# CAREER: Understanding the dynamics and predictability of land-to-aquatic nitrogen loading under climate extremes by combining deep learning with process-based modeling

**Budget Signal Score:** 40/100

| Field | Value |
|---|---|
| Institution | University of Wisconsin-Madison |
| Location | MADISON, WI |
| Project | CAREER: Understanding the dynamics and predictability of land-to-aquatic nitrogen loading under climate extremes by combining deep learning with process-based modeling |
| Award amount | $610,283 |
| Obligated so far | $153,129 |
| Awarded | 2026-09-22 |
| Period | 2026-11-01 to 2027-05-31 |
| Program | Hydrologic Sciences |
| Directorate / division | GEO / GCP |
| Award ID | 2640152 |

## Why this score
- Award of $300K or more.

Source: U.S. National Science Foundation Awards API (https://www.nsf.gov/awardsearch/showAward?AWD_ID=2640152). Last refreshed: 2026-11-04T18:13:44.963Z.
Award data comes from the NSF Awards API and may be amended by NSF. Institution-level only; investigator contact details are not included. Informational only.