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Detrital and volcanic-detrital rocks from the Ifni Buttonhole and Lakhssas Plateau were analyzed to determine their provenance, compositional maturity, and alteration source. Geochemically, the sediments were classified as arkoses, lithic arenites, grauwackes, sandstones, lithic arenites, and Fe-rich sands, indicating low compositional and mineralogical maturity. A high average SiO2 concentration and low Al2O3 were consistent with a low abundance of shale and clay components. The geochemical signatures of the detrital and volcano-detrital (RDVD) rocks indicate that they have undergone a moderate to low degree of chemical alteration. The CIA study also suggests that the granitic, granodioritic rocks represent the source provenance which, during weathering and transport, supplied the detritus to the supra-crustal units. The major trace element data suggest that these rocks are largely derived from felsic igneous rocks, namely granitoids, with a minor contribution from intermediate sources. The carbonate rocks do not represent a wide variety of facies: dolomitic limestone, calcareous limestone, and calcaro-dolomitic chert. Calcitic and dolomitic samples show a linear increase in SiO2, regardless of their CaO/LOI ratio values, which remain relatively constant. The highest SiO2 contents are observed in the calc-dolomitic chert. Geochemical analysis of RDVD from the Ifni buttonhole determined their origin, maturity, and alteration. Major oxides decreased with higher silica content, indicating quartz control. Samples, formed under semi-arid conditions, show maturity under stable deposition. They suggest a felsic, recycled source, with moderate alteration and zircon enrichment during recycling. In the study area, limestones and dolomites serve as materials applicable in the building sector, suitable for all types of concrete. The Taliwine Formation harbors Lower Cambrian dolomites and limestones, ideal for mosaic aggregates. Described as variable in color, compact, homogeneous, very hard, and resistant to alteration, the plutonic rocks form prominent peaks. They exhibit both subalkaline characteristics in granitoids and an alkaline trend in dolerite dykes. Most samples display minimal alteration, indicating the reliability of their major element compositions for geochemical analyses. These granitoids constitute valuable deposits for ornamental and building rock purposes.

Alteration minerals and silicification are typically associated with a variety of ore mineralizations and could be detected using multispectral remote sensing sensors as indicators for mineral exploration. In this investigation, the Visible Near-Infra-Red (VNIR), Short-Wave Infra-Red (SWIR), and Thermal Infra-Red (TIR) bands of the ASTER satellite sensor derived layers were fused to detect alteration minerals and silicification in east the Kerdous inlier for cupriferous mineralization exploration. Several image processing techniques were executed in the present investigation, namely, Band Ratio (BR), Selective Principal Component Analysis (SPCA) and Constrained Energy Minimization (CEM) techniques. Initially, the BR and SPCA processing results revealed several alteration zones, including argillic, phyllic, dolomitization and silicification as well as iron oxides and hydroxides. Then, these zones were mapped at sub-pixel level using the CEM technique. Pyrophyllite, kaolinite, dolomite, illite, muscovite, montmorillonite, topaz and hematite were revealed displaying a significant distribution in relation with the eastern Amlen region lithological units and previously detected mineral potential zones using HyMap imaging spectroscopy. Mainly, a close spatial association between iron oxides and hydroxide minerals, argillic, and phyllic alteration was detected, as well as a strong silicification was detected around doleritic dykes unit in Jbel Lkest area. A weighted overlay approach was used in the integration of hydrothermal alteration minerals and silicification, which allowed the elaboration of a new mineral alteration map of study area with five alteration intensities. ASTER and the various employed processing techniques allowed a practical and cost effective mapping of alteration features, which corroborates well with field survey and X-ray diffraction analysis. Therefore, ASTER data and the employed processing techniques offers a practical approach for mineral prospection in comparable settings.

The Igoudine and Amouslek formations (TerreneuvianâCambrian Epoch 2 boundary) in the western Anti-Atlas of Morocco record the replacement of stromatolite-dominated microbial consortia by thrombolite-metazoan consortia. Carbonate and calcareous shales of both formations have been analyzed for major, trace, and rare earth elements to study their geochemical characteristics and evaluate the provenance of the terrigenous fraction and paleoredox conditions. Discrimination diagrams for the source rocks based on major elements and selected trace elements indicate that the terrigenous fractions of the sediments were likely derived from predominantly felsic rocks, and the source rocks have been identified to be the PaleoproterozoicâNeoproterozoic granites and metasediments of the Kerdous inlier. Paleoredox proxies such as U/Al, V/Al and Mo/Al suggest that the Igoudine and Amouslek formations were deposited in the oxic environment. Our data show that the local water column was prevailingly oxidized before, during and after the transition from the microbial consortium (stromatolite-dominated biota) to the thrombolite-archaeocyathan consortium and shelly metazoans within the studied interval. This implies that the seawater redox status was not driving this change in these biological communities.

Abstract The Souss region in Morocco is known nationally and internationally for its essential knowledge of traditional herbal medicine and the cultural heritage of nutrition. The endemic species Argania spinosa (L.) Skeels is an important crucial plant used by the local population to treat many diseases and prepare some authentic foods. To identify the therapeutic uses of the Argan tree [Argania spinosa (L.) Skeels] and their benefits in preparing authentic foods, the survey was conducted using semi-structured questionnaires. We have achieved 450 interviews with traditional health practitioners and knowledgeable villagers. In the region of Chtouka Aït Baha and Tiznit (Western Anti-Atlas). In parallel with this survey, we collected some old local manuscripts from conventional practitioners in the region. The data obtained were analyzed using specific ethnobotanical indices such as Use Value (UV), Fidelity Level (FL), and Relative Frequency of Citation (RFC). In parallel, we analyzed the nutritional value of some authentic foods derived the argan oil (Amlou, Tagoulla, and Labsis). All 450 interviewees use the argan oil in food or for the preparation of their authentic foods derived (Amlou, Tagoulla, and Labsis); among them, 100 persons use Argan, in addition to food, in the treatment of various diseases with UV and RFC at 1.94 and 0.22, respectively. Among eight treated diseases by argan tree, the treatment of skin and subcutaneous diseases had a very highly significant value of the FL index (98%). Similarly, the analysis of the manuscripts collected in the study area revealed an ancient therapeutic use of the argan tree. The results also show that the Argan oil extracted from the seed is used to prepare authentic foods with significant nutritional value, especially Amlou.

Eastern Kerdous demonstrates a polymetallic hydrothermal activity due its association with a paleorelief area. This study focuses on generating a Mineral Potential Map based on Fuzzy Logic Modelling and HyMap-Based input layers. The Relative Absorption Band Depth, Directed Principal Component Analysis, Line Density, and Mixture Tuned Matched Filtering techniques were implemented to perform 20 thematic layers. As a result, three new prospective zones were identified. Fieldwork, petrography, and XRD analysis verified the remote sensing results. Finally, this investigation highlights the significant potential of HyMap imagery for mineral exploration in inaccessible and remote parts of the western Anti-Atlas belt. [ABSTRACT FROM AUTHOR]

Accurate lithological mapping is a crucial juncture for geological studies and mineral exploration. Hyperspectral data provide the opportunity to extract detailed information about the geology and mineralogy of the Earth’s surface. Machine learning (ML) and deep learning (DL) techniques provide an accurate and effective mapping of various types of lithologies in arid and semi-arid regions. This article discusses the use of machine learning algorithms, specifically Support Vector Machines (SVM), one-dimensional Convolutional Neural Network (1D-CNN), random forest (RF), and k-nearest neighbor (KNN), for lithological mapping in a complex area with strong hydrothermal alteration. The study evaluates the performance of the four algorithms in three different zones in the Ameln valley shear zone (AVSZ) area at eastern Kerdous inlier, Moroccan western Anti-Atlas. The results demonstrated that 1D-CNN achieved the best classification results for most lithological units. Additionally, the LK-SVM demonstrated good mapping results compared to the other SVM models, as well as RF and KNN. Our study concludes that the combination of the CNN and HyMap data can provide the most accurate lithologic mapping for the three selected region, with an overall accuracy of ~95%. However, this study highlights the challenges in identifying different lithological units using remotely sensed data due to spectrum similarities induced by similar chemical and mineralogical compositions. This study emphasizes the importance of carefully considering and evaluating ML and DL methods for lithological mapping studies, then recommends the high-resolution hyperspectral data and DL models for accurate results. The implications of this study would be fascinating to exploration geologists for Mineral Prospectivity Mapping (MPM), especially in selecting the most appropriate techniques for highly accurate mineral mapping in metallogenic provinces.

An assessment of potential groundwater areas in the Ifni basin, located in the western Anti-Atlas range of Morocco, was conducted based on a multicriteria analytical approach that integrated a set of geomorphological and hydroclimatic factors influencing the availability of this resource. This approach involved the use of geographic information systems (GIS) and hierarchical analytical process (AHP) models. Different factors were classified and weighted according to their contribution to and impact on groundwater reserves. Their normalized weights were evaluated using a pairwise comparison matrix. Four classes of potentiality emerged: very high, high, moderate, and low, occupying 15.22%, 20.17%, 30.96%, and 33.65%, respectively, of the basin’s area. A groundwater potential map (GWPA) was validated by comparison with data from 134 existing water points using a receiver operating characteristic (ROC) curve. The AUC was calculated at 80%, indicating the good predictive accuracy of the AHP method. These results will enable water operators to select favorable sites with a high groundwater potential.

The Sidi Ifni region in southwest Morocco is mainly composed of crystalline rocks with limited groundwater storage capacity. These water resources drain in particular fault zones with high fracture permeability. The main objective of this study is to describe the geological structure of the region to optimize future drilling locations. The gravity data were processed using various techniques, such as total horizontal gradient, tilt derivative, and Euler deconvolution, in conjunction with the interpretation of the geological data, to create a new structural map. This map confirms the presence of many previously identified or inferred faults and identifies significant new faults with their respective trends and depths. Analysis of this map shows that major faults are oriented NNE-SSW and NE-SW, while minor faults are oriented E-W, NW-SE, and NNW-SSE. The superposition of the hydrogeological data and the structural map reveals that the high groundwater flow values in the boreholes are located in the vicinity of the major faults and talwegs. The structures deduced from the filtering and interpretation of the gravity data suggest that the hydrogeological system of the Ifni Inlier is controlled by its structures. To confirm this impact, a high-resolution electrical resistivity map (7200 Hz) was used, with penetration depths ranging from 84 to 187 m. Negative boreholes, located in high resistivity ranges corresponding to sound basement formations without fault crossings, showed high resistivity values. The positive holes, located in anomalies with low linear resistivity, revealed the impact of fault crossings, which drain water and tend to decrease the resistivity values of the formations. Therefore, these new structural maps will assist in planning future hydrogeological studies in this area.

The purpose of this paper is to identify, quantify and delineate the areas with suitable aggregate resources in the Precambrian massif of Ifni and the limestone plateau of Lakhssas (southwest Morocco). To fulfill this objective, a study was undertaken on the geotechnical parameters of the various geological outcrops of the region based on the analysis of 42 rock samples (carbonate, magmatic, detritic and volcano-detritic). Initially, we subjected these samples to a series of laboratory tests (impact resistance (L.A), wear resistance (MDE), density, porosity, absorption), to classify them according to geotechnical standards. Then, a geospatial database was created, to exploit these geotechnical data, from a geographical information system (GIS) to produce various thematic maps. Based on the results of this study, all geotechnical classes according to the standards (A to E for the European standard and 1A to 6D for the Moroccan standard) are present with good to very good geomechanical properties (L.A between 12% and 35%, MDE between 5% and 30%). This classification allowed us to use GIS to identify and quantify potential areas for exploitation by assigning five categories of geotechnical suitability levels (high (4), medium (3), low (2), very low (1) and others (0)) and to show that approximately 72% of the study area belongs to the categories high, medium and low. The combination of laboratory results and GIS has allowed us to carry out geotechnical mapping that will be used by regional authorities and actors for good management of the field of quarrying to rationalize the national natural heritage.

Accurate lithological mapping is a crucial juncture for geological studies and mineral exploration. Hyperspectral data provide the opportunity to extract detailed information about the geology and mineralogy of the Earth's surface. Machine learning (ML) and deep learning (DL) techniques provide an accurate and effective mapping of various types of lithologies in arid and semi-arid regions. This article discusses the use of machine learning algorithms, specifically Support Vector Machines (SVM), one-dimensional Convolutional Neural Network (1D-CNN), random forest (RF), and k-nearest neighbor (KNN), for lithological mapping in a complex area with strong hydrothermal alteration. The study evaluates the performance of the four algorithms in three different zones in the Ameln valley shear zone (AVSZ) area at eastern Kerdous inlier, Moroccan western Anti-Atlas. The results demonstrated that 1D-CNN achieved the best classification results for most lithological units. Additionally, the LK-SVM demonstrated good mapping results compared to the other SVM models, as well as RF and KNN. Our study concludes that the combination of the CNN and HyMap data can provide the most accurate lithologic mapping for the three selected region, with an overall accuracy of ~95%. However, this study highlights the challenges in identifying different lithological units using remotely sensed data due to spectrum similarities induced by similar chemical and mineralogical compositions. This study emphasizes the importance of carefully considering and evaluating ML and DL methods for lithological mapping studies, then recommends the high-resolution hyperspectral data and DL models for accurate results. The implications of this study would be fascinating to exploration geologists for Mineral Prospectivity Mapping (MPM), especially in selecting the most appropriate techniques for highly accurate mineral mapping in metallogenic provinces. [ABSTRACT FROM AUTHOR]

Thrombolite reefs with archaeocyaths are common in the subtidal limestones of the lower Cambrian in the western Anti-Atlas of Morocco. The Igoudine Formation of the Tata Group recorded the first replacement of the microbial consortium (stromatolite-dominated) by thrombolite reefs with archaeocyaths and shelly metazoans. In order to better understand the role of the microbial community in the formation of thrombolite reefs with archaeocyaths across this critical transition, the macro-, micro- and ultra-fabric of thrombolites have been studied in detail. Three major components are identified within the first thrombolytic reef: archaeocyaths, calcimicrobes and micritic matrix. The studied thrombolites are typically dominated by the calcimicrobe Renalcis with subordinate Epiphyton and Girvanella. Scanning electron microscopy of the dark micrite of the Renalcis chambers showed amorphous translucent sheet-like structures interpreted as extracellular polymeric substances, closely associated with organominerals including nanoglobules and polyhedrons. Exceptionally well-preserved Renalcis chambers contain bacterial fossils similar to those described in modern microbialites, including microspherical coccoid fossils and filamentous bacteria that are either spaced or in close associations forming colonies. These organomineralization-related features suggest a bacterial origin for the Renalcis calcimicrobe. The matrices between the Renalcis chambers consist predominantly of clotted peloidal micrite. Mineralization of Renalcis microframes may involve two major biomineralization processes: (1) replacement of organic matter by organominerals resulting from anaerobic degradation of extracellular polymeric substances and bacterial sheaths and (2) encrustation of bacterial sheaths and extracellular polymeric substances due to increasing alkalinity of the microenvironment. These mechanisms played a crucial role in the early diagenetic cementation and preservation of the studied reefs. [ABSTRACT FROM AUTHOR]

This study is focused on developing an approach for spatial mapping of groundwater by considering four types of factors (geological, topographical, hydrological, and climatic factors), and by using different bivariate statistical models, such as frequency ratio (FR) and Shannon’s entropy (SE). The developed approach was applied in a fractured aquifer basin (Ameln Basin, Western Anti-Atlas, Morocco), to map the spatial variation of groundwater potential. Fifteen factors (15) influencing groundwater were considered in this study, including slope degree, slope aspect, elevation, topographic wetness index (TWI), slope length (LS), topographic position index (TPI), plane curvature, profile curvature, drainage density, lineament density, distance to rivers and fault network, normalized difference vegetation index (NDVI), lithology, and land surface temperature (LST). The potential maps produced were then classified into five classes to illustrate the spatial view of each potential class obtained. The predictive capacity of the frequency ratio and Shannon’s entropy models was determined using two different methods, the first one based on the use of flow data from 49 boreholes drilled in the study area, to test and statistically calibrate the predictive capacity of each model. The results show that the percentage of positive water points corresponds to the most productive areas (high water flow) (42.86% and 30.61% for the FR and SE models, respectively). On the other hand, the low water flows are consistent with the predicted unfavorable areas for hydrogeological prospecting (4.08% for the FR model and 6.12% for the SE model). Additionally, the second validation method involves the integration of 7200 Hz apparent resistivity data to identify conductive zones that are groundwater circulation zones. The interpretation of the geophysical results shows that the high-potential zones match with low apparent resistivity zones, and therefore promising targets for hydrogeological investigation. The FR and SE models have proved very efficient for hydrogeological mapping at a fractured basement area and suggest that the northern and southern part of the study area, specifically the two major fault zones (Ameln Valley in the north, and the Tighmi-Tifermit Valley in the south) has an adequate availability of groundwater, whereas the central part, covering the localities of Tarçouat, Boutabi, Tililan, and Ighalen, presents a scarcity of groundwater. The trend histogram of the evolution of positive water points according to each potentiality class obtained suggests that the FR model was more accurate than the SE model in predicting the potential groundwater areas. The results suggest that the proposed approach is very important for hydrogeological mapping of fractured aquifers, and the resulting maps can be helpful to managers and planners to generate groundwater development plans and attenuate the consequences of future drought.

This research work is intended as a contribution to the development of a multicriteria methodology, combining several factors to control the availability of groundwater resources, in order to optimize the choice of location of future drilling and increase the chances to take water from productive structures which will satisfy the ever-increasing water demand of local population (Arghen basin in the Western Anti-Atlas chain of Morocco). The geographic information system is used to develop thematic maps describing the geometry and the hydrodynamic functioning of the aquifer. In this study, 11 factors including geology, topography, and hydrology, influencing the distribution of water resources were used. Based on the Analytical Hierarchy Process (AHP) model, GIS, and remote sensing, the study mapped and classified areas according to their hydrogeological potential. The favorable potential sectors cover 17% of the total area of the basin. The medium potential sectors account for 64%, while the unfavorable areas cover 18% of the basin area. The groundwater potential map of the study area has been validated by comparing with data from 159 boreholes scattered throughout the basin.

The Souss region in Morocco is known nationally and internationally for its essential knowledge of traditional herbal medicine and the cultural heritage of nutrition. The endemic species Argania spinosa (L.) Skeels is an important crucial plant used by the local population to treat many diseases and prepare some authentic foods. To identify the therapeutic uses of the Argan tree [Argania spinosa (L.) Skeels] and their benefits in preparing authentic foods, the survey was conducted using semi-structured questionnaires. We have achieved 450 interviews with traditional health practitioners and knowledgeable villagers. In the region of Chtouka Aït Baha and Tiznit (Western Anti-Atlas). In parallel with this survey, we collected some old local manuscripts from conventional practitioners in the region. The data obtained were analyzed using specific ethnobotanical indices such as Use Value (UV), Fidelity Level (FL), and Relative Frequency of Citation (RFC). In parallel, we analyzed the nutritional value of some authentic foods derived the argan oil (Amlou, Tagoulla, and Labsis). All 450 interviewees use the argan oil in food or for the preparation of their authentic foods derived (Amlou, Tagoulla, and Labsis); among them, 100 persons use Argan, in addition to food, in the treatment of various diseases with UV and RFC at 1.94 and 0.22, respectively. Among eight treated diseases by argan tree, the treatment of skin and subcutaneous diseases had a very highly significant value of the FL index (98%). Similarly, the analysis of the manuscripts collected in the study area revealed an ancient therapeutic use of the argan tree. The results also show that the Argan oil extracted from the seed is used to prepare authentic foods with significant nutritional value, especially Amlou.

Remote sensing data proved to be a valuable resource in a variety of earth science applications. Using high-dimensional data with advanced methods such as machine learning algorithms (MLAs), a sub-domain of artificial intelligence, enhances lithological mapping by spectral classification. Support vector machines (SVM) are one of the most popular MLAs with the ability to define non-linear decision boundaries in high-dimensional feature space by solving a quadratic optimization problem. This paper describes a supervised classification method considering SVM for lithological mapping in the region of Souk Arbaa Sahel belonging to the Sidi Ifni inlier, located in southern Morocco (Western Anti-Atlas). The aims of this study were (1) to refine the existing lithological map of this region, and (2) to evaluate and study the performance of the SVM approach by using combined spectral features of Landsat 8 OLI with digital elevation model (DEM) geomorphometric attributes of ALOS/PALSAR data. We performed an SVM classification method to allow the joint use of geomorphometric features and multispectral data of Landsat 8 OLI. The results indicated an overall classification accuracy of 85%. From the results obtained, we can conclude that the classification approach produced an image containing lithological units which easily identified formations such as silt, alluvium, limestone, dolomite, conglomerate, sandstone, rhyolite, andesite, granodiorite, quartzite, lutite, and ignimbrite, coinciding with those already existing on the published geological map. This result confirms the ability of SVM as a supervised learning algorithm for lithological mapping purposes.