A global benchmarking competition finds that shoreline models are ready for real-world coastal planning.
A 草莓视频-led global collaborative study has found that most shoreline prediction models are effective at forecasting changes to natural, sandy beaches with an accuracy of approximately 10 metres.
The findings, published in last month, are the most comprehensive benchmarking of shoreline prediction models to date.
With changing wave climates and rising sea levels, engineers use shoreline models to predict how coastlines will evolve 鈥 whether beaches grow, shrink, or shift due to storms, tides, or erosion.
Accurate predictions help governments, planners, and communities make critical decisions about development, risk management, and environment protection.听
鈥淥ur results indicate that certain beaches can be modelled nearly as well as they can be remotely observed,鈥 says , lead author of the study from 草莓视频 Water Research Lab at the School of Civil and Environmental Engineering.
However, the researchers say further benchmarking is needed to understand model performance for coastlines in urbanised areas, where human-made structures complicate shoreline dynamics 鈥 especially as climate change accelerates coastal impacts.
Blind competition
In the study, 34 shoreline models from various modellers around the world were evaluated on their ability to make predictions of a shoreline position as part of a blind competition, called ShoreShop2.0.
The competition tested how well models could predict shoreline change over short (five-year) and medium (50-year) periods. The real beach 鈥 Curl Curl in New South Wales 鈥 was anonymised as 'BeachX' to ensure unbiased results.
Participants were provided only open-source data, including waves, tides, sea-level rise, and 20 years of shoreline positions derived from public satellite imagery, for calibration.
Shoreline data from other periods were withheld for evaluation.
The researchers found that the top-performing models could predict shoreline change with an accuracy of approximately 10 metres for bay-shaped beaches over both short and medium time scales 鈥 matching the resolution of satellite-based shoreline observations.
鈥淟ike most beaches found in NSW, bay-shaped beaches are curved and bounded by headlands that protect them from the full force of the ocean,鈥 says Dr Mao.
鈥淗owever, these dynamic beaches can evolve rapidly in response to environmental forces that can be exacerbated by changing wave climates and rising sea levels.
鈥淲e found that most shoreline models successfully capture both the response to storms in not only short-term but also medium-term predictions.
鈥淭he results from this study build confidence that existing models can give us robust prediction of how our shorelines will change.鈥
The limitations to address
Over the years, these models have become more accurate at simulating changing shoreline dynamics by integrating advanced computational techniques with increasing volumes of data.
Still, the findings emphasise that the model performance depends not only on the model itself but on the quality of the data used, particularly the pre-processing of satellite-derived shoreline data.
鈥淚n the competition, modellers were provided with remote sensing shoreline data, which is easily accessible but generally less reliable than ground-truth observations,鈥 says Dr Mao.
鈥淎s ground-truth shoreline data is not readily available, to ensure models continue to provide accurate predictions of coastline changes, we recommend more widespread use of spatio-temporal smoothing techniques to reduce the noise of satellite-derived shoreline data and enhance model performance.鈥
Dr Mao says another key limitation for a majority of these models is that they still heavily rely on the Bruun rule 鈥 a 60-year-old principle that says a sandy beach profile will maintain its shape as the sea level rises but shift landward and upward to compensate.
He says many scientists and coastal engineers consider this rule an oversimplification of the complexities of real-world coastal processes.
鈥淔or long-term predictions, we question the reliability of models that are still based on the Bruun rule,鈥 he says.
鈥淭o better reflect the complexities of coastal systems, we need to develop alternative approaches that capture shoreline changes over time.鈥
Informing future coastal planning
Dr Mao says it鈥檚 important to develop models to predict shoreline change, as climate-related risks are among the highest in coastal areas.听
Around 10% of the global population lives within , and many of these areas face growing threats of听coastal erosion and recession.听
Dr Mao believes we expect to see more human intervention to protect these coastal communities 鈥 and that future modelling should focus more on these complex coastal environments.听
鈥淚f we look at densely populated coastal cities around the world, they tend to have more 鈥榚ngineered鈥 beaches, with structures such as breakwaters or seawells,鈥 says Dr Mao.
鈥淏ut now, engineers are starting to look for natural interventions such as sand nourishment programs.
鈥淏eing able to accurately predict how beaches will change over time helps governments, planners, and communities make smarter decisions about how to preserve our natural environment.鈥
