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A study on the characteristics of cyanobacteria in the mainstream of Nakdong river using decision trees

의사결정나무를 이용한 낙동강 본류 구간의 남조류 발생특성 연구

  • Jung, Woo Suk (Dept. of Environmental Engineering, Inje University) ;
  • Jo, Bu Geon (Dept. of Environmental Engineering, Inje University) ;
  • Kim, Young Do (Dept. of Environmental Engineering, Inje University) ;
  • Kim, Sung Eun (Dept. of Civil and Environmental Engineering, University of Hawaii)
  • 정우석 (인제대학교 환경공학과) ;
  • 조부건 (인제대학교 환경공학과) ;
  • 김영도 (인제대학교 환경공학과) ;
  • 김성은 (하와이주립대 도시환경공학과)
  • Received : 2019.10.04
  • Accepted : 2019.10.23
  • Published : 2019.11.30

Abstract

The occurrence of cyanobacteria causes problems such as oxygen depletion and increase of organic matter in the water body due to mass prosperity and death. Each year, Algae bloom warning System is issued due to the effects of summer heat and drought. It is necessary to quantitatively characterize the occurrence of cyanobacteria for proactive green algae management in the main Nakdong river. In this study, we analyzed the major influencing factors on cyanobacteria bloom using visualization and correlation analysis. A decision tree, a machine learning method, was used to quantitatively analyze the conditions of cyanobacteria according to the influence factors. In all the weirs, meteorological factors, temperature and SPI drought index, were significantly correlated with cyanobacterial cell number. Increasing the number of days of heat wave and drought block the mixing of water in the water body and the stratification phenomenon to promote the development of cyanobacteria. In the long term, it is necessary to proactively manage cyanobacteria considering the meteorological impacts.

Acknowledgement

Supported by : 한국연구재단

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