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J Korean Soc Environ Eng > Volume 43(3); 2021 > Article
J Korean Soc Environ Eng 2021;43(3): 171-186. doi: https://doi.org/10.4491/KSEE.2021.43.3.171
다변량 통계분석기법을 활용한 금강수계 14개 호소의 수질평가
김진호1 , 주진철2 , 안채민3 , 황대호4
1토지주택연구원
2한밭대학교 건설환경공학과
3한밭대학교 환경공학과
4한국물관리정책연구소
Water Quality Assessment of 14 Reservoirs in Geum River Basin Using Multivariate Statistical Analysis
Jin Ho Kim1 , Jin Chul Joo2 , Chae Min Ahn3 , Dae Ho Hwang4
1Land & Housing Institute
2Department of Civil and Environmental Engineering, Hanbat National University
3Department of Environmental Engineering, Hanbat National University
4Korea Water Policy Research Institute
Corresponding author  Jin Chul Joo ,Tel: 042-821-1264, Fax: 042-821-1476, Email: jincjoo@hanbat.ac.kr
Received: January 18, 2021;  Revised: February 25, 2021;  Accepted: March 3, 2021.  Published online: March 31, 2021.
ABSTRACT
Objectives
14 reservoirs in the Geum river watershed were clustered and classified using the results of factor analysis based on water quality characteristics. Also, correlation analysis between pollutants (land system, living system, livestock system) and water quality characteristics was performed to elucidate the effect of pollutants on water quality.
Methods
Cluster analysis (CA), principal component analysis (PCA), and factor analysis (FA) using water quality data of 14 reservoirs in the Geum river watershed during the last 5 years (2014-2018) were performed to derive the principal components. Then, correlation analysis between principal components and pollutants was performed to verify the feasibility of clustering.
Results and Discussion
From the factor analysis (FA) using water quality data of 14 reservoirs in the Geum river watershed, three to six principal components (PCs) were extracted and extracted PCs explained approximately 74% of overall variations in water quality. As a result of clustering reservoirs based on the extracted PCs, the reservoirs clustered by nitrogen and seasonal PCs were Ganwol, Geumgang, and Sapgyo, the reservoirs clustered by organic pollution and internal production PCs were Tapjung, Dae, Seokmun, and Yongdam, the reservoirs clustered by organic pollution, internal production, and phosphorus are Bunam, Yedang, and Cheongcheon, and finally the remaining Boryeong, Daecheong, Chopyeong, and Songak were clustered as other factors. From the correlation analysis between principal components and pollutants, significant correlation between the land, living, and livestock pollutants and water quality characteristics was found in Ganwol, Topjeong, Daeho, Bunam, and Daecheong. These reservoirs are considered to require continuous and careful management of specific (land, living, livestock) pollutants. In terms of water quality and pollutant management, the Ganwol, Sapgyo, and Seokmunho are considered to implement intensive measures to improve water quality and to reduce the input of various pollutants.
Conclusions
Although the water quality of the reservoir is a result of complex interactions such as influent water factors, morphological and hydrological factors, internal production factors, and various pollutants, optimized watershed and water quality management measures can be implemented through multivariate statistical analysis.
Key Words: Geum River Watershed, Multivariate Statistical Analysis, Water Quality Management, Pollutants, Principal Component Analysis (PCA)
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