Influence of slab depth spatial variability on skier-triggering probability and avalanche size

Abstract

: The spatial variability of snowpack properties can create uncertainty when assessing avalanche hazards. We suggest a combined mechanical-statistical approach to investigate how changes in slab depth can influence the probability of a skier triggering an avalanche and the potential size of the release. We begin by creating multiple slab depth maps on a fictional slope using Gaussian Random Fields (GRF) with a particular set of mean, variance and correlation length. For each slab depth maps, we calculate the Skier Propagation Index SPI. We ran simulations of multiple skier tracks and calculated the probability based on the number of skiers who encountered a zone of SPI below 1. We used a Depth-Averaged Material Point Method to evaluate the potential size of an avalanche for a given slab depth variation. This analysis has revealed that a large correlation length and small variance lead to a lower probability of skier-triggered avalanches. Additionally, skiing style and skier group size have been shown to have an effect on the probability of skier-triggering. Furthermore, spatial variability can influence the size of an avalanche by introducing stress fluctuations that can cause early or late tensile failure. We illustrate the well-established relationship in avalanche forecasting be-tween the likelihood and the consequence of an avalanche.