Abstract. In cold regions, snow cover and seasonally frozen ground (SFG) exert a substantial influence on hydrological processes, yet their effects – especially at the scale of large basins – remain insufficiently understood due to limited observations and process-based analyses. To address this, we extended the widely used Grid Xinanjiang (GXAJ) hydrological model by developing two physically meaningful yet computationally efficient modules: (i) the GXAJ-S model, which incorporates snowmelt processes, and (ii) the GXAJ-S-SF model, which additionally accounts for freeze–thaw cycles of SFG. These modules strike a balance between physical representation and simplicity, making them applicable in data-sparse cold regions. The model performance was evaluated using multi-source remote sensing/reanalysis data and observed daily runoff, enabling a systematic investigation of how snow and SFG jointly regulate key hydrological processes. The results demonstrate that: (1) including both snowmelt and freeze–thaw processes significantly improves runoff simulation, especially during cold seasons; (2) snow dynamics directly modulates the development of soil freeze–thaw cycles, thereby altering the hydrothermal state of the vadose zone; and (3) the inclusion of the SFG module in the model variant, which already accounted for snowmelt, increased the predicted surface runoff by 39 %–77 % during cold months, reduced evapotranspiration by approximately 85 %, and substantially modified interflow processes, particularly during the early-spring thaw period. These findings provide quantitative evidence of the critical role of SFG in shaping the seasonal hydrological regime of large cold-region basins. Moreover, the modular and transferable design of the snow and SFG components allows for straightforward integration into other hydrological models, offering a valuable tool for hydro-climatic assessments and water resource management in mountainous regions under changing climate conditions.
Wu et al. (Wed,) studied this question.