Generalized daily reference evapotranspiration models based on a hybrid optimization algorithm tuned fuzzy tree approach

Reference evapotranspiration (ET 0 ) is an important driver in managing scarce water resources and making decisions on real-time and future irrigation scheduling. Therefore, accurate prediction of ET 0 is crucial in water resources management. In this study, the prediction of ET 0 was performed employing several optimization algorithms tuned Fuzzy Inference System (FIS) and Fuzzy Tree (FT) models, for the first time, whose generalization capability was tested using data from other stations. The FISs and FTs were developed through parameter tuning using Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Pattern Search (PS), and their combinations. The FT was developed by combining several fuzzy objects that received ranked meteorological variables. A total of 50 FIS and FT models were developed…