Spatial Distribution and Trend Analysis of Groundwater Contaminants Using the ArcGIS Geostatistical Analysis (Kriging) Algorithm; The case of Gurage Zone, Ethiopia

Abstract

The study explores the spatial distribution and trends of groundwater pollutants focusing on calcium and four other key water quality parameters in the Gurage Zone, Ethiopia, in 2024. It uses the ArcGIS geostatistical analysis tool with the Kriging algorithm to map and analyze the spatial variability of contaminants. The primary aim is to identify areas with high levels of pollutants and understand spatial patterns. It identifies contamination hotspots associated with natural processes and human activities. Twenty-seven samples were collected from various sites, and parameters like calcium, total dissolved solids, hardness, conductivity, and alkalinity were measured. The findings show that the distribution of contaminants varies significantly across different areas, with some areas exceeding safe drinking water limits. It reveals that the southern region has the highest calcium concentration, with shallow local boreholes. The deeper wells have higher dissolved solids, hardness, and conductivity. The spatial trend shows increased pollutant levels along the X and Y axes. The Kriging model effectively predicted contaminants in unsampled areas, offering a reliable technique aimed at groundwater quality monitoring. The study provides important insights for the local authorities to implement interventions for groundwater protection in the Gurage Zone.