Physically based dimensionless features for pluvial flood mapping with machine learning
May 30, 2025
When minutes matter, communities need fast, accurate flood forecasts to protect lives and property
Flash floods are among the deadliest natural disasters, accounting for up to 90 percent of flood-related deaths each year. Predicting these events quickly is critical¡ªbut not easy. Traditional flood modeling methods¡ªlike detailed 2D hydraulic models¡ªare too slow and resource-intensive to meet real-time needs.
In collaboration with , our team recently published a study in Water Resources Research. It combines the power of physics with the speed of machine learning to create flood maps that are faster and more adaptable across diverse landscapes. This breakthrough could transform how cities, engineers, and emergency managers prepare for and respond to flash floods.
