Understanding the Water Quality Changes of the Typical Plain River Network Area Using Comprehensive Assessment Methods

Haizhen Hu, Jia Wang (), Gang Zhou, Sichen Tong, Weifu Wang and Tingting Hu
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Haizhen Hu: College of River and Ocean Engineering, Chongqing Jiaotong University, Chongqing 400074, China
Jia Wang: Key Laboratory of River Basin Digital Twinning of Ministry of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Gang Zhou: Institute of Water Environment Research, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
Sichen Tong: College of River and Ocean Engineering, Chongqing Jiaotong University, Chongqing 400074, China
Weifu Wang: School of Environment and Resource, Southwest University of Science and Technology, Mianyang 621010, China
Tingting Hu: Institute of Water Environment Research, Chinese Research Academy of Environmental Sciences, Beijing 100012, China

Sustainability, 2024, vol. 16, issue 20, 1-18

Abstract: Water quality assessment is an important method for understanding the spatial-temporal variation characteristics of water quality. Therefore, the present study has been performed to evaluate the water quality for a typical plain river network area in Changzhou City, Jiangsu, China, where the river system is characterized by reciprocal flow and diverse pollution sources. The water quality samples from 2017 to 2021 were comprehensively assessed using comprehensive methods that combine the single-factor pollution index (SFPI) method with multivariate statistical analysis. Initially, statistical analyses were conducted to evaluate water quality exceedances and correlations and the SFPI method was applied to classify water quality categories. Furthermore, principal component analysis (PCA) and cluster analysis (CA) were employed to reduce the dimensionality of water quality indicators and group monitoring sections with similar characteristics. The results indicate that the overall water quality in Changzhou City is lightly polluted with a trend of improvement. The primary pollutants identified are total phosphorus (TP) and ammonia nitrogen (NH 3 -N). This study highlights that organic pollution, self-purification capacity, and eutrophication of river water bodies are the most significant factors affecting water quality. The sampling sites were classified into three groups (good, moderate, and poor). The water quality assessment results of this study provide a theoretical reference for water environment management and ecological protection in plain river network areas.

Keywords: plain river network; statistical analysis; water quality assessment; principal component analysis; cluster analysis (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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Citations: View citations in EconPapers (1)

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