Determination of snowmelt infiltration coefficients for seasonally frozen regions requires considering the response of the groundwater table to the freeze–thaw process

•Determining snowmelt infiltration coefficient with a simple process, high accuracy.•Overcoming the overestimation of snowmelt recharge in the calculating formula•Improving accuracy of groundwater recharge of seasonal frozen areas by 8.8 %–15.0 % Atmospheric precipitation is an important recharge source for groundwater resources and the precipitation infiltration recharge coefficient (PIRC) is key to accurately assessing the amount of groundwater resources. However, the freeze–thaw process in seasonally frozen areas can significantly reduce the soil infiltration capacity and affect the snowmelt infiltration process, thus changing PIRC during the snowmelt period. Currently, in the calculation of PIRC for snowmelt period, the same method as that used for the flood period is generally adopted, which may cause significant bias in groundwater recharge evaluation results. To resolve these issues, this study performed a method for determining the snowmelt infiltration coefficient based on groundwater level variation with a simplified process, high accuracy, and produces stable results. The results of this study showed that: (1) The groundwater level variation ΔH caused by snowmelt recharge should be determined by considering the water exchange within the unsaturated zone and groundwater caused by the freeze–thaw process of the soil. (2) The total amount of meltwater infiltration recharge P cannot be a simple addition of precipitation during the freeze–thaw period. It is suggested that the actual infiltrated meltwater recharge should be calculated using the improved degree-day model, which improves the accuracy by 50.3 %–66.4 % compared with the existing algorithm. (3) The snowmelt infiltration coefficient determined in this study can improve the calculation accuracy of groundwater recharge resource in a seasonally frozen zone by 8.8 %–15.0 % by considering its seasonal dynamic characteristics. The research results provide a theoretical basis for understanding the recharge potential of winter snow cover in seasonally frozen areas and improving the accuracy of groundwater resource evaluation in such regions.