Hydrological modelling is essential for water-resources assessment and climate adaptation planning; however, its application in many African basins is constrained by sparse hydro-meteorological observations, limited monitoring networks, and high uncertainty in groundwater recharge and subsurface-flow processes. This study presents a systematic review of isotope hydrology and its integration into climate-driven hydrological modelling in data-scarce African basins using the PRISMA framework. A total of 61 studies published between 2005 and 2025 were synthesised to evaluate isotope applications, coupled isotope-hydrological modelling approaches, sources of uncertainty, calibration strategies, sensitivity analyses, and emerging machine-learning applications. The review demonstrates that stable and radioactive isotopes (δ¹⁸O, δ²H, ³H, and ¹⁴C) provide critical process-based information that improves groundwater recharge estimation, groundwater age determination, water-source tracing, and hydrological model calibration. Evidence further indicates that coupled isotope-hydrological models, data-assimilation techniques, Bayesian frameworks, and hybrid physical-artificial intelligence approaches can substantially reduce parameter uncertainty and equifinality while enhancing predictive reliability. Despite these advances, widespread implementation remains limited by inadequate isotope datasets, technical capacity constraints, and insufficient monitoring infrastructure. To address these challenges, an integrated isotope-enabled hydrological modelling framework is proposed that combines isotope, hydroclimatic, hydrogeological, remote-sensing, and machine-learning datasets within a unified decision-support system. The framework provides a practical pathway for strengthening groundwater sustainability assessment, climate-impact evaluation, drought preparedness, and climate-resilient water-resources management across data-scarce African basins.
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Salami et al. (2026) studied this question.
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