Daily reference evapotranspiration modeling by using genetic programming approach in the Basque Country (Northern Spain)

J. Shiri, O. Kisi, G. Landeras, J.J. Lopez, A.H. Nazemi, L.C.P.M. Stuyt

    Research output: Contribution to journalArticleAcademicpeer-review

    103 Citations (Scopus)

    Abstract

    Evapotranspiration, as a major component of the hydrological cycle, is of importance for water resources management and development, as well as for estimating the water budget of irrigation schemes. This study presents a Gene Expression Programming (GEP) approach, for estimating daily reference evapotranspiration (ET0) in four weather stations in Basque Country (Northern Spain), for a 5-year period (1999-2003). The data set comprising air temperature, relative humidity, wind speed and solar radiation was employed for modeling ET0 using FAO-56 Penman Monteith equation as the reference. The GEP results were compared with the Adaptive Neuro-Fuzzy Inference System (ANFIS), Priestley-Taylor and Hargreaves-Samani models. Based on the comparisons, the GEP was found to perform better than the ANFIS, Priestley-Taylor and Hargreaves-Samani models. The ANFIS model is ranked as the second best model.
    Original languageEnglish
    Pages (from-to)302-316
    JournalJournal of Hydrology
    Volume414-415
    DOIs
    Publication statusPublished - 2012

    Keywords

    • daily pan evaporation
    • artificial neural-networks
    • fuzzy inference system
    • computing technique
    • climatic data
    • intelligence
    • prediction
    • parameters
    • anfis
    • river

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