Natural Hazards and Earth System Sciences
Natural Hazards and Earth System Sciences
NHESS
Articles | Volume 25, issue 12
Articles | Volume 25, issue 12
https://doi.org/10.5194/nhess-25-5033-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-25-5033-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 25, issue 12
Research article
 | 
19 Dec 2025
Research article |  | 19 Dec 2025

Assessing the predictive capability of several machine learning algorithms to forecast snow avalanches using numerical weather prediction model in eastern Canada

Francis Gauthier, Jacob Laliberté, and Francis Meloche

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Short summary
This study uses 4 different machine learning (ML) methods to forecast snow avalanches in northern Gaspésie using Québec's Ministry of Transportation avalanche records, and meteorological data. Comparing unsupervised and expert-driven models, results show similar prediction accuracy. Logistic Regression and Random Forest models perform well in real-time forecasting over 24–48 h. Findings suggest ML can enhance avalanche hazard anticipation and support operational decision-making.
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