Advertisement

Environmental Monitoring and Assessment

, Volume 186, Issue 3, pp 1781–1792 | Cite as

Spatial pattern assessment of river water quality: implications of reducing the number of monitoring stations and chemical parameters

  • Yeuh-Bin Wang
  • Chen-Wuing LiuEmail author
  • Pei-Yu Liao
  • Jin-Jing Lee
Article

Abstract

The Tamsui River basin is located in Northern Taiwan and encompasses the most metropolitan city in Taiwan, Taipei City. The Taiwan Environmental Protection Administration (EPA) has established 38 water quality monitoring stations in the Tamsui River basin and performed regular river water quality monitoring for the past two decades. Because of the limited budget of the Taiwan EPA, adjusting the monitoring program while maintaining water quality data is critical. Multivariate analysis methods, such as cluster analysis (CA), factor analysis (FA), and discriminate analysis (DA), are useful tools for the statistically spatial assessment of surface water quality. This study integrated CA, FA, and DA to evaluate the spatial variance of water quality in the metropolitan city of Taipei. Performing CA involved categorizing monitoring stations into three groups: high-, moderate-, and low-pollution areas. In addition, this categorization of monitoring stations was in agreement with that of the assessment that involved using the simple river pollution index. Four latent factors that predominantly influence the river water quality of the Tamsui River basin are assessed using FA: anthropogenic pollution, the nitrification process, seawater intrusion, and geological and weathering processes. We plotted a spatial pattern using the four latent factor scores and identified ten redundant monitoring stations near each upstream station with the same score pattern. We extracted five significant parameters by using DA: total organic carbon, total phosphorus, As, Cu, and nitrate, with spatial variance to differentiate them from the polluted condition of the group obtained by using CA. Finally, this study suggests that the Taiwan EPA can adjust the surface water-monitoring program of the Tamsui River by reducing the monitoring stations to 28 and the measured chemical parameters to five to lower monitoring costs.

Keywords

Tamsui River Cluster analysis Factor analysis Discriminate analysis 

Notes

Acknowledgments

The authors would like to thank the Department of Environmental Monitoring and Information Management, Environmental Protection Administration, Taiwan (R.O.C.), for the data provided for the Tamsui River basin.

References

  1. Chau, L. W., & Muttil, N. (2007). Data mining and multivariate statistical analysis for ecological waters. Journal of Hydroinformatics, 9(4), 305–317.CrossRefGoogle Scholar
  2. Chen, Y. C., Yeh, H. C., & Wei, C. (2012). Estimation of river pollution index in a tidal stream using Kriging analysisInt. Journal of Environmental Research and Public Health, 9, 3085–3100.CrossRefGoogle Scholar
  3. Cheng, B. Y., Liu, T. C., Shyu, G. S., Chang, T. K., & Fang, W. T. (2011). Analysis of trends in water quality: Constructed wetlands in metropolitan Taipei. Water Science and Technology, 64(11), 2143–2150.CrossRefGoogle Scholar
  4. Johnson, R. A., & Wichern, D. W. (1992). Applied multivariate statistical analysis (3rd ed.). Englewood Cliffs, New Jersey: Prentice-Hall International.Google Scholar
  5. Juahir, H., Zain, S. Z., Yusoff, M. K., Hanida, T. I. T., Armi, A. S. M., Toriman, M. E., et al. (2011). Spatial water quality assessment of Langat River Basin (Malaysia) using environmetric techniques. Environmental Monitoring and Assessment, 173, 625–641.CrossRefGoogle Scholar
  6. Kowlkowski, T., Zbytniewski, R., Szpejna, J., & Buszewski, B. (2006). Apllication of chemometrics in water classification. Water Research, 40, 744–752.CrossRefGoogle Scholar
  7. Liou, S. M., Lo, S. L., & Wang, S. H. (2004). A generalized water quality index for Taiwan. Environmental Monitoring and Assessment, 96, 35–52.CrossRefGoogle Scholar
  8. Liu, C. W., Lin, K. H., & Kuo, Y. M. (2003). Application of factor analysis in the assessment of groundwater quality in a blackfoot disease area in Taiwan. Science of the Total Environment, 313, 77–89.CrossRefGoogle Scholar
  9. Lu, K. L., Liu, C. W., & Jang, C. S. (2012). Using multivariate statistical methods to assess the groundwater quality in an arsenic-contaminated area of Southwestern Taiwan. Environmental Monitoring and Assessment, 184, 6071–6085.CrossRefGoogle Scholar
  10. Olsen, R. L., Chappell, R. W., & Lofits, J. C. (2012). Water quality sample collection, data treatment and results presentation for principal components analysis—Literature review and Illinois River watershed case study. Water Research, 46, 3110–3122.CrossRefGoogle Scholar
  11. Pinto, U., & Maheshwari, B. L. (2011). River health assessment in peri-urban landscape: An application of multivariate analysis to identify the key variable. Water Research, 45, 3915–3924.CrossRefGoogle Scholar
  12. Reyment, R. A., & Joreskog, K. H. (1993). Applied factor analysis in the natural sciences. New York: Cambridge University Press.CrossRefGoogle Scholar
  13. Samsudin, M. S., Juahir, H., Zain, S. M., & Adhan, N. H. (2011). Surface river water quality interpretation using environmetric techniques: Case study at Perlis river basin, Malaysia. International Journal of Environmental Protection, 1(5), 1–8.Google Scholar
  14. Sharma, S. (1996). Applied multivariate techniques. New York: Wiley.Google Scholar
  15. Shrestha, S., & Kazama, F. (2007). Assessment of surface water quality using multivariate statistical techniques: A case study of Fuji river basin, Japan. Environmental Modelling and Software, 22, 464–475.CrossRefGoogle Scholar
  16. Simeonov, V., Stratis, J. A., Samara, C., Zachariadis, G., Voutsa, D., Anthemidis, A., et al. (2003). Assessment of the surface water in Northern Greece. Water Research, 37, 4119–4124.CrossRefGoogle Scholar
  17. Singh, K. P., Malik, A., Mohan, D., & Sinha, A. (2004). Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India)—a case study. Water Research, 38, 3980–3992.CrossRefGoogle Scholar
  18. Taiwan Environmental ProtectionAdministration, EPA Taiwan. (2012). The actual record of water quality protection from 1987 to 2012 (pp. 165–171). Taipei: Taiwan Environmental Protection Administration (in Chinese).Google Scholar
  19. Venkastesharaju, K., Somashejar, R. K., & Prakash, K. L. (2010). Study of seasonal and spatial variation in surface water quality of Cauvery river stretch in Karnataka. Journal of Ecology and Natural Environment, 2(1), 1–9.Google Scholar
  20. Wang, X. L., Lu, Y. L., Han, J. Y., He, G. Z., & Wang, T. Y. (2007). Identification of anthropogenic influence on water quality of rivers in Taihu watershed. Journal of Environmental Sciences, 19, 475–481.CrossRefGoogle Scholar
  21. Wang, X., Cai, Q., Ye, L., & Qu, X. (2012). Evaluation of spatial and temporal variation in stream water by multivariate statistical techniques: A case study of the Xiangxi River basin, China. Quaternary International, 1, 1–8.Google Scholar
  22. Wen, L. S., Jiann, K. T., & Liu, K. K. (2008). Seasonal variation and flux of dissolved nutrients in the Danshuei Estuary, Taiwan: A hypoxic subtropical mountain river. Estuarine, Coastal and Shelf Science, 78, 694–704.CrossRefGoogle Scholar
  23. WRA. (2011). Hydrological year book of Taiwan. Taipei: Ministry of Economic Affair, Water Resources Agency (in Chinese).Google Scholar
  24. Yang, Y. H., Zhou, F., Guo, H. C., Sheng, H., Liu, H., & Dao, X. (2010). Analysis of spatial and temporal water pollution patterns in Lake Dianchi using multivariate statistical methods. Environmental Monitoring and Assessment, 170, 407–416.CrossRefGoogle Scholar
  25. 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. Environmental Monitoring and Assessment, 132, 1–13.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Yeuh-Bin Wang
    • 1
    • 2
  • Chen-Wuing Liu
    • 1
    Email author
  • Pei-Yu Liao
    • 1
  • Jin-Jing Lee
    • 3
  1. 1.Department of Bioenvironmental Systems EngineeringNational Taiwan UniversityTaipeiRepublic of China
  2. 2.Department of Water Quality ProtectionEnvironmental Protection AdministrationTaipeiRepublic of China
  3. 3.Water Resources BureauTaichung City GovernmentTaichungRepublic of China

Personalised recommendations