Search Results (308)

Accurate three-dimensional characterization of turbulent flows in natural waterways is essential for the effective design of tidal farms and other critical infrastructure situated along or across rivers. High-fidelity predictions based on the large-eddy simulation (LES) method capture the necessary physics but incur computational costs that hinder rapid scenario testing. Statistically, a relatively long history of instantaneous flow fields is required to generate reliable turbulence statistics, e.g., mean velocity and Reynolds stresses, of river flow. Such a requirement often incurs high simulation runtime and data storage costs. This study seeks to develop a neural network surrogate model that learns from a limited number of instantaneous flow realizations and approximates the outputs of the corresponding time-averaged fields with LES-level accuracy. Such a surrogate would eliminate the need to accumulate extensive ensembles, enabling faster hydrodynamic assessment and making LES-informed analyses more accessible for practical engineering decisions. Full article

Most remote sensing extraction studies utilizing vegetation indices typically classify and extract land cover features based on the phenological characteristics of the study area or rely on a single vegetation index. When attempting to extract multiple land cover types simultaneously, classification accuracy often declines significantly because a single vegetation index is unsuitable for all features. While some recent studies employ deep learning and neural networks for classification and extraction, their complex mechanisms and “black-box effect” hinder clear explanations for accuracy outcomes. In response to the issues outlined above, this paper proposes a simpler and more intuitive method for the hierarchical extraction of typical land cover features. This approach analyzes the difficulty of separating these features based on spectral reflectance data to determine the following extraction order: first water bodies, followed by reed, then Suaeda salsa, and finally tidal flat. Furthermore, by selecting appropriate parameters and substituting vegetation indices for bands that perform better, high extraction accuracy is achieved. The classification and interpretation results were validated using a combination of field survey data and Google imagery, together with a validation sample. Accuracy assessments using overall accuracy and Kappa coefficient demonstrate the following optimal results for the hierarchical approach: NDWI for water, S2REP for reeds, and MSAVI for Suaeda salsa. Overall accuracy reached 98.5% with a Kappa coefficient of 0.9796, validating the effectiveness of this spectral-feature-based hierarchical extraction method using diverse vegetation indices. Using a hierarchical extraction approach to classify typical land cover features in the study area from 2020 to 2025, accuracy rates exceeded 98% in all cases. Based on these classification results, the INVEST model was employed to simulate carbon stock trends in the Liaohe Estuary region over the past five years. The study found that, although factors such as tides and the date of image acquisition had a certain impact on the study area compared with the problems caused by historical development, the ecological environment in the study area is gradually stabilizing at the present stage. Full article

High-precision topography of tidal flats is essential for coastal monitoring, geomorphic change analysis, and ecological assessment. Although satellite remote sensing supports repeated and large-area observation, topographic inversion over small-scale tidal flats—here defined as localized intertidal patches with limited areal extent, represented in this study by a 1.11 km² tidal flat near Dafeng Port—remains challenging, because ICESat-2 laser altimetry tracks across such areas are typically sparse and spatially clustered within narrow sub-regions, leaving extensive observation-blind zones without direct elevation labels. This label-clustering problem constrains the applicability of traditional empirical models and tends to cause deep learning models to generalize poorly beyond the spatial distribution of training samples. To address this issue, this study proposes a Residual Attention Physical-constraint Semi-supervised U-Net (RAPS-UNet) that fuses ICESat-2 ATL03/ATL08 elevation labels with Sentinel-1 SAR and Sentinel-2 optical features. The preprocessing pipeline comprises refined ICESat-2 photon filtering, adaptive inundation-frequency extraction, multi-source feature selection, and baseline DEM construction. RAPS-UNet integrates residual learning, attention-based multi-source fusion, physics-constrained loss, and confidence-weighted pseudo-label augmentation to improve extrapolation under clustered-label conditions. A four-level validation protocol—in-distribution validation, spatial holdout testing, and field-based assessment over both interpolation and extrapolation zones—was designed to evaluate spatial generalization. Against a field-surveyed DEM, RAPS-UNet achieved an overall RMSE of 0.20 m, an MAE of 0.16 m, and an R² of 0.91; the field-based interpolation and extrapolation zones yielded RMSEs of 0.17 m and 0.22 m, respectively, while the spatial holdout test reached an RMSE of 0.23 m and an R² of 0.81. Relative to the traditional inundation frequency–elevation linear model (RMSE = 0.35 m), RAPS-UNet reduced the field-validation RMSE by approximately 43%. The proposed framework therefore offers a practical approach for fine-scale coastal-zone topographic mapping under sparse and spatially clustered altimetry conditions. Full article

This study investigates tide–surge nonlinear interactions along the southeastern coast of China (SCC) using Typhoon Winnie as a case study. A coupled tide–surge model is established based on the Finite-Volume Community Ocean Model (FVCOM), incorporating realistic bathymetry, tidal constituents, wind fields, and atmospheric pressure. The results show that tide–surge interactions contribute up to 1.8 m to the total water level, with the most pronounced effects occurring in shallow, high-friction coastal regions such as Hangzhou Bay, the Yangtze River Estuary, and the Jiangsu coast. Sensitivity experiments reveal that the quadratic bottom friction term is the dominant mechanism driving the nonlinear interaction, while the advection term plays a secondary role. The interaction intensity is highly sensitive to water depth and topographic slope; reducing water depth generally intensifies the interaction, though the response is non-monotonic in regions with complex bathymetry such as the radial sand ridge field. The phase and period of astronomical tides also exert significant control. Notably, semi-diurnal constituents (e.g., M₂, S₂) dominate the interaction, accounting for up to 80% of the nonlinear effect, whereas diurnal constituents contribute negligibly (less than 0.1 m). Tide–surge coupling significantly affects both the magnitude and timing of extreme water levels, with enhanced interaction occurring during astronomical low tide at some stations (e.g., Dinghai). These findings underscore the necessity of incorporating tide–surge interactions, particularly with accurate bottom friction and semi-diurnal tidal forcing, into storm surge models for improved forecasting and disaster risk assessment along China’s southeastern coast. Full article

The global transition to a diversified renewable energy portfolio requires reliable assessment of predictable marine energy resources. This study develops a high-resolution, three-dimensional Regional Ocean Modeling System (ROMS) to quantitatively evaluate theoretical tidal current energy resources in the Bohai and Yellow Seas. The model, configured with fine-scale bathymetry and forced by harmonic tidal constituents, is validated against tide gauge and Acoustic Doppler Current Profiler (ADCP) observations. Multi-year simulations reveal pronounced spatial heterogeneity in tidal current energy distribution. Rather than treating resource assessment as a single power density mapping exercise, this study combines annual mean theoretical power density, peak theoretical power density, threshold-dependent effective flow duration, effective water depth, current directionality, and vertical velocity structure to characterize resource intensity, temporal persistence, and vertical deployability. The results identify distinct hydrodynamic resource regimes. High theoretical resource intensity is concentrated west of Laotieshan Cape and east of Chengshantou, where cumulative annual effective flow duration exceeds 5000 h and short-term instantaneous theoretical power density can reach approximately 10 kW/m² and 8 kW/m², respectively. These peak values indicate strong local tidal acceleration but should be interpreted together with annual mean power density and effective flow duration. In contrast, the northern Jiangsu coastal area exhibits lower peak intensity but relatively persistent moderate flow conditions. The results provide a hydrodynamic resource basis for preliminary site screening and for guiding subsequent turbine-performance, wake/array, environmental, grid accessibility, and techno-economic assessments. Full article

Tropical estuaries are socioeconomically important yet highly vulnerable environments. In the eastern Amazon, the Pará River Estuary (PRE) and adjacent water bodies support the city of Belém and are increasingly affected by environmental pressures but remain underrepresented in numerical modeling efforts. The influence of key input parameters on hydrodynamic model performance in these systems remains poorly characterized, hindering the development of reliable simulation tools for this region. We present the calibration and validation of a two-dimensional hydrodynamic model for the PRE, Guajará Bay, and the Guamá River, examining how parameters such as bathymetry, roughness, and tidal and discharge forcings influence model performance. Delft3D-FM was applied using tidal harmonics and seasonal river discharge as primary forcings, with model skill evaluated against observed water levels and discharge across ten seasonally distinct scenarios over seven calibration iterations. Tidal forcing and bathymetric representation emerged as the dominant performance drivers: replacing global tidal datasets with locally derived harmonics substantially reduced simulation errors, and bathymetric refinements also improved discharge representation. Final performance met established satisfactory thresholds at the majority of observation points and cross-sections. The calibrated model provides a basis for investigating processes governed by local hydrodynamics, such as water quality assessments, contaminant dispersion, and infrastructure planning. Full article

Coastal reclamation reshapes tidal hydrodynamics in semi-enclosed bays by removing intertidal storage, modifying channel conveyance, and redistributing tidal exchange among connected sub-regions. This study quantifies the multi-decadal cumulative impacts of reclamation on tidal currents and tidal prism in Yueqing Bay, China, using shoreline and bathymetric reconstructions for 1978, 2002, 2013, and 2020; hydrological observations; and a two-dimensional MIKE21 FM tidal hydrodynamic model. Characteristic cross-sections were used to estimate bay-wide and sub-regional tidal prisms, and representative stations were used to diagnose current-speed responses. The bay-wide tidal prism decreased from 15.235 × 10⁸ m³ in 1978 to 12.316 × 10⁸ m³ in 2020, corresponding to a reduction of 2.919 × 10⁸ m³ (19.16%). The strongest loss occurred during 1978–2002, when large-scale reclamation and closure of the Xuanmen Channel removed tidal storage and redirected flow into the remaining main-channel system. Although reclamation intensity weakened after 2013, mean current speed still changed by −0.050 to 0.033 m/s and sub-regional tidal-prism shares continued to adjust, indicating delayed hydrodynamic reorganization rather than immediate stabilization. These results show that reclamation impacts cannot be explained by reclaimed area alone; they depend on project timing, spatial layout, and the connectivity with key tidal pathways. The findings support staged assessment and pathway-sensitive shoreline management in reclaimed semi-enclosed bays. Full article

Sea level rise poses a major threat to dry beach areas, particularly in low-lying and managed coastal environments. Reliable assessments of future beach vulnerability therefore require the combined consideration of sea level rise, tidal regime, meteorological forcing, and wave-driven processes. Here, a physically based methodology is applied to evaluate future inundation and beach response at five representative sandy beaches along the southern coast of Spain. The selected sites span mesotidal Atlantic and microtidal Mediterranean settings. The approach integrates present-day conditions with sea level rise projections under RCP 4.5 and RCP 8.5 scenarios, astronomical tide, and meteorological residuals. Wave run-up is estimated using the IH2VOF CFD (Computational Fluid Dynamics) model. Extreme still water levels and maximum inundation levels are derived for mid-century (2026–2045) and end-of-century (2081–2100) periods, and their impacts on available dry beach surface and beach width are quantified using cross-shore profiles. Results indicate a progressive reduction in dry beach surface and width across all sites, with impacts intensifying from mid- to end-century and from moderate to high-emission scenarios. While losses remain comparatively moderate under still-water assumptions, the inclusion of wave effects leads to substantially larger impacts. At the most vulnerable sites, dry beach surface losses reach up to 80% under still-water conditions, and up to complete loss (100%) when wave run-up is included, particularly along the mesotidal Atlantic coast. Overall, the results demonstrate that neglecting wave run-up can lead to a substantial underrepresentation of future beach inundation, and that its explicit inclusion provides a more reliable basis for beach management and adaptation planning under sea level rise. Full article

Tidal energy assessment in tropical estuaries is constrained by low current velocities and high spatial variability, which limit conventional evaluation approaches. This study proposes a methodological framework adapted to velocity-constrained environments. The framework integrates ADCP-calibrated hydrodynamic modeling, velocity-exceedance-based site selection, low cut-in tidal turbine compatibility analysis, and a localized Levelized Cost of Energy evaluation within a unified decision-support structure. The methodology is applied to Buenaventura Bay, Colombia, where numerical simulations reproduce the mixed tidal regime with errors of approximately 0.30 m in water levels and 0.022 m/s in current velocities, enabling consistent characterization under low-flow conditions. Results at three locations indicate average available power densities of 64 W/m² at La Bocana, 19 W/m² at Buoy 29, and negligible values at Aguadulce, supporting the identification of marginal and non-viable sites based on velocity distributions. Under a low-velocity turbine configuration (10 m rotor diameter, 0.4 m/s cut-in speed), annual energy production is about 18 MWh per unit, while a 300-turbine array would generate approximately 5.4 GWh per year. The results indicate that annual energy production and capital expenditure are the main drivers of techno-economic feasibility in low-energy estuarine systems. Full article

Human modification of tidal embayments, estuaries, and deltas through polders, dykes, and embankments has profoundly altered sediment dynamics and coastal morphology worldwide. Mont-Saint-Michel Bay (northwestern France) exemplifies a macrotidal system affected by large-scale land reclamation, accelerated infilling, rapid saltmarsh expansion, and progressive loss of the insular character of the World Heritage abbey. To restore its maritime setting, a large-scale restoration programme initiated in the 1990s combined engineering measures with nature-based management, including embankment removal, managed retreat, and controlled hydraulic flushing. Future morphodynamic evolution was initially assessed using a movable-bed physical model complemented by numerical simulations. Here, a 22-year LiDAR dataset is used to quantify post-restoration topographic changes and sediment budgets, and evaluate model performance. The results show enhanced erosion and deepening of tidal flats around Mont-Saint-Michel, indicating effective sediment export, together with spatial redistribution of salt marshes that maintained the overall ecological value of the bay. Discrepancies between model predictions and field observations reflect both the difficulty of reproducing long-term channel migration variability and evolving hydro-meteorological forcing conditions, as well as differences between the initially modelled restoration scheme and the engineering works ultimately implemented. This study provides a rare multi-decadal comparison between pre-project morphodynamic forecasts and post-restoration observations. The results highlight both the potential and the limitations of long-term morphodynamic forecasting in non-stationary tidal systems undergoing anthropogenic modifications and climate-driven environmental change, emphasising the importance of long-term monitoring and adaptive management strategies. Full article

Marine renewable energy systems, including offshore wind, tidal, and wave technologies, are central to global decarbonisation strategies but remain constrained by reliability-driven costs and uncertainty in long-term structural performance. Existing qualification approaches are largely based on empirical methodologies and deterministic safety factors that inadequately capture coupled degradation mechanisms operating in harsh offshore environments. This review presents a mechanism-based perspective on structural integrity in marine renewable energy systems by linking microstructure-sensitive deformation and damage processes with engineering-scale reliability assessment. Key degradation mechanisms, including corrosion–fatigue, hydrogen embrittlement, wear, and manufacturing-induced variability, are critically examined together with their interactions across multiple length scales. The review synthesises recent advances in multiscale modelling frameworks spanning crystal plasticity, damage mechanics, fracture mechanics, probabilistic reliability methods, and digital twin technologies. Particular emphasis is placed on the role of manufacturing variability, inspection-informed updating, and hybrid physics–data approaches in improving predictive capability and reducing uncertainty. The review identifies major limitations in current offshore qualification practice, including uncoupled degradation assumptions, insufficient representation of manufacturing effects, and limited integration of monitoring data within lifecycle assessment. Building on these findings, an integrated framework is proposed that combines multiscale modelling, manufacturing-aware qualification, adaptive inspection, and digital twin-enabled updating to support predictive and reliability-informed structural integrity assessment for next-generation marine renewable energy systems. Full article

Background and Perspectives: Obstructive sleep apnea (OSA) is a prevalent condition associated with increased perioperative risks. Endobronchial ultrasound (EBUS), a diagnostic and staging procedure requiring deep sedation, may pose additional risks for patients at high risk of OSA. The Integrated Pulmonary Index (IPI), derived from capnography and vital signs, offers a single numerical value reflecting respiratory status. This study aimed to assess the association between high OSA risk and adverse events using the IPI during EBUS under sedation. Materials and Methods: This prospective cohort study included 65 patients undergoing EBUS with sedation between December 2024 and April 2025 at a tertiary referral center. STOP-Bang questionnaire scores were used to stratify patients into high- (≥3) and low-risk (<3) OSA groups. During the procedure, IPI, oxygen saturation, end-tidal carbon dioxide, respiratory rate, and hemodynamic parameters were recorded at multiple time points. Hypoxemia, hypoventilation, and apnea were defined using standard thresholds. Logistic regression and Generalized Linear Mixed Models (GLMM) were applied to examine associations between OSA risk and respiratory outcomes. Results: Forty-three patients (66.2%) were classified as high risk for OSA. Patients with high STOP-Bang scores were older and had higher BMI, comorbidity rates, and ASA scores (all p < 0.05). IPI values were lowest between 5 and 10 min, accompanied by more frequent interventions. Logistic regression showed no significant association between STOP-Bang scores and low IPI or hypoxemia. GLMM analysis also indicated no significant association between high OSA risk and low IPI (OR = 1.02; 95% CI = 0.36–2.86; p = 0.974). Hypoxemia was nearly threefold higher in high-risk patients, though not statistically significant (p = 0.080). Conclusions: Although no statistically significant association was identified between high OSA risk and adverse respiratory events, GLMM analyses revealed that patients with high STOP-Bang scores demonstrated approximately three times higher odds of developing hypoxemia (OR = 2.76; 95% CI = 0.99–7.66; p = 0.052), a result that approached statistical significance. The present findings do not support the routine use of IPI-based monitoring in this setting, and further adequately powered studies are warranted. The early procedural period (5–10 min) is critical for hypoxemia and respiratory compromise. Full article

Driven by sea-level rise and frequent compound coastal flooding, accurate inundation simulation is essential for disaster mitigation and urban planning. To address the topologically disconnected overestimation errors inherent in the traditional bathtub model, this study proposes a dynamic coastal inundation simulation framework based on an 8-neighbor seed-spread algorithm. Within this framework, a digital elevation model (DEM) is resampled to a 10 m spatial resolution, and a high frequency tidal sequence with a 5-min temporal resolution is reconstructed from typical spring tides. The vertical datums of both the topography and tidal water levels are strictly unified to the Mean Sea Level (MSL) to maintain physical consistency. Comparative experiments across multiple water level scenarios reveal a distinct threshold effect and non-linear expansion characteristics in inundation responses under complex geomorphological conditions. Because the traditional bathtub model fails to account for the blocking effects of inland physical barriers, its overestimation increases significantly once the water level exceeds critical flood protection thresholds. By generating high resolution Time of Arrival (ToA) maps, the proposed framework provides a robust spatial–temporal basis for precise coastal risk assessment, evacuation planning, and defense resource allocation. Full article

A growing number of coastal foundation pits are being constructed. Based on an actual coastal deep foundation pit project, this study develops a finite element model that incorporates fluid–soil–structure coupling and dynamic seepage boundaries to simulate tidal fluctuations. The model investigates the influence of seawater and river water on the deformation behavior of the foundation pit. Results demonstrate the feasibility of the proposed modeling approach, which integrates fluid–soil–structure coupling with dynamic seepage boundaries and employs appropriate constitutive models for different soil layers. Under tidal action, deformation of the soil on the seaward side of the pit is significantly greater than at other locations. Pore pressure and pit deformation exhibit periodic fluctuations synchronized with the tidal cycle. Compared to static water conditions, pore pressure and surface settlement increase markedly, whereas horizontal displacement shows no significant final difference. An increase in the mean sea level leads to greater horizontal displacement of the diaphragm wall but reduces ground settlement outside the pit. Although river water level changes affect deformation through a mechanism similar to that of mean sea level, its impact is considerably weaker due to the greater distance from the pit and relatively stable water level. Therefore, tidal effects should be prioritized in the design and risk assessment of coastal foundation pits. Full article

Accurate prediction of wake interactions in twin vertical-axis hydroturbine (VAHT) arrays is important for dense tidal-farm layout assessment but remains computationally expensive when based directly on Computational Fluid Dynamics (CFD) reference simulations. While simplified analytical models offer speed, they fail to capture the non-axisymmetric wake characteristics of VAHT arrays, and standard Physics-Informed Neural Networks (PINNs) often struggle with convergence in small-sample, high-dimensional flow settings. To address this challenge, this study proposes a Physics-Informed POD-PINN framework for predicting configuration-wise time-averaged wake fields. The hybrid architecture combines Proper Orthogonal Decomposition (POD) for dimensionality reduction with a dual-branch neural network: a global POD branch captures dominant flow structures, while a lightweight spatial correction branch acts as a continuity-informed regularization on the predicted field. Trained on CFD-generated reference data covering diverse longitudinal and lateral spacing configurations, the model learns to map geometric parameters to a three-component wake field represented on a regularized 3D grid. Results show that the proposed framework achieves the lowest mean streamwise error among the tested surrogate models while maintaining millisecond-level inference speed. This study provides an efficient and physics-aware surrogate tool for repeated wake-field evaluation in twin-hydroturbine configuration exploration. Full article