Assessment of the spatio-temporal dynamics of agricultural lands in relation to rainfall variability in the Tadla plain (Morocco)

¹ Research Laboratory Landscape Dynamics, Risks and Heritage, Faculty of Letters and Human Sciences, Sultan Moulay Slimane University, Béni Mellal, Morocco.
² Professor of Geography, Faculty of Letters and Human Sciences, Sultan Moulay Slimane University, Béni Mellal, Morocco.
³ Manager of Farmassist Agricultural Company, specialized in agricultural service operations.

^* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

The Tadla Plain, situated in central Morocco under semi-arid climatic conditions, represents a key agricultural area at the national scale, yet it is highly exposed to climate-related constraints, particularly fluctuations in rainfall and increasing stress on irrigation water resources. Building on earlier findings that documented a 21% reduction in cultivated land between 2013 and 2023, this study examines vegetation dynamics during the subsequent period from 2023 to 2025, marked by a notable recovery in precipitation. Vegetation conditions were evaluated using the Normalized Difference Vegetation Index (NDVI) derived from Landsat 8 imagery, in conjunction with rainfall records obtained from the NASA database. Field surveys were conducted to support and validate the remote sensing analysis. The results indicate a clear improvement in vegetation status across the Tadla Plain, with high-density vegetation areas increasing from 5.9% to 11.4% of the total surface area. In parallel, zones with moderate vegetation cover expanded from 24.6% to 29.2%. These changes closely coincide with a substantial rise in annual rainfall, which increased from an average of 240.38 mm in 2023 to 402.43 mm in 2025. The findings underline the strong dependence of agricultural systems in the Tadla Plain on climatic variability and demonstrate the effectiveness of satellite-based indicators as valuable tools for supporting sustainable land and water resource management.