A group of American scientists will develop an artificial intelligence system that predicts coastal flooding in the Gulf of Mexico region.
Under the MuSiKAL project, researchers will combine the U.S. Department of Energy’s large-scale Earth model with a multi-physics coastal circulation model. They say this will enable a high-fidelity digital twin that supports AI with reduced latency in flood forecasting and impact assessment.
They also plan to develop a methodology for continuous AI-driven data collection from satellites and ground observations.
According to Hartmut Kaiser, a professor at Louisiana State University, the Gulf of Mexico is ideal for coastal-protection research. These regions are home to more than half of the U.S. population and account for around 58% of the country’s gross domestic product, he added.
“The Gulf of Mexico coast along Texas, Louisiana and Mississippi is home to both the United States’ critical energy hubs and socially vulnerable populations,” Kaiser said.
The proposed efforts will help minimise flood damage and improve the region’s socio-economic stability, the scientist said.
MuSiKAL is one of three projects funded by the U.S. Department of Energy’s Office of Advanced Scientific Computing Research. Each will receive $15.1 million over three years.
In May 2021, American scientists developed an AI system for predictions of hail, tornadoes and strong winds during a storm.
In September, Britain’s DeepMind introduced the DGMR deep-learning tool, which predicts the probability of rain in the next 90 minutes.
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