Journal of Korean Society of Environmental Engineers (대한환경공학회지)

Korean Society of Environmental Engineers (대한환경공학회)
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Development of Real-Time Water Quality Abnormality Warning System for Using Multivariate Statistical Method

다변량 통계기법을 활용한 실시간 수질이상 유무 판단 시스템 개발

  • Heo, Tae-Young (Department of Information & Statistics, Chungbuk National University) ;
  • Jeon, Hang-Bae (Department of Information & Statistics, Chungbuk National University) ;
  • Park, Sang-Min (Monitoring and Analysis Division, Saemangeum Regional Environmental Office) ;
  • Lee, Young-Joo (Water Research Center, K-water Institute, K-water)
  • Received : 2014.06.03
  • Accepted : 2015.02.03
  • Published : 2015.03.31
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Abstract

The purpose of this study is to develop an warning system to detect real-time water quality abnormality using a multivariate statistical approach. In this study, we applied principal component analysis among multivariate data analyses which was used for the correlation between water quality parameters considering the real-time algorithm to determine abnormality in water quality. We applied our approach to real field data and showed the utilization of algorithm for the real-time monitoring to find water quality abnormality. In addition, our approach with Korea Meterological Adminstration database identified heavy rain data due to climate change is one of the most important factors to explain water quality abnormality.

본 연구는 다변량 통계기법 중 하나인 주성분분석을 활용하여 실시간으로 수질이상 유무를 판단할 수 있는 경보시스템 개발을 목적으로 하였다. 본 연구에서는 다변량 분석 방법 중 수질항목 간의 상관성을 고려한 주성분 분석 방법을 실시간으로 수질이상 유무를 판단하는 알고리즘에 적용시켰다. K-water에서 제공하는 실제 자료를 이용하여 수질 이상에 대한 실시간 감시 알고리즘의 활용성을 검증하였으며, 집중호우 등과 같은 기후변화에 따른 수질이상에 대해서는 기상청 자료와의 비교를 통해 검증하였다.

Keywords

References

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