Spatial variability of the snow depth on mountain slope in Svalbard

• Published in: Ice and Snow
• Main Authors: P. A. Chernous, N. I. Osokin, R. A. Chernov
• Format: Article in Journal/Newspaper
• Language: Russian
• Published: Nauka 2018
• Subjects: avalanches; monitoring; snow depth variability; snow stability evaluation; Science; Q; Svalbard; Khibiny
• Online Access: https://doi.org/10.15356/2076-6734-2018-3-353-358; https://doaj.org/article/924311acf3364d6a9f18a00a64678be8

The study was carried out to estimate the spatial variability of snow cover depths in avalanche centers of the mountain slopes of Svalbard. Accounting for the variability is necessary for monitoring the snow cover depths in the avalanche centers and evaluating the snow cover stability on the slope. The main tasks of the work were to evaluate the variability parameters and compare them with similar estimates obtained in other regions. In contrast to conventional snow surveys, thickness measurements were carried out more frequently (with resolution of every 1 m) in profiles (eight profiles in total), not exceeding the characteristic linear size of the avalanche origin zone (up to 100 m2). Spatial variations of snow cover thickness in each profile are considered as the realization of a random process. Data of the spring measurements of 2015 were used to estimate the mathematical expectations, variances, and autocorrelation functions of the snow cover depth on the Mount Olav slopes. Comparison of parameters of variability with those obtained in different mountain regions of Russia with the similar underlying surface, shows that the variability on Svalbard are the most similar to the variability in the Khibiny Mountains. Although the scattering and coefficients of variation obtained in the Khibiny Mountains are slightly larger, the spatial coherence of the snow cover depths is the lowest on Svalbard. Estimates of the correlation radii are within the range of 2–6 m. With such variability any deterministic estimation of spatial snow accumulation with the help of remote measurement stakes is impossible. The obtained parameters of the spatial statistical structure of the snow cover thickness allow using statistical modeling for the interpretation of point measurements. In that case, uncertainty of snow cover thickness data in places where measurements were not made will be reflected in their probabilistic estimation.