Optimization of Groundwater Quality Monitoring Network Using Geostatistical Method

Optimal design of groundwater monitoring network that is capable of providing accurate and informative data is crucial to improve our understanding of complex groundwater systems. In this study, a geostatistical method to optimize a groundwater quality monitoring network in Shamil-Takht plain, Hormozgan province were used. This study uses the spatial variance of collected data from the field to identify areas that are not covered and lack information. The kriging variance and the vulnerability maps were combined and the final map was used to design the optimum network. Selection of the best-fitted model was based on the values of the RMSE. This approach has been used to assess the electrical conductivity (EC)-as the representative of the most important quality parameters- monitoring network. The results show that 23 wells can be removed from the primary sampling network with 44 wells. On the other hand, 15 wells have been added to cover areas without information. As a result, the number of wells in low density areas has increased. Based on contaminant sources available in the plain, six new sites have been proposed to monitor the potential contamination from cemeteries, health centers, food and livestock industries.