Search Results (2,712)

Ocean winds and waves play a vital role in maritime navigation safety, offshore operations, and coastal zone dynamics. Although both factors have been widely studied individually, the joint characterization of wind and wave events remains limited in the North Indian Ocean. This study, utilizing ERA5 reanalysis data from 1980 to 2022, statistically analyzed the distribution and variation patterns of both wind speed and significant wave height, investigating the occurrence, affected area proportion, frequency, and intensity of SBLWEs. To understand the cause of Strong Breeze and Large Wave Events (SBLWEs), their connections with other phenomena, such as tropical cyclones, were also explored. The results show that regions with strong breezes and large waves are mainly concentrated in the central and western Arabian Sea near Africa and the central and western Bay of Bengal. Monthly averages indicate that wind and wave intensity are much higher during the summer monsoon than in other seasons, with high intensity, probability, and extensive affected areas of SBLWEs. The occurrence probability of SBLWEs is highest in the central and western Arabian Sea (up to ~40%), and the highest probability in the Bay of Bengal is about 20% near the eastern coast of Sri Lanka. The peak period of SBLWEs occurs from June to August, with the largest affected area in July, reaching almost 25%. Over the past 40 years, the number of SBLWEs has shown an increasing trend, with an average of 0.7 events annually. The intensity distribution of SBLWEs resembles that of wind speed and wave height, with the highest intensity areas concentrated in the Bay of Bengal, affected by tropical cyclones. This study can serve as a scientific reference for maritime route planning and offshore operations, helping to reduce the negative impacts of large wind and wave events and enhance navigation safety. Full article

Monitoring construction-phase settlement of estuary-crossing tunnels founded on coastal soft soils is critical for risk management, yet dense in situ measurements are often unavailable along linear corridors. This study uses Sentinel-1A ascending SAR imagery (65 scenes, September 2022–August 2025) to retrieve time-series deformation along the Sanya Estuary Channel tunnel (China) using Permanent Scatterer InSAR (PS-InSAR) and Small Baseline Subset InSAR (SBAS-InSAR). The two approaches reveal a consistent subsidence hotspot at Tunnel Section D (DK0+000–DK0+330), while most of the corridor remains within ±5 mm/a. The line-of-sight deformation rates range from −24 to 17.7 mm/year (PS-InSAR) and −29.9 to 18.7 mm/a (SBAS-InSAR). Time-series analysis at representative points in Section D indicates a maximum cumulative settlement of −75.7 mm and a clear acceleration after May 2023. By integrating the deformation results with geological reports, construction logs and rainfall records, we infer that compressible marine clays and interbedded sand/aquifer zones control the hotspot, whereas excavation/dewatering and rainfall-related groundwater fluctuations further promote consolidation. The results provide a practical basis for subsidence risk screening and monitoring prioritization for estuary-crossing infrastructure in coastal soft-soil settings. From a sustainability perspective, the proposed joint PS–SBAS InSAR framework provides a scalable and cost-effective tool for continuous deformation surveillance, supporting preventive maintenance and risk-informed management of urban underground infrastructure. Full article

Phloeosinus cupressi Hopkins is an invasive bark beetle that poses a serious threat to Cupressus trees, with potential ecological and economic impacts globally. Native to North America, it has spread to Australia and New Zealand, and climate change may further alter its range. Global trade increases the risk of spread, highlighting the need for predictive modeling in management. In this study, we employed CLIMEX and random forest (RF) models to project the potential global distribution of P. cupressi, incorporating host distribution data for Cupressus. Climatic suitability is concentrated in temperate, subtropical, and Mediterranean zones, including Europe, the U.S., South America, China, Australia, and New Zealand, totaling 10,165.22 × 10⁴ km². Coldest-quarter precipitation (bio19) and annual temperature range (bio7) were identified as the most influential variables. Under RCP6.0 scenarios, suitable areas are projected to expand northward, increasing by ~18%. Regional shifts include contraction in southern Europe and South China, expansion in southern Argentina, southeastern Australia, and coastal New Zealand. Temperature sensitivity is expected to exceed precipitation, enhancing colonization. Due to global Cupressus trade, quarantine and monitoring should focus on high-risk regions. Our findings support early detection, long-term monitoring, and control measures for managing P. cupressi under climate change. Full article

This study analyzed the spatial distribution of large green algae (LGA) in the northern coastal waters of China, including the Yellow Sea and Bohai Sea, using Coastal Zone Imager (CZI) data from the HY-1C/D satellites. An inversion model (coastal zone imager model) of LGA was established, based on which the distribution details of large green algae in the Yellow Sea and Bohai Sea were investigated. The results indicated the following: (1) LGA exhibits a clearly seasonal pattern from May to August. Initially occurrences are detected in May in the southern Yellow Sea (32–34° N), followed by a rapid expansion and intensification from June to mid-July, with peak distribution around 35° N near the Shandong Peninsula. The affected area subsequently decreases in late August. (2) High LGA coverage is mainly concentrated along the Subei Shoal and the Shandong Peninsula in the Yellow Sea, as well as the coastal regions of Yantai, Qinhuangdao, and Yingkou in the Bohai Sea. (3) The LGA-M inversion model demonstrates stable performance in nearshore waters with similar optical characteristics and is applicable to LGA extraction in adjacent coastal seas, highlighting the potential of HY-1C/D satellite data in marine environmental monitoring and protection. Full article

Groundwater vulnerability assessments serve as essential tools for sustainable groundwater management, particularly in regions with intensive anthropogenic activities. However, improving the objectivity and predictive reliability of vulnerability assessment frameworks remains a critical scientific challenge in groundwater science, especially for coastal aquifer systems characterized by strong heterogeneity and complex hydrogeological processes. The traditional DRASTIC model is a widely recognized method but suffers from subjectivity in assigning parameter ratings and weights, often leading to arbitrary and potentially inaccurate vulnerability maps. This limitation also restricts its applicability in areas with complex hydrogeological conditions. To enhance the accuracy and adaptability of the traditional DRASTIC model, a hybrid PSO-BP-DRASTIC framework was developed and applied it to a coastal city in China. Specifically, the model employs a backpropagation neural network (BP-NN) to optimize indicator weights and integrates the particle swarm optimization (PSO) algorithm to refine the initial weights and thresholds of the BP-NN. By introducing a data-driven and globally optimized weighting mechanism, the proposed framework effectively overcomes the inherent subjectivity of conventional empirical weighting schemes. Using ten-fold cross-validation and observed nitrate concentration data, the traditional DRASTIC, BP-DRASTIC, and PSO-BP-DRASTIC models were systematically validated and compared. The results demonstrate that (1) the PSO-BP-DRASTIC model achieved the highest classification accuracy on the test set, the highest stability across ten-fold cross-validation, and the strongest correlation with the nitrate concentrations; (2) the importance analysis identified the aquifer thickness and depth to the groundwater table as the most influential factors affecting groundwater vulnerability in Yantai; and (3) the spatial assessments revealed that high-vulnerability zones (7.85% of the total area) are primarily located in regions with intensive agricultural activities and high aquifer permeability. The hybrid PSO-BP-DRASTIC model effectively mitigates the subjectivity of the traditional DRASTIC method and the local optimum issues inherent in BP-NNs, significantly improving the assessment accuracy, stability, and objectivity. From a scientific perspective, this study demonstrates the feasibility of integrating swarm intelligence and neural learning into groundwater vulnerability assessment, providing a transferable and high-precision methodological paradigm for data-driven hydrogeological risk evaluation. This novel hybrid model provides a reliable scientific basis for the reasonable assessment of groundwater vulnerability. Moreover, these findings highlight the importance of integrating a hybrid optimization strategy into the traditional DRASTIC model to enhance its feasibility in coastal cities and other regions with complex hydrogeological conditions. Full article

This study proposes a lightweight framework for transferring pretrained land cover classification architectures without additional training. The system utilizes French IGN imagery and Korean UAV and aerial imagery. It employs FLAIR U-Net models with ResNet34 and MiTB5 backbones, along with the AI-HUB U-Net. The implementation consists of four sequential stages. First, we perform class mapping between heterogeneous schemes and unify coordinate systems. Second, a quadratic polynomial regression equation is constructed. This formula uses multispectral band statistics as hyperparameters and class-wise IoU as the dependent variable. Third, optimal parameters are identified using the stationary point condition of Response Surface Methodology (RSM). Fourth, the final land cover map is generated by fusing class-wise optimal results at the pixel level. Experimental results show that optimization is typically completed within 60 inferences. This procedure achieves IoU improvements of up to 67.86 percentage points compared to the baseline. For automated application, these optimized values from a source domain are successfully transferred to target areas. This includes transfers between high-altitude mountainous and low-lying coastal territories via proportional mapping. This capability demonstrates cross-regional and cross-platform generalization between ResNet34 and MiTB5. Statistical validation confirmed that the performance surface followed a systematic quadratic response. Adjusted R² values ranged from 0.706 to 0.999, with all p-values below 0.001. Consequently, the performance function is universally applicable across diverse geographic zones, spectral distributions, spatial resolutions, sensors, neural networks, and land cover classes. This approach achieves more than a 4000-fold reduction in computational resources compared to full model training, using only 32 to 150 tiles. Furthermore, the proposed technique demonstrates 10–74× superior resource efficiency (resource consumption per unit error reduction) over prior transfer learning schemes. Finally, this study presents a practical solution for inference and performance optimization of land cover semantic segmentation on standard commodity CPUs, while maintaining equivalent or superior IoU. Full article

Coastal ecological regulation plays a crucial role in coordinating the human–environment system and promotes sustainable development, yet it often imposes constraints on the livelihoods of local farmers. Drawing on questionnaire survey data from Chinese coastal farmers, this study quantifies farmers’ opportunity loss through the expectation function and entropy method. Subsequently, a Multinomial Logit model and Generalized Structural Equation Modeling (GSEM) are employed to systematically investigate the mechanisms through which ecological regulation-induced opportunity loss influences coastal farmers’ livelihood transition between 2013 and 2023. The findings reveal that greater opportunity loss significantly inhibits the fishing households’ livelihood transition, exhibiting a ‘livelihood stickiness’ effect. This inhibitory effect is partially mediated by a narrowing of farmers’ psychological distance from environmental issues. Specifically, social distance, reflecting community attachment and identity, plays a dominant mediating role. Furthermore, regulation intensity significantly amplifies this inhibitory effect. Notably, in the absence of substantive compensation or alternative livelihood support, greater policy publicity further reinforces this inhibitory impact. These findings underscore the need for policy interventions that provide compensation and alternative livelihood support commensurate with farmers’ opportunity loss. Enhancing community participation is also crucial to better reconcile coastal conservation objectives with the sustainable livelihoods of local communities. Full article

Climate change and irregular precipitation patterns have increasingly threatened groundwater sustainability in semi-arid regions like the Eastern Mediterranean. Specifically, in coastal Syria, the lack of quantitative understanding regarding aquifer recharge mechanisms hinders effective water resource management. To address this, this study investigates the dynamic relationship between rainfall and groundwater levels in the Al-Hsain Basin coastal plain using 48 months of monitoring data (2020–2024) from 35 wells. We employed a unified analytical framework combining statistical methods (correlation, regression) with advanced time–frequency techniques (Wavelet Coherence) to capture recharge behavior across diverse Quaternary, Neogene, and Cretaceous strata. The results indicate strong climatic control on groundwater dynamics, particularly in shallow Quaternary wells, which exhibit rapid recharge responses (lag < 1 month). In contrast, deeper aquifers showed delayed and buffered responses. A dual-variable model incorporating temperature significantly improved prediction accuracy (R² = 0.97), highlighting the role of evapotranspiration. These findings provide a transferable diagnostic framework for identifying recharge zones and supporting adaptive groundwater governance in data-scarce semi-arid environments. Full article

Accurate characterization of seafloor sediment properties is critical for marine engineering design, resource assessment, and environmental management. Sidescan sonar offers efficient wide-area mapping capabilities, yet establishing robust quantitative relationships between acoustic backscatter intensity and sediment texture remains challenging, particularly in heterogeneous coastal environments. This study investigates the correlation between sidescan sonar backscatter intensity and sediment grain size parameters in waters southwest of Hainan Island, China. High-resolution acoustic data (450 kHz) were acquired alongside surface sediment samples from 18 stations spanning diverse sediment types. Backscatter intensity, represented by grayscale values, was systematically compared with grain size distributions and individual size fractions. Results reveal that mean grain size shows no meaningful correlation with backscatter intensity; however, fine sand fraction content (0.075–0.25 mm) exhibits a strong negative linear relationship (R² = 0.87 under optimal conditions). Distribution-level analysis demonstrates that backscatter variability mirrors sediment textural complexity, with coarse sediments producing broad, elevated intensity distributions and fine sediments yielding narrow, suppressed distributions. Inter-survey variability highlights the sensitivity of absolute intensity values to environmental conditions during acquisition. Spatial distribution analysis reveals that sediment grain size follows a systematic NE-SW gradient controlled by hydrodynamic energy, with notable local anomalies controlled by reef structures (producing coarse bioclastic sediment) and topographic sheltering (maintaining fine-grained deposits in shallow areas). These findings provide a quantitative basis for fraction-specific acoustic classification approaches while emphasizing the importance of multi-scale analysis incorporating both regional hydrodynamic trends and local morphological controls. The established relationship between fine sand abundance and acoustic response enables semi-quantitative sediment prediction from remotely sensed data, supporting improved seafloor mapping protocols for offshore infrastructure siting, aggregate resource evaluation, and coastal zone management in morphologically complex environments. Full article

Dissolved organic matter (DOM) is central to biogeochemical cycles in estuarine-coastal zones, with its source-sink dynamics linking regional ecological functions to global carbon budgets. As a typical semi-enclosed bay in southern China, Zhanjiang Bay (ZJB) features intense tidal mixing and significant seasonal runoff variations, making it a representative system for understanding DOM dynamics in complex land–sea interaction zones. The migration of dissolved organic carbon (DOC) is crucial for bay carbon budgets, yet its estimation is constrained by land–water interface dynamics and in situ observation limitations. To clarify the regulation of DOM’s fate and exchange flux in ZJB, this study integrated in situ observations, ultraviolet spectroscopy, and three-dimensional fluorescence techniques to analyze DOM tidal dynamics and net DOC exchange flux. Results indicated terrestrial runoff dominated rainy-season DOC sources, resulting in slightly higher concentrations (1.86 ± 0.46 mg·L⁻¹) compared to the dry season (1.82 ± 0.20 mg·L⁻¹). Terrestrial inputs endowed rainy-season DOM with high molecular weight and aromaticity, with microbial humic substances (C2) accounting for 36%. Tidal fluctuations affected DOC via water exchange: ebb tides diluted concentrations with low-DOC open-ocean seawater, while flood tides increased them through high-DOC bay water discharge. Dry-season DOM relied on in situ biotransformation, characterized by low molecular weight and aromaticity, with the protein-like fraction (C4) accounting for 24.3%. Fluorescence index (FI = 1.77–1.79) confirmed DOM as a mixture of allochthonous and autochthonous sources, with significant in situ contributions and weak humification. Net DOC exchange flux, regulated by terrestrial runoff, was 3.6–4.6 times higher in the rainy season, decreasing from the estuary to the coast. In conclusion, the joint regulation of terrestrial runoff-driven seasonal dynamics and tidal water exchange governs ZJB’s DOM dynamics, providing valuable insights for biogeochemical research in semi-enclosed bays. Full article

Mangrove ecosystems underpin coastal livelihoods and biodiversity in Mozambique, yet gendered patterns of resource use and their implications for management remain underexplored. This study explores how artisanal fishing and shellfish collection differ between men and women on Inhaca Island (Maputo Bay), focusing on how these gender-specific practices shape livelihood outcomes, spatial use of mangroves, and perceptions of ecological change. To address this question, we combined structured interviews (n = 35; 51.4% men, 48.6% women) and camera-trap monitoring in two mangrove areas during September 2024 to document fishing practices, catch characteristics, spatial patterns, and ecological perceptions. We found pronounced gendered divisions of labor and space use: men, using boats and nets, harvested a median of 15 kg of fish per day for commercial sale, generating cash income, whereas women collected a median of 3 kg of shellfish by hand, primarily for household consumption. Camera traps confirmed pronounced spatial segregation in mangrove use: women foraged in targeted areas, and men traversed broader zones, both synchronizing their activities with tidal and daylight cycles. By integrating social and ecological data, the study revealed nuanced gender roles and resource pressures, with 82.9% of participants reporting declines in fish and shellfish stocks, emphasizing mangroves’ critical role in livelihoods, biodiversity, and climate resilience. Our findings highlight the value of mixed-method approaches for understanding socio-ecological dynamics and advocate for gender-sensitive conservation policies, strengthened Community Fisheries Councils, and infrastructure investments to regulate resource use, enhance mangrove management, and promote equitable livelihoods in Mozambique’s coastal communities. Full article

This study investigates rainstorm-induced highway subgrade slope collapses in the coastal areas of Southeast China. By integrating the seepage–stress coupled finite element method with the strength reduction method, we simulate the entire process of seepage, deformation, and slope collapse under rainstorm conditions, analyzing the variation in the stability factor. The key findings are as follows: (1) During rainstorms, water infiltration increases soil saturation and pore water pressure, while reducing matrix suction and soil shear strength, leading to soil softening. (2) The toe of the subgrade slope first undergoes plastic deformation under rainstorms, which develops upward, and finally the plastic zone connects completely, causing collapse. The simulated landslide surface is consistent with the actual one, revealing the collapse mechanism of the subgrade slope. Additionally, the simulated displacement at the slope toe when the plastic zone connects provides valuable insights for setting warning thresholds in landslide monitoring. (3) The stability factor of the subgrade slope in the case study decreased from 1.24 before the rainstorm to 0.985 after the rainstorm, indicating a transition from a stable state to an unstable state. (4) Parameter analysis shows that heavy downpour or downpour will cause the case subgrade slope to enter an unstable state. The longer the rainfall duration, the lower the stability factor. Analysis of soil parameters indicates that strength parameters, internal friction angle, and effective cohesion exert a significant influence on slope stability, whereas deformation parameters, elastic modulus, and Poisson’s ratio have a negligible effect. Slope collapse can be timely forecasted by predicting the stability factor. Full article

Biochar and beneficial microorganisms (BM) is considered promising soil amendment for saline-alkali amelioration and soil carbon storage.However, the effects of biochar combined with BM addition soil organic carbon (SOC) accumulation and microbial characteristics are less known in coastal saline-alkali soil. Herein, we investigated the SOC content and fractions, soil carbon enzyme activities, and microbial community composition in coastal saline-alkali soil, following three levels of biochar and BM addition. Compared to the control treatment, biochar and BM application effectively reduced soil salinity by 37.58–66.53% and increased soil NH₄⁺ by 9.49–121.16% and NO₃⁻ by 43.56–254.28%, respectively. Biochar integrated with BM addition significantly increased the content of SOC, soil mineral-associated organic carbon (MAOC), soil particulate organic carbon (POC), and carbon pool management index (CPMI) by 37.76–108.02%, 15.43–140.44%, 13.73–64.55%, and 81.11–154.61%, respectively, compared with CK treatment. Additionally, biochar and BM significantly enhanced the activities of soil carbon cycle enzymes, including α-1,4-glucosidase (14.54–124.45%), β-1,4-glucosidase (12.71–133.98%), and cellulose hydrolase (6.07–19.17%). Biochar and BM addition also improved the bacterial diversity and altered the microbial composition at the phylum level. The co-addition of biochar and BM improved SOC by decreasing soil salinity and, enhancing soil nutrient availability, soil carbon cycle enzymes, and microbial activity. Furthermore, the combination of 4% biochar and BM exhibited the highest MAOC/POC ratio, demonstrating the most significant impacts on enhancing SOC stability in coastal saline-alkali soil. This study highlighted that the combined use of biochar and BM could serve as a promising approach to fortify soil carbon pool content and stability in saline-alkali land. Full article

The Changjiang estuary–Hangzhou Bay region is a critical zone of land–sea interaction, where Total Suspended Matter (TSM) dynamics significantly influence coastal ecology and engineering. While previous studies have examined individual factors affecting TSM variability, the synergistic effects of “tide–monsoon–current” interactions and the actual pathways of turbid plume transport remain poorly understood. Using GOCI satellite data, in situ buoy measurements, and voyage data from 2020, this study applied Data Interpolating Empirical Orthogonal Functions (DINEOFs) and comprehensive spatio-temporal analysis to reconstruct continuous high-resolution TSM fields and elucidate multi-factor controls on TSM dynamics. Based on this high-resolution dataset of TSM, we found that, during the dry season, elevated TSM concentrations are primarily driven by wind–tide resuspension and transport under the comprehensive forcing of the Jiangsu Alongshore Current (JAC), the Yellow Sea Warm Current (YSWC), and wind–tide-induced flows. Contrary to the conventional understanding, the Jiangsu-origin surface TSM can transport to the outer sea without supplementing the TSM in the Turbidity Maximum Zone (TMZ). The YSWC in autumn can cause either low C_TSM gradients or high gradients nearshore depending on whether it is carrying Korean coastal turbid water or not. During the wet season, stratification induced by the Changjiang freshwater discharge suppresses wind–tide resuspension, reducing TSM concentrations in the TMZ and the Qidong water. However, the Changjiang freshwater combined with the Taiwan Warm Current (TWC) dilutes surface TSM in Hangzhou Bay, where the two water masses meet on the 10 m isobath. These insights into factor interactions and TSM plume pathways provide a scientific basis for improved environmental monitoring and coastal management. Full article

Harmful algal blooms (HABs) represent an escalating threat in marine and coastal ecosystems, posing increasing risks to ecological balance, public health, and blue economy industries including fisheries, aquaculture, and tourism. This review examines the impact of climate change and anthropogenic pressures on the escalation of HAB occurrences, focusing especially on vulnerable regions in Mexico, which are the primary case study for this investigation. The methodological framework integrates HAB risk assessment (RA) methods found in the literature. Progress in detection and monitoring technologies—such as sensing, in situ sensor networks, and prediction tools based on machine learning—are reviewed for their roles in enhancing early-warning systems and aiding decision support. The key findings emphasize four linked aspects: (i) patterns of HAB risk in coastal zones, (ii) deficiencies and prospects in HAB-related policy development, (iii) how governance structures facilitate or hinder effective actions, and (iv) the growing usefulness of online monitoring and evaluation tools for real-time environmental observation. The results emphasize the need for coupled technological and governance solutions to reduce HAB impacts, protect marine biodiversity, and enhance the resilience of coastal communities confronting increasingly frequent and severe bloom events. Full article