Comparison of Differences in Actual Cropland Evapotranspiration under Two Irrigation Methods Using Satellite-Based Model.

Remote sensing technology is widely used to obtain evapotranspiration (ET_a), but whether it can distinguish the differences in farmland energy balance components and ET_a under different irrigation methods has not been studied. We used Landsat 8 data as the primary dataset to drive the METRIC model and inverted the surface parameters and ET_a of the Shiyang River Basin from 2014 to 2018. After improving the METRIC model using T_a obtained by the regression method instead of interpolation to calculate the net radiation flux (R_n), R² was improved from 0.45 to 0.53, and the RMSE was reduced from 61 W/m² to 51 W/m². The ET_a estimation results on satellite overpass days performed well, with R² equal to 0.93 and RMSE equal to 0.48 mm when compared with the Eddy covariance method (EC) observations. Subsequently, the different growth stages and daily average ET_a estimates of maize were compared with three observations (water balance, WB; Bowen ratio and energy balance method, BREB; and EC). The daily estimates of ET_a correlate well with the observations of BREB (R²_BI = 0.82, R²_DI = 0.92; RMSE_BI = 0.46 mm/day, RMSE_DI = 0.32 mm/day) and EC (R²_BI = 0.85, R²_DI = 0.92; RMSE_BI = 0.45 mm/day, RMSE_DI = 0.34 mm/day), and the estimation for drip irrigation was found to be better than for border irrigation. The total accuracy of the ET_a estimation on the five-year overpass day of maize farmland reached R² = 0.93 and RMSE = 0.48 mm. With sufficient remote sensing data, the 4-year average ET_a of maize was 31 mm lower for DI than for BI, and the mean value of ET_a obtained from the three observation methods was 40 mm. The METRIC model can be used to distinguish ET_a differences between the two irrigation methods in maize farmlands. [ABSTRACT FROM AUTHOR]