Geostatistical analysis of groundwater data in a mining area

Geostatistical methods are increasingly used in earth sciences and engineering to improve space and time predictions. During mining activities, it is essential to monitor contaminant concentrations in soil and groundwater and estimate their spatial distribution in the area to guide environmental monitoring and reclamation once mining operations have been finished. In this work, we present the geostatistical analysis of the groundwater content in certain pollutants (Cd and Mn) in a group of adjacent mines. The available monitoring locations were Sixty-two. The challenge in this work is the grouped location of monitoring stations within the borders of the adjacent mines. This work aims to map the spatial distribution of Cd and Mn concentrations in groundwater in the entire mining area. The Correlation between Cd and Mn was investigated during the preliminary analysis of the data and found significant. The logarithm of the data values was used, and after removing a linear trend, the variogram parameters by means of a spherical model were estimated. In order to create the necessary contaminants concentration maps, we employed the Ordinary Kriging (OK) method and inversed the transformations. Cross-validation shows promising results (ρ = 92% for Cd and ρ = 88% for Mn, RMSE = 5.1 ppm for Cd and RMSE = 18.2 ppm for Mn), while the uncertainty was calculated in acceptable bounds.