Coastal Risk Management Research Articles

Mapping coastal resilience: a Gis-based Bayesian network approach to coastal hazard identification for Queensland’s dynamic shorelines

Coastal regions worldwide face increasing threats from climate change-induced hazards, necessitating more accurate and comprehensive vulnerability assessment tools. This study introduces an innovative approach to coastal vulnerability assessment by integrating Bayesian Networks (BN) with the modern coastal vulnerability (CV) framework. The resulting BN-CV model was applied to Queensland's coastal regions, with a particular focus on tide-modified and tide-dominated beaches, which constitute over 85% of the studied area. The research methodology involved beach classification based on morphodynamic characteristics, spatial subdivision of Queensland's coast into 78 sections, and the application of the BN-CV model to analyze interactions between geomorphological features and oceanic dynamics. This approach achieved over 90% accuracy in correlating beach types with vulnerability factors, significantly outperforming traditional CVI applications. Key findings include the identification of vulnerability hotspots and the creation of detailed exposure and sensitivity maps for Gold Coast City, Redland City, Brisbane City, and the Sunshine Coast Regional area. The study revealed spatial variability in coastal vulnerability, providing crucial insights for targeted management strategies. The BN-CV model demonstrates superior precision and customization capabilities, offering a more nuanced understanding of coastal vulnerability in regions with diverse beach typologies. This research advocates for the adoption of the BN-CV approach to inform tailored coastal planning and management strategies, emphasizing the need for regular reassessments and sustained stakeholder engagement to build resilience against climate change impacts.Recommendations include prioritizing adaptive infrastructure in high-exposure areas like the Gold Coast, enhancing flood management in Brisbane, improving socio-economic adaptive capacity in Redland, and maintaining natural defences in Moreton Bay. This study contributes significantly to the field of coastal risk management, providing a robust tool for policymakers and coastal managers to develop more effective strategies for building coastal resilience in the face of climate change.

Coastal urban flood risk management: Challenges and opportunities − A systematic review

Generational mechanisms and spatio-temporal evolution patterns of Coastal urban flood risk involve complex interactions between climate change, sea level rise and human-induced factors, necessitating integrated adaptive flood management strategies to mitigate evolving vulnerabilities. This systematic review offers a thorough assessment of the challenges and strategic opportunities for sustainable adaptation in managing flood risk in Coastal urban areas. It integrates emerging innovative technologies and financial solutions to identify promising approaches to implement mitigation strategies and improve Coastal urban flood resilience. Enhancing governance and policy frameworks is crucial for the successful implementation of Coastal Urban Flood Risk Management (CUFRM) plans. An innovative participatory planning framework is developed to promote flood management practices which are socially inclusive and equitable. Funding for green infrastructure and nature-based solutions and the strategic use of public–private partnerships are effective methods for advancing sustainable flood risk management (FRM). The advancements in emerging technologies, such as artificial intelligence (AI), machine learning (ML), deep learning (DL), social media and digital twin technologies, provide dynamic and collaborative platforms for simulating flood scenarios and have potential to significantly improve CUFRM practices. In the end, a cross-country comparison of current practices in Australia, China, Netherlands, the UK and the USA reveals a diverse range of approaches and valuable insights derived from regional experiences. The review provides a comprehensive analysis for researchers, policymakers and practitioners aiming to improve flood resilience in coastal metropolitan regions by learning from effective UFRM approaches that enhance governance structures, infrastructure resilience and funding mechanisms.

Coastal rockfall characterisation and risk management on Wadjemup - Rottnest Island, Western Australia

Coastal rockfall characterisation and risk management on Wadjemup - Rottnest Island, Western Australia

O'Brien Award Winners: An Interview with Julie Rosati

An interview with Dr. Julie Roasi, the U.S. Army Corps of Engineers Engineer (USACE) Research & Develop- ment Center’s lead Technical Director (TD) for Civil Works Research & Development (R&D), and TD for Flood and Coastal Risk Management R&D.

Integration of fuzzy AHP and explainable AI for effective coastal risk management: A micro-scale risk analysis of tropical cyclones

The east coast of India, especially the coastal region of Odisha, is highly threatened by tropical cyclones. This study develops a detailed risk map for tropical cyclones in the coastal districts of Odisha at the micro level, focusing on the assessment of risk factors at the block level. Using a multi-criteria decision making (MCDM) approach, the study considers four primary risk components: Exposure, vulnerability, susceptibility, and mitigation options. The Explainable Artificial Intelligence (XAI) framework, which uses the XGBoost model in conjunction with SHAP values, is applied to identify and elucidate the factors influencing risk levels in 69 blocks. Results indicate that about 65% of the area is at high risk to tropical cyclone, especially in the northeastern and central regions. In particular, 32 blocks are classified as high to very high-risk zones. The study shows a contrast in risk levels, with blocks in the northeast and southeast at higher risk, while blocks in the southern regions such as Ganjam and Puri and in the central parts of Kendrapara and Baleswar districts are at lower risk. The findings from this study are crucial for local authorities to identify vulnerable areas and improve cyclone preparedness and risk management strategies in Odisha.

Policy priorities to enable engaged and transformational adaptation on the coast: Learning from practitioner experiences in England

Coastal communities and their environments are facing unprecedented changes, with climate change driving rising global mean sea level, exacerbating extreme sea level events, and increasing hazards. Whilst adaptations to change have been central to coastal life for millennia, climate change brings a speed and intensity of change not previously experienced. Researchers are noting that adaptations are needed that are large scale and systemic with significant changes to lives and livelihoods – Transformational Adaptations – yet there is little evidence of this in practice, and there remains an operationalisation gap between ambitions and actions. This paper uses a qualitative case study method to assess how existing policy may enable and inhibit local stakeholder involvement in transformational adaptation in English coastal flood and erosion risk management. Through twenty interviews with coastal management stakeholders, the capacity for local coastal management stakeholders to initiate transformational adaptation and the perceived involvement of residents are analysed. The results indicate that transformational adaptation remains a distant aspiration in the English coastal management system, with local stakeholders possessing limited capacity to initiate it. The perceived role for residents in adaptation processes is often focused on their being recipients of adaptation interventions, and there are a range of barriers to their further involvement. The paper concludes that despite the theoretical interest in transformational adaptation, there is limited evidence its implementation in English coastal flood and erosion risk management, and there are multiple priority areas for policy development to support capacity for engaged transformational adaptation practices in coastal management contexts.

Addressing risks to mental health from climate change: a policy capacity analysis of England

ABSTRACT Climate change and mental health are inextricably linked crises that demand urgent responses within the health sector and beyond. Mental health challenges associated with climate change are wide-ranging. They include depression, anxiety and post-traumatic stress resulting from increased exposure to extreme weather events, generalized climate anxiety and indirect impacts. However, there is a significant adaptation gap when it comes to addressing the mental health risks posed by climate change. Lack of capacity is frequently cited as a barrier to adaptation, yet ‘capacity’ covers many facets. This article examines the capacities of policy systems to design and implement adaptation initiatives for addressing the increasing risks to mental health posed by climate change. Focusing on England (UK) as an illustrative case study, this article deploys a policy capacity framework and draws on semi-structured interviews and policy document analysis. It identifies the ways that analytical, operational and political policy (in)capacities manifest across relevant policy areas, which include health, flood and coastal erosion risk management, spatial planning, natural environment and emergency management. Our analysis reveals that despite some strengths in analytical and political capacity, strained operational capacity is exacerbating and reinforcing adaptation gaps. We also demonstrate some of the complex interactions between different types of capacities that both enable and hamper adaptation. This article demonstrates the value of analysing policy capacity, and its potential in identifying and designing the necessary interventions to help circumvent a growing mental health crisis under climate change. Key policy insights In England, efforts to adapt to risks to mental health under climate change are supported through strong analytical capacity, involving research and knowledge generation, education and training, particularly in the mental health sector and Flood and Coastal Erosion Risk Management (FCERM). There is, however, room for improvement. Relatively strong political capacity, including advocacy and the role of policy champions, have led to increasing legitimation of the issue and fostered a growing policy landscape. However, some discernible gaps remain. There are significant weaknesses in operational capacity, restricting coordinated, preventative adaptation. This is partly due to significant resource constraints, and historic and current fragmentation within and between the health sector and others.

Challenges for compound coastal flood risk management in a warming climate: a case study of the Gulf Coast of the United States

Compound flooding (CF) events, driven by coincident/concurrent and mutually reinforcing factors such as heavy rainfall, storm surges, and river discharge, pose severe threats to coastal communities around the Globe. Moreover, the exacerbating influence of climate change and sea-level rise further amplifies these risks. This study delves into the complex and multifaceted issue of compound coastal flooding in two freshwater-influenced systems on the Gulf Coast of the United States – Southeast Texas and South Alabama. We first conduct a robust statistical analysis to evaluate the significance of non-stationarity, multi-dimensionality, and non-linearity of interactions among various drivers of CF. Second, to assess the extent to which current flood resilience policies and guidelines account for these characteristics of CF events, we perform a critical review of existing policy documents. The results of the statistical analysis reveal significant compounding and shifts in the statistics of flood drivers that emphasize the pressing need for a multi-mechanism, non-stationary approach to flood hazard assessment. We also found an evident lack of appropriate language/recommendation in policy documents of solid tools that systematically take non-stationarity, multi-dimensionality, and non-linearity of CF into account. By identifying the gaps between current policy measures and the detected complexities of CF, we seek to provide insights that can inform more effective flood resilience policies and design guidelines. Through this robust analysis, we aspire to bridge the divide between research and policy.

VedgeSat: An automated, open‐source toolkit for coastal change monitoring using satellite‐derived vegetation edges

AbstractPublic satellite platforms offer regular observations for global coastal monitoring and climate change risk management strategies. Unfortunately, shoreline positions derived from satellite imagery, representing changes in intertidal topography, are noisy and subject to tidal bias that requires correction. The seaward‐most vegetation boundary reflects a change indicator which shifts on event–decadal timescales, and informs coastal practitioners of storm damage, sediment availability and coastal landform health. We present and validate a new open‐source tool VedgeSat for identifying vegetation edges (VEs) from high (3 m) and moderate (10–30 m) resolution satellite imagery. The methodology is based on the CoastSat toolkit, with streamlined image processing using cloud‐based data management via Google Earth Engine. Images are classified using a newly trained vegetation‐specific neural network, and VEs are extracted at subpixel level using dynamic Weighted Peaks thresholding. We performed validation against ground surveys and manual digitisation of aerial imagery across eroding and accreting open coasts and estuarine environments at a site in Scotland. Smaller‐than‐pixel vegetation boundary detection was achieved across 83% of Sentinel‐2 imagery (Root Mean Square Error of 9.3 m). An overall RMSE of 19.0 m was achieved across Landsat 5 & 8, Sentinel‐2 and PlanetScope images. Performance varied by coastal geomorphology, with highest accuracies across sandy open coasts owing to high spectral contrast and less false positives from intertidal vegetation. The VedgeSat tool can be readily applied in tandem with waterlines near‐globally, to support adaptation decisions with historic coastal trends across the whole shoreface, even in normally data‐scarce areas.

Enhancing Coastal Risk Recognition: Assessing UAVs for Monitoring Accuracy and Implementation in a Digital Twin Framework

This paper addresses the intricate challenges of coastal management, particularly in rapidly forming tidal flats, emphasizing the need for innovative monitoring strategies. The dynamic coastal topography, exemplified by a newly formed tidal flat in Shanghai, underscores the urgency of advancements in coastal risk recognition. By utilizing a digital twin framework integrated with state-of-the-art unmanned aerial vehicles (UAVs), we systematically evaluate three configurations and identify the optimal setup incorporating real-time kinematics (RTK) and light detection and ranging (LiDAR). This UAV configuration excels in efficiently mapping the 3D coastal terrain. It has an error of less than 0.1 m when mapping mudflats at an altitude of 100 m. The integration of UAV data with a precise numerical ocean model forms the foundation of our dynamic risk assessment framework. The results showcase the transformative potential of the digital twin framework, providing unparalleled accuracy and efficiency in coastal risk recognition. Visualization through Unity Engine or Unreal Engine enhances accessibility, fostering community engagement and awareness. By predicting and simulating potential risks in real-time, this study offers a forward-thinking strategy for mitigating coastal dangers. This research not only contributes a comprehensive strategy for coastal risk management but also sets a precedent for the integration of cutting-edge technologies in safeguarding coastal ecosystems. The findings are significant in paving the way for a more resilient and sustainable approach to coastal management, addressing the evolving environmental pressures on our coastlines.

Stochastic properties of coastal flooding events – Part 2: Probabilistic analysis

Abstract. Low-intensity but high-frequency coastal flooding, also known as nuisance flooding, can negatively affect low-lying coastal communities with potentially large socioeconomic effects. Partially driven by wave runup, this type of flooding is difficult to predict due to the complexity of the processes involved. Here, we present the results of a probabilistic analysis of flooding events measured on an eroded beach at the Texas coast. A high-resolution time series of the flooded area was obtained from pictures using convolutional neural network (CNN)-based semantic segmentation methods, as described in the first part of this contribution. After defining flooding events using a peak-over-threshold method, we found that their size follows an exponential distribution. Furthermore, consecutive flooding events were uncorrelated at daily timescales but correlated at hourly timescales, as expected from tidal and day–night cycles. Our measurements confirm the broader findings of a recent multi-site investigation of the probabilistic structure of high-water events that used a semi-empirical formulation for wave runup. Indeed, we found a relatively good statistical agreement between our CNN-based empirical flooding data and predictions using total-water-level estimations. As a consequence, our work supports the validity of a relatively simple probabilistic model of high-frequency coastal flooding driven by wave runup that can be used in coastal risk management and landscape evolution models.

Talking ‘bout a revolution: resilience and coastal policy in England

ABSTRACT Sea defence policy in England has proven contentious in the early twenty-first century, with government willing to defend the coast only where it is considered cost effective and not minded to compensate people for any resulting abandonment of homes. Additional focus is brought to this position by the 2015 United Nations Sustainable Development Goals (SDGs) which reflect a growing emphasis on climate change effects and other environmental hazards, and the wellbeing of the current generation and those to come. This requires policy makers to seek to balance economic, social and environmental dimensions, and to tackle inequalities; with a central commitment of the goals to “leave no one behind”. Subsequent to publication of the SDGs, England was promised a revolution in the government’s approach to Flood and Coastal Erosion Risk Management (FCERM). This paper seeks to understand the nature of this revolution with particular regard to extant issues around just governance. It finds that policy fails to deal with issues over the local acceptability of proposals for change and the bearing of risk, and instead lies principally in the elevation of the problematic concept of resilience and an accompanying ambivalence towards ideas of sustainability and sustainable development. International agreement that compensation should be paid to those countries suffering the worst effects of climate change, including sea level rise, suggests that adoption of a similar approach to vulnerable homeowners might be the more appropriate revolution and bring policy more into line with the aspirations of the SDGs.

Is the coastal future green, grey or hybrid? Diverse perspectives on coastal flood risk management and adaptation in the UK

Abstract Climate change-induced sea level rise has exacerbated coastal change putting millions of people at risk from coastal hazards, such as flooding and coastal erosion. Nature-based solutions have been recognised as an opportunity to simultaneously address the coastal hazard risks and achieve biodiversity goals. While such solutions are included in climate adaptation strategies, “hard” engineered solutions are still often preferred by those implementing the schemes. We sought to explore the diverse perspectives on UK coastal flood risk management among interested and/or affected groups by utilising the Q-methodology. We identified five perspectives: (1) The Pro-Green Practitioners; (2) The Future-Planning Relocators; (3) The Case-by-Case Thinkers; (4) The Cautious Practitioners and (5) The Climate Change Concerned. All five perspectives strongly valued the co-benefits of nature-based solutions and their role in coastal risk reduction. None of the perspectives prioritised hard-engineered solutions as the primary flood protection strategy in the UK, though they recognised their role in protecting essential infrastructure. The main disagreements between perspectives were (1) on the need for relocation strategies, and (2) whether nature-based solutions could cause social inequalities. The Q-methodology does not identify how prevalent such perspectives are, thus further research is needed to assess the social acceptance of nature-based solutions.

State of the shoreline since Hurricane Sandy: Summary of changes at New Jersey Beach Profile Network (NJBPN) sites

Following the devastating impacts from Hurricane Sandy in October 2012, Congress passed Public Law 113-2 in January 2013 which provided the funding for the U.S. Army Corps of Engineers (USACE) to restore authorized federal coastal storm risk management projects in New Jersey to their original design templates. Between 2013 and 2016, approximately 28.3 million cubic yards of sand were used to rebuild the beaches and dunes along 92.7 miles of the 127-mile Atlantic Ocean shoreline (an average of 283,290 cubic yards per mile). Between 2017 and 2019, initial federal beachfill had been completed at the northern Ocean County beaches (an additional 11 million cubic yards). A review of the changes to the New Jersey Beach Profile Network (NJBPN) locations indicates that this influx of sand benefitted nearly all shorelines as well as former erosion hot spots. Examples are provided from each of the four counties (Monmouth, Ocean, Atlantic, Cape May) to show trends in profile volume and shoreline position. State support of beach nourishment continues through the efforts of the New Jersey Department of Environmental Protection and its Office of Coastal Engineering.

Planning and design of three USACE New York District projects

The United States Army Corps of Engineers (USACE) New York District (NYD) has had a tremendous impact on an approximately $6 billion comprehensive coastal storm risk management program in the last 10 years since Hurricane Sandy caused significant damage in the New York (NY) and New Jersey (NJ) area. There was 2013- 2014 emergency repair and restoration to existing beach nourishment and navigation projects, but also USACE NYD accomplished the planning and design for multiple coastal storm risk management projects in the NY and NJ area. Of those projects, specific coastal risk reduction features are described for the Sea Bright to Manasquan, NJ; East Rockaway Inlet to Rockaway Inlet, NY; and Montauk Point Lighthouse Stabilization, NY. The planning and design for these projects exemplifies resilience principles and planned adaptability to withstand the challenges of the dynamic coastal environment. The USACE NYD is faced with numerous challenges such as environmental restrictions, politics, real estate, sea level change, etc.; the magnitude of coastal planning, design and construction that has occurred over these past 10 years for the NYD studies and projects demonstrates the fortitude of collaboration combined with current and innovative engineering principles.

Comparative Analysis of BALSSA and Conventional NWP Methods: A Case Study in Extreme Storm Surge Prediction in Macao

In coastal regions, accurate storm surge prediction is crucial for effective disaster management and risk mitigation. This study presents a comparative analysis between BALSSA (Bidirectional Attention-based LSTM for Storm Surge Architecture) and the Japan Meteorological Agency (JMA) numerical storm surge model, focusing on the Saola-induced storm surge in Macao, September 2023. To train and assess the model, we leverage an extensive dataset comprising meteorological and tide level information from more than 80 typhoon occurrences in Macao spanning the period from 2017 to 2023. The results provide evidence of BALSSA’s effectiveness in capturing the complex spatio-temporal dynamics of storm surges, with a lead time of up to 72 h, as reflected by its MAE of 0.019 and RMSE of 0.024. It demonstrates reliable accuracy in predicting storm surge magnitude, timing, and spatial extent, potentially contributing to more precise and timely warnings for coastal communities. Furthermore, the real-time data assimilation feature of BALSSA ensures up-to-date information, aligned with the latest observations, which is essential for effective emergency preparedness and response. The high-resolution grids enhance risk assessment, highlighting BALSSA’s potential for early warnings, emergency planning, and coastal risk management. This study contributes valuable insights to the broader field of storm surge prediction, guiding decision-making processes and supporting the development of effective strategies to enhance coastal resilience.

Sea-Level Rise in Pakistan: Recommendations for Strengthening Evidence-Based Coastal Decision-Making

Pakistan is vulnerable to a range of climate hazards, including sea-level rise. The Indus Delta region, situated in the coastal Sindh province, is particularly at risk of sea-level rise due to low-lying land and fragile ecosystems. In this article, expertise is drawn together from the newly established Pakistan Sea-Level Working Group, consisting of policy experts, scientists, and practitioners, to provide recommendations for future research, investment, and coastal risk management. An assessment of the current scientific understanding of sea-level change and coastal climate risks in Pakistan highlights an urgent need to improve the availability and access to sea-level data and other coastal measurements. In addition, reflecting on the policy environment and the enablers needed to facilitate effective responses to future sea-level change, recommendations are made to integrate coastal climate services into the National Adaptation Plan and develop a National Framework for Climate Services. Such a framework, alongside collaboration, co-production, and capacity development, could help support required improvements in coastal observations and monitoring and continuously deliver useful, usable, and accessible sea-level information for use by practitioners and decision-makers.

Supporting Informed Public Reactions to Shipping Incidents with Oil Spill Potential: An Innovative Electronic Platform

The analysis of the 2002 Prestige tanker accident showed how public misinformation can worsen marine pollution incidents, rendering their management suboptimal as these evolve, thus raising the issue of appropriately informing and educating coastal and island populations who are at risk. Two decades later, developments in electronic platforms, including Geographic Information Systems (GIS), the Automatic Identification System (AIS) for ship signal transmission, and social media, provide a set of means for public monitoring of such incidents, creating the possibility to antagonise effectively erroneous or malevolent information, which can hinder efficient actions for containing marine pollution risks even without active training of the populations concerned. The authors, in the framework of the development of the Marine Coastal Observatory and Risk Management project “AEGIS+”, have developed E-S.A.V.E., an online innovative platform that (a) meets the needs of different users as revealed by a survey run across groups of them, (b) uses a suitable Geographic Information System (GIS) environment, (c) cooperates with public authorities, for the reliable update of automated systems, and (d) employs an artificial intelligence (AI)-supported tool for social media monitoring; the platform also provides educational resources and information on national and international resources on marine environmental protection and sustainable maritime logistics.

Multi-model chain for climate change scenario analysis to support coastal erosion and water quality risk management for the Metropolitan city of Venice

Under the influence of anthropogenic climate change, hazardous climate and weather events are increasing in frequency and severity, with wide-ranging impacts across ecosystems and landscapes, especially fragile and dynamic coastal zones. The presented multi-model chain approach combines ocean hydrodynamics, wave fields, and shoreline extraction models to build a Bayesian Network-based coastal risk assessment model for the future analysis of shoreline evolution and seawater quality (i.e., suspended particulate matter, diffuse attenuation of light). In particular, the model was designed around a baseline scenario exploiting historical shoreline and oceanographic data within the 2015–2017 timeframe. Shoreline erosion and water quality changes along the coastal area of the Metropolitan city of Venice were evaluated for 2021–2050, under the RCP8.5 future scenario. The results showed a destabilizing trend in both shoreline evolution and seawater quality under the selected climate change scenario. Specifically, after a stable period (2021–2030), the shoreline will be affected by periods of erosion (2031–2040) and then accretion (2041–2050), with a simultaneous decrease in seawater quality in terms of higher turbidity. The decadal analysis and sensitivity evaluation of the input variables demonstrates a strong influence of oceanographic variables on the assessed endpoints, highlighting how the factors are strongly connected.The integration of regional and global climate models with Machine Learning and satellite imagery within the proposed multi-model chain represents an innovative update on state-of-the-art techniques. The validated outputs represent a good promise for better understanding the varying impacts due to future climate change conditions (e.g., wind, wave, tide, and sea-level). Moreover, the flexibility of the approach allows for the quick integration of climate and multi-risk data as it becomes available, and would represent a useful tool for forward-looking coastal risk management for decision-makers.

Estimation of skew surge uncertainties when predicting tides in the past

The study of storm surges and more generally of extreme events is a subject of growing interest in the current context of coastal risk management in a changing climate. Recent studies show that the consideration of past events improves statistical models. In this context, important investigations have been carried out in the last decade to retrieve and quantify water levels and skew surges associated with historical events for the 18th or 19th century. The estimation of the historical surges depends on the calculated tidal prediction, and therefore directly on the tidal components and the mean sea level of the period under consideration.Still, as tidal constituents and mean sea level change over time, it is difficult to estimate these parameters for historical events when sea level data are missing or incomplete. Two cases are considered for calculating tidal predictions. Either short time series are available contemporary to the event of interest, allowing a harmonic analysis and subsequent calculation of tidal constituents and mean sea levels. Or there are no or insufficient contemporary data available for the event of interest and current tidal characteristics are used in combination with a mean sea level adjustment. The present study aims to answer the following questions: depending on the data available for a historical event, which tidal constituents and mean sea level should be used when considering events that occurred several decades or even centuries ago? To what extent does the length of the observation series used in the harmonic analysis influence the tidal predictions? How does a mean sea level correction affect tidal predictions made with current tidal components? Finally, what are the uncertainties associated with the estimation of historical extreme skew surges, when there are not enough contemporary observations to estimate tidal components?Two methods are considered to estimate the uncertainties associated with the calculation of tidal predictions. Either the use of contemporary tidal constituents and mean sea level or the use of current tidal constituents corrected for mean sea level. In this study, 14 sea level records of 100 years or more provided by the Global Extreme Sea Level Analysis (GESLA version 3) were analysed. First, the uncertainties of the astronomical tides are assessed. For this purpose, different lengths of observations are implemented in a harmonic analysis and the resulting tidal constituents and tidal predictions are compared. In a second step, current tidal constituents are used for past tidal predictions and a mean sea level trend is inferred to cope with sea level variations. Different time periods are used to estimate the mean sea level trend and their influence on the tidal predictions is analysed. Furthermore, these two methods are combined to study the effects on the estimated skew surges and to assess the associated uncertainties.This study shows that uncertainties of less than 10 cm can be obtained for skew surges by using contemporary tidal components calculated from at least two years of observations. Larger differences are obtained for microtidal or river-influenced sites. When using current tidal constituents and adjusting a mean sea level trend, linear trend correction gives reliable results when more than 60 years of data are used for the trend estimation. In this case, the extreme skew surges obtained are within a range of more or less 5 cm. Finally, on the basis of the results presented, some suggestions are made on the possible applications of these methods according to the availability of data, stressing the importance of site-specific studies.