Integral Probabilistic Reliability Assessment for Flood Defences: The Impact of Correlations

Since 2017, Dutch flood defences are assessed according to new safety standards. These standards are based on flooding probabilities and rely on several assumptions and approximations. There are concerns that the combination of these assumptions leads to conservative results. Recently computed probabilities of failure are often much higher than expected by dike managers and the outcomes of former assessment methods. This conservative bias results in a large and expensive reinforcement task in the coming years which can be reduced by improving the current assessment procedure. One of the reasons for the current conservatism is the assumption of mutual independence of dike sections and failure mechanisms. Currently, the different elements are assessed independently, while failure mechanisms and failure at different dike sections are likely to occur during the same extreme load event. Furthermore, correlations in space and between different parameters are present within the subsoil characteristics. Neglecting these correlations results in rather high estimations of the failure probabilities. The aim of this thesis is to investigate how correlations affect the reliability assessment of a dike trajectory. To achieve this, an integral, full probabilistic model is developed that enables simultaneous assessment of dike sections and failure mechanisms while accounting for uncertainties and (spatial) correlations within the model input. The model is based on Monte Carlo simulation. The failure probability of a dike trajectory is computed by counting failure if one or more limit state function 푍푗,푘 for failure mechanism 푗 of dike section 푘 returns a negative realisation. Correlations between the model input parameters are provided by means of a Gaussian copula. A particular aspect of the model is the implementation of metamodeling for the assessment of macrostability. This failure mechanism cannot be described by an analytical limit state function that i
Civil Engineering | Hydraulic Engineering | Coastal Engineering