Comparison of Spatial Interpolation Methods for Estimating the Annual Rainfall in the Wadi Al-Mujib Basin in Jordan

Accurate rainfall data are essential for environmental applications in the actual assessment of geographical distribution rainfall. Interpolation methods usually applied to monitor spatial data. There many interpolation methods, but none them can achieve all cases best results. In this study, three different were investigated with regard their suitability producing a distribution. Rainfall from 14 meteorological stations spatially interpolated using common techniques: inverse distance weighting (IDW), ordinary kriging (OK), and kernel smoothing (KS) compared assessed against station modeled Cross-validation was evaluate accuracy terms root-mean-square error (RMSE). The results obtained by lowest RMSE interpolating precipitation (RMSE) = 100.86542, while (IDW) performed worst, least efficient largest RMSE=103.43; addition, minimum (-) maximum (+) is -92.38 mm 313.33 mm.