Digital Water strategies - such as artificial intelligence (including the more traditional machine learning, generative, and agentic AI), digital twins, smart sensing, real-time data systems and decision-support tools - are reshaping how human-water systems are observed, interpreted, modeled, and managed. Their value, however, depends on how effectively they can support (and explain) better decision-making, improve operational planning and strategic management, and enhance resilience in the face of changing climatic and socio-economic conditions.

This session focuses on both emerging Digital Water methods and the pathways through which data and models become actionable. We welcome contributions on new technological and methodological approaches, including behavioral and human-in-the-loop models that represent how individuals, stakeholders, and institutions respond to information, incentives, risks, and changing water conditions. Relevant topics include AI, data-driven and hybrid modeling, digital twins, behavioral modeling, decision-support systems, and human–model interaction, stakeholder engagement and co-production, and institutional dynamics and governance - including data governance, responsible data sharing, accountability, responsibility, and decision authority in digitally supported water governance. Further topics include equity and human values in water decisions, as well as dealing with uncertainty, explainability and interpretability, bias, and implementation barriers.

Applications may span water supply and demand, drought and flood risk, water quality, infrastructure planning and operation, water allocation, conservation, and climate adaptation. The session aims to advance both innovative Digital Water approaches and understanding of how they shape behavior, decisions, governance, and resilience in human-water systems.