Climate variability represents a major threat to agricultural systems, particularly in arid and semi-arid regions such as the Beni-Amir irrigated perimeter, located in the Tadla plain in central Morocco. In this perimeter, olive trees are exposed to multiple environmental and management-related factors that are associated with variations in phenology and vegetation vigor, such as successive drought episodes. This study represents a spatio-temporal assessment of drought impact on olive using satellite- derived vegetation indices from Sentinel-2 imagery and precipitation satellite data from CHIRPS over the period 2015–2024. The Standardized Precipitation Index (SPI-12) was used to identify wet and dry phases over this period. The results indicate an alternation of dry and wet periods between 2015 and 2021, followed by a predominance of dry conditions from September 2021. Over the same period, the time series of the Normalized Difference Vegetation Index (NDVI) and the other vegetation indices reveals marked interannual variability and a progressive degradation of olive tree phenological cycles. A land cover map derived from a supervised support vector machine (SVM) under three classification scenarios achieved high overall accuracies exceeding 94%. Post-classification change detection highlights a substantial reduction in mapped olive-growing areas between 2016 and 2024, with an estimated 72% loss of the initial area. The findings reported in this study indicate that the succession of drought episodes may have contributed to olive grove degradation, including disruptions in phenological cycles and a decline in maximum NDVI values. Even the most resilient olive groves appeared affected following the severe drought period after 2021. The study underscores the usefulness of satellite-derived vegetation indices and drought indicators for the effective monitoring of drought-related stress and supporting improved management practices under climate change.

The objective of this study was to evaluate how different soil types —Calcimagnesic , Fersialitic, Cambisol, Hydromorphic, and Isohumic— influence carbon stocks and key physico-chemical properties in semi-arid irrigated agroecosystems of the Beni Moussa perimeter, Morocco. A total of 85 soil samples (0–20 cm depth) were collected during the 2022–2023 dry season and analyzed for physico-chemical characteristics as well as different carbon fractions. Multiple statistical approaches, including analysis of variance (ANOVA), correlation analysis, and principal component analysis (PCA), were applied to assess variations among soil types and identify the main controlling factors. PCA explained 39.7% of the variance, separating carbonate-rich soils from organic-rich soils. ANOVA revealed significant effects of soil type on SOCS, LCS, and SICS, confirming the strong role of pedological differences in carbon dynamics. Isohumic soils, rich in organic matter, stored the highest SOC (≈11.7 kg C m⁻²) and LC (≈1.2 kg C m⁻²), while Calcimagnesic and Cambisol soils, with high carbonate content, exhibited elevated SICS (~5.2 kg C m⁻²). Our results demonstrate that soil type is a determining factor for carbon stocks and fractions. It is therefore essential to adapt agricultural practices to specific soil properties to maximize carbon sequestration potential and promote sustainable management in semi-arid irrigated regions.