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Artificial intelligence/machine learning estimation of FAO and ASCE standardized reference ET erodes the physical basis and intended purpose of ET standardization
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DOI：10.1016/j.agwat.2026.110657.png)
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Abstract
En 中文
• ETref is a defined physical calculation, not an observable flux to be used as a learnable target. • Use of AI/ML to estimate ETref undermines standardization, transferability, and error attribution. • Reduced-input AI/ML weakens the case for maintaining quality weather networks. • AI/ML adds value in ET science when supporting, not replacing, the ETref equation.
Keywords:
Reference evapotranspiration
Artifical intelligence
Machine learning
FAO56
Agroclimate
Evaporative demand
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