Water Quality Assessment and Potential Source Contribution Using Multivariate Statistical Techniques in Jinwi River Watershed, South Korea

To investigate the effects of rapid urbanization on water pollution, the water quality, daily unit area pollutant load, water quality score, and real-time water quality index for the Jinwi River watershed were assessed. The contribution of known pollution sources was identified using multivariate st...

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Autores principales:	Hyeonmi Choi, Yong-Chul Cho, Sang-Hun Kim, Soon-Ju Yu, Young-Seuk Kim, Jong-Kwon Im
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	dry and wet seasons spatiotemporal variations cluster analysis real-time water quality index (RTWQI) absolute principal component score-multiple linear regression (APCS-MLR) Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500
Acceso en línea:	https://doaj.org/article/96ed3cb208364d22be57cc9eded2e3e3
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id	oai:doaj.org-article:96ed3cb208364d22be57cc9eded2e3e3
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spelling	oai:doaj.org-article:96ed3cb208364d22be57cc9eded2e3e32021-11-11T19:53:18ZWater Quality Assessment and Potential Source Contribution Using Multivariate Statistical Techniques in Jinwi River Watershed, South Korea10.3390/w132129762073-4441https://doaj.org/article/96ed3cb208364d22be57cc9eded2e3e32021-10-01T00:00:00Zhttps://www.mdpi.com/2073-4441/13/21/2976https://doaj.org/toc/2073-4441To investigate the effects of rapid urbanization on water pollution, the water quality, daily unit area pollutant load, water quality score, and real-time water quality index for the Jinwi River watershed were assessed. The contribution of known pollution sources was identified using multivariate statistical analysis and absolute principal component score-multiple linear regression. The water quality data were collected during the dry and wet seasons to compare the pollution characteristics with varying precipitation levels and flow rates. The highest level of urbanization is present in the upstream areas of the Hwangguji and Osan Streams. Most of the water quality parameter values were the highest in the downstream areas after the polluted rivers merged. The results showed a dilution effect with a lower pollution level in the wet season. Conversely, the daily unit area pollutant load was higher in the rainy season, indicating that the pollutants increased as the flow rate increased. A cluster analysis identified that the downstream water quality parameters are quite different from the upstream values. Upstream is an urban area with relatively high organic matter and nutrient loads. The upstream sewage treatment facilities were the main pollution sources. This study provides basic data for policymakers in urban water quality management.Hyeonmi ChoiYong-Chul ChoSang-Hun KimSoon-Ju YuYoung-Seuk KimJong-Kwon ImMDPI AGarticledry and wet seasonsspatiotemporal variationscluster analysisreal-time water quality index (RTWQI)absolute principal component score-multiple linear regression (APCS-MLR)Hydraulic engineeringTC1-978Water supply for domestic and industrial purposesTD201-500ENWater, Vol 13, Iss 2976, p 2976 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	dry and wet seasons spatiotemporal variations cluster analysis real-time water quality index (RTWQI) absolute principal component score-multiple linear regression (APCS-MLR) Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500
spellingShingle	dry and wet seasons spatiotemporal variations cluster analysis real-time water quality index (RTWQI) absolute principal component score-multiple linear regression (APCS-MLR) Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500 Hyeonmi Choi Yong-Chul Cho Sang-Hun Kim Soon-Ju Yu Young-Seuk Kim Jong-Kwon Im Water Quality Assessment and Potential Source Contribution Using Multivariate Statistical Techniques in Jinwi River Watershed, South Korea
description	To investigate the effects of rapid urbanization on water pollution, the water quality, daily unit area pollutant load, water quality score, and real-time water quality index for the Jinwi River watershed were assessed. The contribution of known pollution sources was identified using multivariate statistical analysis and absolute principal component score-multiple linear regression. The water quality data were collected during the dry and wet seasons to compare the pollution characteristics with varying precipitation levels and flow rates. The highest level of urbanization is present in the upstream areas of the Hwangguji and Osan Streams. Most of the water quality parameter values were the highest in the downstream areas after the polluted rivers merged. The results showed a dilution effect with a lower pollution level in the wet season. Conversely, the daily unit area pollutant load was higher in the rainy season, indicating that the pollutants increased as the flow rate increased. A cluster analysis identified that the downstream water quality parameters are quite different from the upstream values. Upstream is an urban area with relatively high organic matter and nutrient loads. The upstream sewage treatment facilities were the main pollution sources. This study provides basic data for policymakers in urban water quality management.
format	article
author	Hyeonmi Choi Yong-Chul Cho Sang-Hun Kim Soon-Ju Yu Young-Seuk Kim Jong-Kwon Im
author_facet	Hyeonmi Choi Yong-Chul Cho Sang-Hun Kim Soon-Ju Yu Young-Seuk Kim Jong-Kwon Im
author_sort	Hyeonmi Choi
title	Water Quality Assessment and Potential Source Contribution Using Multivariate Statistical Techniques in Jinwi River Watershed, South Korea
title_short	Water Quality Assessment and Potential Source Contribution Using Multivariate Statistical Techniques in Jinwi River Watershed, South Korea
title_full	Water Quality Assessment and Potential Source Contribution Using Multivariate Statistical Techniques in Jinwi River Watershed, South Korea
title_fullStr	Water Quality Assessment and Potential Source Contribution Using Multivariate Statistical Techniques in Jinwi River Watershed, South Korea
title_full_unstemmed	Water Quality Assessment and Potential Source Contribution Using Multivariate Statistical Techniques in Jinwi River Watershed, South Korea
title_sort	water quality assessment and potential source contribution using multivariate statistical techniques in jinwi river watershed, south korea
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/96ed3cb208364d22be57cc9eded2e3e3
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Water Quality Assessment and Potential Source Contribution Using Multivariate Statistical Techniques in Jinwi River Watershed, South Korea

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