EARLIEST DETECTION OF SEA-LEVEL RISE ACCELERATIONS TO INFORM UPGRADE/REPLACEMENT OF COASTAL FLOOD DEFENSE INFRASTRUCTURE

2019 ◽  
Author(s):  
ROBERT J. NICHOLLS ◽  
IVAN D. HAIGH ◽  
HAGEN RADTKE ◽  
FRANCISCO CALAFAT ◽  
PAOLO CIPOLLINI ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Coastal Flood ◽  
Flood Defense

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 Modelling Coastal Flood Propagation under Sea Level Rise: A Case Study in Maria, Eastern Canada

Geosciences ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 76 ◽  
Author(s):  
David Didier ◽  
Marion Bandet ◽  
Pascal Bernatchez ◽  
Dany Dumont
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Overland Flow ◽  
Water Levels ◽  
Model Complexity ◽  
Flood Mapping ◽  
Eastern Canada ◽  
Coastal Flood ◽  
The Impact ◽  
Flow Velocities

Coastal management often relies on large-scale flood mapping to produce sea level rise assessments where the storm-related surge is considered as the most important hazard. Nearshore dynamics and overland flow are also key parameters in coastal flood mapping, but increase the model complexity. Avoiding flood propagation processes using a static flood mapping is less computer-intensive, but generally leads to overestimation of the flood zone, especially in defended urban backshore. For low-lying communities, sea level rise poses a certain threat, but its consequences are not only due to a static water level. In this paper, the numerical process-based model XBeach is used in 2D hydrodynamic mode (surfbeat) to reproduce an observed historical flood in Maria (eastern Canada). The main goal is to assess the impacts of a future storm of the same magnitude in the horizon 2100 according to an increase in sea level rise. The model is first validated from in situ observations of waves and water levels observed on the lower foreshore. Based on field observations of a flood extent in 2010, the simulated flooded area was also validated given a good fit (59%) with the actual observed flood. Results indicate that the 2010 storm-induced surge generated overwash processes on multiple areas and net landward sediment transport and accumulation (washover lobes). The flood was caused by relatively small nearshore waves (Hs < 1 m), but despite small water depth (>1.2 m), high flow velocities occurred in the main street (U > 2 m/s) prior to draining in the salt marsh. The impact of sea level rise on the low-lying coastal community of Maria could induce a larger flood area in 2100, deeper floodwater, and higher flow velocities, resulting in higher hazard for the population.

A composite method for past events characterisation providing insights in past, present and future coastal flood hazards: Joining historical, statistical and modeling approaches

2020 ◽  
Author(s):  
Deborah Idier ◽  
Jeremy Rohmer ◽  
Rodrigo Pedreros ◽  
Sylvestre Le Roy ◽  
Jerome Lambert ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Meteorological Data ◽  
Critical Conditions ◽  
Flood Hazards ◽  
Flood Events ◽  
Coastal Flood ◽  
Set Up ◽  
Offshore Wave

&lt;p&gt;The characterisation of past coastal flood events is crucial for risk prevention. However, it is limited by the partial character of historical information on flood events and the lack or limited quality of past hydro-meteorological data. In addition coastal flood processes are complex, driven by many hydro-meteorological processes, making mechanisms and probability analysis challenging. These issues are tackled by joining historical, statistical and modelling approaches. We focus on a macrotidal site (G&amp;#226;vres, France) subject to overtopping and investigate the 1900-2010 period. A continuous hydro-meteorological database is built and a damage event database is set up based on archives, newspapers, maps and aerial photographies. Using together historic information, hindcasts and hydrodynamic models, we identified 9 flood events, among which 5 significant flood events (4 with high confidence: 1924, 1978, 2001, 2008; 1 with a lower confidence: 1904). These flood events are driven by the combination of sea-level rise, tide, atmospheric surge, offshore wave conditions and local wind. The critical conditions leading to flood are further analysed, including the effect of coastal defences, showing that the present coastal defences would not have allowed to face the hydro-meteorological conditions of 09/02/1924 for instance, whose bi-variate return periods of exceedance Tr (still water level relative to the mean sea level and significant wave height) is larger than 1000 y. In addition, Tr is expected to significantly decrease with the sea-level rise, reaching values smaller than 1 y, for 8 of the 9 historical events, for a sea-level rise of 0.63 m, which is equal to the median amount of sea-level rise projected by the 5&lt;sup&gt;th&lt;/sup&gt; Assessment Report of the IPCC in this region for RCP8.5 in 2100.&lt;/p&gt;

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 A global analysis of subsidence, relative sea-level change and coastal flood exposure

2021 ◽  
Author(s):  
Daniel Lincke ◽  
Robert J. Nicholls ◽  
Jochen Hinkel ◽  
Sally Brown ◽  
Athanasios T. Vafeidis ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Global Analysis ◽  
Relative Sea Level ◽  
Sea Levels ◽  
Coastal Flood ◽  
Global Issue ◽  
Flood Exposure ◽  
Relative Sea Level Rise ◽  
Global Sea Level

&lt;p&gt;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.&lt;/p&gt;

Dynamic risk of coastal flood and driving factors: Integrating local sea level rise and spatially explicit urban growth

2021 ◽  
pp. 129039
Author(s):  
Lilai Xu ◽  
Shenghui Cui ◽  
Xiaoming Wang ◽  
Jianxiong Tang ◽  
Vilas Nitivattananon ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Urban Growth ◽  
Driving Factors ◽  
Spatially Explicit ◽  
Coastal Flood ◽  
Dynamic 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 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
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Flood Risk ◽  
Population Change ◽  
Opportunity To Learn ◽  
Population Data ◽  
Population Exposure ◽  
Coastal Flood ◽  
Flood Exposure ◽  
And Sea Level

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.

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