Search Results (1,649)

One of the most significant impacts of climate change is sea-level rise, which is increasingly threatening to the coastal setting, infrastructure, and socioeconomic systems. Since a change at the sea level is spatially non-uniform and highly modulated by local oceanographic and climatic events, local or regional-scale measurements are necessary—especially in semi-enclosed basins. This paper examines the long-term variability of sea levels throughout the Persian Gulf and illustrates a strong spatial variance of the trends over the past and the future. Using three decades of satellite-derived observations, regional sea-level trends were estimated from monthly sea-level anomaly (SLA) data, which were also used to generate future projections to 2100. The analysis shows that the rate of sea-level rise along the UAE–Oman stretch is 3.88 mm year⁻¹ and that of the Strait of Hormuz is 5.23 mm year⁻¹, with a mean of 4.44 mm year⁻¹ in the basin. Statistical forecasts of sea-level change were projected by a statistical forecasting scheme with high predictive ability with the optimal configuration of an average of 0.0391 m, an RMSE of 0.0492 m, and an R² of 0.80 when independent validation was conducted. It is estimated that by 2100, the average rise of the sea level in the Persian Gulf is about 0.30–0.40 m, and the peak rise in sea level is at the Strait of Hormuz. Since these projections are based on statistical extrapolation rather than physics-based climate models, they are interpreted within the uncertainty envelope defined by IPCC AR6 scenarios. This study presents a unique, regionally resolved viewpoint on sea-level rise that is relevant to coastal risk management and adaptation planning in semi-enclosed marine basins by connecting robust statistical performance with physically interpretable regional patterns. Full article

This study presents a validated framework to quantify regional sea-level risk on U.S. coasts by (i) extracting trends and seasonality from satellite altimetry (ADT, GMSL), (ii) learning regional dynamical regimes via PCA-embedded KMeans on gridded ADT time series, and (iii) coupling these regimes with socioeconomic exposure (population, income, ocean-sector employment/GDP) and wetland submersion scoring. Relative to linear and ARIMA/SARIMA baselines, a sinusoid+trend fit and an LSTM forecaster reduce out-of-sample error (MAE/RMSE) across the North Atlantic, North Pacific, and Gulf of Mexico. The clustering separates high-variability coastal segments, and an interpretable submersion score integrates elevation quantiles and land cover to produce ranked adaptation priorities. Overall, the framework converts heterogeneous physical signals into decision-ready coastal risk tiers to support targeted defenses, zoning, and conservation planning. Full article

Climate change and the resulting projected rise in sea level put densely populated urban communities at risk of river flooding, storm surges, and subsurface flooding. Miami finds itself in an increasingly vulnerable position, as compound inundation seems to be a constant and unavoidable occurrence due to its low elevation and limestone geomorphology. Several recent studies on compound overflows have been conducted in Miami-Dade County. However, in-depth research has yet to be conducted on its economic epicenter. Owing to the lack of resilience to tidal surges and extreme precipitation events, Miami’s infrastructure and the well-being of its population may be at risk of flooding. This study applied HEC-RAS 2D to develop one- and two-dimensional water flow models to understand and estimate Miami’s vulnerability to extreme flood events, such as 50- and 100-year return storms. It used Hurricane Irma as a validation and calibration event for extreme event reproduction. The study also explores novel machine learning metamodels to produce a robust sensitivity analysis for the hydrologic model. This research is expected to provide insights into vulnerability thresholds and inform flood mitigation strategies, particularly in today’s unprecedented and intensified weather events. The study revealed that Miami’s inner bay coastline, particularly the downtown coastline, is severely impacted by extreme hydrometeorological events. Under extreme event circumstances, the 35.4 km² area of Miami is at risk of flooding, with 38% of the areas classified as having medium to extreme risk by FEMA, indicating severe infrastructural and community vulnerability. Full article

The rapid expansion of wind power as a key component of global renewable energy systems has led to the widespread deployment of wind turbines in environments exposed to diverse natural hazards. While hazard effects are often investigated individually, real wind turbine systems frequently experience concurrent or sequential hazards over their operational lifetime, giving rise to interaction effects that are not adequately captured by conventional design approaches. This paper presents Part 2 of a comprehensive review on natural hazards affecting wind turbine performance, combining bibliometric keyword co-occurrence analysis with a critical synthesis of recent technical studies. The review focuses on earthquakes, sea waves, and extreme wind events, while also highlighting other hazard types that have received comparatively limited attention in the literature, examining their effects on wind turbine systems and the mitigation strategies reported to address associated risks. Rather than treating hazards in isolation, their impacts are synthesised through cross-hazard interaction pathways and component-level failure modes. The findings indicate that wind turbine vulnerability under multi-hazard conditions is governed not only by load magnitude but also by hazard-induced changes in system properties and operational state. Key research gaps are identified, emphasising the need for state-aware, mechanism-consistent multi-hazard assessment frameworks to support the resilient design and operation of future wind energy systems. Full article

Climate change and sea-level change (SLC) are intensifying flooding in U.S. coastal communities, with disproportionate impacts on Black and minority neighborhoods that face displacement, economic hardship, and heightened health risks. In Norfolk, Virginia, sea levels are projected to rise by at least 0.91 m (3 ft) by 2100, placing underserved neighborhoods such as Oakleaf Forest at particular risk. This study investigates the compounded impacts of flooding at both the building and urban scales, situating the work within the framework of the UN Sustainable Development Goals (UN SDGs). A mixed-method, community-based approach was employed, integrating literature review, field observations, and community engagement to identify flooding hotspots, document lived experiences, and determine preferences for adaptation strategies. Community participants contributed actively through mapping sessions and meetings, providing feedback on adaptation strategies to ensure that the process was collaborative, place-based, and context-specific. Preliminary findings highlight recurring flood-related vulnerabilities and the need for interventions that address both environmental and social dimensions of resilience. The study proposes multi-scale, nature-based solutions (NbS) to mitigate flooding, restore ecological functions, and enhance community capacity for adaptation. Ultimately, this work underscores the importance of coupling technical strategies with participatory processes to strengthen resilience and advance climate justice in vulnerable coastal neighborhoods. Full article

Coastal flooding can result from multiple interacting drivers and can be a complex, challenging topic for learners to grasp. Interactive learning with apps offers new opportunities for improving comprehension and engagement. We present the Floodport app, an educational interactive tool that puts students in the role of coastal risk analysts exploring how natural hazards threaten port safety. Users have to adjust key parameters, including high tides, storm surges, terrestrial rainfall contribution, sea-level rise, and engineered features such as dock height. These forces, individually or jointly, result in water-level rises that may flood the app’s port. The app supports exploration of mitigation designs for the port. Developed in Excel and Python 3.11.4 and deployed as an R/Shiny application, Floodport was used as a classroom game by 153 students with no prior knowledge on coastal flooding concepts. Pre–post survey statistical analysis showed significant learning gains and positively correlation with willingness to engage further. Floodport was found to be a useful tool for basic introduction to flooding concepts. The results indicate strong pedagogical promise and potential for using the app beyond the classroom, in contexts such as stakeholder engagement and training. Full article

The Iraqi coastline in the northern Persian Gulf is highly vulnerable to the impacts of future sea level rise. This study introduces a novel approach in the Arc Geographic Information System (ArcGIS) for inundation risk of the 58 km Iraqi coast of the northern Persian Gulf through a combination of multi-data sources, machine-learning predictions, and hydrological connectivity by Landsat. The Prophet/Neural Prophet time-series framework was used to extrapolate future sea level rise with 11 satellite altimetry missions that span 1993–2023. The coastline was obtained by using the Landsat-8 Operational Land Imager (OLI) imagery based on the Normalised Difference Water Index (NDWI), and topography was obtained by using the ALOS World 3D 30 m DEM. Global Land Use and Land Cover (LULC) projections (2020–2100) and population projections (2020–2100) were used as future inundation values. Two scenarios were compared, one based on an altimeter-based projection of sea level rise (SLR) and the other based on the National Aeronautics and Space Administration (NASA) high-emission scenario, Representative Concentration Pathway 8.5 (RCP8.5). It is found that, by the IPCC AR6 end-of-century projection horizon (relative to 1995–2014), 154,000 people under the altimeter case and 181,000 people under RCP8.5 will have a risk of being inundated. The highest flooded area is the barren area (25,523–46,489 hectares), then the urban land (5303–5743 hectares), and finally the cropland land (434–561 hectares). Critical infrastructure includes 275–406 km of road, 71–99 km of electricity lines, and 73–82 km of pipelines. The study provides the first hydrologically verified Digital Elevation Model (DEM)-refined inundation maps of Iraq that offer a baseline, in the form of a comprehensive and quantitative base, to the coastal adaptation and climate resilience planning. Full article

Issues related to malnutrition are addressed primarily through the consumption of fish meat, as it is both affordable and accessible to economically weaker sections of the population. Therefore, challenges observed in the aquaculture and fishery sectors, such as the detection of environmental changes, disease outbreaks, hindered growth, and poor fish health management, need to be addressed to increase production. The employment of modern technologies, such as (bio)sensors, helps to enhance production in artisanal and large aquaculture systems, because these can timely detect challenges, including climate change factors, sea-level-rise-induced salinity load, changes in inland temperatures, ocean acidification, changes in precipitation patterns, ammonia toxicity, infectious diseases, and stress factors in aquatic systems. As a result, appropriate and timely measures can be taken at various stages of fish culture to address common problems. Using major scientific electronic databases, we comprehensively reviewed the topic of emerging needs, expanding applications, and recent technological advances in biosensors, with a particular focus on pisciculture. We highlight the biosensor technology used in the fisheries industry, which represents a pivotal step towards addressing its various aspects. Full article

Coastal cities face escalating flood risk under sea-level rise, yet landscape-based adaptation strategies often remain speculative and weakly connected to the accessibility and economic constraints that shape sustainable urban development. This study developed a modeling-to-design framework that translates coupled climate and land-use projections into implementable landscape interventions, through planning-level spatial allocation, using Dalian, China as a case study under “middle of the road” (SSP2-4.5) climate conditions. The framework integrates the Land-use Evolution and Assessment Model (LEAM) with connected-bathtub flood modeling to evaluate whether strategic landscape design can redirect development away from flood-prone zones while accommodating projected growth and maintaining accessibility to employment and services. Interventions—protective wetland restoration (810 km²) and blue–green corridors (8 km²)—derived from a meta-synthesis of implemented coastal projects were operationalized as LEAM spatial constraints. Our results show that residential development can be redirected away from coastal risk with 100% demand satisfaction and elimination of moderate-risk allocations. Cropland demand was fully accommodated. In contrast, commercial development experienced 99.8% reduction under strict coastal protection, reflecting locational dependence on port-adjacent sites. This modeling-to-design framework offers a transferable approach to quantifying where landscape interventions succeed, where they face barriers, and where complementary measures are required, supporting decision-making that balances environmental protection, economic function, and social accessibility in sustainable coastal development. Full article

Coastal wetlands, situated at the critical land–sea ecotone, play a vital role in sustaining ecological balance and supporting human activities. Currently, these ecosystems face dual stresses from climate change and intensified anthropogenic activities, making the quantitative assessment of ecosystem functions—represented by Gross Primary Productivity (GPP)—essential for their protection and management. However, a knowledge gap remains regarding coastal–urban complex ecosystems, and existing studies on coastal wetlands often overlook macro-environmental drivers beyond sea-level rise. This study leveraged the MOD17A2H V006 dataset to generate a 500 m GPP product for Zhanjiang City. We analyzed the spatiotemporal dynamics of GPP, utilized land use data to examine the evolution of coastal wetlands, and employed the Geodetector model to quantify the contributions of various factors to GPP in Zhanjiang and its coastal wetlands. The results indicate that: (1) GPP in Zhanjiang exhibited an overall steady upward trend, increasing at an average rate of $13.8\mathrm{g}\mathrm{C}·{\mathrm{m}}^{-2}·{\mathrm{yr}}^{-1}$. However, it displayed strong spatial heterogeneity, characterized by higher values in the southwest and lower values in the northern and coastal regions. (2) The land use pattern in Zhanjiang underwent significant transformations over the past two decades. Cropland and impervious surfaces expanded markedly, increasing by 194.6 km² and 290.42 km², respectively, while coastal wetland areas showed a continuous decline, with degraded and newly formed areas of 101.5 km² and 42 km², respectively. (3) The Geodetector results revealed that the q-value of Nighttime Light (NTL) increased from negligible values to over 0.1, emerging as a dominant driving factor. Although the driving force of anthropogenic activity factors on Zhanjiang and its coastal wetlands has steadily increased, natural factors currently remain the dominant forces. These findings unravel the driving mechanisms of natural and anthropogenic factors on GPP in Zhanjiang, providing valuable scientific evidence for the sustainable development of coastal ecosystems. Full article

Antarctic ice shelves regulate ice-sheet discharge and global sea-level rise, yet their rapid retreat underscores the need for new, low-cost monitoring tools. We analyze ambient seismic noise recorded by seismometers on the Pine Island Glacier ice shelf to characterize wind-induced signals and detect persistent structural resonances. Power spectral analysis shows that wind sensitivity is strongly damped compared with bedrock sites: noise increases only 5–7 dB from 0 to 25 m s⁻¹ winds, versus a 42 dB increase at an inland bedrock station, reflecting the contrasted coupling environments of floating and grounded substrates. The horizontal-to-vertical spectral ratio (HVSR) spectrograms reveal two temporally stable peaks at ~2.2 Hz and ~4.3 Hz that persist across stations and remain independent of environmental forcing. Forward modeling indicates that these peaks correspond to S-wave resonances within the ice shelf. The inferred ice-water interface depth (~440 m) agrees with the Bedmap2 thickness estimate (466 m). This work demonstrates that HVSR provides an effective passive, single-station method for measuring ice shelf thickness. Full article

Seawater intrusion forms a significant environmental and hydrogeological phenomenon that raises significant risks for the sustainability and quality of coastal aquifer hydrosystems. The present review study critically examines the available methodologies for assessing aquifer susceptibility to seawater intrusion, including the GALDIT and SEAWAT models. The GALDIT model is a parametric model that uses six main hydrogeological parameters for assessing groundwater vulnerability to seawater intrusion. Numerous researchers have proposed improvements to GALDIT either by adding new variables such as well density, well pumping rates, and hydrochemical indicators, or by applying machine learning (ML), fuzzy logic, and optimization algorithms to improve spatial resolution and accuracy. The SEAWAT code can be used for simulating variable-density groundwater flow and solute transport and has been widely used to model the salinization process under different pumping and sea-level rise scenarios. The presented case studies show that the combination of GALDIT and SEAWAT offers a stronger and robust framework for both vulnerability zoning and dynamic flow and transport simulation. Recent SEAWAT studies show that paleo-salinization has a significant influence, highlighting the need to measure both the trapped saline water in confined layers and the lateral intrusion of seawater. The present review concludes that future efforts need to focus on hybrid modeling approaches, integration of hydrochemical and geophysical data, and the inclusion of anthropogenic and climate-associated factors to enhance the accuracy and applicability of seawater intrusion risk assessments in coastal areas. Full article

To quantitatively assess the storm surge induced by Super Typhoon Doksuri (2023) along the complex coastline of Fujian Province, a high-resolution Finite-Volume Coastal Ocean Model (FVCOM) was developed, driven by a refined Holland–ERA5 hybrid wind field with integrated physical corrections. The hybrid approach retains the spatiotemporal coherence of the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis in the far field, while incorporating explicit inner-core adjustments for quadrant asymmetry, sea-surface-temperature dependency, and bounded decay after landfall. A series of numerical experiments were conducted, including paired tidal-only and full storm-forcing simulations, along with a systematic sensitivity ensemble in which bottom-friction parameters were perturbed and the anomalous (typhoon-related) wind component was scaled by factors ranging from 0.8 to 1.2. Static sea-level rise (SLR) scenarios (+0.3 m, +0.5 m, +1.0 m) were imposed to evaluate their influence on extreme water levels. Storm surge extremes were analyzed using a multi-scale coastal buffer framework, comparing two extreme extraction methods: element-mean followed by time-maximum, and node-maximum then assigned to elements. The model demonstrates high skill in reproducing astronomical tides (Pearson r = 0.979–0.993) and hourly water level series (Pearson r > 0.98) at key validation stations. Results indicate strong spatial heterogeneity in the sensitivity of surge levels to both bottom friction and wind intensity. While total peak water levels rise nearly linearly with SLR, the storm surge component itself exhibits a nonlinear response. The choice of extreme-extraction method significantly influences design values, with the node-based approach yielding peak values 0.8% to 4.5% higher than the cell-averaged method. These findings highlight the importance of using physically motivated adjustments to wind fields, extreme-value analysis across multiple coastal buffer scales, and uncertainty quantification in future SLR-informed coastal risk assessments. By integrating analytical, physics-based inner-core corrections with sensitivity experiments and multi-scale analysis, this study provides an enhanced framework for storm surge modeling suited to engineering and coastal management applications. Full article

Humanity is at a critical juncture in its response to environmental issues. Coastal land spaces are under threat from rising sea levels and storm surges accelerating erosion and degradation. Children have an important role in sustaining a viable environmental future. Education for sustainability in early childhood (EC) nature-based settings has the potential to disrupt the current crisis by deepening children’s understanding of the environment. Many educators who practice nature pedagogy in early childhood education (ECE) shy away from using technological tools despite our existence in a time of artificial intelligence and digitalisation, some of which is becoming evident in EC sustainability education. This paper will consider the use of blue spaces that incorporate the waters, sands, and coastal land adjacent to the water’s age for EC sustainability teaching and learning. It will focus on questioning the role of technologization, particularly technological tools, on the forms of sustainability education that preschool children experience while in nature-based settings. Interrogating recent research of nature-based kindergartens undertaken at Australian coastal contexts, and drawing on seminal international documentation, it will focus on the development of young children’s empathy and ‘ethos of care’ for living things, their considerations of local ecosystems, and their growing understandings of the interrelationships between elements of their environment. The paper will then consider how the application of technological tools intersects with sustainability education in the context of blue spaces. The research highlights the importance of the educator in the development of interactive, learner-centred opportunities that not only enable investigative, action-adapted learning but also fosters independent learners who are responsive to their natural environment. The implication of this research is that further considerations of technologization and children’s environmental agency through a play-based, emergent curriculum are necessary. Full article

Submesoscale dynamics are critical modulators of upper-ocean biogeochemistry, yet their net influence on chlorophyll concentrations across seasonal to interannual timescales, particularly within productive regions like the Benguela Current Large Marine Ecosystem (BCLME), remains poorly understood. This study quantifies these complex relationships by analyzing 22 years (2001–2022) of physical and biological data. We examined the link between surface chlorophyll (CHL) and key physical drivers: sea level anomaly (SLA) and submesoscale intensity, quantified by the Rossby number (Ro). Using both cross-correlation analysis and Generalized Linear Models (GLMs), our analyses reveal a multi-scale set of spatially dependent and time-lagged biogeochemical responses. At the basin scale, a key finding from cross-correlation is a significant positive correlation where high SLA precedes a rise in CHL by approximately six months, indicating a delayed ecosystem response to large-scale physical forcing. At the event scale, GLMs show the specific impact of eddies is critical: short-lived cyclonic eddies correlate with a significant increase in CHL (~4.6%) in the southern zone, while anticyclonic eddies are associated with a pronounced decrease in CHL (~97.7%) in the central zone during the austral winter. These findings demonstrate that both large-scale preconditions and localized submesoscale features are essential drivers of vertical nutrient transport and the distribution of primary productivity within the BCLME. Full article