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Search Results (629)

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Keywords = sea level rise modeling

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28 pages, 3909 KiB  
Article
Exploring How Climate Change Scenarios Shape the Future of Alboran Sea Fisheries
by Isabella Uzategui, Susana Garcia-Tiscar and Paloma Alcorlo
Water 2025, 17(15), 2313; https://doi.org/10.3390/w17152313 - 4 Aug 2025
Abstract
Climate change is disrupting marine ecosystems, necessitating a deeper understanding of environmental and fishing-related impacts on exploited species. This study examines the effects of physical factors (temperature, thermal anomalies, salinity, seabed conditions), biogeochemical elements (pH, oxygen levels, nutrients, primary production), and fishing pressure [...] Read more.
Climate change is disrupting marine ecosystems, necessitating a deeper understanding of environmental and fishing-related impacts on exploited species. This study examines the effects of physical factors (temperature, thermal anomalies, salinity, seabed conditions), biogeochemical elements (pH, oxygen levels, nutrients, primary production), and fishing pressure on the biomass of commercially important species in the Alboran Sea from 1999 to 2022. Data were sourced from the Copernicus observational program, focusing on the geographical sub-area 1 (GSA-1) zone across three depth ranges. Generalized Additive Models were applied for analysis. Rising temperatures and seasonal anomalies have largely negative effects, disrupting species’ physiological balance. Changes in water quality, including improved nutrient and oxygen concentrations, have yielded complex ecological responses. Fishing indices highlight the vulnerability of small pelagic fish to climate change and overfishing, underscoring their economic and ecological significance. These findings stress the urgent need for ecosystem-based management strategies that integrate climate change impacts to ensure sustainable marine resource management. Full article
(This article belongs to the Special Issue Impact of Climate Change on Marine Ecosystems)
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22 pages, 3013 KiB  
Article
Determining Early Warning Thresholds to Detect Tree Mortality Risk in a Southeastern U.S. Bottomland Hardwood Wetland
by Maricar Aguilos, Jiayin Zhang, Miko Lorenzo Belgado, Ge Sun, Steve McNulty and John King
Forests 2025, 16(8), 1255; https://doi.org/10.3390/f16081255 - 1 Aug 2025
Viewed by 197
Abstract
Prolonged inundations are altering coastal forest ecosystems of the southeastern US, causing extensive tree die-offs and the development of ghost forests. This hydrological stressor also alters carbon fluxes, threatening the stability of coastal carbon sinks. This study was conducted to investigate the interactions [...] Read more.
Prolonged inundations are altering coastal forest ecosystems of the southeastern US, causing extensive tree die-offs and the development of ghost forests. This hydrological stressor also alters carbon fluxes, threatening the stability of coastal carbon sinks. This study was conducted to investigate the interactions between hydrological drivers and ecosystem responses by analyzing daily eddy covariance flux data from a wetland forest in North Carolina, USA, spanning 2009–2019. We analyzed temporal patterns of net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (RE) under both flooded and non-flooded conditions and evaluated their relationships with observed tree mortality. Generalized Additive Modeling (GAM) revealed that groundwater table depth (GWT), leaf area index (LAI), NEE, and net radiation (Rn) were key predictors of mortality transitions (R2 = 0.98). Elevated GWT induces root anoxia; declining LAI reduces productivity; elevated NEE signals physiological breakdown; and higher Rn may amplify evapotranspiration stress. Receiver Operating Characteristic (ROC) analysis revealed critical early warning thresholds for tree mortality: GWT = 2.23 cm, LAI = 2.99, NEE = 1.27 g C m−2 d−1, and Rn = 167.54 W m−2. These values offer a basis for forecasting forest mortality risk and guiding early warning systems. Our findings highlight the dominant role of hydrological variability in ecosystem degradation and offer a threshold-based framework for early detection of mortality risks. This approach provides insights into managing coastal forest resilience amid accelerating sea level rise. Full article
(This article belongs to the Special Issue Water and Carbon Cycles and Their Coupling in Forest)
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17 pages, 4065 KiB  
Article
Relative Sea Level Changes in the Bay of Maladroxia, Southwestern Sardinia, and Their Implications for the Pre- and Protohistoric Cultures
by Steffen Schneider, Marlen Schlöffel, Anna Pint and Constance von Rüden
Geosciences 2025, 15(8), 287; https://doi.org/10.3390/geosciences15080287 - 1 Aug 2025
Viewed by 153
Abstract
A multidisciplinary study was conducted to reconstruct the paleoenvironmental evolution of Maladroxia Bay, one of the principal bays of the islet of Sant’Antioco in southwestern Sardinia, over the past eight millennia. As part of an archaeological landscape project, this study explores the paleogeography [...] Read more.
A multidisciplinary study was conducted to reconstruct the paleoenvironmental evolution of Maladroxia Bay, one of the principal bays of the islet of Sant’Antioco in southwestern Sardinia, over the past eight millennia. As part of an archaeological landscape project, this study explores the paleogeography and environment of the bay from a diachronic perspective to gain insights into the Holocene relative sea level history, shoreline displacements, and the environmental conditions during different phases. This study is based on an analysis of four sediment cores in conjunction with a chronological model that is based on radiocarbon dates. Four relative sea level indicators were produced. These are the first such indicators from the early and middle Holocene for the island of Sant’Antioco. The results indicate that in the early Holocene, the area was a terrestrial, fluvial environment without marine influence. In the 6th millennium BCE, the rising sea level and marine transgression resulted in the formation of a shallow inner lagoon. It reached its maximum extent in the middle of the 5th millennium BCE. Afterwards, a gradual transition from lagoon to floodplain, and a seaward shift of the shoreline occurred. The lagoon potentially served as a valuable source of food and resources during the middle Holocene. During the Nuragic period (2nd to 1st millennium BCE), the Bay of Maladroxia was very similar to how it is today. Its location was ideal for use as an anchorage, due to the calm and sheltered conditions that prevailed. Full article
(This article belongs to the Section Sedimentology, Stratigraphy and Palaeontology)
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19 pages, 4467 KiB  
Article
Delineation of Dynamic Coastal Boundaries in South Africa from Hyper-Temporal Sentinel-2 Imagery
by Mariel Bessinger, Melanie Lück-Vogel, Andrew Luke Skowno and Ferozah Conrad
Remote Sens. 2025, 17(15), 2633; https://doi.org/10.3390/rs17152633 - 29 Jul 2025
Viewed by 138
Abstract
The mapping and monitoring of coastal regions are critical to ensure their sustainable use and viability in the long term. Delineation of coastlines is becoming increasingly important in the light of climate change and rising sea levels. However, many coastlines are highly dynamic; [...] Read more.
The mapping and monitoring of coastal regions are critical to ensure their sustainable use and viability in the long term. Delineation of coastlines is becoming increasingly important in the light of climate change and rising sea levels. However, many coastlines are highly dynamic; therefore, mono-temporal assessments of coastal ecosystems and coastlines are mere snapshots of limited practical value for space-based planning. Understanding of the spatio-temporal dynamics of coastal ecosystem boundaries is important to inform ecosystem management but also for a meaningful delineation of the high-water mark, which is used as a benchmark for coastal spatial planning in South Africa. This research aimed to use hyper-temporal Sentinel-2 imagery to extract ecological zones on the coast of KwaZulu-Natal, South Africa. A total of 613 images, collected between 2019 and 2023, were classified into four distinct coastal ecological zones—vegetation, bare, surf, and water—using a Random Forest model. Across all classifications, the percentage of each of the four classes’ occurrence per pixel over time was determined. This enabled the identification of ecosystem locations, spatially static ecosystem boundaries, and the occurrence of ecosystem boundaries with a more dynamic location over time, such as the non-permanent vegetation zone of the foredune area as well as the intertidal zone. The overall accuracy of the model was 98.13%, while the Kappa coefficient was 0.975, with user’s and producer’s accuracies ranging between 93.02% and 100%. These results indicate that cloud-based analysis of Sentinel-2 time series holds potential not just for delineating coastal ecosystem boundaries, but also for enhancing the understanding of spatio-temporal dynamics between them, to inform meaningful environmental management, spatial planning, and climate adaptation strategies. Full article
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32 pages, 5874 KiB  
Article
A Model for Future Development Scenario Planning to Address Population Change and Sea Level Rise
by Daniel Farrah, Michael Volk, Thomas S. Hoctor, Vivian Young, Margaret Carr, Paul D. Zwick, Crystal Goodison and Michael O’Brien
Land 2025, 14(8), 1536; https://doi.org/10.3390/land14081536 - 26 Jul 2025
Viewed by 220
Abstract
Population growth and land use change often have significant environmental impacts, affecting biodiversity, water supply, agricultural production, and other resources. Future scenario models can provide a better understanding of these changes, helping planners and the public understand the consequences of choices regarding development [...] Read more.
Population growth and land use change often have significant environmental impacts, affecting biodiversity, water supply, agricultural production, and other resources. Future scenario models can provide a better understanding of these changes, helping planners and the public understand the consequences of choices regarding development density, land use, and conservation. This study presents a model that has been used to identify alternative future scenarios for Florida considering future population growth and land use. It includes two scenarios: a “Sprawl” scenario reflecting a continuation of current development patterns and a “Conservation” scenario with higher densities, redevelopment, and more land protection. The study incorporates sea level rise scenarios for both 2040 and 2070. Results show that the Sprawl scenario could lead to 3.5 million acres of new developed land and 1.8 million acres of lost agricultural land by 2070 in Florida. In contrast, the Conservation scenario for 2070 results in 1.3 million fewer acres of developed land and 5 million more acres of protected natural land, showing that it is possible to accommodate future population growth while reducing impacts to agricultural and conservation priorities in Florida. Although this is by no means a “prediction” of future Florida, it has been useful as a tool for evaluating potential future land use scenarios and is a model that may be more broadly applied by other locations and users. Full article
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19 pages, 9601 KiB  
Article
Two-Hour Sea Level Oscillations in Halifax Harbour
by Dan Kelley, Clark Richards, Ruby Yee, Alex Hay, Knut Klingbeil, Phillip MacAulay and Ruth Musgrave
J. Mar. Sci. Eng. 2025, 13(7), 1366; https://doi.org/10.3390/jmse13071366 - 17 Jul 2025
Viewed by 252
Abstract
Halifax Harbour, a major seaport in Nova Scotia that is approximately 100 km southeast of the Bay of Fundy, comprises a deep inner region called Bedford Basin, connected to the adjacent ocean by a shallow channel called The Narrows. A study of sea [...] Read more.
Halifax Harbour, a major seaport in Nova Scotia that is approximately 100 km southeast of the Bay of Fundy, comprises a deep inner region called Bedford Basin, connected to the adjacent ocean by a shallow channel called The Narrows. A study of sea level and currents reveals the presence of episodic oscillations in The Narrows, with a period of approximately 2 h. The oscillation strength varies from day to day and, to some extent, through the seasons. The median amplitude of the associated sea level variation is 18% that of the de-tided signal, rising to 32% at the 95-th percentile. Values this large may be of concern for the transit of deep-draft vessels through shallow parts of the harbour and for the clearance of tall vessels under the two bridges that span The Narrows. Another concerning issue is the matter of oscillations being superimposed on storm surges. In addition to such direct effects of sea level variation, shear associated with the oscillations may increase the turbulent mixing in the region, affecting the overall state of this estuarine system. We explore the nature of the oscillations as a first step towards the improvement of prediction schemes for sea level and currents in the region. This involves an analysis of the oscillations in the context of seiche and Helmholtz resonance theories and the use of a 2D numerical model to handle realistic bathymetric conditions and other complications that the simpler theories cannot address. We conclude that the predictions of Helmholtz resonance theory are in reasonable agreement with both the observations and the predictions of the numerical model. Full article
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23 pages, 48857 KiB  
Article
A 36-Year Assessment of Mangrove Ecosystem Dynamics in China Using Kernel-Based Vegetation Index
by Yiqing Pan, Mingju Huang, Yang Chen, Baoqi Chen, Lixia Ma, Wenhui Zhao and Dongyang Fu
Forests 2025, 16(7), 1143; https://doi.org/10.3390/f16071143 - 11 Jul 2025
Viewed by 309
Abstract
Mangrove forests serve as critical ecological barriers in coastal zones and play a vital role in global blue carbon sequestration strategies. In recent decades, China’s mangrove ecosystems have experienced complex interactions between degradation and restoration under intense coastal urbanization and systematic conservation efforts. [...] Read more.
Mangrove forests serve as critical ecological barriers in coastal zones and play a vital role in global blue carbon sequestration strategies. In recent decades, China’s mangrove ecosystems have experienced complex interactions between degradation and restoration under intense coastal urbanization and systematic conservation efforts. However, the long-term spatiotemporal patterns and driving mechanisms of mangrove ecosystem health changes remain insufficiently quantified. This study developed a multi-temporal analytical framework using Landsat imagery (1986–2021) to derive kernel normalized difference vegetation index (kNDVI) time series—an advanced phenological indicator with enhanced sensitivity to vegetation dynamics. We systematically characterized mangrove growth patterns along China’s southeastern coast through integrated Theil–Sen slope estimation, Mann–Kendall trend analysis, and Hurst exponent forecasting. A Deep Forest regression model was subsequently applied to quantify the relative contributions of environmental drivers (mean annual sea surface temperature, precipitation, air temperature, tropical cyclone frequency, and relative sea-level rise rate) and anthropogenic pressures (nighttime light index). The results showed the following: (1) a nationally significant improvement in mangrove vitality (p < 0.05), with mean annual kNDVI increasing by 0.0072/yr during 1986–2021; (2) spatially divergent trajectories, with 58.68% of mangroves exhibiting significant improvement (p < 0.05), which was 2.89 times higher than the proportion of degraded areas (15.10%); (3) Hurst persistence analysis (H = 0.896) indicating that 74.97% of the mangrove regions were likely to maintain their growth trends, while 15.07% of the coastal zones faced potential degradation risks; and (4) Deep Forest regression id the relative rate of sea-level rise (importance = 0.91) and anthropogenic (nighttime light index, importance = 0.81) as dominant drivers, surpassing climatic factors. This study provides the first national-scale, 30 m resolution assessment of mangrove growth dynamics using kNDVI, offering a scientific basis for adaptive management and blue carbon strategies in subtropical coastal ecosystems. Full article
(This article belongs to the Section Forest Inventory, Modeling and Remote Sensing)
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20 pages, 3656 KiB  
Article
Wetland Ecological Restoration and Geomorphological Evolution: A Hydrodynamic-Sediment-Vegetation Coupled Modeling Study
by Haiyang Yan, Bing Shi and Feng Gao
J. Mar. Sci. Eng. 2025, 13(7), 1326; https://doi.org/10.3390/jmse13071326 - 10 Jul 2025
Viewed by 233
Abstract
This study developed a coupled hydrodynamic-sediment-vegetation model to investigate the effects of Spartina alterniflora management and Suaeda salsa restoration on coastal wetland geomorphological evolution and vegetation distribution. Special attention is paid to the regulatory roles of tidal dynamics, sea-level rise, sediment supply, and [...] Read more.
This study developed a coupled hydrodynamic-sediment-vegetation model to investigate the effects of Spartina alterniflora management and Suaeda salsa restoration on coastal wetland geomorphological evolution and vegetation distribution. Special attention is paid to the regulatory roles of tidal dynamics, sea-level rise, sediment supply, and sediment characteristics. The study shows that the management of Spartina alterniflora significantly alters the sediment deposition patterns in salt marsh wetlands, leading to intensified local erosion and a decline in the overall stability of the wetland system; meanwhile, the geomorphology of wetlands restored with Suaeda salsa is influenced by tidal range, sediment settling velocity, and suspended sediment concentration, exhibiting different deposition and erosion patterns. Under the scenario of sea-level rise, when sedimentation rates fail to offset the rate of sea-level increase, the wetland ecosystem faces the risk of collapse. This study provides scientific evidence for the ecological restoration and management of coastal wetlands and offers theoretical support for future wetland conservation and restoration policies. Full article
(This article belongs to the Section Coastal Engineering)
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31 pages, 6565 KiB  
Article
Remotely Sensing Phytoplankton Size Structure in the Mediterranean Sea: Insights from In Situ Data and Temperature-Corrected Abundance-Based Models
by John A. Gittings, Eleni Livanou, Xuerong Sun, Robert J. W. Brewin, Stella Psarra, Manolis Mandalakis, Alexandra Peltekis, Annalisa Di Cicco, Vittorio E. Brando and Dionysios E. Raitsos
Remote Sens. 2025, 17(14), 2362; https://doi.org/10.3390/rs17142362 - 9 Jul 2025
Viewed by 355
Abstract
Since the mid-1980s, the Mediterranean Sea’s surface and deeper layers have warmed at unprecedented rates, with recent projections identifying it as one of the regions most impacted by rising global temperatures. Metrics that characterize phytoplankton abundance, phenology and size structure are widely utilized [...] Read more.
Since the mid-1980s, the Mediterranean Sea’s surface and deeper layers have warmed at unprecedented rates, with recent projections identifying it as one of the regions most impacted by rising global temperatures. Metrics that characterize phytoplankton abundance, phenology and size structure are widely utilized as ecological indicators that enable a quantitative assessment of the status of marine ecosystems in response to environmental change. Here, using an extensive, updated in situ pigment dataset collated from numerous past research campaigns across the Mediterranean Sea, we re-parameterized an abundance-based phytoplankton size class model that infers Chl-a concentration in three phytoplankton size classes: pico- (<2 μm), nano- (2–20 μm) and micro-phytoplankton (>20 μm). Following recent advancements made within this category of size class models, we also incorporated information of sea surface temperature (SST) into the model parameterization. By tying model parameters to SST, the performance of the re-parameterized model was improved based on comparisons with concurrent, independent in situ measurements. Similarly, the application of the model to remotely sensed ocean color observations revealed strong agreement between satellite-derived estimates of phytoplankton size structure and in situ observations, with a performance comparable to the current regional operational datasets on size structure. The proposed conceptual regional model, parameterized with the most extended in situ pigment dataset available to date for the area, serves as a suitable foundation for long-term (1997–present) analyses on phytoplankton size structure and ecological indicators (i.e., phenology), ultimately linking higher trophic level responses to a changing Mediterranean Sea. Full article
(This article belongs to the Section Ocean Remote Sensing)
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26 pages, 2555 KiB  
Article
A Comparative Evaluation of Harmonic Analysis and Neural Networks for Sea Level Prediction in the Northern South China Sea
by Huiling Zhang, Na Cui, Kaining Yang, Qixian Qiu, Jun Zheng and Changqing Li
Sustainability 2025, 17(13), 6081; https://doi.org/10.3390/su17136081 - 2 Jul 2025
Viewed by 373
Abstract
Long-term sea level variations in the northern South China Sea (SCS) are known to significantly impact coastal ecosystems and socio-economic activities. To improve sea level prediction accuracy, four models—harmonic analysis and three artificial neural networks (ANNs), namely genetic algorithm-optimized back propagation (GA-BP), radial [...] Read more.
Long-term sea level variations in the northern South China Sea (SCS) are known to significantly impact coastal ecosystems and socio-economic activities. To improve sea level prediction accuracy, four models—harmonic analysis and three artificial neural networks (ANNs), namely genetic algorithm-optimized back propagation (GA-BP), radial basis function (RBF), and long short-term memory (LSTM)—are developed and compared using 52 years of observational data (1960–2004). Key evaluation metrics are presented to demonstrate the models’ effectiveness: for harmonic analysis, the root mean square error (RMSE) is reported as 14.73, the mean absolute error (MAE) is 12.61, the mean bias error (MBE) is 0.0, and the coefficient of determination (R2) is 0.84; for GA-BP, the RMSE is measured as 29.1371, the MAE is 24.9411, the MBE is 5.6809, and the R2 is 0.4003; for the RBF neural network, the RMSE is calculated as 27.1433, the MAE is 22.7533, the MBE is 2.1322, and the R2 is 0.4690; for LSTM, the RMSE is determined as 23.7929, the MAE is 19.7899, the MBE is 1.3700, and the R2 is 0.5872. The key findings include the following: (1) A significant sea level rise trend at 1.4 mm/year is observed in the northern SCS. (2) Harmonic analysis is shown to outperform all ANN models in both accuracy and robustness, with sea level variations effectively characterized by four principal and six secondary tidal constituents. (3) Despite their complexity, ANN models (including LSTM) are found to fail in surpassing the predictive capability of the traditional harmonic method. These results highlight the continued effectiveness of harmonic analysis for long-term sea level forecasting, offering critical insights for coastal hazard mitigation and sustainable development planning. Full article
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26 pages, 41871 KiB  
Article
Episodic vs. Sea Level Rise Coastal Flooding Scenarios at the Urban Scale: Extreme Event Analysis and Adaptation Strategies
by Sebastian Spadotto, Saverio Fracaros, Annelore Bezzi and Giorgio Fontolan
Water 2025, 17(13), 1991; https://doi.org/10.3390/w17131991 - 2 Jul 2025
Viewed by 491
Abstract
Sea level rise (SLR) and increased urbanisation of coastal areas have exacerbated coastal flood threats, making them even more severe in important cultural sites. In this context, the role of hard coastal defences such as promenades and embankments needs to be carefully assessed. [...] Read more.
Sea level rise (SLR) and increased urbanisation of coastal areas have exacerbated coastal flood threats, making them even more severe in important cultural sites. In this context, the role of hard coastal defences such as promenades and embankments needs to be carefully assessed. Here, a thorough investigation is conducted in Grado, one of the most significant coastal and historical towns in the Friuli Venezia Giulia region of Italy. Grado is located on a barrier island of the homonymous lagoon, the northernmost of the Adriatic Sea, and is prone to flooding from both the sea and the back lagoon. The mean and maximum sea levels from the historical dataset of Venice (1950–2023) were analysed using the Gumbel-type distribution, allowing for the identification of annual extremes based on their respective return periods (RPs). Grado and Trieste sea level datasets (1991–2023) were used to calibrate the statistics of the extremes and to calculate the local component (subsidence) of relative SLR. The research examined the occurrence of annual exceedance of the minimum threshold water level of 110 cm, indicating Grado’s initial notable marine ingression. The study includes a detailed analysis of flood impacts on the urban fabric, categorised into sectors based on the promenade elevation on the lagoon side, the most vulnerable to flooding. Inundated areas were obtained using a high-resolution digital terrain model through a GIS-based technique, assessing both the magnitude and exposure of the urban environment to flood risk due to storm surges, also considering relative SLR projections for 2050 and 2100. Currently, approximately 42% of Grado’s inhabited area is inundated with a sea level threshold value of 151 cm, which occurs during surge episodes with a 30-year RP. By 2100, with an optimistic forecast (SSP1-2.6) of local SLR of around +53 cm, the same threshold will be met with a surge of ca. 100 cm, which occurs once a year. Thus, extreme levels linked with more catastrophic events with current secular RPs will be achieved with a multi-year frequency, inundating more than 60% of the urbanized area. Grado, like Venice, exemplifies trends that may impact other coastal regions and historically significant towns of national importance. As a result, the generated simulations, as well as detailed analyses of urban sectors where coastal flooding may occur, are critical for medium- to long-term urban planning aimed at adopting proper adaptation measures. Full article
(This article belongs to the Special Issue Urban Flood Frequency Analysis and Risk Assessment)
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19 pages, 6238 KiB  
Article
Overtopping over Vertical Walls with Storm Walls on Steep Foreshores
by Damjan Bujak, Nino Krvavica, Goran Lončar and Dalibor Carević
J. Mar. Sci. Eng. 2025, 13(7), 1285; https://doi.org/10.3390/jmse13071285 - 30 Jun 2025
Viewed by 227
Abstract
As sea levels rise and extreme weather events become more frequent due to climate change, coastal urban areas are increasingly vulnerable to wave overtopping and flooding. Retrofitting existing vertical seawalls with retreated storm walls represents a key adaptive strategy, especially in the Mediterranean, [...] Read more.
As sea levels rise and extreme weather events become more frequent due to climate change, coastal urban areas are increasingly vulnerable to wave overtopping and flooding. Retrofitting existing vertical seawalls with retreated storm walls represents a key adaptive strategy, especially in the Mediterranean, where steep foreshores and limited public space constrain conventional coastal defenses. This study investigates the effectiveness of storm walls in reducing wave overtopping on vertical walls with steep foreshores (1:7 to 1:10) through high-fidelity numerical simulations using the SWASH model. A comprehensive parametric study, involving 450 test cases, was conducted using Latin Hypercube Sampling to explore the influence of geometric and hydrodynamic variables on overtopping rate. Model validation against Eurotop/CLASH physical data demonstrated strong agreement (r = 0.96), confirming the reliability of SWASH for such applications. Key findings indicate that longer promenades (Gc) and reduced impulsiveness of the wave conditions reduce overtopping. A new empirical reduction factor, calibrated for integration into the Eurotop overtopping equation for plain vertical walls, is proposed based on dimensionless promenade width and water depth. The modified empirical model shows strong predictive performance (r = 0.94) against SWASH-calculated overtopping rates. This work highlights the practical value of integrating storm walls into urban seawall design and offers engineers a validated tool for enhancing coastal resilience. Future research should extend the framework to other superstructure adaptations, such as parapets or stilling basins, to further improve flood protection in the face of climate change. Full article
(This article belongs to the Special Issue Climate Change Adaptation Strategies in Coastal and Ocean Engineering)
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22 pages, 8219 KiB  
Article
Estimation of Relative Sea Level Change in Locations Without Tide Gauges Using Artificial Neural Networks
by Heeryun Kim, Young Il Park, Wansik Ko, Taehyun Yoon and Jeong-Hwan Kim
J. Mar. Sci. Eng. 2025, 13(7), 1243; https://doi.org/10.3390/jmse13071243 - 27 Jun 2025
Viewed by 302
Abstract
Sea level rise due to climate change poses an increasing threat to coastal ecosystems, infrastructure, and human settlements. However, accurately estimating sea level changes in regions without tide gauge observations remains a major challenge. While satellite altimetry provides wide spatial coverage, its accuracy [...] Read more.
Sea level rise due to climate change poses an increasing threat to coastal ecosystems, infrastructure, and human settlements. However, accurately estimating sea level changes in regions without tide gauge observations remains a major challenge. While satellite altimetry provides wide spatial coverage, its accuracy diminishes near coastlines. In contrast, tide gauges offer high precision but are spatially limited. This study aims to develop an artificial neural network-based model for estimating relative sea level changes in coastal regions where tide gauge data are unavailable. Unlike conventional forecasting approaches focused on future time series prediction, the proposed model is designed to learn spatial distribution patterns and temporal rates of sea level change from a fusion of satellite altimetry and tide gauge data. A normalization scheme is applied to reduce inconsistencies in reference levels, and Bayesian optimization is employed to fine-tune hyperparameters. A case analysis is conducted in two coastal regions in South Korea, Busan and Ansan, using data from 2018 to 2023. The model demonstrates strong agreement with observed tide gauge records, particularly in estimating temporal trends of sea level rise. This approach effectively compensates for the limitations of satellite altimetry in coastal regions and fills critical observational gaps in ungauged areas. The proposed method holds substantial promise for coastal hazard mitigation, infrastructure planning, and climate adaptation strategies. Full article
(This article belongs to the Section Ocean Engineering)
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17 pages, 3775 KiB  
Article
Suitability Evaluation of Site-Level CO2 Geo-Storage in Saline Aquifers of Ying–Qiong Basin, South China Sea
by Jin Liao, Cai Li, Qihui Yang, Aixia Sun, Guangze Song, Joaquin Couchot, Aohan Jin and Quanrong Wang
Energies 2025, 18(13), 3388; https://doi.org/10.3390/en18133388 - 27 Jun 2025
Viewed by 254
Abstract
CO2 geo-storage is a promising approach in reducing greenhouse gas emissions and controlling global temperature rise. Although numerous studies have reported that offshore saline aquifers have greater storage potential and safety, current suitability evaluation models for CO2 geo-storage primarily focus on [...] Read more.
CO2 geo-storage is a promising approach in reducing greenhouse gas emissions and controlling global temperature rise. Although numerous studies have reported that offshore saline aquifers have greater storage potential and safety, current suitability evaluation models for CO2 geo-storage primarily focus on onshore saline aquifers, and site-level evaluations for offshore CO2 geo-storage remain unreported. In this study, we propose a framework to evaluate the site-level offshore CO2 geo-storage suitability with a multi-tiered indicator system, which considers three types of factors: engineering geology, storage potential, and socio-economy. Compared to the onshore CO2 geo-storage suitability evaluation models, the proposed indicator system considers the unique conditions of offshore CO2 geo-storage, including water depth, offshore distance, and distance from drilling platforms. The Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE) methods were integrated and applied to the analysis of the Ying–Qiong Basin, South China Sea. The results indicated that the average suitability score in the Yinggehai Basin (0.762) was higher than that in the Qiongdongnan Basin (0.691). This difference was attributed to more extensive fault development in the Qiongdongnan Basin, suggesting that the Yinggehai Basin is more suitable for CO2 geo-storage. In addition, the DF-I reservoir in the Yinggehai Basin and the BD-A reservoir in the Qiongdongnan Basin were selected as the optimal CO2 geo-storage targets for the two sub-basins, with storage potentials of 1.09 × 108 t and 2.40 × 107 t, respectively. This study advances the methodology for assessing site-level potential of CO2 geo-storage in offshore saline aquifers and provides valuable insights for engineering applications and decision-making in future CO2 geo-storage projects in the Ying–Qiong Basin. Full article
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31 pages, 10755 KiB  
Article
Exposure of Greek Ports to Marine Flooding and Extreme Heat Under Climate Change: An Assessment
by Isavela N. Monioudi, Dimitris Chatzistratis, Konstantinos Moschopoulos, Adonis F. Velegrakis, Amalia Polydoropoulou, Theodoros Chalazas, Efstathios Bouhouras, Georgios Papaioannou, Ioannis Karakikes and Helen Thanopoulou
Water 2025, 17(13), 1897; https://doi.org/10.3390/w17131897 - 26 Jun 2025
Viewed by 677
Abstract
This study assesses the exposure of the 155 Greek seaports to marine flooding and extreme heat under climate change. Flood exposure was estimated through a threshold approach that compared projected mean and extreme sea levels to high-resolution port quay elevation data. It was [...] Read more.
This study assesses the exposure of the 155 Greek seaports to marine flooding and extreme heat under climate change. Flood exposure was estimated through a threshold approach that compared projected mean and extreme sea levels to high-resolution port quay elevation data. It was found that while relatively few ports will face quay inundation, the majority will experience operational disruptions due to insufficient freeboard for berthing of commercial vessels under both the mean (80%) and extreme sea (96%) levels by 2050. For selected ports, 2-D flood modelling was undertaken that showed that the used ‘static’ flood threshold approach likely underestimates flood exposure. Future heat exposure was studied through the comparison of extreme temperature and humidity projections to operational and health/safety thresholds. Port infrastructure and personnel/users will be exposed to large material, operational and health risks, whereas energy demand will rise steeply. Deadly heat days (due to mean temperature/humidity combination) will increase, particularly at island ports: 20% of Greek ports might face more than 50 such days annually by end-century. As ports are associated with large urban clusters, these findings suggest a broader health risk. Our findings suggest an urgent climate adaptation need given the strategic socio-economic importance of ports. Full article
(This article belongs to the Section Water and Climate Change)
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