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.