Water quality evaluation and apportionment of pollution sources: a case study of the Baralia and Puthimari River (India)

Water quality monitoring programs are indispensable for developing water conservation strategies, but elucidation of large and random datasets generated in these monitoring programs has become a global challenge. Rapid urbanization, industrialization and population growth pose a threat of pollution...

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Autores principales:	Kunwar Raghvendra Singh, Ankit Pratim Goswami, Ajay S. Kalamdhad, Bimlesh Kumar
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	cluster analysis information entropy principal component analysis water quality Environmental technology. Sanitary engineering TD1-1066
Acceso en línea:	https://doaj.org/article/96494079212349efa3cb6844af1aed2d
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spelling	oai:doaj.org-article:96494079212349efa3cb6844af1aed2d2021-11-05T21:09:25ZWater quality evaluation and apportionment of pollution sources: a case study of the Baralia and Puthimari River (India)1751-231X10.2166/wpt.2021.020https://doaj.org/article/96494079212349efa3cb6844af1aed2d2021-04-01T00:00:00Zhttp://wpt.iwaponline.com/content/16/2/692https://doaj.org/toc/1751-231XWater quality monitoring programs are indispensable for developing water conservation strategies, but elucidation of large and random datasets generated in these monitoring programs has become a global challenge. Rapid urbanization, industrialization and population growth pose a threat of pollution for the surface water bodies of the Assam, a state in northeastern India. This calls for strict water quality monitoring programs, which would thereby help in understanding the status of water bodies. In this study, the water quality of Baralia and Puthimari River of Assam was assessed using cluster analysis (CA), information entropy, and principal component analysis (PCA) to derive useful information from observed data. 15 sampling sites were selected for collection of samples during the period May 2016- June 2017. Collected samples were analysed for 20 physicochemical parameters. Hierarchal CA was used to classify the sampling sites in different clusters. CA grouped all the sites into 3 clusters based on observed variables. Water quality of rivers was evaluated using entropy weighted water quality index (EWQI). EWQI of rivers varied from 61.62 to 314.68. PCA was applied to recognise various pollution sources. PCA identified six principal components that elucidated 87.9% of the total variance and represented surface runoff, untreated domestic wastewater and illegally dumped municipal solid waste (MSW) as major factors affecting the water quality. This study will help policymakers and managers in making better decisions in allocating funds and determining priorities. It will also assist in effective and efficient policies for the improvement of water quality. Highlights Evaluation of water quality using entropy weighted WQI.; Entropy provides valuable descriptions of random processes.; Classification of sampling sites by using Hierarchal cluster analysis based on observed parameters.; Application of principal component analysis to recognize the latent pollution sources.; Study will assist policy makers to make better decisions for surface water quality management.;Kunwar Raghvendra SinghAnkit Pratim GoswamiAjay S. KalamdhadBimlesh KumarIWA Publishingarticlecluster analysisinformation entropyprincipal component analysiswater qualityEnvironmental technology. Sanitary engineeringTD1-1066ENWater Practice and Technology, Vol 16, Iss 2, Pp 692-706 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	cluster analysis information entropy principal component analysis water quality Environmental technology. Sanitary engineering TD1-1066
spellingShingle	cluster analysis information entropy principal component analysis water quality Environmental technology. Sanitary engineering TD1-1066 Kunwar Raghvendra Singh Ankit Pratim Goswami Ajay S. Kalamdhad Bimlesh Kumar Water quality evaluation and apportionment of pollution sources: a case study of the Baralia and Puthimari River (India)
description	Water quality monitoring programs are indispensable for developing water conservation strategies, but elucidation of large and random datasets generated in these monitoring programs has become a global challenge. Rapid urbanization, industrialization and population growth pose a threat of pollution for the surface water bodies of the Assam, a state in northeastern India. This calls for strict water quality monitoring programs, which would thereby help in understanding the status of water bodies. In this study, the water quality of Baralia and Puthimari River of Assam was assessed using cluster analysis (CA), information entropy, and principal component analysis (PCA) to derive useful information from observed data. 15 sampling sites were selected for collection of samples during the period May 2016- June 2017. Collected samples were analysed for 20 physicochemical parameters. Hierarchal CA was used to classify the sampling sites in different clusters. CA grouped all the sites into 3 clusters based on observed variables. Water quality of rivers was evaluated using entropy weighted water quality index (EWQI). EWQI of rivers varied from 61.62 to 314.68. PCA was applied to recognise various pollution sources. PCA identified six principal components that elucidated 87.9% of the total variance and represented surface runoff, untreated domestic wastewater and illegally dumped municipal solid waste (MSW) as major factors affecting the water quality. This study will help policymakers and managers in making better decisions in allocating funds and determining priorities. It will also assist in effective and efficient policies for the improvement of water quality. Highlights Evaluation of water quality using entropy weighted WQI.; Entropy provides valuable descriptions of random processes.; Classification of sampling sites by using Hierarchal cluster analysis based on observed parameters.; Application of principal component analysis to recognize the latent pollution sources.; Study will assist policy makers to make better decisions for surface water quality management.;
format	article
author	Kunwar Raghvendra Singh Ankit Pratim Goswami Ajay S. Kalamdhad Bimlesh Kumar
author_facet	Kunwar Raghvendra Singh Ankit Pratim Goswami Ajay S. Kalamdhad Bimlesh Kumar
author_sort	Kunwar Raghvendra Singh
title	Water quality evaluation and apportionment of pollution sources: a case study of the Baralia and Puthimari River (India)
title_short	Water quality evaluation and apportionment of pollution sources: a case study of the Baralia and Puthimari River (India)
title_full	Water quality evaluation and apportionment of pollution sources: a case study of the Baralia and Puthimari River (India)
title_fullStr	Water quality evaluation and apportionment of pollution sources: a case study of the Baralia and Puthimari River (India)
title_full_unstemmed	Water quality evaluation and apportionment of pollution sources: a case study of the Baralia and Puthimari River (India)
title_sort	water quality evaluation and apportionment of pollution sources: a case study of the baralia and puthimari river (india)
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/96494079212349efa3cb6844af1aed2d
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Water quality evaluation and apportionment of pollution sources: a case study of the Baralia and Puthimari River (India)

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