Journal of Wetlands Research (한국습지학회지)

Korean Wetlands Society (한국습지학회)
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Application of Multivariate Statistical Techniques to Analyze the Pollution Characteristics of Major Tributaries of the Nakdong River

낙동강 주요 지류의 오염특성 분석을 위한 다변량 통계기법의 적용

  • Received : 2019.06.24
  • Accepted : 2019.07.10
  • Published : 2019.08.30
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Abstract

In this study, we analyzed the water quality characteristics of major tributaries of Nakdong River through statistical analysis such as correlation analysis, principal component and factor analysis, and cluster analysis. Organic matter and nutrients are highly correlated, and are high in spring and autumn, and seasonal water quality management is required. Principal component and factor analysis showed that 82% of total variance could be explained by 4 principal components such as organic matter, nutrients, nature, and weather. BOD, COD, TOC, and TP items were analyzed as major influencing factors. As a result of the cluster analysis, the four clusters were classified according to seasonal organic matter and nutrient pollution. Kumho River watershed showed high pollution characteristics in all seasons. Therefore, effective management of water quality in tributary streams requires measures in consideration of spatio-temporal characteristics and multivariate statistical techniques may be useful in water quality management and policy formulation.

본 연구에서는 낙동강 주요 지류를 대상으로 상관분석, 주성분 및 요인분석, 군집분석과 같은 통계분석을 통해 수질 특성을 분석하였다. 유기물질과 영양물질은 높은 상관관계를 가지고 있으며 봄철 및 가을철에 높게 나와 해당 계절에 대한 집중적인 수질 관리가 필요한 것으로 나타났다. 주성분 및 요인분석 결과 전체 분산의 82%를 유기물질, 영양물질, 자연, 기상 등 4개의 주성분으로 설명할 수 있으며 BOD, COD, TOC, TP 항목이 주요 영향요인으로 분석되었다. 군집분석 결과 계절별 유기물, 영양물질의 오염도를 고려하여 4개의 군집으로 분류하였으며 금호강 유역은 사계절 높은 오염특성을 나타내고 있었다. 따라서 지류 하천의 효과적인 수질 관리를 위해서는 시공간적 특성을 고려한 대책이 필요하며 다변량 통계기법은 수질 관리 및 정책 수립에서 유용하게 활용 가능할 것으로 분석되었다.

Keywords

References

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