摘要：Estimation of reference evapotranspiration (ET.) is vibrantly required for estimating crop water requirement and budgeting irrigation scheduling. The beneficial use of water is of great importance dueto shortage issues especially in developing coun-tries like Pakistan. The Food and agricultural organ-ization (FAO)developed a Peneman-Montieth (PM)method which can be globally considered as a stand-ard method for estimation of ET.but it requires nu-merous climatic data. Consequently, there is a need to find out the next best suitable method after PM method. The Multi-layer perceptron(MLP), Gene expression programing(GEP)and Radial basis func-tion(RBF)were utilized to calculate ET.values. Monthly meteorological data of six different stations located in arid,semi-arid and humid regions of Paki-stan covered from 1980 to 2015. Seventeen input combinations comprise of various climatic variables were developed toevaluate the impact on ET.Ofthe available meteorological data,70% was employed in training while remaining 30%used in testing process. The yielded values of the developed models were compared with the ET.estimated by PM method. The outcome of the study was also applied on some otherclimatic regions located in USA, New Zealand and China for numerous duration only three climatic parameters, namely, maximum temperature, mean relative humidity and wind velocity had a large pos-itive effect on increasing the accuracy of estimating ET.By comparing the eight performing indices, MLP among all the powerful predictive modeling techniques can also be considered as the superior al-ternative to the conventional methods in estimation of ET.
关键词：Reference Evapotranspiration;Climatic Zones;Penman-Montieth method;Multilayer perceptron;Gene Expression Programming;Radial Basis Function
