Water, heat and salt transport in cold regions are coupled due to phase change in soil during winter. Salt existed in soils result in large uncertainties in cold regions soil hydrology. To disentangle the effects of salts on cold regions water and energy balance, I have conducted laboratory and field experiments and obtained some featured results: 1) a soil freezing characteristic prediction model was devloped for accurate determinations of soil freezing characteristics; 2) we pointed out the importance of salt dispersion and expulsion in frozen soils and estimated the contributions of them to salt redistribution in freezing/thawing soils; 3) we systematically estimated evaporation from freezing/thawing soils and disentangled the combined influences of soil salt contents and groundwater table on evaporation.

Current soil hydrological models do not take the explicitly take into accounts the impacts of salts on soil water and energy balance, which can result in large uncertainties in hydrologcial modeling. I developed the soil hydrological model based on laboratory and field experiments for better representation the coupled transport of water, heat and energy in cold regions. The featured results are: 1) we proposed a dynamical relationship between soil freezing point and soil salt content and implemented it into CoupModel, this new scheme has improved the performance in cold regions soil hydrological modeling, 2) we used the GLUE (Generalized Likelihood Uncertainty Estimation) method to evaluate uncertainties in cold regions soil hydrological modeling, and pointed out that atmospheric boundary posed a large uncertainty in cold regions modeling, 3) we made a quantified demonstration on the importance of water-saving irrigation practice on water resources management in cold regions.

Soil hydrolog plays a vital role in ecosystem evolution because water and carbon cycles are coupled in ecosystems. A better modeling of soil hydrology would benefit the terrestrial carbon fluxes estimates. I used the generic Carbon Cycle Data Assimilation System (CCDAS) to combine satellite observed soil moisture with a terrestrial biosphere model to improve ecosystem modeling. The major results are: 1) we investigated the importance of soil hydrology on ecosystem modeling by using in-situ and satellite observations; 2) we used CCDAS to assimilate 6-year SMOS soil moisture into a terrestrial biosphere model and improved carbon cycle modeling performance at regional and global scale; 3) we assimilated 36-year soil moisture into CCDAS and improved the representation of dought at continental scale.