To guarantee port accessibility, navigation approach channels need to be well maintained. Annual dredging efforts to maintain navigable channels may well exceed tens of millions m3 of sediment per year, which results in high recurrent costs for port operators. Quantification of expected siltation rates with process-based numerical models helps to effectively design and optimise approach channels. The setup of such models requires several assumptions and parameter settings which introduce uncertainty in model output. However, traditional Monte Carlo methods to quantify that uncertainty in model output are often too resource-intensive with current standard computer resources to be feasibly applied in coastal engineering projects such as approach channel design. Here, we use an alternative multifidelity approach to estimate the probability density function of channel siltation, at lower computational costs compared to direct Monte Carlo simulation. The idea behind this method is to map the output uncertainty of a faster, but inaccurate model to a preferred high-detailed model. The key requirement is that the faster, low-fidelity model and the detailed high-fidelity model are correlated, and that his correlation can be modelled with a probabilistic function. Since linearity of the correlation is not a requirement, the coarse-grid model can be very inaccurate but still serve as an adequate predictor of the high-fidelity model. In this study we did observe a highly nonlinear correlation, which in our case is explained by underestimation of channel siltation near the surf zone by the coarse model. In the presented multifidelity approach we adopted a combination of quasi-random Monte Carlo simulation and a non-parametric Gaussian process transfer function to estimate the uncertainty of total siltation and spatial patterns of siltation in a port approach channel. We argue that the multifidelity approach is conceptually straightforward and found that it can be used to significantly decrease the costs of probabilistic analysis; in our case we found a 85% decrease compared to direct Monte Carlo simulation. An additional advantage is that the approach allows for a trade-off between precision and efficiency by varying the number of high-fidelity model runs. Therefore, we conclude that the multifidelity framework is a potential powerful alternative for cases in which direct Monte Carlo simulation is infeasible or undesirable.@en

The twofold aim of this paper is to provide an overview of the current state of resilience research with regard to climate change in the social sciences and propose a research agenda. Resilience research among social scientists is characterized by much more diversity today than a few decades ago. Different definitions and understandings of resilience appear in publications during the last 10 years. Resilience research increasingly bears the mark of social constructivism, a relative newcomer compared to the more long-standing tradition of naturalism. There are also approaches that are indebted to both "naturalism" and "constructivism", which, of course, come in many varieties. Based on our overview of recent scholarship, which is far from being exhaustive, we have identified six research avenues that arguably deserve continued attention. They combine naturalist and constructivist insights and approaches so that human agency, reflexivity, and considerations of justice and equity are incorporated into systems thinking research or supplement such research. Ultimately, we believe that the overarching challenge for future research is to ensure that resilience to climate change does not compromise sustainability and considerations of justice (including environmental, climate, and energy justice)..@en

Structures integrated in a grass-covered dike may increase erosion development. Currently, safety assessment methods for flood defences are only applicable for a conventional grass-covered dike and the effects of structures on dike cover erosion are poorly understood. Since many dikes have a road on top, it is important to study the effect of such a road structure on erosion onset during wave overtopping. To investigate this effect, a coupled hydrodynamic–eroison model was developed. The erosion onset caused by overtopping waves was predicted by combining the time-varying bed shear stresses from the hydrodynamic model with a depth-dependent erosion model. The results show that roads on top of a dike increase the erosion of the neighbouring grass cover. This increase in erosion may have a negative impact on dike stability. Therefore, we recommend considering effects of constructions on top of dike profiles during safety assessments. Explicitly, consideration of the roughness transitions in the safety assessments of dikes is recommended.@en

Turbulence is a dominant factor in the design of scour protections downstream of hydraulic structures. For the detailed design phase, numerous tools are available for quantifying turbulence levels. However, the guidance on turbulence for the feasibility and preliminary design stage is sparse. There is a need for tools to quantify turbulence more accurately in the early stages of design, where the designer has a large number of options on the table and has to judge their performance rapidly. We built up a model that consistently describes the energy levels in the main flow and in turbulence, the transfer between them and the dissipation of turbulent kinetic energy. The model was confronted with laboratory data. First performance of the model was satisfactory and several items for further development were identified.@en

The present study aimed to include the turbulence effects derived from a road located over the crest of a dike, in its probabilistic safety assessment. This was done by building two different computation fluid dynamics models (RANS K-); one of a dike with a road on top and one without it. Both models were validated with experimental data collected from the Wave overtopping simulator experiments performed in the Netherlands. These models were used to produce training data sets which were later used for constructing emulators (computationally cheaper models) which allowed to reduce the computational burden from the required stochastic modelling. These new emulators allowed to calculate bottom shear stress time series in different locations along the dike profile. With these time series, it is possible to estimate the potential scouring depth per wave volume routed. These emulators allowed to model different probabilistic overtopping scenarios without running the CFD models again. The results showed that when assessed under extreme climate scenarios, the presence of a road may reduce the dike safety by almost 50% with respect to the case where no road is present. In addition, it is also concluded that the spatial grass quality distribution is a more important factor for determining dike safety than the spatial grass cover thickness. @en