Coastal Engineering最新文献

Coastal imaging systems have been developed to measure wave runup and total water level (TWL) at the shoreline, which is a key metric for assessing coastal flooding and erosion. However, extracting quantitative measurements from coastal images has typically been done through the laborious task of hand-digitization of wave runup timestacks. Timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. We utilize over 7000 hand-digitized timestacks from six diverse locations to train and validate machine learning models to automate the process of TWL extraction. Using these data, we evaluate two deep learning model architectures for the task of runup detection. One is based on a fully convolutional architecture trained from scratch, and the other is a transformer-based architecture trained using transfer learning. The deep learning models provide a probability of each pixel being either wet or dry. When contoured at the 50% level (equal chance of being wet or dry), the deep learning models more accurately identified TWL maxima than minima at all sites. This resulted in accurate predictions of 2% exceedance runup, but under predictions of significant swash and over predictions of wave setup. Improved agreement with the complete TWL time series was obtained through post-processing by utilizing the wet/dry probability of each pixel to weight the contouring toward lower dryness probabilities for runup minima (maxima agreed well with observations without tuning). Overall, a transformer-based model using transfer learning provided the best agreement with wave runup statistics, including a) the 2% exceedance runup, b) significant swash, and c) wave setup at the shoreline. For a random subset of images, the model was found to be within the uncertainty range of hand-digitization. The relative success of the transfer learning model suggests that fine-tuning a large model has advantages compared to training a smaller model from scratch. Models provide per-pixel probabilistic estimates in less than 10 s per timestack on a single computational unit, versus the more than 5 min required for hand-digitization. The model is therefore well-suited for near real-time applications, allowing for the development of early warning systems for difficult to forecast events. Real-time wave runup and total water level observations can also be incorporated into coastal hazards forecasts for data assimilation and continual model validation and improvement.

The issue of seabed scour around offshore wind turbine foundations is a significant safety concern. In this study, local scour around a specific type of foundation, known as the large-diameter Mono-Column Composite Bucket Foundation (MCCBF) with six connectors, has been investigated through physical experiments. The study involved various flow conditions, including unidirectional flows, tidal flows, and combinations of regular waves and currents. It has been found that under similar flow intensity and orientation angles, unidirectional flow tends to cause deeper scour depths, but with a more limited extent compared to scour induced by tidal flows. The disparity in maximum scour depth between tidal and unidirectional flows decreases as flow velocity increases. Under regular wave-current interaction, both the scour depth and the scour extent are larger than those induced by unidirectional flow. The presence of lee-wake vortices and streamline contractions near the connectors results in larger scour depths on either side of the foundation, especially when the orientation angle is set to 0°. Different methods for predicting scour depth of the MCCBF were applied and discussed.

Emergency managers have an increasing need for tools to enhance preparedness to extreme coastal storms and support disaster risk reduction measures. With the emergence of Early Warning Systems (EWSs) for coastal storm hazards, a fundamental challenge is the accurate prediction of sandy beach erosion at lead times of days to weeks corresponding to an approaching storm event. This work presents a data-driven modelling approach to predict storm-driven beach erosion (shoreline change) using a large dataset of 276 individual storm events at Narrabeen-Collaroy Beach, SE Australia. Correlation analysis between individual storm characteristics and shoreline response at three locations along the embayment with varying exposure to the prevailing waves indicates that cumulative storm wave energy is the dominant driver of storm erosion at this site. This is followed by the pre-storm beach width, storm wave direction and to a minimal extent, storm wave period and water levels. A multi-linear regression model of storm erosion is developed and found to accurately predict shoreline change due to individual storm events (RMSE = 3.7 m–6.4 m). This work highlights the value of high-frequency shoreline data for storm erosion forecasting and provides a framework for real-time forecasting applications.

Sandy beach-dune systems make up a large part of coastal areas world wide. Their function as an eco-system as well as a protective barrier for human and natural habitat is under increased threat due to climate change. A thorough understanding of change processes at the sediment surface is essential to facilitate prediction of future development and management strategies to maintain their function. Especially slow and small scale processes happening over several days up to weeks at cm level, such as aeolian sand transport are difficult to identify and analyse. Permanent laser scanning (PLS) is a useful tool in the study and analysis of coastal processes as it captures a data representation of the evolution of the sediment surface over extended periods of time (up to several years) with high detail (at cm-dm level). The PLS data set considered for this study, consists of hourly acquired 3D point clouds representing the surface evolution of a section of the Dutch coast during three years. However, it is challenging to extract concrete information on specific change processes from the large and complex PLS data set. We use multiple hypothesis testing in order to reduce the PLS data set to a so-called inventory of trends, consisting of 12.8 million partial time series with associated rate of change and elevation. The inventory of trends proofs to be a suitable tool to identify natural processes such as storms and aeolian sand transport in our test area in the aeolian zone of a sandy beach-dune system on the Dutch coast. We identify these processes and provide a tool to derive summarising data from the complex PLS data set. We find that all partial time series identified as most likely representing aeolian sand transport, result in 1354 m${}^3$ of sand deposition in our study area over the course of three years. We also show a comparison with transects from JarKus data and find a correlation between anthropogenic activities and erosion in our test area with a correlation coefficient of 0.3.

Sediment composition, characterized by different contents of cohesive and non-cohesive sediments, is known to play a role on long-term estuarine and deltaic morphodynamics, but the exact impact is poorly understood. We establish a two-dimensional morphodynamic model to investigate the influence of different sediment compositions on the development of a schematic fluvio-deltaic system driven by river and tides. Though excluding the density effects, results suggest that the model captures the development of distributary channels and elongated sand bars with resemblance to that in the Yangtze Estuary. Sensitivity simulations show fundamentally different channel-shoal patterns take shape under different sediment compositions. Ebb dominance and associated seaward sediment flushing lead to faster morphodynamic development and more prograded delta under larger river discharge and sediment supply. We detect a positive correlation between the content of cohesive sediment and the speed of development, particularly cohesive sediment content is <50%. However, when the proportion of mud is larger (i.e., 50–75%), a deceleration of the morphological development occurs after 200 years. A sand-dominated environment exhibits the largest channel numbers and fast channel formation near the mouth within the first 300 morphodynamic years. Spatial distribution of bottom sediments changes with morphology, exhibiting increasing mud deposits near the mouth, whilst the sand remains inside the estuary. This study indicates the importance and need for a more realistic representation of bed compositions in long-term estuarine morphodynamic simulations.

Sandy coasts play a crucial role in various human activities and support the economies of many coastal states. Due to their importance, coastal erosion mitigation techniques are often implemented. Among these techniques, beach nourishment is considered an environmentally acceptable method for coastal protection and restoration. In this work, a methodology for the evaluation of such projects is proposed and applied to the biggest beach nourishment project in the city of Mar del Plata, Argentina. The nourishment was carried out between 1998 and 1999 in Playa Grande (PG), Varese (V) and Bristol (B) bays. The CoastSat toolkit was implemented to obtain shoreline positions from satellite imagery and to derive a 36-year monthly time series of beach width in the region. For the analysis, three distinctives time lapses are identified: pre-intervention, response, and new equilibrium. An exponential decay function was fitted to determine the response lapse and its characteristics. Metrics such as mean beach width and trends were computed and used to compare the condition of beaches before and after the project. Results show that the region experienced a net growth after nourishment, with beach width doubling in Bristol and Playa Grande, and increasing tenfold in Varase. Nourishment did not alter the erosive trends of Playa Grande and Bristol, nor the growth trend of Varese. Regarding renourishment planning, according to our findings, for Playa Grande and Bristol beaches to achieve a net growth of 1 m, it would require the deposition of 17 m³ of sediment per meter of coastline. This study highlights the suitability of the CoastSat toolkit for assessing the effectiveness of beach regeneration.

Wave-driven currents have a substantial impact on local circulation patterns in and across the surf zone, and are responsible for cross-shore and longshore exchange of mass and momentum over a broad range of spatial and temporal scales. Nearshore currents may drive sediment transport, lead to beach erosion, and also affect the spread of bacteria and other marine microorganisms, as well as the distribution of pollutants such as chemicals and microplastics. In addition, surf zone currents can cause hazardous conditions for beach-goers in the form of rip currents.

It is known from previous work (Chen et al., 2003; Feddersen et al., 2011; Hally-Rosendahl and Feddersen, 2016) that Boussinesq-type models in combination with appropriate boundary conditions and wave breaking capabilities can function as powerful tools for the analysis of circulation patterns in the surf zone. In the present work, data from a recent field campaign reported on in Bjørnestad et al. (2021) are used to further validate the capability of Boussinesq systems to simulate nearshore dynamics.

The numerical model is then used to study the influence of tidal elevation, peak direction and directional spread of the incoming wavefield on the quantity, extent, and circulatory magnitude of the nearshore circulation. In addition, fundamental features such as horizontal eddies are investigated, and comparisons are made to solid-body rotation and irrotational vortices.

Overall, it is observed that local variations in the bathymetry across the surf zone are the controlling factor regarding the size of these circulations, and an increasing tidal level, which can be seen as a uniform offset to the bathymetry, favors the generation of larger vortex patterns. For a given tidal stage, the directional spread of the incoming wavefield has the most pronounced influence on the size and strength of the nearshore eddies while the peak direction has the strongest effect on the total number of circulations.

Fluid particle kinematics due to wave motion (i.e. orbital velocities and accelerations) at and beneath the free surface is involved in many coastal and ocean engineering applications, e.g. estimation of wave-induced forces on structures, sediment transport, etc. This work presents the formulations of these kinematics fields within a fully nonlinear potential flow (FNPF) approach. In this model, the velocity potential is approximated with a high-order polynomial expansion over the water column using an orthogonal basis of Chebyshev polynomials of the first kind. Using the same basis, original analytical expressions of the components of velocity and acceleration are derived in this work. The estimation of particle accelerations in the course of the simulation involves the time derivatives of the decomposition coefficients, which are computed with a high-order backward finite-difference scheme in time. The capability of the numerical model in computing the particle kinematics is first validated for regular nonlinear waves propagating over a flat bottom. The model is shown to be able to predict both the velocity and acceleration of highly nonlinear and nearly breaking waves with negligible error compared to the corresponding stream function wave solution. Then, for regular waves propagating over an uneven bottom (bar-type bottom profile), the simulated results are confronted with existing experimental data, and very good agreement is achieved up to the sixth-order harmonics for free surface elevation, velocity and acceleration.

Nonlinear interactions between an extreme wave and a cylindrical structure with its bottom being elevated above the still mean water level are investigated by a set of physical experiments, complemented by advanced CFD-type numerical simulations. The extreme wave is modelled as a solitary wave, which is widely applied as a simple model for tsunamis. Three horizontal (namely forward impacting, backward impacting and cyclic forces) and three vertical (namely uplifting, suction, and slamming forces) force modes are identified. The forward impacting force results from the wave crest impacting on the cylinder front face directly, and its force peak is found to have a quadratic relationship with the velocity of incoming water particle. The slamming force is however caused by the wave hitting on the cylinder bottom from beneath, and other modes are associated with the complex fluid behaviors around the cylinder, e.g. reverse flow and violent surface transformation. In addition, the effects of cylinder clearance (the vertical distance between the cylinder bottom and the mean water level), and the inclined angle are investigated in-depth. It is found that these two play significant roles in the slamming force mode. The former determines the total water momentum that is transferable, and the latter tells how much of this total transferable water momentum could effectively be transferred to the slamming force eventually. A planar collision occurs when the inclined angle is equal or close to the localized slope angle of the undisturbed wave surface, resulting in the largest momentum transfer, and in turn, the largest slamming force for a given cylinder clearance.