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Developing fresh water supply strategies for the long term needs to take into account the fact that the future is deeply uncertain. Not only the extent of climate change and the extent and nature of its impacts are unknown, also socio-economic conditions may change in unpredictable ways, as well as social preferences. Often, it is not possible to find solid ground for estimating probabilities for the relevant range of imaginable possible future developments. Yet, some of these may have profound impacts and consequences for society which could be reduced by timely proactive adaptation. In response to these and similar challenges, various approaches, methods and techniques have been proposed and are being developed to specifically address long-term strategy development under so-called deep uncertainty. This paper, first, offers a brief overview of developments in the field of planning under (deep) uncertainty. Next, we illustrate application of three different approaches to fresh water provision planning under uncertainty in case studies in the Netherlands: a resilience approach, oriented to (re) designing fresh water systems in such a way that they will be less vulnerable, resp. will be able to recover easily from future disturbances; a robustness approach, oriented to quantitative assessment of system performance for various system configurations (adaptation options) under a range of external disturbances, and an exploratory modeling approach, developed to explore policy effectiveness and system operation under a very wide set of assumptions about future conditions.

The contribution of nuclear power to a sustainable energy future is a contested issue. This paper presents a critical review of an attempt to objectify this debate through the calculation of the external costs of a potential large-scale nuclear accident in the ExternE project. A careful dissection of the ExternE approach resulted in a list of 30 calculation steps and assumptions, from which the 6 most contentious ones were selected through a stakeholder internet survey. The policy robustness and relevance of these key assumptions were then assessed in a workshop using the concept of a ‘pedigree of knowledge’. Overall, the workshop outcomes revealed the stakeholder and expert panel's scepticism about the assumptions made: generally these were considered not very plausible, subjected to disagreement, and to a large extent inspired by contextual factors. Such criticism indicates a limited validity and useability of the calculated nuclear accident externality as a trustworthy sustainability indicator. Furthermore, it is our contention that the ExternE project could benefit greatly – in terms of gaining public trust – from employing highly visible procedures of extended peer review such as the pedigree assessment applied to our specific case of the external costs of a potential large-scale nuclear accident.

Communication across the science-policy interface is complicated by uncertainty and ignorance associated with predictions on which to base policies. The international symposium ''Uncertainty and Precaution in Environmental Management'' (UPEM) addressed the philosophy, approaches and scientific tools associated with the analysis and communication of uncertainty and ignorance to decisions makers in relation to the Precautionary Principle. This paper presents a sample of highlights and insights of UPEM of relevance to the environmental modeling communities. Key insights include: (1) Systematic long-term monitoring and learning are essential. (2) More attention is needed for model structure uncertainty and equifinality. (3) Explicit value articulation in environmental assessment is essential. (4) Sophisticated uncertainty assessment and Quality Assurance methods-such as the Walker et al. conceptual uncertainty framework, NUSAP, and codes of uncertainty-explicit modeling practice from RIVM and EPA-are now available and on their way of becoming main stream. (5) There is a wide range of precautionary interventions (a ban is not the only option). (6) Legal and Ethical dimensions of precaution-such as liability, burden of proof, inter- and intra generational equity-require more thought. (7) The problems that developing countries face in implementing the Precautionary Principle need more attention.

Dankel, D. J., Aps, R., Padda, G., Röckmann, C., van der Sluijs, J. P., Wilson, D. C., and Degnbol, P. 2012. Advice under uncertainty in the marine system. – ICES Journal of Marine Science, 69: 3–7. There is some uncertainty in the fisheries science–policy interface. Although progress has been made towards more transparency and participation in fisheries science in ICES Areas, routine use of state-of-the-art quantitative and qualitative tools to address uncertainty systematically is still lacking. Fisheries science that gives advice to policy-making is plagued by uncertainties; the stakes of the policies are high and value-laden and need therefore to be treated as an example of “post-normal science” (PNS). To achieve robust governance, understanding of the characteristics and implications of the scientific uncertainties for management strategies need to come to the centre of the table. This can be achieved using state-of-the-art tools such as pedigree matrices and uncertainty matrices, as developed by PNS scholars and used in similar science–policy arenas on other complex issues. An explicit extension of the peer community within maritime systems will be required to put these new tools in place. These new competences become even more important as many countries within the ICES Area are now embarking on new policies.

This article discusses recent experiences with the Numeral Unit Spread Assessment Pedigree (NUSAP) system for multidimensional uncertainty assessment, based on four case studies that vary in complexity. We show that the NUSAP method is applicable not only to relatively simple calculation schemes but also to complex models in a meaningful way and that NUSAP is useful to assess not only parameter uncertainty but also (model) assumptions. A diagnostic diagram can be used to synthesize results of quantitative analysis of parameter sensitivity and qualitative review (pedigree analysis) of parameter strength. It provides an analytic tool to prioritize uncertainties according to quantitative and qualitative insights in the limitations of available knowledge. We show that extension of the pedigree scheme to include societal dimensions of uncertainty, such as problem framing and value-laden assumptions, further promotes reflexivity and collective learning. When used in a deliberative setting, NUSAP pedigree assessment has the potential to foster a deeper social debate and a negotiated management of complex environmental problems.

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.

Integrated Assessment Models (IAMs) have been widely used in environmental policy making because they simulate natural and socio-economic systems by integrating knowledge derived from a wide range of disciplines. The current IAMs have been found to be limited due to their inability to display both the value-laden nature of the assumptions that underlie the model and the uncertainties in their outputs. A Post-Normal Science approach is required for dealing with these issues, involving participation of ‘extended peer communities’ providing their ‘extended facts’.

Over the past few decades Integrated Assessment (IA) has emerged as an approach to link knowledge and action in a way that is suitable to accommodate uncertainties, complexities and value diversities of global environmental risks. Responding to the complex nature of the climate problem and to the changing role of climate change in the international climate policy process, the scientific community has started to include stakeholder knowledge and perspectives in their assessments. Participatory Integrated Assessment (PIA) is in its early stage of development. Methodology varies strongly across PIA projects. This paper analyzes four recent IA projects of climate change that included knowledge or perspectives from stakeholders in one-way or another. Approaches and methods used turn out to differ in whether stakeholders are involved actively or passively, whether the approach is bottom-up or top-down, and whether the different functions in the IA process are open or closed to stakeholder input. Also, differences can be seen in the degree to which boundaries are pre-set that limit the roles and domains of competencies attributed to each scientific or non-scientific participant (so-called boundary work). The paper discusses pros and cons of the various approaches identified, and outlines heuristics and considerations to assist those who plan, design or fund new IA processes with stakeholder input on what approaches best to choose in view of the objectives for stakeholder involvement, in view of the role that the IA plays in the overall risk management process and in view of considerations regarding boundary work.

This paper discusses recent experiences with the NUSAP system for multidimensional uncertainty assessment, based on case studies that vary in complexity. We show that the NUSAP method, and especially the pedigree analysis part of it, is useful to assess not only parameter uncertainty but also to systematically reflect upon (model) assumptions and problem frames. A diagnostic diagram can be used to synthesize results of quantitative and qualitative analysis. It provides an analytic tool to prioritize uncertainties according to quantitative and qualitative insights in the limitations of available knowledge. We further show that extension of the pedigree scheme to include societal dimensions of uncertainty, such as problem framing and value-laden assumptions, further promotes reflexivity and collective learning. When used in a deliberative setting, NUSAP pedigree assessment has the potential to foster a deeper social debate and a negotiated management of complex environmental problems.

When analysts do model-based scientific assessments of complex environmental problems, they have to make many assumptions. This inevitably involves – to some degree – subjective judgements by the analysts. Although the potential value-ladenness of model-based assessments has been extensively problematized in literature, this has not so far led to a systematic strategy for analyzing this value-ladenness. In this article, a new method is presented to identify, review, and prioritize assumptions in order to assess the potential value-ladenness of important assumptions and to deal with these potentially value-laden assumptions in an explicit and transparent manner. The potential value-ladenness of the assumptions is analyzed using a so-called pedigree matrix. The matrix addresses epistemic (general and discipline-bound) and non-epistemic (socio-political and practical) values. The method can be applied by the analysts doing the assessment in collaboration with peers and stakeholders or by external reviewers. Here, the method is illustrated for the modelling chain that was used to calculate the indicator ‘death and emergency hospital admittances due to the exposure to ozone’ in the Fifth Dutch Environmental Outlook. The weakest links of the calculation chain were identified through a workshop. This method for the analysis of assumptions enables the analysts to make conscious, well-underpinned, transparent choices, and pinpoints the issues in the chain that are important to communicate to the audience of the assessment report.