Continuous inspection and mapping of the seabed allows for monitoring the impact of anthropogenic activities on benthic ecosystems. Compared to traditional manual assessment methods which are impractical at scale, computer vision holds great potential for widespread and long-term monitoring.
We deploy an underwater remotely operated vehicle (ROV) in Jammer Bay, a heavily fished area in the Greater North Sea, and capture videos of the seabed for habitat classification. The collected JAMBO dataset is inherently ambiguous: water in the bay is typically turbid which degrades visibility and makes habitats more difficult to identify. To capture the uncertainties involved in manual visual inspection, we employ multiple annotators to classify the same set of images and analyze time spent per annotation, the extent to which annotators agree, and more.
We then evaluate the potential of vision foundation models (DINO, OpenCLIP, BioCLIP) for automating image-based benthic habitat classification. We find that despite ambiguity in the dataset, a well chosen pre-trained feature extractor with linear probing can match the performance of manual annotators when evaluated in known locations. However, generalization across time and place is an important challenge.
Physical model tests are often conducted during the design process of coastal structures. The wave climate in such tests often includes short-crested nonlinear waves. The structural response is related to the incident waves measured in front of the structure. Existing methods for separation of incident and reflected short-crested waves are based on linear wave theory. For analysis of nonlinear waves, the existing methods are limited to separation of nonlinear long-crested waves. For short-crested waves, the only options so far have been to use estimates without the structure in place. The present paper thus presents a novel method for directional analysis of nonlinear short-crested waves: Non-Linear Single-summation Oblique Reflection Separation (NL-SORS). The method is validated on numerical model data, as for such data, the target is well defined as simulations may be performed with fully absorbing boundaries. Second- and third-order wave theory is used to demonstrate that small errors on the celerity of nonlinear components in the mathematical model of the surface elevation can be obtained if a double narrow-banded directional spectrum is assumed, ie the primary frequency and the directional spreading function must be narrow banded. As the increasing nonlinearity of the waves often arise from waves shoaling on a sloping foreshore, the directional spreading of the waves will decrease due to refraction, and a broad directional spreading function will thus not be experienced in highly nonlinear conditions. The new NL-SORS method is shown to successfully decompose nonlinear short-crested wave fields and estimate the directional spectrum thereof.
This book introduces a novel model to explain how the co-design and co-delivery of ocean science knowledge and solutions is influenced by ocean stakeholders with asymmetric power and resources, policy incentives and ocean conflict, ocean narratives, different knowledge systems, security concerns, principles, formal and informal rules, and communication competencies. Using the International Collaboration in Ocean Science model as a basis, the book advances with three lines of inquiry: ontological security of ocean science participants, the Ocean Decade and human well-being, and strategic narratives about international collaboration in ocean science. Through these, Carolijn van Noort shows the enabling and constraining conditions of co-creating ocean knowledge and solutions. Theoretically novel, the book provides a compelling framework for scholars to study ocean science collaboration.
This paper highlights the urgent need to accelerate research and action on ocean carbon sinks through human intervention, known as Global Ocean Negative Carbon Emissions (Global-ONCE) Programme, as a vital strategy in global efforts to mitigate climate change. Achieving 'net zero' by 2050 cannot rely on emission reductions alone, emphasising the necessity of complementary approaches. Global-ONCE's mission extends beyond scientific exploration. It embodies a profound commitment to protecting and restoring blue carbon ecosystems, as well as implementing ocean-based solutions that are sustainable, equitable, and inclusive. Early Career Ocean Professionals (ECOPs) are at the heart of these efforts, and their innovative approaches, technical expertise, and passion make them indispensable leaders in advancing ONCE initiatives. ECOPs bridge the gap between science and society, playing a relevant role in integrating cutting-edge research, technological advancements, and community-driven action to address climate threats. By bringing together diverse perspectives and leveraging their interdisciplinary expertise, ECOPs ensure ONCE strategies are grounded in scientific rigour and practical feasibility. Through advocacy, education, and collaboration, ECOPs not only spearhead research and innovation but also inspire collective action to safeguard our oceans. This paper amplifies the critical role of ECOPs as agents of change and calls for a unified global commitment to harness the ocean's potential for a climate-resilient future.
A moving static pressure distribution is commonly used to simulate a travelling ship. However, the ship movement changes the fluid velocity around the hull, inducing pressures on the hull surface that are no longer equal to the static pressure. Therefore, we introduce a dynamic pressure correction strategy, which can accurately simulate the impact of the ship movement on the hull-surface pressure and preserve the desired hull shape under both stationary and transient conditions. The strategy is applied to a high-order spectral model and used to investigate ship-induced waves and wave resistance over a both flat and variable topography. We explore various parameters in our study, including the average water depth to ship draft ratio (h(0)/d), the channel width to ship width ratio (W/B), the Froude number (Fr-0 = U/root gh(0)) and variations in bathymetric slope. Compared with experiments on a flat bottom, the numerical results with dynamic correction show better accuracy in the simulation of ship-induced waves and wave resistance than those obtained using a static pressure distribution. The correlation coefficient for wake waves between the numerical and experimental results is improved by approximately 0.25 with the dynamic correction strategy. The amplitude and wavelength of ship-induced mini-tsunamis over a variable topography are found to be reduced when employing a dynamic correction compared with a static pressure distribution, and this effect becomes more pronounced with higher Froude number. The static pressure approach is shown to allow large deformations of the desired hull shape and changes in ship volume which are responsible for the different wave patterns from the two approaches.
Physical wave basin tests with a focus on uncertainty estimation have been conducted on a sphere subjected to wave loads at Aalborg University as part of the effort of the OES Wave Energy Converters Modeling Verification and Validation (formerly, OES Task 10) working group to increase credibility of numerical modeling of WECs. The tests are referred to as the Kramer Sphere Cases, and the present note is dealing with wave excitation force tests on a fixed model. The present note is including details to facilitate CFD models which replicate the physical setup in detail.
This paper presents an assessment of three methods used for sea state estimation via the wave buoy analogy, where measured ship responses are processed. The three methods all rely on Machine Learning exclusively but they have different output; Method 1 provides bulk parameters, Method 2 yields a point wave spectrum and the wave direction, while Method 3 gives the directional wave spectrum in non-parametric form. The assessment is made using full-scale data from an in-service container ship in cross-Atlantic service. Training and testing of the methods are made using data from a wave radar, and the three methods perform well. An uncertainty measure, equivalently, a trust level indicator, based on the variation between the post-processed outputs of the methods is proposed, and this facilitates determination of estimates with small errors; without knowing the ground truth.
Simulating the free decay motion and wave radiation from a heaving semi-submerged sphere poses significant computational challenges due to its three-dimensional complexity. By leveraging axisymmetry, we reduce the problem to a two-dimensional simulation, significantly decreasing computational demands while maintaining accuracy. In this paper, we exploit axisymmetry to perform a large ensemble of Computational Fluid Dynamics (CFDs) simulations, aiming to evaluate and maximize both accuracy and efficiency, using the Reynolds Averaged Navier–Stokes (RANS) solver interFOAM, in the opensource finite volume CFD software OpenFOAM. Validated against highly accurate experimental data, extensive parametric studies are conducted, previously limited by computational constraints, which facilitate the refinement of simulation setups. More than 50 iterations of the same heaving sphere simulation are performed, informing efficient trade-offs between computational cost and accuracy across various simulation parameters and mesh configurations. Ultimately, by employing axisymmetry, this research contributes to the development of more accurate and efficient numerical modeling in ocean engineering.
We present a high-order nodal spectral element method for the two-dimensional simulation of nonlinear water waves. The model is based on the mixed Eulerian–Lagrangian (MEL) method. Wave interaction with fixed truncated structures is handled using unstructured meshes consisting of high-order iso-parametric quadrilateral/triangular elements to represent the body surfaces as well as the free surface elevation. A numerical eigenvalue analysis highlights that using a thin top layer of quadrilateral elements circumvents the general instability problem associated with the use of asymmetric mesh topology.We demonstrate how to obtain a robust MEL scheme for highly nonlinear waves using an efficient combination of (i) global L2 projection without quadrature errors, (ii) mild modal filtering and (iii) a combination of local and global re-meshing techniques. Numerical experiments for strongly nonlinear waves are presented. The experiments demonstrate that the spectral element model provides excellent accuracy in prediction of nonlinear and dispersive wave propagation. The model is also shown to accurately capture the interaction between solitary waves and fixed submerged and surface-piercing bodies. The wave motion and the wave-induced loads compare well to experimental and computational results from the literature.
Ocean monitoring will improve outcomes if ways of knowing and priorities from a range of interest groups are successfully integrated. Coastal Indigenous communities hold unique knowledge of the ocean gathered through many generations of inter-dependent living with marine ecosystems. Experiences and observations from living within that system have generated ongoing local and traditional ecological knowledge (LEK and TEK) and Indigenous knowledge (IK) upon which localized sustainable management strategies have been based. Consequently, a comprehensive approach to ocean monitoring should connect academic practices (“science”) and local community and Indigenous practices, encompassing “TEK, LEK, and IK.” This paper recommends research approaches and methods for connecting scientists, local communities, and IK holders and their respective knowledge systems, and priorities, to help improve marine ecosystem management. Case studies from Canada and New Zealand (NZ) highlight the emerging recognition of IK systems in natural resource management, policy and economic development. The in-depth case studies from Ocean Networks Canada (ONC) and the new Moana Project, NZ highlight real-world experiences connecting IK with scientific monitoring programs. Trial-tested recommendations for successful collaboration include practices for two-way knowledge sharing between scientists and communities, co-development of funding proposals, project plans and educational resources, mutually agreed installation of monitoring equipment, and ongoing sharing of data and research results. We recommend that future ocean monitoring research be conducted using cross-cultural and/or transdisciplinary approaches. Vast oceans and relatively limited monitoring data coupled with the urgency of a changing climate emphasize the need for all eyes possible providing new data and insights. Community members and ocean monitoring scientists in joint research teams are essential for increasing ocean information using diverse methods compared with previous scientific research. Research partnerships can also ensure impactful outcomes through improved understanding of community needs and priorities.