# CAREER: Understanding nutrient dynamics in American rivers through remote sensing and artificial intelligence

> **NSF 01003031DB NSF RESEARCH & RELATED ACTIVIT** · University of Cincinnati Main Campus (OH) · $781,233

## Abstract

This award supports the study of nutrient runoff and its effects on American river systems. Nitrogen and phosphorus are known to cause harmful algal blooms and other ecological impacts in rivers. However, knowledge about the causes of variability in nutrient loads across river networks remains limited. Through the application of artificial intelligence to data from satellite remote sensing, this project will generate a detailed map of nutrients in rivers across the United States over time. This map will then be analyzed to understand human and natural factors affecting nutrient variability. This research integrates with education for high school, undergraduate, and graduate students. Project outcomes will support water management, ecosystem protection, and public health.

This project will pursue three objectives. (1) A novel modeling framework that integrates remote sensing and deep learning will be developed. This framework will be used to estimate daily, reach-level total phosphorus and total nitrogen concentration in American rivers over the past five decades. (2) Major drivers and controlling mechanisms for nutrient variability across space and time will be identified. (3) Relationships between riverine nutrients and harmful algal blooms across various settings will be quantified. Outcomes of these analyses will reveal spatial patterns of nutrient sensitivity and eutrophication risk.

This award reflects NSF's statutory mission and has been deemed worthy of support 

## Key facts

- **NSF award ID:** 2540333
- **Awardee organization:** University of Cincinnati Main Campus (OH)
- **SAM.gov UEI:** DZ4YCZ3QSPR5
- **PI:** Dongmei Feng
- **Primary program:** 01003031DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** CAREER-Faculty Erly Career Dev
- **Estimated total:** $781,233
- **Funds obligated:** $367,829
- **Transaction type:** Continuing Grant
- **Period:** 09/01/2026 → 08/31/2031

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2540333

## Citation

> US National Science Foundation, Award 2540333, CAREER: Understanding nutrient dynamics in American rivers through remote sensing and artificial intelligence. Retrieved via AI Analytics 2026-06-07 from https://api.ai-analytics.org/grant/nsf/2540333. Licensed CC0.

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