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Spatial analysis of seasonal precipitation using various interpolation methods in the Euphrates basin, Turkey

Katipoğlu Okan Mert

Acta Geophysica

2022

Vol. 70, no 2

859--878

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 Informa tion 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.

Analysis of spatial variation of temperature trends in the semiarid Euphrates basin using statistical approaches

Katipoğlu Okan Mert

Acta Geophysica

2022

Vol. 70, no 4

1899--1921

This study analyzes the spatial and temporal distribution of trends on monthly, seasonal, and annual mean temperatures (1967–2017) at 22 stations in the Euphrates Basin of Turkey. The recently proposed innovative trend analysis (ITA) and the nonparametric Mann–Kendall (MK) and Spearman’s rho (SR) test at 5% and 1% significance levels were applied to examine the temporal trends of temperatures. Before using the nonparametric trend analysis, the serial correlation of the temperature data was removed with the pre-whitening (PW) method. Then, MK-Z values were mapped in ArcGIS environment using the Empirical Bayesian Kriging (EBK) method to reveal the spatial variation of temperature trends. As a result, according to the ITA method, increasing temperature trends at 1% significance level dominate almost all periods. Based on the MK and SR tests, it was identified that increase trends were dominant at 1% and 5% significance levels in February, March, April, July, August, Spring, Summer, and Annual periods. According to the spatial temperature trend maps, significant increase trends occupy an important place in most of the basin in February, March, April, June, July, August, Spring, Summer, Winter, and Annual periods. The study results provide important information to water resources managers and decision-makers about the regions at significant risk in climate change in the Euphrates Basin.