scholarly journals Estimating the long-term historic evolution of exposure to flooding of coastal populations

2015 ◽  
Vol 15 (6) ◽  
pp. 1215-1229 ◽  
Author(s):  
A. J. Stevens ◽  
D. Clarke ◽  
R. J. Nicholls ◽  
M. P. Wadey

Abstract. Coastal managers face the task of assessing and managing flood risk. This requires knowledge of the area of land, the number of people, properties and other infrastructure potentially affected by floods. Such analyses are usually static; i.e. they only consider a snapshot of the current situation. This misses the opportunity to learn about the role of key drivers of historical changes in flood risk, such as development and population rise in the coastal flood plain, as well as sea-level rise. In this paper, we develop and apply a method to analyse the temporal evolution of residential population exposure to coastal flooding. It uses readily available data in a GIS environment. We examine how population and sea-level change have modified exposure over two centuries in two neighbouring coastal sites: Portsea and Hayling Islands on the UK south coast. The analysis shows that flood exposure changes as a result of increases in population, changes in coastal population density and sea level rise. The results indicate that to date, population change is the dominant driver of the increase in exposure to flooding in the study sites, but climate change may outweigh this in the future. A full analysis of changing flood risk is not possible as data on historic defences and wider vulnerability are not available. Hence, the historic evolution of flood exposure is as close as we can get to a historic evolution of flood risk. The method is applicable anywhere that suitable floodplain geometry, sea level and population data sets are available and could be widely applied, and will help inform coastal managers of the time evolution in coastal flood drivers.

2015 ◽  
Vol 3 (2) ◽  
pp. 1681-1715 ◽  
Author(s):  
A. J. Stevens ◽  
D. Clarke ◽  
R. J. Nicholls ◽  
M. P. Wadey

Abstract. Coastal managers face the task of assessing and managing flood risk. This requires knowledge of the area of land, the number of people, properties and other infrastructure potentially affected by floods. Such analyses are usually static; i.e. they only consider a snapshot of the current situation. This misses the opportunity to learn about the role of key drivers of historical changes in flood risk, such as development and population rise in the coastal flood plain and sea-level rise. In this paper, we develop and apply a method to analyse the temporal evolution of residential population exposure to coastal flooding. It uses readily available data in a GIS environment. We examine how population and sea level change modify exposure over two centuries in two neighbouring coastal sites: Portsea and Hayling Islands on the UK south coast. The analysis shows that flood exposure changes as a result of increases in population, changes in coastal population density and sea level rise. The results indicate that to date, population change is the dominant driver of the increase in exposure to flooding in the study sites, but climate change may outweigh this in the future. A full analysis of flood risk is not possible as data on historic defences and wider vulnerability are not available. Hence, the historic evolution of flood exposure is as close as we can get to a historic evolution of flood risk. The method is applicable anywhere that suitable floodplain geometry, sea level and population datasets are available and could be widely applied, and will help inform coastal managers of the time evolution in coastal flood drivers.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
A. Hooijer ◽  
R. Vernimmen

AbstractCoastal flood risk assessments require accurate land elevation data. Those to date existed only for limited parts of the world, which has resulted in high uncertainty in projections of land area at risk of sea-level rise (SLR). Here we have applied the first global elevation model derived from satellite LiDAR data. We find that of the worldwide land area less than 2 m above mean sea level, that is most vulnerable to SLR, 649,000 km2 or 62% is in the tropics. Even assuming a low-end relative SLR of 1 m by 2100 and a stable lowland population number and distribution, the 2020 population of 267 million on such land would increase to at least 410 million of which 72% in the tropics and 59% in tropical Asia alone. We conclude that the burden of current coastal flood risk and future SLR falls disproportionally on tropical regions, especially in Asia.


2008 ◽  
Vol 55 (12) ◽  
pp. 1062-1073 ◽  
Author(s):  
Matthew J. Purvis ◽  
Paul D. Bates ◽  
Christopher M. Hayes

2006 ◽  
Vol 32 (2) ◽  
pp. 194-211 ◽  
Author(s):  
Tim L Webster ◽  
Donald L Forbes ◽  
Edward MacKinnon ◽  
Daniel Roberts

2016 ◽  
Vol 137 (3-4) ◽  
pp. 347-362 ◽  
Author(s):  
Maya K. Buchanan ◽  
Robert E. Kopp ◽  
Michael Oppenheimer ◽  
Claudia Tebaldi

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 774
Author(s):  
Jeremy Rohmer ◽  
Daniel Lincke ◽  
Jochen Hinkel ◽  
Gonéri Le Cozannet ◽  
Erwin Lambert ◽  
...  

Global scale assessments of coastal flood damage and adaptation costs under 21st century sea-level rise are associated with a wide range of uncertainties, including those in future projections of socioeconomic development (shared socioeconomic pathways (SSP) scenarios), of greenhouse gas concentrations (RCP scenarios), and of sea-level rise at regional scale (RSLR), as well as structural uncertainties related to the modelling of extreme sea levels, data on exposed population and assets, and the costs of flood damages, etc. This raises the following questions: which sources of uncertainty need to be considered in such assessments and what is the relative importance of each source of uncertainty in the final results? Using the coastal flood module of the Dynamic Interactive Vulnerability Assessment modelling framework, we extensively explore the impact of scenario, data and model uncertainties in a global manner, i.e., by considering a large number (>2000) of simulation results. The influence of the uncertainties on the two risk metrics of expected annual damage (EAD), and adaptation costs (AC) related to coastal protection is assessed at global scale by combining variance-based sensitivity indices with a regression-based machine learning technique. On this basis, we show that the research priorities in terms of future data/knowledge acquisition to reduce uncertainty on EAD and AC differ depending on the considered time horizon. In the short term (before 2040), EAD uncertainty could be significantly decreased by 25 and 75% if the uncertainty of the translation of physical damage into costs and of the modelling of extreme sea levels could respectively be reduced. For AC, it is RSLR that primarily drives short-term uncertainty (with a contribution ~50%). In the longer term (>2050), uncertainty in EAD could be largely reduced by 75% if the SSP scenario could be unambiguously identified. For AC, it is the RCP selection that helps reducing uncertainty (up to 90% by the end of the century). Altogether, the uncertainty in future human activities (SSP and RCP) are the dominant source of the uncertainty in future coastal flood risk.


2021 ◽  
Author(s):  
Daniel Lincke ◽  
Robert J. Nicholls ◽  
Jochen Hinkel ◽  
Sally Brown ◽  
Athanasios T. Vafeidis ◽  
...  

<p>Climate-induced sea-level rise and vertical land movements, including natural and human-induced subsidence in sedimentary coastal lowlands, combine to change relative sea levels around the world's coast. Global-average coastal relative sea-level rise was 2.5 mm/yr over the last two decades. However, as coastal inhabitants are preferentially located in subsiding locations, they experience an average relative sea-level rise up to four times faster at 7.8 to 9.9 mm/yr. This first global quantification of relative sea-level rise shows that the resulting impacts, and adaptation needs are much higher than reported global sea-level rise measurements would suggest. Hence, coastal subsidence is an important global issue that needs more assessment and action. In particular, human-induced subsidence in and surrounding coastal cities can be rapidly reduced with appropriate policy measures for groundwater utilization and drainage. This offers substantial and rapid benefits in terms of reducing growth of coastal flood exposure due to relative sea-level rise.</p>


2020 ◽  
Vol 20 (4) ◽  
pp. 1025-1044 ◽  
Author(s):  
Timothy Tiggeloven ◽  
Hans de Moel ◽  
Hessel C. Winsemius ◽  
Dirk Eilander ◽  
Gilles Erkens ◽  
...  

Abstract. Coastal flood hazard and exposure are expected to increase over the course of the 21st century, leading to increased coastal flood risk. In order to limit the increase in future risk, or even reduce coastal flood risk, adaptation is necessary. Here, we present a framework to evaluate the future benefits and costs of structural protection measures at the global scale, which accounts for the influence of different flood risk drivers (namely sea-level rise, subsidence, and socioeconomic change). Globally, we find that the estimated expected annual damage (EAD) increases by a factor of 150 between 2010 and 2080 if we assume that no adaptation takes place. We find that 15 countries account for approximately 90 % of this increase. We then explore four different adaptation objectives and find that they all show high potential in cost-effectively reducing (future) coastal flood risk at the global scale. Attributing the total costs for optimal protection standards, we find that sea-level rise contributes the most to the total costs of adaptation. However, the other drivers also play an important role. The results of this study can be used to highlight potential savings through adaptation at the global scale.


2019 ◽  
Author(s):  
Timothy Tiggeloven ◽  
Hans de Moel ◽  
Hessel C. Winsemius ◽  
Dirk Eilander ◽  
Gilles Erkens ◽  
...  

Abstract. Coastal flood hazard and exposure are expected to increase over the course of the 21st century, leading to increased coastal flood risk. In order to limit the increase in future risk, or even reduce coastal flood risk, adaptation is necessary. Here, we present a framework to evaluate the future benefits and costs of structural protection measures at the global scale, which accounts for the influence of different flood risk drivers (namely: sea-level rise, subsidence, and socioeconomic change). Globally, we find that the estimated expected annual damage (EAD) increases by a factor of 150 between 2010 and 2080, if we assume that no adaptation takes place. We find that 15 countries account for approximately 90 % of this increase. We then explore four different adaptation objectives and find that they all show high potential to cost-effectively reduce (future) coastal flood risk at the global scale. Attributing the total costs for optimal protection standards, we find that sea-level rise contributes the most to the total costs of adaptation. However, the other drivers also play an important role. The results of this study can be used to highlight potential savings through adaptation at the global scale.


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