Collaborative Research: A Physics-Informed Flood Early Warning System for Agricultural Wat — NSF Award to Tulane University (LA, $
Global floods and extreme rainfall events have surged by more than 50% this decade and are now occurring at a rate four times higher than in 1980. However, the capability of physical models in predicting flood events remains limited across spatial scales, especially in intensively managed agricultural systems like the
| Award title | Collaborative Research: A Physics-Informed Flood Early Warning System for Agricultural Wat |
|---|---|
| Award ID | 2611747 |
| Awardee | Tulane University |
| City | NEW ORLEANS |
| State | LA |
| Amount obligated | $92,927 |
| Principal investigator | Yusuf Sermet |
| Program | GEO CI - GEO Cyberinfrastrctre |
| Start date | 11/01/2025 |
| Abstract | Global floods and extreme rainfall events have surged by more than 50% this decade and are now occurring at a rate four times higher than in 1980. However, the capability of physical models in predicting flood events remains limited across spatial scales, especially in intensively managed agricultural systems like the Midwestern U.S. The apparent disparity between observed seasonal patterns of extreme precipitation and high streamflow events presents a challenge when using precipitation alone to |
| Source | NSF Awards |
$799/mo
Try NSFGrants →