UNASSIGNED: Embankment dams were built south of the Laizhou bay in China for controlling storm surge disasters, but they are not enough to replace coastal forests in protecting the land. This study was designed to evaluate the effects of embankment dams on natural forests dominated by Tamarix austromongolica and test whether the dam-shrub system is a preferable updated defense.
UNASSIGNED: Coastal forests on two typical flats, one before and one behind embankment dams, were investigated using quadrats and lines. Land bareness, vegetation composition and species co-occurrence were assessed; structures of T. austromongolica populations were evaluated; and spatial patterns of the populations were analyzed using Ripley\'s K and K1,2 functions.
UNASSIGNED: In the area before embankment dams, 84.8% of T. austromongolica were juveniles (basal diameter ≤ 3 cm), and 15.2% were adults (basal diameter > 3 cm); behind the dams, 52.9% were juveniles, and 47.1 were adults. In the area before the dams, the land bareness was 13.7%, four species occurred, and they all were ready to co-occur with T. austromongolica; behind the dams, the land bareness was 0%, and 16 species occurred whereas they somewhat resisted co-occurrence with T. austromongolica. In the area before the dams, the T. austromongolica population was aggregated in heterogeneous patches, and the juveniles tended to co-occur with the adults; behind the dams, they were over-dispersed as nearly uniform distributions, while the juveniles could recruit and were primarily independent of the adults. These results indicate that the T. austromongolica species did not suffer from the unnatural dams, but benefited somehow in population expansion and development. Overall, the T. austromongolica species can adapt to artificial embankment dams to create a synthetic defense against storm surges.

Creating ecosystem buffers in intertidal zones, such as seagrass meadows, has gained increasing attention as a nature-based solution for mitigating storm-driven coastal erosion. This study presents what-if scenarios using an integrated model framework to determine the effectiveness and strategies for planting seagrass to reduce coastal erosion. The framework comprises two levels of simulation packages. The first level is a regional-scale coupled hydrodynamic model that simulates the processes of a specific storm and provides boundary forces for the morphodynamic model XBeach to apply at the next level, which simulates nearshore morphological evolution. The framework is applied to the open coast of Norderney in the German Bight of the North Sea. We demonstrate that optimising the location and size of seagrass meadows is crucial to increase the efficiency of onshore sediment erosion mitigation. For a specific depth range, depending on the storm\'s intensity, the most significant reduction in erosion may not be achieved by starting the meadow at the depth that permits the largest meadow size. To maintain a significant coastal protection effect, seagrass density and stem height should be considered together, ensuring erosion reduction by at least 80 % compared to the unprotected coast. This study provides valuable insights for the design and implementation of seagrass transplantation as a nature-based solution, highlighting the importance of considering location, size, density, and stem height when using seagrass meadows for coastal protection.

Coastal levees play a role in protecting coastal areas from storm surges and high waves, and they provide important input information for inundation damage simulations. However, coastal levee data with uniformity and sufficient accuracy for inundation simulations are not always well developed. Against this background, this study proposed a method to extract coastal levees by inputting high spatial resolution optical satellite image products (RGB images, digital surface models (DSMs), and slope images that can be generated from DSM images), which have high data availability at the locations and times required for simulation, into a deep learning model. The model is based on U-Net, and post-processing for noise removal was introduced to further improve its accuracy. We also proposed a method to calculate levee height using a local maximum filter by giving DSM values to the extracted levee pixels. The validation was conducted in the coastal area of Ibaraki Prefecture in Japan as a test area. The levee mask images for training were manually created by combining these data with satellite images and Google Street View, because the levee GIS data created by the Ibaraki Prefectural Government were incomplete in some parts. First, the deep learning models were compared and evaluated, and it was shown that U-Net was more accurate than Pix2Pix and BBS-Net in identifying levees. Next, three cases of input images were evaluated: (Case 1) RGB image only, (Case 2) RGB and DSM images, and (Case 3) RGB, DSM, and slope images. Case 3 was found to be the most accurate, with an average Matthews correlation coefficient of 0.674. The effectiveness of noise removal post-processing was also demonstrated. In addition, an example of the calculation of levee heights was presented and evaluated for validity. In conclusion, this method was shown to be effective in extracting coastal levees. The evaluation of generalizability and use in actual inundation simulations are future tasks.

Climate change alters the climate condition and ocean environment, leading to accelerated coastal erosion and a shift in the coastline shape. From previous studies, Southeast Asia\'s coastal region is suffering from severe coastal erosion. It is most sensitive and vulnerable to climate change, has broad and densely populated coastlines, and is under ecological pressure. Efforts to systematically review these studies are still insufficient despite many studies on the climate change linked to coastal erosion, the correlation between coastal erosion and coastal communities, and the adaptative measures to address these issues and their effectiveness in Southeast Asia. Therefore, by analyzing the existing literature, the purpose of this review was to bridge the knowledge gap and identify the link between climate change and coastal erosion in Southeast Asia in terms of sea-level rise, storm surge, and monsoon patterns. The RepOrting standards for Systematic Evidence Syntheses (ROSES) guided the study protocol, including articles from the Scopus and Dimension databases. There were five main themes considered: 1) climate change impact, 2) contributing factors to coastal erosion, 3) coastal erosion impact on coastal communities, 4) adaptation measure and 5) effectiveness of adaptation measure using thematical analysis. Subsequently, nine sub-themes were produced from the themes. Generally, in Southeast Asia, coastal erosion was reflected by the rising sea level. Throughout reviewing past literature, an interesting result was explored. Storm surges also had the potential to affect coastal erosion due to alterations of the atmospheric system and seasonal monsoon as the result of climate change. Meanwhile, an assessment of current erosion control strategies in relation to the relative hydrodynamic trend was required to avoid the failure of defence structures and the resulting danger to coastal communities. Systematically reviewing the existing literature was critical, hence it could significantly contribute to the body of knowledge. It provides valuable information for interested parties, such as authorities, the public, researchers, and environmentalists, while comprehending existing adaptation practices. This kind of review could strategize adaptation and natural resource management in line with coastal communities\' needs, abilities, and capabilities in response to environmental and other change forms.

The increase in storm surge events caused by climate change exacerbates adverse effects on seawater inundation in coastal areas. An accurate description of the water level curve is crucial for understanding the process of saltwater intrusion (SWI) resulting from storm surge. Most studies involving empirical surges as inputs to groundwater models, often simplify spatial and temporal seawater inundation processes, which may increase the uncertainty in vertical seawater intrusion. To address this gap, we employed a comprehensive modeling approach using storm surge model ADCIRC and numerical simulator HydroGeoSphere to reveal SWI dynamics during a historical storm surge event in a coastal farm, considering varying tidal-surge phases and typhoon intensities. Our findings indicate pronounced SWI variations even with consistently highest water level during a storm surge, contingent on prior tidal processes. The timing of typhoon landfall on an hourly scale yielded diverse water level curves, altering the function of SWI. Intriguingly, SWI exacerbates following a high tide with 31.2 % average salinity higher, highlighting the profound modulation effect of tidal levels on SWI. Local topography significantly influenced SWI dynamics. Ponds, for instance, retained elevated salinity levels for over 15 h, indicating a more prolonged exposure to salinity than roads. These findings underscore the importance of considering both tidal influences and topographical factors in understanding and mitigating SWI in coastal agricultural management.

BACKGROUND: Marine macroalgae (\'seaweeds\') are a diverse and globally distributed group of photosynthetic organisms that together generate considerable primary productivity, provide an array of different habitats for other organisms, and contribute many important ecosystem functions and services. As a result of continued anthropogenic stress on marine systems, many macroalgal species and habitats face an uncertain future, risking their vital contribution to global productivity and ecosystem service provision.
METHODS: After briefly considering the remarkable taxonomy and ecological distribution of marine macroalgae, we review how the threats posed by a combination of anthropogenically induced stressors affect seaweed species and communities. From there we highlight five critical avenues for further research to explore (long-term monitoring, use of functional traits, focus on early ontogeny, biotic interactions and impact of marine litter on coastal vegetation).
CONCLUSIONS: Although there are considerable parallels with terrestrial vascular plant responses to the many threats posed by anthropogenic stressors, we note that the impacts of some (e.g. habitat loss) are much less keenly felt in the oceans than on land. Nevertheless, and in common with terrestrial plant communities, the impact of climate change will inevitably be the most pernicious threat to the future persistence of seaweed species, communities and service provision. While understanding macroalgal responses to simultaneous environmental stressors is inevitably a complex exercise, our attempt to highlight synergies with terrestrial systems, and provide five future research priorities to elucidate some of the important trends and mechanisms of response, may yet offer some small contribution to this goal.

Coastal areas are of paramount importance due to their pivotal role in facilitating a wide range of socio-economic activities and providing vital environmental services. These areas, as the meeting points of land and sea, face significant risks of flooding due to the ongoing rise in sea levels caused by climate change. Additionally, they are susceptible to extreme events like king tides and large waves in the future. This paper introduces a framework for estimating the extreme total water level (TWL) by considering the effects of regional sea level rise (RSLR) resulting from a warming climate under RCP 8.5. It also incorporates the contributions of high tides, 100-year storm surge, and 100-year wave setup and run-up. The proposed framework is utilized to evaluate the occurrence of extreme coastal flooding along the Persian Gulf coast of Iran, an area that is home to significant industries in the country. The results offer an estimated increase of RSLR by 0.23 m from 2020 to 2050 considering an ensemble of climate model projections. Extreme wave setup values are estimated to range between 0.19 and 0.66 m, while storm surge is projected to vary from 0.4 to 1.44 m across the studied coastline. These together yield in a projected extreme TWL along the coastline within the range of 3.18 and 3.90 m above the current sea level. This significant increase in sea level could lead to the inundation of approximately 513 km2 of low-lying coastal land, which accounts for about 16% of the studied domain and could pose serious flooding threat to the people and their assets in this region. Finally, relative ranking of flooded zones (i.e., 6 zones) helps determine the areas with higher chance of flood exposure, at which investment in flood mitigation measures should be prioritized.

Sea level rise (SLR) is the most significant climate change-related threat to coastal wetlands, driving major transformations in coastal regions through marsh migration. Landscape transformations due to marsh migration are manifested in terms of horizontal and vertical changes in land cover and elevation, respectively. These processes will have an impact on saltmarsh wave attenuation that is yet to be explored. This study stands as a comprehensive analysis of spatially distributed wave attenuation by vegetation in the context of a changing climate. Our results show that: i) changes in saltmarsh cover have little to no effect on the attenuation of floods, while ii) changes in elevation can significantly reduce flood extents and water depths; iii) overland wave heights are directly influenced by marsh migration, although iv) being indirectly attenuated by the water depth limiting effects of water depth attenuation driven by changes in elevation; v) the influence of saltmarsh accretion on wave attenuation is largely evident near the marsh edge, where the increasing elevations can drive major wave energy losses via wave breaking. Lastly, vi) considering the synergy between SLR, marsh migration, and changes in elevation results in significantly more wave attenuation than considering the eustatic effects of SLR and/or horizontal marsh migration alone, and therefore should be adopted in future studies.

Integrated hydrological and hydrodynamic modeling study has been conducted to investigate hurricane impact on Woonasquatucket River, Rhode Island, USA. Model simulation was conducted for the case study of 2010 storm event. The hydrological model simulates the runoff from the heavy rainstorm, while the river hydrodynamic model simulates the flood waves affected by the interactions of upstream rainfall runoff and downstream storm surge. Results indicate that the river floods was dominant by rainfall runoff in upper river reaches, but dominant by storm surge in the lower river area near the estuary.

Due to the interaction between upstream discharge and astronomical tides in tidal reaches, the typhoon-induced storm surge processes are quite different from that in other coastal regions. Investigating the contributions of driving factors is essential to deepen the understanding of storm surges in tidal reaches. In this study, a coupled hydrological-hydrodynamic storm surge model is first developed to explore the main driving factors of storm surges in Makou-Dahengqin tidal reach during the three most influential typhoon events (Hagupit, Hato and Mangkhut). After that, the machine learning method is integrated to assess the water level in response to storm surges. The driving factors of storm surge are decomposed into remote forcing (upstream discharge, astronomical tide) and direct local forcing (wind stress, atmospheric pressure). The relative contributions of remote forcing are the highest near the estuary mouth. The relative contributions of local forcing to water levels are higher in the sections 40-80 km away from the estuary mouth. The most impacting period of the local forcing is about 48 h, while the relative contributions of remote forcing increase before and after the period. The local forcing-induced surges are highest at the upper reach during Hagupit, while it causes extreme surges at the estuary mouth during more powerful typhoons (Hato, Mangkhut). The maximum water levels and remote forcing-induced maximum surges invariably appear at the upper reach. However, when local and remote forcings are in the same phase, the maximum storm surge appears in the lower reaches during Hato. If local and remote forcings are in the same phase, the peak water levels would be amplified by up to 15.04 %, 36.23 % and 40.68 % during Hagupit, Hato and Mangkhut, respectively. Moreover, Remote forcing contributes more to the amplification of peak water levels than local forcing does, accounting for 68.5 % to 100 %.