Item: Daily Avalanche Probability Indication Maps: First Operational Experience in Davos, Switzerland
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Title: Daily Avalanche Probability Indication Maps: First Operational Experience in Davos, Switzerland
Proceedings: Proceedings, International Snow Science Workshop, Whistler, BC, Canada, 2026
Authors:
- Julia Glaus [ WSL Institute for Snow and Avalanche Research SLF, Grisons, Switzerland ]
- Pia Ruttner [ WSL Institute for Snow and Avalanche Research SLF, Grisons, Switzerland ] [ Climate Change, Extremes, and Natural Hazards in Alpine Regions Research Centre CERC, Grisons, Switzerland ] [ Institute of Geodesy and Photogrammetry ETH Zurich, Zurich, Switzerland ]
- Lukas Stoffel [ WSL Institute for Snow and Avalanche Research SLF, Grisons, Switzerland ]
- Johan Gaume [ WSL Institute for Snow and Avalanche Research SLF, Grisons, Switzerland ] [ Climate Change, Extremes, and Natural Hazards in Alpine Regions Research Centre CERC, Grisons, Switzerland ] [ Institute for Geotechnical Engineering ETH Zurich, Zurich, Switzerland ]
- Yves Bühler [ WSL Institute for Snow and Avalanche Research SLF, Grisons, Switzerland ] [ Climate Change, Extremes, and Natural Hazards in Alpine Regions Research Centre CERC, Grisons, Switzerland ]
Date: 2026-09-28
Abstract: Avalanche risk management in ski resorts, along traffic routes, and for exposed buildings relies mainly on point-based measurements, field observations, avalanche cadastres, avalanche bulletins, and expert judgment, particularly during storms with limited visibility. At Brämabüel (Davos), three major avalanche paths threaten a cross-country ski track and the Dischma road, requiring timely operational decisions such as road closures or avalanche control, which could have considerable economic impact. During the 2025/26 winter season, we implemented and tested an operational workflow that generates daily, spatially explicit probability indication maps of avalanche runout for direct use by local experts. The approach relies on an avalanche dynamics model that simulates both snow entrainment and the powder cloud. The model is driven by snowpack simulations forced by meteorological station data, low-cost lidar sensor and camera imagery. By coupling dynamic avalanche modeling with measurement-based information on snow cover, the framework provides a practical tool for near-real-time hazard assessment. During a storm event from 16–22 February, a spontaneous avalanche released at night, significantly depleting the release area. A subsequent artificial release remained small. Such changes in snow depth, which strongly affect avalanche formation and release, are not captured by station-based modeling. The lidar information helps to interpret the probability indication maps of the following days or even provides the basis to update them. This case study demonstrates how integrating modeling and remote sensing improves situational awareness and supports more robust decision-making under challenging observational conditions such as snowfall. The approach adds a complementary perspective for practitioners and will be tested across larger regions and different climatic conditions, while its effective use depends on defining robust decision thresholds (e.g., for road closures) in close collaboration with practitioners.
Object ID: ISSW2026_O7.1.pdf
DOI: https://doi.org/10.15788/1790098644
Language of Article: English
Presenter(s): Julia Glaus
Keywords: Avalanche Dynamics, Road Safety, Forecasting, Probability, Hazard Assessment
Page Number(s): 276 - 282
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