| NSF Org: |
ITE Innovation and Technology Ecosystems |
| Recipient: |
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| Initial Amendment Date: | September 15, 2021 |
| Latest Amendment Date: | August 8, 2024 |
| Award Number: | 2134892 |
| Award Instrument: | Cooperative Agreement |
| Program Manager: |
Michael Reksulak
mreksula@nsf.gov (703)292-8326 ITE Innovation and Technology Ecosystems TIP Directorate for Technology, Innovation, and Partnerships |
| Start Date: | October 1, 2021 |
| End Date: | March 31, 2026 (Estimated) |
| Total Intended Award Amount: | $5,000,000.00 |
| Total Awarded Amount to Date: | $5,500,000.00 |
| Funds Obligated to Date: |
FY 2022 = $2,389,834.00 FY 2024 = $500,000.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
845 N PARK AVE RM 538 TUCSON AZ US 85721 (520)626-6000 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
888 Euclid Ave Tucson AZ US 85719-4824 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
Convergence Accelerator Resrch, NAIRR-Nat AI Research Resource |
| Primary Program Source: |
01002425DB NSF RESEARCH & RELATED ACTIVIT 01002122DB NSF RESEARCH & RELATED ACTIVIT 01002223DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070, 47.084 |
ABSTRACT
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.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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