In this study, a hydrological model parameter optimization scheme was constructed in SWAT based on streamflow assimilation using the ensemble Kalman filter(EnKF)approach, in which the model simulation and streamflow observation errors were reasonably quantified and the model parameter evolution and over-fitting issues were effectively treated. Based on this scheme, the capacity of streamflow assimilation on SWAT model parameter optimization was evaluated in the upper Huai River above Huaibin hydrological station. The results showed that the updated parameter ensemble gradually converged and stabilized during the data assimilation process. The runoff process based on the stabilized parameter ensemble was close to the measured runoff. The deterministic coefficient at the outlet of the basin reached 0. 88. The results indicated that the EnKF based streamflow assimilation had the ability to optimize the parameters in SWAT. It was feasible to calibrate model parameters using data assimilation method.