DOI QR코드

DOI QR Code

다변량 통계 분석기법을 이용한 한강수계 지천의 수질 평가

Evaluation of Water Quality for the Han River Tributaries Using Multivariate Analysis

  • 김요용 (경기도보건환경연구원) ;
  • 이시진 (경기대학교 환경에너지시스템공학과)
  • Kim, Yo-Yong (Gyeonggi-do Institute of Health & Environment) ;
  • Lee, Si-Jin (Department of Environmental Energy System Engineering, Kyonggi University)
  • 투고 : 2010.11.22
  • 심사 : 2011.07.26
  • 발행 : 2011.07.29

초록

한강의 주요 14개 지류하천 유역의 수질오염원을 평가하고, 2007. 1~2009. 12의 하천 수질자료(14 data set)로 SPSS-17.0을 이용하여 하천별 수질 특성을 평가하였다. 시 공간변화에 대한 군집 분석을 실시한 결과 공간변화에 따라 4그룹으로 평가되었으며, 유역의 오염원 종류 및 밀도가 군집분류에 가장 큰 영향을 미치는 것으로 나타났다. 시간변화에 따라 여름에서 가을까지(7~10월)와 겨울에서 초여름까지(11~6월)의 2그룹으로 분류되어 강우와 기온 그리고 부영양화 현상이 군집화에 기여하는 것으로 평가되었다. 조사대상 하천의 수질오염 요인은 유기물질 영양염류 세균오염요인과 하천 내 물질대사요인으로(71~90%) 설명되었고, 계절에 따라 주요인(수질오염물질)은 변화하는 것으로 나타났다. 각 하천의 수질특성은 요인과 유역 오염원을 같이 평가하였을 때 유용한 결과를 얻을 수 있었다.

In this study, water pollution sources of 14 major tributaries of Han river and characteristics of water quality for each target streams were evaluated based on water quality data in 2007.1-2009.12 (14 data sets) using a statistical package, SPSS-17.0. Cluster analysis over time and space for each stream resulted in 4 groups for the spatial variations in which type and density of pollution sources in the basins showed the greatest impact on grouping. Moreover, cluster analysis for the time variation in which rainfall, temperature and eutrophication were shown to contribute to the clustering, produced 2 groups, from summer to fall (July-Oct.) and from winter to early summer (Nov.-June). Four factors were found as responsible for the data structure explaining 71-90% of the total variance of the data set depending on the streams and they were organic matter, nutrients, bacterial contamination. Factor analysis showed main factors (water pollutants) changed according to the season with different pattern for each stream. This study demonstrated that water quality of each stream could produce useful outcomes when factor and pollution source of basin were evaluated together.

키워드

참고문헌

  1. Papatheodorou, G., Demopoulou, G. and Lambrakis, N., "A long-term study of temporal hydrochemical data in a shallow lake using multivariate statistical techniques," Ecological Modeling, 193, 759-776(2006). https://doi.org/10.1016/j.ecolmodel.2005.09.004
  2. 원태연, 정성원, "Spss Pasw Statistics 18.0 통계조사분석," 하나래출판사, pp. 377-380(2010).
  3. Papatheorou, G., Hotos, Geraga, M., Avramidou, D. and Vorinakis, "Heavy meatal concentrations in sediments of Klisova lagoon (S.E. Mesolonghi- Aitolikon Lagoon complex)", W Greece. Fresen. Envrion. Bull., 11(11), 951-956 (2002).
  4. Lambrakis, N., Antonakos, A. and Panagopoulos, G., "The use of multicomponent statistical analysis in hydrogeological environmental research," Water Res., 38, 1862-1872 (2004). https://doi.org/10.1016/j.watres.2004.01.009
  5. Seymour, S. K., Christanis, K., Bouzinos, A., Papazisimou, S., Papatheodorou, G., Moran, E. and Denes, G., "Tephrostratigraphy and teptigraphy in the Philippi peat vasin, Macedonia, Northern Hellas (Greece)," Quarter. Int., 121, 53-65(2004). https://doi.org/10.1016/j.quaint.2004.01.023
  6. Papatheodorou, G., Mitsis, C., Christodoulou, D. and Ferentinos, G., "A Multivariate statistical approach to the investigation of pockmarks growth and activity. An example from a pockmark field in the Gulf of Patras (W Greece)," in Proceedimgs of the Eighth Annual Conference of the IAMG, September, Abstract Book, Berlin, pp. 15-20(2002).
  7. Simeonov, V., Stratis, J. A., Samara, C., Zachariadis, G., Voutsa, D., Anthemidis, A., Sofoniou, M. and Kouimtzis, T., "Assessment of the surface water quality in Northern Greece," Water Res., 37, 4119-4124(2003). https://doi.org/10.1016/S0043-1354(03)00398-1
  8. Yu, S., Shang, J., Zhao, J. and Guo, H., "Factor analysis and dynamics of water quality of the Songhua River, Northeast China," Water Air Soil Pollut., 144, 159-169(2003). https://doi.org/10.1023/A:1022960300693
  9. 김종구, "통계분석기법을 이용한 금강수계의 수질 분석," 한국환경학회지, 11(12), 1281-1289(2002).
  10. 김종태, 이병제, 김진영, "Trend of distribution on stream qualities in Gumho River, Journal of the korean data & Information," Science, 18, 713-719(2007).
  11. 김경무, 이인락, 김종태, "Factor analysis of the trend of stream quality in Nakdong River," J. Korea Data & Information Science Society, 19(4), 1201-1210(2008).
  12. 김진호, 최철만, 김원일, 이종식, 정구복, 한국헌, 류종수, 이정택, 권순국, "농촌유역의 수질평가를 위한 다변량 기법의 이용," 한국환경농학학회지, 26(1), 17-24(2007).
  13. 김미아, 이재관, 조경덕, "다변량 분석법을 이용한 금강유 역의 수질오염 특성 연구," 한국물환경학회, 23(1), 161-168 (2007).
  14. 오연찬, 이남도, 김종구, "다변량 해석기법을 이용한 만경강 수계의 수질평가," 한국환경과학학회지, 13(3), 233-244 (2004).
  15. 환경부. "한강수계 상수원수질개선 및 주민지원 등에 관한 법률," (2007).
  16. 환경부. "수질측정망 운영계획," (2010).
  17. Ravichandran, S. Ramanibai, R. and Punderikanthan, N. V., "Ecoregions for describing water quality patterns in Tamiraparani basin South India," J. Hydrol., 178, 257-276(1996). https://doi.org/10.1016/0022-1694(95)02801-3
  18. Cameron, E. M., "Hydrogeochemistry of the Fraser River, British Columbia : seasonal variation in major and minor conponents," J. Hydrol., (Amsterdam) 82, 209-225(1996).
  19. 환경부, "2008년 전국오염원조사자료," (2010).
  20. 환경부, "한강수계오염총량관리계획 수립 지침," (2010).
  21. 환경부, "수질 및 수생태계 보전에 관한 법률," (2007).
  22. 경기도팔당수질개선본부, "샛강살리기 project2013 주요하천․호소 수질개선종합대책," (2010).
  23. Forsberg, C. and Ryding, S. O., "Eutrophication parameters and tropic states in 30 Swedish waste receiving lakes," Arck. Fur Hydrbiol., 89, 189-207(1980).
  24. Shrestha, S. and Kazama, F., "Assessment of surface water quality using multivariate statistical techniques ; A case study of the Fuji river basin, Japan," Environmental Modeling & software, 22, 464-475(2007). https://doi.org/10.1016/j.envsoft.2006.02.001
  25. Ouyang, Y., Nkeci-Kizza, P., Ww, Q. T., Shinde, D., and Huang, C. H., "Assessment of seasonal variations in surface water quality," Quater Res., 40, 3800-3810(2006).

피인용 문헌

  1. Application of Regression Analysis Model to TOC Concentration Estimation - Osu Stream Watershed - vol.23, pp.3, 2014, https://doi.org/10.14249/eia.2014.23.3.187
  2. Assessment of Spatiotemporal Water Quality Variation Using Multivariate Statistical Techniques: A Case Study of the Imjin River Basin, Korea vol.39, pp.11, 2017, https://doi.org/10.4491/KSEE.2017.39.11.641