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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| Format: | Article |
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MDPI AG
2021-10-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/13/21/2976 |
| _version_ | 1797511726706458624 |
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| 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 |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T05:49:14Z |
| format | Article |
| id | doaj.art-96ed3cb208364d22be57cc9eded2e3e3 |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-10T05:49:14Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-96ed3cb208364d22be57cc9eded2e3e32023-11-22T21:53:29ZengMDPI AGWater2073-44412021-10-011321297610.3390/w13212976Water Quality Assessment and Potential Source Contribution Using Multivariate Statistical Techniques in Jinwi River Watershed, South KoreaHyeonmi Choi0Yong-Chul Cho1Sang-Hun Kim2Soon-Ju Yu3Young-Seuk Kim4Jong-Kwon Im5Han River Environment Research Center, National Institute of Environmental Research, 42, Dumulmeori-gil 68beon-gil, Yangseo-myeon 12585, KoreaHan River Environment Research Center, National Institute of Environmental Research, 42, Dumulmeori-gil 68beon-gil, Yangseo-myeon 12585, KoreaHan River Environment Research Center, National Institute of Environmental Research, 42, Dumulmeori-gil 68beon-gil, Yangseo-myeon 12585, KoreaHan River Environment Research Center, National Institute of Environmental Research, 42, Dumulmeori-gil 68beon-gil, Yangseo-myeon 12585, KoreaHan River Environment Research Center, National Institute of Environmental Research, 42, Dumulmeori-gil 68beon-gil, Yangseo-myeon 12585, KoreaHan River Environment Research Center, National Institute of Environmental Research, 42, Dumulmeori-gil 68beon-gil, Yangseo-myeon 12585, KoreaTo 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.https://www.mdpi.com/2073-4441/13/21/2976dry and wet seasonsspatiotemporal variationscluster analysisreal-time water quality index (RTWQI)absolute principal component score-multiple linear regression (APCS-MLR) |
| spellingShingle | 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 Water dry and wet seasons spatiotemporal variations cluster analysis real-time water quality index (RTWQI) absolute principal component score-multiple linear regression (APCS-MLR) |
| title | 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_short | 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 |
| topic | dry and wet seasons spatiotemporal variations cluster analysis real-time water quality index (RTWQI) absolute principal component score-multiple linear regression (APCS-MLR) |
| url | https://www.mdpi.com/2073-4441/13/21/2976 |
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