Selection of variogram model for spatial rainfall mapping using Analytical Hierarchy Procedure (AHP)

In geostatistical analysis, spatial interpolation at any unmeasured point is done using the parameters of a variogram model that matches the experimental data. several variogram models can be used, and the accuracy of the spatial map produced depends on the selection of the most appropriate variogram model that ts the spatial distribution of the experimental data. therefore, in this study, a multiple-criteria decision-making method, i.e. analytical hierarchy procedure (ahp), is used to evaluate and select the best variogram model for mapping spatial rainfall in the upper reaches of the kelang river basin in malaysia. using daily rainfall data from 71 rain gauge stations, geostatistical analysis was done by the ordinary kriging interpolation method and 5 alternatives to variogram models, namely spherical, tetraspherical, pentaspherical, exponential, and gaussian for spatial rainfall mapping. the accuracy of the spatial rainfall map was evaluated using four criteria of spatial interpolation error indicators, which are root-mean-square error (rmse), average standard error (ase), mean standardized error (mse), and root-mean-square standardized error (rmsse). the results showed that the spherical model was ranked at the top for producing the best spatial rainfall map of the study area.