Evidence-Based Expert Judgment in Flood Risk

Abstract

This dissertation investigates the role of structured expert judgment in quantifying uncertainties central to flood risk assessments, particularly for engineered flood defense systems. Flood risk in the Netherlands involves rare events with high consequences that cannot adequately be quantified with empirical data alone. As an alternative to the traditional approach of physics-based modeling, this research explores the use of expert judgment to address these uncertainties. Through the Classical Model (Cooke's Method), expert estimates of uncertainty are evaluated and combined with the aim of improving the credibility of failure probability estimates. Four key research questions are explored: 1) the performance of statistical tests and distributions in the Classical Model, 2) the accuracy of expert estimates for different types of uncertainties related to flood defense safety, 3) the integration of expert judgment into a Bayesian framework to reduce uncertainty in hydrological extremes, and 4) the quantification of statistical dependence through expert judgment. The findings show that while structured expert judgment effectively addresses certain types of uncertainty and dependence, its accuracy depends on the nature of the variables and the methods used to process expert data. This research demonstrates several methods to incorporate expert judgment in flood risk modeling, offering insights, tools, and recommendations for future studies and practitioners.