Hybrid sea defences that incorporate both natural habitats and artificial structures (such as seagrass and artificial reefs) for coastal protection have gained traction because of their dual benefits of ecological enhancement and wave attenuation. However, while the hydrodynamic performance of individual components has been reported, the synergistic effects of such an innovative combination on the wave energy dissipation remain underexplored. This study, for the first time, investigates the hydrodynamic performance of a hybrid structure composed of seagrass and porous artificial reefs through a series of laboratory-scale experiments. Wave transmission, reflection, and dissipation were analysed under both swell and storm representative sea conditions. The developed seagrass mimics exhibit geometric and physical similarities to the real seagrass, Zostera marina. Two types of porous artificial reefs, cubic and trapezoidal, were considered in the current study. The results demonstrate that the presence of seagrass enhances wave attenuation, reducing wave transmission coefficients by up to 9.2% for cubic reefs and 8.6% for trapezoidal reefs compared to bare reef conditions. To quantify this engineering benefit more intuitively, an 'equivalent height enhancement index' is introduced, which represents the reef height increment required for a bare reef to achieve the same wave attenuation as the hybrid system. It was found that the seagrass canopy contributes an equivalent reef height enhancement of up to 39.0% for trapezoidal reefs and 22.2% for cubic reefs. Furthermore, a new empirical model was developed to predict the seagrass contribution to equivalent reef height in the hybrid system. The proposed model provides a foundation for developing practical tools for coastal engineers and stakeholders to design sustainable hybrid sea defences.
During inundation, tsunami-induced scour is a major threat to the stability of onshore coastal structures. Nevertheless, the majority of current experimental research concentrate on single structures orientated perpendicular to the flow propagation, while in the real environment, coastal structures often arranged in sheltered and rotated configurations against the incident waves. This study delineates large-scale experimental research analysing tsunami-induced scour around onshore rectangular and square structures under two different setups: (i) two structures positioned in a sheltered arrangement, and (ii) single structures orientated at a 45°angle to the incoming flow. Three representative long waves with periods of 20 s, 49 s, and 147 s are generated in the HR Wallingford Fast Flow Facility using a pneumatic tsunami generator. Overhead video observations and GoPro camera are employed to analyse the maximum scour depth, spatial development of scour, and flow-structure interaction.The results show that the upstream structure modifies the flow and sediment transport processes around the downstream structure, generally reducing scour development at the rear structure through wake sheltering. The magnitude of this reduction depends on tsunami-wave period, inundation duration, and structural geometry. In contrast, structural rotation changes the flow–structure interaction by directing the incoming flow towards an exposed corner and along the adjacent faces, promoting localised scour near the corners and enhancing lateral base vortex activity. Rotated structures generally produced greater scour than the corresponding non-rotated cases, although the degree of increase varied with wave period and geometry. These findings demonstrate that structural arrangement and orientation can significantly influence the magnitude, location, and temporal development of tsunami-induced scour. The study provides new experimental evidence for improving tsunami scour hazard assessment, resilient coastal layout design, and numerical model validation for non-isolated and obliquely aligned coastal structures.
Hybrid artificial–biological reefs have emerged as a promising strategy for achieving the longer-term goal of ecological coral restoration while providing immediate coastal defense benefits. Although there are a growing number of hybrid reef types and morphologies, there are nearly as many approaches for defining these structures’ hydrodynamic performance. This study presents a new type of hybrid reef structure composed of porous sub-elements that conduct water through the reefs via engineered flow pathways that are intended to (1) dissipate wave energy through breaking and internal friction, and (2) mimic the flow field of natural coral reefs. The aim of this work is to identify optimal reef configurations through rigorous testing, establishing a validated physical and numerical framework prior to construction and deployment. Here, we validate the multi-row reef designs at 1:10 scale in a physical wave tank under regular and irregular wave conditions. Regular wave conditions were then used to calibrate and validate a numerical wave tank (NWT) via the OpenFOAM computational fluid dynamics framework, to develop a deeper understanding of the hydrodynamics and forces acting on and being generated by these reefs. Results indicate that reducing the number of reef rows from three to two only decreases wave energy reduction by 13%, while reducing the total structure footprint by 33%, demonstrating a favorable cost-performance trade-off. The specific reef geometry also strongly influences internal flow, pressure gradients, and drag forces, suggesting minor changes to the reef structural design can meaningfully alter hydrodynamic performance. Yet, all designs are stable for sliding and overturning under the tested conditions. While the offshore reef experiences greater turbulence and surface shear stresses, a sheltering effect on the onshore reef creates a lower stress environment that may be more suitable for coral cultivation.
The Bhola Island coast of Bangladesh is highly dynamic and increasingly affected by shoreline instability and land loss. This study provides one of the first systematic benchmarking assessments of multiple machine learning approaches against standardized DSAS shoreline indicators for a highly dynamic deltaic coastline, while transparently reporting genuine held-out forecasting performance rather than in-sample accuracy. This study analyses changes in the coastline between 1990 and 2025 and assesses the performance of indicators based on the DSAS for analysis and forecasting. Shoreline positions were extracted from multi-temporal Landsat imagery using the Modified Normalized Difference Water Index (MNDWI). Change rates were calculated using End Point Rate (EPR), Linear Regression Rate (LRR), and Weighted Linear Regression (WLR) within the Digital Shoreline Analysis System (DSAS). A total of 2 244 transects were analyzed and grouped into seven alongshore segments. Shoreline sinuosity was also assessed. To extend the analysis, multiple supervised machine learning approaches, including Random Forest, XGBoost, Gaussian Process Regression (GPR), Support Vector Regression (SVR), Multi-Layer Perceptron (MLP), Bayesian Ridge Regression, K-Nearest Neighbors (KNN), Monte Carlo simulation, and an ensemble framework, were evaluated to forecast shoreline positions for 2030, 2040, and 2050. Results show that shoreline change is strongly erosion-dominated, with an average long-term rate of −33.73 m/year. Erosion was observed in 1798 transects, while accretion occurred in 446 transects. Severe erosion is concentrated in the central and northern segments, whereas accretion is limited to the southern segment. Short-term analysis confirms persistent erosion across most periods. Among the evaluated models, Random Forest achieved the lowest prediction error (MAE = 6.64 m/year; RMSE = 33.49 m/year), although R2 values were negative across all approaches (−0.07 to −3.12), indicating that none of the models outperformed a mean-predicting baseline on genuinely unseen transects. Future projections indicate contrasting shoreline evolution among forecasting approaches. Random Forest, XGBoost, KNN, GPR, SVR, and Monte Carlo largely maintain erosion-dominated conditions, whereas MLP and Bayesian Ridge Regression predict increasing shoreline stabilization or accretion over time. Sinuosity exhibits moderate temporal variation. Overall, the Bhola coast is experiencing continuous and spatially uneven erosion, which highlights the need for integrated, predictive and analytical approaches to coastal management.
With regard to the seabed response and local scouring of wind turbine monopiles under the coupled action of currents and vibrations, existing studies have predominantly relied on constant-amplitude cyclic loading, an approach that fails to adequately represent the irregular influence characteristics of the narrow-band random vibration of the tower in practical engineering. The present study was carried out in a wave-current flume, where a total of 27 test conditions were established by varying the incident flow velocity, vibration type, and vibration intensity, to monitor the pore pressure distribution in the seabed around the pile and the corresponding scour topography. Results indicate that flow velocity is a critical factor influencing pore pressure response; increasing velocity intensifies vortex shedding strength and frequency, thereby elevating pore pressure amplitude. Narrow-band random vibration induces a stronger pore pressure response compared to sinusoidal vibration. Increased vibration intensity exacerbates energy dissipation in shallow soil layers, subsequently inhibiting local scour development. Vibration also causes the deposition peak downstream of the pile to shift further downstream, resulting in a more dispersed scour hole morphology. It is recommended that the relative scour depth reduction coefficient proposed in this study be adopted in engineering practice when narrow-band random vibration is of concern.
In addition to accuracy and speed, tsunami inundation forecasts should also account for the uncertainty primarily attributed to the earthquake slip distribution, particularly for near-field events. We propose a method based on artificial intelligence (AI) to timely forecast the tsunami inundation from megathrust earthquakes and efficiently quantify such uncertainties. We trained the AI-based tsunami model using 630 hypothetical scenarios representing a wide range of plausible tsunami occurrences in Pacitan regency, southern coast of Java, Indonesia. In the inference stage, the AI model requires inputs of synthetic tsunami waveforms at specified locations obtained through a Green's function summation technique. Such an approach enables the rapid generation of tsunami waveforms from the corresponding stochastic slip models. Subsequently, the AI model runs multiple ensemble tsunami inundation forecasts derived from its varying set of inputs. The final product of the AI-based ensemble model comprises multiple potential tsunami inundation results as the basis for probabilistic forecasts, and from which the forecast uncertainty can be explicitly defined. A test on an anticipated event generated by an earthquake off the south coast of Java of Mw 8.8 produces an inundation forecast accuracy of 92% using the median ensemble forecast, whereas the standard method based on a uniform slip yields 85%. However, it is noted that the effects of depth-dependent rigidity and tsunami earthquakes are not yet included.
Coastal flood hazard estimates rely on precise hurricane wind forecasts to assess damage and risk. Here, we demonstrate that errors in hurricane wind field representation can lead to significant biases in storm surge and property-level damage estimates. Using Hurricane Ian (2022) as a case study, we compare widely used parametric, reanalysis, and hybrid wind datasets. Parametric models, mainly Holland (2010), systematically overpredict wind speeds by up to 28 m/s, while global reanalysis products (ERA5, CFSR) underpredict peak intensities due to their coarse horizontal resolution. Hybrid wind products that blend reanalysis with high-resolution tropical cyclone analyses achieve a better performance, with calibrated variants reducing peak water level bias to less than 0.05 m. Sensitivity experiments reveal that storm surge responds more strongly to variations in radius of maximum winds than to equivalent intensity changes, highlighting the importance of accurate wind field spatial structure. These controlled experiments also demonstrate that errors in hurricane wind spatial structure can bias peak storm surge by up to ∼70%, and wind forcing choice shapes building-scale distributions of flood depth and flow velocity, with direct implications for emergency management, evacuation planning, and coastal infrastructure design.
This paper presents experimental results for breaker indices as well as wave breaker types for 10 different irregular wave conditions propagating over two different constant sloping profiles as well as two barred profiles. Using video cameras, the breaking locations and breaker types have been identified for more than 8,000 individual waves. The results from the video analysis are coupled with high spatial resolution wave gauge measurements for determination of the breaker indices. Cross-shore evolution of both breaker type and breaker indices are presented, and it is demonstrated that both plungers and spillers are present across the entire coastal profiles and that there is a large cross-shore variation in breaker indices and types even for fixed wave conditions. Similar to previous research, it is shown that plungers have higher breaker indices than spillers and that breaker indices generally increase in shallower water. Measured breaker indices are compared with common empirical formulations from the literature, and a novel formulation is suggested. Finally, parameterizations for the prediction of breaker type are suggested, which can be used on non-constant sloping profiles in contrast to previous formulations. The suggested parameterizations can potentially be used to improve practical coastal engineering models for wave evolution, sediment transport and forces on structures.
In this study, we investigate experimentally and numerically the wave-induced loading and wave attenuation performances of a multifunctional artificial reef with a coral canopy intended for both restoration and shore protection, with special focus on an optimization to achieve good wave attenuation under minimal wave-induced loading by considering different restoration sites across the reef flat. An array of realistic coral branch units is placed on the artificial reef surface to more accurately represent the effect of coral canopies on the hydrodynamic processes in both the experiments and the numerical simulations. It is found that both the wave attenuation performance and the wave-induced loading characteristics are sensitive to the selection of site on the reef flat relative to the reef edge. Locally optimum site selection is possible where the wave attenuation is optimally balanced with a relatively small wave-induced loading amplitude under given wave conditions; placing the artificial reef base at around the middle of the reef flat produced better overall performance, significantly better in terms of both wave energy dissipation and reducing wave loading. Analysis indicates that a second round of wave breaking, in tandem with resonance of partial standing waves are the main reason for this phenomenon. This finding highlights the necessity to carefully consider the site selection when planning multifunctional artificial reefs. Additionally, turbulence structure inside the coral canopy is also investigated and visualized using the Q-criterion method, confirming the effect of the coral canopy in enhancing wave energy dissipation as waves passes the artificial reef base.
In-situ monitoring of waves is usually limited to provide spatio-temporal information. However, remote sensing tools (RSTs) can be complementary to eliminate this limitation. In this study, a novel framework, Lightweight Image Assimilation (LMS), has been developed for RSTs which is capable to gather information on hydro-morphodynamics by utilizing Radon transformation, advanced signal processing methods, and histogramming to eliminate outliers. LMS was tested at our study site where two different RSTs were deployed: an X-Band Radar and a video monitoring system. LMS has been benchmarked with field observations and alternative processing tools by utilizing radar images, which are collected every hour with 0.5 Hz frequency. The statistical measurements showed that LMS was capable to reconstruct the evolution of wave characteristics (e.g. significant wave height, r2=0.79, RMSE=0.21m) and the bathymetry (r2=0.70, RMSE=0.55m). LMS outperformed alternative tools despite less computational demand. However, a systematic overestimation was observed for all methods and the performance was affected by cross-sea altered signals where LMS allowed to diagnose the source of alteration. The wave characteristics derived from the framework were used to force the phase-resolving model to investigate coastal inundation and compare with empirical formulations. Consequently, the framework can be used as a comprehensive tool to investigate hydro-morphodynamic processes, their impacts on the coastal regions, and to have an insight on the coastal resilience.
Satellite-derived waterlines (SDWs) have become a key source of beach morphological information widely used for coastal monitoring. Nevertheless, the robustness of the extraction methods and the resulting SDW accuracy may be substantially compromised in macrotidal and/or energetic coasts with complex intertidal morphology. This study evaluates the performance of 12 combinations of water indices (MNDWI, NDWI, AWEINSH, SCoWI) and thresholding methods (thresholding at 0, Otsu, and Otsu modified) for SDW extraction from Sentinel-2 imagery at two macrotidal beaches. A robust multi-date validation framework was developed by comparing hundreds (285) of SDWs (2015–2024) against simultaneous reference waterlines photointerpreted from Sentinel-2 and independently benchmarked using very-high-resolution imagery across 255 km of European coastline. The assessment of the SDWs was carried out in two macrotidal beaches of the Atlantic coast in northern Spain (El Puntal and Salinas) with complex intertidal morphology that present differences in terms of the nearshore hydrodynamic conditions, the frequency and extension of the foam, and the sand color. Results show strong site-specific differences: El Puntal exhibits consistently lower offsets, whereas Salinas shows much larger variability and occasional extreme biases (>50 m). Across sites, SCoWI combined with the Otsu modified thresholding method provides the lowest sensitivity to hydrodynamic or morphological conditions at both sites (5.7 m and 7.6 m RMSE in El Puntal and Salinas, respectively), constituting the most robust solution. Correlation analyses reveal that tidal level dominates offset variability in Salinas, especially during low and ebb tides when wet intertidal areas are misclassified as water. To a lesser extent, wave action also introduces uncertainty in some index–threshold combinations. The findings highlight the primacy of the initial water/land segmentation step over subpixel refinement in macrotidal settings and support the development of site-specific flagging strategies to filter unreliable SDWs.
This study presents a comprehensive validation and application of an advanced Smoothed Particle Hydrodynamics (SPH) method for investigating wave overtopping at rubble-mound coastal revetments. The numerical framework is based on the SPH–porous media model developed by Jandaghian et al. (2025), incorporating volume-adaptive particle formulations and enhanced stabilization techniques. We evaluate the performance of this model in simulating long-duration breaking-wave interactions with permeable coastal revetments under regular and irregular wave conditions across multiple structural designs. A theoretical benchmark case of seepage flow through multi-layer porous media with distinct porosity and grain size is first considered to assess numerical accuracy and convergence. The model is then applied to simulate monochromatic wave overtopping of a permeable revetment protecting a vertical seawall, including calibration of drag force parameters and particle resolution. Subsequently, a systematic validation and application study is conducted for irregular wave overtopping at rubble-mound revetments under three scenarios with multiple rock-armoured layers. Results demonstrate that the model accurately reproduces wave propagation and overtopping processes across all cases, supported by qualitative and quantitative analyses of wave characteristics and discharge rates, while also identifying model limitations. The findings emphasize the importance of calibrating empirical drag coefficients for physically consistent overtopping estimates. Overall, this work provides the first comprehensive evidence of the reliability and robustness of the SPH–porous media model for wave overtopping performance, supporting design optimization and risk assessment of coastal protection structures.
