Nature-based flood defences receive increasing interest as a viable option for improving flood safety worldwide. A contemporary case is using the ability of saltmarshes to attenuate waves during storm conditions for strengthening coastal flood defences. To ensure a long-term reinforcement of flood protection, it is important to understand the erosion mechanisms of saltmarshes during storms. One of the critical locations for erosion is at the transition between the saltmarsh and the bare mudflat, often characterized by a vertical step or cliff. These cliffs vary between 0.2 to 2.0 m in height, depending on soil characteristics and local hydrodynamics. However, wave-induced hydrodynamics that controls the (mass) erosion at the saltmarsh cliff are not fully understood. Also the role of saltmarsh vegetation on these near-cliff hydrodynamics are not clearly quantified. In this research, we present high-resolution measurements of wave-induced hydrodynamics at a saltmarsh cliff performed in a scaled wave flume experiment.

The mean overtopping discharge and the overtopping flow parameters related to individual overtopping events are often used to characterize the wave overtopping processes at dikes. Roughness, berms and oblique waves have significant effects on the wave overtopping processes at dikes while these effects are still not fully understood. A 2DV OpenFOAM® model is validated using experimental data for predicting flow velocity and layer thickness at the waterside edge of the crest. The validated numerical model is then applied to investigate the effects of roughness and a berm on the flow velocity and layer thickness. The roughness is modelled by creating protrusions along the waterside slope. Numerical model outcomes indicate that existing empirical formulas underestimate wave overtopping quantities. Introducing a roughness factor to existing empirical formulas leads to better estimates of the flow characteristics. We found that the flow characteristics are more sensitive to the variation of the berm width than to the berm level. Model results demonstrate that existing formulas for predicting the flow characteristics, as derived based on smooth straight slopes, also work well for slopes with a berm. Rayleigh and Weibull distribution functions are derived to estimate the flow velocity and layer thickness with exceedance probabilities below 10%. In order to take oblique waves into account, the 2D numerical model is extended into the 3D model domain. This 3D OpenFOAM® model is validated using measured mean overtopping discharges. The influence of oblique waves on the mean overtopping discharge in combination with a berm is analysed. The numerical model computations confirm that the reductive influence factor of oblique waves is dependant on the berm width.

Design discharges corresponding to large return periods are generally highly uncertain because of the relatively short data set of measured discharges. The uncertainty in these discharge predictions can be decreased by extending the data set of annual maximum discharges with historic flood events. However, efficient model approaches, in terms of computational times and model accuracy, are required to reconstruct historic flood events. In this study, the suitability of three data-driven surrogate models are evaluated, namely: a linear regression model, an artificial neural network and a support vector machine. The Rhine river flood event of 1809 is used as a case study. Although all types of surrogate models are capable of reproducing the maximum discharge during the 1809 flood event, the use of an artificial neural network resulted in the smallest 95% uncertainty interval.