Laboratoire de Mobilisation et Gestion des Ressources en Eau

Arid regions of Algeria face persistent water crises due to recurrent droughts and growing water demand, especially for drinking water and agriculture. This pressure have led to overexploitation of local aquifers. Accurately identifying potential groundwater recharge zones is therefore critical for sustaining aquifer replenishment and water security. In this study, we assess groundwater recharge potential zones in the Khanguet Sidi Nadji watershed in North-Eastern Algeria, employing a spatial multi-criteria decision-making (MCDM) methodology which is based on the AHP, that integrates remote sensing and Geographic Information Systems (GIS). The work methodology uses essential data from ten (10) factors, including lithology, rainfall, curve number, land use, lineament density, slope, drainage density, peak runoff, and soil hydrogeological group. Thematic maps /layers of each factor are produced using ArcGIS 10.8 and integrated using AHP to generate a composite groundwater recharge potential map. Results indicate that areas with high recharge potential comprise approximately one-third of the watershed, covering 27% of the area, moderate potential covers 41% and low potential covers 32%. We validated the final recharge potential map by comparing it with data from 55 high-yield wells distributed across the watershed. A strong correlation (r = 0.74) was found between high-potential zones and well locations. Overall, the findings of this study provide a powerful decision-making tool that contributes to the improved exploitation and protection of groundwater resources, thereby enhancing sustainable water resources management and assisting in addressing the growing challenges of water scarcity in the arid regions of Algeria.

Thirteen echinoid taxa are described from Coniacian marl-limestone alternations in three sections south and east of Djebel Metlili, on the southwestern margin of the Aures Mountains in northeastern Algeria. The biostratigraphic framework, based on ammonites and inoceramids, indicates an early to middle Coniacian age. The identified taxa include: Rachiosoma rectilineatum, Phymosoma tamarinense, P. cf. P. mansour, Gomphechinus meslei, Coenholectypus subcrassus, Parapygus coquandi, Petalobrissus trigonopygus, P. rimula, Hemiaster sp., and Mecaster fourneli. Three new species are described, Orthopsis metliliae sp. nov., Coenholectypus sulcatus sp. nov. and a new genus and species referred to the family Phymosomatoidae, Triboporus luluatus gen. et sp. nov. A large amount of well-documented material, comprising 579 specimens, was collected, with the fauna being dominated by the spatangoid Mecaster fourneli. At the genus level, the fauna exhibits characteristics typical of the Tethyan realm, and includes Rachiosoma, Gomphechinus, Mecaster, Parapygus and Petalobrissus. However, at the species level, most taxa are restricted to Algeria. Some are also found in adjacent countries such as Tunisia and Egypt.

This study investigates the biostratigraphic and paleobiogeographic significance of Hemipneustes africanus Deshayes, 1848, with a special attention on its temporal extent and geographical distribution during the Late Cretaceous. The overarching scientific question investigated herein tackles the significance of the distribution and stratigraphic position of this taxon in elucidating its faunal provincialism and dispersal limits within the southern Tethys.

A newly discovered and well-dated occurrence of H. africanus is described in a new area of the Aurès Basin, within the Beni Fedhala syncline (Maafa–Djebel Gueroun, Algeria). This taxon was found associated with the ammonite index species Nostoceras (Bostrychoceras) polyplocum (Roemer, 1841), within the Total Range Zone of the planktic foraminifer Globotruncana calcarata Cushman, 1927, which indicates a Late Campanian age.

The present record represents one of the earliest chronostratigraphically constrained reports of the genus Hemipneustes in the upper Campanian. The limited geographic distribution of the species, restricted to Algeria, Tunisia and Spain, suggests low dispersal ability, further contributing to our general understanding of the regional faunal differentiation within the southern Tethyan region during the Late Cretaceous.

A comprehensive study of the lithological, sedimentological and palaeontological characteristics of deposits belonging to the middle Turonian to Coniacian age in the Bellezma-Batna Mountains was carried out in order to establish a new biostratigraphic framework and interpret the evolution of the palaeoenvironment and sea-level fluctuation during this period. The studied sequences, exposed at Chaabet (Djebel Boukezzez) and Chihat, are mostly composed of marls and limestones. They are mainly composed of three formations: the Marly Limestone of the Chaabet Formation, the Upper Limestone of the Berriche Formation and the Marls of the Chaabet Formation. Biostratigraphic interpretations were based mainly on planktic and benthic foraminifera (H. helvetica, Marginotruncana cf. sigali, Discorbis turnicus, Nezzazatinella picardi HENSON), ostracods (Ovocytheridea sp., Brachycythere ekpo), and rudists Vaccinites praegiganteus, from the lower limestone member at both the Chaabet and Chihat sections, which is considered as a good indicator of the Upper Turonian age. Fourteen types of microfacies were identified and grouped into three facies assemblages- outer, middle, and inner ramp—based on sedimentological and palaeontological features. Sequence stratigraphic analysis establishes five sedimentary sequences that mark successive cycles of transgression and regression. A significant rise in sea level during the middle Turonian led to deep open marine conditions, followed by a regression in the late Turonian and early Coniacian that led to progressively shallower environments. These fluctuations reflect the combined effects of eustatic changes and regional tectonic movements.

A comprehensive study of the lithological, sedimentological and palaeontological characteristics of deposits belonging to the middle Turonian to Coniacian age in the Bellezma-Batna Mountains was carried out in order to establish a new biostratigraphic framework and interpret the evolution of the palaeoenvironment and sea-level fluctuation during this period. The studied sequences, exposed at Chaabet (Djebel Boukezzez) and Chihat, are mostly composed of marls and limestones. They are mainly composed of three formations: the Marly Limestone of the Chaabet Formation, the Upper Limestone of the Berriche Formation and the Marls of the Chaabet Formation. Biostratigraphic interpretations were based mainly on planktic and benthic foraminifera (H. helvetica, Marginotruncana cf. sigali, Discorbis turnicus, Nezzazatinella picardi HENSON), ostracods (Ovocytheridea sp., Brachycythere ekpo), and rudists Vaccinites praegiganteus, from the lower limestone member at both the Chaabet and Chihat sections, which is considered as a good indicator of the Upper Turonian age. Fourteen types of microfacies were identified and grouped into three facies assemblages- outer, middle, and inner ramp—based on sedimentological and palaeontological features. Sequence stratigraphic analysis establishes five sedimentary sequences that mark successive cycles of transgression and regression. A significant rise in sea level during the middle Turonian led to deep open marine conditions, followed by a regression in the late Turonian and early Coniacian that led to progressively shallower environments. These fluctuations reflect the combined effects of eustatic changes and regional tectonic movements.

Groundwater represents the main water resource for irrigation in the Ouled Djellal region (southeast of Algeria). Despite the importance of groundwater in this area, its quality and sustainability remain insufficiently studied. Therefore, this study aimed to introduce an integrated analytical framework by combining multivariate statistical techniques i.e., Principal Component Analysis (PCA) and Hierarchical Ascending Classification (HAC), irrigation indices (IWQI, SAR, Na%, SSP, PS, and RSC), and machine learning (ML) models such as Artificial Neural Network (ANN), Support Vector Machine (SVM), and Multiple Linear Regression (MLR) to assess and predict groundwater quality for irrigation. The main difference with previous studies is the fact that this work applied Empirical Bayesian Kriging Regression Prediction (EBKRP) to spatialize irrigation indices derived from ML with higher precision. The approach enables cross-validation of model performance and captures complex nonlinear interactions among hydrochemical parameters. The attained results revealed that groundwater quality was varied from moderate to poor for irrigation, driven mainly by salinity and sodicity effects. In addition, the ANN model achieved the highest predictive accuracy (R² = 0.97, RMSE = 1.50), confirming its superiority in modelling complex hydrochemical behavior. The proposed modelling framework represents a methodological advancement for data-scarce arid regions, serving as a practical tool adaptable to groundwater monitoring and irrigation planning in similar regions.