Using ensembles of adaptive neuro-fuzzy inference system and optimization algorithms to predict reference evapotranspiration in subtropical climatic zones

Accurate prediction of reference evapotranspiration (ET0) is essential for efficient planning and management of limited water resources through proper irrigation scheduling. The FAO-56 Penman-Monteith approach to ET0 estimation was adopted to compute ET0 from data obtained during the period 2004–2019 in a subtropical climatic region in Bangladesh. Quantified ET0 values along with the meteorological variables for two other stations located in south Florida, USA were directly obtained from the USGS website. A commonly used machine learning algorithm, Adaptive Neuro Fuzzy Inference System (ANFIS), was employed to predict daily ET0 using regional meteorological data (e.g., daily maximum and minimum temperatures, wind speed, relative humidity, sensible heat flux, latent heat and sunshine duration). Four optimization algorithms were employed to tune ANFIS, resulting…