An estimation method of remote sensing evapotranspiration in farmland based on the three-temperature model with adjoint calibrated of WOFOST
Received date: 2023-09-20
Revised date: 2024-01-03
Online published: 2025-01-17
The method for estimating evapotranspiration using remote sensing evapotranspiration models has been widely applied, but there is need for research into improving its accuracy. Crop growth models exhibit strong mechanistic foundations and accuracy in simulating crop transpiration. This study integrated the WOFOST crop growth model with the three-temperature remote sensing evapotranspiration model to design a novel method for estimating remote sensing-based evapotranspiration in maize fields. The core approach involved localizing the WOFOST model, validating its simulation accuracy, and using its simulated crop transpiration data to construct an auxiliary calibration function. This function calibrated the transpiration component of the three-temperature model and combined it with the calibrated soil evaporation component to derive the evapotranspiration for the maize fields. Using actual evapotranspiration observed by an eddy covariance system as a reference, the estimation accuracy and applicability of the novel method were evaluated. The results showed that the correlation coefficients of evapotranspiration, crop transpiration, and soil evaporation in the uncalibrated three-temperature model were 0.61, 0.71, and 0.12, respectively, with root mean square errors (RMSE) of 1.76 mm·d-1, 1.91 mm·d-1, and 3.02 mm·d-1, respectively, and negative Nash-Sutcliffe efficiency coefficients. After calibrating only the soil evaporation component, the correlation coefficients improved to 0.77, but the error remained large (1.91 mm·d-1) with a Nash-Sutcliffe efficiency coefficient of -0.74. However, when the three-temperature model was calibrated using the WOFOST-simulated crop transpiration data, the correlation coefficient between the estimated and observed values significantly increased to 0.89, the RMSE decreased to 0.65 mm·d-1, and the Nash-Sutcliffe efficiency coefficient reached 0.79. These results indicate that the proposed method effectively improves the estimation accuracy of the three-temperature remote sensing evapotranspiration model and offers insights for enhancing the accuracy of other remote sensing evapotranspiration models.
FENG Kepeng , XU Dehao , ZHUANG Haoran . An estimation method of remote sensing evapotranspiration in farmland based on the three-temperature model with adjoint calibrated of WOFOST[J]. Arid Zone Research, 2025 , 42(1) : 166 -178 . DOI: 10.13866/j.azr.2025.01.15
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