This study investigates the response mechanisms between soil water-heat transfer and environmental factors during freeze-thaw periods and establishes soil water-heat transfer functions in a cold region. Based on field-measured values of soil temperature and liquid-phase water content collected at an automatic weather station in the black soil area of the Songnen plain, the influence of the cumulative negative temperature on the soil freezing depth was analyzed under different snow cover conditions. A gray correlation analysis method was used to screen the environmental factors and determine those with the most influence on changes in soil water-heat transfer processes. Then, soil water-heat transfer functions were established between the selected environmental factors and soil temperature, the liquid-phase soil water content. The results showed that during the freezing and thawing period, snow cover hindered the effects of the cumulative temperature on the thickness of the frozen soil layer. Additionally, the time of occurrence of the maximum freezing depth under natural snow (NS), compacted snow (CS) and thickened snow (TS) treatments was delayed 7, 12 and 20 days, respectively, compared with that under bare land (BL). The correlation between atmospheric temperature, total radiation and soil temperature was relatively high, and this effect decreased with the increasing of snow cover. The main driving factors of variations in the liquid-phase water content were ambient humidity and saturated vapor pressure, and the effects of these factors decreased with increasing soil depth and snow cover thickness, similarly. In the active frozen layer, the correlation coefficients of the soil water-heat transfer functions were relatively high, and the function model can be tested by the significance (P < 0.05) test. However, the R-2 values of functions below the active layer were relatively low, and the soil water-heat transfer in the area below the active layer was less affected by the environment. This study reveals the characteristics of energy transfer and mass transfer in a composite system of atmospheric factors and frozen soil under snow cover conditions. It provides a reference for accurate forecasting and the efficient utilization of soil water and heat resources in cold and arid regions.

Alpine vegetation plays a crucial role in global carbon cycle. Snow cover is an essential component of alpine land cover and shows high sensitivity to climate change. The Tibetan Plateau (TP) has a typical alpine vegetation ecosystem and is rich of snow resources. With global warming, the snow of the TP has undergone significant changes that will inevitably affect the growth of alpine vegetation, but observed evidence of such interaction is limited. In particular, a comprehensive understanding of the responses of alpine vegetation growth to snow cover variability is still not well characterized on TP region. To investigate this, we calculated three indicators, the start (SOS) and length (LOS) of growing season, and the maximum of normalized difference vegetation index (NOVImax) as proxies of vegetation growth dynamics from the Moderate Resolution Imaging Spectroradiometer (MODIS) data for 2000-2015. Snow cover duration (SCD) and melt (SCM) dates were also extracted during the same time frame from the combination of MODIS and the Interactive Multi-sensor Snow and Ice Mapping System (IMS) data. We found that the snow cover phenology had a strong control on alpine vegetation growth dynamics. Furthermore, the responses of SOS, LOS and NDVImax to snow cover phenology varied among different biomes, eco-geographical zones, and temperature and precipitation gradients. The alpine steppes showed a much stronger negative correlation between SOS and SCD, and also a more evidently positive relationship between LOS and SCD than other types, indicating a longer SCD would lead to an earlier SOS and longer LOS. Most areas showed positive correlation between SOS and SCM, while a contrary response was also found in the warm but drier areas. Both SCD and SCM showed positive correlations with NDVImax, but the relationship became weaker with the increase of precipitation. Our findings provided strong evidence between vegetation growth and snow cover phenology, and changes in snow cover should be also considered when analyzing alpine vegetation growth dynamics in future,