Evaluating five shoreline change models against 40 years of field survey data at an embayed sandy beach

Journal Article (2025)
Author(s)

Oxana Repina (University of Wollongong)

Rafael C. Carvalho (The University of Newcastle, Australia, University of Wollongong)

Giovanni Coco (The University of Auckland)

José A.Á. Antolínez (TU Delft - Coastal Engineering)

Iñaki de Santiago (Basque Research and Technology Alliance (BRTA))

Mitchell D. Harley (University of New South Wales)

Camilo Jaramillo (Universidad de Cantabria)

Kristen D. Splinter (University of New South Wales)

Sean Vitousek (US Geological Survey)

Colin D. Woodroffe (University of Wollongong)

Research Group
Coastal Engineering
DOI related publication
https://doi.org/10.1016/j.coastaleng.2025.104738
More Info
expand_more
Publication Year
2025
Language
English
Research Group
Coastal Engineering
Volume number
199
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Robust and reliable models are needed to understand how coastlines will evolve over the coming decades, driven by both natural variability and climate change. This study evaluated how accurately five popular ‘reduced-complexity’ models replicate multi-decadal shoreline change at Narrabeen-Collaroy Beach, a sandy embayment in Sydney, Australia. Measured shoreline positions derived from approximately monthly field surveys were used for 20-year calibration and 20-year validation periods. The models performed similarly on average but with large variability between transects. The set-up of several models was modified to compensate for their sensitivity to imperfect input wave data, and further site-specific improvements were identified. Capturing interannual to decadal-scale variability in cross-shore and longshore dynamics at this site was challenging for all five models. Models appeared to aggregate key processes at this timescale into parameter values rather than representing them directly. This suggests time-varying parameters or changes to model structure may be necessary for decadal-scale simulations.