Nadjib Haied

In semi-arid regions, sustainable groundwater management for irrigation is critical for agricultural productivity and food security. This study presents an integrated methodological framework combining hydrochemical characterization, machine learning (ML) modeling, and explainable artificial intelligence (XAI) to predict the Irrigation Water Quality Index (IWQI) in the Ain Oussera plain, Djelfa Province, Algeria. A total of 191 groundwater samples were collected from November 2023 to September 2024 and analyzed for major ions and physicochemical parameters. Multiple irrigation suitability indices were calculated, including Sodium Adsorption Ratio (SAR), Sodium Percentage (Na%), Magnesium Hazard (MH), Permeability Index (PI), Residual Sodium Carbonate (RSC), Soluble Sodium Percentage (SSP), and Kelly’s Ratio (KR). Five ML models were developed and evaluated for IWQI prediction: Random Forest, Gradient Boosting, XGBoost, K-Nearest Neighbors, and Support Vector Regression. Results showed that 55% of groundwater samples exhibited low to no restrictions for irrigation use, while 19% required high to severe restrictions. The XGBoost model demonstrated superior performance, with the highest R² (0.95) and the lowest RMSE (3.22) among all tested algorithms. SHAP (SHapley Additive exPlanations) analysis provided a transparent interpretation of model predictions, identifying electrical conductivity and Sodium Adsorption Ratio as the most influential parameters affecting IWQI, while chloride, sodium, total hardness, and magnesium had minimal impact. Spatial mapping using Inverse Distance Weighting (IDW) interpolation in ArcGIS 10.8 revealed considerable spatial variability in water quality throughout s the plain. This research addresses a critical gap in North African groundwater management by integrating ML predictive capabilities with XAI transparency, providing water resource managers and agricultural stakeholders with interpretable, data-driven tools for sustainable irrigation planning in water-stressed semi-arid environments.

The massive dune aquifer of Bouteldja is one of the most exploited aquifers in Algeria; as a result, its piezometric level has declined. Such pressure on the dune aquifer, in addition to its moderate-to-severe vulnerability to pollution, may lead to deterioration of groundwater quality. This...

Drought is considered a natural hazard and has become a recurrent phenomenon in Algeria since the 1970s. Algeria is characterized by three different climates, namely, sub-humid, semi-arid and arid climates. In this study, we aimed to spatiotemporally assess drought hazard, vulnerability and risk in the three climates of three sub-basins, namely, the Seybouse Maritime, Wadi Djelfa-Hadjia and Wadi M’Zi sub-basins. To this end, the standardized precipitation index (SPI) and the reconnaissance drought index (RDI) were used to evaluate drought physical characteristics on a 12-month timescale, based on precipitation and temperature monthly data covering the period of 1979–2019. High values of the coefficient of determination (R²) (0.76–0.99) confirmed by low values of the root-mean-square error (RMSE) (0.08–0.49) proved that the drought indices displayed a high correlation. Drought hazard and vulnerability were evaluated based on physical characteristics and socioeconomic aspects, respectively. The results led to the determination of a high correlation between the two indices used; the determination of the main drought events; and the mapping of the drought hazard, vulnerability and risk using a geographic information system (GIS). These findings suggest that the SPI provided the highest intensities, while the longest periods and the strongest magnitudes were given by the RDI. The spatiotemporal drought distributions varied with time from station to station and from sub-basin to sub-basin. Risk maps revealed that vulnerability based on socioeconomic factors controls drought risk.

The Mio-plio-quaternary aquifer of the Djelfa Syncline is part of a region in Algeria which is characterized by the lack of surface water resources and located in a semi-arid climate. Since alluvial aquifers, and among them our aquifer, are the most vulnerable because of thier direct exposure to...

Un site aquifère contaminé, situé en bordure de l’oued Meboudja (Annaba, Algérie), a été caractérisé en mettant en place une surveillance de la qualité des eaux de surface et souterraines affectées par les nombreux rejets industriels et urbains sur une période de 11 ans (1999−2009). Les déchets industriels sont déposés directement sur le sol et les effluents sont déversés dans l’oued Meboudja sans aucun traitement préalable. Les eaux souterraines présentent une conductivité électrique élevée (de 1000 à 6000 μS/cm), de fortes teneurs en chlorure et en sodium avec respectivement un maximum de 1400 et 730 mg/L. Partant des résultats de l’analyse en composantes principales effectuée sur 33 puits en juillet 2009, les trois principaux processus responsables de l’évolution chimique observée au niveau de l’aquifère ont été identifiés: (a) l’apport salifère du lac Fetzara et le lessivage des formations métamorphiques carbonatées (responsables de l’augmentation de la minéralisation) ; (b) l’alimentation de la nappe par les eaux de l’oued Meboudja, recevant de nombreux polluants industriels (responsable des fortes teneurs en fer et en manganèse) ; et (c) l’utilisation des produits chimiques dans l’agriculture (responsable de l’augmentation des teneurs en nitrates). Les fortes minéralisations sont enregistrées notamment dans les puits situés à proximité des rejets industriels. En outre, de fortes concentrations métalliques en fer et en manganèse sont observées dans les eaux de l’oued. L’évolution de ces deux éléments dans les eaux de la nappe au cours d’un cycle hydrologique montre que l’augmentation des teneurs est liée notamment à une réalimentation de la nappe par l’oued et à une mauvaise oxygénation de la nappe. L’existence de niveaux argileux peut en effet jouer le rôle d’écran en surface et favoriser les conditions réductrices dans la nappe. La Meboudja agit par conséquent comme une source diffuse de contaminants tout au long de son parcours. Les caractéristiques hydrodynamiques de l’aquifère ont été estimées à l’aide de l’interprétation des données des pompages d’essai effectués dans plus d’une dizaine de puits. Des modèles d’écoulement et de transport de polluants ont été élaborés en utilisant le code MODFLOW-MT3D. L’ampleur de la migration des contaminants a été évaluée pendant une période de 11 ans (1999−2009). L’interaction oued-nappe est considérée comme responsable de la migration des contaminants dans la plaine de la Meboudja.

Seybous Watershed is one of the largest basins in Algeria. It is characterized by a large urban and industrial activity presented on both banks of the river and tributaries Seybous. It daily receives discharged without treatment. This work provides an overview of the quality of urban wet weather discharges; this study is based on several morphological parameters Hydrometeorological basin. During the year 2012, two samples were performed (in August and September). These have worn on urban waste and the waters of Seybous Wadi. The analysis results indicate that urban waste are characterized by high pollutant load varies with the rain and the influence of these releases is visually along the rivers and waters of the different stations are between the classes of poor quality very bad.