In the heart of northwestern Algeria, a groundbreaking study is reshaping how we assess groundwater quality, with significant implications for the energy sector and beyond. Laouni Benadela, a researcher at the Laboratory of Water Science and Technology (LSTE) at the University of Mustapha Stambouli in Mascara, has pioneered a hybrid approach that combines conventional groundwater quality indices with fuzzy logic to provide a more nuanced and reliable evaluation of drinking water safety.
The Sidi Kada Mountains, a semi-arid region, rely heavily on groundwater for drinking water due to the unreliability of surface water sources. Benadela’s study, published in the Journal of Degraded and Mining Lands Management (translated as the Journal of Degraded and Reclaimed Lands Management), focuses on the Jurassic aquifer in this area. The research integrates three classic groundwater quality indices—the Weighted Water Quality Index (WQI), the Analytic Hierarchy Process Water Quality Index (AHP-WQI), and the Entropy Water Quality Index (EWQI)—with a Mamdani-type fuzzy inference system.
“While traditional indices classified most sampling points as Good to Excellent, we found that chloride and nitrate concentrations in several boreholes approached or exceeded WHO drinking water standards,” Benadela explained. This discrepancy highlighted the need for a more precautionary classification framework. By incorporating nitrate and chloride concentrations as explicit corrective parameters, the fuzzy system provided a more robust assessment.
The study also examined the spatial distribution of boreholes using a land use/land cover (LULC) map to identify links between local exceedances and anthropogenic pressures. The results were striking: while global index scores suggested generally safe water quality, five boreholes (19%) were ultimately classified as NonAcceptable for drinking.
This integrated approach offers practical guidance for water managers, helping them select priority monitoring stations and secure a safe and sustainable drinking water supply. For the energy sector, which often relies on groundwater for various operations, this research provides a valuable tool for ensuring water quality and mitigating risks associated with contamination.
Benadela’s work demonstrates that combining conventional indices with fuzzy logic and compliance checks improves the robustness and reliability of groundwater quality assessments. This hybrid approach could be a game-changer for semi-arid regions, where water scarcity and quality are critical concerns.
As the energy sector continues to expand in water-scarce regions, the need for reliable water quality assessments becomes increasingly urgent. Benadela’s research not only addresses this need but also sets a new standard for groundwater quality evaluation. By providing a more nuanced and accurate assessment, this study paves the way for better water management practices and more sustainable energy operations.
In the words of Benadela, “This research offers a more precautionary and reliable framework for assessing groundwater quality, which is crucial for ensuring safe drinking water and supporting sustainable development in semi-arid regions.” The implications of this work extend far beyond the Sidi Kada Mountains, offering valuable insights and tools for water managers and energy sector professionals worldwide.