Application of empirical and random forest models in estimating reference evapotranspiration of humid regions

Accurate estimation of reference evapotranspiration (ETo) is an important issue in agricultural engineering, irrigation scheduling, water resources management, etc. Nowadays, the physics-based Penman-FAO-Monteith model is a standard model of ETo determining as well as calibrating other ETo equations. However, the need for large amount of hydro climatologic data has limited its application, especially in regions without sufficient necessary weather data. The present study aimed at assessing the performance accuracy of empirical temperature/radiation- based ETo models in humid regions and comparing the results with random forest (RF)-based models that used the same input variables of the applied empirical equations. The obtained results showed that the Random forest models gave the most accurate results when compared to the commonly used original and calibrated empirical equations (with similar input variables) with global MAE and SI values of 0.4 and 0.008. Nonetheless, the calibration procedure could not improve the performance accuracy of the equations in some cases.