Search Results (73)

Public health suffers from noxious gas emitted by massive beached Sargassum algae. Net-barrages deployed in near-shore seas can contain Sargassum, provided they efficiently resist the additional hydrodynamic pressure induced by the catch. Nowadays, the design and installation of net-barrages are empiric. Structural breaks and anchor and mooring chain drifts can arise. We provide a mechanical model to evaluate stresses and loads on a structure made of fishing nets and buoy moorings. Hydrodynamic uncertainties occur through catches, fouling and sea current amplitudes appearing in lagoons or sheltered bays. This study presents a non-linear four-node finite-element model for continuous elastic membranes undergoing large displacements and small strains. The model relies on the Lagrangian linearly elastic membrane theory, employing the non-linear Green strain tensor and a non-updated hydrodynamic loading. We study forcings fixed a priori on a netting section of barrage that is 50 m long and 1 m high with double layer, e.g., two net-faces. We consider low and moderate current velocities, 0.05 and 0.35 m∙s⁻¹, while assuming specific vertical and horizontal catch pressures. A barrage installed in the reef lagoon at Le François on Martinique Island that is observable by satellite imagery could benefit of the computed net and mooring tensions. Full article

This study presents a hydrodynamic assessment of a toroidal wave energy converter (WEC) operating under low-energy conditions of the west coast of Mexico. Performance analysis incorporates the coupling surge, heave, and pitch motions. To investigate mooring–device interaction, two mooring configurations were examined: (A) a single catenary system and (B) a catenary system with a surface-floating buoy. The WEC was evaluated under operational conditions, operational conditions with a constant surface current, and extreme seas. The results show that under operational conditions, the WEC-mooring B configuration achieves higher energy capture than the WEC-mooring A configuration, with performance peaks at 13 s and 11 s, respectively. The presence of a surface current does not significantly influence absorbed power. Under extreme conditions, mooring B reduces mooring-line stresses but causes greater horizontal foundation forces and increased floater drift compared to mooring A. When mooring effects are included, mooring A’s performance is advantageous because it shifts peak energy capture toward the dominant sea states at the study site. This maintains better station-keeping capability and achieves a maximum capture width ratio (CWR) of approximately 0.5. Full article

Drifting fish aggregating devices (DFADs) are central to tropical tuna purse-seine fisheries, yet their hydrodynamic performance under realistic seas has not been adequately addressed, particularly for emerging eco-friendly designs. A three-dimensional framework based on computational fluid dynamics is developed to assess the motion response and mooring loads of full-scale DFADs comprising raft buoys, biodegradable cotton rope, and iron sinkers, using four buoy layouts (Models A to D). Unsteady Reynolds-averaged Navier–Stokes (URANS) simulations are performed with a realizable k–ε closure, volume of fluid (VOF) free-surface capturing, the Euler overlay method, dynamic overset meshes, and catenary mooring coupling. Regular waves representative of operational conditions (T = 1.40 to 2.40 s, H = 0.10 to 0.40 m) are imposed via a VOF wave-forcing technique, and mesh/time-step sensitivity analyses demonstrate the accurate reproduction of the first-order wave elevation (error < 0.8%). Surge drift per cycle and heave response amplitude operators, with the relative mooring force, are evaluated as functions of the relative wavelength (λ/L_a) and wave steepness (H/λ). The results reveal that the buoy layout exerts first-order control on DFAD dynamics, whereas short, steep waves dominate motion and line loads. The intermediate end-point sinker mass achieves a favorable balance between motion suppression and mooring load control, whereas distributing a fixed total sinker mass along the rope reduces heave response and mooring force by improving the tension redistribution and overall stability. Across all sea states, Models A and D reduced motion envelopes and mooring forces, indicating their suitability as robust, low-impact configurations. The proposed framework and design recommendations provide quantitative guidance for optimizing eco-DFAD geometry and deployment strategies, supporting safer and more sustainable DFAD-based tuna fisheries. Full article

Accurate prediction of tuna distribution is essential for sustainable fisheries management. This study develops a two-stage hybrid model combining Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Random Forest (RF) to predict tuna distribution around drifting fish aggregating devices (DFAD) in the Western and Central Pacific Ocean (WCPO). Echo-sounder buoy data from DFAD were aggregated into 2° × 2° grid cells and matched with oceanographic variables from the Copernicus Marine Service. Random Forest-based variable importance analysis identified primary productivity (27%), chlorophyll-a (22%), and dissolved oxygen (18%) as the three dominant environmental drivers. The CNN-RNN component extracts spatiotemporal features from multi-layer ocean data, while the RF classifier performs binary classification of tuna aggregation zones (high-yield vs. low-yield). All five models (Decision Tree, RF, CNN, Transformer, and CNN-RNN-RF) were evaluated on 557 samples using 5-fold stratified cross-validation, with each fold further split 80:20 for training and validation. The proposed CNN-RNN-RF model achieved the highest performance with an AUC of 0.830, accuracy of 82.6%, and F1-scores of 86.3% (high-yield) and 76.2% (low-yield), outperforming the best baseline model (RF: AUC 0.761, accuracy 75.4%). Predicted high-yield zones showed strong consistency with fishing log records, demonstrating the potential of integrating echo-sounder data with hybrid deep learning for data-driven tuna fisheries management. Full article

Stokes drift is the net displacement of ocean surface water particles caused by nonlinear surface waves. Its estimation typically relies on sea surface wave spectra, and truncation of the high-frequency spectral tail can significantly affect accuracy. This study uses directional wave spectrum data from the SWIM instrument onboard CFOSAT. By introducing a wind-speed-dependent parameterization scheme for the transition wavenumber (k_n) between the equilibrium and saturation ranges, as well as a cutoff wavenumber (k_m), we constructed a model to supplement the high-frequency tail of the wave spectrum combined with mask filtering to optimize spectrum reconstruction. The Stokes drift calculated with this model shows a better correlation (R = 0.699) with buoy observations than the widely used ERA5 reanalysis (R = 0.613). Analysis reveals pronounced regional differences in the contribution of high-frequency waves to surface Stokes drift, exceeding 80% in equatorial low-wind regions while dropping below 10% in the high-wind Southern Ocean due to enhanced breaking dissipation. The global Stokes drift distribution exhibits clear hemispheric asymmetry and seasonal evolution, with peak values (>0.12 m/s) in the Antarctic Circumpolar Current region. The proposed method provides a reliable, observation-based approach for improving global Stokes drift estimation, with direct implications for modelling ocean transport, Langmuir turbulence, and air–sea interactions. Full article

The presence of ice cover significantly alters the hydraulic characteristics of river channels, and the evolutionary law of ice drift velocity is crucial for understanding the ice-jam floods (IJFs) formation mechanism during the spring IJFs breakup period. Based on miniature ice buoy locators and Sentinel-2 satellite remote sensing data, this study systematically analyzes the channel characteristics of the upper Heilongjiang River and the regulatory effect of channel morphology on ice drift velocity. The results show that the river width of the upper Heilongjiang River exhibits a widening trend, with a variation range of 212 to 1292 m, characterized by large longitudinal dispersion and significant spatial variability. During the 2024 spring IJFs breakup period, the ice drift velocity ranges from 0.57 to 3.48 m/s with an average of 1.92 m/s, and a significant decreasing trend is observed when the ice drift passes through the entrances/exits of meandering bends and the confluences of distributaries in braided channels. The longitudinal distribution law of ice drift velocity revealed in this study can provide key data support and scientific reference for the accurate prediction of IJFs and the prevention and control of IJFs. Full article

Accurate wave detection is essential for reliable ship motion prediction and the safety of offshore operations. Wave buoys are widely deployed as key instruments for capturing wave characteristics. However, buoys drift due to the waves and currents, resulting in errors in reconstructed wave elevation. To address this challenge, a fixed-position wave-elevation reconstruction method is proposed in this paper. First, a temporal convolutional network (TCN) module is integrated with a gated recurrent unit (GRU) network to efficiently capture the nonlinear relationship between buoy motion and wave elevation, enabling simultaneous wave elevation reconstruction and dynamic deviation compensation. Second, a static deviation compensation algorithm developed from wave theory is introduced to convert the spatial deviation into temporal misalignment. The proposed method is evaluated in both time and frequency domains across various sea conditions. Results demonstrate that the proposed method effectively compensates for deviations and achieves accurate reconstruction of wave elevation at the target position. In higher sea states, accurate reconstruction is maintained even at large static deviations, with relative errors typically within 10–15%. Frequency-domain analysis shows that coherence approaches 1 near the spectral peak and below 0.3 at higher frequencies, indicating that the dominant wave components are accurately reconstructed and that high-frequency noise has a limited impact on overall accuracy. Full article

The Strait of Gibraltar is a major biogeographic bottleneck connecting the Atlantic Ocean and the Mediterranean Sea, where migratory cetaceans coexist with an intense maritime traffic. To evaluate the feasibility of broadband passive acoustic monitoring (PAM) for both soundscape characterisation and cetacean detection, a short drifting-buoy experiment was conducted near Barbate, Spain, in May 2025. The system, equipped with a calibrated SoundTrap 400 recorder, continuously sampled the underwater acoustic environment for 2.5 h. Analysis of the recordings revealed vocalisations of Orcinus orca, representing the first preliminary and incomplete description of the Iberian killer whale acoustic repertoire, and numerous transient tonal events with energy peaks between 40 and 50 Hz, consistent with baleen whale sounds previously attributed to foraging fin whales (Balaenoptera physalus). Sperm whale clicks and delphinid whistles were also occasionally detected. The power spectral density analysis further showed a persistent anthropogenic component dominated by vessel noise below 200 Hz and narrow-band echosounder signals at 30 and 50 kHz. These findings confirm the potential of PAM to detect multiple cetacean species and to resolve the complex interplay between biophony and anthropophony in one of the world’s busiest marine corridors. Establishing a permanent PAM observatory in the Strait would enable continuous, non-intrusive monitoring of species presence, behaviour, and habitat use, thereby contributing to conservation efforts for endangered populations such as the Iberian killer whale. Full article

The Search and Rescue at Sea Manual defines several uncertainties related to the initial position and the time elapsed between an accident and the onset of SAR operations. The present article seeks an approach to address this problem through the assimilation of drifting buoy data and their use in correcting the system parameters via an ill-posed inverse problem. The results demonstrate that, in the search for objects at sea, the uncertainty of their initial position must be explicitly considered. Quantitatively, the proposed methodology reduced the uncertainty of the initial search area by approximately 55–60% compared with the traditional approach that assumes a single deterministic initial point. This outcome underscores the potential of data assimilation techniques to enhance the probabilistic accuracy of maritime search and rescue planning. Full article

Sea ice is highly dynamic. Differences in the sea ice drift velocity and direction can cause deformations such as ridges and rubble fields or open up leads. These and other deformations have a major impact on the interaction between the atmosphere, sea ice and the ocean, and strongly influence ship navigability in polar waters. Spaceborne Synthetic Aperture Radar (SAR) data is well suited to observing the sea ice and retrieving sea ice drift vector fields at a small scale (<1 km), revealing deformation zones. This paper introduces a software processor designed to retrieve high-resolution sea ice drift vector fields from pairs of subsequent SAR acquisitions using phase correlation embedded in a multiscale Gaussian image pyramid. We assess the accuracy of the algorithm by using drift buoys and landfast ice boundaries manually outlined from large series of TerraSAR-X acquisitions taken during winter and spring sea ice break up. In particular, we provide a first analysis of the localization accuracy in deformation zones. Overall, our experiments show that deformation zones are well detected, but can be misplaced by up to 1.1 km. An additional interferometric analysis narrows down the location of the landfast ice boundary. Full article

The rapid expansion of deep-sea sensing networks underscores the critical need for accurate underwater positioning of observation base stations. However, achieving precise acoustic localization, particularly at depths exceeding 4 km, remains a significant challenge due to systematic ranging errors, clock drift, and inaccuracies in sound speed modeling. This study proposes and validates a three-tier calibration framework consisting of a Dynamic Single-Difference (DSD) solver, a geometrically optimized reference buoy selection algorithm, and a Virtual Beacon (VB) depth inversion method based on sound speed profiles. Through simulations under varying noise conditions, the DSD method effectively mitigates common ranging and clock errors. The geometric reference optimization algorithm enhances the selection of optimal buoy layouts and reference points. At a depth of 4 km, the VB method improves vertical positioning accuracy by 15% compared to the DSD method alone, and nearly doubles vertical accuracy compared to traditional non-differential approaches. This research demonstrates that deep-sea underwater target calibration can be achieved without high-precision time synchronization and in the presence of fixed ranging errors. The proposed framework has the potential to lower technological barriers for large-scale deep-sea network deployments and provides a robust foundation for autonomous deep-sea exploration. Full article

Accurate short-term wave forecasting is critical for the safe and efficient operation of marine structures that rely on real-time, phase-resolved ocean wave information for control and monitoring purposes (e.g., digital twins). These systems often depend on environmental sensors (e.g., waverider buoys, wave-sensing LIDAR). Challenges arise when upstream sensor data are missing, sparse, or phase-shifted due to drift. This study investigates the performance of two machine learning models, time-series dense encoder (TiDE) and long short-term memory (LSTM), for forecasting phase-resolved ocean surface elevations under varying degrees of data degradation. We introduce the $\tau$-trimming algorithm, which adapts the prediction horizon based on uncertainty thresholds derived from historical forecasts. Numerical wave tank (NWT) and wave basin experiments are used to benchmark model performance under short- and long-term data masking, spatially coarse sensor grids, and upstream phase shifts. Results show under a 50% probability of upstream data loss, the $\tau$-trimmed TiDE model achieves a 46% reduction in error at the most upstream target, compared to 22% for LSTM. Furthermore, phase misalignment in upstream data introduces a near-linear increase in forecast error. Under moderate model settings, a ±3 s misalignment increases the mean absolute error by approximately 0.5 m, while the same error is accumulated at ±4 s using the more conservative approach. These findings inform the design of resilient, uncertainty-aware wave forecasting systems suited for realistic offshore sensing environments. Full article

Ocean surface radial current velocities can be derived from synthetic aperture radar (SAR) Doppler shift observations using the Doppler centroid technique and a recently developed Doppler velocity model. However, comprehensive evaluations of the accuracy and reliability of these retrievals remain limited. To address this gap, we analyzed 6341 Sentinel-1 SAR scenes acquired over the South China Sea (SCS) between December 2017 and October 2023, in conjunction with drifting buoy observations, to systematically validate the retrieved radial current velocities. A linear fitting method and the dual co-polarization Doppler velocity (DPDop) model were applied to correct for the influence of non-geophysical factors and sea state effects. The validation against the drifter data yielded a bias of 0.01 m/s, a root mean square error (RMSE) of 0.18 m/s, and a mean absolute error (MAE) of 0.16 m/s. Further comparisons with the Surface and Merged Ocean Currents (SMOC) dataset revealed bias, RMSE, and MAE values of 0.07 m/s, 0.14 m/s, and 0.12 m/s in the Beibu Gulf, and −0.06 m/s, 0.23 m/s, and 0.19 m/s in the Kuroshio intrusion area. These results demonstrate that SAR Doppler measurements have a strong potential to complement existing ocean observations in the SCS by providing high-resolution (1 km) ocean surface current maps. Full article

To study the response of a flexible offshore floating photovoltaic (FPV) array under waves and a current, a numerical model is established using OrcaFlex. The effects of different waves and currents, as well as their coupled effects on the motion response of the offshore PFV array and the tension in the connectors and moorings under different static tensions, are investigated. Differences are illustrated between the responses of the buoys at different positions and under different moorings under the wave. With the relaxed moorings, the surge response of the buoy facing the wave increased by 159.3% compared with the buoy facing away from the wave. The current causes the overall drift of the array, which greatly influences the buoys facing the current. The mooring tension facing the wave restricts the motion of the buoys under the same direction as the wave and current, which shows that the trend of the buoys’ responses with the wave decreases with the increase in the current velocity, as the pitch reduces to 76.9% under relaxed moorings. There is a significant difference between the results obtained by the superposition summation wave and current loads and the ones of the combined wave–current. With the increase in the wave–current angle, the response is increased by 348.2% as the constraint of the moorings and the connectors is weakened. Full article

Field observations revealed that a mooring buoy rapidly drifts in a reciprocating motion along an arcuate path between two extreme positions. When the anchor point is considered the origin and viewed from an aerial perspective, this movement resembles a pendulum. The implications of this motion for data acquisition efficiency prompted our inquiry into this phenomenon. The comparative analysis of the model’s different movements under wave-only, current-only, and wave–current conditions demonstrates that currents are the source inducing this pendulum-like motion. To investigate the mechanism of this current-driven motion, the flow field around the buoy was visualized through numerical simulations. Specifically, the CFD results aligned with the field data and confirmed that periodic vortex shedding induces oscillatory forces, which dominate the rapid reciprocating movement. The findings emphasize the significant impact of fluid viscosity and the resulting vortex effects on the motion characteristics of buoys. They can provide a foundation for addressing more applied problems of data error-correcting and trajectory predictions. Full article