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Water-R2O: National Science Foundation Research Traineeship (NRT)
Water R2O NRT Logo
National Science Foundation Logo
Alabama Water Institute Logo
CIROH - Cooperative Institute for Research to Operations in Hydrology

The NSF Water-R2O NRT program at The University of Alabama empowers students with knowledge, skills, and confidence to advance research into water prediction operations and impact. The unique graduate education program engages students in interdisciplinary courses in applied hydrology, water forecasting, and decision science; skill-building courses and workshops in artificial intelligence, machine learning, and hydrologic prediction; seminar courses and study tours connecting student research to operational hydrology; an experiential learning element such as a study abroad, internship, or other learning experience placing students in an operational hydrology context; and professional development workshops to enhance team science, communication, and problem solving. Graduates of the program will have the capability and confidence to design use-inspired research, translate that research into practice, and be thought leaders as part of the water prediction community of practice spanning academia, government, nonprofit, and the private sector.

This leverages best practices for professional training, adopted from the life and health-sciences, and builds on the institutional strengths at the UA and AWI. The novel use of stakeholder-driven challenges to guide the interdisciplinary curriculum creates a practice-driven and student-centered graduate education model that acts on longstanding recommendations for the improvement of STEM graduate education and ensures graduates overcome historical limitations identified by our external collaborators. Driving convergence, NRT faculty, students, and collaborating practitioners will advance ways to overcome the challenges of translating interdisciplinary scientific research into practice, building confidence in AIML use in hydrologic forecasting, and developing forecast products that lead to appropriate societal response.

Graduates of the program will be prepared to:

Address the interconnected hydrologic science and AIML challenges of nonstationarity and uncertainty

Aid stakeholder decision making under uncertainty

Enter the workforce with enhanced professional skills and the confidence to make decisions

Co-produce needs-based research following a team science approach engaging practitioners


Drastic and rapid onset of conditions, such as drought, intense rainfall, violent hurricanes, and dangerous water quality, and the growing consequences of these events is one of the most pressing challenges facing society. Decision-making to save lives, protect property, and sustain commerce needs precise, accurate, and early forecasts of these water-driven extreme hazards. Forecasters with the National Weather Service (NWS), other agencies, and the private sector continuously work to improve predictions and have ideas to guide research into practical applications. An opportunity exists to strengthen the water prediction community of practice by creating a transdisciplinary graduate training program that fuses research and innovation from academia with practical understanding from the operational context. Water R2O addresses this opportunity with a use-inspired graduate training program merging innovations in education with genuine practical experiences to address the most difficult water forecasting challenges.


The vision of the Water-R2O NRT is training a new generation of convergent scientists and engineers at the nexus of hydrology, geoscience, computer science, risk perceptions, and operational opportunities, who are expert in research in the NRT AI priority area and the NSF Bit Ideas of Harnessing the Data Revolution and the Future of Work at the Human-Technology Frontier.


The University of Alabama NRT project aims to integrate hydrologic engineering, artificial intelligence, and decision science into an interdisciplinary education program enhancing student capabilities for use-inspired research and careers in water forecasting.