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Brad A Murray - One of the best experts on this subject based on the ideXlab platform.
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twenty first century projections of Shoreline Change along inlet interrupted coastlines
Scientific Reports, 2021Co-Authors: Brad A Murray, Roshanka Ranasinghe, Robert J Nicholls, Janaka Bamunawala, Ali Dastgheib, Patrick L Barnard, T A J G SirisenaAbstract:Sandy coastlines adjacent to tidal inlets are highly dynamic and widespread landforms, where large Changes are expected due to climatic and anthropogenic influences. To adequately assess these important Changes, both oceanic (e.g., sea-level rise) and terrestrial (e.g., fluvial sediment supply) processes that govern the local sediment budget must be considered. Here, we present novel projections of Shoreline Change adjacent to 41 tidal inlets around the world, using a probabilistic, reduced complexity, system-based model that considers catchment-estuary-coastal systems in a holistic way. Under the RCP 8.5 scenario, retreat dominates (90% of cases) over the twenty-first century, with projections exceeding 100 m of retreat in two-thirds of cases. However, the remaining systems are projected to accrete under the same scenario, reflecting fluvial influence. This diverse range of response compared to earlier methods implies that erosion hazards at inlet-interrupted coasts have been inadequately characterised to date. The methods used here need to be applied widely to support evidence-based coastal adaptation.
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modeling large scale Shoreline Change caused by complex bathymetry in low angle wave climates
Marine Geology, 2017Co-Authors: Patrick W Limber, Peter N Adams, Brad A MurrayAbstract:Abstract Coastlines where waves consistently approach at highly oblique angles experience anti-diffusional behavior, causing perturbations to grow seaward and form sand waves, capes, and spits. Coasts where waves approach at low offshore angles experience the opposite: perturbations diffuse and the coastline remains (or becomes) smooth. In this paper, by coupling a 2-D large-scale coastline evolution model to a spectral wave model, we show that anti-diffusional behavior is also possible in low-angle wave climates if the nearshore wave field is altered by complex bathymetry. In model simulations, low-angle waves refract over local shoals, creating a convergence in alongshore sediment flux behind the shoals that coalesces into small ‘minor capes’. Depending on wave height and period, Shoreline features take 80–400 years to reach an equilibrium cross-shore relief of 1–1.5 km over an alongshore distance of ~ 20 km. The modeled equilibrium time scale is consistent with analytically-determined characteristic Shoreline diffusion time scales, and the modeled cross-shore relief and aspect ratio are similar to observed ‘minor capes’ along the U.S. Atlantic Coast where offshore bathymetric anomalies have previously been linked to Shoreline Change patterns. Better understanding of the links among nearshore bathymetry, wave transformation, and alongshore sediment transport is critical to understanding Shoreline Change patterns at the local level and how they fit into broader, regional-scale behavior.
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cumulative versus transient Shoreline Change dependencies on temporal and spatial scale
Journal of Geophysical Research, 2011Co-Authors: Eli D Lazarus, Andrew D Ashton, Brad A Murray, S F Tebbens, Stephen M BurroughsAbstract:Using Shoreline Change measurements of two oceanside reaches of the North Carolina Outer Banks, USA, we explore an existing premise that Shoreline Change on a sandy coast is a self-affine signal, wherein patterns of Change are scale invariant. Wavelet analysis confirms that the mean variance (spectral power) of Shoreline Change can be approximated by a power law at alongshore scales from tens of meters up to ∼4–8 km. However, the possibility of a power law relationship does not necessarily reveal a unifying, scale-free, dominant process, and deviations from power law scaling at scales of kilometers to tens of kilometers may suggest further insights into Shoreline Change processes. Specifically, the maximum of the variance in Shoreline Change and the scale at which that maximum occurs both increase when Shoreline Change is measured over longer time scales. This suggests a temporal control on the magnitude of Change possible at a given spatial scale and, by extension, that aggregation of Shoreline Change over time is an important component of large-scale shifts in Shoreline position. We also find a consistent difference in variance magnitude between the two survey reaches at large spatial scales, which may be related to differences in oceanographic forcing conditions or may involve hydrodynamic interactions with nearshore geologic bathymetric structures. Overall, the findings suggest that Shoreline Change at small spatial scales (less than kilometers) does not represent a peak in the Shoreline Change signal and that Change at larger spatial scales dominates the signal, emphasizing the need for studies that target long-term, large-scale Shoreline Change.
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an integrated hypothesis for regional patterns of Shoreline Change along the northern north carolina outer banks usa
Marine Geology, 2011Co-Authors: Eli D Lazarus, Brad A MurrayAbstract:Combining analyses of plan-view Shoreline Change and Shoreline curvature with existing nearshore geologic and bathymetric data and the results of a recent theoretical, large-scale Shoreline-evolution model that couples geologic framework to alongshore sediment transport, we propose an integrated explanation for persistent patterns of Shoreline Change observed on the northern Outer Banks of North Carolina, USA. Concentrated sources of coarse-grained sediment, derived from relict fluvial stratigraphy or densely grouped relict inlet channels excavated from the shoreface, may both enable persistence of nearshore bathymetric anomolies and control multi-km-scale undulations in Shoreline curvature, which in turn affect gradients in wave-driven alongshore sediment transport that drive long-term Shoreline Change.
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process signatures in regional patterns of Shoreline Change on annual to decadal time scales
Geophysical Research Letters, 2007Co-Authors: Eli D Lazarus, Brad A MurrayAbstract:Gradients in wave-driven alongshore sediment transport influence the morphologies of sediment-covered coastlines on a range of spatial and temporal scales, affecting accretion and erosion patterns relevant to human development. Recent theoretical findings predict that a correlation between Shoreline Change and Shoreline curvature results from patterns of alongshore sediment flux; the sign (positive or negative) of that correlation depends on whether high- or low-angle waves dominated the wave climate. Using lidar surveys of the northern North Carolina coast from 1996–2005 to document Shoreline Change and quantify alongshore patterns of erosion and deposition, we isolate these signals diagnostic of alongshore-transport processes. Our analyses show a persistent, significant negative correlation between Shoreline-position Change and Shoreline curvature consistent with a low-angle-dominated incident wave climate over the last decade. At large spatial scales, convex-seaward promontories have eroded landward, while concave-seaward bays have aggraded seaward, resulting in an apparent diffusion of alongshore morphological features
Eli D Lazarus - One of the best experts on this subject based on the ideXlab platform.
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masked Shoreline erosion at large spatial scales as a collective effect of beach nourishment
Earth’s Future, 2019Co-Authors: Scott B Armstrong, Eli D LazarusAbstract:Sea‐level rise along the low‐lying coasts of the world's passive continental margins should, on average, drive net Shoreline retreat over large spatial scales (>102 km). A variety of natural physical factors can influence trends of Shoreline erosion and accretion, but trends in recent rates of Shoreline Change along the U.S. Atlantic Coast reflect an especially puzzling increase in accretion, not erosion. A plausible explanation for the apparent disconnect between environmental forcing and Shoreline response along the U.S. Atlantic Coast is the application, since the 1960s, of beach nourishment as the predominant form of mitigation against chronic coastal erosion. Using U.S. Geological Survey Shoreline records from 1830–2007 spanning more than 2500 km of the U.S. Atlantic Coast, we calculate a mean rate of Shoreline Change, prior to 1960, of ‐55 cm/yr (a negative rate denotes erosion). After 1960, the mean rate reverses to approximately +5 cm/yr, indicating widespread apparent accretion despite steady (and, in some places, accelerated) sea‐level rise over the same period. Cumulative sediment input from decades of beach nourishment projects may have sufficiently altered Shoreline position to mask "true" rates of Shoreline Change. Our analysis suggests that long‐term rates of Shoreline Change typically used to assess coastal hazard may be systematically underestimated. We also suggest that the overall effect of beach nourishment along of the U.S. Atlantic Coast is extensive enough to constitute a quantitative signature of coastal geoengineering, and may serve as a bellwether for nourishment‐dominated Shorelines elsewhere in the world.
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cumulative versus transient Shoreline Change dependencies on temporal and spatial scale
Journal of Geophysical Research, 2011Co-Authors: Eli D Lazarus, Andrew D Ashton, Brad A Murray, S F Tebbens, Stephen M BurroughsAbstract:Using Shoreline Change measurements of two oceanside reaches of the North Carolina Outer Banks, USA, we explore an existing premise that Shoreline Change on a sandy coast is a self-affine signal, wherein patterns of Change are scale invariant. Wavelet analysis confirms that the mean variance (spectral power) of Shoreline Change can be approximated by a power law at alongshore scales from tens of meters up to ∼4–8 km. However, the possibility of a power law relationship does not necessarily reveal a unifying, scale-free, dominant process, and deviations from power law scaling at scales of kilometers to tens of kilometers may suggest further insights into Shoreline Change processes. Specifically, the maximum of the variance in Shoreline Change and the scale at which that maximum occurs both increase when Shoreline Change is measured over longer time scales. This suggests a temporal control on the magnitude of Change possible at a given spatial scale and, by extension, that aggregation of Shoreline Change over time is an important component of large-scale shifts in Shoreline position. We also find a consistent difference in variance magnitude between the two survey reaches at large spatial scales, which may be related to differences in oceanographic forcing conditions or may involve hydrodynamic interactions with nearshore geologic bathymetric structures. Overall, the findings suggest that Shoreline Change at small spatial scales (less than kilometers) does not represent a peak in the Shoreline Change signal and that Change at larger spatial scales dominates the signal, emphasizing the need for studies that target long-term, large-scale Shoreline Change.
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an integrated hypothesis for regional patterns of Shoreline Change along the northern north carolina outer banks usa
Marine Geology, 2011Co-Authors: Eli D Lazarus, Brad A MurrayAbstract:Combining analyses of plan-view Shoreline Change and Shoreline curvature with existing nearshore geologic and bathymetric data and the results of a recent theoretical, large-scale Shoreline-evolution model that couples geologic framework to alongshore sediment transport, we propose an integrated explanation for persistent patterns of Shoreline Change observed on the northern Outer Banks of North Carolina, USA. Concentrated sources of coarse-grained sediment, derived from relict fluvial stratigraphy or densely grouped relict inlet channels excavated from the shoreface, may both enable persistence of nearshore bathymetric anomolies and control multi-km-scale undulations in Shoreline curvature, which in turn affect gradients in wave-driven alongshore sediment transport that drive long-term Shoreline Change.
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process signatures in regional patterns of Shoreline Change on annual to decadal time scales
Geophysical Research Letters, 2007Co-Authors: Eli D Lazarus, Brad A MurrayAbstract:Gradients in wave-driven alongshore sediment transport influence the morphologies of sediment-covered coastlines on a range of spatial and temporal scales, affecting accretion and erosion patterns relevant to human development. Recent theoretical findings predict that a correlation between Shoreline Change and Shoreline curvature results from patterns of alongshore sediment flux; the sign (positive or negative) of that correlation depends on whether high- or low-angle waves dominated the wave climate. Using lidar surveys of the northern North Carolina coast from 1996–2005 to document Shoreline Change and quantify alongshore patterns of erosion and deposition, we isolate these signals diagnostic of alongshore-transport processes. Our analyses show a persistent, significant negative correlation between Shoreline-position Change and Shoreline curvature consistent with a low-angle-dominated incident wave climate over the last decade. At large spatial scales, convex-seaward promontories have eroded landward, while concave-seaward bays have aggraded seaward, resulting in an apparent diffusion of alongshore morphological features
Charles H Fletcher - One of the best experts on this subject based on the ideXlab platform.
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are beach erosion rates and sea level rise related in hawaii
Global and Planetary Change, 2013Co-Authors: Bradley M. Romine, Matthew M Barbee, Charles H Fletcher, Tiffany R Anderson, Neil L FrazerAbstract:Abstract The islands of Oahu and Maui, Hawaii, with significantly different rates of localized sea-level rise (SLR, approximately 65% higher rate on Maui) over the past century due to lithospheric flexure and/or variations in upper ocean water masses, provide a unique setting to investigate possible relations between historical Shoreline Changes and SLR. Island-wide and regional historical Shoreline trends are calculated for the islands using Shoreline positions measured from aerial photographs and survey charts. Historical Shoreline data are optimized to reduce anthropogenic influences on Shoreline Change measurements. Shoreline Change trends are checked for consistency using two weighted regression methods and by systematic exclusion of coastal regions based on coastal aspect (wave exposure) and coastal geomorphology. Maui experienced the greatest extent of beach erosion over the past century with 78% percent of beaches eroding compared to 52% on Oahu. Maui also had a significantly higher island-wide average Shoreline Change rate at − 0.13 ± 0.05 m/yr compared to Oahu at − 0.03 ± 0.03 m/yr (at the 95% Confidence Interval). Differing rates of relative SLR around Oahu and Maui remain as the best explanation for the difference in overall Shoreline trends after examining other influences on Shoreline Change including waves, sediment supply and littoral processes, and anthropogenic Changes; though, these other influences certainly remain important to Shoreline Change in Hawaii. The results of this study show that SLR is an important factor in historical Shoreline Change in Hawaii and that historical rates of Shoreline Change are about two orders of magnitude greater than SLR.
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transient and persistent Shoreline Change from a storm
Geophysical Research Letters, 2010Co-Authors: Tiffany R Anderson, Neil L Frazer, Charles H FletcherAbstract:[1] There is disagreement as to whether Shoreline position eventually recovers from large storms. In an earlier paper we showed that statistical modeling of historical Shoreline data was improved by including large storms in the model via a transient storm function. Here we show that, at shorter timescales of months to years, modeling of the Shoreline at Assateague Island, MD is improved by a storm model with both transient and persistent components. We find that the Shoreline recovers from the storm rapidly, almost within a year, but that the recovery is only partial, despite anthropogenic reconstruction of a pre-existing berm. The long-term trend of a Shoreline (whether erosive, accretive, or stationary) can thus be regarded as the cumulative persistent component of successive storms, although most long-term data sets are too temporally sparse to make such a parameterization more useful than a steady long-term rate.
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Historical Shoreline Change, Southeast Oahu, Hawaii; Applying Polynomial Models to Calculate Shoreline Change Rates
Journal of Coastal Research, 2009Co-Authors: Bradley M. Romine, Ayesha S. Genz, L. Neil Frazer, Charles H Fletcher, Matthew M BarbeeAbstract:Abstract Here we present Shoreline Change rates for the beaches of southeast Oahu, Hawaii, calculated using recently developed polynomial methods to assist coastal managers in planning for erosion hazards and to provide an example for interpreting results from these new rate calculation methods. The polynomial methods use data from all transects (Shoreline measurement locations) on a beach to calculate a rate at any one location along the beach. These methods utilize a polynomial to model alongshore variation in the rates. Models that are linear in time best characterize the trend of the entire time series of historical Shorelines. Models that include acceleration (both increasing and decreasing) in their rates provide additional information about Shoreline trends and indicate how rates vary with time. The ability to detect accelerating Shoreline Change is an important advance because beaches may not erode or accrete in a constant (linear) manner. Because they use all the data from a beach, polynomial mod...
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modeling storms improves estimates of long term Shoreline Change
Geophysical Research Letters, 2009Co-Authors: Neil L Frazer, Tiffany R Anderson, Charles H FletcherAbstract:[1] Large storms make it difficult to extract the long-term trend of erosion or accretion from Shoreline position data. Here we make storms part of the Shoreline Change model by means of a storm function. The data determine storm amplitudes and the rate at which the Shoreline recovers from storms. Historical Shoreline data are temporally sparse, and inclusion of all storms in one model over-fits the data, but a probability-weighted average model shows effects from all storms, illustrating how model averaging incorporates information from good models that might otherwise have been discarded as un-parsimonious. Data from Cotton Patch Hill, DE, yield a long-term Shoreline loss rate of 0.49 ± 0.01 m/yr, about 16% less than published estimates. A minimum loss rate of 0.34 ± 0.01 m/yr is given by a model containing the 1929, 1962 and 1992 storms.
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toward parsimony in Shoreline Change prediction i basis function methods
Journal of Coastal Research, 2009Co-Authors: Neil L Frazer, Ayesha S. Genz, Charles H FletcherAbstract:Abstract Single-transect methods of Shoreline Change prediction are unparsimonious, i.e., they tend to overfit data by using more parameters than necessary because they assume that both signal and noise at adjacent transects are independent. Here we introduce some new methods that reduce overfitting by expressing Change rate as a linear sum of basis functions. In the method of IC-binning, the basis functions are boxcars—an information criterion is used to assign contiguous alongshore locations into bins within which Change rate is constant; the resulting rate is discontinuous but may be useful for beach management. In the polynomial method, the basis functions are polynomials in alongshore distance, and the Change rate varies continuously along the beach. In the eigenbeaches method, the basis functions are the principal components of the matrix of Shorelines. To choose the number of basis functions in each method, and to compare methods with each other, we use an information criterion. We apply these new ...
Arjen Luijendijk - One of the best experts on this subject based on the ideXlab platform.
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mapping spatial variability in Shoreline Change hotspots from satellite data a case study in southeast australia
Estuarine Coastal and Shelf Science, 2020Co-Authors: Teresa M Konlechner, Roshanka Ranasinghe, Arjen Luijendijk, David M Kennedy, Julian J Ogrady, Chloe Leach, Rafael Cabral Carvalho, Kathleen L Mcinnes, Daniel IerodiaconouAbstract:Abstract This study demonstrates how a large-scale satellite-derived dataset can be used to investigate statistically robust trends in Shoreline position over a 31-year period from 1987 to 2017, at a regional scale. Regional patterns of Shoreline behaviour are important for resolving consistent or, alternatively, dissimilar patterns of past Shoreline Change. Such patterns are best explored using temporally frequent and spatially extensive datasets. Here we analyse satellite-derived Shorelines to identify spatial patterns of hotspots of coastline Change on the wave-exposed coast of Victoria in south-east Australia where rates of Change exceed 0.5 m yr−1. Analysis of Shoreline position Changes at a 50 m alongshore interval along 900 km of the 1230 km coastline reveals a number of distinct behaviours related to coastal type (rock vs sand coast), landform, Shoreline orientation and/or anthropogenic drivers of Change. Overall the results show that statistically significant Change in Shoreline position has affected only a relatively small proportion of the study region over the last 31 years; that the proportion and rate of progradational and recessional Change is similar; and that Change is localised but dispersed widely along the Victorian coast. Coasts located at the entrances to large tidal inlets have shown the greatest Change. The association of hotspots with embayed sandy beaches and adjacent to headlands points to the importance of geological control on Shoreline behaviour. Consistent with other regional scale studies of Shoreline Change, this study found little regional coherence in Shoreline behaviour. Instead Change is predominately attributed to local factors such as the geological framework of the coast, localised hydrodynamic conditions and anthropogenic influences. Collectively, these results indicate that there is strong geologic control on Shoreline erosion in Victoria due to the high diversity of landforms along the coastline; and that further analysis is required to tease out the seasonal to interannual sensitivities to Changes in the historical wave climate and the secondary interaction of sediment supply for headlands and hydrodynamics for tidal inlets.
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multi decadal Shoreline Change in coastal natural world heritage sites a global assessment
Environmental Research Letters, 2020Co-Authors: Salma Sabour, Sally Brown, Robert J Nicholls, Ivan D Haigh, Arjen LuijendijkAbstract:Natural World Heritage Sites (NWHS), which are of Outstanding Universal Value, are increasingly threatened by natural and anthropogenic pressures. This is especially true for coastal NWHS, which are additionally subject to erosion and flooding. This paper assesses Shoreline Change from 1984 to 2016 within the boundaries of 67 designated sites, providing a first global consistent assessment of its drivers. It develops a transferable methodology utilising new satellite-derived global Shoreline datasets, which are classified based on linearity of Change against time and compared with global datasets of geomorphology (topography, land cover, coastal type, and lithology), climate variability and sea-level Change. Significant Shoreline Change is observed on 14% of 52 coastal NWHS Shorelines that show the largest recessional and accretive trends (means of -3.4 m yr-1 and 3.5 m yr-1, respectively). These rapid Shoreline Changes are found in low-lying Shorelines (< 1 m elevation) composed of unconsolidated sediments in vegetated tidal coastal systems (means of -7.7 m yr-1 and 12.5 m yr-1), and vegetated tidal deltas at the mouth of large river systems (means of -6.9 and 11 m yr-1). Extreme Shoreline Changes occur as a result of redistribution of sediment driven by a combination of geomorphological conditions with (1) specific natural coastal morphodynamics such as opening of inlets (e.g. Rio Platano Biosphere Reserve) or gradients of alongshore sediment transport (e.g. Namib Sea) and (2) direct or indirect human interferences with natural coastal processes such as sand nourishment (e.g. Wadden Sea) and damming of river sediments upstream of a delta (e.g. Danube Delta). The most stable soft coasts are associated with the protection of coral reef ecosystems (e.g. Great Barrier Reef) which may be degraded/destroyed by climate Change or human stress in the future. A positive correlation between Shoreline retreat and local relative sea-level Change was apparent in the Wadden Sea. However, globally, the effects of contemporary sea-level rise are not apparent for coastal NWHS, but it is a major concern for the future reinforcing the Shoreline dynamics already being observed due to other drivers. Hence, future assessments of Shoreline Change need to account of other drivers of coastal Change in addition to sea-level rise projections. In conclusion, extreme multi-decadal linear Shoreline trends occur in coastal NWHS and are driven primarily by sediment redistribution. Future exacerbation of these trends may affect heritage values and coastal communities. Thus Shoreline Change should be considered in future management plans where necessary. This approach provides a consistent method to assess NWHS which can be repeated and help steer future management of these important sites.
Roshanka Ranasinghe - One of the best experts on this subject based on the ideXlab platform.
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twenty first century projections of Shoreline Change along inlet interrupted coastlines
Scientific Reports, 2021Co-Authors: Brad A Murray, Roshanka Ranasinghe, Robert J Nicholls, Janaka Bamunawala, Ali Dastgheib, Patrick L Barnard, T A J G SirisenaAbstract:Sandy coastlines adjacent to tidal inlets are highly dynamic and widespread landforms, where large Changes are expected due to climatic and anthropogenic influences. To adequately assess these important Changes, both oceanic (e.g., sea-level rise) and terrestrial (e.g., fluvial sediment supply) processes that govern the local sediment budget must be considered. Here, we present novel projections of Shoreline Change adjacent to 41 tidal inlets around the world, using a probabilistic, reduced complexity, system-based model that considers catchment-estuary-coastal systems in a holistic way. Under the RCP 8.5 scenario, retreat dominates (90% of cases) over the twenty-first century, with projections exceeding 100 m of retreat in two-thirds of cases. However, the remaining systems are projected to accrete under the same scenario, reflecting fluvial influence. This diverse range of response compared to earlier methods implies that erosion hazards at inlet-interrupted coasts have been inadequately characterised to date. The methods used here need to be applied widely to support evidence-based coastal adaptation.
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mapping spatial variability in Shoreline Change hotspots from satellite data a case study in southeast australia
Estuarine Coastal and Shelf Science, 2020Co-Authors: Teresa M Konlechner, Roshanka Ranasinghe, Arjen Luijendijk, David M Kennedy, Julian J Ogrady, Chloe Leach, Rafael Cabral Carvalho, Kathleen L Mcinnes, Daniel IerodiaconouAbstract:Abstract This study demonstrates how a large-scale satellite-derived dataset can be used to investigate statistically robust trends in Shoreline position over a 31-year period from 1987 to 2017, at a regional scale. Regional patterns of Shoreline behaviour are important for resolving consistent or, alternatively, dissimilar patterns of past Shoreline Change. Such patterns are best explored using temporally frequent and spatially extensive datasets. Here we analyse satellite-derived Shorelines to identify spatial patterns of hotspots of coastline Change on the wave-exposed coast of Victoria in south-east Australia where rates of Change exceed 0.5 m yr−1. Analysis of Shoreline position Changes at a 50 m alongshore interval along 900 km of the 1230 km coastline reveals a number of distinct behaviours related to coastal type (rock vs sand coast), landform, Shoreline orientation and/or anthropogenic drivers of Change. Overall the results show that statistically significant Change in Shoreline position has affected only a relatively small proportion of the study region over the last 31 years; that the proportion and rate of progradational and recessional Change is similar; and that Change is localised but dispersed widely along the Victorian coast. Coasts located at the entrances to large tidal inlets have shown the greatest Change. The association of hotspots with embayed sandy beaches and adjacent to headlands points to the importance of geological control on Shoreline behaviour. Consistent with other regional scale studies of Shoreline Change, this study found little regional coherence in Shoreline behaviour. Instead Change is predominately attributed to local factors such as the geological framework of the coast, localised hydrodynamic conditions and anthropogenic influences. Collectively, these results indicate that there is strong geologic control on Shoreline erosion in Victoria due to the high diversity of landforms along the coastline; and that further analysis is required to tease out the seasonal to interannual sensitivities to Changes in the historical wave climate and the secondary interaction of sediment supply for headlands and hydrodynamics for tidal inlets.
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Quantifying uncertainties of sandy Shoreline Change projections as sea level rises
Scientific Reports, 2019Co-Authors: Gonéri Le Cozannet, Thomas Bulteau, Bruno Castelle, Roshanka Ranasinghe, Guy Woppelmann, Jeremy Rohmer, Nicolas Bernon, Jessie Louisor, David Salas-y-mélia, Déborah IdierAbstract:Sandy Shorelines are constantly evolving, threatening frequently human assets such as buildings or transport infrastructure. In these environments, sea-level rise will exacerbate coastal erosion to an amount which remains uncertain. Sandy Shoreline Change projections inherit the uncertainties of future mean sea-level Changes, of vertical ground motions, and of other natural and anthropogenic processes affecting Shoreline Change variability and trends. Furthermore, the erosive impact of sea-level rise itself can be quantified using two fundamentally different models. Here, we show that this latter source of uncertainty, which has been little quantified so far, can account for 20 to 40% of the variance of Shoreline projections by 2100 and beyond. This is demonstrated for four contrasting sandy beaches that are relatively unaffected by human interventions in southwestern France, where a variance-based global sensitivity analysis of Shoreline projection uncertainties can be performed owing to previous observations of beach profile and Shoreline Changes. This means that sustained coastal observations and efforts to develop sea-level rise impact models are needed to understand and eventually reduce uncertainties of Shoreline Change projections, in order to ultimately support coastal land-use planning and adaptation.