Tarbiat Modares University (TMU) ECOPERSIA 2322-2700 1 2 2013 06 01 Parametric and Non-Parametric Trend of Reference Evapotranspiration and its key influencing climatic variables (Case study: Southern Iran) 123 144 17086 EN Ali Reza Nafarzadegan Management Center for Strategic Projects, Fars Organization Center of Jahad-e-Agriculture, Shiraz, Iran Hossein Ahani Management Center for Strategic Projects, Fars Organization Center of Jahad-e-Agriculture, Shiraz, Iran Vijay P. Singh Department of Civil and Environmental Engineering and Department of Biological and Agricultural Engineering, Texas A & M University, Scoates Hall, College Station, USA Mehrzad Kherad Management Center for Strategic Projects, Fars Organization Center of Jahad-e-Agriculture, Shiraz, Iran Journal Article <span>Evapotranspiration is one of the most important components of the hydrological cycle which is directly influenced by atmospheric conditions. This study investigated annual and seasonal trends in reference evapotranspiration (ET<sub>0</sub>) and its key influencing climatic variables during 1966-2005 at 10 stations in southern Iran (with centrality of Fars province). First, multivariate regression analysis was performed to identify the major meteorological variables affecting ET<sub>0</sub>. Second, annual and seasonal trends in climatic variables as well as ET<sub>0</sub> were assessed using the Mann-Kendall test, Spearman's rho, the Pearson correlation and linear regression to evaluate their contribution to the temporal trend in ET<sub>0</sub>. Results suggested that the more effective variables for ET<sub>0</sub> were wind speed (<em>U<sub>2</sub></em>), relative humidity (<em>RH</em>) and sunshine hours (<em>n</em>). Also, the<span> majority of trends in seasonal and annual </span>ET<sub>0</sub> were non-significant and after that decreasing<span> and increasing trends had higher frequencies. In addition, distributions of relative frequencies of trend types at all considered time-scales were similar for both parametric and non-parametric techniques. Hence, the disagreement between parametric and non-parametric trend results did not depend on the degree of normality in the annual and seasonal ET<sub>0</sub> distributions in the study area.</span> Climate variables Lilliefors test Normality degree Trend analysis https://ecopersia.modares.ac.ir/article_17086_f9c6f82cb3e872a20e6a310f33a9c450.pdf