Resumen
Various methods have been developed to estimate daily crop coefficients, but their performance varies. In this paper, a comprehensive evaluation was conducted to estimate the crop coefficient of winter wheat in four growth stages based on the observed data of weighing-type lysimeters and the high-precision automatic weather station in the Wudaogou Hydrological Experimental Station from 2018 to 2019. The three methods include the temperature effect method, the cumulative crop coefficient method, and the radiative soil temperature method. Our results suggest that the performance of these methods was different in each individual growth stage. The temperature effect method was better in the emergence-branching (RMSE = 0.06, r = 0.80) and heading-maturity stages (RMSE = 0.16, r = 0.94) because the temperature is suitable for crop growth during most of these two periods. The cumulative crop coefficient method was better in the greening-jointing (RMSE = 0.16, r = 0.88) and heading-maturity stages (RMSE = 0.20, r = 0.91) because this method is closely related to crop growth, which is vigorous during these two stages. The radiative soil temperature method was better in the emergence-branching (RMSE = 0.20, r = 0.35) and branch-overwintering stages (RMSE = 0.25, r = 0.52) as the energy balance can be ensured by the relatively high level of the effective energy during these periods. By comparing the estimation accuracy indices of the three methods, we found that the temperature effect method performed the best during the emergence-branching stage (RMSE = 0.06, MAE = 0.06, r = 0.80, dIA = 0.88), branch-overwintering stage (RMSE = 0.13, MAE = 0.11, r = 0.44, dIA = 0.55), and heading-maturity stage (RMSE = 0.16, MAE = 0.13, r = 0.94, dIA = 0.97), while the cumulative crop coefficient method performed best during the greening-jointing stage (RMSE = 0.16, MAE = 0.13, r = 0.88, dIA = 0.89). Based on this result, an integrated modelling procedure was proposed by applying the best method in each growth stage, which provides higher simulation precision than any single method. When the best method was adopted in each growth stage, the estimated accuracy of the whole growth process was RMSE = 0.13, MAE = 0.09, r = 0.98, dIA = 0.99.