Skip to main content

Advertisement

SpringerLink
Log in

Comparison of seven water quality assessment methods for the characterization and management of highly impaired river systems

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

In the context of water resource management and pollution control, the characterization of water quality impairments and identification of dominant pollutants are of critical importance. In this study, water quality impairment was assessed on the basis of 7 hydrochemical variables that were monitored bimonthly at 17 sites in 2010 along the rural-suburban-urban portion of the Wen-Rui Tang River in eastern China. Seven methods were used to assess water quality in the river system. These methods included single-factor assessment, water quality grading, comprehensive pollution index, the Nemerow pollution index, principle component analysis, fuzzy comprehensive evaluation, and comprehensive water quality identification index. Our analysis showed that the comprehensive water quality identification index was the best method for assessing water quality in the Wen-Rui Tang River due to its ability to effectively characterize highly polluted waters with multiple impairments. Furthermore, a guideline for the applications of these methods was presented based on their characteristics and efficacy. Results indicated that the dominant pollutant impairing water quality was total nitrogen comprised mainly of ammonium. The temporal variation of water quality was closely related to precipitation as a result of dilution. The spatial variation of water quality was associated with anthropogenic influences (urban, industrial, and agriculture activities) and water flow direction (downstream segments experiencing cumulative effects of upstream inputs). These findings provide valuable information and guidance for water pollution control and water resource management in highly polluted surface waters with multiple water quality impairments in areas with rapid industrial growth and urbanization.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Ban, X., Wu, Q. Z., Pan, B. Z., et al. (2014). Application of composite water quality identification index on the water quality evaluation in spatial and temporal variations: a case study in Honghu Lake, China. Environmental Monitoring and Assessment, 186, 4237–4247.

    Article  CAS  Google Scholar 

  • Bu, H. M., Tan, X., Li, S. Y., et al. (2010). Water quality assessment of the Jinshui River (China) using multivariate statistical techniques. Environmental Earth Sciences, 60, 1631–1639.

    Article  CAS  Google Scholar 

  • Chen, H. W., Chang, N. B., & Shaw, D. (2005). Valuation of in-stream water quality improvement via fuzzy contingent valuation method. Stochastic Environmental Research and Risk Assessment, 19(2), 158–171.

    Article  Google Scholar 

  • Cheng, J. L., Zhou, S., & Zhu, Y. M. (2007). Assessment and mapping of environmental quality in agriculture soils of Zhejiang Province, China. Journal of Environmental Sciences, 19, 50–54.

    Article  CAS  Google Scholar 

  • Dalal, S. G., Shirodkar, P. V., Jagtap, T. G., et al. (2010). Evaluation of significant sources influencing the variation of water quality of Kandla Creek, Gulf of Katchchh, using PCA. Environmental Monitoring and Assessment, 16, 49–56.

    Article  Google Scholar 

  • Dierk, W., & Michael, R. (2008). Modelling the impact of river morphology on nitrogen retention—a case study of the Weisse Elster River (Germany). Ecological Modelling, 211, 224–232.

    Article  Google Scholar 

  • Fu, T. Y., Zou, Z. H., & Wang, X. J. (2014). Water quality assessment for Taizi River watershed in Liaoyang section based on multivariate statistical analysis and water quality identification index. Acta Scientiae Circumstantiae, 34(2), 473–480 (in Chinese).

    Article  CAS  Google Scholar 

  • Helena, B., Pardo, R., Vega, M., et al. (2000). Temporal evolution of groundwater composition in an alluvial aquifer (Pisuerga River, Spain) by principal component analysis. Water Research, 34, 807–816.

    Article  CAS  Google Scholar 

  • Holloway, J. M., Dahlgren, R. A., Hansen, B., et al. (1998). Contribution of bedrock nitrogen to high nitrate concentrations in stream water. Nature, 395, 785–788.

    Article  CAS  Google Scholar 

  • Hope, C., Parker, J., & Peake, S. (1992). A pilot environmental index for the UK in the 1980s. Energy Policy, 20, 335–343.

    Article  Google Scholar 

  • Houser, J. N., & Richardson, W. B. (2010). Nitrogen and phosphorous in the Upper Mississippi River: transport, processing, and effects on the river ecosystem. Hydrobiologia, 640, 71–88.

    Article  CAS  Google Scholar 

  • Huang, F., Wang, X. Q., Lou, L. P., et al. (2010). Spatial variation and source apportionment of water pollution in Qiantang River (China) using statistical techniques. Water Research, 44, 1562–1572.

    Article  CAS  Google Scholar 

  • Khanna, N. (2000). Measuring environmental quality: an index of pollution. Ecological Economics, 35, 191–202.

    Article  Google Scholar 

  • Li, S., & Zhang, Q. (2010). Spatial characterization of dissolved trace elements and heavy metals in the upper Han River (China) using multivariate statistical techniques. Journal of Hazardous Materials, 176, 579–588.

    Article  CAS  Google Scholar 

  • Liu, X. Z., Heilig, G. K., Chen, J. M., et al. (2007). Interactions between economic growth and environmental quality in Shenzhen, China’s first special economic zone. Ecological Economics, 62, 559–570.

    Article  Google Scholar 

  • Lu, R. S., & Lo, S. L. (2002). Diagnosing reservoir water quality using self-organizing maps and fuzzy theory. Water Research, 36, 2265–2274.

    Article  CAS  Google Scholar 

  • Lu, P., Mei, K., Zhang, Y. J., et al. (2011). Spatial and temporal variations of nitrogen pollution in Wen-Rui Tang River watershed, Zhejiang, China. Environmental Monitoring and Assessment, 180, 501–520.

    Article  CAS  Google Scholar 

  • Massoud, M. A. (2012). Assessment of water quality along a recreational section of the Damour River in Lebanon using the water quality index. Environmental Monitoring and Assessment, 184, 4151–4160.

    Article  Google Scholar 

  • Mei, K., Liao, L. L., Zhu, Y. L., et al. (2014). Evaluation of spatial-temporal variations and trends in surface water quality across a rural-suburban-urban interface. Environmental Science and Pollution Research, 21, 8036–8051.

    Article  CAS  Google Scholar 

  • Morse, N. B., & Wollheim, W. M. (2014). Climate variability masks the impacts of land use change on nutrient export in a suburbanizing watershed. Biogeochemistry, 121, 45–59.

    Article  Google Scholar 

  • National Research Council (NRC). (2001). Assessing the TMDL approach to water quality management. Washington, D C: National Academy Press.

    Google Scholar 

  • Phung, D., Huang, C. R., Rutherford, S., et al. (2015). Temporal and spatial assessment of river surface water quality using multivariate statistical techniques: a study in Can Thi City, a Mekong Delta area, Vietnam. Environmental Monitoring and Assessment, 187, 229.

    Article  CAS  Google Scholar 

  • Shin, J. Y., Artigas, F., Hobble, C., et al. (2013). Assessment of anthropogenic influences on surface water quality in urban estuary, northern New Jersey: multivariate approach. Environmental Monitoring and Assessment, 185, 2777–2794.

    Article  CAS  Google Scholar 

  • Shrestha, S., & Kazama, F. (2007). Assessment of surface water quality using multivariate statistical techniques: a case study of the Fuji River basin, Japan. Environmental Modeling and Software, 22, 464–475.

    Article  Google Scholar 

  • Simeonov, V., Stratis, J. A., Samara, C., et al. (2003). Assessment of the surface water quality in northern Greece. Water Research, 37, 4119–4124.

    Article  CAS  Google Scholar 

  • Singh, K. P., Malik, A., Mohan, D., et al. (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.

    Article  CAS  Google Scholar 

  • Singh, K. P., Basant, N., & Gupta, S. (2011). Support vector machines in water quality management. Analytical Chimca Acta, 703, 152–162.

    Article  CAS  Google Scholar 

  • Wang, X. Z., & Wang, P. (2011). The application and analysis of several appraisal methods for river water quality in Huairou reservoir. Beijing Water, 1, 31–33 (in Chinese).

    Google Scholar 

  • Xu, Z. X. (2005). Comprehensive water quality identification index for environmental quality assessment of surface water. Journal of Tongji University (Natural Science), 33, 482–488 (in Chinese).

    CAS  Google Scholar 

  • Yang, L. P., Mei, K., Liu, X. M., et al. (2013). Spatial distribution and source apportionment of water pollution in different administrative zones of Wen-Rui-Tang river watershed (WRT), China. Environmental Science and Pollution Research, 20, 5341–5352.

    Article  CAS  Google Scholar 

  • Zhejiang Environmental Protection Bureau (ZEPB). (2010). Scheme for river function zoning and water environment zoning of Zhejiang Province document of Zhejiang Government. (in Chinese)

Download references

Acknowledgements

The authors would like to acknowledge the funding support from a project of the Science and Technology Department of Zhejiang Province (award number 2008C03009). We are also thankful to the Wenzhou Environmental Protection Agency for the data provided for the Wen-Rui Tang River.

Author information

Authors and Affiliations

  1. Institute of Wenzhou Applied Technology in Environmental Research, Wenzhou Medical University, Wenzhou, 325035, China

    Xiaoliang Ji, Randy A. Dahlgren & Minghua Zhang

  2. Southern Zhejiang Water Research Institute, Wenzhou, 325035, China

    Xiaoliang Ji, Randy A. Dahlgren & Minghua Zhang

  3. Department of Land, Air and Water Resources, University of California Davis, Davis, CA, 95616, USA

    Randy A. Dahlgren & Minghua Zhang

Authors
  1. Xiaoliang Ji
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Randy A. Dahlgren
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Minghua Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Minghua Zhang.

Appendices

Appendix A

Table 7 Environmental guideline of national quality standards for surface waters, China (GB3838-2002) (units: mg/L)
Full size table

Appendix B

Table 8 Average concentration of the water quality parameters at each sampling site considered in this study (mg/L)
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ji, X., Dahlgren, R.A. & Zhang, M. Comparison of seven water quality assessment methods for the characterization and management of highly impaired river systems. Environ Monit Assess 188, 15 (2016). https://doi.org/10.1007/s10661-015-5016-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-015-5016-2

Keywords

Search

Navigation