MAPPING INTRINSIC GROUNDWATER POLLUTION BY APPLYING THE DRASTICGOS MODEL USING GEOSPATIAL DATA: THE CASE OF THE GHRISS PLAIN (NORTHWESTERN ALGERIA) - KHELFI, Messaouda; BENSLIMANE, Mohammed; BENTKHICI, Nadjla; KAROUI, Soufiane (GeoScience Engineering, 2024)
The Ghriss aquifer in northwestern Algeria is undoubtedly one of the country’s most important reservoirs. Highly coveted by an ever-increasing domestic and agricultural demand, this potential has been confronted in recent years with a high pollution load from chemical inputs, nitrogen fertilizers and phytosanitary products, which are added to the discharge of poorly treated wastewater, leading to contamination risks for public health and disruption of local biodiversity. The aim of this study is to determine the degree of intrinsic vulnerability of the various forms of pollution introduced into the groundwater by the socio-economic activities carried out on the plain. The method is based on the universal DRASTIC model, supplemented by GOS parameters, coupled with a Geographic Information System (GIS) and geospatial data, obtained by remote sensing, enabling the various modeled parameters to be measured: water aquifer depth, net recharge, aquifer lithology, soil type, topography, impact of the vadose zone, aquifer hydraulic conductivity, land use and aquifer type. The cross-referencing of thematic maps highlights the emergence of groundwater pollution vulnerability classes (very high, high, medium, and low) and consequently the related causes. The results obtained and validated by the DRASTIC model indicate high vulnerability in 31% of the plain’s alluvial aquifer, medium-sensibility zones in 68% and low-sensibility zones in 1%. As for the DRASTIC-GOS model, vulnerability to water pollution is classified into four distinct levels: low (0.04%), moderate (2.17%), high (1.21%) and very high (96.58%). In other words, the DRASTIC-GOS model reveals that the entire plain is threatened by anthropogenic pollution, confirming the good performance of this mapping approach for monitoring groundwater resources.