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.

We present the first extended intercomparison of snow avalanche flow simulation tools. In this pilot-study, simulation results of mainly thickness/depth-integrated shallow flow models are compared for three simple test cases representative of standard applications. This analysis serves as a first quantitative assessment of the uncertainty introduced by the different implementation workflows (e.g., numerical schemes, ad-hoc treatments, geo-data handling, curvature treatment, etc.).

Matter is a new computer model that simulates granular media like sand, snow, and soil. These materials can behave like both solids and fluids, making their modeling difficult. Matter addresses this with a unified framework, using a numerical solver called MPM. Able to capture cohesion, density variations and complex terrains, it's particularly relevant for snow avalanches or landslides. Matter runs efficiently on standard computers, making advanced simulations more accessible.

Advanced 3D numerical models can simulate alpine mass movements at the slope scale, but their use in natural hazard mapping remains challenging. We present a tool that converts 3D simulation results into 2D maps, making them more accessible and useful for hazard assessment and mitigation. Applied to an ice avalanche simulated with the Material Point Method, it reveals key features such as slope-normal velocities and flow detachment from terrain, which are often overlooked in simpler models.

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.