Oil spills can be among the most devastating environmental disasters, with the potential to severely damage marine ecosystems, disrupt coastal communities, and impose lasting economic damage. Traditional numerical models, such as MEDSLIK-II, simulate the movement and transformation of oil particles in seawater, but their accuracy has been limited by dependence on expert judgment for tuning critical physical parameters. This manual calibration process, while informed by experience, is not always able to capture the complexity and variability of real-world ocean and atmospheric conditions.
AI-powered oil spill prediction system can improve emergency response accuracy by up to 25%
