Climate warming has been driving hydrological changes across the globe, especially in high latitude and altitude regions. Long-term (1962–2012) streamflow records and permafrost data in the Yangtze River source region were selected to analyze streamflow variations and groundwater storage in response to climate warming. Results of Mann–Kendall test and Morlet wavelet analysis show that the anomalies of both annual streamflow and winter baseflow are near the year 2010, and their main period scales are 37 years and 34 years, respectively. The annual streamflow and the annual baseflow increased significantly, as assessed by the recursive digital filtering baseflow separation. Results of Pearson correlation coefficient indicate that the rising air temperature is the primary cause for the increased streamflow instead of precipitation and evaporation. By using the top temperature of permafrost model, the total permafrost area has decreased by 8200 km² during the past 50 years, which causes groundwater storage to increase by about 1.62 km³ per year due to climate warming. More space has been made available to store the increasing meltwater during the permafrost thawing. Permafrost thawing and increasing temperature are the direct and indirect causes of the increasing groundwater storage. The results of the cumulative anomaly method and Pearson correlation coefficients show that permafrost thawing has a greater impact than increasing temperature on the increase of groundwater storage. Permafrost thawing due to climate warming show compound effects on groundwater storage–discharge mechanism, and significantly affects the mechanisms of streamflow generation and variation.

Thermal conductivity is a basic parameter of soil heat transferring, playing an important role in many fields including groundwater withdrawal, ground source heat pump, and heat storage in soils. However, it usually requires a lot of time and efforts to obtain soil thermal conductivity. To conveniently obtain accurate soil thermal conductivity, a new model describes the relationship between soil thermal conductivity (λ) and degree of saturation (S_r) was proposed in this study. Dry soil thermal conductivity (λ_dry) and saturated soil thermal conductivity (λ_sat) were described using a linear expression and a geometric mean model, respectively. A quadratic function with one constant was added to calculate λ beyond the lower λ_dry and upper λ_sat limit conditions. The proposed model is compared with five other frequently used models and measured data for 51 soil samples ranging from sand to silty clay loam. Results show that the proposed model match the measured data well. The proposed model can be used to determine soil thermal conductivity of a variety of soil textures over a wide range of water content.