Measuring the quantity and quality of water in river, lake, reservoir, and wetland systems is essential for water resource management and for understanding of the global hydrologic cycle. Remote sensing techniques, both passive and active, offer the potential to address knowledge gaps by providing near real-time observations and multi-decadal data records across local to global scales, particularly important in data-sparse regions. This session invites contributions that leverage remote sensing—from airborne to spaceborne platforms—to characterize water levels, volumes, flows, connectivity, extent dynamics, inland and coastal flooding, and water quality conditions. We encourage submissions that feature innovative methodologies and applications including new algorithms/datasets leveraging AI/ML, integration with models or in situ data, as well as new applications for exploring the roles of these inland water bodies in water management, flood and drought mitigation, hydrologic cycles, land-atmosphere interactions, and ecosystem services.