AquaCrop modelling with frost risk in Southern Africa for bambara groundnut suitability and optimal planting dates

Résumé

Bambara groundnut ( Vigna subterranea ) is a resilient indigenous African legume with potential for improving food and nutrition security in semi-arid environments. However, conventional land suitability assessments often rely on static climatic averages, which fail to capture the dynamic interactions between climate variability and crop phenology. This study proposes a novel, process-based framework that integrates the AquaCrop simulation model with a custom frost-trigger algorithm to map land suitability and optimal planting dates across 5,838 altitude zones in Southern Africa. By simulating crop growth dynamics over 49 consecutive seasons, the framework explicitly accounts for inter-seasonal variability and extreme events, specifically frost and water stress, that are typically overlooked in conventional assessments. A sequential filtering procedure was applied to exclude unsuitable areas based on seasonal rainfall thresholds, risk of crop failure, and variability in water productivity. Findings indicate that October is the most favourable planting month, as later sowings face increased yield reductions due to potential frost risk. Accounting for frost occurrence reduced suitable growing areas by 28%, with refined land-use filtering further reducing viable area by 20%. These results highlight the critical role of dynamic environmental stressors in accurately assessing crop suitability. Ultimately, this framework provides a scalable tool for climate-smart agricultural planning, offering a more robust approach to identifying viable production zones for resilient underutilised crops.

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