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    Leveraging Artificial Intelligence and Machine-Learning Methods for Bias Correction of Reference Evapotranspiration Utilizing ERA5 Data 

    Source: Journal of Irrigation and Drainage Engineering:;2025:;Volume ( 151 ):;issue: 004:;page 04025021-1
    Author(s): Shadman Veysi; Soheila Zarei; Eslam Galehban; Amir Tahooni
    Publisher: American Society of Civil Engineers
    Abstract: This study addresses the challenge of mitigating biases in daily reference evapotranspiration (ETo) computations, utilizing the ECMWF Reanalysis version 5 reanalysis data set within coastal regions. Data from 14 weather ...
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