Time-Varying Beach Memory Applied to Cross-Shore Shoreline Evolution Modelling

Sánchez, Jara Martínez; González, M.; Medina, Raúl; Jaramillo, Camilo

doi:10.2112/jcoastres-d-17-00041.1

Cited by 5 publications

(3 citation statements)

References 28 publications

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“…We can estimate the number of time steps required for the initial conditions to be 'forgotten' by the following analysis. If we assume that the initial conditions become negligible in Equation 52 This example illustrates the concept of "beach memory" that has been discussed in the literature (Jara et al 2015(Jara et al , 2018Reeve et al, 2014;Turki et al 2012Turki et al , 2013. Here, we define beach memory as the degree to which the current shoreline state "remembers" or "forgets" its past state and antecedent wave conditions.…”

Section: Example #2: Damped Random Walk Ensemblementioning

confidence: 86%

The Application of Ensemble Wave Forcing to Quantify Uncertainty of Shoreline Change Predictions

et al. 2021

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Sandy shorelines respond to oceanographic and geologic processes at a variety of temporal (e.g., seconds to decades) and spatial (e.g., surf zone to ocean basin wide) scales. Thus, forecasting short-and long-term shoreline change remains difficult. Accurate predictions of shoreline movement in response to sea-level rise, changing wave climates, and reduced sediment supplies are increasingly sought to support coastal management, often out of fears that many beaches may be severely impacted by climate change (Le Cozan-

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Section: Example #2: Damped Random Walk Ensemblementioning

confidence: 86%

The Application of Ensemble Wave Forcing to Quantify Uncertainty of Shoreline Change Predictions

et al. 2021

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“…Beach profile features and evolution are essential considerations for coastal engineering projects. In the eastern Baltic Sea, profile dynamics have received comparatively less attention than alongshore processes, and the available knowledge remains partly qualitative and empirical [1,10,[51][52][53][54].…”

Section: Discussionmentioning

confidence: 99%

Cross-Shore Profile Evolution after an Extreme Erosion Event—Palanga, Lithuania

Kelpšaitė-Rimkienė

Parnell

Žaromskis

et al. 2021

JMSE

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We report cross-shore profile evolution at Palanga, eastern Baltic Sea, where short period waves dominate. Cross-shore profile studies began directly after a significant coastal erosion event caused by storm “Anatol”, in December of 1999, and continued for a year. Further measurements were undertaken sixteen years later. Cross-shore profile changes were described, and cross-shore transport rates were calculated. A K-means clustering technique was applied to determine sections of the profile with the same development tendencies. Profile evolution was strongly influenced by the depth of closure which is constrained by a moraine layer, and the presence of a groyne. The method used divided the profile into four clusters: the first cluster in the deepest water represents profile evolution limited by the depth of closure, and the second and third are mainly affected by processes induced by wind, wave and water level changes. The most intensive sediment volume changes were observed directly after the coastal erosion event. The largest sand accumulation was in the fourth profile cluster, which includes the upper beach and dunes. Seaward extension of the dune system caused a narrowing of the visible beach, which has led to an increased sand volume (accretion) being misinterpreted as erosion

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Section: Discussionmentioning

confidence: 99%

Coastal Morphology Assessment and Coastal Protection

2021

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Time-Varying Beach Memory Applied to Cross-Shore Shoreline Evolution Modelling

Cited by 5 publications

References 28 publications

The Application of Ensemble Wave Forcing to Quantify Uncertainty of Shoreline Change Predictions

The Application of Ensemble Wave Forcing to Quantify Uncertainty of Shoreline Change Predictions

Cross-Shore Profile Evolution after an Extreme Erosion Event—Palanga, Lithuania

Coastal Morphology Assessment and Coastal Protection

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