Authors: Jonathan Frame – University of Alabama
Title: CIROH AI Strategy
Presentation Type: Poster Presentation
Abstract:
The Cooperative Institute for Research to Operations in Hydrology (CIROH) AI strategy aligns with NOAA’s vision to transform water prediction through coordinated, high-stakes operational deployment. By defining AI as a system for increasing efficiency, precision, and objectivity, CIROH bridges the gap between research and operations through five key pillars: expanding AI focus beyond streamflow to include decision support and water quality; prioritizing ‘small wins’ and benchmarking via the NextGen framework to build institutional trust; developing an ‘end-to-end’ training environment to prevent model degradation; pursuing high-risk, high-reward foundation models that reveal emergent physical behaviors; and ensuring responsible, human-centric forecasting through explainability and uncertainty quantification. As national infrastructure initiatives like the Genesis Mission accelerate, CIROH ensures that domain-specific hydrologic expertise leads the AI transition, delivering fair, scalable, and actionable water intelligence that enhances community resilience against extreme events.