Understanding Snow Deposition Patterns Leading to Natural Avalanche Formation in Heterogenous Mountain Terrain

Snow depth is difficult to assess due to its variability across different spatial and temporal scales, which is especially challenging in mountainous regions around the world. Despite these difficulties, understanding of the fine-scale distribution of seasonal snow is essential in avalanche risk assessment for professionals and recreationalists. This research explores the spatial and temporal variability of snow depth in a steep mountain couloir over the course of a winter and examines the influence of individual storm on avalanche formation. Our project used Uncrewed Aerial Systems (UASs) and Structure-from-Motion (SfM) photogrammetry to observe snow depth distributions at sub-decimeter spatial resolutions at a site in the Bridger Mountains of southwest Montana. We analyzed the observed snow depth distributions and quantified the spatial and temporal variability of snow deposition patterns at our study site. We then compared those results with in-situ observed snow pit profiles, meteorological data from adjacent automated weather stations and a large natural avalanche event at our site. We found that snow depths were correlated over smaller distances (15 m) and sampling resolutions greater than 0.5 m were inadequate for capturing patterns of spatial variability in the steep heterogenous terrain of our study site. We also found the spatial variability of snow depth generally decreases as snow depths increase throughout the season, presumably because the snow fills in some of the existing surface roughness of the snow-free terrain. Finally, our results suggest that wind was the dominant driver of individual storm influence on snow distribution and avalanche formation at our study site. Our efforts identify the spatial resolutions necessary for accurately sampling snow depth, thereby quantifying a primary driver of avalanche formation in complex mountain terrain.