Akademik Veri Yönetim Sistemi
Acta Geophysica, cilt.70, sa.2, ss.859-878, 2022 (SCI-Expanded)
© 2022, The Author(s) under exclusive licence to Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences.It is vital to accurately map the spatial distribution of precipitation, which is widely used in many fields such as hydrology, climatology, meteorology, ecology, and agriculture. This study aimed to reveal the spatial distribution of seasonal, long-term average precipitation in the Euphrates Basin with various interpolation methods. For this reason, Simple Kriging, Ordinary Kriging, Universal Kriging, Ordinary CoKriging, Empirical Bayesian Kriging, Radial Basis Functions (Completely Regularized Spline, Thin Plate Spline, Multiquadratic, Inverse Multiquadratic, Spline with Tensor), Local Polynomial Interpolation, Global Polynomial Interpolation, and Inverse Distance Weighting methods have been applied in the Geographical Information Systems environment. Long-term seasonal precipitation averages between 1966 and 2017 are presented as input for predicting precipitation maps. The accuracy of the precipitation prediction maps was based on linear regression analysis, root mean square error (RMSE), mean absolute error (MAE), correlation coefficient (R), and determination coefficient (R2) values obtained from the cross-validation tests. The most suitable method was chosen for the interpolation method that gives the lowest RMSE, MAE, and the largest R and R2. As a result of the study, Ordinary CoKriging in spring and winter precipitation, Local Polynomial Interpolation in summer precipitation, and Ordinary Kriging in autumn precipitation were the most appropriate estimation methods.