Freshwater systems are sentinels of environmental change, yet the ways they are reshaped by global change and local human pressures remain difficult to quantify across scales. Rapid advances in Earth observation and artificial intelligence (AI) create opportunities to integrate heterogeneous datasets into coherent, multidimensional views of rivers, lakes, and wetlands. This session explores how these emerging approaches can improve our understanding of freshwater change across scales, with particular emphasis on geomorphic trajectories and human impacts. We invite contributions combining remote sensing, in-situ observations, and models to investigate processes such as glacier melt, permafrost thaw, mining, and river regulation, including dams and other infrastructure, and their impacts on freshwater systems. We encourage submissions assessing uncertainties, scaling challenges, and opportunities and limits of AI-based approaches for leveraging new data. The goal is to advance remote sensing, data fusion, and AI-based approaches for observing, integrating, and interpreting freshwater geomorphic change at large scales.

• GC - Global Environmental Change
• H - Hydrology
• SY - Science and Society