The experimental data from Baicheng Station, Jilin Province, are used to calibrate the parameters in crop model WOFOST, and the independent observation data including development stages, leaf area index, biomass for each organ are adopted to verify and evaluate the adaption. The parameters from Baicheng and Yushu Stations represent the parameters in the western and central parts of Jilin Province. The developmental phase data, weather data and daily soil moisture data under optimization from automatic soil observation stations are used in the simulation of WOFOST model. To improve the simulation accuracy of WOFOST, the volume content of soil calculated based on precipitation is replaced by the volume content of soil calculated based on the observed soil moisture data, which was used in the nextstep computing of model to simulate the biomass from 2001 to 2016. The improvement rate of volume content of soil (PD) is constructed to analyze the different changes by using soil moisture data and precipitation data. The results showed that (1) the model simulation is more accurate for the growth period, leaf area, total biomass and leaf biomass of spring maize at Baicheng Station, while the simulation effect of spike biomass is general. (2) From the perspective of the typical Baicheng Station, there is a significant positive correlation between the simulated value of spike biomass and precipitation, and the simulation effect of soil in years with less precipitation is significantly better than that driven by precipitation. (3) Regionally speaking, the driving effect of soil moisture in regions dominated by salinealkali soil or with less precipitation years is better than that driven by precipitation. In the region where the soil type is backland and in the year with more precipitation, the simulation results of the two are similar. (4) In general, the WOFOST model can significantly improve the simulation accuracy by replacing precipitation with observed soil moisture.