Estimation methods to define reference evapotranspiration: a comparative perspective

Abstract Evapotranspiration is a key variable for hydrologic, climatic, agricultural, and environmental studies. Given the non-availability of economically technically easy to implement direct measurement methods, evapotranspiration estimated primarily through application empirical regression models, machine learning algorithms that incorporate conventional meteorological variables. While FAO-56 Penman-Monteith equation worldwide has been recognized as most accurate estimate reference (ETo), number required climatic variables makes its questionable regions with limited ground-based climate data. This note provides summary semi-empirical equations linked data requirement problems associated these models (transferability quality), an overview potential in tasks, trends studies, some recommendations topics future research should address would lead further improvement performance generalization available models. The terminology used this consistent both theoretical practical field evapotranspiration, which often dispersed academic literature. goal provide perspective stimulate discussion.