Data-driven approaches demonstrate legacy N accumulation in Upper Mississippi River Basin groundwater
Increases in nitrogen (N) fertilizer application, livestock densities, and human population over the last century have led to substantial increases in nitrate contamination. While increases in riverine N loads are well-documented, the total magnitude of N accumulation in groundwater remains unknown....
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Format: | Article |
Language: | English |
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IOP Publishing
2023-01-01
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Series: | Environmental Research Letters |
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Online Access: | https://doi.org/10.1088/1748-9326/acea34 |
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author | Kimberly J Van Meter Victor O Schultz Shuyu Y Chang |
author_facet | Kimberly J Van Meter Victor O Schultz Shuyu Y Chang |
author_sort | Kimberly J Van Meter |
collection | DOAJ |
description | Increases in nitrogen (N) fertilizer application, livestock densities, and human population over the last century have led to substantial increases in nitrate contamination. While increases in riverine N loads are well-documented, the total magnitude of N accumulation in groundwater remains unknown. Here we provide a first data-driven estimate of N mass accumulation in groundwater within the Upper Mississippi River Basin (UMRB), an area of intensive row-crop agriculture and the primary contributor to Gulf of Mexico hypoxia. Using approximately 49 000 groundwater nitrate well concentration values and a suite of geospatial predictors, we developed a Random Forest model to produce gridded predictions of depth-varying nitrate concentrations. Our results suggest that approximately 15 Tg of N (328 ± 167 kg-N ha ^−1 ) is currently stored in UMRB groundwater recharged over the last 50 years. For context, we compare these predictions to those from a lumped statistical model, which predicts accumulation of 387 ± 133 kg-N ha ^−1 , as well as to a simple N mass balance model of the UMRB, which puts an upper bound on accumulation of approximately 1000 kg-N ha ^−1 (1967–2017). These findings highlight the importance of considering legacy N when forecasting future water quality, as N in the subsurface will continue to impair drinking water quality and elevate surface water N concentrations for decades to come. |
first_indexed | 2024-03-12T15:01:49Z |
format | Article |
id | doaj.art-b8160722d68c440c9582f5605a446ead |
institution | Directory Open Access Journal |
issn | 1748-9326 |
language | English |
last_indexed | 2024-03-12T15:01:49Z |
publishDate | 2023-01-01 |
publisher | IOP Publishing |
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series | Environmental Research Letters |
spelling | doaj.art-b8160722d68c440c9582f5605a446ead2023-08-14T06:23:38ZengIOP PublishingEnvironmental Research Letters1748-93262023-01-0118909401610.1088/1748-9326/acea34Data-driven approaches demonstrate legacy N accumulation in Upper Mississippi River Basin groundwaterKimberly J Van Meter0https://orcid.org/0000-0002-3698-7850Victor O Schultz1Shuyu Y Chang2Department of Geography, Pennsylvania State University, 302 Walker Building , University Park, PA 16802, United States of America; Earth and Environmental Systems Institute, Pennsylvania State University, 2217 Earth-Engineering Sciences Building , University Park, PA 16802-6813, United States of AmericaDepartment of Earth and Environmental Sciences, University of Illinois at Chicago , 845 W. Taylor St., Chicago, IL 60608, United States of AmericaDepartment of Geography, Pennsylvania State University, 302 Walker Building , University Park, PA 16802, United States of America; Earth and Environmental Systems Institute, Pennsylvania State University, 2217 Earth-Engineering Sciences Building , University Park, PA 16802-6813, United States of AmericaIncreases in nitrogen (N) fertilizer application, livestock densities, and human population over the last century have led to substantial increases in nitrate contamination. While increases in riverine N loads are well-documented, the total magnitude of N accumulation in groundwater remains unknown. Here we provide a first data-driven estimate of N mass accumulation in groundwater within the Upper Mississippi River Basin (UMRB), an area of intensive row-crop agriculture and the primary contributor to Gulf of Mexico hypoxia. Using approximately 49 000 groundwater nitrate well concentration values and a suite of geospatial predictors, we developed a Random Forest model to produce gridded predictions of depth-varying nitrate concentrations. Our results suggest that approximately 15 Tg of N (328 ± 167 kg-N ha ^−1 ) is currently stored in UMRB groundwater recharged over the last 50 years. For context, we compare these predictions to those from a lumped statistical model, which predicts accumulation of 387 ± 133 kg-N ha ^−1 , as well as to a simple N mass balance model of the UMRB, which puts an upper bound on accumulation of approximately 1000 kg-N ha ^−1 (1967–2017). These findings highlight the importance of considering legacy N when forecasting future water quality, as N in the subsurface will continue to impair drinking water quality and elevate surface water N concentrations for decades to come.https://doi.org/10.1088/1748-9326/acea34water qualitygroundwaternitrogen |
spellingShingle | Kimberly J Van Meter Victor O Schultz Shuyu Y Chang Data-driven approaches demonstrate legacy N accumulation in Upper Mississippi River Basin groundwater Environmental Research Letters water quality groundwater nitrogen |
title | Data-driven approaches demonstrate legacy N accumulation in Upper Mississippi River Basin groundwater |
title_full | Data-driven approaches demonstrate legacy N accumulation in Upper Mississippi River Basin groundwater |
title_fullStr | Data-driven approaches demonstrate legacy N accumulation in Upper Mississippi River Basin groundwater |
title_full_unstemmed | Data-driven approaches demonstrate legacy N accumulation in Upper Mississippi River Basin groundwater |
title_short | Data-driven approaches demonstrate legacy N accumulation in Upper Mississippi River Basin groundwater |
title_sort | data driven approaches demonstrate legacy n accumulation in upper mississippi river basin groundwater |
topic | water quality groundwater nitrogen |
url | https://doi.org/10.1088/1748-9326/acea34 |
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