Large areas of the world are protected by flood defence systems. A common part of flood defence systems is a levee with grass cover, with the primary function to protect hinterland against floods. Waveovertopping might lead to erosion of the grass cover, followed by erosion of the inner slope and potentially levee breaching. The wave overtopping simulator (WOS) was developed for full-scale and insitu testing of the erosional resistance of levees against wave overtopping. The first experiment with this simulator was carried out in 2007 and more followed. However, the data gathered during these overtopping experiments has always been considered on individual experiment scale or in small subsets, exception being the Cumulative Overload method. The experiments proved to be difficult to reproduce, seemingly identical experiments gave different results. The objective of this thesis is to combine WOS data and multiple grass erosion models to make a prediction for the failure of the grass cover. Key features that determine the prediction of failure are the location and moment of failure. Therefore, these are included in the main research question, which is identified as: How can grass erosion models and WOS experiment data be combined in a new method to generate a prediction of the moment and location of the grass cover failure due to wave overtopping? A literature study on grass erosion and grass erosion provides the basis for modelling grass erosion, a review of combination techniques gives insight in combining results for a prediction. A selection of models is discussed and used for setting up a prediction method. These include three flow-based models which are semi-realistic simplified representations and time-independent over a single overtopping event: Cumulative Overload Method, Analytical Grass Erosion Model and Dean Stream Power. These models are, where required, adjusted to model grass cover failure and to comply with identical hydrodynamic input. A fourth model, the Wave Impact Approach, is an impact-based approach. Each model is calibrated on each WOS experiment, creating a set of calibrated models, which function as the set of predictors. The number of predictors equals the number of models times the number of experiments. During calibration, the moment of failure has been traced back using the control list of the WOS, and vice-versa, resulting in a moment during the experiment at which the grass cover failed. Detailed review of all factual reports on WOS experiments and the nature of the grass erosion models highlighted the need for a locationdependent resistance parameter to determine the location of failure. Therefore, calibration was based on a location-depended resistance parameter; critical flow velocity for the flow-based models and critical pressure for the impact based model. This set of predictors has been used to create a set of predictions for each of the five validation experiments, input being the geometry, loading and initial condition of the slope. The initial condition given by a registration of anomalies to the average grass cover. Failure is determined by vote and averaging. After validation, none of the final predictions proved to be fully correct. Meaning that none of the final predictions correctly indicated the location and moment of the first grass cover failure. Despite this, in four of the five validations at least one correct failure location was indicated when considering the specific anomalies. The main shortcoming is concluded to be the prediction of number of waves until grass cover failure. Based on this research and given a certain average grass cover quality, it is concluded that the resistance against grass erosion by wave overtopping is described by resistance against erosion of anomalies. For at least 22 of 28 sections in the dataset, grass cover failure occurred at an anomaly of the average grass cover. No grass cover failures occurred related to the average grass quality. Especially mole activity showed a significant 46% decrease in the averaged calibrated critical flow velocity with relative to that for the average grass cover. This leads to the conclusion that design and safety assessments should include conditions other than the average grass quality. For future research a method is recommended that divides mole activity into classes, based on certain characteristics. Each class distinguishable by unique combination of properties and assigned a resistance against erosion. For design, the probability of occurrence of each class must be determined and combined with the corresponding influence on the resistance against erosion. For assessment, an inventory or representative sample of animal activity must be available to asses if the occurrences of animal activity are within the design requirements.

Internal erosion is a frequent cause of dike failure, also known as piping or backward erosion. Uplift is considered a submechanism of internal erosion, together with heave and piping, where all three submechanisms must occur for the dike to reach a failure condition. The principle of the uplift phenomenon is straightforward: it occurs when high pore water pressures in the aquifer lift the cover layer, which is located at ground surface. If the pressure is great enough, the cover layer begins to float ('opdrijven'), and may also bulge ('opbollen') or crack ('opbarsten'). Currently, the assessment for uplift is based on a vertical equilibrium, which relates to a floating condition of the cover layer. The forming of an exit point for concentrated seepage is presumed to happen simultaneously with the increase in uplift pressure and is therefore not explicitly considered in the current assessment. This thesis aimed to investigate in what way the uplift assessment may be improved, both to describe the complex behavior better and to decrease the need for costly countermeasures. The evaluation of uplift was conducted in two parts: by making explicit what the causes of uncertainty are in the current assessment, as well as by proposing a new model to describe the complete uplift behavior better. It is recommended to evaluate the ‘floating’ and ‘bulging-cracking’ phases directly. In the ‘bulging-cracking’ phase, the forming of an exit point can either occur by a tension or shear failure.

Coral reefs are degrading across the entire Great Barrier Reef. Rehabilitation of the Great Barrier Reef is crucial for Australia, both socially and economically because it provides $6 billion in revenue and 63,000 jobs. The Queensland state government issued a challenge within the "Small Business Innovation Research" program to quickly restore ecological functions provided by the reef. Van Oord and CSIRO participated in this challenge by testing a concept designed to scale-up rehabilitation efforts. This concept involves rehabilitation of the reef by increasing the number of larvae deployed onto the reef. To achieve this, coral-spawn slicks should be collected from areas with healthy coral populations that show a redundancy of embryos. During transport, these slicks should then be stimulated to grow into settlement competent larvae. Subsequently, they can be deployed at a degraded coral reef. The collection phase should be executed with pumps to reach considerable volumes of coral embryos for significant ecological scale. Unfortunately, the mortality rate of coral embryos due to pumping is so far unknown, yet crucial to determine. Therefore, the objective of this research is to develop a method for designing a pumping system that can pump coral embryos and larvae into a vessel-based container or hopper with maximal survival rates.
To achieve this objective, the strength of coral embryos and larvae as well as the stressors in a pumping system are investigated. In order to design and optimise the pumping process for survival, it is useful to have a framework that estimates the balance between strength of coral embryos and larvae and stressors. In literature, comparable strength and stress balances are known in, for example, thermal stress onto corals. The cause of failure (or mortality) is a combination between the strength, the exposed stress (or load) for a certain period of time and the capability to regain strength. Failure happens when the strength cannot withstand the stress (or load). These failure effects are also described through threshold limit values (TLV) which indicate a limit that the stresses may not exceed. Examples of such limits are time weighted average, short-term exposure limit and ceiling limit. Within the design of a pumping system, these values are expected to be acute (e.g. in the pump) and chronic stress (e.g. in the pipeline). In order to distinguish between pumping systems, the stressors in the system can be calculated by using tools such as a mathematical model.

The coral life cycle commences with gametes that contain eggs which are fertilised in the slick at the ocean surface, before developing into embryos. Because the buoyancy of coral embryos is positive until 36h following spawning, dispersion is limited. Hence, they are easiest collected within this period of time. The pumping related strength of coral embryos and larvae is therefore investigated in this research. The assumption is made that the strength of the embryos and larvae differ in the first period following spawning. In order to gain insight in the strength limits of coral embryos and larvae within this period, strength tests are executed. During the mass-spawning event in November 2018, fertilised eggs were collected and used in a Couette-rheometer test at the Heron Island Research Station. These tests consist of a cylinder rotating at different speeds in a container filled with water and embryos. Due to the rotation of the cylinder, the coral embryos and larvae experience stress. The living coral embryos are counted before and after each experiment by use of a microscope experiment in order to define the survival rate. After 5-7 hours the embryos have developed a considerable strength (larger than can be applied by the Couette-Rheometer). Therefore, it is recommended to start the collection process after 5-7 hours following spawning. Nevertheless, the tests do not define the exact strength of the embryos. Hence, it is advisable to investigate the exact strength in further research.

To design a pumping system that can pump coral embryos and larvae with low mortality, the stressors in the system should be minimal. The main technical criteria of the pumping system include low shear stresses, low-pressure fluctuations and low flow accelerations. Practical criteria such as availability, scalability and handling should also be considered in the design. A mathematical model was designed to calculate the previously described factors by calculating the magnitude of the stressors in a pumping system. Based on the model, it can be concluded that the pipeline configuration of a coral slick collection system should contain minimum pipe length, maximum diameter, minimal surface to encounter (e.g. bends and connections), low rpm and flow velocities and submerged in- and outflows openings.

Laboratory tests in the Netherlands and field tests in Australia have been executed in order to validate the relation between the strength of coral embryos and larvae and stressors in a pumping system. During laboratory tests, pumping system aspects that contribute most to damage have been investigated, and potential practical issues have been identified. Damage rates were estimated for different pumps and pipeline configurations using different proxies such as, hydrogell balls, peas, berries and fish eggs. From these tests, the Hidrostal and Diaphragm pump resulted in low damage rates and were selected to be applied during the field tests. Additionally, a skimmer (intake) to collect the floating particles was designed and tested, both in the laboratory as well as the field.

The field test has been executed in the Southern Great Barrier Reef around the Heron and Wistari reef. Currently, this part of the reef boasts the highest level of coral cover throughout the entire reef, and is almost at its historical maximum. Therefore, it was chosen as research location because of its expected large supply of coral spawn. The main goal of the field study was to investigate the possibility to pump coral embryos following the mass spawning in November 2018. The experimental setup consisted of a tug vessel with two pumping systems, each with a different pump (i.e. the Hidrostal and Diaphragm pump) and the same configuration. A total of total twelve tanks was used for cultivation of which six plastic and six steel. The total number of living coral embryos that have been pumped was approximately 29 million from which 19% developed into competent larvae within five days. The competent larvae were pumped through the same system to investigate their survival rate, which was around 88%. This indicates that deployment of larvae onto degraded reefs should be possible by pumping without much loss and that coral larvae are less fragile compared to coral embryos.

The objective of this research was to develop a method for designing a pumping system that can pump coral eggs, embryos or larvae, from the sea surface onto a vessel housing an aquaculture facility. By using the previously described criteria, it is concluded that coral embryos and larvae are able to survive pumping related stressors. Further research should aim to find the exact strength of coral embryos after which a more precise model can be created to estimate mortality. Furthermore, limitations for pressure differences should be determined. For now, the assumption is made that for designing a pumping system, atmospheric pressure should be the minimum local pressure which is conservative. Additionally, the controlled deployment of the competent larvae onto degraded reefs should be further investigated because this project was not focused on that phase. To conclude, the project needs up-scaling towards hopper sizes, with a broader range of coral species and various weather conditions.

Given the previous described challenge, this research proofs that it is possible to pump coral embryos, after which they can grow into competent larvae and be deployed onto degraded reefs. Significant quantities of new recruits can be collected at healthy reefs and by using hopper size vessels, the collection of coral embryos from slicks become promising.

An ongoing trend of increased environmental awareness and a corresponding willingness to combat climate change influences the dredging industry. Policy developments that encourage contractors to work more sustainable and shifting client demands indicate that the amount of emitted CO2 is becoming an increasingly significant incentive for tender assessment. To increase the probability of winning a tender and make a profit, Van Oord needs to be able to quantify the emitted CO2 during both the engineering phase and the execution phase.

CSD spillage is defined as “any soil that is dislodged above the lowest cutter tip trajectory of a single swing, but is not sucked into the suction pipe”. In addition to higher energy consumption and material wear for delivering the targeted depth, spillage can lead to a variety of environmental issues. As of yet, no analytical model exists in literature that can estimate spillage rates for a given set of cutting parameters. This thesis presents the Sand-Rock Cutting Spillage Model (SRCSM), an engineering model that is particle size-agnostic and makes use of cutting parameters that are all available to the dredge operator.
Prediction accuracy of 5 percentage point is achieved with a two-disc potential flow model complemented with empirical closing relationships. A triad of forces governs flow in the cutter head for typical cutting conditions: a centrifugal, suction and gravitational force are considered. For the centrifugal pump effect, and centrifugal pump effect only, the flow inside the cutter is considered steady, non-gravitational, inviscid and non-axial. This allows for the derivation of a pressure-discharge affinity law from the Navier-Stokes. The axial pump effect is governed by the mixture velocity at the suction mouth. It is hypothesized that the pressure difference over the discs drives an inflow at the disc closest to the nose. Centrifugal advection and rapid redeposition spillage are considered the two most significant spillage types out of the six classified. Centrifugal advection can be determined by identifying the onset of radial outflow at the disc near the cutter ring. The magnitude of rapid redeposition flow and its concentration depend on mixing effects that are proportional to the ratio particle settling velocity and the mixture velocity squared. The model is calibrated with three coefficients. User input parameters are the cutter geometry, cut-type factor f_d,type (-1 for under-cut), bank slope angle ξ, cutter inclination angle λ, bank height h, step size l_step, rotational velocity ω, settling velocity v_ts, swing velocity v_s, mixture velocity v_m and material densities.
Spillage=f(D_ring,D_nose,D_pipe,b,f_d,type,ξ,γ,h,l_step,ω,v_ts,v_s,v_m,ρ_q,ρ_b,ρ_w )
For calibration, an inverse flow number θ^-1 is used that is proportional to the ratio of centrifugal flow over mixture flow. Spillage rates from SRCSM are in high agreement with reference data for sand (Miltenburg, 1983) and rock (Den Burger, 2003) in an under-cut swing. A sensitivity analysis suggests that most cutter head dynamics are adequately incorporated. The model is less reliable for (non-typical) inverse flow numbers of  θ^-1= 6 [-] and higher due to a mixture velocity that drops below zero. In addition, the model is calibrated for a relatively high cutter inclination angle of 45 [deg] and bank angle of 45 [deg]. Caution should be observed with the results. It is also suggested that mixing effects related to the swing velocity are incorporated more explicitly in the model. For typical sand cutting conditions, the highest spillage reduction (-4.6%) is achieved by a 1 [%] smaller step size. For rock, the highest spillage reduction (-0.63%) is achieved for a 1 [%] decrease in swing velocity. Spillage appears to follow the theorem of Ellington (1934): it don’t mean a thing if it ain’t got that swing.

Understanding the erosion process of sand will help improve dredging projects. Pickup functions are used to predict the amount of sand that can be eroded by a flow with certain parameters. The most common functions that are used have been validated to data in the low velocity regime (θ < 1). However, modern day dredging processes are in the high velocity erosion regime (θ > 1).An example of such a function is the widely used pickup function of Van Rijn (1984). It predicts the pickup of grains well at low flow velocities, but overestimates pickup at high flow velocities.Recently Bisschop (2018) has performed erosion experiments at high flow velocities. In 2015 Boskalis performed experiments in the same velocity regime during a preliminary study, however, a different setup was used. It was found that there is a large (factor 2) discrepancy between the two studies.The present study has performed experiments with a setup similar to that of Van Rijn (1984), however, the flow velocity was not limited to the low velocity regime. Erosion tests were done with bed shear stresses up to 60 Pa (θ<30). The setup in question uses a sediment lift to push a prepared sand bed up into the flow.The determination of the bed shear stress was questionable in preliminary study of Boskalis. Since it is a very important parameter in erosion predictions, it was a focus of the present study to determine the bed shear stress accurately. The bed shear stress was determined with three different methods which all agree within an acceptable range (up to 8%).The erosion velocity is determined by measuring the lift velocity, which is equal to the erosion velocity when the top of the sand bed is level with the floor of the setup. Whether the top of the sand bed is level or not has been determined with the use of a high speed camera.The produced data has been compared to existing data and pickup functions of other studies. From this comparison it is clear that no existing functions match the data of the present study.In the present study an analysis is done to find out why the new data does not match existing functions. Also, based on several existing functions, a new function is presented that has a good fit with the data of the present study.

When dredging close to underwater sand slopes, steep slopes might form. In dense sand with low permeability this might lead to the so-called breaching process. The creation of a steep underwater slope marks the beginning of a breaching process.
Pore volumes of densely packed sand tend to increase during shear deformations. This effect is called dilation. As the grain slides over each other, the pore volume increases resulting in increased underpressures. Water, eventually, has to flow in to compensate for this underpressure. The flow rate depends on sand properties. The underpressure keeps the sand body, temporarily, stable. When enough water has flowed in and the sand has dilated enough, sand particles release at the front. This is at the start of the breaching process. This leads to a density current consisting of sand mixed with the surrounding water, which runs down the slope and might cause erosion. The steep front of the slope moves with a certain velocity, which is called the headwall velocity.

A breach can be stable or unstable. A breach is stable if the breaching height decreases in time and unstable if the breaching height increases in time. This work aims to improve the prediction of the stability of a breach. For this purpose I carried out a series of large scale breaching experiments. During these experiments the initial breaching height, slope angles, and sand types and varied.

Literature suggest that the stability of a breach can be predicted using the headwall velocity and the angle at the toe of the breach. The experiments show that this is indeed the case, but that breaches are more stable than literature suggests.

Therefore, to predict the stability of a breach we must know the angle at the toe, and the headwall velocity.
The experiments show that the angle at the toe converges towards the angle that is predicted using equations found in literature.

A formula to predict the wall velocity can be found in literature. Comparison with the experiments show that this formula can predict the wall velocity when no slides are present, but at large breach heights these slides often occur.

The experiments show a clear correlation between the breach height, and the frequency of sliding wedges.
Empirical equations following from the test data predict the percentage of the sliding wedges at different breaching heights are proposed.

A steady state numerical model, to calculate the pore pressure during a breaching process, was programmed in MATLAB. Using these pore pressures, a stability analysis was carried out. This analysis confirms that breaching height is an important factor for the prediction of sliding wedges.