/Brinzauls instability, we measured surface velocity and mapped the landslide event with unprecedented precision. This underscores the potential of satellite SAR for timely hazard assessment in remote regions and aiding disaster mitigation efforts effectively.
Elisabeth D. Hafner, Theodora Kontogianni, Rodrigo Caye Daudt, Lucien Oberson, Jan Dirk Wegner, Konrad Schindler, and Yves Bühler
The Cryosphere, 18, 3807–3823, https://doi.org/10.5194/tc-18-3807-2024, https://doi.org/10.5194/tc-18-3807-2024, 2024
Short summary
Short summary
For many safety-related applications such as road management, well-documented avalanches are important. To enlarge the information, webcams may be used. We propose supporting the mapping of avalanches from webcams with a machine learning model that interactively works together with the human. Relying on that model, there is a 90% saving of time compared to the "traditional" mapping. This gives a better base for safety-critical decisions and planning in avalanche-prone mountain regions.
Elisabeth D. Hafner, Frank Techel, Rodrigo Caye Daudt, Jan Dirk Wegner, Konrad Schindler, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 23, 2895–2914, https://doi.org/10.5194/nhess-23-2895-2023, https://doi.org/10.5194/nhess-23-2895-2023, 2023
Short summary
Short summary
Oftentimes when objective measurements are not possible, human estimates are used instead. In our study, we investigate the reproducibility of human judgement for size estimates, the mappings of avalanches from oblique photographs and remotely sensed imagery. The variability that we found in those estimates is worth considering as it may influence results and should be kept in mind for several applications.
Leon J. Bührle, Mauro Marty, Lucie A. Eberhard, Andreas Stoffel, Elisabeth D. Hafner, and Yves Bühler
The Cryosphere, 17, 3383–3408, https://doi.org/10.5194/tc-17-3383-2023, https://doi.org/10.5194/tc-17-3383-2023, 2023
Short summary
Short summary
Information on the snow depth distribution is crucial for numerous applications in high-mountain regions. However, only specific measurements can accurately map the present variability of snow depths within complex terrain. In this study, we show the reliable processing of images from aeroplane to large (> 100 km2) detailed and accurate snow depth maps around Davos (CH). We use these maps to describe the existing snow depth distribution, other special features and potential applications.
Adrian Ringenbach, Peter Bebi, Perry Bartelt, Andreas Rigling, Marc Christen, Yves Bühler, Andreas Stoffel, and Andrin Caviezel
Earth Surf. Dynam., 11, 779–801, https://doi.org/10.5194/esurf-11-779-2023, https://doi.org/10.5194/esurf-11-779-2023, 2023
Short summary
Short summary
Swiss researchers carried out repeated rockfall experiments with rocks up to human sizes in a steep mountain forest. This study focuses mainly on the effects of the rock shape and lying deadwood. In forested areas, cubic-shaped rocks showed a longer mean runout distance than platy-shaped rocks. Deadwood especially reduced the runouts of these cubic rocks. The findings enrich standard practices in modern rockfall hazard zoning assessments and strongly urge the incorporation of rock shape effects.
Gregor Ortner, Michael Bründl, Chahan M. Kropf, Thomas Röösli, Yves Bühler, and David N. Bresch
Nat. Hazards Earth Syst. Sci., 23, 2089–2110, https://doi.org/10.5194/nhess-23-2089-2023, https://doi.org/10.5194/nhess-23-2089-2023, 2023
Short summary
Short summary
This paper presents a new approach to assess avalanche risk on a large scale in mountainous regions. It combines a large-scale avalanche modeling method with a state-of-the-art probabilistic risk tool. Over 40 000 individual avalanches were simulated, and a building dataset with over 13 000 single buildings was investigated. With this new method, risk hotspots can be identified and surveyed. This enables current and future risk analysis to assist decision makers in risk reduction and adaptation.
Adrian Ringenbach, Peter Bebi, Perry Bartelt, Andreas Rigling, Marc Christen, Yves Bühler, Andreas Stoffel, and Andrin Caviezel
Earth Surf. Dynam., 10, 1303–1319, https://doi.org/10.5194/esurf-10-1303-2022, https://doi.org/10.5194/esurf-10-1303-2022, 2022
Short summary
Short summary
The presented automatic deadwood generator (ADG) allows us to consider deadwood in rockfall simulations in unprecedented detail. Besides three-dimensional fresh deadwood cones, we include old woody debris in rockfall simulations based on a higher compaction rate and lower energy absorption thresholds. Simulations including different deadwood states indicate that a 10-year-old deadwood pile has a higher protective capacity than a pre-storm forest stand.
John Sykes, Pascal Haegeli, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 22, 3247–3270, https://doi.org/10.5194/nhess-22-3247-2022, https://doi.org/10.5194/nhess-22-3247-2022, 2022
Short summary
Short summary
Automated snow avalanche terrain mapping provides an efficient method for large-scale assessment of avalanche hazards, which informs risk management decisions for transportation and recreation. This research reduces the cost of developing avalanche terrain maps by using satellite imagery and open-source software as well as improving performance in forested terrain. The research relies on local expertise to evaluate accuracy, so the methods are broadly applicable in mountainous regions worldwide.
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
Short summary
Short summary
Knowing where avalanches occur is very important information for several disciplines, for example avalanche warning, hazard zonation and risk management. Satellite imagery can provide such data systematically over large regions. In our work we propose a machine learning model to automate the time-consuming manual mapping. Additionally, we investigate expert agreement for manual avalanche mapping, showing that our network is equally as good as the experts in identifying avalanches.
Aubrey Miller, Pascal Sirguey, Simon Morris, Perry Bartelt, Nicolas Cullen, Todd Redpath, Kevin Thompson, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 22, 2673–2701, https://doi.org/10.5194/nhess-22-2673-2022, https://doi.org/10.5194/nhess-22-2673-2022, 2022
Short summary
Short summary
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
Nat. Hazards Earth Syst. Sci., 22, 2433–2443, https://doi.org/10.5194/nhess-22-2433-2022, https://doi.org/10.5194/nhess-22-2433-2022, 2022
Short summary
Short summary
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.
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
Short summary
Short summary
To mark the 20th anniversary of Natural Hazards and Earth System Sciences (NHESS), an interdisciplinary and international journal dedicated to the public discussion and open-access publication of high-quality studies and original research on natural hazards and their consequences, we highlight 11 key publications covering major subject areas of NHESS that stood out within the past 20 years.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Feiko Bernard van Zadelhoff, Yves Bühler, and Michael Bründl
EGUsphere, https://doi.org/10.5194/egusphere-2026-4604, https://doi.org/10.5194/egusphere-2026-4604, 2026
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
Debris flows are a major hazard in mountainous areas, causing millions of francs in damage in Switzerland every year. Therefore, the Swiss national railway company aims to identify dangerous areas along their infrastructure. We perform this analysis by identifying critical areas using machine learning and detailed simulation modelling of debris flow events caused by extreme rainfall. The results are a valuable baseline to plan mitigation measures and be better prepared for the future.
Jan Kleinn, Dörte Aller, Yves Bühler, Julia Glaus, Adrian Peter, and Nils Hählen
EGUsphere, https://doi.org/10.5194/egusphere-2026-3799, https://doi.org/10.5194/egusphere-2026-3799, 2026
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
We have demonstrated that it is possible to apply an approach to hazard and risk modelling of avalanches, which is commonly used for seismic risks and other hazards. This approach provides more differentiated results and additional information compared to the current approach used in Switzerland for hazard assessment. The applicability of the approach has been demonstrated with an avalanche model commonly used in Switzerland and can be applied to other avalanche models.
Pia Ruttner, Nora Helbig, Annelies Voordendag, Andreas Wieser, and Yves Bühler
The Cryosphere, 20, 4185–4208, https://doi.org/10.5194/tc-20-4185-2026, https://doi.org/10.5194/tc-20-4185-2026, 2026
Short summary
Short summary
The spatial variability of snow depth distribution in avalanche release areas is key for avalanche forecasting but is strongly influenced by the interaction of wind with the terrain. We generate maps of high resolution snow depth changes during three snowfall events by using low-cost terrestrial laser scanner measurements and compare them to the results of selected snow depth distribution models. We show that basic terrain derivations have the highest correlations to our measurement results.
Harsh Beria, Sven Kotlarski, Adrien Michel, Jan Magnusson, and Christoph Marty
EGUsphere, https://doi.org/10.5194/egusphere-2026-3478, https://doi.org/10.5194/egusphere-2026-3478, 2026
Short summary
Short summary
Snow is a vital water store for Switzerland, supporting hydropower, winter tourism, and aquatic ecosystems. Using the latest Swiss climate projections, we project future snow water across Switzerland at high spatial resolution. By the end of this century under high emission scenarios, low-lying regions are projected to become nearly snow-free, while even high mountains lose much of their snow. These results can support planning for future Alpine water resources under a warming climate.
Joël Borner, Peter Bebi, Leon Bührle, Adrian Ringenbach, and Remco Ingmar Leine
EGUsphere, https://doi.org/10.5194/egusphere-2026-130, https://doi.org/10.5194/egusphere-2026-130, 2026
Short summary
Short summary
Deadwood supports biodiversity and contributes to the protective function of mountain forests, but under certain conditions it can itself become a hazard when sliding downslope. This study examines when and why sliding deadwood occurs and how far it can travel. Using a physics-based simulation model and forest data, we show that sliding is favoured by steep slopes, wet surfaces, and specific decay stages, helping identify where hazards can be reduced while preserving protective forest functions.
Elizabeth Fischer, Gabriel J. Wolken, Yves Bühler, Marc Christen, and Rick Lader
EGUsphere, https://doi.org/10.5194/egusphere-2026-1345, https://doi.org/10.5194/egusphere-2026-1345, 2026
Short summary
Short summary
Snow avalanches are a major hazard in Southeast Alaska, where limited data and climate change complicate risk planning. We created the first regional hazard maps using past and projected climate conditions. Results show hazard decreasing at lower elevations as rain replaces snow but increasing at high elevations due to more snow and longer avalanche runouts. These maps provide an important tool for informed land-use and infrastructure planning as Alaska’s landscapes adapt to a changing climate.
Julia Glaus, Jan Kleinn, Lukas Stoffel, Pia Ruttner, Katreen Wikstrom Jones, Johan Gaume, and Yves Bühler
EGUsphere, https://doi.org/10.5194/egusphere-2026-999, https://doi.org/10.5194/egusphere-2026-999, 2026
Short summary
Short summary
Snow avalanches threaten roads, ski areas, and communities in mountain regions. We present a practical method to create daily maps showing where avalanches are likely to travel and how strong they may be. By combining weather data, snow measurements, and computer simulations, our approach supports safer decisions on road closures and avalanche control and helps protect people and infrastructure.
Bettina Richter and Christoph Marty
Hydrol. Earth Syst. Sci., 30, 659–670, https://doi.org/10.5194/hess-30-659-2026, https://doi.org/10.5194/hess-30-659-2026, 2026
Short summary
Short summary
We developed a literature-based approach for projecting future snow depths, which was applied to four measurement stations in Switzerland under a +2 °C temperature scenario, revealing significant declines in snow depths. Validation against published data shows that the approach captures key trends in snow loss. This resource-efficient method provides a practical tool for estimating climate change related snow depth declines, which are lacking highly resolved climate projections.
Jaeyoung Lim, Elisabeth Hafner-Aeschbacher, Florian Achermann, Rik Girod, David Rohr, Nicholas Lawrance, Yves Bühler, and Roland Siegwart
Nat. Hazards Earth Syst. Sci., 26, 411–431, https://doi.org/10.5194/nhess-26-411-2026, https://doi.org/10.5194/nhess-26-411-2026, 2026
Short summary
Short summary
As avalanches occur in remote and potentially dangerous locations, data relevant to avalanche monitoring is difficult to obtain. Uncrewed fixed-wing aerial vehicles are promising platforms for gathering aerial imagery to map avalanche activity over a large area. In this work, we present an unmanned aerial system (UAS) capable of autonomously navigating and mapping avalanches in steep mountainous terrain. We expect our work to enable efficient large-scale autonomous avalanche monitoring.
Christoph Marty, Adrien Michel, Tobias Jonas, Cynthia Steijn, Regula Muelchi, and Sven Kotlarski
The Cryosphere, 19, 4391–4407, https://doi.org/10.5194/tc-19-4391-2025, https://doi.org/10.5194/tc-19-4391-2025, 2025
Short summary
Short summary
This work presents the first long-term (since 1962), daily, 1 km gridded dataset of snow depth and water storage for Switzerland. Its quality was assessed by comparing yearly, monthly, and weekly values to a higher-quality model and in situ measurements. Results show good overall performance, though some limitations exist at low elevations and short timescales. Despite this, the dataset effectively captures trends, offering valuable insights for climate monitoring and elevation-based changes.
Julia Glaus, Katreen Wikstrom Jones, Perry Bartelt, Marc Christen, Lukas Stoffel, Johan Gaume, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 25, 2399–2419, https://doi.org/10.5194/nhess-25-2399-2025, https://doi.org/10.5194/nhess-25-2399-2025, 2025
Short summary
Short summary
This study assesses RAMMS::EXTENDED's predictive power in estimating avalanche runout distances critical for mountain road safety. Leveraging meteorological data and sensitivity analyses, it offers meaningful predictions, aiding near real-time hazard assessments and future model refinement for improved decision-making.
Yu Zhuang, Brian W. McArdell, and Perry Bartelt
Nat. Hazards Earth Syst. Sci., 25, 1901–1912, https://doi.org/10.5194/nhess-25-1901-2025, https://doi.org/10.5194/nhess-25-1901-2025, 2025
Short summary
Short summary
The experimentally based μ(I) rheology, widely used for gravitational mass flows, is reinterpreted as a Voellmy-type relationship to highlight its link to grain flow theory. Through block modeling and case studies, we establish its equivalence to μ(R) rheology. μ(I) models shear thinning but fails to capture acceleration and deceleration processes and deposit structure. Incorporating fluctuation energy in μ(R) improves accuracy, refining mass flow modeling and revealing practical challenges.
Pia Ruttner, Annelies Voordendag, Thierry Hartmann, Julia Glaus, Andreas Wieser, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 25, 1315–1330, https://doi.org/10.5194/nhess-25-1315-2025, https://doi.org/10.5194/nhess-25-1315-2025, 2025
Short summary
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.
John Sykes, Pascal Haegeli, Roger Atkins, Patrick Mair, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 25, 1255–1292, https://doi.org/10.5194/nhess-25-1255-2025, https://doi.org/10.5194/nhess-25-1255-2025, 2025
Short summary
Short summary
We model the decision-making of professional ski guides and develop decision support tools to assist with determining appropriate terrain based on current conditions. Our approach compares a manually constructed Bayesian network with machine learning classification models. The models accurately capture the real-world decision-making outcomes in 85–93 % of cases. Our conclusions focus on strengths and weaknesses of each model and discuss ramifications for practical applications in ski guiding.
Jan Magnusson, Yves Bühler, Louis Quéno, Bertrand Cluzet, Giulia Mazzotti, Clare Webster, Rebecca Mott, and Tobias Jonas
Earth Syst. Sci. Data, 17, 703–717, https://doi.org/10.5194/essd-17-703-2025, https://doi.org/10.5194/essd-17-703-2025, 2025
Short summary
Short summary
In this study, we present a dataset for the Dischma catchment in eastern Switzerland, which represents a typical high-alpine watershed in the European Alps. Accurate monitoring and reliable forecasting of snow and water resources in such basins are crucial for a wide range of applications. Our dataset is valuable for improving physics-based snow, land surface, and hydrological models, with potential applications in similar high-alpine catchments.
Adrien Michel, Johannes Aschauer, Tobias Jonas, Stefanie Gubler, Sven Kotlarski, and Christoph Marty
Geosci. Model Dev., 17, 8969–8988, https://doi.org/10.5194/gmd-17-8969-2024, https://doi.org/10.5194/gmd-17-8969-2024, 2024
Short summary
Short summary
We present a method to correct snow cover maps (represented in terms of snow water equivalent) to match better-quality maps. The correction can then be extended backwards and forwards in time for periods when better-quality maps are not available. The method is fast and gives good results. It is then applied to obtain a climatology of the snow cover in Switzerland over the past 60 years at a resolution of 1 d and 1 km. This is the first time that such a dataset has been produced.
Matthew Switanek, Gernot Resch, Andreas Gobiet, Daniel Günther, Christoph Marty, and Wolfgang Schöner
The Cryosphere, 18, 6005–6026, https://doi.org/10.5194/tc-18-6005-2024, https://doi.org/10.5194/tc-18-6005-2024, 2024
Short summary
Short summary
Snow depth plays an important role in water resources, mountain tourism, and hazard management across the European Alps. Our study uses station-based historical observations to quantify how changes in temperature and precipitation affect average seasonal snow depth. We find that the relationship between these variables has been surprisingly robust over the last 120 years. This allows us to more accurately estimate how future climate will affect seasonal snow depth in different elevation zones.
Andrea Manconi, Yves Bühler, Andreas Stoffel, Johan Gaume, Qiaoping Zhang, and Valentyn Tolpekin
Nat. Hazards Earth Syst. Sci., 24, 3833–3839, https://doi.org/10.5194/nhess-24-3833-2024, https://doi.org/10.5194/nhess-24-3833-2024, 2024
Short summary
Short summary
Our research reveals the power of high-resolution satellite synthetic-aperture radar (SAR) imagery for slope deformation monitoring. Using ICEYE data over the Brienz/Brinzauls instability, we measured surface velocity and mapped the landslide event with unprecedented precision. This underscores the potential of satellite SAR for timely hazard assessment in remote regions and aiding disaster mitigation efforts effectively.
Elisabeth D. Hafner, Theodora Kontogianni, Rodrigo Caye Daudt, Lucien Oberson, Jan Dirk Wegner, Konrad Schindler, and Yves Bühler
The Cryosphere, 18, 3807–3823, https://doi.org/10.5194/tc-18-3807-2024, https://doi.org/10.5194/tc-18-3807-2024, 2024
Short summary
Short summary
For many safety-related applications such as road management, well-documented avalanches are important. To enlarge the information, webcams may be used. We propose supporting the mapping of avalanches from webcams with a machine learning model that interactively works together with the human. Relying on that model, there is a 90% saving of time compared to the "traditional" mapping. This gives a better base for safety-critical decisions and planning in avalanche-prone mountain regions.
Elisabeth D. Hafner, Frank Techel, Rodrigo Caye Daudt, Jan Dirk Wegner, Konrad Schindler, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 23, 2895–2914, https://doi.org/10.5194/nhess-23-2895-2023, https://doi.org/10.5194/nhess-23-2895-2023, 2023
Short summary
Short summary
Oftentimes when objective measurements are not possible, human estimates are used instead. In our study, we investigate the reproducibility of human judgement for size estimates, the mappings of avalanches from oblique photographs and remotely sensed imagery. The variability that we found in those estimates is worth considering as it may influence results and should be kept in mind for several applications.
Leon J. Bührle, Mauro Marty, Lucie A. Eberhard, Andreas Stoffel, Elisabeth D. Hafner, and Yves Bühler
The Cryosphere, 17, 3383–3408, https://doi.org/10.5194/tc-17-3383-2023, https://doi.org/10.5194/tc-17-3383-2023, 2023
Short summary
Short summary
Information on the snow depth distribution is crucial for numerous applications in high-mountain regions. However, only specific measurements can accurately map the present variability of snow depths within complex terrain. In this study, we show the reliable processing of images from aeroplane to large (> 100 km2) detailed and accurate snow depth maps around Davos (CH). We use these maps to describe the existing snow depth distribution, other special features and potential applications.
Adrian Ringenbach, Peter Bebi, Perry Bartelt, Andreas Rigling, Marc Christen, Yves Bühler, Andreas Stoffel, and Andrin Caviezel
Earth Surf. Dynam., 11, 779–801, https://doi.org/10.5194/esurf-11-779-2023, https://doi.org/10.5194/esurf-11-779-2023, 2023
Short summary
Short summary
Swiss researchers carried out repeated rockfall experiments with rocks up to human sizes in a steep mountain forest. This study focuses mainly on the effects of the rock shape and lying deadwood. In forested areas, cubic-shaped rocks showed a longer mean runout distance than platy-shaped rocks. Deadwood especially reduced the runouts of these cubic rocks. The findings enrich standard practices in modern rockfall hazard zoning assessments and strongly urge the incorporation of rock shape effects.
Johannes Aschauer, Adrien Michel, Tobias Jonas, and Christoph Marty
Geosci. Model Dev., 16, 4063–4081, https://doi.org/10.5194/gmd-16-4063-2023, https://doi.org/10.5194/gmd-16-4063-2023, 2023
Short summary
Short summary
Snow water equivalent is the mass of water stored in a snowpack. Based on exponential settling functions, the empirical snow density model SWE2HS is presented to convert time series of daily snow water equivalent into snow depth. The model has been calibrated with data from Switzerland and validated with independent data from the European Alps. A reference implementation of SWE2HS is available as a Python package.
Gregor Ortner, Michael Bründl, Chahan M. Kropf, Thomas Röösli, Yves Bühler, and David N. Bresch
Nat. Hazards Earth Syst. Sci., 23, 2089–2110, https://doi.org/10.5194/nhess-23-2089-2023, https://doi.org/10.5194/nhess-23-2089-2023, 2023
Short summary
Short summary
This paper presents a new approach to assess avalanche risk on a large scale in mountainous regions. It combines a large-scale avalanche modeling method with a state-of-the-art probabilistic risk tool. Over 40 000 individual avalanches were simulated, and a building dataset with over 13 000 single buildings was investigated. With this new method, risk hotspots can be identified and surveyed. This enables current and future risk analysis to assist decision makers in risk reduction and adaptation.
Yu Zhuang, Aiguo Xing, Perry Bartelt, Muhammad Bilal, and Zhaowei Ding
Nat. Hazards Earth Syst. Sci., 23, 1257–1266, https://doi.org/10.5194/nhess-23-1257-2023, https://doi.org/10.5194/nhess-23-1257-2023, 2023
Short summary
Short summary
Tree destruction is often used to back calculate the air blast impact region and to estimate the air blast power. Here we established a novel model to assess air blast power using tree destruction information. We find that the dynamic magnification effect makes the trees easier to damage by a landslide-induced air blast, but the large tree deformation would weaken the effect. Bending and overturning are two likely failure modes, which depend heavily on the properties of trees.
Moritz Buchmann, Gernot Resch, Michael Begert, Stefan Brönnimann, Barbara Chimani, Wolfgang Schöner, and Christoph Marty
The Cryosphere, 17, 653–671, https://doi.org/10.5194/tc-17-653-2023, https://doi.org/10.5194/tc-17-653-2023, 2023
Short summary
Short summary
Our current knowledge of spatial and temporal snow depth trends is based almost exclusively on time series of non-homogenised observational data. However, like other long-term series from observations, they are susceptible to inhomogeneities that can affect the trends and even change the sign. To assess the relevance of homogenisation for daily snow depths, we investigated its impact on trends and changes in extreme values of snow indices between 1961 and 2021 in the Swiss observation network.
Adrian Ringenbach, Peter Bebi, Perry Bartelt, Andreas Rigling, Marc Christen, Yves Bühler, Andreas Stoffel, and Andrin Caviezel
Earth Surf. Dynam., 10, 1303–1319, https://doi.org/10.5194/esurf-10-1303-2022, https://doi.org/10.5194/esurf-10-1303-2022, 2022
Short summary
Short summary
The presented automatic deadwood generator (ADG) allows us to consider deadwood in rockfall simulations in unprecedented detail. Besides three-dimensional fresh deadwood cones, we include old woody debris in rockfall simulations based on a higher compaction rate and lower energy absorption thresholds. Simulations including different deadwood states indicate that a 10-year-old deadwood pile has a higher protective capacity than a pre-storm forest stand.
François Noël, Michel Jaboyedoff, Andrin Caviezel, Clément Hibert, Franck Bourrier, and Jean-Philippe Malet
Earth Surf. Dynam., 10, 1141–1164, https://doi.org/10.5194/esurf-10-1141-2022, https://doi.org/10.5194/esurf-10-1141-2022, 2022
Short summary
Short summary
Rockfall simulations are often performed to make sure infrastructure is safe. For that purpose, rockfall trajectory data are needed to calibrate the simulation models. In this paper, an affordable, flexible, and efficient trajectory reconstruction method is proposed. The method is tested by reconstructing trajectories from a full-scale rockfall experiment involving 2670 kg rocks and a flexible barrier. The results highlight improvements in precision and accuracy of the proposed method.
John Sykes, Pascal Haegeli, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 22, 3247–3270, https://doi.org/10.5194/nhess-22-3247-2022, https://doi.org/10.5194/nhess-22-3247-2022, 2022
Short summary
Short summary
Automated snow avalanche terrain mapping provides an efficient method for large-scale assessment of avalanche hazards, which informs risk management decisions for transportation and recreation. This research reduces the cost of developing avalanche terrain maps by using satellite imagery and open-source software as well as improving performance in forested terrain. The research relies on local expertise to evaluate accuracy, so the methods are broadly applicable in mountainous regions worldwide.
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
Short summary
Short summary
Knowing where avalanches occur is very important information for several disciplines, for example avalanche warning, hazard zonation and risk management. Satellite imagery can provide such data systematically over large regions. In our work we propose a machine learning model to automate the time-consuming manual mapping. Additionally, we investigate expert agreement for manual avalanche mapping, showing that our network is equally as good as the experts in identifying avalanches.
Aubrey Miller, Pascal Sirguey, Simon Morris, Perry Bartelt, Nicolas Cullen, Todd Redpath, Kevin Thompson, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 22, 2673–2701, https://doi.org/10.5194/nhess-22-2673-2022, https://doi.org/10.5194/nhess-22-2673-2022, 2022
Short summary
Short summary
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
Nat. Hazards Earth Syst. Sci., 22, 2433–2443, https://doi.org/10.5194/nhess-22-2433-2022, https://doi.org/10.5194/nhess-22-2433-2022, 2022
Short summary
Short summary
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.
Moritz Buchmann, John Coll, Johannes Aschauer, Michael Begert, Stefan Brönnimann, Barbara Chimani, Gernot Resch, Wolfgang Schöner, and Christoph Marty
The Cryosphere, 16, 2147–2161, https://doi.org/10.5194/tc-16-2147-2022, https://doi.org/10.5194/tc-16-2147-2022, 2022
Short summary
Short summary
Knowledge about inhomogeneities in a data set is important for any subsequent climatological analysis. We ran three well-established homogenization methods and compared the identified break points. By only treating breaks as valid when detected by at least two out of three methods, we enhanced the robustness of our results. We found 45 breaks within 42 of 184 investigated series; of these 70 % could be explained by events recorded in the station history.
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
Short summary
Short summary
To mark the 20th anniversary of Natural Hazards and Earth System Sciences (NHESS), an interdisciplinary and international journal dedicated to the public discussion and open-access publication of high-quality studies and original research on natural hazards and their consequences, we highlight 11 key publications covering major subject areas of NHESS that stood out within the past 20 years.
Achille Capelli, Franziska Koch, Patrick Henkel, Markus Lamm, Florian Appel, Christoph Marty, and Jürg Schweizer
The Cryosphere, 16, 505–531, https://doi.org/10.5194/tc-16-505-2022, https://doi.org/10.5194/tc-16-505-2022, 2022
Short summary
Short summary
Snow occurrence, snow amount, snow density and liquid water content (LWC) can vary considerably with climatic conditions and elevation. We show that low-cost Global Navigation Satellite System (GNSS) sensors as GPS can be used for reliably measuring the amount of water stored in the snowpack or snow water equivalent (SWE), snow depth and the LWC under a broad range of climatic conditions met at different elevations in the Swiss Alps.
Johannes Aschauer and Christoph Marty
Geosci. Instrum. Method. Data Syst., 10, 297–312, https://doi.org/10.5194/gi-10-297-2021, https://doi.org/10.5194/gi-10-297-2021, 2021
Short summary
Short summary
Methods for reconstruction of winter long data gaps in snow depth time series are compared. The methods use snow depth data from neighboring stations or calculate snow depth from temperature and precipitation data. All methods except one are able to reproduce the average snow depth and maximum snow depth in a winter reasonably well. For reconstructing the number of snow days with snow depth ≥ 1 cm, results suggest using a snow model instead of relying on data from neighboring stations.
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
Short summary
Short summary
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.
Moritz Buchmann, Michael Begert, Stefan Brönnimann, and Christoph Marty
The Cryosphere, 15, 4625–4636, https://doi.org/10.5194/tc-15-4625-2021, https://doi.org/10.5194/tc-15-4625-2021, 2021
Short summary
Short summary
We investigated the impacts of local-scale variations by analysing snow climate indicators derived from parallel snow measurements. We found the largest relative inter-pair differences for all indicators in spring and the smallest in winter. The findings serve as an important basis for our understanding of uncertainties of commonly used snow indicators and provide, in combination with break-detection methods, the groundwork in view of any homogenization efforts regarding snow time series.
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
Short summary
Short summary
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.
Cited articles
Aydin, A. and Eker, R.: GIS-Based snow avalanche hazard mapping:
Bayburt-AşağıDere catchment case, J. Environ.
Biol., 38, 937-943, https://doi.org/10.22438/jeb/38/5(SI)/GM-10, 2017.
Aydin, A., Eker, R., and Odabasi, Y. B.: Generating Avalanche Hazard
Indication Map and Determining Snow Avalanche Protection Forests in
Caykara-Trabzon (NE-Turkey), Forestist, 72, 62–72, https://doi.org/10.5152/forestist.2021.20060, 2021.
BAFU: SilvaProtect-CH: Prozessmodellierung, Federal Office for the
Environment FOEN, Bern, 74 pp., https://www.bafu.admin.ch/dam/bafu/de/dokumente/naturgefahren/fachinfo-daten/silvaprotect-ch_prozessmodellierung.pdf.download.pdf/silvaprotect-ch_prozessmodellierung.pdf (last access: 24 May 2022), 2013.
Barbolini, M. and Keylock, C. J.: A new method for avalanche hazard mapping using a combination of statistical and deterministic models, Nat. Hazards Earth Syst. Sci., 2, 239–245, https://doi.org/10.5194/nhess-2-239-2002, 2002.
Barbolini, M., Pagliardi, M., Ferro, F., and Corradeghini, P.: Avalanche
hazard mapping over large undocumented areas, Nat. Hazards, 56, 451–464, https://doi.org/10.1007/s11069-009-9434-8, 2011.
Bartelt, P., Bühler, Y., Buser, O., Christen, M., and Meier, L.:
Modeling mass-dependent flow regime transitions to predict the stopping and
depositional behavior of snow avalanches, J. Geophys. Res.,
117, F01015, https://doi.org/10.1029/2010JF001957, 2012.
Bartelt, P., Vera Valero, C., Feistl, T., Christen, M., Bühler, Y., and
Buser, O.: Modelling cohesion in snow avalanche flow, J. Glaciol.,
61, 837–850, https://doi.org/10.3189/2015JoG14J126, 2015.
Bebi, P., Kienast, F., and Schönenberger, W.: Assessing structures in
mountain forests as a basis for investigating the forests' dynamics and
protective function, Forest Ecol. Manag., 145, 3–14,
https://doi.org/10.1016/S0378-1127(00)00570-3, 2001.
Bebi, P., Kulakowski, D., and Rixen, C.: Snow avalanche disturbances in
forest ecosystems – State of research and implications for management,
Forest Ecol. Manag., 257, 1883–1892, https://doi.org/10.1016/j.foreco.2009.01.050,
2009.
Bebi, P., Bast, A., Helzel, K., Schmucki, G., Brozova, N., and Bühler,
Y.: Avalanche Protection Forest: From Process Knowledge to Interactive Maps,
in: Protective forests as Ecosystem-based solution for Disaster Risk
Reduction, edited by:
Teich, M., Accastello, C., Perzl, F., and Kleemayr, K., IntechOpen, London, United Kingdom, https://doi.org/10.5772/intechopen.99514, 2021.
Brožová, N., Baggio, T., D'Agostino, V., Bühler, Y., and Bebi, P.: Multiscale analysis of surface roughness for the improvement of natural hazard modelling, Nat. Hazards Earth Syst. Sci., 21, 3539–3562, https://doi.org/10.5194/nhess-21-3539-2021, 2021.
Bründl, M. and Margreth, S.: Integrative Risk Management: The Example of
Snow Avalanches, in: Snow and Ice-Related Hazards, Risks, and Disasters,
edited by: Häberli, W., and Whiteman, C., Elsevier, 259–296, https://doi.org/10.1016/C2018-0-00970-6, 2021.
Bründl, M., Hafner, E., Bebi, P., Bühler, Y., Margreth, S., Marty, C., Schaer, M., Stoffel, L., Techel, F., Winkler, K., Zweifel, B., and Schweizer, J.: Ereignisanalyse Lawinensituation im Januar 2018, WSL Berichte, Vol. 76, Birmensdorf: Eidg. Forschungsanstalt für Wald, Schnee und Landschaft WSL,
https://www.dora.lib4ri.ch/wsl/islandora/object/wsl:19842 (last access: 24 May 2022), 2019.
Bühler, Y., Kumar, S., Veitinger, J., Christen, M., Stoffel, A., and Snehmani: Automated identification of potential snow avalanche release areas based on digital elevation models, Nat. Hazards Earth Syst. Sci., 13, 1321–1335, https://doi.org/10.5194/nhess-13-1321-2013, 2013.
Bühler, Y., Marty, M., Egli, L., Veitinger, J., Jonas, T., Thee, P., and Ginzler, C.: Snow depth mapping in high-alpine catchments using digital photogrammetry, The Cryosphere, 9, 229–243, https://doi.org/10.5194/tc-9-229-2015, 2015.
Bühler, Y., von Rickenbach, D., Stoffel, A., Margreth, S., Stoffel, L., and Christen, M.: Automated snow avalanche release area delineation – validation of existing algorithms and proposition of a new object-based approach for large-scale hazard indication mapping, Nat. Hazards Earth Syst. Sci., 18, 3235–3251, https://doi.org/10.5194/nhess-18-3235-2018, 2018a.
Bühler, Y., von Rickenbach, D., Christen, M., Margreth, S., Stoffel, L.,
Stoffel, A., and Kühne, R.: Linking modelled potential release areas
with avalanche dynamic simulations: An automated approach for efficient
avalanche hazard indication mapping, International Snow Science Workshop
ISSW, Innsbruck, Austria, https://arc.lib.montana.edu/snow-science/item/2653 (last access: 24 May 2022), 2018b.
Bühler, Y., Hafner, E. D., Zweifel, B., Zesiger, M., and Heisig, H.: Where are the avalanches? Rapid SPOT6 satellite data acquisition to map an extreme avalanche period over the Swiss Alps, The Cryosphere, 13, 3225–3238, https://doi.org/10.5194/tc-13-3225-2019, 2019.
Bühler, Y., Hafner, E., and Techel, F.: Mapping avalanches with
satellites – the vision of more complete avalanche datasets, 2021 IEEE
Int. Geosci. Remote Se., 11–16 July
2021, 232–235, https://doi.org/10.1109/IGARSS47720.2021.9553577, 2021.
Bühler, Y., Bebi, P., and
Christen, M.: Large Scale Hazard Indication Simulations for avalanches,
canton of Grisons, Envidat [data set], https://doi.org/10.16904/envidat.316, 2022.
Bührle, L. J., Marty, M., Eberhard, L. A., Stoffel, A., Hafner, E. D., and Bühler, Y.: Spatially continuous snow depth mapping by airplane photogrammetry for annual peak of winter from 2017 to 2021, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2022-65, in review, 2022.
Buser, O. and Bartelt, P.: An energy-based method to calculate streamwise
density variations in snow avalanches, J. Glaciol., 61, 563–575, https://doi.org/10.3189/2015JoG14J054, 2015.
Choubin, B., Borji, M., Mosavi, A., Sajedi-Hosseini, F., Singh, V. P., and
Shamshirband, S.: Snow avalanche hazard prediction using machine learning
methods, J. Hydrol., 577, 123929, https://doi.org/10.1016/j.jhydrol.2019.123929, 2019.
Christen, M., Bartelt, P., and Kowalski, J.: Back calculation of the In den
Arelen avalanche with RAMMS: Interpretation of model results, Ann.
Glaciol., 51, 161–168, 2010a.
Christen, M., Kowalski, J., and Bartelt, P.: RAMMS: Numerical simulation of
dense snow avalanches in three-dimensional terrain, Cold Reg. Sci.
Technol., 63, 1–14, https://doi.org/10.1016/j.coldregions.2010.04.005, 2010b.
Deschamps-Berger, C., Gascoin, S., Berthier, E., Deems, J., Gutmann, E., Dehecq, A., Shean, D., and Dumont, M.: Snow depth mapping from stereo satellite imagery in mountainous terrain: evaluation using airborne laser-scanning data, The Cryosphere, 14, 2925–2940, https://doi.org/10.5194/tc-14-2925-2020, 2020.
Eberhard, L. A., Sirguey, P., Miller, A., Marty, M., Schindler, K., Stoffel, A., and Bühler, Y.: Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping, The Cryosphere, 15, 69–94, https://doi.org/10.5194/tc-15-69-2021, 2021.
Ghinoi, A. and Chung, C. J.: STARTER: A statistical GIS-based model for the
prediction of snow avalanche susceptibility using terrain features –
application to Alta Val Badia, Italian Dolomites, Geomorphology, 66,
305–325, 2005.
Gruber, U. and Baltensweiler, A.: SilvaProtect-CH, Eidg. Forschungsanstalt
WSL, Birmensdorf, Schweiz, 40, 2004.
Gruber, U. and Bartelt, P.: Snow avalanche hazard modelling of large areas
using shallow water numerical methods and GIS, Environ. Modell.
Softw., 22, 1472–1481, https://doi.org/10.1016/j.envsoft.2007.01.001, 2007.
Hafner, E. D., Techel, F., Leinss, S., and Bühler, Y.: Mapping avalanches with satellites – evaluation of performance and completeness, The Cryosphere, 15, 983–1004, https://doi.org/10.5194/tc-15-983-2021, 2021.
Hafner, E. D., Barton, P., Daudt, R. C., Wegner, J. D., Schindler, K., and Bühler, Y.: Automated avalanche mapping from SPOT 6/7 satellite imagery: results, evaluation, potential and limitations, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2022-80, in review, 2022.
Harvey, S., Schmudlach, G., Bühler, Y., Dürr, L., Stoffel, A., and
Christen, C.: Avalanche terrain maps for backcountry skiing in switzerland,
International Snow Science Workshop ISSW, Innsbruck, Austria, https://arc.lib.montana.edu/snow-science/item/2833 (last access: 24 May 2022), 2018.
Horton, P., Jaboyedoff, M., Rudaz, B., and Zimmermann, M.: Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale, Nat. Hazards Earth Syst. Sci., 13, 869–885, https://doi.org/10.5194/nhess-13-869-2013, 2013.
Issler, D.: Approaches to Including Climate and Forest Effects in Avalanche
Hazard Indication Maps in Norway, https://www.nve.no/media/10589/20150457-10-tn.pdf (last access: 24 May 2022), 2020.
Larsen, H. T., Hendrikx, J., Slåtten, M. S., and Engeset, R. V.:
Developing nationwide avalanche terrain maps for Norway, Nat. Hazards, 103, 2829–2847, https://doi.org/10.1007/s11069-020-04104-7, 2020.
Leinss, S., Wicki, R., Holenstein, S., Baffelli, S., and Bühler, Y.: Snow avalanche detection and mapping in multitemporal and multiorbital radar images from TerraSAR-X and Sentinel-1, Nat. Hazards Earth Syst. Sci., 20, 1783–1803, https://doi.org/10.5194/nhess-20-1783-2020, 2020.
Maggioni, M. and Gruber, U.: The influence of topographic parameters on
avalanche release dimension and frequency, Cold Reg. Sci.
Technol., 37, 407–419, https://doi.org/10.1016/S0165-232X(03)00080-6, 2003.
Maggioni, M., Bovet, E., Freppaz, M., Segor, V., and Bühler, Y.:
Potential of automated avalanche dynamic simulations for large scale hazard
indication mapping in italy: a first test appli-cation in aosta valley,
International Snow Science Workshop ISSW, Innsbruck, Austria, https://arc.lib.montana.edu/snow-science/item/2637 (last access: 24 May 2022), 2018.
Margreth, S.: Lawinenverbau im Anbruchgebiet. Technische Richtlinie als
Vollzugshilfe, Eidgenössisches Institut für Schnee- und
Lawinenforschung SLF, Bern, 101, https://www.bafu.admin.ch/bafu/de/home/themen/naturgefahren/publikationen-studien/publikationen/lawinenverbau-im-anbruchgebiet.html
(last access: 24 May 2022),
2007.
Margreth, S.: Lawinengefahrenkarten in der Schweiz [Avalanche hazard maps in
Switzerland], Wildbach- und Lawinenverbau, 83, 80–92, 2019.
Margreth, S. and Romang, H.: Effectiveness of mitigation measures against
natural hazards, Cold Reg. Sci. Technol., 64, 199–207, 2010.
Marti, R., Gascoin, S., Berthier, E., de Pinel, M., Houet, T., and Laffly, D.: Mapping snow depth in open alpine terrain from stereo satellite imagery, The Cryosphere, 10, 1361–1380, https://doi.org/10.5194/tc-10-1361-2016, 2016.
McClung, D. M. and Mears, A. I.: Extreme value prediction of snow avalanche
runout, Cold Reg. Sci. Technol., 19, 163–175, 1991.
Meyer, J. and Skiles, S. M.: Assessing the Ability of Structure From Motion
to Map High-Resolution Snow Surface Elevations in Complex Terrain: A Case
Study From Senator Beck Basin, CO, Water Resour. Res., 55, 6596–6605, https://doi.org/10.1029/2018wr024518, 2019.
Monti, F., Alberti, R., Comin, P., Wolynski, A., and Bühler, Y.:
Automated identification of forest with protective function against snow
avalanches in the Trento Province (Italy), International Snow Science
Workshop ISSW, Innsbruck, Austria, https://arc.lib.montana.edu/snow-science/item/2636
(last access: 24 May 2022), 2018.
Ortner, G., Bründl, M., Kropf, C. M., Röösli, T., Bühler, Y., and Bresch, D. N.: Large-scale risk assessment on snow avalanche hazard in alpine regions, Nat. Hazards Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/nhess-2022-112, in review, 2022.
Rudolf-Miklau, F., Sauermoser, S., and Mears, A., Rudolf-Miklau, F.,
Sauermoser, S., and Mears, A. (Eds.): The Technical Avalanche Protection
Handbook, Wiley-VCH, Berlin, Germany, 430 pp., https://doi.org/10.1002/9783433603840.ch01,
2014.
Salm, B., Burkhard, A., and Gubler, H. U.: Berechnung von Fliesslawinen.
Eine Anleitung für den Praktiker mit Beispielen, Eidgenössisches
Institut für Schnee- und Lawinenforschung SLF, Davos, 1990.
Sappington, J. M., Longshore, K. M., and Thompson, D. B.: Quantifying
landscape ruggedness for animal habitat analysis: A case study using bighorn
sheep in the Mojave Desert, J. Wildlife Manage., 71, 1419–1426, https://doi.org/10.2193/2005-723, 2007.
Schaer, M.: Avalanche activity during major avalanche events, a case study
for hydroelectric reservoirs, Les rapports de la recherche scientifique à
la sécurité neige, glace et avalanche, Chamonix, FR1995, 1995.
Schneebeli, M. and Meyer-Grass, M.: Avalanche starting zones below the
timber line – Structure of forest., International Snow Science Workshop
ISSW, Breckenridge, Colorado, USA, https://arc.lib.montana.edu/snow-science/item/1250
(last access: 24 May 2022), 1993.
Schweizer, J., Mitterer, C., Techel, F., Stoffel, A., and Reuter, B.: On the relation between avalanche occurrence and avalanche danger level, The Cryosphere, 14, 737–750, https://doi.org/10.5194/tc-14-737-2020, 2020.
SLF, Ammann, W., and Bründl, M. (Eds.): Der Lawinenwinter 1999 –
Ereignisanalyse, Eidgenössisches Institut für Schnee- und
Lawinenforschung, Davos, 588 pp., https://www.dora.lib4ri.ch/wsl/islandora/object/wsl:17698
(last access: 24 May 2022), 2000.
Soteres, R. L., Pedraza, J., and Carrasco, R. M.: Snow avalanche
susceptibility of the Circo de Gredos (Iberian Central System, Spain),
J. Maps, 16, 155–165, https://doi.org/10.1080/17445647.2020.1717655, 2020.
Stritih, A., Bebi, P., Rossi, C., and Grêt-Regamey, A.: Addressing
disturbance risk to mountain forest ecosystem services, J.
Environ. Manage., 296, 113188, https://doi.org/10.1016/j.jenvman.2021.113188, 2021.
swisstopo: swissALTI3D – Das hoch aufgelöste Terrainmodell der Schweiz, Swiss Federal Office of Topography swisstopo,
Berne, Switzerland, 27, https://www.swisstopo.admin.ch/en/geodata/height/alti3d.html
(last access: 24 May 2022), 2018.
Sykes, J., Haegeli, P., and Bühler, Y.: Automated snow avalanche release area delineation in data sparse, remote, and forested regions, Nat. Hazards Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/nhess-2021-330, in review, 2021.
Teich, M., Bartelt, P., Grět-Regamey, A., and Bebi, P.: Snow avalanches
in forested terrain: Influence of forest parameters, topography, and
avalanche characteristics on runout distance, Arct. Antarct. Alp. Res., 44, 509–519, https://doi.org/10.1657/1938-4246-44.4.509, 2012.
Volk, G. and Kleemayr, K.: ELBA – Ein GIS-gekoppeltes
Lawinensimulationsmodell Anwendungen und Perspektiven, VGI –
Österreichische Zeitschrift für Vermessung und Geoinformation, 87,
84–92, 1999.
Walter, F., Amann, F., Kos, A., Kenner, R., Phillips, M., de Preux, A.,
Huss, M., Tognacca, C., Clinton, J., Diehl, T., and Bonanomi, Y.: Direct
observations of a three million cubic meter rock-slope collapse with almost
immediate initiation of ensuing debris flows, Geomorphology, 351, 106933, https://doi.org/10.1016/j.geomorph.2019.106933, 2020.
Weber, D., Rüetschi, M., Small, D., and Ginzler, C.: Grossflächige
Klassifikation von Gebüschwald mit Fernerkundungsdaten, Schweizerische
Zeitschrift fur Forstwesen, 171, 51–59, https://doi.org/10.3188/szf.2020.0051, 2020.
Zweifel, B., Lucas, C., Hafner, E., Techel, F., Marty, C., and Stucki, T.:
Schnee und Lawinen in den Schweizer Alpen. Hydrologisches Jahr 2018/19,
WSL-Institut für Schnee- und Lawinenforschung SLF; Eidg.
Forschungsanstalt für Wald, Schnee und Landschaft WSL, Davos,
Birmensdorf, 134, https://www.wsl.ch/de/publikationen/default-34cd5573e3.html
(last access: 24 May 2022), 2019.
Short summary
To calculate and visualize the potential avalanche hazard, we develop a method that automatically and efficiently pinpoints avalanche starting zones and simulate their runout for the entire canton of Grisons. The maps produced in this way highlight areas that could be endangered by avalanches and are extremely useful in multiple applications for the cantonal authorities, including the planning of new infrastructure, making alpine regions more safe.
To calculate and visualize the potential avalanche hazard, we develop a method that...
Altmetrics
Final-revised paper
Preprint