Investigation of the Soan River Water Quality Using Multivariate Statistical Approach

Evaluating the quality of river water is a critical process due to pollution and variations of natural or anthropogenic origin. For the Soan River (Pakistan), seven sampling sites were selected in the urban area of Rawalpindi/Islamabad, and 18 major chemical parameters were examined over two seasons...

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Bibliographic Details
Published in:International journal of photoenergy 2020, Vol.2020 (2020), p.1-15
Main Authors: Zakaullah, Dhruba B., Ejaz, Naeem
Format: Article
Language:English
Subjects:
Agriculture
Biochemical oxygen demand
Chemical oxygen demand
Cluster analysis
Correlation analysis
Correlation coefficients
Creeks & streams
Developing countries
Discriminant analysis
Drinking water
Effluents
Evaluation
Freshwater resources
Industrial development
Industrial wastes
LDCs
Mathematical analysis
Multivariate analysis
Parameters
Population growth
Principal components analysis
Quality management
Rivers
Sampling
Solid suspensions
Turbidity
Urban areas
Urbanization
Wastewater
Water pollution
Water quality
Waterborne diseases
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Summary:Evaluating the quality of river water is a critical process due to pollution and variations of natural or anthropogenic origin. For the Soan River (Pakistan), seven sampling sites were selected in the urban area of Rawalpindi/Islamabad, and 18 major chemical parameters were examined over two seasons, i.e., premonsoon and postmonsoon 2019. Multivariate statistical approaches such as the Spearman correlation coefficient, cluster analysis (CA), and principal component analysis (PCA) were used to evaluate the water quality of the Soan River based on temporal and spatial patterns. Analytical results obtained by PCA show that 92.46% of the total variation in the premonsoon season and 93.11% in the postmonsoon season were observed by only two loading factors in both seasons. The PCA and CA made it possible to extract and recognize the origins of the factors responsible for water quality variations during the year 2019. The sampling stations were grouped into specific clusters on the basis of the spatiotemporal pattern of water quality data. The parameters dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), turbidity, and total suspended solids (TSS) are among the prominent contributing variations in water quality, indicating that the water quality of the Soan River deteriorates gradually as it passes through the urban areas, receiving domestic and industrial wastewater from the outfalls. This study indicates that the adopted methodology can be utilized effectively for effective river water quality management.
ISSN:1110-662X
1687-529X
DOI:10.1155/2020/6644796