Chris Micucci

Flood inundation models are tools that predict where water flows, how deep it gets, how fast it moves and how long it remains during a flood event. But despite recent advances in flood inundation models, some flood modeling paradigms are being used beyond their range of applicability rather than leveraging the strengths of different methods.

Machine learning (ML)-based models hold great potential to enhance and perhaps transform simulations of the Earth’s weather and climate across the range from synoptic to seasonal to annual to multi-decadal time scales. However, ML-based models should also produce results consistent with the physical laws of the Earth system.