Estimating daily actual evapotranspiration of a rice-wheat rotation system in typical farmland in the Huai River Basin using a two-step model and two one-step models

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 R-2 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.

Automated summary

This study evaluated three models for estimating daily evapotranspiration (ET) and found that the PM-K-c model performed better after calibration, while the R-K model and AA model underestimated the daily ET of winter wheat and rice. The AA model showed better simulation results, especially for rice.