Estimating Snow Water Equivalent in the Swedish Mountains based on the Frequency and Amplitude of the Local Topography
Ingvander, Susanne; Brown, Ian
INK, Stockholm University, SWEDEN
The municipalities situated in the Swedish mountain regions cover one third of the Swedish land areal. These regions are sparsely populated but are nationally important with their contribution to water reservoirs in hydro-power production where 40% of the power generation is from hydropower sources (2004). Understanding the contribution of snow accumulation in these areas is vital for estimating the contribution to the hydrological system during snow melt and possible spring floods. Further, winter recreation is an important employer in many northern communities, the understanding of snow cover stability and presence during the season is important and possible to monitor using remotely sensed data.
Field verification is significant part of the development of new or improved methodologies. A thorough investigation of reference areas in the mountain regions is important for understanding the snow accumulation patterns, the reproducibility of these patterns and their connection to metrological parameters and information in the landscape. By determining the frequency and amplitude of the topography in combination with measuring snow accumulation and density we can increase the accuracy of the estimation of spatial variability of SWE (Snow Water Equivalent) in the Swedish mountain regions. Understanding the distribution of snow depth at the sub meter scale using ground penetrating radar (GPR) is our basis for extrapolating the information to kilometre scale based on digital elevation models (DEMs) and weighted by the land cover in the area. By establishing the relationship between accumulation patterns and physical parameters in the landscape, and with reference to climate data from automatic weather station a model of accumulation patterns in different types of reference areas can be produced.
By upscaling the information from high resolution field data, the information can be used to derive new satellite algorithms. Snow cover mapping is developing towards operational service provision through programs such as ESA's GlobSnow. Thus there is a need for validation datasets and an exploration of new methods.