State-of-the-art approach for potential evapotranspiration assessment

The aim of the PhD thesis is the foundation of a new temperature-based model since simplified PET estimation proves very useful in absence of a complete data set. In this respect, the Parametric model is presented based on a simplified formulation of the well-established Penman-Monteith expression, which only requires mean daily or monthly temperature data. The model was applied at both global and local regions and the outcomes of this new approach are very encouraging, as indicated by the substantially high validation scores of the proposed approach across all examined data sets. In general, the parametric model outperforms well-established methods of the everyday practice. A second analysis which was examined as part of this thesis is related to which spatial techniques is the optimal in order to transform the point scale estimate in regional. A thorough analysis of different geostatistical model was carried out (Kriging, IDW, NN, BSS) and it can be concluded that the IDW even is the most simplify geostatistical model, it can be produce consistent spatial PET results. Another part of the thesis was the development of an R function for testing the trend significance of time series. The function calculates the trend significance using a modified Mann- Kendall test, which takes into account the well-known physical behavior of the Hurst-Kolmogorov dynamics. The function is tested in 10 stations in Greece, with approximately 50 years of PET data with the use of a recent parametric model. Finally, a number of hydrological, agronomist and climatologist applications are presented for lighting the robustness of the new Parametric approach in multidiscipline areas.