Projections of climate induced changes in streamflow of 11 large-scale rivers located in five continents were modeled up to 2100 using meteorological projections simulated by five global circulation models (GCMs) for four climatic scenarios. Contribution of different sources of uncertainties into a total uncertainty of river runoff projections was analyzed. It was found that contribution of GCMs into the total uncertainty is, on the average, nearly twice larger than that of climatic scenarios.

It is shown that in agriculture technologies soil mulching with plant remains leads to increase in the ratio of actual transpiration to potential one and to increase in the yield of crops. Soil mulching with plant remains in combination with subsurface cultivation is the most efficient agricultural mode for the regions of the steppe and forest-steppe zones of the East-European (Russian) plain. This technology is most promising for development of agriculture in these regions.

The land surface model SWAP was found to be robust and can be applied for climate change studies. The river runoff projections up to 2100 were calculated for two greenhouse gas emission scenarios: RCP8.5 and RCP4.5. Scatter among SWAP’s projections due to application of different post-processing techniques for correcting biases in meteorological forcing data did not exceed 8%, while differences between changes in runoff projected by two models are much larger.

Scenario projections of the dynamics of meteocharacteristics for basins of the Olenek and Indigirka rivers in the 21 century have been obtained for four global climate change scenarios. The projections have been used to calculate scenarios of possible changes in water balance components for the selected basins in the 21 century. The calculation procedure involves a physically-based model for interaction between the land surface and the atmosphere SWAP and climate scenario generator.