ESTIMATION OF MONTHLY MEAN REFERENCE EVAPOTRANSPIRATION USING GENE EXPRESSION PROGRAMMING

Abstract

Evapotranspiration is a main component of the water cycle and is important in crop growth. Monthly mean reference evapotranspiration (ETo) is estimated using gene expression programming (GEP) in Basrah City, south of Iraq. Various climatic data, such as air temperature, relative humidity, and wind speed are used as inputs of GEP model to estimate the values of reference evapotranspiration (ETo) given by the FAO-56 (Penman-Monteith equation). Nine input combinations tested with GEP are coded as model No. (1-9). Root relative squared error (RRSE) is taken as fitness function in each of GEP models. GEP models with three climatic input variables (temperature, relative humidity, and wind speed) take the highest level in the performance. The GEP technique was successfully employed to estimate ETo in the study area. The explicit formulas obtained can be used as powerful models for estimating the mean monthly ETo in the irrigation practices with limited climatic data.