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Spatial Snow Cover Processes at Kühtai and Reynolds Creek

In many climates, predicting and understanding the spatio-temporal variability of snow-related quantities plays a key role in catchment hydrology. Practical applications include the prediction of snowmelt induced floods and the estimation of water yield from snow-covered catchments for water resources management. The snow cover is also a key link in the climate system via its effect on the surface energy and water balance, so its accurate representation is essential to a better understanding of climate effects on the hydrological cycle. Modelling the spatio-temporal variability of snow-related quantities is complicated by the interrelated and multiscale nature of the processes involved. Natural snow variability is extreme and although snow related data such as snow water equivalent is often available in considerable temporal detail as time series (e.g. the US SNOTEL network, NRCS, 1998), the spatial resolution of snow-related data is notoriously poor. Often, at best, a few point measurements are available in the catchment of interest and, because of the extreme spatial variability, point data are not very representative of the spatial patterns and/or the spatial averages. Although runoff does provide a spatially aggregated estimate of melt water yield from a catchment, it is not possible to infer the actual melt processes and their spatial distribution from runoff data alone. Recently, progress in remote sensing of snow has shown potential. Snow-covered area can be measured using a variety of methods. However, remote sensing of snow water equivalent has not been sufficiently developed for operational observation of deep snowcover in rugged mountain terrain (Elder et al., 1998). Therefore it has been suggested in the literature (e.g., Bloschl et al., 1991b) to use snow cover patterns for evaluating and improving distributed snow models. This is consistent with the general thrust of this book of using observed patterns for assessing distributed models. As compared to other components of the hydrologic cycle described in this book such as rainfall, runoff and soil moisture, snow has the definite advantage that