Climate change and socio-economic development result in increasing flood risk which challenges flood risk management policy making and practice. Each situation, however, is different and calls for not only understanding the natural context, but also the socio-economic and cultural context. Only then Flood Risk Management strategies can be designed that are not only 1) fit for purpose but also 2) feasible for local implementation and 3) sustainable into the future. Flood consequences that are accepted in some cultures (fatalist), may not be acceptable in other cultures (controlist). This calls for considering the local normative context in order to understand current differences in policy and practice. More importantly, the design of strategic alternatives for Flood Risk Management into the future should consider this socio-economic and cultural context as well because not every society aims for the same goals in the same proportion, nor is equally willing or capable to implement and maintain sophisticated infrastructure and dedicated institutions. Based on literature on cultural theory and national cultures, we hypothesized that acknowledging socio-economic and cultural differences would allow to better appreciate the rationale of current flood risk management policies and practices in different parts of the world. By analysing cases related to Deltares projects abroad, we explored whether these factors explain the main differences observed. Based on this preliminary exploration, we propose a shortlist of factors to consider when designing future flood risk management strategies tailored to local socio-economic and cultural contexts.

This paper describes a novel sensitivity analysis method, able to handle dependency relationships between model parameters. The starting point is the popular Morris (1991) algorithm, which was initially devised under the assumption of parameter independence. This important limitation is tackled by allowing the user to incorporate dependency information through a copula. The set of model runs obtained using latin hypercube sampling, are then used for deriving appropriate sensitivity measures. Delft3D-WAQ (Deltares, 2010) is a sediment transport model with strong correlations between input parameters. Despite this, the parameter ranking obtained with the newly proposed method is in accordance with the knowledge obtained from expert judgment. However, under the same conditions, the classic Morris method elicits its results from model runs which break the assumptions of the underlying physical processes. This leads to the conclusion that the proposed extension is superior to the classic Morris algorithm and can accommodate a wide range of use cases.