The aim of this paper is to provide a conceptual basis for the systematic treatment of uncertainty in model-based decision support activities such as policy analysis, integrated assessment and risk assessment. It focuses on the uncertainty perceived from the point of view of those providing information to support policy decisions (i.e., the modellers' view on uncertainty) -uncertainty regarding the analytical outcomes and conclusions of the decision support exercise. Within the regulatory and management sciences, there is neither commonly shared terminology nor full agreement on a typology of uncertainties. Our aim is to synthesise a wide variety of contributions on uncertainty in model-based decision support in order to provide an interdisciplinary theoretical framework for systematic uncertainty analysis. To that end we adopt a general definition of uncertainty as being any deviation from the unachievable ideal of completely deterministic knowledge of the relevant system. We further propose to discriminate among three dimensions of uncertainty: location, level and nature of uncertainty, and we harmonise existing typologies to further detail the concepts behind these three dimensions of uncertainty. We propose an uncertainty matrix as a heuristic tool to classify and report the various dimensions of uncertainty, thereby providing a conceptual framework for better communication among analysts as well as between them and policymakers and stakeholders. Understanding the various dimensions of uncertainty helps in identifying, articulating, and prioritising critical uncertainties, which is a crucial step to more adequate acknowledgement and treatment of uncertainty in decision support endeavours and more focused research on complex, inherently uncertain, policy issues.

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Flood management of the Rhine and Meuse is surrounded by major uncertainties. The central question is then: given the uncertainties, what is the best management strategy? Moreover, flood management cannot be considered independently from other river functions such as nature, agriculture, inland navigation and landscape values. This raises the need for integrated scenarios that consider possible futures in a coherent and consistent way. In the present project a scenario study was carried out in which physical modelling has been combined with socio-cultural theory. The focus of the study was on flood risk management. Existing climate, land use and socio-economic scenarios, as well as water management strategies have been structured using the Perspectives method. This resulted in integrated scenarios for water management, each representing a different view of the future, together with the corresponding water management style. These were put in a scenario matrix with combinations of world views and management styles, where these both match and mis-match. Using a suite of existing modelling tools the implications of each scenario for the water systems were evaluated. Finally, a comparison of different water management styles under different possible futures was made, showing the risk, cost and benefits of different strategies. The scenario analyses demonstrate that-at the scale of the entire Rhine basin-the influence of climate change on extreme floods is much stronger than the influence of land use changes. Flood risk management in the lower river deltas should not fully rely on flood mitigation measures in the upstream basin. It also becomes clear that no flood risk management strategy is superior in all respects and in all circumstances and that safety versus societal costs is really a policy dilemma: win-win situations cannot always be attained. Under changing climate conditions, the present-day type of management in the lower river reaches runs the risk of becoming an expensive attempt to fully control flood risk problems, while trying to avoid real choices, without actually solving the problems in a long-term view.

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