Search Results (307)

Coastal erosion, exacerbated by climate change, poses a critical global threat to both the environment and human livelihoods. Acquiring accurate, high-resolution topo-bathymetric data is vital for understanding these dynamic environments, without underestimating the hydrodynamic and meteo-oceanographic conditions. However, traditional methods often present significant challenges in achieving comprehensive, high-resolution topo-bathymetric coverage efficiently in shallow coastal zones, leading to a notable ”white ribbon” data gap. This study introduces a novel, integrated methodology combining unmanned aerial vehicles (UAVs) for terrestrial surveys, unmanned surface vehicles (USVs) for bathymetry, and the Global Navigation Satellite System (GNSS) for ground control and intertidal gap-filling. Through this technologically rigorous approach, a seamless Bathymetry-Topography Digital Surface Model for the Guardamar del Segura dune system (Spain) was successfully elaborated using a DJI Mini 2 UAV, Leica Zeno FLX100 GNSS, and Apache 3 USV. The method demonstrated a substantial time reduction of at least 50–75% for comparable high-resolution coverage, efficiently completing the 86.4 ha field campaign in approximately 4 h. This integrated approach offers an accessible and highly efficient solution for generating detailed coastal elevation models crucial for coastal management and research. Full article

Extreme surface winds and wave heights of tropical cyclones (TCs)—pose serious threats to coastal community, infrastructure and environments. In recent decades, progress in numerical wave modeling has significantly enhanced the ability to reconstruct and predict wave behavior. This review offers an in-depth overview of TC-related wave modeling utilizing different computational schemes, with a special attention to WAVEWATCH III (WW3) and Simulating Waves Nearshore (SWAN). Due to the complex air–sea interactions during TCs, it is challenging to obtain accurate wind input data and optimize the parameterizations. Substantial spatial and temporal variations in water levels and current patterns occurs when coastal circulation is modulated by varying underwater topography. To explore their influence on waves, this study employs a coupled SWAN and Finite-Volume Community Ocean Model (FVCOM) modeling approach. Additionally, the interplay between wave and sea surface temperature (SST) is investigated by incorporating four key wave-induced forcing through breaking and non-breaking waves, radiation stress, and Stokes drift from WW3 into the Stony Brook Parallel Ocean Model (sbPOM). 20 TC events were analyzed to evaluate the performance of the selected parameterizations of external forcings in WW3 and SWAN. Among different nonlinear wave interaction schemes, Generalized Multiple Discrete Interaction Approximation (GMD) Discrete Interaction Approximation (DIA) and the computationally expensive Wave-Ray Tracing (WRT) A refined drag coefficient (C_d) equation, applied within an upgraded ST6 configuration, reduce significant wave height (SWH) prediction errors and the root mean square error (RMSE) for both SWAN and WW3 wave models. Surface currents and sea level variations notably altered the wave energy and wave height distributions, especially in the area with strong TC-induced oceanic current. Finally, coupling four wave-induced forcings into sbPOM enhanced SST simulation by refining heat flux estimates and promoting vertical mixing. Validation against Argo data showed that the updated sbPOM model achieved an RMSE as low as 1.39 m, with correlation coefficients nearing 0.9881. Full article

Wave deformation and sediment transport nearest the shoreside are among the main reasons for sand erosion and beach profile changes. In particular, identifying the areas of incident-wave breaking and longshore current generation parallel to the shoreline is important for understanding the morphological changes of coastal beaches. In this study, a two-phase incompressible flow model along with a sandy sloping topography was employed to investigate the wave deformation and longshore current generation areas in a circular wave basin model. The finite volume method (FVM) was implemented to discretize the governing equations in cylindrical coordinates, the volume-of-fluid method (VOF) was adopted to differentiate the air–water interfaces in the control cells, and the zonal embedded grid technique was employed for grid generation in the cylindrical computational domain. The water surface elevations and velocity profiles were measured in different wave conditions, and the measurements showed that the maximum water levels per wave were high and varied between cases, as well as between cross-sections in a single case. Additionally, the mean water levels were lower in the adjacent positions of the approximated wave-breaking zones. The wave-breaking positions varied between cross-sections in a single case, with the incident-wave height, mean water level, and wave-breaking position measurements indicating the influence of downstream flow variation in each cross-section on the sloping topography. The cross-shore velocity profiles became relatively stable over time, while the longshore velocity profiles predominantly moved in the alongshore direction, with smaller fluctuations, particularly during the same time period and in measurement positions near the wave-breaking zone. The computed velocity profiles also varied between cross-sections, and for the velocity profiles along the cross-shore and longshore directions nearest the wave-breaking areas where the downstream flow had minimal influence, it was presumed that there was longshore-current generation in the sloping topography nearest the shoreside. The computed results were compared with the experimental results and we observed similar characteristics for wave profiles in the same wave period case in both models. In the future, further investigations can be conducted using the presented circular wave basin model to investigate the oblique wave deformation and longshore current generation in different sloping and wave conditions. Full article

Flooding due to dam failures is a critical issue with significant impacts on human safety, infrastructure, and the environment. This study assessed the potential flood hazard that could be generated from breaching of the Alacranes dam in Villa Clara, Cuba. Thirteen reservoir breaching scenarios were simulated under several criteria for modeling the flood wave through the 2D Saint Venant equations using the Hydrologic Engineering Center’s River Analysis System (HEC-RAS). A sensitivity analysis was performed on Manning’s roughness coefficient, demonstrating a low variability of the model outputs for these events. The results show that, for all modeled scenarios, the terrain topography of the coastal plain expands the flood wave, reaching a maximum width of up to 105,057 km. The most critical scenario included a 350 m breach in just 0.67 h. Flood, velocity, and hazard maps were generated, identifying populated areas potentially affected by the flooding events. The reported depths, velocities, and maximum flows could pose extreme danger to infrastructure and populated areas downstream. These types of studies are crucial for both risk assessment and emergency planning in the event of a potential dam breach. Full article

Mesoscale coastal eddies are key components of ocean circulation, mediating the transport of heat, nutrients, and marine debris. The Surface Water and Ocean Topography (SWOT) mission provides high-resolution sea surface height data, offering a novel opportunity to improve the observation and characterization of these features, especially in coastal regions where conventional altimetry is limited. In this study, we investigate a mesoscale anticyclonic coastal eddy observed southwest of Mallorca Island, in the Balearic Sea, to assess the impact of SWOT-enhanced altimetry in resolving its structure and dynamics. Initial eddy identification is performed using satellite ocean color imagery, followed by a qualitative and quantitative comparison of multiple altimetric datasets, ranging from conventional nadir altimetry to wide-swath products derived from SWOT. We analyze multiple altimetric variables—Sea Level Anomaly, Absolute Dynamic Topography, Velocity Magnitude, Eddy Kinetic Energy, and Relative Vorticity—highlighting substantial differences in spatial detail and intensity. Our results show that SWOT-enhanced observations significantly improve the spatial characterization and dynamical depiction of the eddy. Furthermore, Lagrangian transport simulations reveal how altimetric resolution influences modeled transport pathways and retention patterns. These findings underline the critical role of SWOT in advancing the monitoring of coastal mesoscale processes and improving our ability to model oceanic transport mechanisms. Full article

In recent years, China has experienced growing impacts from extreme weather events, emphasizing the importance of understanding regional atmospheric moisture dynamics, particularly Precipitable Water Vapor (PWV), to support sustainable environmental and urban planning. This study utilizes ten years (2013–2022) of Global Navigation Satellite System (GNSS) observations in typical cities in eastern China and proposes a comprehensive multiscale frequency-domain analysis framework that integrates the Fourier transform, Bayesian spectral estimation, and wavelet decomposition to extract the dominant PWV periodicities. Time-series analysis reveals an overall increasing trend in PWV across most regions, with notably declining trends in Beijing, Wuhan, and southern Taiwan, primarily attributed to groundwater depletion, rapid urban expansion, and ENSO-related anomalies, respectively. Frequency-domain results indicate distinct latitudinal and coastal–inland differences in the PWV periodicities. Inland stations (Beijing, Changchun, and Wuhan) display annual signals alongside weaker semi-annual components, while coastal stations (Shanghai, Kinmen County, Hong Kong, and Taiwan) mainly exhibit annual cycles. High-latitude stations show stronger seasonal and monthly fluctuations, mid-latitude stations present moderate-scale changes, and low-latitude regions display more diverse medium- and short-term fluctuations. In the short-term frequency domain, GNSS stations in most regions demonstrate significant PWV periodic variations over 0.5 days, 1 day, or both timescales, except for Changchun, where weak diurnal patterns are attributed to local topography and reduced solar radiation. Furthermore, ERA5-derived vertical temperature profiles are incorporated to reveal the thermodynamic mechanisms driving these variations, underscoring region-specific controls on surface evaporation and atmospheric moisture capacity. These findings offer novel insights into how human-induced environmental changes modulate the behavior of atmospheric water vapor. Full article

The Ganges–Brahmaputra–Meghna (GBM) delta, characterized by complex topography and hydrological conditions, is highly susceptible to recurrent flooding, particularly in its coastal regions where tidal dynamics hinder floodwater discharge. This study integrates Synthetic Aperture Radar (SAR) imagery with machine learning (ML) techniques to assess near real-time flood inundation patterns associated with extreme weather events, including recent cyclones between 2017 to 2024 (namely, Mora, Titli, Fani, Amphan, Yaas, Sitrang, Midhili, and Remal) as well as intense monsoonal rainfall during the same period, across a large spatial scale, to support disaster risk management efforts. Three machine learning algorithms, namely, random forest (RF), support vector machine (SVM), and K-nearest neighbors (KNN), were applied to flood extent data derived from SAR imagery to enhance flood detection accuracy. Among these, the SVM algorithm demonstrated the highest classification accuracy (75%) and exhibited superior robustness in delineating flood-affected areas. The analysis reveals that both cyclone intensity and rainfall magnitude significantly influence flood extent, with the western coastal zone (e.g., Morrelganj and Kaliganj) being most consistently affected. The peak inundation extent was observed during the 2023 monsoon (10,333 sq. km), while interannual variability in rainfall intensity directly influenced the spatial extent of flood-affected zones. In parallel, eight major cyclones, including Amphan (2020) and Remal (2024), triggered substantial flooding, with the most severe inundation recorded during Cyclone Remal with an area of 9243 sq. km. Morrelganj and Chakaria were consistently identified as flood hotspots during both monsoonal and cyclonic events. Comparative analysis indicates that cyclones result in larger areas with low-level inundation (19,085 sq. km) compared to monsoons (13,829 sq. km). However, monsoon events result in a larger area impacted by frequent inundation, underscoring the critical role of rainfall intensity. These findings underscore the utility of SAR-ML integration in operational flood monitoring and highlight the urgent need for localized, event-specific flood risk management strategies to enhance flood resilience in the GBM delta. Full article

Copiapoa solaris is an endemic cactus species from the Antofagasta region, Chile, thriving in arid coastal ecosystems known as “fog oases,” where the rising marine moisture is the primary water source. This study investigates the role of microbial communities associated with the rhizosphere of C. solaris in adapting to extreme environmental conditions, particularly focusing on the acdS gene, which encodes ACC deaminase—an enzyme that reduces ethylene production under stress. This research aims to elucidate the gene’s contribution to the adaptation of C. solaris in these challenging environments. Samples were collected from three sites (El Cobre, Quebrada Botija, and Quebrada Izcuña) that differ in relative humidity, temperature, and topography. Environmental DNA was extracted, phylogenetic diversity was analyzed, and metagenomic annotation of the acdS gene was conducted. The acdS gene was detected in all samples, with the highest relative abundance at Quebrada Izcuña (0.05%), characterized by low relative humidity (<70%) and severe water stress. Phylogenetic analysis revealed conserved sequences across sites, while taxonomic and alpha diversity were similar among them. However, beta diversity indicated that Quebrada Izcuña was the least homogeneous, hosting distinct taxa potentially associated with stress mitigation. The acdS gene was detected on plasmids at El Cobre and Quebrada Izcuña, suggesting its potential mobility within the metagenome. The results of this study highlight the intricate relationships between microbial communities and the resilient cactus species C. solaris in extreme environments. The conservation and abundance of the acdS gene, particularly in low-humidity conditions, suggest its vital role in facilitating stress tolerance through microbial interactions. Understanding these dynamics is crucial for developing strategies to enhance plant resilience in arid ecosystems, with potential applications in sustainable agriculture and ecosystem management under changing climatic conditions. Full article

The Eastern Mediterranean region is experiencing accelerated climate warming, yet localized patterns remain poorly understood, particularly in areas with complex topography. This study examines long-term air temperature trends from 1992 to 2024 at two sites in Lebanon: Beirut Airport (urban–coastal) and Houch Al Oumaraa station in Zahlé (inland–valley). Using homogeneity testing, linear regression, and the Mann–Kendall trend test, we assess trends in minimum, maximum, and mean temperatures. The results show a strong and statistically significant warming trend in Beirut, with mean temperatures rising by +0.536 °C per decade and minimum temperatures showing the steepest increase (+0.575 °C/decade). In Zahlé, the warming trend is less pronounced, particularly for maximum temperatures (+0.369 °C/decade), while minimum temperatures increased by +0.528 °C/decade. Data from fixed stations and drone-based vertical profiling in Zahlé confirmed the presence of cold-air pooling and thermal inversions, which moderate air temperatures and may contribute to a subdued warming trend. The strongest inversion recorded in 2022 reached 6.7 °C between ground level and an altitude of 500 m. In contrast, the urban heat island (UHI) effect in Beirut and Zahlé appear to drive nighttime warming, particularly in summer and early autumn months. These findings highlight the roles of topography and urbanization in shaping local climate trends. Full article

The Advanced Topographic Laser Altimeter System (ATLAS) on the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) employs a photon-counting detection mode with a 532 nm laser to obtain high-precision Earth surface elevation data and offers a new remote sensing method for nearshore bathymetry. The key issues in using ATLAS ATL03 data for bathymetry are achieving automatic and accurate extraction of signal photons in different water environments. Especially for areas with sharply fluctuating topography, the interaction of various impacts, such as topographic fluctuations, sea waves, and laser pulse direction, can result in a sharp change in photon density and distribution at the seafloor, which can cause the signal photon detection at the seafloor to be misinterpreted or omitted during analysis. Therefore, an improved size and direction adaptive filtering (ISDAF) method was proposed for nearshore bathymetry using ATLAS ATL03 data. This method can accurately distinguish between the original photons located above the sea surface, on the sea surface, and the seafloor. The size and direction of the elliptical density filter kernel automatically adapt to the sharp fluctuations in topography and changes in water depth, ensuring precise extraction of signal photons from both the sea surface and the seafloor. To evaluate the precision and reliability of the ISDAF, ATLAS ATL03 data from different water environments and seafloor terrains were used to perform bathymetric experiments. Airborne LiDAR bathymetry (ALB) data were also used to validate the bathymetric accuracy and reliability. The experimental findings show that the ISDAF consistently exhibits effectiveness in detecting and retrieving signal photons, regardless of whether the seafloor terrain is stable or dynamic. After applying refraction correction, the high accuracy of bathymetry was evidenced by a strong coefficient of determination (R²) and a low root mean square error (RMSE) between the ICESat-2 bathymetry data and ALB data. This research offers a promising approach to advancing remote sensing technologies for precise nearshore bathymetric mapping, with implications for coastal monitoring, marine ecology, and resource management. Full article

Terrain conditions may significantly affect the near-ground-layer wind speed in coastal areas. In this research, wind tunnel tests and computational fluid dynamics (CFD) were performed to investigate the impact of topographic changes on the local wind field at coastal bridge sites. Considering the geographic information system (GIS) information of an offshore bridge site, a 1:1000 topographic model was constructed to conduct tests in the wind tunnel lab under different wind directions. The influences of terrain conditions on localized wind characteristics such as the wind speed and wind attack angle under different test conditions were obtained. The results show that the wind angle varied between −6° and 6° under different conditions. To more comprehensively show the radius of influence on the local terrain, a CFD simulation was conducted. To verify the results of the wind tunnel tests, the SST k-ω model was compared and selected for simulation in this research. The influence radius of localized wind characteristics was determined by CFD simulation. The results indicate that the original topography showed “reverse amplification” on the leeward side, resulting in complex wake flows. These results may provide a reference for the design of wind-resistant structures such as bridges and offshore wind turbines in coastal areas. Full article

As ecologically sensitive interfaces shaped by the interplay of land and sea, coastal zones demand close attention. Uncovering the spatiotemporal evolution of ecosystem service value (ESV) and the intricate interrelations among ecosystem service (ES) functions is imperative for the informed governance of human–land interactions and for fostering sustainable regional development. This study analyzes the spatiotemporal evolution of ESV based on the modified equivalent factor table, combining the Geo-information Tupu, Markov transfer model, and standard deviation ellipse. Additionally, we introduce an ecosystem service tradeoff degree (ESTD) to assess the tradeoffs and synergies among various ESs, and we utilize GeoDetector to elucidate the driving forces behind the spatial disparities in ESV. Our findings reveal that (1) Although the land use composite index in the Liaoning coastal economic belt (LCEB) increased, the pace of land use transformation demonstrated a trend toward stabilization over the study duration. (2) Between 2000 to2020, ESV initially declined but subsequently experienced an upward rebound, resulting in a net gain of approximately 48 billion yuan. Spatial analysis indicated continuous enlargement of the standard deviation ellipse, with its centroid consistently located within Yingkou City and a gradual directional shift toward the southwest. (3) The dominant relationship among ESs showed synergy, with notable tradeoffs between hydrological regulation and other services. (4) Topography and climate factors were the primary drivers of spatial heterogeneity of ESV in the LCEB. The research provides spatial decision support for optimizing the ecological security pattern of the coastal zone. Full article

Surface water is the primary freshwater supply for Earth. Small lakes and ponds provide important ecological and economic services to society but are often left undocumented, or their documentation is outdated, due to their small sizes and temporal dynamics. This study tested the feasibility of the new Surface Water and Ocean Topography (SWOT) mission regarding the 3D documentation of small waterbodies in a coastal area of South Carolina, USA. Via deep learning using a recent 15 cm aerial image, small waterbodies (>0.02 ha) were extracted at an average precision score of 0.81. The water surface elevation (WSE) of each waterbody was extracted using the SWOT Level-2 Water Mask Pixel Cloud (PIXC) product, with the data collected on 1 June 2023. Using a statistical noise-removal approach, the average WSE values of small waterbodies revealed a significant correlation (Pearson’s r = 0.64) with their bottom elevations. Via spatial interpolation, the water levels of small waterbodies across the study area were generally aligned with the state-reported Cone of Depression of ground water surfaces in underlying aquifers. While the WSE measurements of SWOT pixel points are noisy due to the land–water interactions in small waterbodies, this study indicates that the SWOT PIXC product could provide a valuable resource for assessing freshwater availability to assist in water-use decision-making. Full article

With the intensification of global climate change, the underground rail transit system of Guangzhou, as a major coastal city, faces severe flood risks. Through field investigations of 313 metro stations, this study identified 472 flood-related risk points, primarily involving water backflow at low-lying stations, insufficient elevation of structural components, and the threat of overbank flooding from adjacent rivers. By integrating GIS-based spatial analysis with the SCS-CN runoff model, an extreme rainfall scenario (534.98 mm) was simulated, revealing a maximum runoff depth of 484.23 mm. Based on these results, it is recommended to raise the flood protection design elevation to 582 mm and install additional waterproof barriers. Optimization strategies include establishing flood protection standards for new stations based on site topography and runoff volume, elevating station platforms or adding waterproof structures at existing stations, and upgrading drainage systems with real-time monitoring and early-warning mechanisms. This study emphasizes the necessity for Guangzhou’s metro system to integrate climate-adaptive urban planning and technological innovation to enhance flood resilience and promote sustainable urban development. Full article

This study introduces an innovative long-lead-time prediction model for typhoon-induced waves through the back-propagation neural network (BPNN) method along Taiwan’s northwest coast, a region vulnerable to severe coastal hazards due to its exposure to frequent typhoons and ongoing offshore energy development. Utilizing data from 13 typhoons (2001–2024) at the Hsinchu buoy station, the model integrates nine parameters—including significant wave height, typhoon parameters (e.g., wind speed, central pressure), and novel geometric factors like topographic elevation—to enhance forecast accuracy. The proposed WVPDUG model, incorporating forward speed, movement direction, and topography, outperforms traditional approaches, achieving over 60% improvement in RMSE and CC for lead times up to 10 h. A knowledge extraction method (KEM) further unveils the neural network’s internal dynamics, offering unprecedented insight into parameter contributions. This research addresses a critical gap in long-term wave forecasting under complex topographic influences, providing a robust tool for early warning systems and coastal disaster mitigation in typhoon-prone regions. Full article