The Alabama Water Institute continues to support its affiliated faculty members and their research across The University of Alabama with new tools that expand capabilities in labs and in the field.
CIROH researchers have harnessed NASA’s satellite data to sharpen a critical piece of flood forecasting: river slope. Their new datasets improve U.S. flood models by more than 30%, giving emergency managers faster, more reliable information to protect communities during extreme weather.
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.
Op-Ed by Dr. Travis Loof Setting the Scene A few minutes before 8 a.m., the room was a quiet mix of coffee cups, maps and county binders. Then the briefing began. A Helene-like hurricane had tracked inland and pushed up the I-65 corridor. The scenario was blunt. Statewide power impacts. Road washouts. Compounding hazards. My…
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.
AWI’s Water-R2O NSF Research Traineeship program celebrated the graduation of its 2024-2025 cohort, capping a year of hands-on water science training that spanned the Southeastern U.S. and four European countries.
Dr. Jonathan Frame has secured a National Science Foundation grant to investigate how expanding AI infrastructure will impact water resources—a critical issue he believes will define the next decade of water management.
Tuscaloosa, a town synonymous with SEC football, becomes the epicenter of America’s next-generation water workforce development each summer.
The University of Alabama's Water-R2O NRT program welcomes third cohort of graduate students for study tours, seminars and international experiences while developing cutting-edge skills in machine learning applied to hydrologic prediction.
AWI and CIROH highlighted their water resource management collaborations at the AMS 105th Annual Meeting.
