A new project led by the University of Hawaiʻi at Mānoa will use artificial intelligence (AI) to help predict how rising seas and stronger storms could threaten coastal freshwater supplies and ecosystems.
Associate Professor Jonghyun “Harry” Lee of the UH Mānoa Water Resources Research Center and Department of Civil, Environmental and Construction Engineering has been awarded a $500,000 grant from the National Science Foundation under its Collaborations in Artificial Intelligence and Geosciences program. UH Mānoa will serve as the lead institution on a three-year, nearly $1 million collaborative project, alongside the University of Texas at Austin, to advance AI applications in geoscience.
Rising seas, stronger storms, saltwater contamination of freshwater resources and coastal ecosystem degradation pose increasing threats to coastal communities. These environmental pressures impact drinking water supplies, agriculture, infrastructure, local economies and daily life for millions of people.
To address these challenges, the joint project will develop fast, accessible AI models to better understand how water exchanges between coastal aquifers and the ocean. By combining recent advances in AI with traditional environmental modeling, the team aims to predict critical coastal risks—such as seawater intrusion into freshwater aquifers and freshwater flowing from land into the ocean—faster and more accurately.
“This project will improve our understanding and prediction of how groundwater and the ocean interact in Hawaiʻi’s coastal aquifers, helping communities better protect freshwater resources and coastal ecosystems from challenges, such as seawater intrusion and coastal inundation,” principal investigator Lee said.
Advancing coastal science through next-gen AI
The researchers will develop a new system that combines AI with proven physics models to better understand coastal water systems. This approach creates high-speed “surrogate models” capable of running complex simulations of groundwater and ocean interactions at a fraction of the cost, while preserving essential physics laws at the land-sea boundary.
Key features and goals of the project include:
- Flexible AI architecture: Combining different AI tools to analyze both long-term ocean patterns and short-term events, such as storm surges.
- Real-world testing: Validating models on benchmark applications in Hawaiʻi and Texas coastal systems.
- Near-real-time forecasts: Enabling rapid assessments of seawater intrusion and coastal groundwater discharge to support digital twin models of complex ecosystems.
- Practical decision tools: Providing actionable insights to guide water management, infrastructure planning and long-term coastal resilience.
- Open science and education: Developing open-source software, interactive visualization tools, and interdisciplinary training for students and early-career researchers.
“Students and postdocs working on this project will be supported by hands-on research and training at the intersection of groundwater hydrology, coastal science, computational modeling, and artificial intelligence, preparing them for careers addressing Hawaiʻi’s water and environmental challenges,” Lee stated.
Read the entire story on the Water Resources Research Center website.
