This summer, nine students participated in the AI for Operational Hydrology REU, a partnership between the Cooperative Institute for Research to Operations in Hydrology and The University of Alabama Graduate School that focuses on applying artificial intelligence to water forecasting challenges.
Springtime river ice floods threaten northern communities, but a CIROH-funded project is changing that. A team at Stevens Institute of Technology, led by Marouane Temimi, has developed a system that combines satellite imagery and machine learning to monitor river ice in near real-time.
The Alabama Water Institute has selected four UA faculty as 2025–28 fellows, advancing research in algae and coral science, water security, AI in hydrology and environmental modeling.
More than 225 researchers, students and partners gathered at the University of Vermont for the 2025 CIROH Developers Conference.
CIROH’s new Student Developer Award spotlights early career innovation. Winner Savalan Naser Neisary shares how DevCon and mentorship are shaping his path.
Most rivers lack gauges, leaving gaps in flood forecasting, water management and emergency planning. This new machine learning approach uses downstream data to predict upstream flow with no sensors needed.
New machine learning tool sharpens National Water Model forecasting—cutting bias, boosting accuracy and helping water managers respond to drought across the Western U.S. and beyond.
The CIROH Developers Conference is back for its third year—this time with an even stronger focus on hands-on training and interdisciplinary collaboration.
Researchers are transforming weather forecasting in American Samoa by deploying AI and machine learning to enhance local monitoring and connecting the region to national and global climate models
Global water experts gathered in Tuscaloosa for HEPEX 2025, spotlighting breakthroughs in ensemble forecasting, AI modeling and CIROH’s role in shaping the future of hydrological prediction.
