Flood risk rarely originates from a single source. The concurrent or sequential occurrence of riverine flooding, urban inundation, and coastal surge, compounded by extreme precipitation, antecedent soil moisture, and vulnerable entities, poses escalating threats to lives, infrastructure, and ecosystems worldwide. Yet modelling frameworks for these interacting hazards remain largely siloed, limiting our ability to capture cross-system feedbacks, cascading failures, and the full spectrum of compound flood scenarios.
This session invites contributions that advance the science of multi-hazard flood risk modelling across interconnected riverine, urban, and coastal systems. We particularly welcome studies that compare or couple hydrodynamic, statistical, and data-driven approaches, including machine learning and physics-based models, with an emphasis on model benchmarking, performance under data-scarce conditions, uncertainty quantification, and scalable flood mapping. Contributions addressing process representation of compound events, non-stationarity, and climate change impacts on flood frequency are strongly encouraged.

• A - Atmospheric Sciences
• GC - Global Environmental Change
• H - Hydrology
• OS - Ocean Sciences