Assessment of Optimum Interpolation Method to Estimate Groundwater Chemical Data

Nowadays, the interpolation methods have become an important technology on the groundwater research. Many geographic information system software based on different interpolator tools have been developed and used widely such as ArcGIS, MapInfo and ArcView. This study was conducted to evaluate interpolation tools for the prediction of HCO3, Cl, SO4, Ca and Na distribution in groundwater of northern regions of Khuzestan province. Inverse distance weighted, kriging, radial basis functions, local and global polynomial interpolation were five interpolation methods that used for this subject. 98 deep wells was selected and chemical analysis data was collected in summer 2008. Predicted values of contaminants were compared to observed data by RMSE, MAE (Mean Absolute Error) and MSDR (Mean Squared Standardized Deviation Ratio) indexes to select the optimum interpolator technique. The results show that the kriging method has the highest interpolation accuracy among five interpolation methods for mapping Ca, SO4 and HCO3 by RMSE equal to 0.56, 0.9 and 0.6 respectively. Also, RBF and IDW Methods have acceptable estimations for Cl and Na ions.