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

水是洪水、干旱和野火等极端事件背后的驱动力。仅在过去三年中，这些事件就造成了2343亿美元的损失，预计这一数字还会增加。最近发生的事件，如加利福尼亚创纪录的野火和科罗拉多河的特大干旱，只是最新的例证。历史数据不再是我们未来将面临的风险的可靠指南。该项目解决了给决策者带来巨大挑战的不确定性。HydroGEN是一个基于网络的机器学习（ML）平台，可以根据需要生成定制的水文场景。它将强大的基于物理的模拟与ML和观察相结合，从基岩到树顶提供可定制的场景。没有任何先前的建模经验，水资源管理者和规划者可以直接操纵最先进的工具来探索对他们重要的场景。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.