한국해안·해양공학회논문집 (Journal of Korean Society of Coastal and Ocean Engineers)

  • 제26권4호
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  • Pages.207-216
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  • 2014
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  • 1976-8192(pISSN)
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  • 2288-2227(eISSN)
한국해안·해양공학회 (Korean Society of Coastal and Ocean Engineers)
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화학적산소요구량의 총유기탄소 변환을 위한 이상자료의 탐지와 처리

Outlier Detection and Treatment for the Conversion of Chemical Oxygen Demand to Total Organic Carbon

  • 조범준 (한국해양과학기술원 해양환경.보전연구부) ;
  • 조홍연 (한국해양과학기술원 해양환경.보전연구부) ;
  • 김성 (한국해양과학기술원 해양생태계연구부)
  • Cho, Beom Jun (Marine Environments & Conservation Research Division, Korea Institute of Ocean Science & Technology) ;
  • Cho, Hong Yeon (Marine Environments & Conservation Research Division, Korea Institute of Ocean Science & Technology) ;
  • Kim, Sung (Marine Ecosystem Research Division, Korea Institute of Ocean Science & Technology)
  • 투고 : 2014.06.26
  • 심사 : 2014.08.22
  • 발행 : 2014.08.30
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초록

총유기탄소(TOC)는 해양의 탄소순환 연구분야에서 직접적인 생물학적 지표로 이용되는 중요한 인자다. 가용한 TOC 자료가 상대적으로 화학적산소요구량(COD) 자료 보다 부족하기 때문에 COD 자료를 활용하여 TOC 자료를 추정할 수 있다. COD를 TOC 로의 변환 시 TOC 추정에 직접적으로 영향을 미치는 COD 관측자료에 포함된 이상자료의 탐지와 적절한 처리는 합리적이고 객관적으로 수행되어야 한다. 본 연구에서는 국내 연안해역에서 관측된 염분, COD 및 TOC 자료에 대한 최적회귀모형을 제시하였다. 최적회귀모형은 이상자료와 영향자료를 여러 가지 탐색방법으로 진단하여 제거 전 후의 자료 개수 변화, 변동계수 및 RMS 오차를 비교 및 분석하여 선택하였다. 연구수행 결과, Cook의 진단방법과 SIQR의 boxplot 방법을 조합한 방법이 가장 적절한 것으로 파악되었다. 최적 회귀 함수는 TOC(mg/L) = $0.44{\cdot}COD(mg/L)+1.53$ 이고, 결정계수는 0.47 정도로 나타났으며, RMS 오차는 0.85 mg/L이다. RMS 오차와 지레계수(leverage values)의 변동계수는 이상자료 제거 전에 비하여 각각 31%, 80%로 크게 감소되었다. 본 연구에서 제시된 방법을 통해 COD와 TOC 관측자료에 포함된 이상자료와 영향자료의 과도한 영향을 진단 및 제거하였기 때문에 보다 적절한 회귀곡선식을 제시할 수 있었다.

Total organic carbon (TOC) is an important indicator used as an direct biological index in the research field of the marine carbon cycle. It is possible to produce the sufficient TOC estimation data by using the Chemical Oxygen Demand(COD) data because the available TOC data is relatively poor than the COD data. The outlier detection and treatment (removal) should be carried out reasonably and objectively because the equation for a COD-TOC conversion is directly affected the TOC estimation. In this study, it aims to suggest the optimal regression model using the available salinity, COD, and TOC data observed in the Korean coastal zone. The optimal regression model is selected by the comparison and analysis on the changes of data numbers before and after removal, variation coefficients and root mean square (RMS) error of the diverse detection methods of the outlier and influential observations. According to research result, it is shown that a diagnostic case combining SIQR (Semi - Inter-Quartile Range) boxplot and Cook's distance method is most suitable for the outlier detection. The optimal regression function is estimated as the TOC(mg/L) = $0.44{\cdot}COD(mg/L)+1.53$, then determination coefficient is showed a value of 0.47 and RMS error is 0.85 mg/L. The RMS error and the variation coefficients of the leverage values are greatly reduced to the 31% and 80% of the value before the outlier removal condition. The method suggested in this study can provide more appropriate regression curve because the excessive impacts of the outlier frequently included in the COD and TOC monitoring data is removed.

키워드

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  1. Classification and Performance Evaluation Methods of an Algal Bloom Model vol.26, pp.6, 2014, https://doi.org/10.9765/KSCOE.2014.26.6.405