A global benchmarking competition finds shoreline models are ready for real-world coastal planning.
A UNSW-led global collaborative study has found most shoreline prediction models are effective at forecasting changes to natural, sandy beaches with an accuracy of approximately 10 metres.
The findings, published in Communications Earth & Environment 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 – whether beaches grow, shrink, or shift due to tides, storms, or erosion.
Accurate predictions help governments, planners, and communities make critical decisions about development, risk management, and environment protection.
"Our results indicate that certain beaches can be modelled nearly as well as they can be remotely observed," says Dr Yongjing Mao, lead author of the study from UNSW 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 – 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 (5-year) and medium (50-year) time periods. The real beach—Curl Curl in New South Wales—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 – matching the resolution of satellite-based shoreline observations.
"Like most beaches found in NSW, bay-shaped beaches are curved and bounded by headlines that protect them from the full force of the ocean," says Dr Mao.
"However, these dynamic beaches can evolve rapidly in response to environmental forces that can be exacerbated by changing wave climates and rising sea levels.
"We found that most shoreline models successfully capture both the response to storms in not only short-term but also medium-term predictions.
"The results from this study build confidence that existing models can give us robust prediction of how our shorelines will change."
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.
"In the competition, modellers were provided with remote sensing shoreline data, which is easily accessible but generally less reliable than ground-truth observations," says Dr Mao.
"As 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."
Dr Mao says another key limitation for a majority of these models is that they still heavily rely on the Bruun rule – a 60-year-old principal 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.
"For long-term predictions, we question the reliability of models that are still based on the Bruun rule," he says.
"To better reflect the complexities of coastal systems, we need to develop alternative approaches that capture shoreline changes over time."
Informing future coastal planning
Dr Mao says it's important to develop models to predict shoreline change, as climate-related risks are among the highest in coastal areas.
Around 10% of the global population lives within five kilometres of a coast, and many of these areas face growing threats of coastal erosion and recession.
Dr Mao believes we can expect to see more human intervention to protect these coastal communities – and that future studies should focus more on these complex coastal environments.
"If we look at densely populated coastal cities around the world, they tend to have more 'engineered' beaches, with structures such as breakwaters or seawalls," says Dr Mao.
"But now, engineers are starting to look for natural interventions such as sand nourishment programs.
"Being able to accurately predict how beaches will change helps governments, planners, and communities make smarter decisions about how to preserve our natural environment."
