As the drawback exists in data assimilation method for soil moisture simulation，the unscented weighted ensemble Kalman filter ( UWEnKF) based on unscented transformation and ensemble Kalman filter ( EnKF) is proposed，which improves the weight of the important ensemble member，and the ensemble members are symmetry about the mean values． The performance of UWEnKF is verified through the soil moisture assimilation experiment by assimilating the hourly in situ soil surface moisture observations into the one － dimensional ( 1 － D) Ｒichard equation at Meilin study area，eastern China． The results show that ① the one－dimensional Ｒichards equation can well simulate the soil moisture change，② data assimilation method can improve the soil moisture simulation accuracy，but the performance of assimilation method is related to simulation accuracy，③ UWEnKF can significantly improve soil moisture simulations and perform better than EnKF obviously in improving the accuracy of the model． Overall，UWEnKF is an efficient and practical data assimilation method，and is an important technique to improve the soil moisture simulation accuracy．