A decision-support framework for prioritising climate adaptation in smallholder rice systems: evidence from Uganda

Abstract Smallholder rice production in Uganda is increasingly affected by the combined effects of climate variability and structural production constraints, yet adaptation decisions remain only weakly informed by empirical evidence. This study developed and evaluated an integrated decision-support framework for prioritising climate adaptation strategies across four major rice-growing districts representing Uganda’s principal rice production systems. District-level climate and yield data (1995–2024), household survey data from 384 farmers (2025), and institutional indicators were analysed using panel regression, stochastic frontier analysis (SFA), and a composite Adaptation Priority Index (API). Climate-related moisture stress increased yield variability, while variance decomposition showed that persistent structural differences accounted for a larger share of yield variability than interannual climate fluctuations. SFA further identified substantial recoverable productivity gaps. Integrating climate-risk reduction, efficiency improvement, implementation feasibility, and system co-benefits, the API ranked water control (drainage and supplemental irrigation), stress-tolerant varieties, and soil fertility restoration as the highest-priority adaptation strategies. Monte Carlo simulation and weighting-sensitivity analyses confirmed that these rankings remained robust under plausible parameter and weighting uncertainty. The proposed framework provides a transparent, reproducible, and operational approach for translating climate-impact evidence into adaptation priorities, thereby supporting evidence-based adaptation planning in data-constrained smallholder agricultural systems.