Rock groins in the Elbe Estuary are constructed to maintain proper water levels for navigation and for embankment erosion protection. At certain localities, significant damages to rock groins have been observed due to the primary ship-generated waves. Primary waves are generated along the ship's hull and then propagate toward the river banks and groin fields, appearing in the interaction with the structures as a turbulent overflow phenomenon. Eventually, this overflowing may cause damages mainly to the crest and leeward side of the groins. Since this overflowing is the most pronounced with large primary waves at certain water levels, the estimation of the probabilities of extreme primary waves is a key element for a safe and reliable design of groins. For this goal, nonparametric Bayesian networks (NPBNs) are used here to infer the probability distribution function of the extreme primary wave heights at the tip of a groin in the Elbe Estuary. Results demonstrate the suitability of the NPBN in their prediction. The model framework allows the designer to predict the probabilities of primary ship-generated waves at groins when the information of ship dimensions, nautical parameters, and waterway geometry is available. These probabilities can later be used for design purposes for current and future conditions.

The passage of ships in confined waterways creates a stern wave that can overflow bank protection structures such as groins. This overflow, due to the long-period primary ship-induced waves, can be high in velocity, especially at the lee-side slope of groins, potentially causing significant damage to the structure. This study derives an equation to express overflow velocities, intended as a design tool for groins exposed to these types of waves. A detailed experimental investigation was performed on four physical models of groins with different slopes and stone sizes in the armor layer under the influence of different hydraulic heads. Particle image velocimetry (PIV) was used to measure the flow velocities at the crest and lee sides of the structure. All PIV measurements were performed thrice under free-flow conditions with no initial water level at the lee side of the structure. The depth- and time-averaged flow velocities (Uavg) were extracted from four positions along the lee-side slope and accelerated from 0.7 to 2.2 m/s. A dimensionless equation of the overflow velocities was obtained as a function of the hydraulic head (h), slope (θ), freeboard (Rc), and nominal rock diameter (dn50).

The severity of damages to riverine structures, such as groynes or revetments, across German estuaries has increased in the past years due to the increase in the ship-induced loads. However, few studies can be found in the literature focused on the damage of rock slopes under ship wave attack. In this study, the field data of a rock-armored groyne (lateral slope 1/4 and rocks with nominal diameter Dn50»12.6cm and high density ρs=3.7t/m3) tracked for a year by Melling et al. (2020) is analyzed; the field campaign began after the structure was rebuilt and finished when the structure already presented severe damage. During this field campaign, the incident ship-induced primary waves and water levels were recorded, and laser scans of the groyne armor were taken. Using those field laser scans, damage curves along the life of the structure were derived. Also, ship data from the AIS was retrieved. Then, each increment of the damage (increment of the dimensionless eroded area, ΔSe) was related to a ship-wave event and a passing ship. The most significant variable to describe ΔSe was found to be the primary wave height Hp, while the best explanatory variables for Hp were the partial blockage factor, the ship length and width and the relative velocity of the ship. The shape of the dependence between these variables is also analyzed by pairs using copula space. A clear tail dependence is observed between several pairs. For instance, the pair ΔSe and Hp presents upper tail dependence, meaning that the high values of ΔSe and Hp are more correlated than the smaller ones. This implies that models more complex than Gaussian copula, which is commonly used in Coastal Engineering applications, might be needed to model the probabilistic dependence between the variables.

During the last two decades, increasing vessel size in major German estuaries has led to the significant change of the local loading regime i.e. increased importance of ship-induced waves and currents. As a consequence, the intensity of ship-induced loads has increased considerably, resulting in damage to rock structures such as revetments, training walls, and groynes. Research into the causes of rock structure deterioration by the Federal Waterways Engineering and Research Institute (BAW) has shown that for large ships in relatively narrow waterways, the long-period primary ship wave loading has become the most prescient factor for rock structure damage. Looking into the future, it can be expected that the increase in the vessel dimensions will lead to an increase in the ship-wave loading. For this reason, analysing long-term changing trends of long-period ship waves and vessel speed to understand the wave-structure interaction is of significant importance. In this study, the stochastic characterization of long-period primary wave height, drawdown, and speed of the vessel through the water at Juelssand in the Lower Elbe Estuary was analysed via extreme value analysis and copula modeling, and the bivariate return periods were calculated. The one-parameter bivariate copula was utilized to analyse the data. The dependence pattern between the variables was investigated using five parametric copula families: Gaussian, Gumbel, Clayton, Frank, and student's t.