Estimating coastal recession due to sea level rise: beyond the Bruun rule

Ranasinghe, Roshanka; Callaghan, David P.; Stive, M.J.F.

doi:10.1007/s10584-011-0107-8

Cited by 210 publications

(199 citation statements)

References 22 publications

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“…The quantification of the local probabilities of failure is input for any probabilistic dike safety assessment or probabilistic design. These results become even more relevant in cases of dike concepts such as the unbreachable dike and the multi-functional flood defence [51] which are designed to cope with climate change [5] and to withstand large amounts of overflow and storms similar or larger than the largest ones tested in this study.…”

Section: Applications Of the Probabilistic Methodsmentioning

confidence: 83%

“…For rivers, extreme water levels occur more frequently as shown for the River Rhine basin [4], for example. Such climate change effects increase the risk of flooding of low lying, highly populated areas around world [5,6]. In the last decades, flood defence design has moved towards a risk-based approach [7,8] in which it is possible to express the design parameters uncertainty as probabilistic distributions [8].…”

Section: Introductionmentioning

confidence: 99%

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Failure of Grass Covered Flood Defences with Roads on Top Due to Wave Overtopping: A Probabilistic Assessment Method

Lopez

Warmink²,

Bomers³

et al. 2018

JMSE

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Abstract:Hard structures, i.e., roads, are commonly found over flood defences, such as dikes, in order to ensure access and connectivity between flood protected areas. Several climate change future scenario studies have concluded that flood defences will be required to withstand more severe storms than the ones used for their original design. Therefore, this paper presents a probabilistic methodology to assess the effect of a road on top of a dike: it gives the failure probability of the grass cover due to wave overtopping over a wide range of design storms. The methodology was developed by building two different dike configurations in computational fluid dynamics Navier-Stokes solution software; one with a road on top and one without a road. Both models were validated with experimental data collected from field-scale experiments. Later, both models were used to produce data sets for training simpler and faster emulators. These emulators were coupled to a simplified erosion model which allowed testing storm scenarios which resulted in local scouring conditioned statistical failure probabilities. From these results it was estimated that the dike with a road has higher probabilities (5 × 10 −5 > P f >1 × 10 −4 ) of failure than a dike without a road (P f < 1 × 10 −6 ) if realistic grass quality spatial distributions were assumed. The coupled emulator-erosion model was able to yield realistic probabilities, given all the uncertainties in the modelling process and it seems to be a promising tool for quantifying grass cover erosion failure.

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Section: Applications Of the Probabilistic Methodsmentioning

confidence: 83%

Section: Introductionmentioning

confidence: 99%

Failure of Grass Covered Flood Defences with Roads on Top Due to Wave Overtopping: A Probabilistic Assessment Method

Lopez

Warmink²,

Bomers³

et al. 2018

JMSE

View full text Add to dashboard Cite

show abstract

“…Cooper and Pilkey (2004) concluded that the assumptions to be satisfied for applying this model are very restrictive and, in consequence it should only likely to be applicable on a small number of coasts. Ranasinghe et al (2012) proposed a probabilistic model based on governing physical processes to estimate coastal erosion (PCR) due to SLR. However, these authors explicitly stated that "several simplifying assumptions in the model need to be rigorously evaluated" and some elements of the model need to be defined using empirical evidence that are often absent (e.g.…”

Section: Shoreline Retreatmentioning

confidence: 99%

Impacts of sea-level rise-induced erosion on the Catalan coast

et al. 2016

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The Catalan coast as most of the developed Mediterranean coastal zone is characterized by the coincidence of stresses and pressures on the natural system with a high exposure and low adaptive capacity. Due to this, Climate Change-induced effects will increase natural hazards and aggravate their associated impacts and, in consequence, it is necessary to assess their effects for proper long-term management. In this work, we assess the impact of sea-level rise (SLR) induced shoreline retreat on the Catalan coast for three scenarios ranging from 0.53 m to 1.75 m by the year 2100. Implications are analyzed in terms of affectation of two main functions provided by beaches, i.e. recreation and protection. Obtained results show that CC will be a serious threat to analyzed functions since the expected enhanced shoreline retreat will severely decrease the recreational carrying capacity and, the capacity of protection in the near future under tested scenarios. The actual level of development along the coastal zone reduces the natural resilient capacity of beaches to SLR in such a way that, the lack of accommodation space can be identified as a main factor for the estimated impacts.

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“…More importantly, this approach fails to include the dynamic response due to anthropogenic, ecologic 10 , or morphologic processes such as erosion and deposition-that drives coastal landscape evolution 11 . Dynamic response assessments 11,12 tend to represent cross-shore sediment transport processes explicitly with highly parameterized models, and can be used to make probabilistic assessments 13 via Monte Carlo methods and sensitivity analyses to communicate uncertainty 14 . Uncertainty affecting these approaches includes unknowns regarding rates and magnitudes of SLR, storminess, model parameter values, and the extrapolation from cross-shore profiles to spatially extensive domains.…”

mentioning

confidence: 99%

Evaluation of dynamic coastal response to sea-level rise modifies inundation likelihood

et al. 2016

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2 Sea-level rise (SLR) poses a range of threats to natural and built environments 1,2 , making assessments of SLR-induced hazards essential for informed decision-making 3 . We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30x30 m resolution predictions for more than 38,000 km 2 of diverse coastal landscape in the northeastern United States (U.S.). Probabilistic SLR projections, coastal elevation, and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response vs. inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge.This approach is well-suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints. As an alternative, we developed a data-driven coastal response (CR) model that considers both inundation and dynamic response using a range of SLR scenarios and datasets describing elevation and vertical land movement. We integrate these elements with land-cover information to assess CR likelihoods in the form of a dynamic probability, DP = 1-Prob. (inundate), using a Bayesian network Maine through Virginia, and includes a region with a wide range of coastal development, infrastructure, and environments found globally; including uplands, barrier beaches, spits, islands, mainland beaches, cliffs, rocky headlands, estuaries, and wetlands. The study area is defined by the -10 and +10 m elevation contours and mapped as a 30 m grid.To predict CR likelihoods (Figure 2), we first compute an adjusted land elevation with respect to projected sea levels:where AE represents the adjusted elevation with respect to a future sea level; E denotes the initial land elevation; SL is a projected sea level in the 2020s, 2030s, 2050s, or 2080s; and VLM gives the current rate of vertical land movement due to glacial isostatic adjustment, tectonics, and other non-climatic effects such as groundwater withdrawal and sediment compaction 15 . Sources of uncertainty in AE predictions include SLR projections, elevation data accuracy, vertical datum adjustments, and the interpolation of VLM rates from point data; these geospatially-explicit input uncertainties are propagated through the model to produce a probability mass function P(AE) for every grid cell (Figure 2c,d). Once generated, AEs are related through evaluation of their dynamic response potential with generalized landcover information and used to produce a CR likelihood (Figures 1, 2).Discretized AE predictions provide an estimated submergence level comparable to many existing inundation models 3, 16 (Figure 2). However, our predictions include several notable improvement...

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Estimating coastal recession due to sea level rise: beyond the Bruun rule

Cited by 210 publications

References 22 publications

Failure of Grass Covered Flood Defences with Roads on Top Due to Wave Overtopping: A Probabilistic Assessment Method

Failure of Grass Covered Flood Defences with Roads on Top Due to Wave Overtopping: A Probabilistic Assessment Method

Impacts of sea-level rise-induced erosion on the Catalan coast

Evaluation of dynamic coastal response to sea-level rise modifies inundation likelihood

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