Interannual and Seasonal Variability of Snow Depth Scaling Behavior in a Subalpine Catchment

Understanding and characterizing the spatial distribution of snow are critical to represent the energy balance and runoff production in mountain environments. In this study, we investigate the interannual and seasonal variability in snow depth scaling behavior at the Izas experimental catchment of the Spanish Pyrenees (2,000 to 2,300 m above sea level). We conduct variogram analyses of 24 snow depth maps derived from terrestrial light detection and ranging scans, acquired during six consecutive snow seasons (2011–2017) that span a range of hydroclimatic conditions. We complement our analyses with bare ground topography data and wind speed and direction measurements. Our results show temporal consistency in the spatial variability of snow depth, with short‐range fractal behavior and scale break lengths that are similar to the optimal search distance (25 m) previously reported for the topographic position index, a terrain‐based predictor of snow depth. Beyond the 25‐m scale break, there is little to no fractal structure. We report a long‐range scale break of the order of 185–300 m for most dates—aligned with the dominant wind direction—and patterns between anisotropies in scale break lengths of shallow snow cover and directional terrain scaling behavior. The temporal consistency of snow depth scaling patterns suggests that, in addition to guiding the spatial configuration of physically based models, fractal analysis could be used to inform the design of independent variables for statistical models used to predict snow depth and its variability. Key Points Consistent short‐range fractal behavior and scale breaks in snow depth were detected for six consecutive seasons in a subalpine catchment Scale break anisotropies in shallow snowpacks during melt periods can be explained by bare‐earth terrain scaling patterns Variogram analysis can inform statistical and dynamical model decisions to best simulate snow distribution