Advances in hydroclimatic forecasting, from short-term to seasonal scales, offer growing potential to inform water resources management, climate adaptation, and resilience to extremes. While uptake has expanded in some domains, challenges remain in aligning forecasts with decision processes, demonstrating value in practice, and integrating them into institutional workflows. Increasing model complexity, including AI-based forecasts, also raises new challenges around interpretability, trust, and operational use. This session invites transdisciplinary contributions that advance both the development and application of hydroclimatic forecasts in water resources decision-making. We welcome work on improving forecast accuracy and uncertainty characterization, alongside efforts to better understand how forecasts are interpreted, communicated, and used. Topics may include decision-centered evaluation of forecasts, uncertainty communication, co-production with stakeholders, and challenges related to human-AI integration including interpretability, trust, and effective human-machine collaboration. Contributions on sequential and adaptive decision-making and real-world integration into planning, operations, and institutional frameworks are especially encouraged.

• A - Atmospheric Sciences
• NH - Natural Hazards
• SY - Science and Society