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 is easily implemented in the Monte Carlo framework. Therefore, metamodels are created by means of Gaussian process regression. This method makes it possible to assess macrostability within an integral, full-probabilistic framework that is able to include interdependencies between e.g. macrostability and piping, within acceptable computation costs. The model is applied to a case study of dike trajectory 43-4, which is located along the Waal between Sprok and Sterreschans, in the east of the Netherlands.  The effects of different plausible correlations have been studied. This research shows that including certain correlations can significantly reduce the assessed failure probabilities, by a factor ten or more in some situations. However, the impact of correlation strongly depends on the situation. The most significant reduction can be achieved for cases in which (1) parameters that play a dominant role in failure of the corresponding mechanism are correlated; (2) the failure probabilities of the different elements are similar, i.e. for a flood defence where failure is not dominated by one dike section or one failure mechanism; and (3) the failure probabilities of the corresponding elements are smaller than approximately 10−3. The model forms a solid, flexible basis that can easily be adapted or extended to improve the understanding about interactions between failure mechanisms, even though some aspects are simplified or neglected. All in all, the conservatism in current safety assessments can be partly solved by considering the interdependencies between mechanisms and dike sections and by approaching a dike trajectory as an integral system.