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www.hydrol-earth-syst-sci-discuss.net/2/1185/2005/
doi:10.5194/hessd-2-1185-2005
© Author(s) 2005. This work is licensed
under a Creative Commons License.
A Bayesian spatial assimilation scheme for snow coverage observations in a gridded snow model
1SINTEF Energy Research, Sem Sælands vei 11, 7465 Trondheim, Norway
2Department of Mathematical Sciences, NTNU, 7491 Trondheim, Norway
3Department of Geosciences, University of Oslo. P.O. Box 1047 Blindern, 0316 Oslo, Norway
Abstract. A spatial probability distribution of the variables in a parametric snow depletion curve (SDC) is tailored to the assimilation of satellite snow cover data into a gridded hydrological model. The assimilation is based on Bayes' theorem, in which the proposed distribution represents the a priori information about the SDC variables. From the prior gridded maps of snow storage and accumulated melt depth, the elevation gradients and the degree-day factor are separated out, creating elevation-normalised surfaces of snow storage and degree-day sum. Because the small-scale variability linked to elevation is removed, these surfaces can be described by prior distribution models with a strong spatial dependency structure. This reduction of spatial uniqueness in the prior distribution greatly increases the informational value of the remotely sensed snow coverage data.
The assimilation is evaluated in a 2400 km2 mountainous region in central Norway (61° N, 9° E), based on two Landsat 7 ETM+ images evaluated at 1 km2 scale. An image acquired on 11 May, a week before the peak flood, removes 78% of the variance in the remaining snow storage. Even an image from 4 May, less than a week after the melt onset, reduces this variance by 53%. Including observed discharge in the updating information improves the 4 May results, but has weak effect on 11 May. Estimated elevation gradients are shown to be sensitive to informational deficits occurring at high altitude, where snowmelt has not yet started. Caution is therefore required when using early images.
Discussion Paper (PDF, 1525 KB) Interactive Discussion (Closed, 3 Comments) Final Revised Paper (HESS)
Citation: Kolberg, S., Rue, H., and Gottschalk, L.: A Bayesian spatial assimilation scheme for snow coverage observations in a gridded snow model, Hydrol. Earth Syst. Sci. Discuss., 2, 1185-1219, doi:10.5194/hessd-2-1185-2005, 2005. Bibtex EndNote Reference Manager XML
