Using Principal Components Analysis and IDW Interpolation to Determine Spatial and Temporal Changes of Surface Water Quality of Xin’anjiang River in Huangshan, China

Wenjie Yang, Yue Zhao, Dong Wang, Huihui Wu, Aijun Lin and Li He
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Wenjie Yang: College of Renewable Energy, North China Electric Power University, Beijing 102206, China
Yue Zhao: Chinese Academy for Environmental Planning, Beijing 100012, China
Dong Wang: Chinese Academy for Environmental Planning, Beijing 100012, China
Huihui Wu: Beijing City Environment Pollution Control and Resource Reuse Engineering Research Center, Beijing University of Chemical Technology, Beijing 100029, China
Aijun Lin: Beijing City Environment Pollution Control and Resource Reuse Engineering Research Center, Beijing University of Chemical Technology, Beijing 100029, China
Li He: College of Renewable Energy, North China Electric Power University, Beijing 102206, China

IJERPH, 2020, vol. 17, issue 8, 1-14

Abstract: This study was aimed at assessing the spatial and temporal distribution of surface water quality variables of the Xin’anjiang River (Huangshan). For this purpose, 960 water samples were collected monthly along the Xin’anjiang River from 2008 to 2017. Twenty-four water quality indicators, according to the environmental quality standards for surface water (GB 3838-2002), were detected to evaluate the water quality of the Xin’anjiang River over the past 10 years. Principal component analysis (PCA) was used to comprehensively evaluate the water quality across eight monitoring stations and analyze the sources of water pollution. The results showed that all samples could be analyzed by three main components, which accounted for 87.24% of the total variance. PCA technology identified important water quality parameters and revealed that nutrient pollution and organic pollution are major latent factors which influence the water quality of Xin’anjiang River. It also showed that agricultural activities, erosion, domestic, and industrial discharges are fundamental causes of water pollution in the study area. It is of great significance for water quality safety management and pollution control of the Xin’anjiang River. Meanwhile, the inverse distance weighted (IDW) method was used to interpolate the PCA comprehensive score. Based on this, the temporal and spatial structure and changing characteristics of water quality in the Xin’anjiang River were analyzed. We found that the overall water quality of Xin’anjiang River (Huangshan) was stable from 2008 to 2017, but the pollution of the Pukou sampling point was of great concern. The results of IDW helped us to identify key areas requiring control in the Xin’anjiang River, which pointed the way for further delicacy management of the river. This study proved that the combination of PCA and IDW interpolation is an effective tool for determining surface water quality. It was of great significance for the control of water pollution in Xin’anjiang River and the reduction of eutrophication pressure in Thousand Island Lake.

Keywords: Xin’anjiang River; principal component analysis (PCA); surface water quality; inverse distance weighted (IDW) (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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