Model-based and satellite estimates of snow hydrology and carbon fluxes at high latitudes

This thesis is a study of how satellite data can be used to improve our understanding of the snow hydrology of boreal regions and its effects on their hydrological and carbon balance. The key parameter is the snow water equivalent (SWE). The thesis addresses two themes; (1) snow parameter retrieval from satellite data, and (2) the dependence on SWE of the hydrological and carbon balance of boreal regions. Using radiative transfer models, linked to a climate-driven snow model, it was found that the brightness temperature is most sensitive to the snow grain size, with SWE the second most significant parameter. Comparison of model predictions with SSMII satellite data showed a significant difference in spatial patterns in central Siberia. The most likely reasons are thought to be either an inaccurate estimate of snow grain size, or errors in the land cover description. For SWE or snow depth retrieval from passive microwave data to be successful, the evolution of the grain size needs to be better quantified. The combination of dynamic algorithm in early winter and static algorithm in middle to late winter produces the best overall results, particularly in Eurasia. The final part of the thesis uses a Dynamic Vegetation Model, SDGVM, to model the hydrological and carbon balance of the major boreal catchments, using a simple climate-driven model of SWE. It was found that there. was broad agreement in the annual water balance between the SDGVM and measured data of river discharge. There is a significant difference in seasonal timing due to the absence of some hydrological processes in SDGVM. Analysis of 21 SI century climate scenarios for the Ob basin indicates a slight reduction in annual runoff, but a significant increase in Net Biome Productivity.EThOS - Electronic Theses Online ServiceGBUnited Kingdo