Search Results (1,185)

Tidal inlets regulate the exchange of water and sediment between the open sea and adjacent basins. In many locations, engineering interventions combined with coastal protections and polders have intensified erosion and scouring. This study reports on a three-year monitoring program following the implementation of a Nature-based Solution (NbS) at a previous engineering tidal inlet in the Zwin, located along the Belgian–Dutch coast. In 2019, large-scale modifications to the intertidal zone and the opening of a dyke doubled the surface area of the tidal inlet and its associated tidal marsh. Results revealed rapid and substantial morphological adjustments: the main channel deepened, widened, and migrated eastward. Sediment balance analyses showed stability at the inlet entrance but material loss further inland. Tidal prism and cross-sectional measurements indicated a fourfold increase in tidal prism immediately after NbS implementation, triggering strong channel responses. Within a year, the channel cross-sectional area reached a new equilibrium, which remained stable in the following years. These patterns highlight active sediment transport driven by coupled hydrodynamic and morphodynamic processes. Using an extensive data set, a conceptual model is presented to illustrate how the NbS influenced tidal inlet dynamics through the interaction of flow and sedimentation processes. Full article

Soil salinization poses a severe threat to agricultural sustainability in the Yellow River Delta, where conventional spectral indices are limited by vegetation interference and seasonal dynamics in coastal saline-alkali landscapes. To address this, we developed an inversion framework integrating spectral indices and vegetation temporal features, combining multi-temporal Sentinel-2 optical data (January 2024–March 2025), Sentinel-1 SAR data, and terrain covariates. The framework employs Savitzky–Golay (SG) filtering to extract vegetation temporal indices—including NDVI temporal extremum and principal component features, capturing salt stress response mechanisms beyond single-temporal spectral indices. Based on 119 field samples and Variable Importance in Projection (VIP) feature selection, three ensemble models (XGBoost, CatBoost, LightGBM) were constructed under two strategies: single spectral features versus fused spectral and vegetation temporal features. The key results demonstrate the following: (1) The LightGBM model with fused features achieved optimal validation accuracy (R² = 0.77, RMSE = 0.26 g/kg), outperforming single-feature models by 13% in R². (2) SHAP analysis identified vegetation-related factors as key predictors, revealing a negative correlation between peak biomass and salinity accumulation, and the summer crop growth process affects soil salinization in the following spring. (3) The fused strategy reduced overestimation in low-salinity zones, enhanced model robustness, and significantly improved spatial gradient continuity. This study confirms that vegetation phenological features effectively mitigate agricultural interference (e.g., tillage-induced signal noise) and achieve high-resolution salinity mapping in areas where traditional spectral indices fail. The multi-temporal integration framework provides a replicable methodology for monitoring coastal salinization under complex land cover conditions. Full article

This article addresses the multifaceted challenges inherent in the development of the novel REEFS (Renewable Electric Energy From Sea) wave energy converter (WEC). Building on the submerged pressure differential principle, it frames similar WECs before focusing on REEFS that combines renewable energy generation with coastal protection, functioning as an artificial reef. The review follows chronological criteria, encompassing experimental proof-of-concept, small-scale laboratory modeling, simplified and advanced computational fluid dynamics (CFD) simulations, and the design of a forthcoming real-sea model deployment. Key milestones include the validation of a passive variable porosity system, demonstration of wave-to-wire energy conversion, and quantification of wave attenuation for coastal defense. Additionally, the study introduces a second patent-protected REEFS configuration, isolating internal components from seawater via an elastic enveloping membrane. Challenges related to scaling, numerical modeling, and funding are thoroughly examined. The results highlight the importance of the proof-of-concept as the keystone of the development process, underscore the relevance of mixed laboratory-computational approaches and emphasize the need for a balanced equilibrium between intellectual property safeguard and scientific publishing. The REEFS development trajectory offers interesting insights for researchers and developers navigating the complex innovation seas of emerging wave energy technologies. Full article

Accurate identification of bare soil exposure and quantification of associated dust emissions are essential for understanding land degradation and air quality risks in intensively farmed regions. This study develops a monthly monitoring and modeling framework to quantify bare soil dynamics and wind erosion-induced particulate matter (PM) emissions across Shandong Province from 2017 to 2024. By integrating Sentinel-1/2 imagery, climate reanalysis, terrain and soil data, and employing a stacking ensemble classification model, we mapped bare soil areas at 10 m resolution with an overall accuracy of 93.1%. The results show distinct seasonal variation, with bare soil area peaking in winter and early spring, exceeding 25,000 km² or 15% of the total area, which is far above the 6.4% estimated by land cover products. Simulations using the CLM5.0 dust module indicate that annual PM₁₀ emissions from bare soil averaged (2.72 ± 1.09) × 10⁵ tons across 2017–2024. Emissions were highest in March and lowest in summer months, with over 80% of the total emitted during winter and spring. A notable increase in emissions was observed after 2022, likely due to more frequent extreme wind events. Spatially, emissions were concentrated in coastal lowlands such as the Yellow River Delta and surrounding saline–alkali lands. Our approach explicitly advances traditional methods by generating monthly 10 m bare soil maps and linking satellite-derived dynamics with process-based dust emission modeling, providing a robust basis for targeted dust control and land management strategies. Full article

Sessile marine organisms form the foundation of many coastal ecosystems, playing crucial roles in functions like water filtration and habitat provision. Understanding their population dynamics—particularly the interplay of growth, reproduction, and detachment under environmental stress—is essential for both ecological research and effective coastal management. This work presents a comprehensive numerical model for simulating the growth, reproduction, mortality and detachment of sessile organisms using a hybrid dynamic energy budget (DEB)–statistical approach. Our model incorporates bioenergetic processes, environmental stress responses, space competition, and layering dynamics. The simulation framework considers the effects of temperature, salinity, dissolved oxygen, and food availability on organism physiology while tracking growth, reproduction, and mortality and detachment. Model validation was performed using field data collected from sessile invertebrate populations around a floating platform in the estuary of the Sumida River in Tokyo, Japan, from September 2002 to September 2003. Our approach successfully reproduced observed patterns with high accuracy. The model revealed that temperature stress and salinity fluctuations interact synergistically, amplifying mortality and detachment rates beyond what would be predicted by each factor independently. Comparative analyses with reduced models lacking either mortality or detachment components demonstrated the importance of including both processes for the accurate prediction of population dynamics. Our case study provides a robust framework for predicting sessile organism responses to environmental variability and highlights key areas for future research in benthic ecosystem modeling. Full article

To elucidate the hydrochemical characteristics and evolution mechanisms of shallow groundwater in the alluvial–coastal transitional zone of the Tangshan Plain, 76 groundwater samples were collected in July 2022. An integrated approach combining Piper and Gibbs diagrams, ionic ratio analysis, multivariate statistical methods (including Pearson correlation, hierarchical cluster analysis, and principal component analysis), and PHREEQC inverse modeling was employed to identify hydrochemical facies, dominant controlling factors, and geochemical reaction pathways. Results show that groundwater in the upstream alluvial plain is predominantly of the HCO₃–Ca type with low mineralization, primarily controlled by carbonate weathering, water–rock interaction, and natural recharge. In contrast, groundwater in the downstream coastal plain is characterized by high-mineralized Cl–Na type water, mainly influenced by seawater intrusion, evaporation concentration, and dissolution of evaporite minerals. The spatial distribution of groundwater follows a pattern of “freshwater in the north and inland, saline water in the south and coastal,” reflecting the transitional nature from freshwater to saline water. Ionic ratio analysis reveals a concurrent increase in Na⁺, Cl⁻, and SO₄²⁻ in the coastal zone, indicating coupled processes of saline water mixing and cation exchange. Statistical analysis identifies mineralization processes, carbonate weathering, redox conditions, and anthropogenic inputs as the main controlling factors. PHREEQC simulations demonstrate that groundwater in the alluvial zone evolves along the flow path through CO₂ degassing, dolomite precipitation, and sulfate mineral dissolution, whereas in the coastal zone, continuous dissolution of halite and gypsum leads to the formation of high-mineralized Na–Cl water. This study establishes a geochemical evolution framework from recharge to discharge zones in a typical alluvial–coastal transitional setting, providing theoretical guidance for salinization boundary identification and groundwater management. Full article

Vessel arrival priority determination is a critical factor affecting port safety and efficiency in maritime traffic management, yet existing approaches relying on First Come, First Served (FCFS) principles or empirical judgment have limitations in systematic decision-making. This study aims to develop a systematic decision-making framework that overcomes these limitations by creating an automated, expert knowledge-based priority determination system for vessel traffic services. A dynamic score-based vessel arrival priority determination model was developed integrating the Delphi technique and Fuzzy Analytic Hierarchy Process (Fuzzy AHP). Basic score evaluation factors were derived through Delphi surveys conducted with 50 field experts, and weights were calculated by differentially applying Fuzzy AHP and conventional AHP according to hierarchical complexity. The proposed model consists of a dynamic scoring system integrating basic scores reflecting vessel characteristics and operational conditions, special situation scores considering emergency situations, and risk scores quantifying safety intervals between vessels. To validate the model performance, simulation-based evaluation with eight scenarios was conducted targeting experienced VTS (Vessel Traffic Services) officers, demonstrating strong agreement with expert judgment across diverse operational conditions. The developed algorithm processes real-time maritime traffic data to dynamically calculate priorities, providing port managers and maritime authorities with an automated decision support tool that enhances VTS management and coastal traffic operations. Full article

Ecotourism is vital for harmonious human–nature coexistence in national parks, making the quantification of its spatial suitability an urgent scientific priority. This study took the Yellow River Estuary National Park (YRENP) as the study area and constructed a multi-criteria evaluation model by interpreting the relationship between Ecotourism Environmental Carrying Capacity (EECC) and Ecotourism Development Suitability (EDS), addressing the critical gap in the integrated land–sea ecotourism suitability assessment for coastal national parks, using the Analytic Hierarchy Process (AHP) to determine indicator weights and ArcGIS for spatial visualization. Multi-source geospatial data, including land use, NDVI, DEM, and socio-economic datasets, were integrated. The results revealed the following: (1) Overall moderate EECC levels with stronger terrestrial capacity contrast with weaker marine capacity—high-carrying zones being limited to nearshore areas; (2) The overall EDS level was favorable, where southern section significantly outperformed northern zones, forming concentrated high-suitability clusters encircling lower-suitability areas; (3) Marine EDS slightly exceeds terrestrial suitability, with optimal coastal zones transitioning landward toward progressively higher suitability. This research provided a replicable methodology for ecotourism suitability assessment in coastal protected areas and supported sustainable spatial planning in land–sea integrated national parks. Full article

The increasing frequency and magnitude of flood-related disasters has led to adopting advanced flood models to provide a better understanding of flood vulnerability, particularly for human lives. Human flood vulnerability assessment is a primary objective when planning and designing in urban areas. Results of a numerical model in the coastal hamlet of Solanas (Sardinia, IT), in terms of water velocity and depth, have been processed using the empirical method of the regional legislation (RAS), as suggested by the National Network for Environmental Protection. Vulnerability maps and statistical parameters were compared and benchmarked with the DEFRA method, which is largely used in the UK and is regarded as a state-of-the-art empirical approach. The main findings from the benchmark results between the DEFRA and RAS methods suggest that the applicability threshold of the RAS method can significantly underestimate the pedestrian vulnerability to urban flood in Solanas, and this paper suggests a preliminary step in improving that method could be a tentative threshold value of 0.10 m depth to assure a more realistic evaluation of human vulnerability in Solanas. Full article

Composite breakwater is a commonly employed structure for coastal and harbor protection. However, strong hydrodynamic impact can lead to failure and instability of these protective structures. In this study, a two-dimensional fluid-porous-solid coupling model is developed to investigate the stability of composite breakwaters. The fluid-porous model is based on the Volume-Averaged Reynolds-Averaged Navier-Stokes equations, in which the nonlinear Forchheimer equations are added to describe the porous layer. The solid model employs the Nodal-based Discontinuous Deformation Analysis (NDDA) method to analyze the displacement of the caisson. NDDA is a nodal-based method that couples FEM and DDA to improve non-linear processes. This proposed coupled model permits the examination of the influence of the thickness and porosity of the porous layer on maximum impacting wave height (${\mathrm{IWH}}_{\max }$) and the turbulent kinetic energy (TKE) generation. The results show that high porosity values lead to the dissipation of TKE and reduce the ${\mathrm{IWH}}_{\max }$. However, the reduction in the ${\mathrm{IWH}}_{\max }$ is not monotonic with increasing porous layer thickness. We observed that ${\mathrm{IWH}}_{\max }$ reaches an optimum value as the porous layer thickness continues to increase. These results can contribute to improve the design of composite breakwaters. Full article

The maritime defence settlements of the Ming Dynasty are a key component of China’s military cultural heritage. This study examines the three coastal defence sectors of Fujian by establishing a three-tier evaluation framework utilising GIS spatial analysis and the Analytic Hierarchy Process (AHP) for quantitative assessment. The findings reveal that the synergy between military outposts significantly enhances overall defence effectiveness, while the independent defence capability of each stronghold is crucial for withstanding external threats. A comprehensive evaluation further indicates that the Fujian central coastal defence sector, characterized by its robust economy and densely distributed fortifications, demonstrates the highest level of defensive performance. By systematically quantifying the defensive performance of Fujian’s maritime defence settlements, this study develops an evaluation model that provides a scientific basis and decision support for value assessment, sustainable conservation, and adaptive reuse of this category of military cultural heritage. Full article

Coastal marshes provide essential ecosystem services, yet they are vulnerable to anthropogenic stressors and climate change, particularly sea level rise (SLR). Restoration approaches like marsh terracing have emerged as nature-based strategies to enhance resilience and reduce habitat loss. This study applies the Sea Level Affecting Marshes Model (SLAMM) to assess the potential of marsh terraces to mitigate future losses, while also examining the model’s limitations, including its assumptions and capacity to reflect complex marsh processes. A geospatial approach was used to generate 3D representations of terraces through morphostatic modeling within digital elevation models (DEMs). Under a no-restoration scenario, SLAMM projections show that all marshes analyzed are at risk of total loss by 2100. In contrast, scenarios including terracing demonstrate a delay in net marsh loss, extending the persistence of key marsh habitats by approximately a decade. Although marsh degradation remains likely under high SLR conditions, the results underscore the utility of marsh terraces in prolonging habitat stability. Additionally, the study demonstrates the feasibility of integrating restoration features like terraces into DEMs and wetland models. Despite SLAMM’s simplified erosion and accretion assumptions, the model yields important insights into restoration effectiveness and long-term marsh dynamics, informing more adaptive, forward-looking coastal management strategies. Full article

Reservoir water and the adjacent soil are ecologically interconnected yet distinct microhabitats in saline coastal wetland ecosystems, but direct comparisons of their bacterial community composition and assembly remain limited. Here, we integrated high-throughput 16S rRNA gene sequencing with statistical, null model, and network analyses to compare diversity patterns, assembly mechanisms, and interactions of abundant and rare bacterial taxa in both habitats. Soil communities exhibited greater taxonomic diversity but a lower overall abundance, while reservoir communities displayed a pronounced vertical stratification, in contrast to the more spatially uniform soil communities at the sampled scale. Key environmental drivers differed: salinity (reflecting the harsh saline context) and nutrient levels structured reservoir communities, whereas the nutrient availability and cation exchange capacity predominated in soils. Stochastic processes mainly governed the assembly of abundant taxa in both habitats, whereas deterministic selection more strongly structured rare taxa, especially in soils subject to harsh saline conditions. The co-occurrence network analysis revealed higher connectivity and modularity in soils, with moderate taxa acting as critical connectors between modules. In contrast, rare taxa played a pivotal role in sustaining network stability in the reservoir. Together, these findings demonstrate distinct, habitat-dependent assembly mechanisms and ecological roles of abundant and rare bacterial taxa in saline coastal wetland microhabitats, providing insights that can inform wetland conservation and ecosystem management. Full article

The Doce River basin is the largest river system in southeastern Brazil. Over the last century, the Doce River has been undergoing a serious process of degradation, culminating in a huge environmental disaster due to Fundão tailing dam bursting in Mariana (Minas Gerais) and causing severe damage to biodiversity and local human communities. Near its mouth, the Doce River harbors an extensive lake area, with over ninety lakes on coastal lowlands. These lakes are of fluvial origin and connected to each other and to the main Doce River by small tributary streams. In this area, one of the main sources of impact on the fish fauna is the presence of non-native fish species. We compared richness, taxonomic diversity, beta diversity, species composition and proportion of non-native species in lakes and streams, and related these variables to each other and to environmental variables. We used the indicator species index (IndVal) to identify species associated with each type of environment. We used multivariate analyses to test the influence of stream habitat on the fish fauna in streams and Generalized Linear Models (GLMs) to test the influence of distance to lakes on the proportion of non-native species in streams, and the influence of this proportion on total and native fish richness and diversity. The results showed that some non-native species originating from lentic environments have adapted to the lakes and are spread throughout the internal lake system. In streams, there are proportionally fewer non-native fish and their distribution is more fragmented, as some stretches do not provide the conditions for the establishment of some of these species, making them potential refuges for native ichthyofauna. As the streams move away from the lakes, the proportion of non-native species tends to decrease. In streams, the richness and diversity of native species are affected by the proportion of non-native species, but not in lakes. The native vegetation in the landscape showed no potential for reducing the invasion of non-native species. The depth and width of the streams are directly related to the proportion of non-native species within the streams and are structural characteristics that should be considered in strategies for the conservation of the fish fauna. Full article

In the context of global climate change and accelerated urbanization, coastal cities face severe threats from storm surges, and accurately predicting coastal water level changes during storm surges has become a core technological demand for disaster prevention and reduction. Storm surges are caused by atmospheric pressure and wind conditions, and their destructive power is closely related to the morphology of the coastline. Traditional tide level prediction models often face difficulties in boundary condition parameterization. Tide level changes result from the combined effect of various complex processes. In past prediction studies, harmonic analysis and numerical simulations have dominated, each with their own limitations. Although machine learning applications in tide prediction have garnered attention, issues such as data inconsistency or missing data still exist. The physical–data fusion approach aims to overcome the limitations of single methods but still faces some challenges. This paper proposes a Deep-Numerical-Reinforcement learning fusion prediction model (DNR), which adopts ensemble learning. First, deep learning models and the numerical model Finite-Volume Coastal Ocean Model (FVCOM) are used to predict tide levels at different tide stations, and then a fusion approach based on the improved reinforcement learning model DDPG_dual is applied for model assimilation. This reinforcement learning fusion model includes a module specifically designed to handle tide extreme points. In the case of the Typhoon Mangkhut storm surge, the DNR model achieved the best results for tide level predictions at six tide stations in the South China Sea. Full article