Land degradation is a worldwide phenomenon that negatively affects the topsoil of agricultural land. The Mediterranean region is the hardest hit by this phenomenon, which is set to increase due to climate change. This study aims to assess the susceptibility of land to degradation under climate change, based on the calculation of the Land Degradation Sensitivity Index (LDI) in the upstream Ouergha catchment in in Northern Morocco (Southern Mediterranean), using Geographic Information Systems (GIS) and the Analytic hierarchy process (AHP) multi-criteria decision analysis (MCDM) method. In this study, 4 main criteria (climate, vegetation, soil and human environment) divided into 15 sub-criteria were used to assess soil sensitivity to degradation. The weight of each criterion was assigned using the AHP method. The degree of soil degradation was classified on a map based on four categories (low, moderate, high and critical). About 14.9% of land is not very sensitive to degradation, while 37.2% of land is highly sensitive to degradation. Vegetation and climate were identified as the main drivers of land degradation (37% and 28% respectively). Climate scenarios for model EC-Earth3-Veg (CMIP6) indicate a significant drop in precipitation in this region, which accelerates soil degradation. The result represents a planning tool that can help decision-makers to take the necessary measures to ensure sustainable soil management in the face of climate change

Objectif de recherche:L’objectif de cet article consiste à évaluer et quantifier les impacts de défrichement sur les sols: La perte de fertilité des sols défrichés a été évaluée à l'aide d'analyses physico-chimiques des sols sous forêt (Chêne vert), et dans des terrains de parcours et les parcelles défrichées Transformées en terres arables depuis longtemps (+10 ans).Méthodologie:La simulation de pluies (avec simulateur simple) a été utilisée pour évaluer les impacts du défrichement et de la mise en culture sur le comportement hydrodynamique du sol. Résultats: Les résultats obtenus montent que la dégradation des forêts, a des conséquences négatives sur le milieu naturel. Premièrement le sol devient instable sous les effets du piétinement du cheptel et les labours successifs. Deuxièmementil y a réduction des réserves du sol, à savoir la matière organique qui baisse de 33,61% de sa teneur initiale, l’augmentation du taux l’azote minéral est passé de 1,61 à 7,73 mg/100g. Troisièmement, les pertes en sols par l'érosion hydrique ont atteint 0,85 t/ha pourune séquence de précipitation de 80 mm h-1 pendant 45 minutes. Les résultats expérimentaux de cette analyse au niveau de la dépression Ain Nokra montrent le rôle non négligeable des écosystèmes forestiers bien conservés dans la protection du sol contre l'érosion hydrique, et dans la conservation des ressources en eau.Originalité/Valeur : Cette étude représente la première simulation de l'érosion au niveau d'Ain Nokra (Moyen Atlas). Sur le plan scientifique, cet article aborde le rôle de la végétation dans la préservation des sols contre l'érosion, ainsi que son impact dans l'enrichissementdu sol en matières organiques

This paper focuses on a quantitative assessment of desertification in the Admer-Ezem basin, using Sentinel-2A satellite images and indices to map the degree of basin-wide desertification in 2023. The methodology is based on the extraction of several spectral indices, such as the normalized difference vegetation index (NDVI), albedo, topsoil grain size index (TGSI) and the modified soil adjusted vegetation index (MSAVI), as well as the tasseled cap transformation (TCT) indices: brightness (TCB), greenness (TCG) and wetness (TCW). Different combinations of these indices were then created and analyzed using linear regression to identify low correlation rates. Based on these results, three characteristic zones were selected: TGSI-Albedo (r = -0.95), TGSI-TCW (r = -0.74) and TCW-TCB (r = -0.73). The resulting map subdivides the region into five categories of desertification: extreme, severe, moderate, low and non-desertified. The results show that the forest is undergoing progressive desertification. In general, and according to the different models used, more than 50% of the area studied is subject to severe to extreme desertification, while less than 30% of the area is classified as no-desertified, or slightly affected. Thanks to the high accuracy of the models used (Area Under the Curve (AUC) from 79 to 83%), this approach proves to be almost optimal for the quantitative analysis and monitoring of desertification in the Moroccan Middle Atlas. Finally, this work can help planners identify the most suitable sites for future forest development.