Snow distribution in a mountainous region. A remote sensing study

Typ: Rapport
Serie: Hydrologi 86
Författare: Josef Källgården


The spatial distribution of snow is of importance in several hydrological and climatological processes. Today, one of the main climatological issues is the fundamental question if there is a climate change ongoing and if so, what the effects are? Several projects aim to model the climate and different climate scenarios for the future. For these simulations the snowcover is of major importance because of its high albedo and thus its high ability to reflect incoming solar radiation. A model that considers the spatial distribution of snow would be very useful when trying to simulate different climate change scenarios (Cline et al. 1998). Furthermore, a spatially distributed model would enable the use of spatially distributed input data, e.g. from satellite images. Runoff forecasts would be improved if models were updated in real-time, from e.g. satellite images (Kirschbaum 1998). Improving the forecasts is a major issue for e.g. the hydro-power companies for security and economical reasons.

Also within other sciences, a spatially distributed snowmelt model would be useful. Better spatial estimate of snowmelt would be helpful for forest harvesting, since the surface runoff may cause loss of nutrients (Ohta 1994). Furthermore, the distribution of snow in arctic tundra regions is of high importance for the survival of different plant and animal communities (Liston & Sturm 1998).

High-resolution satellite imagery is a useful tool for studying the snow distribution over large areas. According to Elder et al. (1991) a digital elevation model combined with a GIS (Geographical Information System) is an ideal tool for obtaining spatial topographic information about an area. Furthermore, remote sensing data and GIS are, according to Baumgartner & Apfl (1997), fundamental parts of several hydrological applications and they should more often be used by hydrologists. Especially information about snowcover has been obtained by various remote sensing techniques, see for instance Brandt & Bergström (1984), Sand & Bruland (1998), Rango & Martinec (1997) and Kuittinen (1989). In particular the satellite images have been widely used for obtaining information about snow distribution (Rango 1993). Furthermore, Cline et al. (1998) have concluded that remote sensing in combination with modelling could be used for water supply forecasting.