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J Korean Soc Environ Eng > Volume 42(10); 2020 > Article
J Korean Soc Environ Eng 2020;42(10): 452-462. doi: https://doi.org/10.4491/KSEE.2020.42.10.452
수질지수와 군집분석을 활용한 서울시 주요 하천 수질평가
이진효1,2 , 하현주1 , 이만호1 , 이목영1 , 김태호2 , 차윤경2 , 구자용2
1서울특별시보건환경연구원 물환경연구부
2서울시립대학교 환경공학부
Assessment of Water Quality of Major Tributaries in Seoul using Water Quality Index and Cluster Analysis
Jinhyo Lee1,2 , Hyunju Ha1 , Manho Lee1 , Mokyoung Lee1 , Taeho Kim2 , Yoonkyung Cha2 , Jayong Koo2
1Water Environment Research Department, Seoul Metropolitan Government Research Institute of Public Health and Environment
2Department of Environmental Engineering, University of Seoul
Corresponding author  Jayong Koo ,Tel: 02-6490-2866, Fax: 02-6490-5465, Email: jykoo@uos.ac.kr
Received: August 19, 2020;  Revised: October 1, 2020;  Accepted: October 5, 2020.  Published online: October 31, 2020.
ABSTRACT
Objectives
17 water quality measurement networks (WQMNs, tributaries) in Seoul were analyzed by using NSFWQI and cluster analysis to provide basic data for future river water quality management so that citizens could easily and comprehensively understand the water quality information on the rivers in Seoul.
Methods
For the past 3 years (2015~2017), in order to estimate WQI, 9 items, DO (% sat), Fecal coliform, pH, BOD, Temperature change (TC), TP, NO3-, Turbidity and Total solids, were selected from among the 19 water quality data measurement items produced monthly from 17 WQMNs in Seoul. WQI was derived and graded using NSFWQI and cluster analysis was performed using Ward Linkage Method, SOM (Self Organizing Map).
Results and Discussion
Water quality of most water quality monitoring networks was BOD Ⅱ grade (slightly good) or higher and TP Ⅲ grade (normal) or higher according to the standard of water quality and water ecosystem river living environment, and NSFWQI was also 64 (Medium)~89 (Good). All showed good water quality. NSFWQI does not show a significant difference by season, so it is believed that it is affected by anthropogenic sources rather than seasonal effects. As a result of examining the correlation between NSFWQI and water quality level according to environmental standards, it was confirmed that R2 has a relatively good correlation with 0.78, and there is no clear difference between the two groups, and through this, it was found that the currently implemented water quality rating system and NSFWQI are well matched. As a result of cluster analysis using ward linkage method and SOM for 17 WQMNs, it was largely divided into 6 groups according to water quality characteristics.
Conclusions
It is important to manage pollution sources to systematically manage river water quality as a water resource. It is therefore expected that by converting from the complicated and various water quality information such as is found in this study into a simple water quality index and grouping, the river water quality can be easily understood and can be utilized in the future as basic data for water quality management in Seoul.
Key Words: Water Quality Measurement Networks, WQI, Cluster Analysis, Ward Linkage, SOM
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