Monitoring and spatial traceability of river water quality using Sentinel-2 satellite images

Yingyin Zhang; Xianqiang He; Gang Lian; Yan Bai; Ying Yang; Fang Gong; Difeng Wang; Zili Zhang; Teng Li; Xuchen Jin

doi:10.1016/j.scitotenv.2023.164862

Monitoring and spatial traceability of river water quality using Sentinel-2 satellite images

Sci Total Environ. 2023 Oct 10:894:164862. doi: 10.1016/j.scitotenv.2023.164862. Epub 2023 Jun 20.

Authors

Yingyin Zhang¹, Xianqiang He², Gang Lian³, Yan Bai⁴, Ying Yang³, Fang Gong⁵, Difeng Wang⁵, Zili Zhang³, Teng Li⁵, Xuchen Jin⁶

Affiliations

¹ Ocean College, Zhejiang University, Zhoushan 316021, China.
² State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China. Electronic address: hexianqiang@sio.org.cn.
³ Zhejiang Key Laboratory of Ecological and Environmental Monitoring, Zhejiang Ecological and Environmental Monitoring Centre, Hangzhou 310012, China.
⁴ State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China; Donghai Laboratory, Zhoushan 316021, China; School of Oceanography, Shanghai Jiao Tong University, Shanghai 200030, China.
⁵ State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China.
⁶ South Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 510000, Guangdong, China.

PMID: 37348720
DOI: 10.1016/j.scitotenv.2023.164862

Abstract

Due to limited monitoring stations along rivers, it is difficult to trace the specific locations of high pollution areas along the whole river by traditionally in situ measurement. High-spatiotemporal-resolution Sentinel-2 satellite images make it possible to routinely monitor and trace the spatial distributions of river water quality if reliable retrieval algorithms are available. This study took seven major rivers (Qiantang River (QTR), Cao'e River (CEJ), Yongjiang River (YJ), Jiaojiang River (JJ), Oujiang River (OJ), Feiyun River (FYR), and Aojiang River (AJ)) in Zhejiang Province, China, as examples to illustrate the spatial traceability of river water quality parameters (permanganate index (COD_Mn), total phosphorus (TP), and total nitrogen (TN)) from Sentinel-2 satellite images. The regional retrieval models established for these parameters (COD_Mn, TP and TN) provided correlation coefficients (R) of 0.68, 0.82, and 0.7, respectively. Based on these models, time-series COD_Mn, TP, and TN products were obtained for the seven rivers from 2016 to 2021 from Sentinel-2 satellite images, and the results show that the COD_Mn, TP and TN were high downstream and low upstream; exceptions the CEJ, which was slightly higher in the middle reach than other reaches, and the TN in YJ, which was higher upstream than downstream. The downstream reaches were the main areas suffering from relatively high values in most seasons. Except for the springtime TN level in CEJ, the high value areas were located along the middle reaches. In summer and autumn, the high TN areas in JJ, OJ, and AJ were located along the middle and lower reaches, and the TN in YJ was highest in the upstream. More importantly, this study revealed that the specific locations of high pollution areas along rivers can be effectively traced using Sentinel-2 satellite images, which would be helpful for precise water quality control of rivers.

Keywords: Retrieval algorithms; River water quality; Satellite remote sensing; Sentinel-2 images; Spatial traceability.