Resumen
The crop coefficient (Kc) is widely used for operational estimation of actual evapotranspiration (ETa) and crop water requirements. The standard method for obtaining Kc is via a lookup table from FAO-56 (Food and Agriculture Organization of the United Nations Irrigation and Drainage Paper No. 56), which broadly treats Kc as a function of four crop-growing stages. However, the distinctive physiological characteristics of overwintering crops, such as winter wheat (Triticum aestivum L.), which is extensively planted in the North China Plain (NCP), are not addressed in this method. In this study, we propose a stage-wise method that accounts for Kc variations for winter wheat at each critical phenological stage, thereby estimating Kc at finer temporal scales. Compared with the conventional FAO method, the proposed stage-wise method successfully captures the bimodal pattern in Kc time series for winter wheat, which is shown at both ten-day and phenological time scales. In addition, the accuracies of the proposed stage-wise Kc method and the FAO method were evaluated using micro-meteorological measurements of ETa collected at the Gucheng agrometeorological experimental station in the NCP. Using a leave-one-out strategy, the evaluation revealed that the stage-wise method significantly outperformed the FAO method at both daily and critical phenological time scales, with root-mean-square errors in ETa for the stage-wise method and the FAO method being 0.07 mm·day-1 and 0.16 mm·day-1, respectively, at the daily time scale, and 0.01 mm·day-1 and 0.27 mm·day-1 at the critical phenological time scale. Generally, the FAO method underestimates ETa during the initial stage and overestimates ETa during both the development and mid-season stages. It is shown that the proposed stage-wise method is important for the water-stressed NCP where precision irrigation is highly desirable, especially during the critical phenological stages. Results from this study provide insight into accurate estimation of water requirements for winter wheat at phenological time scales.