Trekking to the beach only to find the surf full of stinging bluebottles could soon be a thing of the past as scientists investigate how to predict when they are likely to wash ashore.
Swell and wind forecasts and machine learning are being used in a bid to build a predictive model for bluebottle movements by researchers at the University of NSW.
But it won't be ready this summer as scientists continue testing with plans to make the technology available in late 2025.
Bluebottles are biologically closer to coral than jellyfish and cannot swim, placing them at the mercy of ocean currents.
Bluebottles deliver a sting which can cause redness and pain but do not generally cause serious harm.
They would sink if fitted with the trackers used to keep an eye on sharks and other fish.
Scientists instead placed trackers on 3D-printed replica bluebottles placed about five kilometres off the coast of Sydney's Botany Bay in January to get an idea how the stingers could spread.
One washed up at Bondi Beach, along with a number of actual bluebottles.
Another was picked up by a dog at Palm Beach, at the far end of the city's northern beaches, more than 40km away from the release location.
Like bluebottles, the replicas had their sails pointing either left or right, dictating the direction they drifted in the 20km/h winds.
But winds over 30km/h overcame those directions, blowing a whole colony of bluebottles the same way.
UNSW oceanography researcher Amandine Schaeffer said machine learning and oceanographic models were being used to analyse where bluebottles reached the Australian coast and where they come from.
"We're trying to understand how they move with ocean currents, winds and waves, and which conditions bring them to shore," she said.
Forecasts for currents, wind and swell could then be used to predict swarms.
"The idea is to have a statistical model that is fed with these environmental variables, which will allow us to make predictions about the likelihood of bluebottles being on a particular beach," Dr Schaeffer said.
The researchers are working with Surf Life Saving Australia to incorporate the predictions into its Beachsafe app once the predictive model is operational.
