Monitoring Water Quality Parameters Using Sentinel-2 Data: A Case Study in the Weihe River Basin (China)

Tieming Liu, Zhao Guo, Xiaoping Li, Teng Xiao, Jiaxin Liu and Yuanzhi Zhang ()
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Tieming Liu: Xi’an Land Improvement and Ecological Restoration Center, Xi’an 710018, China
Zhao Guo: College of Geology and Environment, Xi’an University of Science and Technology, Xi’an 710054, China
Xiaoping Li: Chinese Geological Engineering Group, 92 Xiangshan South Road, Beijing 100089, China
Teng Xiao: School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
Jiaxin Liu: School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
Yuanzhi Zhang: School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China

Sustainability, 2024, vol. 16, issue 16, 1-18

Abstract: Based on Sentinel-2 multispectral image data and existing research results, the comprehensive water quality index (CWQI), NH 4 + -N, and total phosphorus (TP) in the Weihe River and its tributaries were estimated. Furthermore, a verified model was obtained by fitting the regression using the measured and inverted data. The verified model results show that the average relative error of the CWQI is only 9.80%, the goodness of fit of NH 4 + -N and TP concentrations is 0.62 and 0.61, respectively, and the average relative errors are 19.40% and 24.70%, respectively. The accuracy of the verified model is relatively high, and it can approximately invert the distribution of the three parameters of the Weihe River and its tributaries. In December 2023, except for the Bahe River between Puhua Town and Sanli Town in Lantian County, most of the water bodies in the Weihe River and its tributaries had good water quality. The study can provide an example of how to monitor water quality information using Sentinel-2 data in similar river basins.

Keywords: Sentinel-2; Weihe River; water quality; inversion (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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