Spatial analysis and geostatistical characterization of nitrate pollution in Mahdia's shallow aquifers

Industrial wastewater discharge, intensive livestock farming, and irrigation practices may be the primary groundwater pollution sources of nitrate in arid countries like Tunisia. Currently, this contamination is a real concern for the sustainable use of groundwater. In this regard, the primary difficulty facing Tunisia's water resource management is assessing the quality of the groundwater. To determine the spatial distribution of nitrate pollution in the groundwater system of the Mahdia region in Tunisia, 35 groundwater samples collected from shallow groundwater wells across the years 2006 and 2016 and their nitrate concentrations were determined by the Regional Commissariat for Agricultural Development of Mahdia (CRDA). The spatial distribution behavior of nitrate concentrations in groundwater was assessed by using GIS and ordinary kriging techniques. It was determined that exponential semi-variogram models were the most suitable to delineate the spatial dependence structure of nitrate concentration over the study area. Nitrate contour maps showed the high concentration of nitrates and the expansion of polluted groundwater areas in the last decade, especially in zones close to irrigated perimeters, textile industries, livestock farming, olive mills, and rural agglomerations without sanitation networks. The findings emphasize the critical necessity for formulating targeted groundwater management frameworks that prioritize the implementation of comprehensive monitoring and regulatory measures in high-risk zones. It is essential to deploy advanced nitrate removal technologies within industrial wastewater treatment systems and to expand rural sanitation infrastructure to mitigate further nitrate contamination from domestic sources. These results furnish essential data that can guide policymakers in devising precise, evidence-based interventions aimed at ensuring the long-term sustainability of groundwater resources.