Particle and front tracking in experimental and computational avalanche dynamics

Abstract. Understanding particle motion in snow avalanches is crucial for improving the representation of flow dynamics in numerical models. In this study, we develop and apply a general framework for testing and calibrating thickness-integrated flow models using in-flow sensor data from AvaNodes, radar measurements, and simulations with the com1DFA module of the open-source AvaFrame framework. This includes an implementation of particle tracking functionalities and focuses on assessing a modified Voellmy friction relation. Radar measurements of the avalanche front and three-dimensional AvaNode trajectories provide a comprehensive observational basis for model comparison. By minimizing the differences between measured and simulated velocities and front positions, we identify parameter sets that achieve high agreement with observed dynamics, yielding deviations below 5 %–10 % in maximum velocity and travel distance. However, the results reveal a trade-off between accurately reproducing particle vs. front behaviour, reflecting model limitations and the presence of equifinality in the parameter space. We also find that the simulated particle velocities are primarily controlled by initial position, contrasting with experimental observations that show more complex particle interactions. These findings underline the need for enhanced model formulations to better capture flow regime transitions and particle-scale effects. Our results highlight the potential of combining multiple measurement types for calibration and future improvements in avalanche modelling.