In arid areas，snowmelt is the main source of water resource formation. Therefore, the formation, transformation and utilization of snow resources are important research topics on the development and utilization of water resources in Xinjiang, China. Further, hydrological model is a key to determine the formation and transformation of water resources. This study uses the field experimental area of Tianshan Snow Station, Chinese Academy of Sciences, as the experimental area. The meteorological data and snowmelt amount were adopted as the independent and dependent variables. A snowmelt model based on temperature change is studied, and a single-factor simple model is calibrated and validated. Simultaneously, the variation law of snowmelt in the experimental area for many years and the response process of snowmelt to temperature are analyzed. The results indicate that snowmelt still occurs in winter in certain low-temperature ranges. In the study area of Tianshan Mountains, the critical value of daily average temperature of snowmelt is approximately -7 ℃. When the temperature is lower than -7 ℃, snowmelt is basically suspended, reflecting the characteristics of snowmelt in arid areas. In terms of the model, a single factor simple snowmelt model based on temperature exhibits good performance in simulating snowmelt in mountainous areas. During the calibration period (2016—2020), the correlation parameters of Bias, MAE, RMSE, NSE and R² between the observed and simulated snowmelt values were -0.037, 0.367, 0.482, 0.870, and 0.876 respectively. The values of validation period were -0.210, 0.292, 0.577, 0.845, and 0.811, respectively. The simulation results and correlation coefficients during the validation period indicate that the simulated value of the model has good consistency with the measured value. The advantage is that the amount of snowmelt in the basin can be estimated through the available meteorological data. The results provide a relatively simple algorithm for snowmelt calculation in arid areas and a simple and effective snowmelt submodule for a hydrological model. This study has an important reference value for understanding the change law of snowmelt and the simulation and prediction of snowmelt runoff in subsequent studies.