Search Results (66)

Coastal Louisiana continues to experience rapid wetland loss, increasing the exposure of marsh-creation containment dikes to storm-driven waves, erosion, and sediment loss. This study evaluated offshore-to-nearshore wave transformation, erosion risk reduction, wave runup, and hydrodynamic loading at a representative marsh-creation site in Plaquemines Parish, Louisiana. A 25-year return-period offshore wave condition was derived from long-term Wave Information Study hindcast data and propagated using the SWAN spectral wave model. Two idealized foreshore conditions were examined: a bare-bed case and a marsh-roughened shallow water case represented through enhanced bottom friction. Web Soil Survey data were used to characterize the local soil context of the containment-dike zone. The results show strong wave attenuation across the inner shelf and marsh platform. Relative to the bare-bed case, marsh roughness reduced dike toe significant wave height by 16.1–27.4% and decreased the Hs²-based erosion exposure proxy by 29.6–47.4% across three still-water levels. These reductions produced 15.4–26.4% lower 2% exceedance runup and 28.5–45.8% lower quasi-hydrostatic loading on the containment dike. The results indicate that marsh-induced dissipation can help reduce erosion potential and support sustainable coastal restoration infrastructure management. Full article

The design of coastal protection structures requires design parameters that accurately represent the hydrodynamic conditions along the coast. Currently, these input variables are based on univariate probability models, which do not consider the joint probability of water level and statistical wave parameters such as significant wave height. Bivariate probability modeling using copula models offers an alternative. Copulas can be used to describe the dependencies between water level and significant wave height and to compute joint probabilities of occurrence. First, various copulas are fitted to samples of physically consistent combinations of water level and significant wave height extracted from storm surge events along the German Baltic Sea coast of Mecklenburg-Western Pomerania. Next, the most appropriate copula model is used to compute design combinations of water level and significant wave height for selected return periods. The bivariate design parameters are compared with the univariate ones in a simplified design example for wave run-up on a dike. The validation of various models shows that the Frank copula best describes the dependence structure. The bivariate design parameters obtained for the same return periods are lower than those determined using the univariate method. The available data only allow a limited application of the copulas for engineering design in the study area. Nevertheless, copulas have the potential to replace univariate methods for determining design parameters and thus contribute to more reliable and cost-efficient coastal protection structure design. Full article

Impulsive overtopping generated by dam-break surges is a critical hazard for dikes and flood-protection embankments, especially in reservoirs and mountainous catchments. Unlike classical coastal wave overtopping, which is governed by long, irregular wave trains and usually characterized by mean overtopping discharge over many waves, these dam-break-type events are dominated by one or a few strongly nonlinear bores with highly transient overtopping heights. Accurately predicting the resulting overtopping levels under such impulsive flows is therefore important for flood-risk assessment and emergency planning. Conventional cluster-then-predict approaches, which have been proposed in recent years, often first partition data into subgroups and then train separate models for each cluster. However, these methods often suffer from rigid boundaries and ignore the uncertainty information contained in clustering results. To overcome these limitations, we propose a GMM+MoE framework that integrates Gaussian Mixture Model (GMM) soft clustering with a Mixture-of-Experts (MoE) predictor. GMM provides posterior probabilities of regime membership, which are used by the MoE gating mechanism to adaptively assign expert models. Using SPH-simulated overtopping data with physically interpretable dimensionless parameters, the framework is benchmarked against XGBoost, GMM+XGBoost, MoE, and Random Forest. Results show that GMM+MoE achieves the highest accuracy ($R^2=0.9638$ on the testing dataset) and the most centralized residual distribution, confirming its robustness. Furthermore, SHAP-based feature attribution reveals that relative propagation distance and wave height are the dominant drivers of overtopping, providing physically consistent explanations. This demonstrates that combining soft clustering with adaptive expert allocation not only improves accuracy but also enhances interpretability, offering a practical tool for dike safety assessment and flood-risk management in reservoirs and mountain river valleys. Full article

Many studies have been conducted on wave and sediment movement with submerged dikes. However, the effect of a submerged dike’s height and orientation on hydrodynamics has not been thoroughly examined from the perspective of the marine ecology impact. This paper employs a two-dimensional numerical model to investigate effects of submerged dike height and orientation on flow, specifically flow velocity and cross-dike flux. The findings indicate that the most significant velocity variation occurs at a distance of approximately one-fifth of the dike length (0.2 L) from the dike head, when the flow is perpendicular to the dike and parallel to the coastline. And this area as the submerged dike’s protection zone will have the least impact on the surrounding environment. The change pattern of the flow velocity with the distance apart from the submerged dike varies for different submerged dike heights. A submerged dike height of 0.7 times the water depth (0.7 H) is a dividing value. Additionally, as the orientation angle increases, the cross-dike flux rises. From the perspective of the impact on the marine ecological environment, the design angle of the submerged dike should be as small as possible. The findings establish a theoretical hydrodynamic basis that may support future integrated studies on coastal zone management. Full article

This study investigates the water-stability performance and stabilization mechanism of a hybrid-modified dredged muck sampled from the protection channel of the southern seawall, Cangnan County, China, and explores the feasibility of reusing the modified soil as backfill or non-structural fill behind the dike body. The muck was amended with two industrial by-products: (i) coarse-grained spoil excavated from an adjacent power-plant project, serving as a particle-size modifier, and (ii) ordinary Portland cement, acting as the chemical stabilizer. Unconfined compressive strength (UCS) tests were conducted on specimens cured for 7 d and 28 d under both saturated and unsaturated conditions, complemented by scanning electron microscopy (SEM) to elucidate microstructural evolution. An optimal mix proportion that satisfies the prescribed water-stability criterion while maintaining cost-effectiveness was thereby identified. Experimental results demonstrate that cement content, coarse-spoil fraction and curing age govern the water-stability behavior, with cement dosage exerting the most pronounced influence. A 28 d cured blend containing only 5% cement yielded a low water-stability coefficient (31.8%) and negligible post-immersion strength. Conversely, a ternary mixture comprising 40% muck, 60% coarse spoil and 15% cement achieved the highest water stability, recording UCS values of 1582 kPa (saturated) and 2025 kPa (unsaturated), corresponding to 78.1%. These findings provide a theoretical basis and practical guidance for the valorization of waste soils in coastal engineering and for the design/construction of seawalls. These findings not only provide a theoretical basis and practical guidance for the valorization of waste soils in coastal engineering and for the design/construction of seawalls, but also substantially expand the available material source, drive down construction costs, and markedly mitigate the environmental impacts associated with the off-site disposal of excavated waste. Full article

Efforts have been underway worldwide to reintroduce seawater to many historically diked salt marshes for restoration of tidal flow and associated estuarine habitat. Seawater restoration to a diked Cape Cod marsh was simulated using the computer program PHREEQC based on previously conducted microcosm experiments to better understand the associated timing and sequence of multiple biogeochemical reactions and their implications to aquatic health. Model simulations show that acidic, reducing waters with high concentrations of sorbed ferrous iron (Fe[II]), aluminum (Al), sulfide (S²⁻), ammonia (NH₄⁺ + NH₃), and phosphate (PO₄³⁻) are released through desorption and sediment weathering following salination that can disrupt aquatic habitat. Models were developed for one-dimensional reactive transport of solutes in diked, flooded (DF) marsh sediments and subaerially exposed, diked, drained (DD) sediments by curve matching porewater solute concentrations and adjusting the sedimentary organic matter (SOM) degradation rates based on the timing and magnitude of Fe(II) and S²⁻ concentrations. Simulated salination of the DD sediments, in particular, showed a large release of Al, Fe(II), NH₄⁺, and PO₄³⁻; the redox shift to reductive dissolution provided higher rates of SOM oxidation. The sediment type, iron source, and seasonal timing associated with seawater restoration can affect the chemical speciation and toxicity of constituents to aquatic habitat. The constituents of concern and their associated complex biogeochemical reactions simulated in this study are directly relevant to the increasingly common coastal marsh salination, either through tidal restoration or rising sea level. Full article

Laizhou Bay, a semi-enclosed bay, is prone to storm surges from cold waves due to its geographic and environmental characteristics. This study uses satellite data, in situ measurements, and the MIKE numerical model to analyze storm surges along Laizhou Bay’s coast under no-dike conditions. It examines the surges caused by cold waves with different intensities and directions. This study provides the storm surge disaster risk levels along Laizhou Bay’s coast. The results show that the maximum sustained wind speed during cold waves is distributed between the NW and NE. The NE wind direction causes the most severe storm surge along Laizhou Bay. Under NE-directed cold waves with level 12 wind, the maximum risk areas for Level III and IV are approximately 1341 km² and 1294 km², respectively. Dongying, Shouguang, and Hanting exhibit large Level I and II risk zones. The maximum seawater intrusion distance along the Kenli coast is about 41 km. The coastal segment from Kenli to Changyi is most severely affected by storm surges. It is recommended to effectively maintain and heighten seawalls along this segment to mitigate storm surge disasters caused by strong NE winds. Full article

Standalone tsunami defense structures have demonstrated limitations in mitigating wave energy during the 2011 Japan tsunami. In order to mitigate future tsunamis in Japan, multi-layered protective mechanisms have been suggested or implemented after the incident. These include heightening the destroyed or existing embankment with concrete or stones, protecting embankments with concrete blocks, compacting the landward soil, elevating the ground following the coastal embankment, and incorporating green belts. Despite extensive research on the mitigation effects of such multiple countermeasures, the optimal structural configuration remains uncertain. In this study, we evaluated the performance of a multiple mitigation system consisting of a landward forest (F) on an elevated mound (M) following a seaward embankment (E) under a range of supercritical flow conditions using a flume experiment. Several mound heights and lengths were selected to determine the optimum mound for installing the forest. The combination of E and F of 12 rows of trees on M with a minimum height of 1.8 cm (Case EMF_R12) created the greatest water cushion depth between E and M. When M was positioned without F, the water cushion between E and M was created by raising the height of the mound rather than its length. Conversely, a mound with a minimum height and length with a forest was found to be effective in creating the largest water cushion and maximum reduction of the flow energy. The highest energy reduction was between 45 and 70% in this experiment. These findings provide useful insights for developing multiple tsunami mitigation strategies that combine artificial and natural approaches. Full article

Urban flooding is a growing concern, particularly in coastal lowland cities where climate change exacerbates hazards through rising sea levels and intense rainfall. Traditional flood defenses like fluvial polders often exacerbate urban fragmentation and maintenance costs if poorly integrated into planning. This study proposes a multifunctional assessment design framework to evaluate polder design effectiveness considering both the hydraulic and social–environmental dimensions, emphasizing blue–green infrastructure (BGI) for flood control, leisure, and landscape integration. Three design scenarios for Rio de Janeiro’s Jardim Maravilha neighborhood were modeled hydrodynamically: S1 (dike near urban areas, pump-dependent) and S2/S3 (dikes along the riverbank, gravity-driven). Results show S2/S3 outperformed S1 in storage capacity (2.7× larger volume), freeboard resilience (0.42–0.43 m vs. 0.25 m), and urban integration (floodable parks accessible to communities), though S1 had faster reservoir emptying. Under climate change, all scenarios sustained functionality, but S1’s freeboard reduced by 86%, nearing its limit. The framework’s standardized scoring system balanced quantitative and qualitative criteria, revealing trade-offs between hydraulic efficiency and urban adaptability. The optimized S3 design, incorporating external storage and dredging, achieved the best compromise. This approach aids decision-making by systematically evaluating resilience, operational feasibility, and long-term climate adaptation, supporting sustainable flood infrastructure in coastal cities. Full article

Taiwan is frequently affected by typhoons, which cause storm surges and wave impacts that damage sea dikes, resulting in overflow and subsequent flooding. Therefore, it is essential to analyze the damage to sea dikes caused by storm surges and wave impacts, leading to overflow, for effective coastal protection. This study employs the ADCIRC model coupled with the SWAN model to simulate storm surges and waves around Taiwan and develops a sea dike failure model that incorporates mechanisms for impact damage, run-up damage, and overflow calculation. To ensure model accuracy, three historical typhoon events were used for calibration and validation of the ADCIRC+SWAN model. The results show that the ADCIRC coupled with SWAN model can effectively simulate storm surges and waves during typhoons. Typhoon Soulik (2013) was simulated to examine a breach in the Tamsui Youchekou sea dike in northern Taiwan, and an uncertainty analysis was conducted using the Monte Carlo method and Bayesian theorem. The results indicate that when the compressive strength of the sea dike is reduced to 5% of its original strength, impact and run-up damage occur, leading to overflow. In the case of impact damage, the overflow volume due to the breach falls within a 95% confidence interval of 0.16 × 10⁶ m³ to 130 × 10⁶ m³. For run-up damage, the 95% confidence interval for the overflow volume ranges from 0.16 × 10⁶ m³ to 639 × 10⁶ m³. The ADCIRC+SWAN model is used to simulate storm surge and waves, incorporating impact damage and run-up damage mechanisms to represent concrete sea dike failure. This approach effectively models dike failure and calculates the resulting overflow. Full article

A type of aquaculture pond called a dike-pond system is distributed in the low-lying river delta of China’s eastern coast. Along with the swift growth of the coastal economy, the water surfaces of the dike-pond system (WDPS) play a major role attributed to pond aquaculture yielding more profits than dike agriculture. This study aims to explore the performance of deep learning methods for extracting WDPS from high spatial resolution remote sensing images. We developed three fully convolutional network (FCN) models: SegNet, UNet, and UNet++, which are compared with two traditional methods in the same testing regions from the Guangdong–Hong Kong–Macao Greater Bay Area. The extraction results of the five methods are evaluated in three parts. The first part is a general comparison that shows the biggest advantage of the FCN models over the traditional methods is the P-score, with an average lead of 13%, but the R-score is not ideal. Our analysis reveals that the low R-score problem is due to the omission of the outer ring of WDPS rather than the omission of the quantity of WDPS. We also analyzed the reasons behind it and provided potential solutions. The second part is extraction error, which demonstrates the extraction results of the FCN models have few connected, jagged, or perforated WDPS, which is beneficial for assessing fishery production, pattern changes, ecological value, and other applications of WDPS. The extracted WDPS by the FCN models are visually close to the ground truth, which is one of the most significant improvements over the traditional methods. The third part is special scenarios, including various shape types, intricate spatial configurations, and multiple pond conditions. WDPS with irregular shapes or juxtaposed with other land types increases the difficulty of extraction, but the FCN models still achieve P-scores above 0.95 in the first two scenarios, while WDPS in multiple pond conditions causes a sharp drop in the indicators of all the methods, which requires further improvement to solve it. We integrated the performances of the methods to provide recommendations for their use. This study offers valuable insights for enhancing deep learning methods and leveraging extraction results in practical applications. Full article

Tide dikes play a key role in preventing seawater intrusion in coastal regions; however, their effects on trace metal distribution and accumulation remain unclear. This study explored the distribution and enrichment of trace metals (As, Cr, Cu, Ni, Pb, and Zn) inside and outside tide dikes in Laizhou Bay. The accumulative risk of these metals in the two habitats was analyzed by combining their sources. The results show that the average enrichment factor, geological accumulation index, and potential ecological risk index of As in the outside habitat are significantly higher than those in the inside habitat (p < 0.001), which indicates that the tide dike effectively reduces the migration of As from outside to inside habitats. For other trace metals, no statistical differences were found between the two habitats. Based on principal component analysis and redundancy analysis of trace metals and their correlations with soil physicochemical properties, we speculated that Cr and Zn may derive from soil parent material and rock weathering. Cu, Pb, and Ni may be related to atmospheric nitrogen deposition resulting from nearby agricultural activities, and As may come from industrial wastewater or transport through seagoing rivers. The findings suggest that tide dikes effectively block exogenous trace metals but not those from natural sources. Full article

This study introduces a new software, cLASpy_T, that helps design models for the automatic 3D point cloud classification of coastal environments. This software is based on machine learning algorithms from the scikit-learn library and can classify point clouds derived from LiDAR or photogrammetry. Input data can be imported via CSV or LAS files, providing a 3D point cloud, enhanced with geometric features or spectral information, such as colors from orthophotos or hyperspectral data. cLASpy_T lets the user run three supervised machine learning algorithms from the scikit-learn API to build automatic classification models: RandomForestClassifier, GradientBoostingClassifier and MLPClassifier. This work presents the general method for classification model design using cLASpy_T and the software’s complete workflow with an example of photogrammetry point cloud classification. Four photogrammetric models of a coastal dike were acquired on four different dates, in 2021. The aim is to classify each point according to whether it belongs to the ‘sand’ class of the beach, the ‘rock’ class of the riprap, or the ‘block’ class of the concrete blocks. This case study highlights the importance of adjusting algorithm parameters, selecting features, and the large number of tests necessary to design a classification model that can be generalized and used in production. Full article

This research examines the overtopping volumes associated with focused wave groups on smooth dikes with an emerged toe. Focused wave groups are employed to represent the highest waves of random sea states in a compact form, obviating the need to model the entire irregular wave train. This study investigates how overtopping volumes are affected by focus location and phase. A total of 418 experimental tests were gathered and analyzed. Data with overtopping volumes below 600 L per meter (prototype conditions) were excluded in order to focus on extreme overtopping events, resulting in 324 relevant test cases. The experiments used first-order wave generation theory to analyze structural response. Subsequent studies will address the errors induced by this approximation and compare it with second-order wave generation. The experiments simulated extreme wave impacts on an idealized coastal layout, comprising a 1:6.3 foreshore slope and three different dike slopes, including vertical structures, with the initial still water level set below the dike toe. This study employed the NewWave theory to generate focused wave groups, with the objective of extending recent research on wave overtopping under varied conditions. The results, analyzed in both dimensional and non-dimensional forms, indicate that overtopping volumes are significantly influenced by the focus phase. Critical focus locations were identified at a distance of one-third of the deep-water wavelength from the toe. Full article

Coastal aquaculture has made an important contribution to global food security and the economic development of coastal zones in recent decades. However, it has also damaged these coastal zones’ ecosystems. Moreover, coastal aquaculture is poised to play a key role in the achievement of Sustainable Development Goals (SDGs). Consequently, extracting aquaculture has become crucial and valuable. However, due to the limitations of remote sensing image spatial resolution and traditional extraction methods, most research studies focus on aquaculture areas containing dikes rather than individually separable aquaculture ponds (ISAPs). This is not an accurate estimation of these aquaculture areas’ true size. In our study, we propose a rapid and effective object-based method of extracting ISAPs. We chose multi-scale segmentation to generate semantically meaningful image objects for various types of land cover, and then built a decision tree classifier according to the unique features of ISAPs. The results show that our method can remove small rivers and other easily confused features, which has thus far been difficult to accomplish with conventional methods. We obtained an overall precision value of 85.61% with a recall of 84.04%; compared to the support vector machine’s (SVM) overall precision value of 78.85% and recall rate of 61.21%, our method demonstrates greater accuracy and efficiency. We used this method to test the transferability of the algorithm to nearby areas, and the obtained accuracy exceeded 80%. The method proposed in this study could provide a readily available solution for the simple and efficient extracting of ISAPs and shows high spatiotemporal transferability. Full article