Spatial distribution of the groundwater quality using kriging and Co-kriging interpolations

Abstract

The present work is aimed for investigation the groundwater quality for drinking purposes in El Mila plain, Algeria. This is carried out through an integrated approach of groundwater quality index (GWQI) and geostatistical method for mapping this index based on 35 wells and then hydrochemical parameters. Kriging has become a widely used interpolation method to estimate the spatial distribution of the groundwater quality index. The main objective of this study is to evaluate two geostatistical interpolation methods such as Ordinary kriging (OK) and Co-kriging (CK) for enhanced spatial interpolation of the groundwater quality index. The results of GWQI show that about 11.43% of the total samples fall in the excellent water class, and 85.71% samples reported good water quality type, whereas 2.86% groundwater samples exhibited poor water quality type. GWQI had a very strong significant correlation with EC, Ca, Mg, SO4 and HCO3. Therefore, these parameters were used as co-variables for Co-kriging method. The prediction performance of the adopted interpolation methods is assessed through cross-validation test. The results show that Co-kriging model with electrical conductivity (EC) as co-variable is superior to the other models to predict the groundwater quality index.