Track D: Hidden Water and Extreme Events: HydroGEN, A Physically Rigorous Machine Learning Platform for Hydrologic Scenario Generation

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Water is the driving force behind extreme events like floods, droughts and wildfires. These events have cost the US $234.3B in damages just in the past three years, and this figure is projected to increase. Recent events like the record setting wildfires in California and the mega drought on the Colorado river are merely the latest illustrations. Historical data are no longer a reliable guide for the risks we will face in the future. This project addresses the uncertainty that poses a huge challenge for decision makers. HydroGEN is a web-based machine learning (ML) platform that generates custom hydrologic scenarios on demand. It combines powerful physics-based simulations with ML and observations to provide customizable scenarios from the bedrock through the treetops. Without any prior modeling experience, water managers and planners can directly manipulate state-of-the-art tools to explore scenarios that matter to them.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.