Climate and anthropogenic stressors influence urban hydrology through local- and regional-scale mechanisms such as changing natural flow pathways, disturbing short- and long-term water and energy balance, and altering ecosystem functions. Physical-based modeling and data-driven analyses can provide insights into the intricacies of interactions between these stressors and urban hydrological systems. The physical-based modeling approach allows us to experiment with various conceptual frameworks, while the data-driven approach facilitates integrating GIS and remote sensing technologies for testing different hypotheses and identifying emerging patterns.

This session invites studies towards (1) quantifying the impacts of anthropogenic stressors in urban areas at local, regional, and global scales, (2) advances in multiscale integrated physically based models for urban hydrology, (3) advances in data-based models for direct and indirect assessment of the stressors, (4) advances in integrating remote sensing and ground-truth data with machine learning techniques for urban studies.