Anthropocene Coasts最新文献

This study analyzes the content of internet ratings of beaches to identify the indicators used. The methodology used an exploratory internet survey using the term ‘best beaches’ in five languages. For each site, the ranking method used was extracted and the indicators considered were listed, where applicable. Of the 70 websites analyzed, 47 ranked the beaches (67%) but less than 50% used indicators. The remaining were based on the opinion of the editorial board, personal experience, and users’ perceptions. The most used indicator was the color of water, followed by the color of the sand. These results show that the majority of ‘best beaches’ lists are based on subjective criteria. They are an overview of places that appeal to the person that wrote the page and are not scientifically or analytically based. Even when indicators are considered, these are mostly a reflection of the idea of an idealized beach, crystal blue waters with white or gold sand. The actual quality of the beach, including water quality, carrying capacity, and ecosystem balance, is not addressed. Although visual attractiveness is a key element for the public, these rankings should incorporate a wider range of indicators to fully assess the quality of a beach.

The aim of the present contribution has been to present a methodological framework to gauge/assess the perceptions and identify the policy priorities of local-decision-makers for the management of the coastal zone under a changing climate, on the basis of structured ‘interviews’ of the local decision makers. The framework was applied in two different coastal areas in Greece: a) Elefsina, an urban-industrial area west of Athens with a long industrial history (and the 2023 European Capital of Culture); and b) the Aegean island of Santorini/Thera, a major international tourist destination due to the rare aesthetics of its volcanic landscape. The framework implementation showed that a) policy prioritization is characterized by an (understandably) overarching objective to address immediate environmental and socio-economic challenges in short time tables due also to constraints in appropriate human and financial resources and the reliance on higher governance (regional/national) levels; b) policy axis and action prioritizations are controlled by the local environmental setting and development model; c) interestingly for coastal municipalities policy actions associated with the study/protection of coastal ecosystems ranked very low albeit for different stated reasons; and d) climate change impacts and adaptation have not been prioritized highly in both coastal municipalities, in contrast to the large impacts and needs for adaptation projected for these areas and the evolving policy and legislation frameworks. It appears that higher efforts should be made in terms of the assessment of climate change impacts, and the dissemination of the assessment results and the relevance of the evolving policy and legislation regimes to the local policy makers.

The present study uses nine machine learning (ML) methods to predict wave runup in an innovative and comprehensive methodology. Unlike previous investigations, which often limited the factors considered when applying ML methodologies to predict wave runup, this approach takes a holistic perspective. The analysis takes into account a comprehensive range of crucial coastal parameters, including the 2% exceedance value for runup, setup, total swash excursion, incident swash, infragravity swash, significant wave height, peak wave period, foreshore beach slope, and median sediment size. Model performance, interpretability, and practicality were assessed. The findings from this study showes that linear models, while valuable in many applications, proved insufficient in grasping the complexity of this dataset. On the other hand, we found that non-linear models are essential for achieving accurate wave runup predictions, underscoring their significance in the context of the research. Within the framework of this examination, it was found that wave runup is affected by median sediment size, significant wave height, and foreshore beach slope. Coastal engineers and managers can utilize these findings to design more resilient coastal structures and evaluate the risks posed by coastal hazards. To improve forecast accuracy, the research stressed feature selection and model complexity management. This research proves machine learning algorithms can predict wave runup, aiding coastal engineering and management. These models help build coastal infrastructure and predict coastal hazards.

Graphical Abstract

River systems play an important role in the development of human society. However, they have been significantly affected by human activities, reducing the capacity for water supply, flood regulation, and aquatic ecosystem services. Identifying changes in river systems and hydrological responses to these changes is crucial for regional water management. In this study, based on the data derived from topographic maps of the 1960s, 1980s, and 2010s, we comprehensively quantified changes in river systems of the Yangtze River Delta (YRD), China. The results show that the density of rivers and the proportion of water surface decreased over the past several decades, while changes in the evolutionary coefficient of rivers and the ratio of area to length of rivers exhibited clear spatial differences. Low-grade rivers in urbanized areas have declined severely, leading to a simplification of river structure. Furthermore, the hydrological response to changes in the river system was revealed in the Taihu Lake Plain, an area of the YRD with a plain river network. A longitudinal functional connectivity index (LFCI) was adopted to assess the hydrological dynamics in water level, and it was found to have an increasing trend. In addition, the specific storage capacity (SSC) and the specific regulation capacity (SRC) were established to reveal the impact of changes in the structure and connectivity of the river system on the regulation and storage capacity, and both indicators exhibited a downward trend. Simulations based on the MIKE 11 model show that the reduction of tributaries across the region can result in an earlier peak timing and higher peak water level. Our results can support the development of river system protection and flood adaptation strategies in the delta plains.

Different countries practice various approaches to coastal erosion management, which have characteristics strengths and weaknesses. Protection of the land from coastal erosion is a complex task, and it depends on many socioeconomic and environmental factors. Asian countries have unique cultural, social, environmental, and political behaviors. Therefore, the objectives of this study are to analyze the current status of coastal management in Thailand, Malaysia, and Sri Lanka, and to synthesize a common coastal management framework for those countries. In this study, we analyzed the situation of coastal erosion, and the existing responsible government department and their legal authorities in Thailand, Malaysia, and Sri Lanka. After that, we evaluated specific challenges and common issues in the management of coastal erosion. The main challenges can be summarized as rapid urbanization and the construction of infrastructure along the coasts, rising sea levels as a consequence of climate change, inadequate coastal zone planning and management framework, a deficit of sediment supply compared to erosion rates, and face constraints in terms of financial and technical resources for coastal erosion management. A multi-faceted approach is required to address these challenges, and it combines both structural and non-structural measures. For example, this approach involves (i) sustainable coastal zone planning, (ii) the implementation of nature-based solutions, (iii) restoration of natural coastal features, (iv) regulation of coastal development activities, and (v) the integration of climate change considerations into coastal management practices. Finally, collaborative efforts among government agencies, researchers, local communities, and international organizations are crucial for successful coastal erosion management in Thailand, Malaysia, Sri Lanka, and potentially other Asian regions.

There is a void in the knowledge of the acidification status of Eastern Canada's coastal waters. This knowledge is crucial to evaluating the threats posed to marine life, particularly oyster farming, a flagship of New Brunswick seafood production. In this study, we measured the temporal variability of pH and related environmental parameters in three bays of Northeastern New Brunswick. We also evaluated the potential impact of the observed pH levels on the Eastern oyster (Crassostrea virginica Gmelin, 1791), based on the available literature on this species’ sensitivity to acidification. We investigated the presence of inherent cycles of pH with the Fourier transform and the spectral filtering technique. Our results show that pH is highly variable in the studied area, with values ranging from 7.31 to 8.90. A seasonal effect was apparent, as the pH fluctuations were set at the lowest level in winter when the cover of ice and snow on the bay was present. The spectral analysis revealed a clear semidiurnal tidal pattern of pH, this variable being inversely related to the water level in summer and directly related to it in winter. The spectral subtraction of all the tidal components allowed the detection of a circadian rhythm that was not in pace with the alternation between day and night but rather slowly drifted so that the pH troughs occurred at night during the full moon period. Short periodicities of circa 8 and 6 h also existed in two of the three bays. Based on current knowledge of C. virginica’s sensitivity to acidification, this species’ recruitment, growth, and survival are unlikely to be impacted by the present pH levels in the studied area. However, further acidification might overcome the resilience of C. virginica, especially that of the larvae that are produced during the winter in commercial hatcheries.

The United Nations estimate that by 2030 about half of the world’s population would be comprised of the middle-class, who mostly live in the increasing number of megacities around the world. Southeast Asian megacities, such as Metropolitan Manila, have long been troubled by rapid urbanization, increasing disaster risk, and the looming impacts of climate change. As a response, there is a growing focus on disaster and climate resilient policies in megacities, most of which have only centered on how future disasters and climate uncertainty would impact vulnerable communities. This has resulted in policies that cater towards relocation of the poor to combat disasters and climate change. This exploratory study attempts to elucidate how the middle-class views disasters and land reclamation in Metro Manila, the Philippines. Using an online questionnaire survey of 425 middle-class respondents, the study shows that middle-class perception of risk potentially amplifies vulnerability and reduces the resilience of the poor. While knowledge about the risks is high, the capacity of the middle class to act is low, especially compared to vulnerable communities. Also, climate change and disasters are viewed primarily as environmental issues, which is compounded by inadequate defenses. Land reclamation, along with coastal informal settlements, are viewed as an intrusion into the environment. This study finds that the middle-class’s perception of risk may marginalize the poor by favoring eviction of vulnerable communities in coastal areas, including those targeted for land reclamation, under the pretext of controlling the city’s population growth and environmental impact.