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Article

Water Quality Variability and Related Factors along the Yangtze River Using Landsat-8

1
School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
2
Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China
3
College of Sciences, Shanghai University, Shanghai 200444, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2021, 13(12), 2241; https://doi.org/10.3390/rs13122241
Submission received: 16 April 2021 / Revised: 2 June 2021 / Accepted: 7 June 2021 / Published: 8 June 2021

Abstract

Chlorophyll-a (Chl-a), total nitrogen (TN), and total phosphorus (TP) are important indicators to evaluate water environmental quality. Monitoring water quality and its variability can help control water pollution. However, traditional monitoring techniques of water quality are time-consuming and laborious, and can mostly conduct with sample point-to-point at the edge of lakes and rivers. In this study, an empirical (regression-based) model is proposed to retrieve Chl-a, TN, and TP concentrations in the Yangtze River by Landsat-8 images from 2014 to 2020. The spatial-temporal distribution and variability of water quality in the whole Yangtze River are analyzed in detail. Furthermore, the driving forces of water quality variations are explored. The results show that the mean absolute percentage error (MAPE) of the water quality parameters are 25.88%, 4.3%, and 8.37% for Chl-a, TN, and TP concentrations, respectively, and the root mean square errors (RMSE) are 0.475 μg/L, 0.110 mg/L, and 0.01 mg/L, respectively. The concentrations of Chl-a, TN, and TP in the upstream of the Yangtze River are lower than those in the midstream and downstream. These water quality parameters have a seasonal cycle with a maximum in summer and minimum in winter. The hydrological and meteorological factors such as water level, flow, temperature, and precipitation are positively correlated with Chl-a, TN, and TP concentrations. The larger the impervious surface and cropland area, the greater the cargo handling capacity (CHC), higher ratio of TP to TN will further pollute the water. The methods and results provide essential information to evaluate and control water pollution in the Yangtze River.
Keywords: chlorophyll-a; total nitrogen; total phosphorus; Yangtze River; Landsat-8 chlorophyll-a; total nitrogen; total phosphorus; Yangtze River; Landsat-8

Share and Cite

MDPI and ACS Style

He, Y.; Jin, S.; Shang, W. Water Quality Variability and Related Factors along the Yangtze River Using Landsat-8. Remote Sens. 2021, 13, 2241. https://doi.org/10.3390/rs13122241

AMA Style

He Y, Jin S, Shang W. Water Quality Variability and Related Factors along the Yangtze River Using Landsat-8. Remote Sensing. 2021; 13(12):2241. https://doi.org/10.3390/rs13122241

Chicago/Turabian Style

He, Yang, Shuanggen Jin, and Wei Shang. 2021. "Water Quality Variability and Related Factors along the Yangtze River Using Landsat-8" Remote Sensing 13, no. 12: 2241. https://doi.org/10.3390/rs13122241

APA Style

He, Y., Jin, S., & Shang, W. (2021). Water Quality Variability and Related Factors along the Yangtze River Using Landsat-8. Remote Sensing, 13(12), 2241. https://doi.org/10.3390/rs13122241

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