Search Results (492)

This study assesses the feasibility and profitability of marine hybrid clusters, combining wave energy converters (WECs) and offshore wind turbines (OWTs) to power households and marine aquaculture. Researchers analyzed two coastal sites: La Serena, Chile, with high and consistent wave energy resources, and Ensenada, Mexico, with moderate and more variable wave power. Two WEC technologies, Wave Dragon (WD) and Pelamis (PEL), were evaluated alongside lithium-ion battery storage and green hydrogen production for surplus energy storage. Results show that La Serena’s high wave power (26.05 kW/m) requires less hybridization than Ensenada’s (13.88 kW/m). The WD device in La Serena achieved the highest energy production, while PEL arrays in Ensenada were more effective. The PEL-OWT cluster proved the most cost-effective in Ensenada, whereas the WD-OWT performed better in La Serena. Supplying electricity for seaweed aquaculture, particularly in La Serena, proves more profitable than for households. Ensenada’s clusters generate more surplus electricity, suitable for the electricity market or hydrogen conversion. This study emphasizes the importance of tailoring emerging WEC systems to local conditions, optimizing hybridization strategies, and integrating consolidated industries, such as aquaculture, to enhance both economic and environmental benefits. Full article

Coastal profile models are frequently used for the computation of storm-induced erosion at (nourished) beaches. Attention is focused on new developments and new validation exercises for the detailed process-based CROSMOR-model for the computation of storm-induced morphological changes in sand and gravel coasts. The following new model improvements are studied: (1) improved runup equations based on the available field data; (2) the inclusion of the uniformity coefficient (C_u = d₆₀/d₁₀) of the bed material affecting the settling velocity of the suspended sediment and thus the suspended sediment transport; (3) the inclusion of hard bottom layers, so that the effect of a submerged breakwater on the beach–dune morphology can be assessed; and (4) the determination of adequate model settings for the accretive and erosive conditions of coarse gravel–shingle types of coasts (sediment range of 2 to 40 mm). The improved model has been extensively validated for sand and gravel coasts using the available field data sets. Furthermore, a series of sensitivity computations have been made to study the numerical parameters (time step, grid size and bed-smoothing) and key physical parameters (sediment size, wave height, wave incidence angle, wave asymmetry and wave-induced undertow), conditions affecting the beach morphodynamic processes. Finally, the model has been used to study various alternative methods of reducing beach erosion. Full article

Extreme sea conditions caused by tropical cyclones pose significant risks to coastal safety, infrastructure, and ecosystems. Although existing models have advanced in predicting Significant Wave Height (SWH), their performance in predicting Maximum Wave Height (MWH) remains limited, particularly in capturing rapid wave fluctuations and localized meteorological dynamics. This study proposes a novel MWH prediction framework that integrates high-resolution buoy observations with deep learning. A moored buoy deployed in the Qiongzhou Strait provides precise nearshore observations, compensating for limitations in reanalysis datasets. Light Gradient Boosting Machine (LightGBM) is employed for key feature selection, and a hybrid Bidirectional Temporal Convolutional Network-Bidirectional Gated Recurrent Unit (BiTCN-BiGRU) model is constructed to capture both short- and long-term temporal dependencies. The results show that BiTCN-BiGRU outperforms BiGRU, reducing MAE by 6.11%, 5.41%, and 14.09% for 1-h, 3-h, and 6-h forecasts. This study also introduces the Time Distortion Index (TDI) into MWH prediction as a novel metric for evaluating temporal alignment. This study offers valuable insights for disaster warning, coastal protection, and risk mitigation under extreme marine conditions. Full article

This study introduces a novel adaptive Mechanical Wave Energy Converter (MWEC) designed to efficiently capture nearshore wave energy for sustainable electricity generation along the southeast surf coast of NEOM (135° longitude). The MWEC system features a polyvinyl chloride (PVC) cubic buoy integrated with a mechanical power take-off (PTO) mechanism, optimized for deployment in shallow waters for a depth of around 1 m. Three buoy volumes, V1: 6000 cm³, V2: 30,000 cm³, and V3: 72,000 cm³, were experimentally evaluated under consistent PTO and spring tension configurations. The findings reveal a direct relationship between buoy volume and force output, with larger buoys exhibiting greater energy capture potential, while smaller buoys provided faster and more stable response dynamics. The energy retention efficiency of the buoy–PTO system was measured at 20% for V1, 14% for V2, and 10% for V3, indicating a trade-off between responsiveness and total energy capture. Notably, the largest buoy (V3) generated a peak power output of 213 W at an average wave amplitude of 65 cm, confirming its suitability for high-energy conditions along NEOM’s surf coast. In contrast, the smaller buoy (V1) performed more effectively during periods of reduced wave activity. Wave climate data collected during November and December 2024 support a hybrid deployment strategy, utilizing different buoy sizes to adapt to seasonal wave variability. These results highlight the potential of modular, wave-adaptive mechanical systems for scalable, site-specific renewable energy solutions in coastal environments like NEOM. The proposed MWEC offers a promising path toward low-cost, low-maintenance wave energy harvesting in shallow waters, contributing to Saudi Arabia’s sustainable energy goals. Full article

Coastal communities and marine ecosystems face increasing risks due to changing ocean conditions, yet effective wave monitoring remains limited in many low-resource regions. This study investigates the use of seismic data to predict significant wave height (SWH), offering a low-cost and scalable solution to support coastal conservation and safety. We developed a baseline machine learning (ML) model and improved it using a longest-stretch algorithm for seismic data selection and station-specific hyperparameter tuning. Models were trained and tested on consumer-grade hardware to ensure accessibility and availability. Applied to the Sicily–Malta region, the enhanced models achieved up to a 0.133 increase in R² and a 0.026 m reduction in mean absolute error compared to existing baselines. These results demonstrate that seismic signals, typically collected for geophysical purposes, can be repurposed to support ocean monitoring using accessible artificial intelligence (AI) tools. The approach may be integrated into conservation planning efforts such as early warning systems and ecosystem monitoring frameworks. Future work may focus on improving robustness in data-sparse areas through augmentation techniques and exploring broader applications of this method in marine and coastal sustainability contexts. Full article

This study examines the evolution of a beach formed along the coastline of a semi-enclosed, essentially tideless, embayment in the eastern Mediterranean Sea. The analysis revealed that the primary factors influencing its recent evolution are the terrestrial sediment influxes, current nearshore oceanographic conditions, and the existence of coastal constructions. The beach zone is exposed to waves approaching from the south with extreme values of height and period of 7 m and 4.3 s, respectively. Associated morphodynamic characteristics include a closure depth of 7 m, a breaking depth of 4.3 m, and a maximum run-up of 2.4 m. Since the mid-1900s, the shoreline has evolved through an accretional phase from 1960 to 1988, followed by a retreating phase from 1989 to 1997, except in the central part, where progradation has continued. The most recent period (1998–2017) has been relatively stable, though with a slight retreating trend. During storm events, changes to the beach are not uniform along-shore. Gross estimates of beach retreat due to sea level rise induced by climate change threaten the existence of the entire beach (for moderate and extreme IPCC Special Report Emissions Scenarios); however, this does not seem to be the case if riverine sediment influx continues. Full article

The study focuses on the detection of breaking wave crests in the highly dynamic waters of an Antarctic coastal polynya using high-resolution panchromatic satellite imagery. Accurate assessment of whitecap coverage is crucial for improving our understanding of the interactions between wave generation, air–sea heat exchange, and sea ice formation in these complex environments. As open-ocean whitecap detection methods are inadequate in coastal polynyas partially covered with frazil ice, we discuss an approach that exploits specific lighting conditions: the alignment of sunlight with the dominant wind direction and low solar elevation. Under such conditions, steep breaking waves cast pronounced shadows, which are used as the primary indicator of wave crests, particularly in frazil streak zones. The algorithm is optimized to exploit these conditions and minimize false positives along frazil streak boundaries. We applied the algorithm to a WorldView-2 image covering different parts of Terra Nova Bay Polynya (Ross Sea), a dynamic polar coastal zone. This case study demonstrates that the spatial distribution of detected breaking waves is consistent with ice conditions and wind forcing patterns, while also revealing deviations that point to complex wind–wave–ice interactions. Although quantitative validation of satellite-derived whitecaps coverage was not possible due to the lack of in situ data, the method performs reliably under a range of conditions. Limitations of the proposed approach are pointed out and discussed. Finally, the study highlights the risk of misinterpretation of lower-resolution reflectance data in areas where whitecaps and sea ice coexist at subpixel scales. Full article

Coastal vegetated ecosystems, including tidal marshes, vegetated dunes, and shrub- and forest-dominated wetlands, can mitigate hurricane impacts such as coastal flooding and erosion by increasing surface roughness and reducing wave energy. Land cover maps can be used as input to improve simulations of surface roughness in advanced hydro-morphological models. Consequently, there is a need for efficient tools to develop up-to-date land cover maps that include the accurate distribution of vegetation types prior to an extreme storm. In response, we developed the RUSH tool (Rapid remote sensing Updates of land cover for Storm and Hurricane forecast models). RUSH delivers high-resolution maps of coastal vegetation for near-real-time or historical conditions via a Jupyter Notebook application and a graphical user interface (GUI). The application generates 3 m spatial resolution land cover maps with classes relevant to coastal settings, especially along mainland beaches, headlands, and barrier islands, as follows: (1) open water; (2) emergent wetlands; (3) dune grass; (4) woody wetlands; and (5) bare ground. These maps are developed by applying one of two seasonal random-forest machine learning models to Planet Labs SuperDove multispectral imagery. Cool Season and Warm Season Models were trained on 665 and 594 reference points, respectively, located across study regions in the North Carolina Outer Banks, the Mississippi Delta in Louisiana, and a portion of the Florida Gulf Coast near Apalachicola. Cool Season and Warm Season Models were tested with 666 and 595 independent points, with an overall accuracy of 93% and 94%, respectively. The Jupyter Notebook application provides users with a flexible platform for customization for advanced users, whereas the GUI, designed with user-experience feedback, provides non-experts access to remote sensing capabilities. This application can also be used for long-term coastal geomorphic and ecosystem change assessments. Full article

Understanding the morphodynamic evolution of muddy coasts under complex wave–tidal forcing is crucial for effective coastal management, particularly under the unstable hydrodynamic conditions associated with global climate change. This study employs a one-dimensional Delft3D model to investigate a tidal flat north of Dafeng Port, Jiangsu Province, China, validated with multi-year profile measurements. Under typical conditions, the profile consistently exhibits upper-flat accretion and lower-flat erosion, with threshold values of Hs ≈ 1.2 m and Tp ≈ 4.5 s triggering nonlinear bed-level changes. During storm tides, the profile displays a distinct upper flood-tide and lower ebb-tide response. Long-term simulations suggest that the profile will likely reach dynamic equilibrium by 2026. Overall, this study demonstrates the capability of one-dimensional modeling to capture nonlinear tidal flat evolution and provides valuable insights into the spatially variable morphodynamics of muddy coasts for adaptive management. Full article

Understanding coastal hydraulic processes is essential for sustainable coastal planning and management, especially in semi-arid regions where data scarcity represents a significant challenge. This study sought to apply the Brazilian Coastal Modelling System (SMC-Brasil) to analyse the coastal hydraulic processes present on the Brazilian semi-arid coast in Rio Grande do Norte, seeking to understand its boundary conditions given the scarcity of data and limited monitoring network. The methodological procedures followed five main stages: data collection and processing, running the models, statistical analysis, and interpretation of the results. The simulations identified wave propagation and dissipation patterns influenced by local bathymetric features such as sandy banks and submarine canyons. The modelling indicated waves with an average Hs₅₀% of 1.14 m, with dominant directions from ENE to ESE. Longitudinal flows ranged from 1 to 8 m³/h, with a predominance of east to west at medium and high tides. The modelling indicated spatial gradients of energy and sediment transport compatible with historical records and field observations. The results show that submerged relief irregularities play a central role in regional coastal dynamics, conditioning current flows and deposition. The application of SMC-Brasil has shown potential to fill monitoring gaps in regions with low infrastructure, offering affordable and effective technical support for adaptive coastal planning in the face of climate change impacts. Full article

This study presents the implementation and evaluation of a high-resolution operational forecasting system for the Tagus estuary (Portugal), focusing on inundation and water quality predictions to support estuarine management. Developed using the relocatable Water Information Forecast Framework (WIFF), the system integrates two implementations of SCHISM: a 2D barotropic model including wave–current interactions for flood-prone areas, and a 3D baroclinic model simulating salinity, temperature, and biogeochemical variables. Forecasts were assessed over six months using in situ and satellite near real-time observations. Results show that the operational models represent well water levels, waves, salinity, temperature, and water quality dynamics. Compared to a regional model, the local forecast system generally offers improved accuracy within the estuary due to higher spatial resolution and better representation of local dynamics. Several challenges remain, including uncertainties in oceanic and riverine boundary conditions and limited high-resolution near real-time observations to continuously assess and improve operational models. Furthermore, the absence of operational two-way coupling between regional and local models limits cross-scale integration of physical and biogeochemical processes. The forecasting system for the Tagus estuary demonstrates the potential of local high-resolution operational models as reliable, user-oriented tools for managing transitional water systems, and as core elements for coastal management. Full article

Silty seabed sediments in the subaqueous delta of the Yellow River are heavily contaminated with petroleum-derived polycyclic aromatic hydrocarbons (PAHs). Storm-induced sediment resuspension and liquefaction are key mechanisms responsible for the remobilization of PAHs into the overlying water column. In this study, laboratory-scale wave flume experiments were conducted to simulate PAH release under three hydrodynamic scenarios: (i) static diffusion (Stage I), (ii) low-intensity wave action (5 cm wave height, Stage II), and (iii) high-intensity wave action (12 cm wave height, Stage III). Results revealed a strong positive correlation between suspended particulate matter (SPM) and PAH concentrations in the aqueous phase during sediment disturbance. In particular, sediment liquefaction significantly enhanced PAH release, with concentrations up to five times higher than those under static conditions. Furthermore, liquefaction facilitated vertical migration of PAHs within sediments, resulting in reductions in PAH levels below the original background concentrations. The release dynamics varied notably among PAH species: low-molecular-weight (2–3 ring) PAHs, with lower hydrophobicity, were primarily detected in the aqueous phase, while medium- and high-molecular-weight PAHs remained predominantly associated with sediment particles. These findings underscore the critical role of hydrodynamic disturbances—especially sediment liquefaction—in influencing PAH mobility and offer important implications for pollution risk assessment and coastal management in storm-impacted deltaic environments. Full article

This study presents an analytical model to reduce the impact of wave-induced forces on a vertical seawall by introducing a floating elastic plate (EP) located at a specific distance from two bottom-standing porous structures (BSPs). The hydrodynamic interaction with the EP is described using thin plate theory, while the fluid flow through the porous medium is described by the model developed by Sollit and Cross. The resulting boundary value problem is addressed through linear potential theory combined with the eigenfunction expansion method (EEM), and model validation is achieved through consistency checks with recognized results from the literature. A comprehensive parametric analysis is performed to evaluate the influence of key system parameters such as the porosity and frictional coefficient of the BSPs, their height and width, the flexural rigidity of the EP, and the spacing between the EP and BSPs on vital hydrodynamic coefficients, including the wave force on the seawall, free surface elevation, wave reflection coefficient, and energy dissipation coefficient. The results indicate that higher frictional coefficients and higher BSP heights significantly enhance wave energy dissipation and reduce reflection, in accordance with the principle of energy conservation. Oscillatory trends observed with respect to wavenumbers in the reflection and dissipation coefficients highlight resonant interactions between the structures. Moreover, compared with a single BSP, the double BSP arrangement is more effective in minimizing the wave force on the seawall and free surface elevation in the region between the EP and the wall, even when the total volume of porous material remains unchanged. The inter-structural gap is found to play a crucial role in optimizing resonance conditions and supporting the formation of a tranquility zone. Overall, the proposed configuration demonstrates significant potential for coastal protection, offering a practical and effective solution for reducing wave loads on marine infrastructure. Full article

Accurate wave forecasting under typhoon conditions is essential for coastal safety in the Pearl River Estuary. This study explores the use of Random Forest (RF) and Long Short-Term Memory (LSTM) models to predict significant wave heights, using SWAN-simulated data from 87 historical typhoon events. Ten representative typhoons were reserved for independent testing. Results show that the LSTM model outperforms RF in 3 h forecasts, achieving a lower mean RMSE and higher R², particularly in capturing wave peaks under highly dynamic conditions. For 6 h forecasts, both models exhibit decreased accuracy, with RF performing slightly better in stable scenarios, while LSTM remains more responsive in complex wave evolution. Generalization tests at three nearby stations demonstrate that both models, especially LSTM, retain strong predictive skill beyond the training location. These findings highlight the potential of combining numerical wave models with machine learning for short-term, data-driven wave forecasting in typhoon-prone and observation-sparse regions. The study also points to future improvements through integration of wind field predictors, model updating strategies, and ensemble meteorological data. Full article

In recent years, the irregular wave characteristics of ocean dynamics have often been overlooked in the study of the driving mechanism of groundwater movement in coastal aquifers. To clarify the propagation mechanisms of groundwater fluctuations driven by irregular waves in beach aquifers, we employed spectral analysis based on numerical simulations to examine the energy migration processes and evolution characteristics of wave signals at different frequencies. It elucidates the response mechanism of groundwater movement characteristics (head, velocity) to irregular waves in the sea. The energy density in the low-frequency region is enhanced compared to the incident wave and continuously increases in the direction away from the sea within the aquifer. The wavelet power corresponding to the 1/2 spectral peak frequency is significantly enhanced. The energy density in the high-frequency region is generally weaker than that of the incident waves, and the wavelet power corresponding to double spectral peak frequency is enhanced. The correlation between incident waves and groundwater fluctuations is highest near the spectral peak period. This study addresses some problems in modeling surface water–groundwater interactions under irregular wave conditions and provides a theoretical reference for investigating the impacts of extreme climate events (such as typhoon waves and low-frequency offshore oscillations generated by storm surges) on seawater intrusion into coastal groundwater systems. Full article