Coastal indices to assess sea-level rise impacts - A brief review of the last decade

Rocha, Carolina; Antunes, Carlos; Catita, Cristina

doi:10.1016/j.ocecoaman.2023.106536

Cited by 20 publications

(11 citation statements)

References 93 publications

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“…The problem is that "everyone knows the weather", but as the costs associated with responding to natural and human-caused events increase, there is a growing demand for incorporating risk-based assessments in both the public and private sectors, partially through technology collection but also through better forecasting, big data, and cooperation. One of the challenges Rocha et al describe through a proposed Coastal Vulnerability Index is that these models and indices are not standardized in their approach to calibrating a coastal baseline [11].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Cultural events may draw large crowds but are seen as a net positive from a wellness and economic perspective and are a component of the Sustainability Development Goals for supporting communities. Rocha et al stressed, "It is recommended that coastal risk assessments include an integrated approach that considers the environmental changes, socioeconomic developments, and the interactions between these elements" [11].…”

Section: Literature Reviewmentioning

confidence: 99%

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Standing Watch: Baselining Predictable Events That Influence Maritime Operations in the Context of the UN’s Sustainable Development Goals

Lambert,

Merten

2024

Sustainability

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The authors present a practical framework for assessing seasonal events that may influence maritime operations, seeking to tie in discussions about climate change adoption to maritime operational assessments. Most maritime-related research tends to focus on a single event, such as a storm, but maritime systems operate within complex systems that have some predictable patterns. These predictable patterns due to natural events, such as weather and water levels, can influence operations. By contrast, other factors, such as cargo peaks or cultural activities, could also shape maritime systems. The growing focus on adopting human activities to the United Nations’ Sustainability Development Goals means that system operations should consider their relationship to these broader goals. By integrating data from emergency management databases and weather information sources with other inputs, the authors, in collaboration with various stakeholder groups, created a matrix of regionally specific predictable events that may occur within a region by time of year that can be linked to the Sustainability Development Goals. The matrix was vetted to verify the information, ensuring that all perspectives were considered. The main findings were that a seasonal event matrix was not just a theoretical tool but a practical reference for examining operational patterns in a river for various uses, such as training, operational planning, and emergency response coordination.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Standing Watch: Baselining Predictable Events That Influence Maritime Operations in the Context of the UN’s Sustainable Development Goals

Lambert,

Merten

2024

Sustainability

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“…Addressing coastal erosion and mangrove conservation challenges requires scientific methods and innovative strategies. Rocha et al [12] presented a comprehensive overview of current coastal vulnerability and risk assessment methodologies, encompassing various temporal and spatial scales to capture coastal processes [12]. Their approach involved categorizing these processes into different intervals and classifying the outcomes of each variable, thereby delineating a broad spectrum of vulnerability and risk levels.…”

Section: Current Status and Challenges Of Marine Regulation By Coasta...mentioning

confidence: 99%

Priority Setting and Resource Allocation in Coastal Local Government Marine Regulatory Reform: Application of Machine Learning in Resource Optimization

Tian,

Wang

2024

Water

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This study investigates the prioritization and resource allocation strategies adopted by the coastal local governments of Qingdao, Dalian, and Xiamen in the context of marine regulatory reform aimed at enhancing regulatory efficiency. Data on relevant opinions, departmental requirements, and existing resource allocations were collected through a questionnaire survey. A backpropagation (BP) neural network was then applied to analyze the survey data, prioritize regulatory tasks, and propose resource allocation schemes. The findings demonstrate that integrating machine learning into marine regulation can significantly improve resource utilization efficiency, optimize task execution sequences, and enhance the scientific and refined nature of regulatory work. The BP neural network model exhibited strong predictive capabilities on the training set and demonstrated good generalization abilities on the test set. The performance of the BP neural network model varied slightly across different management levels. For the management level, the accuracy, precision, and recall rates were 85%, 88%, and 82%, respectively. For the supervisory level, these metrics were 81%, 83%, and 78%, respectively. At the employee level, the accuracy, precision, and recall rates were 79%, 81%, and 76%, respectively. These results indicate that the BP neural network model can provide differentiated resource allocation recommendations based on the needs of different management levels. Additionally, the model’s performance was assessed based on the employees’ years of experience. For employees with 0–5 years of experience, the accuracy, precision, and recall rates were 82%, 84%, and 79%, respectively. For those with 5–10 years of experience, the metrics were 83%, 86%, and 80%, respectively. For employees with over 10 years of experience, the accuracy, precision, and recall rates were 85%, 88%, and 82%, respectively. These data further confirm the applicability and effectiveness of the BP neural network model across different experience groups. Thus, the adoption of machine learning technologies for optimizing marine regulatory resources holds significant practical value, aiding in the enhancement of regulatory capacity and effectiveness within coastal local governments.

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“…The Coastal Vulnerability Index (CVI) is the most common index for assessing coastal vulnerability to physical climate change and sea level rise (Rocha et al, 2023;Roy et al, 2023). All CVI methods are based on an index that simplifies a number of complex and interactive parameters and is widely used to measure coastal vulnerability on a global scale (Khouakhi et al, 2013;Koroglu et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Previous studies from the late twentieth century demonstrate significant variation in the number of variables included in published Coastal Vulnerability Index (CVI) methodologies (Rocha et al, 2023). At the time, former researchers believed that the more variables there were, the more reliable the result would be.…”

Section: Introductionmentioning

confidence: 99%

Geomatics Assessment of Coastal Erosion Vulnerability: A Case Study of Agadir Bay, Morocco

FAJRI,

BEROHO,

LAMHADRI

et al. 2024

AgricultForest

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Coastal zones are characterized by a complex interaction between continental and marine ecosystems. They are often subject to anthropogenic and natural pressures such as urbanization, pollution, erosion, storms, and the impact of climate change. It is an environment that requires sustainable management to preserve its biodiversity and ecosystem services. This study focuses on assessing coastal vulnerability to erosion in the Bay of Agadir, one of Morocco's main tourist attractions. The methodology adopted is based on geomatic science such as GIS and geospatial remote sensing. This approach involved the preparation of a database for the study area, relating mainly to geomorphological parameters, topography, sea level rise, and shoreline change data. The latter was assessed using DSAS (Digital Shoreline Analysis System) tools and then all data were integrated into a GIS software to evaluate the Coastal Vulnerability Index (CVI). The first result shows that the EPR (endpoint rate) index reveals an erosion trend over the 8.3 km studied area. Over the 262 transects analyzed, the variations show a predominant erosion (92%) with rates of up to -13.5 m/year over 46 years. This justifies the use of the LRR (Linear Regression Rate-of-Change) index rather than the EPR for kinematic analysis of the coastline. The results of the CVI index show that 2.58 km of the coastal zone, and 1.68 km of the Bay are successively highly and very highly vulnerable to coastal erosion (20-60%). This study can be considered as a basic document, providing crucial information to guide decision-makers and planners in the implementation of effective coastal conservation strategies.

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Coastal indices to assess sea-level rise impacts - A brief review of the last decade

Cited by 20 publications

References 93 publications

Standing Watch: Baselining Predictable Events That Influence Maritime Operations in the Context of the UN’s Sustainable Development Goals

Standing Watch: Baselining Predictable Events That Influence Maritime Operations in the Context of the UN’s Sustainable Development Goals

Priority Setting and Resource Allocation in Coastal Local Government Marine Regulatory Reform: Application of Machine Learning in Resource Optimization

Geomatics Assessment of Coastal Erosion Vulnerability: A Case Study of Agadir Bay, Morocco

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