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Nearshore water-level prediction has a substantial impact on the daily lives of coastal residents, fishing operations, and disaster prevention and mitigation. Compared to the limitations and high costs of traditional empirical forecasts and numerical models for nearshore water-level prediction, data-driven artificial intelligence methods can more efficiently predict water levels. Attention mechanisms have recently shown great potential in natural language processing and video prediction. Convolutional long short-term memory (ConvLSTM) combines the advantages of convolutional neural networks (CNN) and long short-term Memory (LSTM), enabling more effective data feature extraction. Therefore, this study proposes a ConvLSTM nearshore water level prediction model that incorporates an attention mechanism. The ConvLSTM model extracts multiscale information from historical water levels, and the attention mechanism enhances the importance of key features, thereby improving the prediction accuracy and timeliness. The model structure was determined through experiments and relevant previous studies using five years of water level data from the Zhuhai Tide Station and the surrounding wind speed and rainfall data for training and evaluation. The results indicate that this model outperforms the four other baseline models of PCCs, RMSE, and MAE, effectively predicting future water levels at nearshore stations up to 48 h in advance. Compared to the ConvLSTM model, the model with the attention mechanism showed an average improvement of approximately 10% on the test set, with a greater error reduction in short-term forecasts than that in long-term forecasts. During Typhoon Higos, the model reduced the MAE of the best-performing baseline model by approximately 3.2 and 2.4 cm for the 6- and 24-hour forecasts, respectively, decreasing forecast errors by approximately 18% and 11%, effectively enhancing the ability of the model to forecast storm surges. This method provides a new approach for forecasting nearshore tides and storm surges. [ABSTRACT FROM AUTHOR]

The frequency of extreme hydrologic events such as floods, storm surges, droughts, heat waves, extreme precipitation, and other similar occurrences has been increasing in Bangladesh due to the impact of climate change. Therefore, the assessment of changes in future climates is essential for climate-induced risk management in the country to safeguard natural resources and human lives. The main purpose of the current study is to assess the trend of maximum temperature (Tmax), minimum temperature (Tmin), and precipitation for the north-west region of Bangladesh in seasonal and annual scales for three future periods, including 2025–2050, 2051–2080, and 2081–2100, respectively. In order to achieve this goal, a large-scale atmospheric dataset obtained from the well-known general circulation model (GCM), CanESM2, is downscaled to finer scales at the local level using the widely used statistical downscaling model (SDSM). The downscaling of local climate variables is carried out using daily observed climate data under three representative concentration pathways (RCP) scenarios, including RCP2.6, RCP4.5, and RCP8.5, respectively. Correlation matrices with p-values have been utilized to select the most suitable predictors from NCEP/NCAR reanalysis data. Both the calibration (0.87 < R2 < 0.98, 0.87 < EV < 0.99, 19.24 > SE < 0.12) and validation findings demonstrate that the model performs satisfactorily. The bias correction approach is also adopted to achieve more consistent results. Seasonally, the mean seasonal temperature and precipitation are projected to rise in all seasons (except winter for precipitation). Annually, Tmax and Tmin have grown by 0.49 °C and 1.36 °C, respectively, whereas precipitation has increased by 49% up to the next century considering the RCP8.5 scenario (worst case). Overall, the outcome of the current study is expected to be supportive to policymakers and water managers in planning climate-resilient agricultural and infrastructure development activities for managing climate-induced disastrous events in the north-west region of Bangladesh. [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) are highly destructive weather systems, typically accompanied by heavy rainfall, extreme winds and storm surges, significantly impacting residents’ safety and property, and economic development. Accurate and efficient TC monitoring methods are of great importance for disaster prevention and mitigation, and emergency response. In recent years, multi-source remote sensing has provided important data sources for TC monitoring. In addition, the rapid development of artificial intelligence, particularly deep learning, has demonstrated tremendous potential in TC monitoring due to its powerful feature learning and representation capabilities. Therefore, this paper provides a comprehensive review of monitoring TCs using multi-source data and deep learning. This review first presents an overview of TC monitoring tasks, including TC centre identification, intensity estimation, and wind radii estimation. Subsequently, the widely used multi-source data types and a list of publicly available datasets are provided. Towards typical TC monitoring tasks, this review demonstrates how to transform these tasks into fundamental tasks. The corresponding network architectures, specific models, and multi-source data involved, and detailed implementations are summarised. In addition, this review provides insights into challenges and future directions, focusing on aspects including multi-task learning, multi-modal data fusion, incomplete data modalities, lightweight models, and physics-informed models for TC monitoring. [ABSTRACT FROM AUTHOR]

The across‐shore transport of meroplanktonic larvae is predominantly driven by coastal physical processes, resulting in episodic recruitment of benthic species. Historically, due to the sampling challenges associated with resolving these advective mechanisms across the continental shelf, relevant components of larval transport have been difficult to isolate and understand. We use three‐dimensional temperature and velocity data from an array of 29 moorings to identify fundamental physical processes that could have generated successful across‐shore transport and settlement of meroplankton. The dense spatial and temporal sampling from this array allows us to use Lagrangian particle tracking to estimate the influences of wind conditions and the internal tide on the across‐shore transport of planktonic larvae. Settlement was found to be episodic at all depths studied. Above mid‐water, modeled larvae were successfully transported onshore by the internal tide during wind relaxations. Surprisingly, abundant pulses of shallow‐water larvae were supplied to the coast on occasions when strong, upwelling‐favorable winds (> 4 m s−1) drove offshore‐flowing surface waters, revealing a complex, potentially topographically influenced flow. These intense upwelling‐favorable winds also contributed to subsurface onshore flows that created large pulses of larval settlement in deeper waters (> 20 m). Our analyses from this highly resolved data set provide novel insights into the interactions of physical drivers in creating episodic pulses of coastal larval recruitment. [ABSTRACT FROM AUTHOR]

Most knowledge about the Cretaceous–Paleogene strata in the Tarim Basin is mainly inferred from the outcrops at the basin's margin, but first time in the basin. The formation mechanism of the Paleocene basal conglomerate was determined using geochemical isotopes of the breccia from Well PBX1 in the southwestern Tarim Basin. The results showed that the global K/Pg (i.e., Cretaceous/Paleogene) clay layer boundary was located in the middle of the Paleocene basal conglomerate at the depth of 7 066.75 m in Well PBX1. In the Late Cretaceous, associated with volcanic activities and earthquakes, the caldera in the Well PBX1 Block formed an annular depression with large elevation differences in response to the Pamir Block collision. As a result, the collapsed breccia with storm tide genesis deposited at the periphery and inside of the depression, characterized by syn-sedimentary deformation. During the Paleocene, multiple sets of interbedded carbonate and collapsed breccia deposited in response to multi-phased transient transgression-regression cycles. The transportation of breccia exhibited near-source accumulation/extremely close or in-situ rapid accumulation. The studied region is located in the eastern end of the Tethys Sea, the Late Cretaceous–Early Paleocene breccia is of great significance for reconstructing the paleogeography of the Tarim basin in Tethys. [ABSTRACT FROM AUTHOR]

In recent decades, the scientific community has increasingly focused on extreme events linked to climate change, which are leading to more intense and frequent natural disasters. The Mediterranean can be considered a hotspot where the effects of these changes are expected to be more intense compared to other regions of the planet. Italy is not exempt; in fact, with its extensive shoreline, it is particularly vulnerable, especially to high sea levels and coastal erosions. In this framework, from late October to early November 2023, six storm surges occurred in the Gulf of Trieste (NE Italy). These events, characterized by winds from 190°N to 220°N and the significant wave height, which reached up to 1.81 m nearshore—an uncommon meteorological condition in the northern Adriatic Sea—caused the occurrence of eight coastal sinkholes and substantial damages to man-made structures. Thanks to Unmanned Aerial Vehicles (UAVs) and their derived products (high-resolution orthomosaics, Digital Elevation Models—DEMs, and point clouds), it was possible to study these features over time, enabling long-term coastal dynamics monitoring, which can be crucial for timely and effective response and restoration efforts. [ABSTRACT FROM AUTHOR]

Hurricane incidents have become increasingly frequent along the coastal United States and have had a negative impact on the mangrove forests and their ecosystem services across the southeastern region. Mangroves play a key role in providing coastal protection during hurricanes by attenuating storm surges and reducing erosion. However, their resilience is being increasingly compromised due to climate change through sea level rises and the greater intensity of storms. This article examines the role of remote sensing tools in studying the impacts of hurricanes on mangrove forests in the coastal United States. Our results show that various remote sensing tools including satellite imagery, Light detection and ranging (LiDAR) and unmanned aerial vehicles (UAVs) have been used to detect mangrove damage, monitor their recovery and analyze their 3D structural changes. Landsat 8 OLI (14%) has been particularly useful in long-term assessments, followed by Landsat 5 TM (9%) and NASA G-LiHT LiDAR (8%). Random forest (24%) and linear regression (24%) models were the most common modeling techniques, with the former being the most frequently used method for classifying satellite images. Some studies have shown significant mangrove canopy loss after major hurricanes, and damage was seen to vary spatially based on factors such as proximity to oceans, elevation and canopy structure, with taller mangroves typically experiencing greater damage. Recovery rates after hurricane-induced damage also vary, as some areas were seen to show rapid regrowth within months while others remained impacted after many years. The current challenges include capturing fine-scale changes owing to the dearth of remote sensing data with high temporal and spatial resolution. This review provides insights into the current remote sensing applications used in hurricane-prone mangrove habitats and is intended to guide future research directions, inform coastal management strategies and support conservation efforts. [ABSTRACT FROM AUTHOR]

In this study, the application of microbially induced carbonate precipitation for coastline protection was investigated. Untreated, moderately, and heavily cemented near-prototype dunes were fabricated in the largest wave flume in North America at the O.H. Hinsdale Wave Research Laboratory at Oregon State University. Dunes were stabilized with two treatment application systems known as surface spraying and prefabricated vertical drains. Untreated and stabilized dunes were subjected to waves similar to Hurricane Sandy conditions recorded in New Jersey in 2012. Laboratory tests and in situ assessments were performed to quantify the improvement of mechanical properties of soil and investigate the performance of dunes subjected to extreme wave actions. Post-treatment cone penetration test sounding results indicated a significant cone tip resistance that was controlled by carbonate content and cementation distribution pattern. Similarly, monitoring the changes in the morphology of dunes demonstrated that the shear strength, cementation level, and cementation distribution pattern control the equilibrium beach profile, erosion rate, and mass loss. [ABSTRACT FROM AUTHOR]

In this study, the storm surge processes and characteristics of Tide-Surge Interactions (TSI) induced by the sequential tropical cyclones (TCs) BARIJAT and MANGKHUT (2018) in the Northern South China Sea (NSCS) are investigated using the numerical model. By comparing the impacts of the two TCs, we find that storm surges are significantly influenced by multiple factors. Notably, bays situated on the western side of the cyclone's landfall point exhibit a double peak pattern in storm surge. In addition, TSI exhibits a pronounced impact across bays affected by the two TCs, with amplitude fluctuations ranging from -0.3 to 0.3 meters and contributing approximately -5% to -20% to the peaks of storm surge. Comparative analysis of TSI variations reveals that tides act as the primary determinant, significantly influencing both the magnitude and period of TSI. Dynamic analysis further highlights that variations in TSI are dominated by barotropic pressure gradient and bottom friction stress. Moreover, TSI affects the frequency of storm surges, introducing high-frequency tidal signals to storm surges and reducing the frequency of storm surges. [ABSTRACT FROM AUTHOR]

In the Casablanca-Mohammedia corridor (Morocco), flooding episodes have happened frequently over the past 20 years, damaging coastal settlements through overtopping and overflowing processes. In this context, a realistic assessment of the flood risk on this coastline is required. For this, the marine water level variations were computed by combining the involved variables (astronomical tide, storm surge, wave run-up, and sea level rise) during energetic events. They were compared with the seafront altitude to delineate the maximum spatial extent of flooded areas for the current and future (2100) time horizons. These variables were obtained through numerical and empirical modeling using topobathymetry, tide gauge, wind, and reanalysis data for wave and atmospheric pressure. Statistical methods were used to determine trends and distributions, including linear regression and the GEV model. Our approach was validated by comparing the estimated results of the total water level with the observations made in situ during previous events. Results show that flooding occurs mainly at high tides. The run-up is the largest contributor to total water level during energetic events (45–60% in structure defense areas against ~ 35% in natural areas). Currently, the floodable area for all of Casablanca-Mohammedia's coastline (109 km2) is estimated to be ~ 23.5 km2, of which ~ 13.9 km2 is urban. This area would grow by 10.87% and 20.9% by 2100, respectively. The most vulnerable zones are Mohammedia, Ain Sbâa, and Merzeg quarters, as well as Tamaris beaches. The touristic quarters of Ain Diab and the promenades on either side of the Hassan II Mosque are also vulnerable and can be dangerous for pedestrians. This study is crowned by the proposal of numerous necessary protection and adaptation measures, considering the specificities of the sections characterizing this coastline. [ABSTRACT FROM AUTHOR]

Coastal lagoons are important wetland sites for migratory species and the local flora and fauna population. The Stagnone Lagoon is a coastal lagoon located on the west edge of Sicily between the towns of Marsala and Trapani. The area is characterized by salt-harvesting plants and several archaeological sites and is affected by microtidal excursion. Two mouths allow exchange with the open sea: one smaller and shallower in the north and one larger and deeper in the south. This study aims to understand the lagoon's hydrodynamics, in terms of circulation and involved forces. The circulation process appears to be dominated mainly by tide excursions and wind forces. Wind velocity, water levels, and water velocity were recorded during different field campaigns in order to obtain a benchmark value. The hydrodynamic circulation has been studied with a 2DH (two-dimensional in the horizontal plane) unstructured mesh model, calibrated with data collected during the 2006 field campaign and validated with the data of the 2007 campaign. Rapid changes in averaged velocity have been found both in Vx and Vy components, showing the strong dependence on seiches. This study tries to identify the main factor that domains the evolution of the water circulation. Sensitivity analyses were conducted to estimate the correct energy transfer between the forcing factors and dissipating ones. A Gauckler–Strickler roughness coefficient between 20 and 25 m1/3/s is found to be the most representative in the lagoon. To enhance the knowledge of this peculiar lagoon, the MIKE 21 model has been used, reproducing all the external factors involved in the circulation process. Nash–Sutcliffe coefficient of efficiency (NSE) values up to 0.92 and 0.79 are reached with a Gauckler–Strickler coefficient equal to 20 m1/3/s related to water depth and the Vy velocity component. The Vx velocity component NSE has never been satisfying, showing the limits of the 2D approach in reproducing the currents induced by local morphological peculiarities. Comparing the NSE value of water depth, there is a loss of up to 70% in model predictivity capability between the southern and the northern lagoon areas. This study aims to support the local decision-makers to improve the management of the lagoon itself. [ABSTRACT FROM AUTHOR]

The article in the journal "Oceanography" discusses a project-based learning activity that focuses on developing engineering skills through the creation of an Arduino-based submersible temperature and depth sensor. The project aims to teach students about sensors, circuits, hardware, and software design, as well as data collection and analysis. Students build, calibrate, and test the instrument, gaining hands-on experience in marine science engineering. The project is designed for undergraduates and graduate students with minimal engineering experience, allowing for customization based on students' interests and expertise levels. The course emphasizes problem-solving skills and critical thinking, preparing students for future research and career opportunities in marine science and engineering. [Extracted from the article]

Simple Summary: In China, in addition to green tides and red tides, outbreaks of Cnidaria (jellyfish organisms), Annelida (Urechis unicinctus Drasche, 1880), Mollusca (Philine kinglipini S. Tchang, 1934), Arthropoda (Acetes chinensis Hansen, 1919), and Echinodermata (Asteroidea organisms (commonly known as starfish), Ophiuroidea organisms, and Acaudina molpadioides Semper, 1867) not only damage marine resources, tourism, coastal industries, and navigation but also profoundly impact ecosystems near nuclear plants, beaches, and infrastructures, endangering human lives. This article suggests measures to mitigate future disasters, emphasizing enhanced monitoring and integration into China's marine ecological disaster monitoring system. This review is conducive to enhancing researchers' comprehension and reflection regarding biological disasters in marine ecosystems. Owing to global climate change or the ever-more frequent human activities in the offshore areas, it is highly probable that an imbalance in the offshore ecosystem has been induced. However, the importance of maintaining and protecting marine ecosystems' balance cannot be overstated. In recent years, various marine disasters have occurred frequently, such as harmful algal blooms (green tides and red tides), storm surge disasters, wave disasters, sea ice disasters, and tsunami disasters. Additionally, overpopulation of certain marine organisms (particularly marine faunas) has led to marine disasters, threatening both marine ecosystems and human safety. The marine ecological disaster monitoring system in China primarily focuses on monitoring and controlling the outbreak of green tides (mainly caused by outbreaks of some Ulva species) and red tides (mainly caused by outbreaks of some diatom and dinoflagellate species). Currently, there are outbreaks of Cnidaria (Hydrozoa and Scyphozoa organisms; outbreak species are frequently referred to as jellyfish), Annelida (Urechis unicinctus Drasche, 1880), Mollusca (Philine kinglipini S. Tchang, 1934), Arthropoda (Acetes chinensis Hansen, 1919), and Echinodermata (Asteroidea organisms, Ophiuroidea organisms, and Acaudina molpadioides Semper, 1867) in China. They not only cause significant damage to marine fisheries, tourism, coastal industries, and ship navigation but also have profound impacts on marine ecosystems, especially near nuclear power plants, sea bathing beaches, and infrastructures, posing threats to human lives. Therefore, this review provides a detailed introduction to the marine organisms (especially marine fauna species) causing marine biological disasters in China, the current outbreak situations, and the biological backgrounds of these outbreaks. This review also provides an analysis of the causes of these outbreaks. Furthermore, it presents future prospects for marine biological disasters, proposing corresponding measures and advocating for enhanced resource utilization and fundamental research. It is recommended that future efforts focus on improving the monitoring of marine biological disasters and integrating them into the marine ecological disaster monitoring system. The aim of this review is to offer reference information and constructive suggestions for enhancing future monitoring, early warning systems, and prevention efforts related to marine ecological disasters in support of the healthy development and stable operation of marine ecosystems. [ABSTRACT FROM AUTHOR]

Previous research has shown that people use a benchmark hurricane as part of their preparation and evacuation decision-making process. While hurricanes are a common occurrence along the Gulf Coast, research on personal memories of past storms is lacking. Particularly, how well do people remember the track and geophysical hazards (wind speed, storm surge, and total rainfall) of past storms? The accurate or inaccurate recollection and perception of previous storm details can influence personal responses to future storms, such as the decision to evacuate or take other life-saving actions. Survey responses of residents in Alabama and Mississippi were studied to determine if people were accurately able to recall a notable storm's name when seeing an image of the storm's track. Those who were able to identify the storm by its track were also asked if they could remember the storm's maximum reported rainfall, maximum sustained winds, and storm surge at landfall. Results showed that there were statistically significant differences between the levels of accurate recall for different storms, with Hurricanes Katrina and Michael having the most correct responses. Regardless of the storm, most people struggled to remember geophysical hazards. The results of this study are important as they can inform broadcast meteorologists and emergency managers on forecast elements of the storm to better emphasize in future communication in comparison to the actual values from historical benchmark storms. [ABSTRACT FROM AUTHOR]

The analysis of extreme rainfall parameters, particularly rainfall intensities, plays a serious role in the protection, productivity, and resilience of hydrological systems against storms and floods. This is especially important in arid and semi-arid regions like Pakistan, where inclusive long-term rainfall data with short aggregation periods is limited. Addressing this need, the current study develops intensity-duration-frequency (IDF) curves using rainfall data from four cities across different elevations and geographical regions within Pakistan. By statistically fitting the Gumbel distribution to observed data at different durations (1 h, 6 h, 12 h, and 24 h), the study originates rainfall intensities for distinct return periods. The analysis discloses an average annual rainfall of 25.42 mm, 9.62 mm, 9.25 mm, and 28.02 mm, with standard deviations of 6.45 mm, 9.67 mm, 7.50 mm, and 11.96 mm for Lahore, Karachi, Quetta, and Peshawar, respectively, based on data from 2001 to 2022. Notably, the assessed rainfall intensities for various return periods (2, 5, 10, and 25 years) are higher in mountainous regions compared to interior and coastal regions. Additionally, the study develops empirical parameters for the IDF formula for each city through a linear regression technique, allowing the prediction of rainfall intensities based on desired return periods. Finally, contour maps for all the parameters were created, which can be used to determine IDF relationships for un-gauged locations. These outcomes underscore the vulnerability of mountainous regions to extreme rainfall events, focus the necessity for updated infrastructure and robust flood management strategies. The derived IDF curves and empirical parameters offer valuable tools for policymakers and urban planners to plan effective interventions aimed at mitigating the adverse impacts of extreme rainfall in Pakistan. [ABSTRACT FROM AUTHOR]

Coastal ecosystems provide critical storm and flood protection but are rapidly degrading worldwide, making their restoration urgent. We evaluated whether successional facilitation, where pioneers facilitate climax species, could be leveraged to accelerate coastal dune revegetation. A survey spanning 270 km of Southeast U.S. coastline revealed that Panicum amarum (bitter panicum) supported higher plant richness than Uniola paniculata (sea oats) and that sea oat cover was 230% greater on mature dunes than disturbed dunes, suggesting bitter panicum functions as a pioneer and sea oats as a climax species. A reciprocal transplant experiment confirmed this interpretation: bitter panicum stem production and height fell by 37% and >20 cm, respectively, when planted proximate to sea oats versus in isolation, whereas sea oats produced 38% more and >12 cm taller stems when planted proximate to bitter panicum versus in isolation. A second experiment evaluating the density‐dependence of this facilitative interaction revealed that sea oats transplanted into low densities of bitter panicum grew >15% taller than isolated and high‐density treatments. However, within 7 months, wave inundation eliminated over 60% of propagules in both experiments. To explore foredune inundation frequency and its implications for dune revegetation, we applied empirical wave runup models at 101 locations throughout Volusia County, Florida. While disturbance frequency varied seasonally and annually, sites with low dune crests and steep beach slopes experienced frequent inundation (>50 events/year). Given the interactions between geomorphology and vegetation success, we present a decision matrix to guide managers in determining optimal revegetation methods tailored to project goals and site conditions. [ABSTRACT FROM AUTHOR]

Stalter, R. and Lonard, R.I., 2024. Biological flora of sand dunes on the northwest Pacific coastline of North America: Ammophila arenaria (L.) Link and Ammophila breviligulata Fernald. Journal of Coastal Research, 40(5), 994–1000. Charlotte (North Carolina), ISSN 0749-0208. Ammophila arenaria, native to European coastal dunes, was initially introduced on the Pacific coast of North America in 1868, while A. breviligulata was introduced to temperate regions along the Pacific coast in 1935. Both rhizomatous taxa are often dominant on coastal foredunes. Ammophila arenaria has short, thick rhizomes, while A. breviligulata has a spreading rhizome system. Both species have been introduced for sand stabilization and shoreline protection. The primary method of reproduction for both taxa is fragmentation of rhizomes. Ammophila breviligulata aggressively competes with A. arenaria and is now dominant over A. arenaria at many sites. The introduction of A. arenaria and A. breviligulata has contributed to dense cover on foredunes and a concomitant decline of native plants and animals, especially those dependent on open sand habitats. Ammophila breviligulata successfully competes with A. arenaria, which has reduced dune heights, increasing the number of areas vulnerable to storm surges and dune erosion. [ABSTRACT FROM AUTHOR]

Wang, P.; Royer, E.L.; Jackson, K., and Gutierrez, S., 2024. Impacts of Hurricane Ian along the low-lying southwest Florida coast (USA) in 2022: Lessons learned. Journal of Coastal Research, 40(5), 827–851. Charlotte (North Carolina), ISSN 0749-0208. Hurricane Ian made landfall in the low-lying, densely populated, and developed southwestern Florida coast on 28 September 2022 as a large and slow-moving category 4 hurricane. Various U.S. federal and state agencies collected a large and comprehensive data set, including pre- and poststorm airborne LIDAR topography, in situ water level and wave measurements at numerous locations before, during, and after the storm, and poststorm high-water marks over a large area. This study reports results from a series of poststorm field investigations including ground observations of beach-dune erosion and deposition, catastrophic damage to various infrastructure, and widespread distribution of non-biodegradable materials washed into the estuary and numerous mangrove islands. Hurricane Ian induced large-scale inundation in low-lying southwest Florida, submerging all the barrier islands bordering Charlotte Harbor estuary, all the islands within the estuary, and up to 5 km into the mainland. Dense tree-type vegetation limited the landward penetration of beach-dune erosion and overwash deposition along the barrier islands. Net sand-volume loss from the beach-dune system ranged 10–25 m3/m and was controlled by the deep submergence of the system during the peak of the storm. The extremely high storm surge of up to 5.2 m above mean sea level generated by Hurricane Ian caused severe damage to the built environments over a large area. High storm waves superimposed on the elevated water level, reaching 1.2 m at the seaward edge of vegetated dunes, contributed to the destruction along the barrier islands. Hurricane Ian distributed a tremendous amount of non-biodegradable artificial debris over a large area and into sensitive natural environments, including numerous mangrove islands, barrier-island interior wetlands, and the estuary waterbody. Measures to prevent materials such as single-use plastics, insulation fibers, and household appliances from being washed into sensitive environments should be a significant part of prestorm preparation. [ABSTRACT FROM AUTHOR]

Hucks, K.D. and Leberg, P.L., 2024. Evaluation of maximum entropy models for assessing coastal bird distributions under restoration scenarios. Journal of Coastal Research, 40(5), 901–918. Charlotte (North Carolina), ISSN 0749-0208. Coastal systems are facing many challenges, including climate change, sea-level rise, storm surge, and erosion, all of which contribute to land loss. In Louisiana, this has led to the development of a coastal master plan supported by habitat suitability index (HSI) models to predict wildlife responses under various management scenarios. However, HSI models were not originally intended for this purpose, and their functionality at large spatial scales is unclear. The goal was to use maximum entropy modeling to predict how various bird distributions might change with coastal restoration and management and to compare those results to HSI model predictions. Using field surveys and sources of bird locations, as well as environmental projections from the Comprehensive Master Plan habitat and hydrology models, the authors predicted the probability of occurrence for each target species for current conditions and projected the distributions into the future at 25 and 50 years using sea-level rise and coastal change scenarios. Predictive models for each species under current conditions show good agreement with field observations. Future models generally show reductions in areas of potentially high habitat use, with a few notable exceptions in the Brown Pelican habitat. Both MaxEnt and HSI modeling approaches had advantages and disadvantages; neither was clearly superior for predicting wildlife habitat. Increasing the resolution and quality of environmental data used in coastal monitoring efforts, as well as additional field validation of model predictions, will improve estimates of suitable habitat, habitat use, and restoration outcomes for wildlife. [ABSTRACT FROM AUTHOR]

Cold surges (CSs) often occur in the mid-latitude regions of the Northern Hemisphere and have enormous effects on socioeconomic development. We report that the occurrences of CSs and persistent CSs (PCSs) have rebounded since the 1990s, but the trends related to the frequencies of strong CSs (SCSs) and extreme CSs (ECSs) changed from increasing to decreasing after 2000. The highest-ranked model ensemble approach was used to project the occurrences of various CSs under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios. The frequencies of the total CSs show overall decreasing trends. However, under the SSP1-2.6 scenario, slight increasing trends are noted for SCSs and ECSs in China. Atmospheric circulations that are characterized by an anomalous anticyclonic circulation with a significantly positive 500-hPa geopotential height (Z500) anomaly at high latitudes along with significant negative anomalies in China were favorable for cold air intrusions into China. In addition, the frequencies of all CS types under the SPP5-8.5 scenario greatly decreased in the long term (2071–2100), a finding which is thought to be related to negative SST anomalies in the central and western North Pacific, differences in sea level pressure (SLP) between high- and mid-latitude regions, and a weaker East Asian trough. In terms of ECSs, the decreasing trends observed during the historical period were maintained until 2024 under the SSP1-2.6 scenario. Compared to the SSP1-2.6 scenario, the Z500 pattern showed a trend of strengthened ridges over the Ural region and northern East Asia and weakened troughs over Siberia (60°–90°E) under the SSP2-4.5 and SSP5-8.5 scenarios, contributing to the shift to increasing trends of ECSs after 2014. [ABSTRACT FROM AUTHOR]

Compound flooding, the concurrence of multiple flooding mechanisms such as storm surge, heavy rainfall, and riverine flooding, poses a significant threat to coastal communities. To mitigate the impacts of compound flooding, forecasts must represent the variability of flooding drivers over a wide range of spatial scales while remaining timely. One approach to develop these forecasts is through subgrid corrections, which utilize information at smaller scales to "correct" water levels and current velocities averaged over the model scale. Recent studies have shown that subgrid models can improve both accuracy and efficiency; however, existing models are not able to account for the dynamic interactions of hydrologic and hydrodynamic drivers and their contributions to flooding along the smallest flow pathways when using a coarse resolution. Here, we have developed a solver called CoaSToRM (Coastal Subgrid Topography Research Model) with subgrid corrections to compute compound flooding in coastal systems resulting from fluvial, pluvial, tidal, and wind-driven processes. A key contribution is the model's ability to enforce all flood drivers and use the subgrid corrections to improve the accuracy of the coarse-resolution simulation. The model is validated for Hurricane Eta 2020 in Tampa Bay, showing improved prediction accuracy with subgrid corrections at 42 locations. Subgrid models with coarse resolutions (R2 = 0.70, 0.73, 0.77 for 3-, 1.5-, 0.75-km grids) outperform standard counterparts (R2 = 0.03, 0.14, 0.26). A 3-km subgrid simulation runs roughly 50 times faster than a 0.75-km subgrid simulation, with similar accuracy. [ABSTRACT FROM AUTHOR]

An understanding of turbulence and mixing is essential to the knowledge of turbulent dissipation, sediment transport, advection of nutrient-rich and organic effluents, and stormwater runoff in prototype water systems, as well as in laboratory channels used for physical modeling of geometrically-scaled full-scale water bodies and for validation of computational models. The acoustic Doppler velocimeter (ADV) system is a robust instrument well suited for such turbulence measurements in open channel flows. The application of acoustic Doppler velocimeter to transient free-surface flows is reviewed in this paper. Based upon field applications and laboratory experiments, the intricacy and inherent difficulties are discussed. The experience and expertise in transient flows highlighted the importance of the signal processing and precise synchronization. Finally, we stress a major benefit of the acoustic Doppler velocimetry for its capability to be used in both field and laboratory, in turn providing some level of confidence in the comparison between full-scale and laboratory data. [ABSTRACT FROM AUTHOR]

Salinization threatens freshwater resources and freshwater‐dependent wetlands in coastal areas worldwide. Many research efforts focus on gradual or chronic salinization, but the phenomenon is also episodic in nature, particularly in small streams and artificial waterways. In surface waters, salinization events may coincide with storms, droughts, wind tides, and other episodic events. A lack of standardized quantitative methods and metrics for describing and discussing episodic salinization hinders cross‐disciplinary efforts by scientists and others to analyze, discuss, and make recommendations concerning these events. Here, we present a set of metrics that use statistics which describe flow characteristics in rivers and streams as a template for empirically describing and characterizing salinization events. We developed a set of metrics to quantify the duration, magnitude, and other characteristics of episodic salinization, and we apply the metrics to extensive time‐series data from a field site in coastal North Carolina. We then demonstrate the utility of these metrics by coupling them with ancillary data to perform an unsupervised classification that groups individual salinization events by their primary meteorological driver. We provide simple and flexible code needed to compute metrics in any environment experiencing salinization events in hopes that it will facilitate more standardized approaches to the quantification and study of widespread freshwater salinization. [ABSTRACT FROM AUTHOR]

Salt marshes act as natural barriers that reduce wave energy during storm events and help protect coastal communities located in low-lying areas. This ecosystem can be an important asset for climate adaptation due to its particular capability of vertically accrete to adjust to long-term changes in water levels. Therefore, understanding marsh protection benefits thresholds in the face of sea-level rise (SLR) is important for planning future climate adaptation. In this context, the main goal of this manuscript is to examine how the storm protection benefits provided by salt marshes might evolve under SLR projections with different probability levels and emission pathways. In this study, a modeling framework that employs marsh migration predictions from the Sea Level Affecting Marshes Model (SLAMM) as parameterization into a hydrodynamic and wave model (ADCIRC + SWAN) was utilized to explicitly represent wave attenuation by vegetation under storm surge conditions. SLAMM predictions indicate that the SLR scenario, a combination of probability level and emission pathways, plays a substantial role in determining future marsh migration or marsh area loss. For example, results based on the 50% probability, stabilized emissions scenario show an increase of 45% in the marsh area on Maryland's Lower Eastern Shore by 2100, whereas Dorchester County alone could experience a 75% reduction in total salt marsh areas by 2100 under the 1% probability, growing emissions scenario. ADCIRC + SWAN results using SLAMM land cover and elevation outputs indicate that distinct temporal thresholds emerge where marsh extent sharply decreases and wave heights increase, especially after 2050, and exacerbates further after 2080. These findings can be utilized for guiding environmental policies and to aid informed decisions and actions in response to SLR-driven environmental changes. [ABSTRACT FROM AUTHOR]

The performance of an intermediate-scale modular, permeable, floating breakwater comprised of an array of vertical screens is optimized and tested. A distinctive attribute of this breakwater design is its adaptive capacity to fluctuating water levels owing to its floating configuration, thereby preserving its efficacy during high tide and storm tide scenarios—an advancement over conventional bottom-mounted structures. The initial validation of the concept was tested in a laboratory wave basin in regular waves, which demonstrated promising results for three porous panels. Next, the breakwater's design parameters were optimized using a finite difference computational fluid dynamics software, (FLOW-3D version 2023R2), considering porosity, spacing, and panel count. A scaled prototype, representative of a 1:2 ratio was then deployed during the summer of 2022 along the coast of Castine, ME, within a mesotidal, semi-sheltered system characterized by tidal currents and waves. Notably, the breakwater succeeded in attenuating half of the wave energy for periods shorter than 4 s, evidenced by transmission coefficients below 0.5, making this technology suitable for locally generated waves with shorter periods. During storm events, instantaneous transmission coefficients decreased to as low as 0.25, coinciding with significant wave heights exceeding 0.8 m. Additionally, the efficacy of wave attenuation improved slightly over time as biofoulants adhered to the structure, thereby enhancing drag and mass. [ABSTRACT FROM AUTHOR]

Multiple submerged breakwaters (MSBWs) are commonly used coastal protection structures due to their specific advantages over the emerged ones. Rip currents, as the inevitable natural hazard in the gaps of these constructions, are investigated numerically in the present study. A fully nonlinear mild-slope equation (NMSE) model possessing both fully nonlinear and fully dispersive properties is validated and adopted in the simulations. With four monochromatic wave conditions of different wave heights, periods and incidences representing low-energy, typical, storm and oblique waves tested, the flow patterns and the low-frequency oscillations of the rip currents are studied. For the convenience of risk assessment, the rip risk level is divided into three degrees according to the maximum rip flow speed. The effects of the configurations of the MSBWs on the rip current system as well as the rip risk level are examined, considering different breakwater widths, heights, forms, gap widths and gap numbers. Simulation results suggest that the cross-shore configurations of MSBWs influence the rip risk level by inducing different wave energy dissipations but the longshore configurations of MSBWs by changing flow field patterns. [ABSTRACT FROM AUTHOR]

The present study is devoted to the analysis of extreme sea level oscillations of the Laptev Sea using the ADCIRC model. The numerical modeling is performed on a high-resolution grid and verified for sea level observations from three tide gauges. We have revealed regional characteristics of extreme sea level oscillations for different parts of the Laptev Sea coast. The maximum total sea level range was 544 cm in Ebelyakh Bay, while the minimum was 267 cm in Khatanga Bay, where maximum tidal ranges were obtained. Some areas in Khatanga Bay and Anabar Bay had maximum tidal ranges exceeding 200 cm. The study provided an estimation of the possible magnitude of coastal flooding by calculating the extreme total and residual sea levels for different return periods: 1, 2, 5, 10, 20, 50, and 100 years. The amplitude of extreme surges calculated for the 100-year return period can exceed 300 cm for several sections of the Laptev Sea coast, with the maximum sea level range being about 680 cm for Anabar and Ebelyakh Bays. [ABSTRACT FROM AUTHOR]

This study evaluates the storm surge inundation risk in three anthropogenically infilled estuaries—Xichong, Renshan, and Kaozhouyang—located in the Guangdong–Macao–Hong Kong Great Bay Area, China. By integrating GIS spatial analysis with storm surge modeling, we conducted 204 numerical experiments to simulate storm surge inundation under varying typhoon intensities and astronomical tide conditions. Results revealed that coastal terrain plays a crucial role in influencing storm surge levels and inundation extents. Specifically, the pocket-shaped terrain in the Renshan and Kaozhouyang estuaries amplified storm surges, resulting in higher inundation levels compared to the relatively open terrain of Xichong. Furthermore, anthropogenically reclaimed land in these estuaries appear to be particularly vulnerable to storm-induced inundation. Overall, this study underscores the importance of considering coastline morphology and the anthropogenic modifications of coastal terrain in storm surge risk assessments, offering valuable insights for disaster prevention and mitigation strategies. The use of ArcGIS spatial analysis coupled with storm surge modeling, facilitated by high-resolution DEMs, provides a statistical risk assessment of inundation. However, more complex flooding dynamics models need to be developed, particularly when terrestrial bottom friction information, which is heavily modified by human activities, can be accurately incorporated. [ABSTRACT FROM AUTHOR]

This investigation explores the interactions of different shaped debris with an array of obstacles under subcritical flow conditions, representative of a flood associated with a storm surge or tsunami. Panels, blocks and cylinders were used in a flow channel, as analogues for house panels, cars/containers and trees respectively, whilst some tests used a mix of debris. The backwater effect due to the blockage caused by the obstacles was most (least) significant for panels (cylinders). There was some evidence that smaller key log types and higher flow rates led to smaller dams. It was also evident that key logs formed at different depths depending on debris shape; debris shape also determined the vertical shape of the dam. Capture efficiency had a broadly negative (positive) correlation with the Froude number (permeability). Also, from video footage there were examples of the debris moving more quickly through partial dams. Finally, the drag force, deduced from only the water depths and the flow discharge, showed a clear relationship between drag force and Froude number, and a dependency of drag force on debris shape. There are some implications for the layout of building footprints in the inundation zones and the use of large, break‐away panels. [ABSTRACT FROM AUTHOR]

The annual maximum (AM) method, which subsamples time series to retain the maximum event per year, and the peak‐over‐threshold (POT) method, which extracts values exceeding a threshold to define extremes, have long histories in determining flood event frequency. In practice, extreme value distributions applied to AM and POT events often assume that the data comes from the same statistical population. Locations across the world, like the United States (U.S.) Atlantic coastline, however, experience high coastal water levels driven by various individual processes and storms with different driving mechanisms during different seasons. This research investigates when extreme total water levels (TWLs) occur during the year along the U.S. Atlantic coast and whether individual components, like waves, tides, and storm surge, contributing to TWLs vary across regions and during the year. From 1980 to 2020, extreme TWLs occurred during the extratropical and tropical seasons, with the relative proportion of extreme TWLs occurring during the extratropical season increasing northward. Still water levels drive spatial variability in extreme TWL magnitude, while wave climate drives differences in extreme TWL magnitude between extratropical and tropical seasons. Month‐to‐month variability in the composition of extreme TWLs varies more than spatial variability, highlighting the importance of understanding the components driving extremes at different times of the year. Variations across storm seasons in the processes contributing to extreme TWLs may have implications for how large‐scale changes to the climate impact hazards along open sandy coastlines and influence the robustness of extrapolating rare events from models fit to a single population. Plain Language Summary: To predict extreme sea level impacts, rare events (e.g., 100‐year event) are often determined by evaluating the maximum event of the year or high values above a threshold. These techniques, however, often assume that the same storm type causes all extreme events. This might not be true in regions affected by extratropical (e.g., winter storms) and tropical (e.g., hurricanes) storms, potentially resulting in the incorrect prediction of extreme coastal sea levels. To address this, we analyze when extreme coastal sea levels happen during the year on open‐coast sandy beaches along the U.S. Atlantic coast, and whether the proportion waves, tides, and storm surge contribute to driving extreme coastal sea levels varies by storm seasons. We find that extreme coastal sea levels occur year‐round, and seasonal variations are more noticeable in the northeast because the influence of winter storms is stronger moving northwards. Tides influence regional variability in extreme coastal sea level magnitude, while waves control magnitude changes related to storm seasons. Moreover, extreme coastal sea level drivers vary more between storm seasons than across regions. Our research demonstrates that considering seasonal variations is essential to evaluate the impacts of weather and ocean hazards where winter storms and hurricanes occur frequently. Key Points: The relative composition of extreme total water levels has more month‐to‐month variation than spatial variationStill water levels drive spatial variability of extreme total water levels, while wave climate drives variability across storm seasonsExtreme total water levels occurring in different storm seasons can impact the robustness of rare event extrapolation methods [ABSTRACT FROM AUTHOR]

Convergent estuaries have been shortened by dam‐like structures worldwide. Here, we evaluate 31 long‐term water level stations and use a semi‐analytical tide model to investigate how landward‐funneling and a dam influence tidal and storm surge propagation in the greater Charleston Harbor region, South Carolina, where three rivers meet: the Ashley, Cooper, and Wando. Results show that the phase speed and amplification of the principal tidal harmonic (M2) is larger than other long waves such as storm surge (∼1–4 days) and setup‐setdown (∼4–10 days). Further landward, all waves attenuate, but, as they approach the dam on the Cooper River, a frequency dependent response in amplitude and phase progression occurs. A semi‐analytical tidal model shows that funneling and the presence of a dam amplify tidal waves through wave interference from partial and full reflection, respectively. The different phase progressions of the reflected waves interact with the incident wave to increase or decrease the summed overall wave amplitude. Using a friction‐convergence parameter space, we demonstrate that dominant tides in 23 estuaries and the tidal, storm surge, and setup‐setdown waves in the Cooper River can be delineated into three regimes that describe landward amplification or attenuation associated with funneling, a dam, or both. The regime of each tidal constituent is consistent but can change with the duration and height of each storm surge event; dam associated wave interference can attenuate long‐duration events, while the most intense events (short duration, high water) are amplified by dams more than funneling and greatly increase flood exposure. Plain Language Summary: Most ports and cities are located along estuaries and deltas where flood hazards are increasing partially due to human modifications of channel geometry and land use. Dams, salt barrages, and surge barriers are common in estuaries. They modify estuarine geometry, regulate river flow, protect against flooding, and prevent salt intrusion. Many estuaries are naturally convergent, wide near the sea and narrower landward. Dams are barriers which shorten an estuary. Like ocean swell at a seawall, tides reflect off dams and often increase tidal range. Here we investigate how dams and landward changes in estuarine geometry influence tides and storm surges. Using measurements from the greater Charleston Harbor, SC, we find that constructing a dam either increases or decreases water levels, depending primarily on estuary convergence and surge event duration, as well as flow resistance and river flow. The presence of dams results in higher water levels, and thus flood exposure, when convergence is weak and storm surge at the sea has a short duration and high water levels. Further, channelization that extends inland, resulting from dredging of shipping channels, increases the magnitude and seaward extent of dam effects with increasing flood risk. Key Points: Estuarine geomorphic funneling and dams produce partial and full reflections, respectively, with magnitudes that are frequency dependentThree convergence regimes emerge: dominant tides have near peak amplification, overtides attenuate, and long duration surges mildly amplifyDams reflect and amplify long waves—increasing flood exposure—the most in weakly convergent estuaries with low friction [ABSTRACT FROM AUTHOR]

This study addresses the limitations of and the common challenges faced by one-dimensional river-routing methods in hydrological models, including the National Water Model (NWM), in accurately representing coastal regions. We developed a two-way coupling between the NWM and the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM). The approach demonstrated improvements in modeling coastal river dynamics, particularly during extreme events like Hurricane Matthew. The coupled model successfully captured tidal influences, storm surge effects, and complex river–river interactions that the standalone NWM missed. The approach revealed more accurate representations of peak discharge timing and magnitude as well as water storage and release in coastal floodplains. However, we also identified challenges in reconciling variable representations between hydrological and hydraulic models. This work not only enhances the understanding of coastal–riverine interactions but also provides valuable insights for the development of next-generation hydrological models. The improved modeling capabilities have implications for flood forecasting, coastal management, and climate change adaptation in vulnerable coastal areas. [ABSTRACT FROM AUTHOR]

This summary is about a special issue of the journal Environmental Science and Pollution Research that focuses on innovative methodologies in natural hazard management, specifically related to remote sensing and risk assessment. The issue covers various topics such as fire regime dynamics, coastal vulnerability assessment, landslide susceptibility, seismic response of structures, flood impact assessment, microbial communities in anaerobic digestion, tropical cyclone risk assessment, and cloudburst event forecasting. The articles aim to provide insights for policy-making, emergency response, and sustainable development, with the goal of enhancing the safety and resilience of communities worldwide. [Extracted from the article]

The vulnerability of coastal regions to climate change is a growing global concern, particularly in Bangladesh, which is vulnerable to flooding and storm surges due to its low-lying coastal areas. In this study, we used the fuzzy analytical hierarchy process (FAHP) method to assess the physical and social vulnerability of the entire coastal areas of Bangladesh, using 10 critical factors to evaluate the coastal vulnerability model (CVM). Our analysis indicates that a significant portion of the coastal regions of Bangladesh is vulnerable to the impacts of climate change. We found that one-third of the study area, encompassing around 13,000 km2, was classified as having high or very high coastal vulnerability. Districts in the central delta region, such as Barguna, Bhola, Noakhali, Patuakhali, and Pirojpur, were found to have high to very high physical vulnerability. Meanwhile, the southern parts of the study area were identified as highly socially vulnerable. Our findings also showed that the coastal areas of Patuakhali, Bhola, Barguna, Satkhira, and Bagerhat were particularly vulnerable to the impacts of climate change. The coastal vulnerability map we developed using the FAHP method showed satisfactory modeling, with an AUC of 0.875. By addressing the physical and social vulnerability factors identified in our study, policymakers can take proactive steps to ensure the safety and wellbeing of coastal residents in the face of climate change. [ABSTRACT FROM AUTHOR]

A standalone Advanced Circulation (ADCIRC) model for the east coast of India with a high-resolution grid of 100 m near the coast is used to evaluate coastal inundation resulting from the storm tides generated by recent cyclones. A directional surface roughness parametrization that alters wind speed and Manning's n friction coefficient to compute bottom friction based on land use/land cover (LULC) at a particular location is incorporated in the model. ERA5 reanalysis winds highlight that the cyclonic winds over the land are less intensive than nearby coastal oceans, particularly during landfall time, by approximately 29%–50%. Experiments are also designed to quantify the impact of surface and bottom friction on wind speed and the inward propagation of storm tides. A comparison of cyclonic wind speed after incorporating LULC data in the model is made with an automatic surface observation system (ASOS). It suggests a 15%–29% reduction, consistent with ASOS. The inundated area computed for the cyclones advocates a significant reduction (15%–50%) due to LULC. Sensitivity experiments with LULC are performed to examine the impact of mangroves in the Krishna estuary located in between two concave-shaped coastal geometries. Replacing wetlands with Mangroves results in a simultaneous decline in wind speed (12.5%) and inundated area (13.4%). It also highlights that bottom friction contributes (9.4%) in the inundated area against surface friction (4%). This study infers that further investigation and planning are mandatory to ensure coastal mangrove restoration initiatives and effective coastal management practices. [ABSTRACT FROM AUTHOR]

Flooding represents the greatest natural threat to the UK, presenting severe risk to populations along coastlines and floodplains through extreme tidal surge and hydrometeorological events. Climate change is projected to significantly elevate flood risk through increased severity and frequency of occurrences, which will be exacerbated by external drivers of risk such as property development and population growth throughout floodplains. This investigation explores the entire flood hazard modelling chain, utilising the nonparametric bias correction of UKCP18 regional climate projections, the distributed HBV-TYN hydrological model and HEC-RAS hydraulic model to assess future manifestation of flood hazard within the Broadland Catchment, UK. When assessing the independent impact of extreme river discharge and storm surge events as well as the impact of a compound event of the two along a high emission scenario, exponential increases in hazard extent over time were observed. The flood extent increases from 197 km2 in 1990 to 200 km2 in 2030, and 208 km2 in 2070. In parallel, exponential population exposure increases were found from 13,917 (1990) to 14,088 (2030) to 18,785 (2070). This methodology could see integration into policy-based flood risk management by use of the developed hazard modelling tool for future planning and suitability of existing infrastructure at a catchment scale. [ABSTRACT FROM AUTHOR]

The Río de la Plata Estuary (RdP) is frequently affected by large storm surges that have historically caused social and economic losses. According to recent research, the number and strength of surge events have been increasing over time as a result of climate change. Although process-based models have been widely used for the storm surge prediction, their high computational demand may be a significant disadvantage in some applications, such as rapid or neartime forecasting. Artificial neural network (ANN) becomes an alternative tool to forecast the water level, taking into account meteorological and astronomical forcing as numerical models also do. In this work, an ANN model performance was evaluated to hindcast and forecast water levels in the RdP. Several combinations of lead times and inputs were assessed in order to find the best configuration. The resulting model provides 4-day forecasts for Buenos Aires and Torre Oyarvide stations (located at the upper and intermediate estuary, respectively), using observed water levels, meteorological inputs and predicted astronomical tides. Results also support the ANN model's ability to simulate even extreme events. For instance, for a 12 h-forecast, the RMSE is about 20 cm. Finally, we conclude that the model developed here can effectively complement the empirical and numerical forecasts executed by Naval Hydrographic Service, reducing computational costs and leveraging available datasets. [ABSTRACT FROM AUTHOR]

This article discusses the impacts of climate change on four national parks in the United States: Everglades, Mesa Verde, Joshua Tree, and Mount Rainier. It emphasizes the importance of visible climate impacts in these parks as a way to engage the public in understanding and addressing climate change. The article provides visual examples of these impacts, such as rising sea levels in Everglades National Park and the retreat of glaciers in Mount Rainier National Park. The goal is to use the power of national parks to inspire the American public to take action on climate change. [Extracted from the article]

We developed a robust InSAR processing strategy that can effectively mitigate severe decorrelation noise in a large volume of InSAR data. We mapped the average land subsidence rate (2017–2020) over the 131,572 km2 Upper Texas and Louisiana coasts from Sentinel‐1 data, with ∼2 mm/yr accuracy based on independent GPS and tide gauge validation at 189 locations. The improved InSAR observations reveal widespread subsidence that was previously undetected in coastal wetlands and rural areas with small communities. Our InSAR surface deformation map is at the spatial scale that overlaps with the scale of hydrodynamic model grids. This allows us to integrate InSAR observations into operational storm surge models to analyze future flooding risks due to relative sea level change. We found that these subtle millimeter‐to‐centimeter subsidence features can substantially increase hurricane‐induced inundation, and passive flood mapping (known as the "bathtub" approach) can lead to inaccurate flood risk predictions. Plain Language Summary: The analysis of future storm surge risks along the Gulf Coast often focuses only on projected sea level rise estimates due to the lack of spatially dense land subsidence data. Here we show advances in spaceborne Interferometric Synthetic Aperture Radar (InSAR) techniques can enable the retrieval of coastal subsidence patterns over a 131,572 km2 region along the Gulf Coast of the United States, a challenging terrain for InSAR analysis due to the presence of dense vegetation coverage. Our results reveal widespread subsidence features due to oil and gas production, groundwater pumping, and wetland degradation that were previously undetected. Physics‐based storm surge modeling shows that the detected subtle millimeter‐to‐centimeter land subsidence can substantially elevate flood water depth and flood extent. We demonstrate that the relationship between coastal subsidence and flood depth increase is complex, and communities vulnerable to future flood risk are highly variable along the Gulf Coast of the United States. Key Points: A robust InSAR processing algorithm enables accurate retrieval of subtle surface deformation signals over densely vegetated Gulf CoastInSAR reveals many coastal subsidence features that were previously undetected by existing GPS and tide gauge stationsStorm surge modeling suggests that passive flood mapping based on topography can lead to inaccurate flood risk predictions [ABSTRACT FROM AUTHOR]

Although coastal islands are home to many endemic species, they are also at risk of inundation from storm surge and sea level rise. Three subspecies of mole skink (Plestiodon egregius egregius, P. e. insularis, and the Egmont Key Mole Skink known from a single occurrence) occur on a small number of islands off the Gulf Coast of Florida, USA. We used the most recent sea level rise projections and the latest storm surge simulation data to predict impacts to habitat for insular mole skinks in Florida from 2030 to 2150. Our models predicted that in <100 years (by 2100; intermediate sea level rise scenario; ~1.08–1.15 m sea level rise), >78% of preferred habitat for the Florida Keys Mole Skink, >65% of preferred habitat for the Cedar Key Mole Skink, and >36% of preferred habitat for the Egmont Key Mole Skink will be inundated from sea level rise. Storm surge from tropical cyclones presents a more immediate risk to insular mole skink habitat: our models predicted that between 58% and 75% of Florida Keys Mole Skink habitat is at risk of being submerged under an average maximum of between 0.60 (SD = 0.86) and 0.98 (SD = 0.36) m of storm surge water for a category 1 storm, and the amount of habitat predicted to be impacted increases for higher intensity storms. Our models predicted similar trends for Cedar Key and Egmont Key Mole Skink habitat. Given current sea level rise projections, our models predicted that all three subspecies could be extinct by 2140 due to habitat inundation. There remains uncertainty about how species and ecosystems will respond to sea level rise, thus research to fill these gaps could help mitigate the effects of sea level rise in areas most vulnerable to the effects of climate change. [ABSTRACT FROM AUTHOR]

In this study, two hydrodynamic models, TELEMAC-2D and HEC-RAS 2D, were compared for their Rain-on-Grid (RoG) technique with a particular focus on runoff generation processes in a small and steep catchment. Curve number (CN) method was applied in both the models to simulate two single storm events up to 20 h of duration, whereas the Green-Ampt Redistribution (GAR) method was additionally applied in HEC-RAS 2D for a multi-peak flood event with sustained flow between the peaks. CN and GAR methods were compared for this flood event, and a sensitivity analysis of the GAR parameters was also done. Moreover, the two models were compared for their calibration process, computational time, mesh size and shape, and model availability, in general, as well as the results including inundated areas, water depth, and velocity. The results indicate that both the models are capable of reproducing short duration single storm floods. NSE and R2 for both models ranged from 0.70 to 0.90 and from 0.93 to 0.95. However, the models struggled to reproduce the long-duration multipeak flood event. The sensitivity analysis showed that the results are not very sensitive to the two GAR parameters which are responsible to influence the flow of the second peak in the flood event. Neither the CN nor the GAR infiltration method successfully replicated such events because the hydraulic models permanently lose infiltrated water from the domain. The returned sub-surface flow significantly contributes to river flow during these flood events; however, none of the model incorporates a return flow algorithm. [ABSTRACT FROM AUTHOR]

Green sea dykes, also known as ecosystem-based sea dykes, represent a novel type of coastal defense consisting of both traditional structural engineering and coastal ecosystems, designed to cope with the future trends of sea level rise and intensified storms. Here we focus on the mid-latitude mud coasts (eastern China in particular), which face the most prominent risks of storm surge, storm-induced giant waves, and shoreline erosion, and summarizes the scientific basis of green sea dykes and the current status of engineering practices. We show that the basic mechanisms of nearshore wave energy dissipation include bottom friction, sediment transport, and form drag. These explain the wave damping capacity of oyster reefs and salt marshes on mud coasts. In tidal flat environments, oyster growth increases frictional resistance and even causes wave breaking; the resuspension and transport of fine-grained sediments on salt marsh beds and the movement or resistance to hydrodynamic forcing of salt marsh vegetation stems effectively dissipate wave kinetic energy, and their efficiency increases with the elevation of the bed surface. Based on the wave damping capacity of oyster reefs and salt marshes on mud coasts, ecosystem-based sea dykes are being built in combination with traditional structured sea dykes. By utilizing natural tidal flats outside the dykes or implementing artificial modification projects, a certain scale of salt marshes and/or oyster reefs can be maintained, which serve to protect the sea dykes and enhance their wave resistance functions. From the perspective of system optimization, it is necessary to further improve the efficiency and sustainability of green sea dykes under constraints such as regional environment characteristics, ecosystem health, investment capacity, and ecological resilience. Related scientific issues include the theorization of the wave damping process of salt marshes, the niche and scale control of oyster reef and salt marsh ecosystems, the establishment of engineering standards and the design of the optimal form of sea dykes. [ABSTRACT FROM AUTHOR]

Coastal areas are currently exposed to numerous hazards exacerbated by climate change, including erosion, flooding, storm surges, and other sea level rise phenomena. Mediterranean countries, in particular, are facing a constant shrinking of coastal areas. This region also hosts significant cultural heritage assets, including several UNESCO World Heritage Sites. The present research demonstrates a methodological approach to assess the current and future exposure of Mediterranean coastal areas and heritage assets to Sea Level Rise using open access data regarding elevation, vertical ground motion, and Sea Level Change factors (e.g., ice sheets, glaciers, etc.). The future projections regard 2050 and 2100 and are based on RCP scenarios 2.6, 4.5 and 8.5. The datasets used include Copernicus GLO-30 DSM, the European Ground Motion Service's dataset on Vertical Ground Motion, the Sea Level Change Projections' Regional Dataset by NASA, and a hybrid coastline dataset created for the present research purposes to assist in delineating the study area. The research results demonstrate that Greece, Italy, and France's mainland and cultural heritage assets already face SLR-related hazards but are expected to be further exposed in the future, always taking into consideration the high level of uncertainty regarding SLR projections and RCP scenarios' hypotheses. [ABSTRACT FROM AUTHOR]

Coastal regions have experienced significant environmental changes and increased vulnerability to floods caused by the combined effect of multiple flood drivers such as storm surge, heavy rainfall and river discharge, i.e., compound floods. Hence, for a sustainable development of coastal cities, it is necessary to understand the spatiotemporal dynamics and future trends of compound flood hazard. While the statistical dependence between flood drivers, i.e., rainfall and storm surges, has been extensively studied, the sensitivity of the inundated areas to the relative timing of a driver's individual peaks is less understood and location dependent. To fill this gap, here we propose a framework combining a statistical dependence model for compound event definition and a hydrodynamic model to assess inundation maps of compound flooding from storm surge and rainfall during typhoon season in Shanghai. First, we determine the severity of the joint design event, i.e., peak surge and precipitation, based on the copula model. Second, we use the same frequency amplification (SFA) method to transform the design event values in hourly time series so that they represent boundary conditions to force hydrodynamic models. Third, we assess the sensitivity of inundation maps to the time lag between storm surge peak and rainfall. Finally, we define flood zones based on the primary flood driver, and we delineate flood zones under the worst compound flood scenario. The study highlights that the temporal delay between storm surge and rainfall plays a pivotal role in shaping the dynamics of flooding events. More specifically, that the peak rainfall occurs 2 h before the peak storm surge would cause the deepest average cumulative inundation depth. At the same time, the results show that in Shanghai surge is the primary flood driver. High storm surge at the eastern part of the city (Wusongkou tidal gauge) propagates upstream in the Huangpu River, resulting in fluvial flooding in Shanghai city center and several surrounding districts. This calls for a better fluvial flooding control system hinging on the backwater effect during high surge in the upper and middle Huangpu River and in the newly added urbanized areas to ensure flood resilience. The proposed framework is useful to evaluate and predict flood hazard in coastal cities, and the results can provide guidance for urban disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

Coastal cities are becoming more vulnerable to flood risks due to climate change, rising sea levels, intense storm surges, population growth, and land subsidence. Developing emergency preparedness and response strategies can reduce the impact of coastal flooding and enhance a city's resilience. This article presents a flood relief logistics planning aimed at providing decision-makers with a feasible framework. The framework integrates geographic information system (GIS) network analysis and resource allocation optimization models. Considering the fairness of resource allocation, a biobjective allocation model that minimizes the total transportation cost and maximum unsatisfied rate is developed. This flood relief logistics planning approach is applied to Shanghai, China to presents feasible distribution strategies. And, the case study indicates that the current capacity of emergency flood shelters (EFSs) and the supplies stored in emergency reserve warehouses (ERWs) are adequate to meet the demand of the elderly population if affected by a 100-year coastal flood scenario. However, they would not be sufficient to cover the demand in a 1000-year coastal flood scenario and could only serve half of the affected elderly people. The results also suggest that the city-level ERW in Jiading District and the branch warehouse in Minhang District play a crucial role in distribution. Additionally, the study highlights the importance of increasing resource investments to tackle the inherent unfairness caused by resource shortages. This study provides a scientific reference for developing flood relief logistics plans in Shanghai, and it presents a transferable framework that is applicable to other coastal cities. [ABSTRACT FROM AUTHOR]

The study of Neoproterozoic carbonate sequences is complicated due to several variables influencing the geochemical and mineralogical composition, compounded by the scarcity of environmental analogs. The Tamengo Formation in the Corumbá Group is one of the most extensively studied archives of the Neoproterozoic in South America and encompasses Ediacaran guide fossils of Corumbella werneri and Cloudina lucianoi. This research focused on a marl sample containing well-preserved bioclasts of exoskeletons of Corumbella werneri, which is one of the earliest biomineralizing organisms. By utilizing diverse techniques such as optical and SEM microscopy, QEMSCAN imaging, electron microprobe, in situ ICP-MS, and isotope analyses, this study reveals primary and secondary signals in the bioclastic exoskeletons and the matrix within. These findings shed light on the sedimentary environment and diagenetic history of the Tamengo Formation. It is revealed that Corumbella werneri likely inhabited calm conditions, just below the base of storm waves and above a sharp chemocline at the bottom. In addition, the presence of distinct hydrothermal signals in the composition of REEs indicates a potential magmatic event that occurred in the region after the deposition of the succession. This pilot study highlights that the history recorded in the Neoproterozoic rocks of the Tamengo Formation is complex, and thus more detailed studies integrating lithological, paleontological, and geochemical parameters are necessary to reach a correct interpretation of this sequence. [ABSTRACT FROM AUTHOR]

This research is the first attempt to examine the hydrodynamic loads of nonlinear solitary waves on bridge decks near a coastline. We employ laboratory experiments and a large eddy simulation model to simulate the wave motion and wave loads on a partially submerged rectangular deck near a sloped beach. The measured wave heights and wave loads from wave flume experiments verify the accuracy of the computational fluid dynamics model. A series of parametric studies investigates the effects of wave height, submergence, and beach slope on the wave loads of the bridge deck. The simulation results revealed that the hydrodynamic forces are linearly proportional to the wave height, and the dimensionless force coefficients depend on the submergence ratio and beach slope. For the mild slope case (θ = 18.5°), the wave load during the run-up stage is larger than that during the run-down stage. The largest drag coefficient CD = 0.58, lift coefficient CL = 0.45, and pitch moment coefficient Cm = −0.21 occur when the deck is initially above the still wave level. On a steeper slope (θ = 30°), the run-down current could generate a large downward force and a clockwise moment when the bridge deck is close to a shoreline. Hereafter, coastal bridges should consider the impact of the run-down flow during tsunamis and storm surges. [ABSTRACT FROM AUTHOR]

Coastal areas play a crucial role in regional development and the environment, but they are increasingly vulnerable to extreme weather events due to global climate change. Sea surface temperature (SST) is an important parameter in the ocean-atmosphere system and can help monitor and understand climate change. Changes in SST have significant impacts on extreme weather events, such as typhoons, and can threaten the safety of coastal cities. Advances in satellite remote sensing technology have improved the accuracy and resolution of SST data, providing new opportunities for studying the impact of SST on urban development in coastal cities. Future research should focus on the impact of SST on the ocean-atmosphere CO2 flux, climate change, typhoons, hazardous weather, the energy balance of coastal megacities, and sea-land breeze circulation. [Extracted from the article]

One risk posed by hurricanes and typhoons is local inundation as ocean swell and storm surge bring a tremendous amount of energy and water flux to the shore. Numerical wave tanks are developed to understand the dynamics computationally. The three-dimensional equations of motion are solved by the software 'Open Field Operation And Manipulation' v2206. The 'Large Eddy Simulation' scheme is adopted as the turbulence model. A fifth-order Stokes wave is taken as the inlet condition. Breaking, 'run-up', and overtopping waves are studied for concave, convex, and straight-line seafloors for a fixed ocean depth. For small angles of inclination (<10°), a convex seafloor displays wave breaking sooner than a straight-line one and thus actually delivers a smaller volume flux to the shore. Physically, a convex floor exhibits a greater rate of depth reduction (on first encounter with the sloping seafloor) than a straight-line one. Long waves with a speed proportional to the square root of the depth thus experience a larger deceleration. Nonlinear (or 'piling up') effects occur earlier than in the straight-line case. All these scenarios and reasoning are reversed for a concave seafloor. For large angles of inclination (>30°), impingement, reflection, and deflection are the relevant processes. Empirical dependence for the setup and swash values for a convex seafloor is established. The reflection coefficient for waves reflected from the seafloor is explored through Fourier analysis, and a set of empirical formulas is developed for various seafloor topographies. Understanding these dynamical factors will help facilitate the more efficient designing and construction of coastal defense mechanisms against severe weather. [ABSTRACT FROM AUTHOR]

The Western Pacific region is highly vulnerable to typhoon storm surge disasters, with localized erosion posing a particularly prominent issue for coastal marine structures. The prevalence of extreme typhoon storm surges poses a significant threat to the safety of engineering projects in these areas. In this study, a parameterized wind field model with precise calculation of wind speed was employed to establish a numerical model for typhoon storm tides. Based on the Western Pacific typhoon data from 1949 to 2023, hydraulic simulations were conducted for Hangzhou Bay, Xiangshan Port, and Yueqing Bay, revealing maximum flow velocities of 4.5 m/s, 1.95 m/s, and 2.09 m/s, respectively. These velocities exceeded the maximum possible tidal flow by 0.47–1.17 m/s. Additionally, using Sun's velocity formula, the initiation flow velocities were calculated to be 1.85 m/s, 1.81 m/s, and 2.06 m/s for the aforementioned locations. Through localized erosion tests conducted around typical bridge piers and the subsequent application of similarity criteria, the maximum depth of localized erosion in the study area was determined to range from 2.16 m to 16.1 m, which corresponds to 1.1–2.3 times the scour caused by the maximum tidal flow scenario. A comparison of the erosion test results with calculations based on several formulas demonstrated that the scour prediction formula proposed by Sun exhibited the highest accuracy. This study supplements the understanding of the impact of typhoon storm surges on bridge pier erosion and provides a scientific basis for the design of bridge foundations. [ABSTRACT FROM AUTHOR]