Chapter 9
Conclusion: Perspectives of Modelling in the Context of Risk and Uncertainty and Further Research
The book has introduced a variety of methodologies, techniques and algorithms now available for the analyst wishing to model consistently in the context of risk and uncertainty and to best value all quantitative information available to support decision-making. However, important scientific challenges lie ahead. The whole rationale of this book was intended to show that the coupling of probabilistic approaches with large-scale physical-numerical models generates new requirements from applied mathematics, statistics and numerical analysis: it also renews old epistemological debates and decision theory issues. The scientific challenges will be summarised in Section 6.1. More importantly perhaps, practical dissemination of the techniques and methodologies also raises a number of challenges that will be recalled briefly in Section 9.2.
