Haji Karimi; Hasan Fathizade
Volume 19, Issue 53 , September 2015, , Pages 277-297
Abstract
Abstract
Selection of an optimal interpolation method for estimating the characteristics of the not-sampled points was the main aim of this study, due to the important role of data management. In this study, ordinary Kiriging interpolation models including linear, exponential, spherical, Gaussian were ...
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Abstract
Selection of an optimal interpolation method for estimating the characteristics of the not-sampled points was the main aim of this study, due to the important role of data management. In this study, ordinary Kiriging interpolation models including linear, exponential, spherical, Gaussian were used to estimate the mean annual rainfall of Ilam Province. For this purpose the normality of the data was checked using the Kolmogorov-Smirnov method and then the variogram of each model was calculated and plotted. In continuation, the best spatially fitted variogram between the data was used being compared to the other variograms. For this purpose, the relation between the piece effect and the roof of variogram was used (Co+C). According to the parameters obtained from the fitted variograms, the Gaussian variogram with the 0.33 best fitted the correlation between the data and was used for interpolation. In order to evaluate the efficiency of employed models, the root mean square error (RMSE) and the standard error of results were used. The results showed that the Gaussian Variogram having the lowest estimation error (6.12) and root mean square error (166) were the best model for the interpolation of the data in this investigation. Furthermore, comparison of RMSE with Standard Error (SE) for calculating the amount of expectations demonstrated that the four models gave overestimations.
