Small Scale Spatial Variability of Snow Density and Depth over Complex Alpine Terrain: Implications for Estimating Snow Water Equivalent

18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 Snow density is a key property in monitoring the water content of snow-covered regions. However, sampling snow density is a difficult and time consuming task, which explains why few previous studies have analyzed the spatial variability of snow density. In this study we analyzed snow density measurements made in February and April of 2010 and 2011 in three 1–2 km areas within a valley of the central Spanish Pyrenees. Snow density was correlated with snow depth and terrain characteristics including elevation, potential incoming solar radiation, terrain curvature and slope angle. Regression models were used to predict the spatial variability of snow density, and to assess how the error in computed densities might influence estimates of snow water equivalent (SWE). The variability in snow depth was much greater than that of snow density. The average snow density was much greater in April than in February. However, the spatial variability of snow density was greater among sites in February than in April; in the latter month it varied less and was more consistent among sites and surveys. The correlations between snow depth and density were generally statistically significant but typically not very high, and their magnitudes and signs were highly variable among sites and surveys. The correlation with other topographic variables showed the same variability in magnitude and sign, and consequently the resulting regression models were very inconsistent, and in general explained little of the variance. Antecedent climatic and snow conditions prior to each survey help highlight the main causes of the contrasting relation shown between snow depth, density and terrain characteristics in the three analysed sites during the four surveys. However, as a consequence of the moderate spatial variability of snow density relative to snow depth, the absolute error in the SWE estimated from computed densities using the regression models was generally