Stream Nutrient Load and Concentration Estimation From Minimal Measurements
Document Type
Article
Publication Date
4-2025
Publisher
Wiley
Source Publication
Geophysical Research Letters
Source ISSN
0094-8276
Original Item ID
DOI: 10.1029/2025GL114935
Abstract
High-resolution measurements of nutrients in rivers are vital to assess water quality and catchment material balances. Yet, such measurements are often cost-prohibitive. To improve sampling efficiency, data-driven sparse sensing (DSS) is proposed to recover high-resolution nutrient time-series from sparse flow and concentration measurements. DSS leverages dimension-reduction to identify basis functions that optimally represent available data, and analyzes these basis functions to identify optimal times and locations for future measurements. A model trained on high-resolution flow and concentration measurements from few locations accurately reconstructed nutrient concentration time-series and annual loads at target sites spanning the Midwest region of the US. Optimal sampling times occurred in spring, while sampling locations were distributed across catchment area and flow. Sparse measurements (20–80 per year) at optimal sampling times and locations were sufficient to accurately estimate nutrient concentrations and loads (error < ±2% for NOx; < ±9% for total phosphorus). DSS promises to enable cost-effective water quality monitoring.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Mamoon, Wasif Bin; Zhang, Kun; Luhar, Mitul; and Parolari, Anthony J., "Stream Nutrient Load and Concentration Estimation From Minimal Measurements" (2025). Civil and Environmental Engineering Faculty Research and Publications. 412.
https://epublications.marquette.edu/civengin_fac/412
Comments
Geophysical Research Letters, Vol. 52, No. 8 (April 2025). DOI.