An estimation method of remote sensing evapotranspiration in farmland based on the three-temperature model with adjoint calibrated of WOFOST
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 estima-tion accuracy and applicability of the novel method were evaluated.The results showed that the correlation coeffi-cients 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 evap-oration 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 us-ing the WOFOST-simulated crop transpiration data,the correlation coefficient between the estimated and ob-served values significantly increased to 0.89,the RMSE decreased to 0.65 mm·d-1,and the Nash-Sutcliffe effi-ciency coefficient reached 0.79.These results indicate that the proposed method effectively improves the estima-tion accuracy of the three-temperature remote sensing evapotranspiration model and offers insights for enhancing the accuracy of other remote sensing evapotranspiration models.
harmonic analysis of time seriesadjoint calibrated functionk-means++algorithmcrop growth modelevapotranspiration
万方数据
维普
