Abstract: Nowadays, more attention has been focused on the estimation of the land surface turbulent fluxes (sensible and latent heat fluxes) with data assimilation method. In this study, a sequential data assimilation scheme is developed based on the concept of the Ensemble Kalman filter (EnKF). It assimilates land surface temperature into a simple land surface model which based on the energy balance theory for the estimation of surface turbulent fluxes. Moreover, from the perspective of error estimation, the simple schemes for estimating model errors and ensemble size are discussed. After construction of the assimilation system, the several numerical experiments tested by Yucheng cropland site in the province of Shandong. Results show that the land surface turbulent fluxes can be retrieved with satisfactory accuracy by using our method(compared to MODIS ET products(MOD16A2), the RMSE of ET results are dropped from 4.18mm to 2.99mm), which indicate the availability of our method in the prediction of surface turbulent fluxes.