Agriculture in West Africa faces multiple challenges, such as climate variability, soil degradation, and limited access to reliable agroecological information for agricultural planning. In this context, traditional zonation approaches have often relied solely on rainfall patterns, potentially overlooking critical biophysical factors that influence agricultural productivity. This study presents a comprehensive agroecological zoning approach for Burkina Faso as a case study in West Africa, using multiple biophysical variables and k-means clustering analysis. The methodology integrates climate data from ERA5 reanalysis and TAMSAT satellite precipitation estimates, soil characteristics from the Harmonized World Soil Database, and derived agroclimatic indices for Burkina Faso for the period 1991-2020. Twelve variables, including precipitation, temperature, consecutive dry and wet days, onset and length of growing season, aridity index, and soil water content, were analyzed at 0.25˚ × 0.25˚ spatial resolution. The k-means clustering analysis identified four distinct agroecological zones (AEZs) with unique biophysical characteristics in Burkina Faso. The northern zone (AEZ1) exhibits semi-arid conditions, with longer dry spells and higher temperatures, while the southwestern zone (AEZ4) shows more favorable agricultural conditions with higher rainfall and longer growing seasons. The transitional zones (AEZ2 and AEZ3) display intermediate characteristics reflecting gradual changes in agroclimatic conditions. Comparison with the well-known rainfall-based zonation using the V-measure framework yielded a score of 0.55, indicating that the new AEZs incorporate additional biophysical factors resulting in more nuanced spatial differentiation for Burkina Faso. The methodology demonstrates the value of integrating multiple data sources and analytical approaches to better understand agricultural potential and constraints. This zonation provides a scientific basis for agricultural planning and policy development in Burkina Faso, with potential applications in other regions in West Africa facing similar agricultural challenges.
KeywordsAgroecological Zonesk-Means ClusteringClimate VariabilityAgricultural PlanningBurkina FasoWest Africa
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