Journal of Korean Society on Water Environment (한국물환경학회지)

Korean Society on Water Environment (한국물환경학회)
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Application of SOM for the Detection of Spatial Distribution considering the Analysis of Basic Statistics for Water Quality and Runoff Data

수질 및 유량자료의 기초통계량 분석에 따른 공간분포 파악을 위한 SOM의 적용

  • Jin, Young-Hoon (Institute of Industrial Research and Technology, Dongshin University) ;
  • Kim, Yong-Gu (Department of Civil Engineering, Dongshin University) ;
  • Roh, Kyong-Bum (Department of Civil Engineering, Dongshin University) ;
  • Park, Sung-Chun (Department of Civil Engineering, Dongshin University)
  • 진영훈 (동신대학교 공업기술연구소) ;
  • 김용구 (동신대학교 토목공학과) ;
  • 노경범 (동신대학교 토목공학과) ;
  • 박성천 (동신대학교 토목공학과)
  • Received : 2009.06.09
  • Accepted : 2009.08.12
  • Published : 2009.09.30
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Abstract

In order to support the basic information for planning and performing the environment management such as Total Maximum Daily Loads (TMDLs), it is highly recommended to understand the spatial distribution of water quality and runoff data in the unit watersheds. Therefore, in the present study, we applied Self-Organizing Map (SOM) to detect the characteristics of spatial distribution of Biological Oxygen Demand (BOD) concentration and runoff data which have been measured in the Yeongsan, Seomjin, and Tamjin River basins. For the purpose, the input dataset for SOM was constructed with the mean, standard deviation, skewness, and kurtosis values of the respective data measured from the stations of 22-subbasins in the rivers. The results showed that the $4{\times}4$ array structure of SOM was selected by the trial and error method and the best performance was revealed when it classified the stations into three clusters according to the basic statistics. The cluster-1 and 2 were classified primarily by the skewness and kurtosis of runoff data and the cluster-3 including the basic statistics of YB_B, YB_C, and YB_D stations was clearly decomposed by the mean value of BOD concentration showing the worst condition of water quality among the three clusters. Consequently, the methodology based on the SOM proposed in the present study can be considered that it is highly applicable to detect the spatial distribution of BOD concentration and runoff data and it can be used effectively for the further utilization using different water quality items as a data analysis tool.

Keywords

Acknowledgement

Supported by : 한국학술진흥재단

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