Currently, the effect of dike breaches on downstream discharge partitioning and flood risk is not addressed in flood safety assessments. In a bifurcating river system, a dike breach may cause overland flows which can change downstream flood risk and discharge partitioning. This study examines how dike breaches and overflow affect overland flow patterns and discharges of the rivers of the Rhine delta. For extreme discharges, an increase in flood risk along the river branch with the smallest discharge capacity was found, while flood risk along the other river branches was reduced. Therefore, dike breaches and resulting overland flow patterns must be included in flood safety assessments.

Grid shape (curvilinear/structured versus triangular/unstructured) and grid size affect model output. In this study structured, unstructured and hybrid grids with a high and low resolution were compared. As a case study, we use the Waal River (with main channel and floodplains). We studied simulated water levels using the six grids, considering equal main channel friction, which enabled to study the isolated effects of grid shape and size. The spread in simulated water levels was found to be rather large with a maximum deviation of 78 cm. Therefore, calibration was performed such that simulated water levels resembled measured water levels by adjusting the main channel friction. This enabled us to draw conclusions on the choice of optimal usage of the grids in engineering studies. Bathymetry accuracy and numerical friction, both as a result of grid resolution, and numerical viscosity as a result of grid shape play a vital role. The analysis shows that unstructured grids are affected most by the calibration which is reflected in the wide spreading of calibrated friction values. From the six grids studied, the hybrid grid with curvilinear grid cells in the main channel and triangular grid cells in the floodplain is recommended for hydraulic modelling since computation time is low, while model output shows sufficient accuracy.

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-erosion 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.Electronic supplementary material The online version of this article (https://doi

Two dimensional hydraulic models are useful to reconstruct maximum discharges and uncertainties of historic flood events. Since many model runs are needed to include the effects of uncertain input parameters, a sophisticated 2D model is not applicable due to computational time. Therefore, this papers studies whether a lower-fidelity model can be used instead. The presented methodological framework shows that a 1D-2D coupled model is capable of simulating maximum discharges with high accuracy in only a fraction of the calculation time needed for the high-fidelity model. Therefore, the lower-fidelity model is used to perform the sensitivity analysis. Multiple Linear Regression analysis and the computation of the Sobol' indices are used to apportion the model output variance to the most influential input parameters. We used the 1926 flood of the Rhine river as a case study and found that the roughness of grassland areas was by far the most influential parameter.

The uncertainty in flood frequency relations can be decreased by adding reconstructed historic flood events to the data set of measured annual maximum discharges. This study shows that an artificial neural network trained with a 1‐D/2‐D coupled hydraulic model is capable of reconstructing river floods with multiple dike breaches and inundations of the hinterland with high accuracy. The benefit of an artificial neural network is that it reduces computational times. With this network, the maximum discharge of the 1809 flood event of the Rhine River and its 95% confidence interval was reconstructed. The study shows that the trained artificial neural network is capable of reproducing the behavior of the hydraulic model correctly. The maximum discharge during the flood event was predicted with high accuracy even though the underlying input data are, due to the fact that the event occurred more than 200 years ago, uncertain. The confidence interval of the prediction was reduced by 43% compared to earlier predictions that did not use hydraulic models.