Estimation of Evapotranspiration Using Reanalysis Models based on Global Earth Observations at Distinct Climate Regions of Iran

Accurate estimation of evapotranspiration is one of the most important issues in water balance calculation at the catchment and field scale. The lack of meteorological observations for using empirical methods and the high costs of measuring evapotranspiration using lysimeter restricts the usability of these methods in most cases. To tackle these problems, this research addressed the performance of reanalysis models including W3RA, HBV-SIMREG, PCR-GLOBW, WATER-GAP, and Ensemble for estimation of evapotranspiration at different climate regions of Iran. Besides, the reference evapotranspiration for assessment of the above models obtained using lysimeter measurements. Findings showed that in most cases studies the Ensemble model’s performance with the RMSE value ranges from 3.42 to 7.57 mm/day is the weakest one, while the results of HBV-SIMREG and W3RA show the best agreements with lysimeter dataset. Analyzing the outputs based on mean bias error (MBE) depicted that the estimated evapotranspiration based on W3RA and Ensemble have the minimum and maximum bias, respectively. As an overall conclusion, although results indicate that PCR-GLOBW has the maximum correlation coefficient (CC) with the reference datasets, HBV-SIMREG is the best and reliable model for estimation of evapotranspiration in most climate regions of Iran and can be considered as an alternative dataset, especially in data-limited areas.