Uncertainty, sensitivity and scenario analysis: how do they fit together?

Session J5. Advances and applications in decision making in the face of multiple plausible futuresDealing with uncertainty is becoming increasingly important in model-based decision support. Various methods have been developed in order to do this, including uncertainty, sensitivity and scenario analysis. Although these different methods serve their purpose, the availability of a large number of methods can make it difficult for practitioners to understand the similarities and differences between them and when the use of one is more suitable than another, resulting in confusion. In addition, researchers often identify with belonging to a group dealing with a particular approach, which can lead to a lack of crossfertilisation and understanding. In order to assist with bridging the gap between researchers working on different approaches to dealing with uncertainty and eliminate confusion for practitioners, the objective of this paper is to examine the relationship between uncertainty, sensitivity and scenario analysis in the context of model-based decision support, and to take the first steps towards establishing common ground between these methods and assess the contexts under which they are most suitable. This is achieved by conceptualising the various methods as different approaches to “sampling” the hyperspace of model inputs, although this is done from different perspectives and for different ends (Figure 1). It is therefore also necessary to think about the assumptions each method is making about the space being explored, and there are benefits to be gained in thinking about how best to sample the space for each purpose. The approaches identified in this conference paper provide a first level of coarse characterisations. Further refinements in categorisation is possible (with the differentiation between narrative and stress testing scenarios as a first example), and likely to be useful. There are connections to be made to other disciplines, such as philosophy and decision theory, regarding the assumptions each method makes.H.R. Maier, J.H.A. Guillaume, C. McPhail, S. Westra, J.H. Kwakkel, S. Razavi, H. van Delden, M.A. Thyer, S.A. Culley and A.J. Jakema

Relating the microscopic rules in coalescence-fragmentation models to the macroscopic cluster size distributions which emerge

Coalescence-fragmentation problems are of great interest across the physical, biological, and recently social sciences. They are typically studied from the perspective of the rate equations, at the heart of such models are the rules used for coalescence and fragmentation. Here we discuss how changes in these microscopic rules affect the macroscopic cluster-size distribution which emerges from the solution to the rate equation. More generally, our work elucidates the crucial role that the fragmentation rule can play in such dynamical grouping models. We focus on two well-known models whose fragmentation rules lie at opposite extremes setting the models within the broader context of binary coalescence-fragmentation models. Further, we provide a range of generalizations and new analytic results for a well-known model of social group formation [V. M. Eguiluz and M. G. Zimmermann, Phys. Rev. Lett. 85, 5659 (2000)]. We develop analytic perturbation treatment of the original model, and extend the mathematical to the treatment of growing and declining populations

Application of an Adaptive Method for Integrated Assessment of Water Allocation Issues in the Namoi River Catchment, Australia

Integrated Assessment is increasingly being applied to manage natural resource problems internationally. The development of Integrated Assessment models requires application of an adaptive process of model development, incorporating both stakeholder and scientific knowledge in model development. Such a process should allow the development of trust between stakeholders and scientists to help overcome conflicts arising from model application. This paper outlines one such adaptive approach to Integrated Assessment modelling. It examines an integrated assessment model which has been developed using this process to assess long term outcomes of management options for water allocation in the Namoi River catchment, Australia. The development of this tool has been undertaken using an iterative approach with key stakeholders. The approach embraces collaboration with relevant stakeholder groups on the issues to be addressed by the model (conceptualisation, regional discretisation, system knowledge, scenario framing and results) and preferred future directions of model development. A key aspect of the model framework is that it has been developed to be sufficiently general for reapplication and extension to a wide range of water allocation issues in other catchments. Lessons are drawn from this experience in framework development for the field of integrated assessment

Participatory Modelling in Natural Resource Management: A Comparison of Four Case Studies

The need to understand what might constitute best practice in participatory methods for resource management is becoming ever more important as the requirement for a high level of participation becomes prescribed in the environmental directives of the EU and elsewhere. Since there are numerous potential stakeholders who may participate, various different goals of participation and many potential participatory methods designed to achieve them, there is a need for better understanding of how the methods can be practicably applied to particular stakeholders and for what purpose. As input into this process, this paper presents an overview of four natural resource management projects carried out using participatory modelling methods involving stakeholders in the co-design and social learning of management solutions. From these case studies, a description is elicited of the different types of participatory process structures adopted, as well as an analysis of the influences behind the selection of stakeholders and their level of involvement. Six influences in the design of such structures are identified and illustrated with examples: project goals, democratic participatory goals, existing power structures, stakeholder numbers, researchers’ normative beliefs and the scale at which decisions need to be supported. These influences place limits on the freedom of practitioners to develop the type of processes they might otherwise intend. Classification of the process structures according to the level of involvement of stakeholders and their scale of action leads to a discussion about a particular problem of co-design processes: a scale of action mismatch. That is, some process structures, due to the influences mentioned above, end up not involving all the necessary decision makers in the co-design of management solutions. As a result, there has to be additional methods employed to ensure that the results of co-design, i.e. a set of management options, can be passed on to and adopted by excluded decision makers. The paper concludes by briefly looking at examples of possible methods, such as process extensions, e.g., consultation meetings and information campaigns, and the adoption of institutional safeguards