In arid and semi-arid regions, agriculture is an important element of the national economy, but this sector is a large consumer of water. In a context of high pressure on water resources, appropriate management is required. In semi-arid, intensive agricultural systems, such as the Tadla irrigated perimeter in central Morocco, a large amount of water is lost by evapotranspiration (ET), and farmers need an effective decision support system for good irrigation management. The main objective of this study was to combine a high spatial resolution Sentinel-2 satellite and meteorological data for estimating crop water requirements in the irrigated perimeter of Tadla and qualifying its irrigation strategy. The dual approach of the FAO-56 (Food and Agriculture Organization) model, based on the modulation of evaporative demand, was used for the estimation of crop water requirements. Sentinel-2A temporal images were used for crop type mapping and deriving the basal crop coefficient (Kcb) based on NDVI data. Meteorological data were also used in crop water requirement simulation, using SAMIR (satellite monitoring of irrigation) software. The results allowed for the spatialization of crop water requirements on a large area of irrigated crops during the 2016–2017 agricultural season. In general, the crops’ requirement for water is at its maximum during the months of March and April, and the critical period starts from February for most crops. Maps of water requirements were developed. They showed the variability over time of crop development and their estimated water requirements. The results obtained constitute an important indicator of how water should be distributed over the area in order to improve the efficiency of the irrigation scheduling strategy.

Lineament mapping is a very important step in geological studies and mineral exploration, with the evolution of remote sensing, processing methods as well as the availability of several optical and radar satellite data, lineaments can be detected without using traditional methods. The objective of this work is to recommend the most suitable data for lineaments to be used in the field of geological science, by comparing the performance of three different RADAR data, namely ALOS PALSAR (The Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar), Radarsat-1 and Sentinel-1 for automatic lineament extraction using a combination of edge detection and line linking algorithms. The methodology consists to link between the length, number, orientation and density of lineaments with surface characteristics such as the slope, faults, lithology, discontinuities and mineral veins. The results obtained show that the extracted lineaments from Sentinel-1 VH polarization have a better correlation with geological units, tectonic system direction, as well as shading and slope maps, which is due to the effectiveness of VH polarization, which is independent of soil properties compared to the other polarizations that have shown an overestimation of the lineaments.

The progression and refinement of remote sensing techniques now allow the extraction of geological lineaments without traditional methods. This study aims to detect lineaments using Synthetic Aperture Radar (SAR) data from three sensors with different bands: Alos-Palsar, Radarsat-1, and Sentinel-1. Automatic lineament extraction is performed by combining two different parameters along with the Palsar Digital Elevation Model in order to recommend the most powerful sensor for this task. The methodology involves relating the length, number, orientation, and density of lineaments to surface features such as slope, lithology, and discontinuities. The results of this evaluation show that the lineaments obtained of both polarizations of sentinel correlate better with geological units, the orientation of the tectonic system, shadow and slope maps. This is attributable to the high efficiency of VH polarization, which is not dependent on soil characteristics, in comparison with other polarizations that overestimated lineaments with different directions.

The copper belt of Anti-Atlas is recognized with several mineral occurrences of Cu, Zn, Mn, Ag, Au, and iron. We used ASTER and OLI in lithological and mineral detection and mapping. The lithological mapping was performed using principal components analysis (PCA), minimum noise fraction (MNF), and two classifiers: maximum likelihood (ML) and support vector machine (SVM). The hydrothermally altered zones were detected based on ASTER VNIR/SWIR bands by the integration of Ninomiya indices and constrained energy minimization (CEM) algorithm. In our study area, the enhanced band combinations of ASTER MNF1, PC4, and PC2 and OLI MNF1, PC5, and PC3 were applied for lithological discrimination. The OLI and ML classification shows the best lithological mapping accuracy with an overall accuracy of 91.74% and a 0.90 Kappa coefficient, followed by SVM with an overall accuracy of 88.82% and a 0.86 Kappa coefficient using the same sensor. The hydrothermal alteration mapping reveals alunite, chlorite, calcite, epidote, illite, kaolinite, montmorillonite, muscovite, and pyrophyllite minerals, principally in phyllic and argillic altered areas. The adopted methodology for lithological and mineralogical mapping can be used in other regions with similar criteria to the study area.

This study proposes a segmentation & GPLM framework to estimate nonstationary rating curves, and their uncertainties at the Tamgnounte hydrometric station, Moroc-co. Based on 176 stage discharge gaugings from 2000 to 2020, a residual based PELT & CROPS procedure was first used to detect homogeneous periods, and GPLM was then fitted independently, within each segment. Results identified robust changepoints at positions 40, 80, and 105, while an additional changepoint at 150 was detected only under a lower CROPS penalty range. Segment specific GPLM calibrations showed sat-isfactory fits, with most observations within the 95% posterior predictive intervals and residuals generally centered around zero. These results confirm the nonstationarity of the stage discharge relationship and support the use of one rating curve per homoge neous period rather than a single global curve.