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A model is put forward which focuses on the dynamical evolution of the spatial distribution of snow water equivalent (SWE). We make use of the fact that when the accumulation and ablation process of the snow reservoir is modelled as a summation of a gamma-distributed variable, both skewed distributions, typical of alpine areas, and more normal distributions, typical of forested areas, can be accounted for. A particular problem is to represent fractional snow-covered area (SCA) within the distribution framework. The change in SCA as a response to a melting event is explicitly linked to the shape of the distribution of SWE and is estimated as the probability of non-exceedance of the melted amount from a scaled version of the spatial distribution of SWE. An extensive snow-measuring programme, where several snow courses have been measured repeatedly throughout the melting season, justifies the dynamical aspects of the snow distribution in the modelling approach. The modelling approach has been tested with the Swedish rainfall–runoff model, HBV, and estimated values of SWE and SCA are compared with results obtained using the statistical distribution (log-normal) traditionally used in the model.
Snow-courses data have been collected in order to investigate the temporal variability of snow distribution in two catchments in southern Norway during the 2002 melt season. The profiles represent different elevations, aspects and terrain types. At snow maximum the spatial distribution of snow above the tree line was positively skewed (long tail in the positive direction), whereas the spatial distribution below the tree line followed a more normal distribution. During the snowmelt season the spatial distribution of snow became increasingly skewed. By separating the datasets into two terrain classes, alpine and forest, the snow distribution could be described by a time-variant gamma distribution function, one for each terrain class. The results of the study will be used to formulate a new snow routine in the Swedish rainfall–runoff model HBV, which is used for flood forecasting in Norway.
This study presents results from an Airborne Laser Scanning (ALS) mapping survey of snow depth on the mountain plateau Hardangervidda, Norway, in 2008 and 2009 at the approximate time of maximum snow accumulation during the winter. The spatial extent of the survey area is >240 km2. Large variability is found for snow depth at a local scale (2 m2), and similar spatial patterns in accumulation are found between 2008 and 2009. The local snow-depth measurements were aggregated by averaging to produce new datasets at 10, 50, 100, 250 and 500 m2 and 1 km2 resolution. The measured values at 1 km2 were compared with simulated snow depth from the seNorge snow model (www.senorge.no), which is run on a 1 km2 grid resolution. Results show that the spatial variability decreases as the scale increases. At a scale of about 500 m2 to 1 km2 the variability of snow depth is somewhat larger than that modeled by seNorge. This analysis shows that (1) the regional-scale spatial pattern of snow distribution is well captured by the seNorge model and (2) relatively large differences in snow depth between the measured and modeled values are present.
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