The objective of this study is to evaluate the performance of three models for estimating daily evapotranspiration (ET) by employing flux observation data from three years (2007, 2008 and 2009) during the growing seasons of winter wheat and rice crops cultivated in a farmland ecosystem (Shouxian County) located in the Huai River Basin (HRB), China. The first model is a two-step model (PM–K_c); the other two are one-step models (e.g., Rana–Katerji (R–K) and advection-aridity (AA)). The results showed that the energy closure degrees of eddy covariance (EC) data during winter wheat and rice-growing seasons were reasonable in the HRB, with values ranging from 0.84 to 0.91 and R² of approximately 0.80. Daily ET of winter wheat showed a slow decreasing trend followed by a rapid increase, while that of rice presented a decreasing trend after an increase. After calibrating the crop coefficient (K_c), the PM–K_c model performed better than the model using the K_c recommended by the Food and Agricultural Organization (FAO). The calibrated key parameters of the R–K model and AA model showed better universality. After calibration, the simulation performance of the PM–K_c model was satisfactory. Both the R–K model and AA model underestimated the daily ET of winter wheat and rice. Compared with that of the R–K model, the simulation result of the AA model was better, especially in the simulation of daily ET of rice. Overall, this research highlighted the consistency of the PM–K_c model to estimate the water demand for rice and wheat crops in the HRB and in similar climatic regions in the world.