Deep uncertainties challenge sustainable water-energy systems, particularly in small islands where resource scarcity and isolation amplify vulnerability. Deterministic optimization approaches often fail to capture how the wide range of possible futures can affect system performance and design. This study applies a Decision Making under Deep Uncertainty framework integrating exploratory modeling, multi-energy system optimization, global sensitivity analysis and scenario discovery to assess how uncertainties shape optimal configurations. Using Lampedusa as a case study, we evaluate 25,000 scenarios varying population trajectories, fuel prices, desalination efficiency, and stakeholder preferences. Results show that annual costs and emissions fluctuate substantially depending on future conditions. Two dominant system archetypes emerge: renewable-powered desalination, selected over 90% of scenarios for its consistently favorable cost and emission performance, and water imports, attractive only under low ship emissions and strong environmental priorities. Sensitivity analysis identifies diesel efficiency, fuel price, population influx and desalination performance as the main driver on outcomes, while scenario discovery reveals the combinations of conditions triggering shifts between archetypes. Importantly, several uncertainties substantially affect costs and emissions but do not alter technology adoption, showing that system behavior can be highly sensitive without necessarily being structurally vulnerable. Rather than seeking a single robust design, the framework maps how uncertainty shapes system behavior and under which conditions current plans may face stress or require alternative strategies. While tailored to Lampedusa, the workflow is readily applicable to other small, resource-constrained islands, offering a structured way to explore uncertain futures and support more informed and adaptable water–energy planning.
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