Deep learning model predicts US pluvial flood damage at continental scale
Researchers have built DELUGE, a multimodal deep learning system that predicts pluvial flood damage across the continental US at 1 km resolution on a daily basis. The framework conditions on foundation model embeddings to interpret hazard, exposure, and vulnerability signals from satellite and claims data, addressing a critical gap in disaster forecasting where rainfall-driven floods represent 45% of US flood insurance claims yet remain harder to model than riverine or coastal events. The work demonstrates how foundation models can be repurposed for high-stakes infrastructure prediction at national scale, moving beyond regional or computationally prohibitive approaches.62
