Skip to main content

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

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.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

References

  • Chau, L. W., & Muttil, N. (2007). Data mining and multivariate statistical analysis for ecological waters. Journal of Hydroinformatics, 9(4), 305–317.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    CAS  Article  Google Scholar 

  • Johnson, R. A., & Wichern, D. W. (1992). Applied multivariate statistical analysis (3rd ed.). Englewood Cliffs, New Jersey: Prentice-Hall International.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • Kowlkowski, T., Zbytniewski, R., Szpejna, J., & Buszewski, B. (2006). Apllication of chemometrics in water classification. Water Research, 40, 744–752.

    Article  Google Scholar 

  • Liou, S. M., Lo, S. L., & Wang, S. H. (2004). A generalized water quality index for Taiwan. Environmental Monitoring and Assessment, 96, 35–52.

    CAS  Article  Google Scholar 

  • 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.

    CAS  Article  Google Scholar 

  • 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.

    CAS  Article  Google Scholar 

  • 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.

    CAS  Article  Google Scholar 

  • 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.

    CAS  Article  Google Scholar 

  • Reyment, R. A., & Joreskog, K. H. (1993). Applied factor analysis in the natural sciences. New York: Cambridge University Press.

    Book  Google Scholar 

  • 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 

  • Sharma, S. (1996). Applied multivariate techniques. New York: Wiley.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    CAS  Article  Google Scholar 

  • 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.

    CAS  Article  Google Scholar 

  • 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 

  • 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 

  • 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.

    CAS  Article  Google Scholar 

  • 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 

  • 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.

    Article  Google Scholar 

  • WRA. (2011). Hydrological year book of Taiwan. Taipei: Ministry of Economic Affair, Water Resources Agency (in Chinese).

    Google Scholar 

  • 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.

    CAS  Article  Google Scholar 

  • 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.

    CAS  Article  Google Scholar 

Download references

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.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chen-Wuing Liu.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Wang, YB., Liu, CW., Liao, PY. et al. Spatial pattern assessment of river water quality: implications of reducing the number of monitoring stations and chemical parameters. Environ Monit Assess 186, 1781–1792 (2014). https://doi.org/10.1007/s10661-013-3492-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10661-013-3492-9

Keywords

  • Tamsui River
  • Cluster analysis
  • Factor analysis
  • Discriminate analysis