Search Results (396)

Coastal waters are vulnerable ecosystems that are increasingly affected by sediment and nutrient inputs, as well as pollution resulting from both natural processes and anthropogenic pressures. Monitoring the pattern of chlorophyll-a and turbidity is essential for understanding the dynamics of coastal ecosystems and supporting environmental management. This study investigates the spatial and seasonal patterns of water quality in the coastal zone of Heraklion, Crete (Greece), for the period 2016–2024 using OCEANIDS Data Cube products (GA 101112919). Water quality variability was assessed using satellite-derived spectral indices, including the Normalized Difference Chlorophyll Index (NDCI) and the Normalized Difference Turbidity Index (NDTI). Monthly observations were analyzed using a GIS-based workflow to assess seasonal spatiotemporal variability. The results revealed strong seasonal variability, with higher winter NDCI values in all coastal zones and persistent hotspots concentrated near river estuaries and waters influenced by port activities. Meanwhile, the analysis was used to prioritize the region for further monitoring and to support decision-making for stakeholders. In summary, this study demonstrates the potential of OCEANIDS Data Cube products (NDCI, NDTI) for long-term monitoring of surface coastal water quality in a Mediterranean environment with limited data and supports evidence-based coastal management. Full article

The ecological status of the two nautical mile (2 nm) coastal waters of Bulgaria (BG) and Romania (RO) is evaluated in terms of eutrophication, focusing on various environmental and chemical indicators related to nutrient enrichment and its effects. Applying the Blue2 Modelling Framework (Blue2MF) Black Sea model, we simulate diverse combinations of nitrogen (N) and phosphorus (P) reduction. By integrating atmospheric and marine conditions, hydrology and environmental dynamics, the model provides a comprehensive framework for analysing the impact of external pressures on the marine environment and can be used to set regional sustainability goals. Each scenario is assessed with respect to environmental impact, such as enhanced water quality and potential alterations in phytoplankton communities. Furthermore, we establish integrated nutrient criteria for eutrophication control, concentrating on the management of both N and P inputs while maintaining the current ratio between them. The model results indicate that a 20% reduction in both N and P from European Union (EU) rivers would result in about a 24% decrease in N within the BG and RO 2 nm coastal waters, whilst sustaining the N:P ratio across various spatial scales—from river inputs to coastal and offshore zones. This approach is valuable for assessing the potential impacts of different nutrient reduction strategies, aiding the effective management of marine ecosystems to address eutrophication challenges. Full article

Charybdis (Gonioneptunus) bimaculata (Miers, 1886), C. (Charybdis) japonica (A. Milne-Edwards, 1861), and C. (Charybdis) miles (De Haan, 1835) are dominant target species harvested by small-scale artisanal fisheries in the coastal waters of China. Characterizing their spatial distribution and interannual population variability is critical for sustainable crustacean stock conservation. Previous investigations of these three Charybdis congeners have been limited to short-duration, single-season, or geographically restricted descriptive surveys, with no systematic cross-species comparison of seasonal habitat use. This has created major knowledge gaps regarding their long-term spatiotemporal dynamics and ecological niche partitioning. We conducted standardized bottom-trawl surveys aboard research vessels across the southern Yellow Sea and East China Sea from 2018 to 2021 to quantify numerical abundance and biomass of the three congeneric crabs. Two species distribution modeling frameworks—Generalized Additive Models (GAMs) and Boosted Regression Trees (BRTs)—were implemented to generate fine-resolution seasonal habitat suitability maps for each species. We identified minimum thermal thresholds for species presence: bottom water temperature > 8 °C for C. bimaculata and >10 °C for C. miles. Core aggregation zones of C. bimaculata and C. japonica occurred in waters adjacent to the Yangtze River Estuary (32–34° N), whereas C. miles predominated in offshore habitats of the southern East China Sea (27–31° N). In this study, C. bimaculata favors shallow seas with warm bottom water and euryhaline conditions, C. japonica prefers low-salinity coastal waters with cold bottom water, and C. miles thrives in deep, high-salinity offshore waters with eurythermal tolerance. The findings of this study can contribute to the sustainable fisheries management and conservation of these species. Full article

Geochemical proxies in coastal sediments are widely applied to reconstruct past climatic and environmental changes, yet their sensitivity to climate versus localized depositional processes remains debated in dynamic land–sea interfaces. Here, we present major, trace, and rare earth element (REE) data from two Holocene sediment cores (QX01 and QX02) from the western coast of Bohai Bay to decouple provenance, weathering, and hydrodynamic controls. Provenance-sensitive trace element ratios (La/Sc and Th/Sc) and REE fractionation patterns indicate exceptional source stability dominated by the Yellow River and adjacent cratonic catchments throughout the Holocene, eliminating provenance shifts as a confounding variable. Since ~8 ka, an overarching upward increase in raw chemical index of alteration (CIA), accompanied by increasing Al/Si ratios and grain sizes, broadly aligned with the warm and humid Holocene Climate Optimum. Crucially, a highly significant linear relationship between grain size, Al/Si and CIA (R² > 0.78) demonstrates that raw CIA variations were decisively modulated by sea-level-driven hydrodynamic sorting during the Holocene transgression, which shifted the depositional setting from high-energy fluvial regimes to low-energy marine settings, preferentially trapping fine-grained, clay-hosted aluminosilicates with inherently high CIA values. During the late Holocene (~5 ka to present), stabilizing sea-level conditions shifted the raw records into an elevated plateau punctuated by high-frequency fluctuations and localized geochemical anomalies, reflecting a dynamic interface sensitive to episodic fluvial floods or tidal/storm reworking that periodically introduced coarser, quartz-rich detritus. The resulting sorting-corrected CIA_C removes the transgressive clay-trapping artifact and reveals a broad, subdued weathering plateau between ~8 ka and 4 ka BP, consisting with previous Chinese Loess Plateau weathering intensity. These findings highlight that in dynamic marginal-marine sinks, raw silicate weathering indices reflect physical sorting overprints, and hydrodynamic detrending is essential to extract genuine continental paleoclimate signals. Full article

The mechanistic understanding of biogeochemical dynamics in the Gulf of Guinea (GoG) has historically been hindered by persistent cloud cover and reliance on static geographic boundaries. In this study, we analysed a 20-year (2003–2022) satellite-derived chlorophyll-a (Chl-a) dataset to overcome these observational limitations through a three-part spatial and machine-learning framework. First, the Data Interpolating Empirical Orthogonal Functions (DINEOF) algorithm reconstructed a gap-free climatology, demonstrating robustness under extreme simulated cloud cover (R² = 0.884). Second, a Fuzzy C-Means (FCM) clustering algorithm objectively partitioned the basin into three dynamic, physically driven bioregions: an oligotrophic gyre, river plumes, and an upwelling mega-cluster. Third, we applied an explainable Random Forest framework, supported by SHapley Additive exPlanations (SHAP), to identify the main physical and biogeochemical predictors associated with coastal Chl-a variability using hindcast nutrients and a strict chronological split (training: 2003–2018; test: 2019–2022). The models produced conservative but meaningful independent test-period performance across coastal zones, with R²_log values from 0.437 to 0.595. Rather than revealing a new ecological paradox, the framework provides a basin-specific interpretation of a globally documented pattern: offshore oligotrophication alongside localized coastal enrichment. The open ocean and transition/upwelling sectors show negative Chl-a tendencies consistent with sea surface warming, enhanced stratification, and reduced upward nutrient supply. Conversely, coastal ecosystems are structured by local hydrological and wind-driven forcings that modulate the regional climate signal. In the Congo plume, Chl-a variability is primarily structured by haline plume dynamics and secondary nutrient constraints, whereas the Niger plume reflects coupled mixed-layer and terrigenous nutrient controls. These findings establish a spatially objective typology of the GoG, providing a regional reference framework for future high-resolution missions, monitoring, and coupled physical–biogeochemical modelling. Full article

Flooding associated with rising inland lake levels represents a distinct and understudied hazard compared to conventional river or coastal flooding. Unlike riverine floods, lake inundation develops gradually and persists over extended periods, yet integrated flood risk assessments specifically addressing this phenomenon remain scarce. This study uses Lake Baringo in Kenya’s Rift Valley as a case study, a lake that has experienced exceptional water level rises of nearly 10 m since 2010, to assess flood risk through the integration of scenario-based flood hazard modelling, spatial exposure assessment, and household vulnerability analysis. Three lake level scenarios were developed, spanning from maximum observed conditions to a worst-case threshold at the lake’s sill point. Results show that under the worst-case scenario, the lake area could expand by approximately 64%, potentially exposing nearly 18,000 people and 156 km of road infrastructure. A Flood Vulnerability Index (FVI) ranging from 0.58 to 0.73 indicated consistently high socioeconomic vulnerability across all shoreline communities, with vulnerability accounting for 42–53% of overall flood risk across scenarios. Flood risk was highest along the flat southern shoreline, where topography amplifies lateral inundation extent. The findings highlight the importance of integrating lake level dynamics into spatial planning and flood risk management, and the need for improved monitoring, livelihood diversification, and institutional coordination in semi-arid inland lake regions facing increasing hydro-climatic variability. Full article

High-resolution Normalized Difference Vegetation Index (NDVI) data are essential for monitoring fine-scale coastal environmental dynamics, yet persistent cloud cover, rapid geomorphic change, and strong spatial heterogeneity limit the availability of temporally continuous observations. Existing spatiotemporal fusion approaches can partially address these limitations, but many rely primarily on data-driven feature learning and do not explicitly incorporate geographic information, leading to boundary blurring, structural inconsistency, and sensitivity to background noise in complex coastal environments. This study presents a geographically constrained Transformer-based framework for 2 m NDVI spatiotemporal reconstruction in coastal landscapes named Coastal-Prior-Embedded Global–Local Fusion Transformer (Coastal-GLFT). The approach integrates high-resolution Gaofen-6 panchromatic and multispectral imagery with high-frequency wide-field-view observations and auxiliary geographic datasets describing elevation, coastline proximity, and land use/land cover. Geographic priors were incorporated as explicit spatial constraints, while a spatiotemporal gating mechanism and global–local fusion architecture were used to improve the representation of temporal variation and multi-scale spatial structure. The method was evaluated using a multi-temporal dataset for the Yellow River Delta comprising 49 high-resolution scenes and 137 coarse-resolution scenes acquired between 2020 and 2025. Compared with representative physics-based, convolutional neural network, generative adversarial network, and Transformer-based fusion methods, the proposed approach reduced reconstruction error by approximately 5–72%, increased signal fidelity by approximately 1–12%, and improved structural similarity by approximately 2–52%. Compared with the strongest Transformer-based baseline, SwinSTFM, Coastal-GLFT reduced RMSE from 0.0896 to 0.0855, increased PSNR from 36.19 dB to 37.09 dB, and improved SSIM from 0.8551 to 0.8742. Qualitative analysis further demonstrated improved preservation of boundary structure, spatial continuity, and heterogeneous coastal features, including aquaculture ponds, tidal creeks, and fragmented wetlands. These results indicate that integrating geographic constraints with multi-scale Transformer-based reconstruction can improve the fidelity and structural consistency of high-resolution NDVI reconstruction in complex coastal environments. The framework provides a basis for fine-scale coastal vegetation monitoring and land-cover analysis, while future work should assess transferability across diverse coastal systems and improve computational scalability. Full article

The escalating global contradiction between water supply and demand has imposed novel imperatives on regional water security within the paradigm of resilient city development. To elucidate the supply–demand dynamics of water provisioning services under heterogeneous institutional contexts, this study selected the Guangdong–Hong Kong–Macao (GHKM) region as the empirical study area. Employing the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, we coupled meteorological, land-use/land-cover (LULC), and pedological data to quantify the provisioning of water yield services in 2024. Concurrently, sector-specific water demands—encompassing agricultural, industrial, domestic, and ecological categories—were accounted for using statistical yearbooks. Subsequently, a Supply–Demand Index (SDI) was formulated to delineate the spatial matching patterns. The findings reveal pronounced spatial heterogeneity in water service provisioning; high-value zones are predominantly aggregated along the western and southern coastal belts, whereas low-value zones are dispersed across the northern mountainous terrains. Based on the SDI classification, the study area comprises 12 supply-surplus, 6 supply–demand-equilibrium, and 5 supply-deficit administrative units. Notably, the northern Guangdong mountainous region assumes a critical ecological role in water conservation, whereas the core megalopolises of the Pearl River Delta exhibit an acute dependency on extrinsic water subsidies, with Macao demonstrating a distinct ecological deficit in water provisioning. Furthermore, this study uncovers the overestimation artifact of water yield estimations over urban impervious surfaces, thereby providing a robust empirical foundation for the cross-regional synergistic governance and adaptive management of water resources. Full article

The Mississippi River Delta region is of national and international relevance in terms of agriculture, energy, river navigation, and fisheries. Being one of the most engineered rivers in the world, the Mississippi River has been intensively altered over the past 150 years. The river alterations included the construction of dams, levees, diversions, channelization, spillway flood control systems, and many others. These engineering practices have significantly modified the natural hydrology and sediment dynamics of the river and its deltaic region. While these interventions have provided critical benefits such as flood protection, improved navigation, and economic development, they have also led to profound environmental and ecological consequences. The reduction in sediment delivery to the Mississippi River Delta has accelerated land loss, contributing to the disappearance of coastal wetlands at an alarming rate. The land loss has diminished critical habitats for wildlife, reduced storm surge protection for coastal communities, and disrupted the delta’s natural ability to adapt to fast subsidence. The long-term sustainability of the delta is further threatened by the compounding effects of climate change, including rising sea levels, increased storm intensity, and extreme precipitation and drought conditions. This paper examines the effects, consequences, and future risks of the major river engineering practices on the Mississippi River Delta and provides strategic recommendations that balance human needs with changing natural conditions to ensure sustainability. Specific recommendations include river diversion upstream of New Orleans, better strategies to deal with floods and droughts, strategic maintenance or removal of portions of levees, hybrid coastal-inland human migration, improved transportation connections between coast and inland, and better preparation for future ecosystem shifts. This review is needed because river engineering has made the Mississippi River Delta economically vital yet increasingly vulnerable to sediment loss, wetland collapse, saltwater intrusion, flooding, and population decline. By synthesizing these linked natural and human consequences, it provides a timely framework for rethinking delta sustainability under climate change. Full article

Mangrove forests provide essential ecosystem services but are increasingly threatened by anthropogenic pressures and climate-related disturbances. Effective and accessible tools for assessing mangrove ecosystem condition are therefore needed to soundly support their conservation and management. This study adapted the “Coastal Health” framework originally proposed for assessing coastal ecosystems health to evaluate the health status of mangrove forests along the Caribbean coast of Colombia. Using freely available high-resolution imagery from Google Earth Pro 7.3, complemented by field observations, technical reports, and unpublished literature, 56 mangrove sites distributed across eight coastal departments were assessed according to their ecological integrity, hydrological connectivity, sediment dynamics, freshwater and marine inputs, mangrove species condition, and their potential for landward and seaward migration. The results showed that 54% of the evaluated sites were classified as being in “Good Health”, while 2% were categorized as “Health Warning”, 3% as “Surface Wounds”, 14% as “Minor Injury”, 25% as “Major Injury”, and 2% as “Deceased”. Mangroves in good condition were generally associated with protected areas, river mouths, estuaries, and relatively isolated coastal systems, whereas degraded ecosystems were affected by urban expansion, tourism infrastructure, hydrological alterations, coastal engineering works, and reduced freshwater inputs. The proposed methodology proved to be a simple, low-cost, and easily replicable tool for large-scale mangrove health assessment. It provides valuable information for prioritizing conservation and restoration actions and can be adapted to support mangrove monitoring and ecosystem-based coastal management in other regions worldwide. Full article

The Guajira Upwelling System (GUS) is located between 10–12.5° N and 61–75.5° W in the Southern–Central Caribbean Sea. This study examines its spatial and seasonal variability using upwelling indices derived from surface differences in temperature, salinity, density, and absolute dynamic topography between the GUS and a nearby Caribbean region (78–68° W, 10–16° N) not affected by coastal upwelling. Weekly time series from 1998 to 2022 were analyzed. The difference-based indices were compared with Ekman transport, a conventional proxy for upwelling intensity, and with satellite-derived chlorophyll-a to evaluate the phytoplankton response. Seasonal cycles were further examined at four representative grid points along the system. Among the indices, sea surface temperature most effectively delineated the spatial extent and seasonal variability of the GUS. Comparisons with chlorophyll-a revealed a strong upwelling–biomass relationship in the northern sector (east of 73.5° W), whereas productivity in the southern sector was not primarily driven by coastal upwelling. Correlation maps indicated that the weakening of upwelling influence coincided with the region affected by the Magdalena River plume. Full article

Achieving coordinated development between higher education and regional economies is central to sustainable urban growth. This study examines the spatiotemporal coupling coordination between higher education and economic development across 90 cities within seven major coastal urban agglomerations in China over the period 2008–2021. An evaluation index system was constructed across seven dimensions, and three analytical methods were integrated: the entropy weight method for composite index calculation, the coupling coordination degree model for assessing synergistic development, and the panel vector autoregression (PVAR) model for dynamic interaction analysis. A fixed-effects regression model was further applied to identify key driving factors. The results indicate that: (1) higher education levels showed a steady upward trend across all agglomerations, while widening absolute disparities persisted among cities; (2) although a bidirectional Granger-causal relationship exists between higher education and economic development, the interaction is asymmetric along two distinct dimensions: higher education exerts a more statistically robust predictive influence on the economy, while unforecast economic shocks transmit more strongly to higher education than the reverse; this asymmetry manifests in specific urban agglomerations—most notably the Pearl River Delta—as a structural mismatch between economic strength and higher education development; (3) economic development level, government fiscal support, urbanization, and higher education scale are significantly associated with the coupling coordination between the two systems. These findings highlight the structural misalignment between higher education supply and regional economic demand and underscore the need for differentiated, spatially targeted policy interventions to promote sustainable regional development. Policy recommendations are proposed for optimizing higher-education resource allocation, reforming talent cultivation, and strengthening intra-agglomeration coordination mechanisms. Full article

This study investigated vegetation frontline dynamics, fractional vegetation cover (FVC), and community succession in the tidal-flat wetlands of the Liaohe Estuary. The eastern bank of the Liaohe River within the Shuangtaihe National Nature Reserve was selected as the study area, and six periods of Landsat and Gaofen-1 (GF-1) imagery from 2000 to 2025 were used. Remote-sensing preprocessing, normalized difference vegetation index (NDVI)-based FVC inversion, vegetation frontline extraction, Digital Shoreline Analysis System (DSAS)-based rate calculation, land-cover classification, and spatial correlation analysis were integrated to characterize wetland spatiotemporal dynamics and succession patterns. The results showed that the linear regression rate (LRR) and end point rate (EPR) effectively captured the long-term trend and five short-term fluctuations in vegetation frontline migration. FVC fluctuated markedly over the 25-year period, whereas the weighted average (WA) of the five FVC classes remained generally stable and effectively summarized overall vegetation growth. Vegetation frontline migration was spatially associated with annual FVC change (ΔFVC); both LRR and ΔFVC showed significant positive spatial autocorrelation and evident spatial clustering. In addition, the conversion among mudflats, Suaeda salsa, Phragmites australis, and water bodies was closely coupled with frontline migration. These findings provide a scientific basis for quantifying coastal wetland sustainability and for designing spatially targeted restoration strategies in the Liaohe Estuary. The proposed coupling analysis framework also offers a transferable remote sensing approach for monitoring wetland sustainability under changing environmental conditions. Full article

Extreme meteorological and climate events, such as floods and prolonged droughts, cause socio-environmental disasters in several regions of the world, including the Amazon. The Amazon Delta-Estuary, which is shaped by coastal and river environments, has constantly changing land use patterns, making it vulnerable to such events. This study aimed to evaluate rainfall regimes and flood scenarios in the tributaries of the Amazon Delta-Estuary, known as the Ottocoded River sub-basins, which are located in the municipalities of Abaetetuba and Barcarena in the Brazilian state of Pará. The Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) dataset was used to analyze rainfall dynamics. The Height Above the Nearest Drainage (HAND) model was employed for flood modeling. The geomorphological, altimetric, bathymetric, and hydrodynamic components of the water bodies were also analyzed. Flood susceptibility was zoned as follows: Very High, High, Medium, Low and Very Low. Of the surveyed buildings, 28.8% were classified as ‘Very High’, 29.1% as ‘High’, 20.2% as ‘Medium’, 13.4% as ‘Low’, and 8.5% as ‘Very Low’. Many of these buildings are located in flood-prone areas, posing a significant risk of socio-environmental disasters. This research could inform public policies aimed at managing the risks associated with environmental disasters and extreme events. Full article