Abstract: In recent years, the progress of remote sensing technology has brought great convenience for obtaining large-scale continuous hydrological variables. In order to explore the feasibility of using other remote sensing hydrological variables to calibrate hydrological model parameters in case of lack of data in the basin, the Xin'anjiang model was taken as the research model using Shuffled Complex Evolution (SCE-UA) algorithm to calibrate hydrological model parameters, and the impact of combined remote sensing soil moisture and runoff data on model parameter calibration results in case of short series discharge data was analyzed. The results show that there are some uncertainties when using short series discharge data to calibrate hydrological model, and the simulation accuracy is poor in the validation period, while the simulation results obtained by introducing soil moisture to carry out parameter calibration are reduced in the rate period, but it is better than the former in the validation period, and it can be close to the level of using long series discharge data to calibrate parameters.