Monitoring Dissolved Organic Carbon Concentration and Flux in the Qiantang Riverine System Using Sentinel-2 Satellite Images
Real-time monitoring of riverine-dissolved organic carbon (DOC) and its controlling factors is critical for formulating strategies regarding the river basin and marginal seas pollution prevention and control. In this study, we established a linear regression formulation that relates the permanganate...
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2024-11-01
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| author | Yujia Yan Xianqiang He Yan Bai Jinsong Liu Palanisamy Shanmugame Yaqi Zhao Xuan Zhang Zhihong Wang Yifan Zhang Fang Gong |
| author_facet | Yujia Yan Xianqiang He Yan Bai Jinsong Liu Palanisamy Shanmugame Yaqi Zhao Xuan Zhang Zhihong Wang Yifan Zhang Fang Gong |
| author_sort | Yujia Yan |
| collection | DOAJ |
| description | Real-time monitoring of riverine-dissolved organic carbon (DOC) and its controlling factors is critical for formulating strategies regarding the river basin and marginal seas pollution prevention and control. In this study, we established a linear regression formulation that relates the permanganate index (COD<sub>Mn</sub>) to the DOC concentration based on in situ measurements collected on five field surveys in 2023–2024. This regression formulation was used on a large number of data collected from automatic monitoring stations in the Qiantang River area to construct a daily quasi-in situ database of DOC concentration. By combining the quasi-in situ DOC data and Sentinel-2 measurements, an enhanced algorithm for empirical DOC estimation was developed (R<sup>2</sup> = 0.66) using the extreme gradient boosting (XGBoost) method and its spatial and temporal variations in the Qiantang River were analyzed from 2016 to 2023. Spatially, the main stream of the Qiantang River exhibited an overall decreasing and increasing trend influenced by population density, economic development, and pollutant discharge in the basin area, and the temporal distribution of DOC was controlled by meteorological conditions. The DOC contents had the highest in summer, primarily due to high rainfall and leaching. The inter-annual variation in DOC concentration was influenced by the total annual runoff volumes, with a minimum level of 2.24 mg L<sup>−1</sup> in 2023 and a maximum level of 2.45 mg L<sup>−1</sup> in 2019. The monthly DOC fluxes ranged from 6.3 to 13.8 × 10<sup>4</sup> t, with the highest values coinciding with the maximum river discharge volumes in June and July. The DOC levels in the Qiantang River remained relatively high in recent years (2016–2023). This study enables the concerned stakeholders and researchers to better understand carbon transportation and its dynamics in the Qiantang River and its coastal areas. |
| format | Article |
| id | doaj-art-7df8046e42154e20ab3ff60dac7fb5e8 |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-7df8046e42154e20ab3ff60dac7fb5e82024-11-26T18:20:11ZengMDPI AGRemote Sensing2072-42922024-11-011622425410.3390/rs16224254Monitoring Dissolved Organic Carbon Concentration and Flux in the Qiantang Riverine System Using Sentinel-2 Satellite ImagesYujia Yan0Xianqiang He1Yan Bai2Jinsong Liu3Palanisamy Shanmugame4Yaqi Zhao5Xuan Zhang6Zhihong Wang7Yifan Zhang8Fang Gong9Ocean College, Zhejiang University, Zhoushan 316021, ChinaState Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, ChinaState Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, ChinaZhejiang Ecological Environment Monitoring Center, Hangzhou 310012, ChinaOcean Optics and Imaging Laboratory, Department of Ocean Engineering, Indian Institute of Technology Madras, Chennai 600036, IndiaOcean College, Zhejiang University, Zhoushan 316021, ChinaState Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, ChinaState Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, ChinaState Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, ChinaState Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, ChinaReal-time monitoring of riverine-dissolved organic carbon (DOC) and its controlling factors is critical for formulating strategies regarding the river basin and marginal seas pollution prevention and control. In this study, we established a linear regression formulation that relates the permanganate index (COD<sub>Mn</sub>) to the DOC concentration based on in situ measurements collected on five field surveys in 2023–2024. This regression formulation was used on a large number of data collected from automatic monitoring stations in the Qiantang River area to construct a daily quasi-in situ database of DOC concentration. By combining the quasi-in situ DOC data and Sentinel-2 measurements, an enhanced algorithm for empirical DOC estimation was developed (R<sup>2</sup> = 0.66) using the extreme gradient boosting (XGBoost) method and its spatial and temporal variations in the Qiantang River were analyzed from 2016 to 2023. Spatially, the main stream of the Qiantang River exhibited an overall decreasing and increasing trend influenced by population density, economic development, and pollutant discharge in the basin area, and the temporal distribution of DOC was controlled by meteorological conditions. The DOC contents had the highest in summer, primarily due to high rainfall and leaching. The inter-annual variation in DOC concentration was influenced by the total annual runoff volumes, with a minimum level of 2.24 mg L<sup>−1</sup> in 2023 and a maximum level of 2.45 mg L<sup>−1</sup> in 2019. The monthly DOC fluxes ranged from 6.3 to 13.8 × 10<sup>4</sup> t, with the highest values coinciding with the maximum river discharge volumes in June and July. The DOC levels in the Qiantang River remained relatively high in recent years (2016–2023). This study enables the concerned stakeholders and researchers to better understand carbon transportation and its dynamics in the Qiantang River and its coastal areas.https://www.mdpi.com/2072-4292/16/22/4254dissolved organic carbonQiantang Rivertime series analysisSentinel-2machine learningremote sensing |
| spellingShingle | Yujia Yan Xianqiang He Yan Bai Jinsong Liu Palanisamy Shanmugame Yaqi Zhao Xuan Zhang Zhihong Wang Yifan Zhang Fang Gong Monitoring Dissolved Organic Carbon Concentration and Flux in the Qiantang Riverine System Using Sentinel-2 Satellite Images Remote Sensing dissolved organic carbon Qiantang River time series analysis Sentinel-2 machine learning remote sensing |
| title | Monitoring Dissolved Organic Carbon Concentration and Flux in the Qiantang Riverine System Using Sentinel-2 Satellite Images |
| title_full | Monitoring Dissolved Organic Carbon Concentration and Flux in the Qiantang Riverine System Using Sentinel-2 Satellite Images |
| title_fullStr | Monitoring Dissolved Organic Carbon Concentration and Flux in the Qiantang Riverine System Using Sentinel-2 Satellite Images |
| title_full_unstemmed | Monitoring Dissolved Organic Carbon Concentration and Flux in the Qiantang Riverine System Using Sentinel-2 Satellite Images |
| title_short | Monitoring Dissolved Organic Carbon Concentration and Flux in the Qiantang Riverine System Using Sentinel-2 Satellite Images |
| title_sort | monitoring dissolved organic carbon concentration and flux in the qiantang riverine system using sentinel 2 satellite images |
| topic | dissolved organic carbon Qiantang River time series analysis Sentinel-2 machine learning remote sensing |
| url | https://www.mdpi.com/2072-4292/16/22/4254 |
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