Mohamed Belmahi

The upper Sebou River occupies a strategic territory draining varied mountain reaches in northern Morocco. As such, it is rich in surface water resources and karst springs with important downstream uses. However, the variability of rainfall threatens its water potential, making it highly vulnerable and at risk of desiccation. This study explores rainfall trends and their effects on streamflow and water resource availability. Data from three stations representing the upstream section of the watershed, along with two streamflow series—one for the upper Sebou River (Pont Medz) and the other for the Aïn Timdrine karst spring—cover the period from 1956 to 2018. The methodology employs Mann–Kendall trend tests, Sen’s Slope test, and the Standardized Precipitation Index (SPI) for rainfall series, as well as the Streamflow Drought Index (SDI) for hydrological series. The results demonstrate a decline in rainfall since 1979, significant at the 5% threshold. This trend has an immediate impact on the flow rates of the area’s rivers and karst springs, which have also tended to decline, with a succession of dry years and seasons since 1980. This observation highlights the depletion of water resources of the fragile upper Sebou region in the face of decreasing rainfall and snowfall, compounded by the rampant and unsustainable exploitation of groundwater resources linked to the development of irrigated cash crops in the Middle Atlas Mountains.

This article analyzes the state of water resources in the Guercif Plain (Morocco) under the combined effects of drought and increasing consumption pressures. The study adopts a quantitative and analytical approach based on climatic and hydrological data, demographic information, and Landsat satellite imagery. The main findings reveal pronounced rainfall variability with an overall declining tendency, with drought years accounting for approximately 58% of the observation period. This climatic context has been accompanied by strong interannual fluctuations in the discharge of Oued Melloulou, with a slight long-term declining trend, along with a continuous and accelerating groundwater decline in the Tafrata aquifer at an average rate of 0.98 m per year. The analysis also indicates an estimated urban water deficit approaching 77% under peak demand conditions in 2025. Furthermore, NDVI-based analysis of satellite imagery highlights a marked expansion of irrigated areas in the Guercif Plain, increasing from about 2% of the total plain area in 1985 to approximately 9% in 2020. This vegetation expansion is largely associated with irrigation development, suggesting increasing pressure on groundwater resources rather than recovery linked to rainfall conditions. Overall, the findings raise critical concerns regarding the long-term sustainability of water resources and underscore the need for integrated and adaptive water-management strategies under persistent drought conditions.

The Fez-Meknes region is distinguished by its agricultural vocation and its emergence as a hub in the agro-food industry. This study aims to assess the main crop yield, production, and percentage of the agricultural area within each province of the Fez-Meknes region from 2000 to 2020, based on an...

Exploring the relationship between cereal yield and the remotely sensed normalized difference vegetation index (NDVI) is of great importance to decision-makers and agricultural stakeholders. In this study, an approach based on the Pearson correlation coefficient and linear regression is carried out to reveal the relationship between cereal yield and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data in the Fez-Meknes region of Morocco. The results obtained show strong correlations reaching 0.70 to 0.89 between the NDVI and grain yield. The linear regression model explains 58 to 79% of the variability in yield in regional provinces marked by the importance of cereal cultivation, and 51 to 53% in the mountainous provinces with less agricultural land devoted to major cereals. The regression slopes indicate that a 0.1 increase in the NDVI results in an expected increase in grain yield of 4.9 to 8.7 quintals (q) per ha, with an average of 6.8 q/ha throughout the Fez-Meknes region. The RMSE ranges from 2.12 to 4.96 q/ha. These results are promising in terms of early yield forecasting based on MODIS-NDVI data, and consequently, in terms of grain import planning, especially since the national grain production does not cover the demand. Such remote sensing data are therefore essential for administrations that are in charge of food security decisions.

Exploring the relationship between cereal yield and remotely sensed normalized difference vegetation index (NDVI) is of great importance to decision-makers and agricultural stakeholders. In this study, an approach based on the Pearson correlation coefficient and linear regression method is carried out to reveal the relationship between cereal yield and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data in the Fez-Meknes region of Morocco. The results obtained show strong correlations reaching 0.70 to 0.89 between NDVI and grain yield. The linear regression model explains 58 to 79% of the variability in yield in regional provinces marked by the importance of cereal cultivation, and 51 to 53% in the mountainous provinces with less agricultural land devoted to major cereals. The regression slopes indicate that a 0.1 increase in NDVI results in an expected increase in grain yield of 4.9 to 8.7 quintals (q) per ha, with an average of 6.8 q/ha throughout the Fez-Meknes region. RMSE ranges from 2.12 to 4.96 q/ha. These results are promising in terms of early yield forecasting based on MODIS NDVI data.