Articles | Volume 17, issue 6
https://doi.org/10.5194/tc-17-2245-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-2245-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Jun 2023
Research article |
| 05 Jun 2023
| 05 Jun 2023
Combining modelled snowpack stability with machine learning to predict avalanche activity
Léo Viallon-Galinier
CORRESPONDING AUTHOR
Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM,Centre d’Études de la Neige, Grenoble, France
Univ. Grenoble Alpes, INRAE, CNRS, IRD, Grenoble INP, IGE, Grenoble, France
École des Ponts, Champs-sur-Marne, France
Pascal Hagenmuller
Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM,Centre d’Études de la Neige, Grenoble, France
Nicolas Eckert
Univ. Grenoble Alpes, INRAE, CNRS, IRD, Grenoble INP, IGE, Grenoble, France
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Cited
24 citations as recorded by crossref.
- Can model-based avalanche forecasts match the discriminatory skill of human danger-level forecasts? A comparison from Switzerland F. Techel et al.
- Machine learning for automated avalanche terrain exposure scale (ATES) classification K. Markov et al.
- Avalanche Hazard Prediction in East Kazakhstan Using Ensemble Machine Learning Algorithms Y. Fedkin et al.
- Thermo-hydro-mechanics of thawing permafrost: a phase-field framework with enriched modified Cam-Clay plasticity M. Kebria et al.
- Creating probability maps for avalanche hazardous areas reflecting snowpack uncertainty updates T. Tanabe et al.
- Probability models to convert snowpack stability into the number of dry-snow avalanches in North Japan Y. Katsuyama et al.
- Assessing the performance and explainability of an avalanche danger forecast model C. Pérez-Guillén et al.
- Climate change impacts on snow avalanche activity and related risks N. Eckert et al.
- From the Swiss Alps to the Pyrenees: Evaluating the transferability of machine learning models for avalanche forecasting C. Pérez-Guillén et al.
- Changing drivers of regional large magnitude avalanche frequency throughout Colorado, USA E. Peitzsch et al.
- Identification and correction of snow depth bias in ERA5 datasets over Central Europe using machine learning G. Stachura & Z. Ustrnul
- Coupling Different Machine Learning and Meta-Heuristic Optimization Techniques to Generate the Snow Avalanche Susceptibility Map in the French Alps E. Kayhan & Ö. Ekmekcioğlu
- Impact of climate change on snow avalanche activity in the Swiss Alps S. Mayer et al.
- Integrating snowpack mechanical properties into snow avalanche susceptibility mapping in continental dry–cold mountain regions H. Li et al.
- Can Sentinel-1 reliably provide regional-scale information on avalanche activity S. Kaushik et al.
- Predicting glacial lake outburst susceptibility on the southern Tibetan Plateau with historical events and machine learning methods H. Liu et al.
- Twenty first century snow cover prediction using deep learning and climate model data in the Teesta basin, eastern Himalaya A. Patel et al.
- A quantitative module of avalanche hazard – comparing forecaster assessments of storm and persistent slab avalanche problems with information derived from distributed snowpack simulations F. Herla et al.
- Assessing the predictive capability of several machine learning algorithms to forecast snow avalanches using numerical weather prediction model in eastern Canada F. Gauthier et al.
- Predicting avalanche danger in northern Norway using statistical models K. Eiselt & R. Graversen
- Spatial heterogeneity and temporal tendency of channeled snow avalanche activity retrieved from Landsat images in the maritime snow climate of the Parlung Tsangpo catchment, southeastern Tibet H. Wen et al.
- Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations S. Mayer et al.
- Machine learning of Antarctic firn density by combining radiometer and scatterometer remote-sensing data W. Li et al.
- Addressing class imbalance in avalanche forecasting M. Kala et al.
24 citations as recorded by crossref.
- Can model-based avalanche forecasts match the discriminatory skill of human danger-level forecasts? A comparison from Switzerland F. Techel et al.
- Machine learning for automated avalanche terrain exposure scale (ATES) classification K. Markov et al.
- Avalanche Hazard Prediction in East Kazakhstan Using Ensemble Machine Learning Algorithms Y. Fedkin et al.
- Thermo-hydro-mechanics of thawing permafrost: a phase-field framework with enriched modified Cam-Clay plasticity M. Kebria et al.
- Creating probability maps for avalanche hazardous areas reflecting snowpack uncertainty updates T. Tanabe et al.
- Probability models to convert snowpack stability into the number of dry-snow avalanches in North Japan Y. Katsuyama et al.
- Assessing the performance and explainability of an avalanche danger forecast model C. Pérez-Guillén et al.
- Climate change impacts on snow avalanche activity and related risks N. Eckert et al.
- From the Swiss Alps to the Pyrenees: Evaluating the transferability of machine learning models for avalanche forecasting C. Pérez-Guillén et al.
- Changing drivers of regional large magnitude avalanche frequency throughout Colorado, USA E. Peitzsch et al.
- Identification and correction of snow depth bias in ERA5 datasets over Central Europe using machine learning G. Stachura & Z. Ustrnul
- Coupling Different Machine Learning and Meta-Heuristic Optimization Techniques to Generate the Snow Avalanche Susceptibility Map in the French Alps E. Kayhan & Ö. Ekmekcioğlu
- Impact of climate change on snow avalanche activity in the Swiss Alps S. Mayer et al.
- Integrating snowpack mechanical properties into snow avalanche susceptibility mapping in continental dry–cold mountain regions H. Li et al.
- Can Sentinel-1 reliably provide regional-scale information on avalanche activity S. Kaushik et al.
- Predicting glacial lake outburst susceptibility on the southern Tibetan Plateau with historical events and machine learning methods H. Liu et al.
- Twenty first century snow cover prediction using deep learning and climate model data in the Teesta basin, eastern Himalaya A. Patel et al.
- A quantitative module of avalanche hazard – comparing forecaster assessments of storm and persistent slab avalanche problems with information derived from distributed snowpack simulations F. Herla et al.
- Assessing the predictive capability of several machine learning algorithms to forecast snow avalanches using numerical weather prediction model in eastern Canada F. Gauthier et al.
- Predicting avalanche danger in northern Norway using statistical models K. Eiselt & R. Graversen
- Spatial heterogeneity and temporal tendency of channeled snow avalanche activity retrieved from Landsat images in the maritime snow climate of the Parlung Tsangpo catchment, southeastern Tibet H. Wen et al.
- Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations S. Mayer et al.
- Machine learning of Antarctic firn density by combining radiometer and scatterometer remote-sensing data W. Li et al.
- Addressing class imbalance in avalanche forecasting M. Kala et al.
Saved (final revised paper)
Latest update: 16 May 2026
Short summary
Avalanches are a significant issue in mountain areas where they threaten recreationists and human infrastructure. Assessments of avalanche hazards and the related risks are therefore an important challenge for local authorities. Meteorological and snow cover simulations are thus important to support operational forecasting. In this study we combine it with mechanical analysis of snow profiles and find that observed avalanche data improve avalanche activity prediction through statistical methods.
Avalanches are a significant issue in mountain areas where they threaten recreationists and...
