A large part of the Baltic Sea coastline in the north-eastern provinces of Germany (Mecklenburg-Vorpommern and Schleswig-Holstein) is protected by coastal protection dunes, which are constructed and maintained to preserve a quasi-natural beach environment. The latest IPCC report predicts a significant sea level rise even in the Baltic, together with an increase in storm surges within the next decades. Sand dune constructions are particularly affected by these developments, in close connection to the increasing problems of sediment mining for beach nourishment and dune maintenance. In the BMBF research project PADO (Processes and Implications of Dune Breaching at the German Baltic Sea Coast), scientists from Rostock University and RWTH Aachen University investigated together with various partners how constructed sand dunes would fail during a storm surge, focusing on the erosion and the initiation and development of a breach. Therefore, a large-scale field experiment was installed at the beach of Rostock-Warnemünde, which was instrumented and surveyed in high resolution during the storm surge in November 2018, leading to the collapse of the dune, using innovative measurement systems, including terrestrial laser scanning and photogrammetry. The measurements were used to run a numerical model (XBeach) to simulate dune breaching for three different sections of existing sand dunes at the coast of Mecklenburg-Vorpommern. Additional investigations were made to analyse the filling and emptying of the polder areas behind the coastal protection dunes and the consequences of the floods with respect to saltwater intrusion. In this paper, the field experiment and the results from measurements and simulations are compared to one of the real reference dunes, and the transfer of results to a dune breach incident near Rostock in 2019 is discussed.

The design of coastal protection structures requires design parameters that accurately represent the hydrodynamic conditions along the coast. Currently, these input variables are based on univariate probability models, which do not consider the joint probability of water level and statistical wave parameters such as significant wave height. Bivariate probability modeling using copula models offers an alternative. Copulas can be used to describe the dependencies between water level and significant wave height and to compute joint probabilities of occurrence. First, various copulas are fitted to samples of physically consistent combinations of water level and significant wave height extracted from storm surge events along the German Baltic Sea coast of Mecklenburg-Western Pomerania. Next, the most appropriate copula model is used to compute design combinations of water level and significant wave height for selected return periods. The bivariate design parameters are compared with the univariate ones in a simplified design example for wave run-up on a dike. The validation of various models shows that the Frank copula best describes the dependence structure. The bivariate design parameters obtained for the same return periods are lower than those determined using the univariate method. The available data only allow a limited application of the copulas for engineering design in the study area. Nevertheless, copulas have the potential to replace univariate methods for determining design parameters and thus contribute to more reliable and cost-efficient coastal protection structure design.