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1 2022

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A comparative study in quantifcation of maize evapotranspiration for Iranian maize farm using SEBAL and METRIC-1 EEFLux algorithms

Kamyab Abolfazl Delavari, Mokhtari Shahroo, Jafarinia Reza

Acta Geophysica

2022

Vol. 70, no 1

319--332

Evapotranspiration (ET) is one of the key components of the hydrological cycle, and its accurate estimation is very important in agricultural usages. In this study, actual daily ET (ETa) from the Surface Energy Balance Algorithm for Land (SEBAL) and Mapping Evapotranspiration with Internalized Calibration/Earth Engine Evapotranspiration Flux (EEFLux) algorithms were used to compare the relative performance of the algorithms for the Landsat 8 images during the maize growth period. The results indicated that ETa was low at the beginning of the growing season and then came up to the middle of the growing season and then decreased due to decreasing temperature as well as changes in maize cover. The EEFLux algorithm has estimated about 7.71% of daily ET more than the SEBAL algorithm at the Arak maize farm. The results of performance evaluation showed that root mean squared error (RMSE), Nash–Sutclife coefficient of efficiency (NSE), percent bias error (PBIAS), and coefficient of determination (R2 ) criteria were obtained 0.711, 0.807, 7.398, and 0.885, respectively, based on the EEFLux algorithm and for SEBAL algorithm were equal to 1.046, 0.582, 15.080, and 0.793, respectively. According to the Taylor diagrams and observed data (lysimeter data), the EEFLux algorithm was closer to measured ETa values and had a higher correlation and a less standard deviation than the SEBAL algorithm. Therefore, the EEFLux algorithm had better estimation than the SEBAL algorithm.