Based on the seven monthly mean precipitation data averaged over years from the Urumqi River basin, the authors put forward the Gauss parameter model which can meet the interpolation demand in time and space dimensions. The fitting goodness of the models is 4%. This model builds the relationship between the Gauss function and precipitation, according to the mathematical meaning of the Gauss function and distributional rule of precipitation, and converts the traditional interpolation into function model, advances the application of the precipitation data, solves the problem of calculating precipitation and precipitation distribution under the conditions of the scarcity of rainfall data, especially in the alpine mountain with sparse meteorological stations. It will significantly improve the availability of precipitation data. This paper presents the principle, derivation process and the typical application methods, integrating with specific data. The precipitation distribution simulated by the Gaussian function is consistent with the actual precipitation amount. Each parameter of Gaussian function has a very clear physical meaning. The method of Gaussian function parameter has a strong practical value, and is widely used.The details are discussed below. As the time function of precipitation distribution, the model can calculate precipitation amount of any time. Through integration of the precipitation distribution function within a certain period, the precipitation amount of any time cycle can be calculated. Through the spatial interpolation of rainfall distribution parameters of different sites, the precipitation distribution function can be achieved in different regions, thereby calculating the precipitation amount of any time periods and at any time. The simplified Gauss model can transform the estimates of three parameters into one parameter, which can meet the needs of application in the high mountains with sparse meteorological stations, but also can calculate precipitation amount in the historical period. The promoted model can be applied to the precipitation distribution of more than one peak, which expands the application of Gaussian parameters. However, we must point out that the method of the Gaussian model is based on the data of meteorological stations in Urumqi River valley. The application of models might have some limitations, especially in this region.