Optimization of the Spatial Interpolation for Groundwater Depth in Shule River Basin

To understand the spatial interpolation optimization laws of groundwater depth, two different methods of spatial interpolation are compared: (1) inverse distance weighting (IDW), (2) Ordinary Kriging (OK), using the recorded data of groundwater depth in the Shule River basin, China, in March from 2001 to 2006. The result indicates that the accuracy of the OK is the highest. After exploratory spatial analysis for groundwater data, it shows that the groundwater depth is characterized by high dispersion, with a few outliers, and a positively skewed distribution. However, data transformation reduces the variances and skewed distribution, and effectively removes various interpolation noises in the interpolation surfaces. The cross-validation results indicate that data transformation can improve accuracy of the OK.