Application of remote sensing data derived from NOAA-AVHRR images for spatial snow water equivalent modelling

Spatial snow water equivalent modelling in mesoscale catchments requires spatially distributed information. This can be provided by remote sensing data. On the one hand remote sensing data are applied as model input parameter fields. On the other hand they can be used as model validation data. Due to its several repetition rate per day and the spatial resolution of 1 km² the NOAA-AVHRR is the preferred satellite for those applications. In this approach the spatially distributed, physically based snow submodel ESCIMO (Energy Balance Snow Cover GIS Integrated Model) is presented that is integrated in the multiscale modelling shell PROMET. ESCIMO calculates hourly snow cover distribution and snowmelt runoff by an energy and mass balance assertion. The model applies remote sensing data as model input parameter fields. The spatial land use information is derived from a multitemporal spectral unmixing procedure of NOAA-AVHRR satellite data from the vegetation period 1995. The temporal distribution of the snow cover and snow water equivalent was modelled for the winter season of 1993/94 in the Weser catchment. The calculated snow water equivalent is verified with measurements of a German Weather Service station. The snow cover results are validated with the snow cover derived from a NOAA image from 14 February 1994