Probability indication maps for avalanche runout for decision support in daily traffic rout risk management
- 1WSL Institute for Snow and Avalanche Research SLF (Davos, Switzerland)
- 2Institute for Geotechnical Engineering (Zurich, Switzerland)
Abstract
In alpine regions, snow avalanches endanger infrastructure such as roads, ski slopes and buildings. While permanent protection measures minimize avalanche impact, local experts must implement additional safety measures such as road or ski slope closures during critical situations. To support this demanding decision-making process, we propose a framework that can be used on a daily basis to calculate avalanche probability indication maps of potential avalanche runout extents and intensities. The probability indication maps are generated by running multiple avalanche simulations, based on an ensemble of estimations of input parameters derived from weather station measurements and weather forecasts, to assess a range of possible scenarios, e.g. for fracture depth, maximum erosion depth and snow temperature. We aim to identify the minimum number of input parameters needed to meaningfully represent daily snowpack conditions. We focus on cold snow conditions that produce powder snow avalanches. To evaluate the quality of the proposed probability indication maps, we conduct a hindcast for four well-documented avalanche events around Davos, Switzerland, using meteorological station data from the day before the avalanches released, weather forecast and SNOWPACK simulations. For validation we compare the resulting predictions to the measured outlines of the avalanche cores. This study demonstrates how real-time weather and snowpack data can be utilized effectively to provide practitioners with an overview of the current avalanche situation to support their decision-making process. In the future, such approaches could be implemented into more data-based decision-making processes to better protect traffic infrastructure in high-risk avalanche hazard areas.
Versions
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BibTeX
@article{glaus2026probability,
title = {{Probability indication maps for avalanche runout for decision support in daily traffic rout risk management}},
author = {Julia Glaus and Jan Kleinn and Lukas Stoffel and Pia Ruttner and Katreen Wikstrom Jones and Johan Gaume and Yves Bühler},
journal = {The Cryosphere},
year = {2026},
month = oct,
doi = {10.5194/tc-20-6087-2026},
url = {https://doi.org/10.5194/tc-20-6087-2026},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Probability indication maps for avalanche runout for decision support in daily traffic rout risk management
AU - Julia Glaus
AU - Jan Kleinn
AU - Lukas Stoffel
AU - Pia Ruttner
AU - Katreen Wikstrom Jones
AU - Johan Gaume
AU - Yves Bühler
PY - 2026
DA - 2026/10/26
JO - The Cryosphere
DO - 10.5194/tc-20-6087-2026
UR - https://doi.org/10.5194/tc-20-6087-2026
AB - In alpine regions, snow avalanches endanger infrastructure such as roads, ski slopes and buildings. While permanent protection measures minimize avalanche impact, local experts must implement additional safety measures such as road or ski slope closures during critical situations. To support this demanding decision-making process, we propose a framework that can be used on a daily basis to calculate avalanche probability indication maps of potential avalanche runout extents and intensities. The probability indication maps are generated by running multiple avalanche simulations, based on an ensemble of estimations of input parameters derived from weather station measurements and weather forecasts, to assess a range of possible scenarios, e.g. for fracture depth, maximum erosion depth and snow temperature. We aim to identify the minimum number of input parameters needed to meaningfully represent daily snowpack conditions. We focus on cold snow conditions that produce powder snow avalanches. To evaluate the quality of the proposed probability indication maps, we conduct a hindcast for four well-documented avalanche events around Davos, Switzerland, using meteorological station data from the day before the avalanches released, weather forecast and SNOWPACK simulations. For validation we compare the resulting predictions to the measured outlines of the avalanche cores. This study demonstrates how real-time weather and snowpack data can be utilized effectively to provide practitioners with an overview of the current avalanche situation to support their decision-making process. In the future, such approaches could be implemented into more data-based decision-making processes to better protect traffic infrastructure in high-risk avalanche hazard areas.
SN - 1994-0424
SN - 1994-0416
ER -