scholarly journals Deep Uncertainties in Sea‐Level Rise and Storm Surge Projections: Implications for Coastal Flood Risk Management

Risk Analysis ◽  
2017 ◽  
Vol 40 (1) ◽  
pp. 153-168 ◽  
Author(s):  
Perry C. Oddo ◽  
Ben S. Lee ◽  
Gregory G. Garner ◽  
Vivek Srikrishnan ◽  
Patrick M. Reed ◽  
...  
Keyword(s):  
Risk Management ◽  
Sea Level Rise ◽  
Sea Level ◽  
Storm Surge ◽  
Flood Risk ◽  
Flood Risk Management ◽  
Coastal Flood ◽  
Coastal Flood Risk

scholarly journals What has changed in France in coastal flood risk management after Xynthia storm

2014 ◽  
Vol 46 (3) ◽  
pp. 181-196
Author(s):  
Jean Cunge ◽  
Marc Erlich
Keyword(s):  
Risk Management ◽  
Storm Surge ◽  
Flood Risk ◽  
Atlantic Coast ◽  
Flood Risk Management ◽  
National Plan ◽  
Catastrophic Event ◽  
Coastal Flood ◽  
Coastal Flood Risk ◽  
One Year

Abstract What has changed in France in coastal flood risk management after Xynthia storm. One year after the Xynthia storm surge, which struck the Vendée and the Charente-Maritime counties of the French Atlantic Coast in the night of 27/28 February 2010, French authorities implemented a national plan for mitigation and management of the fl ash submersions (MEDDTL 2011). In this paper authors analyse partial results of this plan after almost three years of its effectiveness in the perspective of Xynthia catastrophic event, but also taking into account other dramatic coastal submersions, which occured during winter 2014 in the same region.

scholarly journals Global LiDAR land elevation data reveal greatest sea-level rise vulnerability in the tropics

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
A. Hooijer ◽  
R. Vernimmen
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Flood Risk ◽  
Land Area ◽  
Area At Risk ◽  
Population Number ◽  
Coastal Flood ◽  
Elevation Data ◽  
Coastal Flood Risk ◽  
The Tropics

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.

A probabilistic methodology to estimate future coastal flood risk due to sea level rise

2008 ◽  
Vol 55 (12) ◽  
pp. 1062-1073 ◽  
Author(s):  
Matthew J. Purvis ◽  
Paul D. Bates ◽  
Christopher M. Hayes
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Flood Risk ◽  
Coastal Flood ◽  
Coastal Flood Risk

scholarly journals Allowances for evolving coastal flood risk under uncertain local sea-level rise

2016 ◽  
Vol 137 (3-4) ◽  
pp. 347-362 ◽  
Author(s):  
Maya K. Buchanan ◽  
Robert E. Kopp ◽  
Michael Oppenheimer ◽  
Claudia Tebaldi
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Flood Risk ◽  
Coastal Flood ◽  
Coastal Flood Risk

scholarly journals Unravelling the Importance of Uncertainties in Global-Scale Coastal Flood Risk Assessments under Sea Level Rise

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 774
Author(s):  
Jeremy Rohmer ◽  
Daniel Lincke ◽  
Jochen Hinkel ◽  
Gonéri Le Cozannet ◽  
Erwin Lambert ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Flood Risk ◽  
Global Scale ◽  
Short Term ◽  
Sea Levels ◽  
Coastal Flood ◽  
Extreme Sea Levels ◽  
Coastal Flood Risk ◽  
Adaptation Costs

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.

scholarly journals Global-scale benefit–cost analysis of coastal flood adaptation to different flood risk drivers using structural measures

2020 ◽  
Vol 20 (4) ◽  
pp. 1025-1044 ◽  
Author(s):  
Timothy Tiggeloven ◽  
Hans de Moel ◽  
Hessel C. Winsemius ◽  
Dirk Eilander ◽  
Gilles Erkens ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Flood Risk ◽  
Flood Hazard ◽  
Global Scale ◽  
Protection Measures ◽  
Benefit Cost Analysis ◽  
Coastal Flood ◽  
Expected Annual Damage ◽  
Coastal Flood Risk

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.

scholarly journals Coastal-flood risk management in central Algarve: Vulnerability and flood risk indices (South Portugal)

2016 ◽  
Vol 71 ◽  
pp. 302-316 ◽  
Author(s):  
A.M. Martínez-Graña ◽  
T. Boski ◽  
J.L. Goy ◽  
C. Zazo ◽  
C.J. Dabrio
Keyword(s):  
Risk Management ◽  
Flood Risk ◽  
Flood Risk Management ◽  
Coastal Flood ◽  
Risk Indices ◽  
Coastal Flood Risk ◽  
South Portugal
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