Exploring the Spatiotemporal Heterogeneity of Stream Nitrogen Concentrations in a Typical Human‐Activity‐Influenced Headwater Watershed in South China
Abstract Stream nitrogen concentrations significantly impact nitrogen loads and greenhouse gas emissions, but their spatiotemporal heterogeneity and human influences remain highly uncertain. This study thoroughly explored the spatiotemporal variations in stream nitrogen concentrations in a typical h...
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| Format: | Article |
| Language: | English |
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Wiley
2024-09-01
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| Series: | Water Resources Research |
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| Online Access: | https://doi.org/10.1029/2024WR038050 |
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| author | Congsheng Fu Haixia Zhang Huawu Wu Haohao Wu Yang Cao Ye Xia Zichun Zhu |
| author_facet | Congsheng Fu Haixia Zhang Huawu Wu Haohao Wu Yang Cao Ye Xia Zichun Zhu |
| author_sort | Congsheng Fu |
| collection | DOAJ |
| description | Abstract Stream nitrogen concentrations significantly impact nitrogen loads and greenhouse gas emissions, but their spatiotemporal heterogeneity and human influences remain highly uncertain. This study thoroughly explored the spatiotemporal variations in stream nitrogen concentrations in a typical headwater watershed in South China. Spatially distributed measurements were conducted during 2020–2022, and mathematical modeling was implemented based on incorporating these data. More than 4,400 data points were collected for water temperature and concentrations of ammonium nitrogen (NH4‐N), nitrate nitrogen (NOx‐N), dissolved total nitrogen (DTN), total nitrogen (TN), and dissolved oxygen. Results showed that NOx‐N was the largest component of TN, with average concentrations of 1.20 and 1.66 mg L−1, respectively. The stream N2O concentration could be predicted using NH4‐N and NOx‐N concentrations via the Michaelis‐Menten equation. Significant downstream decreases in NH4‐N, NOx‐N, DTN, and TN concentrations were identified in the largest river in the watershed, and clear spatial differences in these nitrogen concentrations existed among the three main rivers. Clear seasonal and annual variations in stream nitrogen concentrations were observed. NH4‐N, NOx‐N, DTN, and TN concentrations correlated with cumulative precipitation from the preceding 8–12 days, while stream N2O concentrations correlated over 13–20 days. Stream N2O concentrations and emissions averaged 12.77 nmol L−1 and 1.12 nmol m−2 s−1, respectively, and were lower in summer than in other seasons. Upstream tea plantations, villages, and adjacent agricultural lands significantly affected nitrogen concentrations, while overflow dams did not. These findings highlight nitrogen cycle's complexity and the need for high‐resolution data to guide effective watershed management. |
| format | Article |
| id | doaj-art-fe5c0b61822344eaa5c3ca0601ac56b6 |
| institution | Kabale University |
| issn | 0043-1397 1944-7973 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | Water Resources Research |
| spelling | doaj-art-fe5c0b61822344eaa5c3ca0601ac56b62025-08-20T03:30:53ZengWileyWater Resources Research0043-13971944-79732024-09-01609n/an/a10.1029/2024WR038050Exploring the Spatiotemporal Heterogeneity of Stream Nitrogen Concentrations in a Typical Human‐Activity‐Influenced Headwater Watershed in South ChinaCongsheng Fu0Haixia Zhang1Huawu Wu2Haohao Wu3Yang Cao4Ye Xia5Zichun Zhu6Key Laboratory of Watershed Geographic Sciences Nanjing Institute of Geography and Limnology Chinese Academy of Sciences Nanjing ChinaKey Laboratory of Watershed Geographic Sciences Nanjing Institute of Geography and Limnology Chinese Academy of Sciences Nanjing ChinaKey Laboratory of Watershed Geographic Sciences Nanjing Institute of Geography and Limnology Chinese Academy of Sciences Nanjing ChinaKey Laboratory of Watershed Geographic Sciences Nanjing Institute of Geography and Limnology Chinese Academy of Sciences Nanjing ChinaKey Laboratory of Watershed Geographic Sciences Nanjing Institute of Geography and Limnology Chinese Academy of Sciences Nanjing ChinaKey Laboratory of Watershed Geographic Sciences Nanjing Institute of Geography and Limnology Chinese Academy of Sciences Nanjing ChinaKey Laboratory of Watershed Geographic Sciences Nanjing Institute of Geography and Limnology Chinese Academy of Sciences Nanjing ChinaAbstract Stream nitrogen concentrations significantly impact nitrogen loads and greenhouse gas emissions, but their spatiotemporal heterogeneity and human influences remain highly uncertain. This study thoroughly explored the spatiotemporal variations in stream nitrogen concentrations in a typical headwater watershed in South China. Spatially distributed measurements were conducted during 2020–2022, and mathematical modeling was implemented based on incorporating these data. More than 4,400 data points were collected for water temperature and concentrations of ammonium nitrogen (NH4‐N), nitrate nitrogen (NOx‐N), dissolved total nitrogen (DTN), total nitrogen (TN), and dissolved oxygen. Results showed that NOx‐N was the largest component of TN, with average concentrations of 1.20 and 1.66 mg L−1, respectively. The stream N2O concentration could be predicted using NH4‐N and NOx‐N concentrations via the Michaelis‐Menten equation. Significant downstream decreases in NH4‐N, NOx‐N, DTN, and TN concentrations were identified in the largest river in the watershed, and clear spatial differences in these nitrogen concentrations existed among the three main rivers. Clear seasonal and annual variations in stream nitrogen concentrations were observed. NH4‐N, NOx‐N, DTN, and TN concentrations correlated with cumulative precipitation from the preceding 8–12 days, while stream N2O concentrations correlated over 13–20 days. Stream N2O concentrations and emissions averaged 12.77 nmol L−1 and 1.12 nmol m−2 s−1, respectively, and were lower in summer than in other seasons. Upstream tea plantations, villages, and adjacent agricultural lands significantly affected nitrogen concentrations, while overflow dams did not. These findings highlight nitrogen cycle's complexity and the need for high‐resolution data to guide effective watershed management.https://doi.org/10.1029/2024WR038050headwater watershedstream nitrogen concentrationhuman influencesspatially distributed samplingmathematical modeling |
| spellingShingle | Congsheng Fu Haixia Zhang Huawu Wu Haohao Wu Yang Cao Ye Xia Zichun Zhu Exploring the Spatiotemporal Heterogeneity of Stream Nitrogen Concentrations in a Typical Human‐Activity‐Influenced Headwater Watershed in South China Water Resources Research headwater watershed stream nitrogen concentration human influences spatially distributed sampling mathematical modeling |
| title | Exploring the Spatiotemporal Heterogeneity of Stream Nitrogen Concentrations in a Typical Human‐Activity‐Influenced Headwater Watershed in South China |
| title_full | Exploring the Spatiotemporal Heterogeneity of Stream Nitrogen Concentrations in a Typical Human‐Activity‐Influenced Headwater Watershed in South China |
| title_fullStr | Exploring the Spatiotemporal Heterogeneity of Stream Nitrogen Concentrations in a Typical Human‐Activity‐Influenced Headwater Watershed in South China |
| title_full_unstemmed | Exploring the Spatiotemporal Heterogeneity of Stream Nitrogen Concentrations in a Typical Human‐Activity‐Influenced Headwater Watershed in South China |
| title_short | Exploring the Spatiotemporal Heterogeneity of Stream Nitrogen Concentrations in a Typical Human‐Activity‐Influenced Headwater Watershed in South China |
| title_sort | exploring the spatiotemporal heterogeneity of stream nitrogen concentrations in a typical human activity influenced headwater watershed in south china |
| topic | headwater watershed stream nitrogen concentration human influences spatially distributed sampling mathematical modeling |
| url | https://doi.org/10.1029/2024WR038050 |
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