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One beach... many models! Combining models to predict multidecadal coastal erosion.

Authors :
Cussioli, Mariana
Berthot, Alexis
Thiebaut, Severin
Watson, Holly
Meirelles, Saulo
Gardiner, Sarah
Knight, Sam
Source :
EA National Conference Publications; 2023, p941-950, 10p
Publication Year :
2023

Abstract

Coastlines around the world are being impacted by storm erosion and Sea Level Rise (SLR). This leads to an increase in damage exposure for coastal assets and structures. We developed a multi-model approach to better understand current and future coastal processes at a Port Fairy beach (Australia), where coastal assets have been impacted by storm erosion and Sea Level Rise (SLR). Our methodology leveraged the output of a long-term shoreline model, as initial conditions for a storm erosion model, on a feedback loop. We first assessed erosion and shoreline retreat trends based on aerial imagery and shoreline datasets. We then ran a one-line shoreline model (GenCade), forced with a long-term SWAN wave hindcast, to estimate alongshore accretion and erosion on either side of proposed seawall structures for the years of 2050, 2070, and 2100. The results of the shoreline model were used to establish shoreline changes and provide an updated bathymetry for use in the XBeach beach erosion model. XBeach was used to analyse the morphodynamic changes for a reconstructed storm centred on the 500-year Annual Recurrence Interval wave. The model provided results of cross-shore changes, as well as potential accretion and erosion areas. Our study offered a useful method for evaluating coastal erosion issues using a multi-model approach that accounted for the trends in shoreline retreat, SLR in future scenarios, storm conditions, and both longshore and cross-shore sediment transport. All of which are crucial factors to consider when mitigating erosion and designing coastal protection structures with potential adaptation of the design over future decades. [ABSTRACT FROM AUTHOR]

Details

Language :
English
Database :
Complementary Index
Journal :
EA National Conference Publications
Publication Type :
Conference
Accession number :
178346056