This session invites contributions that advance the theory, development, and application of digital solutions, such as digital twins, in water resources research and management. Hydrologic digital twins are virtual representations of water systems that are continuously updated with real-time observations, allowing for simulation, analysis, and automatic and autonomous management. These, and other digital solutions are crucial in advancing the application and impact of scientific technical and theoretical findings by end user stake holders. Under changing environmental conditions and risk of regional and global natural hazards, advanced two-ways data transfer and scientific information solutions are more crucial than ever. We welcome presentations on multi-scale digital solutions, such as: physical modelling frameworks; fusion of next-generation hydrologic observations into modelling frameworks, including remote sensing, in-situ, and crowd-sourced data; automated data networking, processing, and assimilation systems; machine learning and hybrid approaches in model-data integration; uncertainty quantification and propagation in data assimilation workflows; real-time forecasting and decision support systems for water resources and disaster management; autonomous processes and embedded devices in water resources management; and case studies of digital twins in water resources research and applications. We are particularly interested in work that supports scale translation in hydrologic systems modelling (both spatial and temporal), and enables the coupling of physical and data-driven models. Submissions from the Digital Waters Flagship and Pilot (https://digitalwaters.fi) are strongly encouraged.