In order to explore the influence of the uncertainty of input parameters in the SHAW (Simultaneous heat and water) model on the output results and the key influencing factors in the simulation of soil thermal process under snow cover conditions，in this study，the experiment station of Northeast Agricultural University in the black soil area of the Songnen Plain was taken as the research area，the SHAW model was used to simulate the dynamic changes of the thermal process of six soil layers with different depths under the condition of snow cover. Combined with the LHS sampling method，the standard rank stepwise regression was used to explore the effects of parameter uncertainty on soil freezing depth and temperature output uncertainty. The results show that the SHAW model can reflect the law of soil freezing and thawing，the average absolute error is less than 2 ℃ between the simulated and the measured soil temperatures at six depths，the output sensitivity of the selected parameters to soil temperature is weak，and the initial snow thickness has a significant effect on soil temperature. The output of soil freezing depth plays a leading role. Overall，the SHAW model based on LHS sampling and standard rank stepwise regression methods can be used to simulate soil thermal processes under snow cover conditions.