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주성분분석(PCA) 방법을 이용한 금강 수질의 주요 오염원 영향 평가

Evaluation of significant pollutant sources affecting water quality of the Geum River using principal component analysis

  • Legesse, Natnael Shiferaw (Department of Environmental & IT Engineering, Chungnam National University) ;
  • Kim, Jaeyoung (Department of Environmental & IT Engineering, Chungnam National University) ;
  • Seo, Dongil (Department of Environmental & IT Engineering, Chungnam National University)
  • 투고 : 2022.05.16
  • 심사 : 2022.06.15
  • 발행 : 2022.08.31

초록

본 연구는 금강의 조류 성장에 대한 제한영양소와 수질에 영향을 미치는 주요 지류를 파악하고 수질개선을 위한 관리대안을 제시하는 것을 목적으로 수행되었다. 금강 대청댐 하류에 위치한 5개 수질측정소에서 약 8년간(2013~202) 환경부의 물환경정보시스템(water.nier.go.kr)과 수자원관리정보시스템(wamis.go.kr)에서 14개의 수질항목의 자료를 분석하였다. 금강의 4대강 수중보 수문 개방 시 TP(총인)와 수온은 하천 하류의 조류 성장에 큰 영향을 미친다. 본 연구에는 수질변수간의 상관관계를 규명하고 금강의 조류 성장에 영향을 미치는 중요인자를 파악하고자 하였다. 최하류에 위치한 백제보수질측정소(WQ5)에서 TP와 수온은 Chl-a와 특별히 높은 상관관계를 보여 조류 번식에 상당한 영향을 미친다는 것을 나타냈다. 또한 본 연구에서는 금강의 양대 지류인 갑천과 미호천의 주요 오염원을 식별하고 우선순위를 지정하기 위해 주성분분석(Principal Component Analysis, PCA) 방법을 이 적용하였다. PCA방법을 이용하여 갑천과 미호천의 수질에 영얗ㅇ을 미치는 3대 오염원을 각각 파악하였다. 갑천의 경우 폐수처리장과 도시·농업 오염이 주요 오염원으로, 미호천의 경우 농지, 도시, 산림이 주요 오염원으로 각각 확인되었다. PCA는 금강 및 그 지류의 수질오염원을 구체적으로 파악하는 데 효과적인 것으로 판단되어 수질관리 전략의 효율을 제고하는 데에, 활용될 수 있을 것으로 보인다.

This study aims to identify the limiting nutrient for algal growth in the Geum River and the significant pollutant sources from the tributaries affecting the water quality and to provide a management alternative for an improvement of water quality. An eight-year of daily data (2013~2020) were collected from the Water Environment Information System (water.nier.go.kr) and Water Resources Management Information System (wamis.go.kr). 14 water quality variables were analyzed at five water quality monitoring stations in the Geum River (WQ1-WQ5). In the Geum River, the water quality variables, especially Chl-a vary greatly in downstream of the river. In the open weir gate operation, TP (total phosphorus) and water temperature greatly influence the growth of algae in downstream of the river. A correlation analysis was used to identify the relationship between variables and investigate the factor affecting algal growth in the Geum River. At the downstream station (WQ5), TP and Temp have shown a strong correlation with Chl-a, indicating they significantly influence the algal bloom. The principal component analysis (PCA) was applied to identify and prioritize the major pollutant sources of the two major tributaries of the river, Gab-cheon and Miho-cheon. PCA identifies three major pollutant sources for Gab-cheon and Miho-cheon, respectively. For Gab-cheon, wastewater treatment plant, urban, and agricultural pollutions pollution are identified as significant pollutant sources. For Miho-cheon, agricultural, urban, and forest land are identified as major pollutant sources. PCA seems to be effective in identifying water pollutant sources for the Geum River and its tributaries in detail and thus can be used to develop water quality management strategies.

키워드

과제정보

This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korean government(MSIT) (No.2018-0-00219, Spacetime complex artificial intelligence blue-green algae prediction technology based on direct-readable water quality complex sensor and hyperspectral image).

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