Hydrologic data have traditionally been sparse in space and time, requiring process-based models to interpolate observations and predict fluxes under limited data availability. Rapid advances in observation technologies are now enabling near–real-time monitoring of complex hydrologic processes across a wide range of spatial and temporal scales, fundamentally transforming hydrology from data scarcity to data abundance. Fully exploiting these emerging observation systems requires parallel advances in digital tools for data processing, integration, modeling, and visualization. New digital solutions—including digital twins, real-time data platforms, and interactive visualization environments—play a critical role in translating novel observations and scientific insights into actionable information for water resources research, management, and decision-making. Under accelerating environmental change, two-way data exchange between models, observations, and stakeholders is increasingly essential for responsive forecasting and intervention. This session invites contributions on next-generation hydrologic observation systems and multi-scale digital solutions that advance process understanding, modeling, and application. Topics of interest include, but are not limited to:
- Novel observation techniques enabling improved parametrization of hydrologic processes
- Integration and fusion of next-generation hydrologic observations into modeling frameworks
- Digital twins and other advanced digital representations of hydrologic systems
- Real-time forecasting, early-warning, and decision-support systems for water resources and hydrologic hazards
- Case studies demonstrating the operational use and societal impact of hydrologic digitization