Journal of Environmental Impact Assessment (환경영향평가)

Korean Society of Environmental Impact Assessment (한국환경영향평가학회)
권호 표지
DOI QR코드

DOI QR Code

Spatial and Seasonal Water Quality Variations of Han River Tributries

한강 주요지천의 지역적 및 계절적 수질변화

  • Lee, Young Joon (Han-River Environment Research Center, National Institute of Environmental Research) ;
  • Park, Minji (Han-River Environment Research Center, National Institute of Environmental Research) ;
  • Son, Juyeon (Han-River Environment Research Center, National Institute of Environmental Research) ;
  • Park, Jinrak (Han-River Environment Research Center, National Institute of Environmental Research) ;
  • Kim, Geeda (Han-River Environment Research Center, National Institute of Environmental Research) ;
  • Hong, Changsu (Han-River Environment Research Center, National Institute of Environmental Research) ;
  • Gu, Donghoi (Han-River Environment Research Center, National Institute of Environmental Research) ;
  • Lee, Joonggeun (Han-River Environment Research Center, National Institute of Environmental Research) ;
  • Noh, Changwan (Han-River Environment Research Center, National Institute of Environmental Research) ;
  • Shin, Kyung-Yong (Han-River Environment Research Center, National Institute of Environmental Research) ;
  • Yu, Soon-Ju (Han-River Environment Research Center, National Institute of Environmental Research)
  • 이영준 (국립환경과학원 한강물환경연구소) ;
  • 박민지 (국립환경과학원 한강물환경연구소) ;
  • 손주연 (국립환경과학원 한강물환경연구소) ;
  • 박진락 (국립환경과학원 한강물환경연구소) ;
  • 김귀다 (국립환경과학원 한강물환경연구소) ;
  • 홍창수 (국립환경과학원 한강물환경연구소) ;
  • 구동회 (국립환경과학원 한강물환경연구소) ;
  • 이중근 (국립환경과학원 한강물환경연구소) ;
  • 노창완 (국립환경과학원 한강물환경연구소) ;
  • 신경용 (국립환경과학원 한강물환경연구소) ;
  • 유순주 (국립환경과학원 한강물환경연구소)
  • Received : 2017.10.22
  • Accepted : 2017.11.28
  • Published : 2017.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

The quality of surface water is a very important issue to use various demands like as drinking water, industrial, agricultural and recreational usages. There has been an increasing demand for monitoring water quality of many rivers by regular measurements of various water quality variables. However precise and effective monitoring is not enough, if the acquired dataset is not analyzed thoroughly. Therefore, the aim of this study was to estimate differences of seasonal and regional water quality using multivariate data analysis for each investing tributaries in Han River. Statistical analysis was applied to the data concerning 11 mainly parameters (flow, water temperature, pH, EC, DO, BOD, COD, SS, TN, TP and TOC) for the time period 2012~2016 from 12 sampling sites. The seasonal water quality variations showed that each of BOD, TN, TP and TOC average concentration in spring and winter was higher than that of summer and fall, respectively. In summer each flow rate and average concentration of SS was higher than any other seasons, respectively. The correlation analysis were explained that EC had a strong relationship with BOD (r=0.857), COD (r=0.854), TN (r=0.899) and TOC (r=0.910). According to principal component analysis, five principal components (Eigenvalue > 1) are controlled 98.0% of variations in water quality. The first component included TP, DO, pH. The second component included EC, TN. The third component included SS. The fourth component included flow. The last component included Temp. Cluster analysis classified that spring is similar to fall and winter with water quality parameters. AnyA, WangsA, JungrA and TancA were identified as affected by organic pollution. Cluster analysis derived seasonal differences with investigating sites and better explained the principal component analysis results.

지표수의 수질은 음용수, 공업용수, 농업용수 등과 같이 다양한 용도로 이용하기 위해서 아주 중요하다. 다양한 수질변수들에 대한 정기적인 수질조사가 실시되고 있으며 정확하고 효과적인 분석 및 해석이 수반되어야 한다. 본 연구의 목적은 다변량 분석방법을 이용하여 지역적 및 계절적 수질변화를 평가하는데 있다. 2012년부터 2016까지 5년간 12개 조사지점에 대하여 유량(flow)과 수질항목(water temperature, pH, EC, DO, BOD, COD, SS, TN, TP 및 TOC)을 조사 분석하였다. 계절적 수질변화에서는 봄과 겨울의 BOD, TN, TP 및 TOC 평균농도가 여름 및 가을에 비하여 높게 조사되었다. 유량 및 SS의 평균농도가 다른 계절에 비하여 여름이 높았다. 상관분석에서 EC는 BOD(r=0.857), COD(r=0.854), TN(r=0.899) 및 TOC(r=0.910) 와 높은 상관성을 나타냈다. 주성분분석에서 요인 1은 TP, DO 및 pH을 포함하며 32.0%, 요인 2는 EC 및 TN을 포함하며 26.0%, 요인 3은 SS을 포함하며 18.0%의 기여율을 보였고, 요인 4는 유량을 포함하며 12.0%, 요인 5는 수온을 포함하며 10.0%를 보였다. 5개의 요인은 전체 수질변동 특성의 98.0%를 설명할 수 있었다. 안양천, 왕숙천, 중량천 및 탄천은 유기오염물질의 영향을 받는 것으로 조사되었다. 군집분석에서 조사지점에 대한 계절적 차이를 도출하였으며, 또한 군집분석 결과는 주성분분석 결과 해석을 더 잘 설명하게 되었다.

Keywords

References

  1. Barakat A, Baghdadi ME, Rais J, Aghezzaf B, Slassi M. 2016. Assessment of spatial and seasonal water quality variation of Oum Er Rbia River (Morocco) using multivariate statistical techniques. International Soil and Water Conservation Research. 4: 284-292. https://doi.org/10.1016/j.iswcr.2016.11.002
  2. Carpenter S, Caraco NF, Correll DL, Howarth RW, Sharpley AN, Smith VH. 1998. Nonpoint pollution of surface waters with phosphorus and nitrogen. Ecological Applications. 8(3): 59-568.
  3. Dixon W, Chiswell B. 1996. Review of aquatic monitoring program design, Water Research. 30: 1935-1948. https://doi.org/10.1016/0043-1354(96)00087-5
  4. Forina M, Armanino C, Raggio V. 2002. Clustering with dendrograms on interpretation variables. Analytica Chimica Acta. 454: 13-19. https://doi.org/10.1016/S0003-2670(01)01517-3
  5. Jarvie HP, Whitton BA, Neal C. 1998. Nitrogen and phosphorus in east coast British rivers: Speciation, sources and biological significance. Science of the Total Environment. 210-211:79-109. https://doi.org/10.1016/S0048-9697(98)00109-0
  6. Jung S, Lee D, Hwang K, Lee K, Choi K, Im S, Lee Y, Lee J, Lim B. 2012. Evaluation of Pollutant Characteristics in Yeongsan River Using Multivariate Analysis. Korean Journal of Limnology. 45(4): 368-377. [Korean Literature] https://doi.org/10.11614/KSL.2012.45.4.368
  7. Kaiser HF. 1960. The application of electronic computers to factor analysis. Educational and Psychological Measurement. 20: 141-151. https://doi.org/10.1177/001316446002000116
  8. Kim G, Kim Y, Song M, Ji K, Yu P, Kim C. 2007a. Evaluation of Water Quality Characteristics in the Nakdong River suing Multivariate Analysis, Journal of Society on Water Quality. 23(6): 814-821. [Korean Literature]
  9. Kim MA, Lee JK, Zoh KD. 2007b. Evaluation of the Geum River by Multivariate Analysis: Principal Component Analysis and Factor Analysis, Journal of Korean Society on Water Quality. 23(1): 161-168. [Korean Literature]
  10. Kim Y, Lee S. 2011. Evaluation of Water Quality for the Han River Tributaries Using Multivate Analysis, Korean Society of Environmental Engineers, 33(7): 501-510. [Korean Literature] https://doi.org/10.4491/KSEE.2011.33.7.501
  11. Kumar M, Ramanathan A, Rao MS, Kumar B. 2006. Identification and evaluation of hydrogeochemical processes in the groundwater environment of Delhi, India. Environmental Geology. 50: 1025-1039. https://doi.org/10.1007/s00254-006-0275-4
  12. Liun CW, Linn KH, Kuon YM. 2003. Application of factor analysis in the assessment of groundwater quality in a black foot disease area in Taiwan. Science of The Total Environment. 313(1-3): 77-89. https://doi.org/10.1016/S0048-9697(02)00683-6
  13. Magyar N, Hatvani II, Szekely IK, Herzigc A, Dinka M, Kovacs J. 2013. Application of multivariate statistical methods in determining spatial changes in water quality in the Austrian part of Neusiedler See. Ecological Engineering. 55: 82-92. https://doi.org/10.1016/j.ecoleng.2013.02.005
  14. Ministry of Environment. 2011. Standard Method for Examination of Water.
  15. Oh YC, Lee ND, Kim JG. 2004. The Evalutation of Water Quality in the Mankyung River using Multivariate Analysis, Journal of the Environmental Sciences. 13(3): 233-244. [Korean Literature] https://doi.org/10.5322/JES.2004.13.3.233
  16. Park J, Moon M, Lee H, Kim K. 2014. A Study on Characteristics of Water Quality using Multivariate Analysis in Sumjin River Basin, Journal of Korean Society on Water Environment. 30(2): 119-127. [Korean Literature]
  17. Sargaonkar A, Deshpande V. 2003. Development of an overall index of pollution for surface water based on a general classification scheme in Indian context. Environ. Monit. Assess. 89 (1): 43-67. https://doi.org/10.1023/A:1025886025137
  18. Simeonov V, Stratis JA, Samara C, Zachariadis G, Voutsa D, Anthemidis A, Sofoniou M, Kouimtzis T. 2003. Assessment of the surface water quality in Northern Greece, Water Research. 37: 4119-4124. https://doi.org/10.1016/S0043-1354(03)00398-1
  19. Singh KP, Malik A, Sinha S. 2005. Water quality assessment and apportionment of pollution sources of Gomti river (India) using multivariate statistical techniques - A case study. Analytica Chimica Acta. 538(1-2): 355-374. https://doi.org/10.1016/j.aca.2005.02.006
  20. Zhou F, Liu Y, Guo H. 2007. Application of multivariate statistical methods to water quality assessment of the watercourses in Northwestern New Territories, Hong Kong. Environ. Monit. Assess. 132 (1-3): 1-13. https://doi.org/10.1007/s10661-006-9497-x