Primary Convener:
Majid Shafiee-Jood, University of Virginia

Convener:
Paul Block, University of Wisconsin Madison
Hamid Moradkhani, The University of Alabama
David Watkins, Michigan Technological University
Ximing Cai, University of Illinois

Early Career Convener:
Majid Shafiee-Jood, University of Illinois at Urbana Champaign

Chair:
Majid Shafiee-Jood, University of Illinois at Urbana Champaign
Paul Block, University of Wisconsin Madison

Advances in hydroclimatic forecasting, including short-term, sub-seasonal, and seasonal forecasts, can support more effective water resources management, climate adaptation, and resilience to extreme events. However, forecast use in the water sector remains limited when forecasts are not aligned with information needs and institutional contexts, or when benefits and risks are poorly understood by decision-makers. While emerging tools such as machine learning offer exciting opportunities to enhance forecast skill, their increasing complexity may widen the gap between technical potential and societal benefit, particularly if outputs are not transparent, interpretable, or aligned with decision-makers’ needs. This session brings together communities of practice and researchers to discuss interdisciplinary perspectives on using forecasts in water resources decision-making. Topics may include advances in forecast accuracy and timeliness, uncertainty quantification, communication, usability, and co-production of forecasts. We also welcome contributions on integrating forecasts into real-world planning and institutional arrangements that support adaptive use of hydroclimatic information.

Index Terms
1833 Hydroclimatology
1880 Water management
1922 Forecasting
6309 Decision making under uncertainty

Suggested Itineraries:
Disasters‚ Calamities and Extreme Events
Science Communications
Machine Learning and AI

Cross-Listed:
SY - Science and Society

Neighborhoods:
3. Earth Covering