Skip to main content
SpringerLink
Log in

Dynamic water quality evaluation based on fuzzy matter–element model and functional data analysis, a case study in Poyang Lake

  • Research Article
  • Published:
Environmental Science and Pollution Research Aims and scope Submit manuscript

Abstract

Comprehensively evaluating water quality with a single method alone is challenging because water quality evaluation involves complex, uncertain, and fuzzy processes. Moreover, water quality evaluation is limited by finite water quality monitoring that can only represent water quality conditions at certain time points. Thus, the present study proposed a dynamic fuzzy matter–element model (D–FME) to comprehensively and continuously evaluate water quality status. D–FME was first constructed by introducing functional data analysis (FDA) theory into a fuzzy matter–element model and then validated using monthly water quality data for the Poyang Lake outlet (Hukou) from 2011 to 2012. Results showed that the finite water quality indicators were represented as dynamic functional curves despite missing values and irregular sampling time. The water quality rank feature curve was integrated by the D–FME model and revealed comprehensive and continuous variations in water quality. The water quality in Hukou showed remarkable seasonal variations, with the best water quality in summer and worst water quality in winter. These trends were significantly correlated with water level fluctuations (R = −0.71, p < 0.01). Moreover, the extension weight curves of key indicators indicated that total nitrogen and total phosphorus were the most important pollutants that influence the water quality of the Poyang Lake outlet. The proposed D–FME model can obtain scientific and intuitive results. Moreover, the D–FME model is not restricted to water quality evaluation and can be readily applied to other areas with similar problems.

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
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Abtahi M, Golchinpour N, Yaghmaeian K et al (2015) A modified drinking water quality index (DWQI) for assessing drinking source water quality in rural communities of Khuzestan Province, Iran. Ecol Indic 53:283–291

    Article  CAS  Google Scholar 

  • Akkoyunlu A, Akiner ME (2012) Pollution evaluation in streams using water quality indices: a case study from Turkey’s Sapanca Lake Basin. Ecol Indic 18:501–511

    Article  CAS  Google Scholar 

  • Ban X, Wu Q, Pan B 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. Environ Monit Assess 186(7):4237–4247

    Article  CAS  Google Scholar 

  • Beck MB (1987) Water quality modeling: a review of the analysis of uncertainty. Water Resour Res 23(8):1393–1442

    Article  CAS  Google Scholar 

  • Beyhan M, Kaçıkoç M (2014) Evaluation of water quality from the perspective of eutrophication in Lake Eğirdir, Turkey. Water Air Soil Poll 225(7):1–13

    Article  CAS  Google Scholar 

  • Cai W (1999) Extension theory and its application. Chinese Sci Bull 44(17):1538–1548

    Article  Google Scholar 

  • Champely S, Doledec S (1997) How to separate long-term trends from periodic variation in water quality monitoring. Water Res 31(11):2849–2857

    Article  CAS  Google Scholar 

  • Chinese Environmental Protection Agency (2002) National surface water environmental quality standards of China (GB3838-2002). China Standards Press, Beijing (in Chinese)

    Google Scholar 

  • Conley DJ, Markager S, Andersen J (2002) Coastal eutrophication and the Danish national aquatic monitoring and assessment program. Estuaries 25(4):848–861

    Article  Google Scholar 

  • Coops H, Beklioglu M, Crisman TL (2003) The role of water-level fluctuations in shallow lake ecosystems–workshop conclusions. Hydrobiologia 506(1–3):23–27

    Article  Google Scholar 

  • Deng X, Xu Y, Han L et al (2015) Assessment of river health based on an improved entropy-based fuzzy matter-element model in the Taihu plain, China. Ecol Indic 57:85–95

    Article  Google Scholar 

  • Gazzaz NM, Yusoff MK, Aris AZ et al (2012) Artificial neural network modeling of the water quality index for Kinta River (Malaysia) using water quality variables as predictors. Mar Pollut Bull 64(11):2409–2420

    Article  CAS  Google Scholar 

  • Gharibi H, Mahvi AH, Nabizadeh R et al (2012) A novel approach in water quality assessment based on fuzzy logic. J Environ Manag 112:87–95

    Article  CAS  Google Scholar 

  • Haggarty R, Miller C, Scott E et al (2012) Functional clustering of water quality data in Scotland. Environmetrics 23(8):685–695

    Article  CAS  Google Scholar 

  • Henderson B (2006) Exploring between site differences in water quality trends: a functional data analysis approach. Environmetrics 17(1):65–80

    Article  Google Scholar 

  • Hurley M, Currie J, Gough J et al (1996) A framework for the analysis of harmonised monitoring scheme data for England and Wales. Environmetrics 7(4):379–390

    Article  Google Scholar 

  • Ip W, Hu B, Wong H et al (2007) Applications of rough set theory to river environment quality evaluation in China. Water Resour 34(4):459–470

    Article  CAS  Google Scholar 

  • Kazi T, Arain M, Jamali M (2009) Assessment of water quality of polluted lake using multivariate statistical techniques: a case study. Ecotox Environ Safet 72(2):301–309

    Article  CAS  Google Scholar 

  • Kolpin DW, Barbash JE, Gilliom RJ (1998) Occurrence of pesticides in shallow groundwater of the United States: initial results from the National Water-Quality Assessment Program. Environ Sci Technol 32(5):558–566

    Article  CAS  Google Scholar 

  • Lermontov A, Yokoyama L, Lermontov M et al (2009) River quality analysis using fuzzy water quality index: Ribeira do Iguape river watershed, Brazil. Ecol Indic 9(6):1188–1197

    Article  CAS  Google Scholar 

  • Li Y, Li D (2014) Assessment and forecast of Beijing and Shanghai’s urban ecosystem health. Sci Total Environ 487:154–163

    Article  CAS  Google Scholar 

  • Li H, Gu C, Liang T et al (2011) A new perspective of ecosystem health. J Forestry Res 22(1):127–132

    Article  Google Scholar 

  • Li B, Yang G, Wan R et al (2016) Spatiotemporal variability in the water quality of Poyang Lake and its associated responses to hydrological conditions. Water 8(7):296

    Article  Google Scholar 

  • Li B, Yang G, Wan R et al (2017) Using fuzzy theory and variable weights for water quality evaluation in Poyang Lake, China. Chinese Geogr Sci 27(1):39–51

    Article  Google Scholar 

  • Liu D, Zou Z (2012) Water quality evaluation based on improved fuzzy matter-element method. J Environ Sci 24(7):1210–1216

    Article  CAS  Google Scholar 

  • Liu L, Zhou J, An X et al (2010) Using fuzzy theory and information entropy for water quality assessment in three gorges region, China. Expert Syst Appl 37(3):2517–2521

    Article  Google Scholar 

  • Liu X, Teubner K, Chen Y (2016) Water quality characteristics of Poyang Lake, China, in response to changes in the water level. Hydrol Res 47(S1):238–248

    Article  Google Scholar 

  • Müller HG, Sen R, Stadtmüller U (2011) Functional data analysis for volatility. J Econometrics 165(2):233–245

    Article  Google Scholar 

  • O’Farrell I, Izaguirre I, Chaparro G et al (2011) Water level as the main driver of the alternation between a free-floating plant and a phytoplankton dominated state: a long-term study in a floodplain lake. Aquat Sci 73(2):275–287

    Article  Google Scholar 

  • Ocampo-Duque W, Ferre-Huguet N, Domingo JL et al (2006) Assessing water quality in rivers with fuzzy inference systems: a case study. Environ Int 32(6):733–742

    Article  CAS  Google Scholar 

  • Ouyang Y, Nkedi-Kizza P, Wu Q et al (2006) Assessment of seasonal variations in surface water quality. Water Res 40(20):3800–3810

    Article  CAS  Google Scholar 

  • Ramsay JO (2006) Functional data analysis. Wiley Online Library

  • Ramsay JO, Dalzell C (1991) Some tools for functional data analysis. Journal of the Royal Statistical Society Series B (Methodological):539–572

  • Ramsay JO, Silverman BW (2002) Applied functional data analysis: methods and case studies, vol 77. Citeseer

  • Ramsay J O, Hooker G, Graves S (2009) Functional data analysis with R and MATLAB. Springer Science & Business Media

  • Seiler LM, Fernandes EHL, Martins F et al (2015) Evaluation of hydrologic influence on water quality variation in a coastal lagoon through numerical modeling. Ecol Model 314:44–61

    Article  CAS  Google Scholar 

  • Semiromi FB, Hassani A, Torabian A et al (2011) Evolution of a new surface water quality index for Karoon catchment in Iran. Water Sci Technol 64(12):2483–2491

    Article  CAS  Google Scholar 

  • Smith VH, Tilman GD, Nekola JC (1999) Eutrophication: impacts of excess nutrient inputs on freshwater, marine, and terrestrial ecosystems. Environ Pollut 100(1):179–196

    Article  CAS  Google Scholar 

  • Srebotnjak T, Carr G, Sherbinin A et al (2012) A global water quality index and hot-deck imputation of missing data. Ecol Indic 17:108–119

    Article  CAS  Google Scholar 

  • Taner MÜ, Üstün B, Erdinçler A (2011) A simple tool for the assessment of water quality in polluted lagoon systems: a case study for Küçükçekmece Lagoon, Turkey. Ecol Indic 11(2):749–756

    Article  CAS  Google Scholar 

  • Tang X, Li H, Xu X et al (2016) Changing land use and its impact on the habitat suitability for wintering Anseriformes in China’s Poyang Lake region. Sci Total Environ 557:296–306

    Article  Google Scholar 

  • Team R (2012) Development core. R: A language and environment for statistical computing

  • Teng J, Zhang T, Lu W (2012) Structural stress identification using fuzzy pattern recognition and information fusion technique. J of Civ Eng Architec 6(4):479

    Google Scholar 

  • Ullah S, Finch CF (2013) Applications of functional data analysis: a systematic review. BMC Med Ees Methodol 13(1):1

    Article  Google Scholar 

  • Vega M, Pardo R, Barrado E et al (1998) Assessment of seasonal and polluting effects on the quality of river water by exploratory data analysis. Water Res 32(12):3581–3592

    Article  CAS  Google Scholar 

  • Vitousek PM, Mooney HA, Lubchenco J et al (1997) Human domination of Earth’s ecosystems. Science 277(5325):494–499

    Article  CAS  Google Scholar 

  • Wahba G, Craven P (1978) Smoothing noisy data with spline functions. Estimating the correct degree of smoothing by the method of generalized cross-validation. Numer Math 31:377–404

    Article  Google Scholar 

  • Wang H, Liu Z, Sun L et al (2015) Optimal design of river monitoring network in Taizihe River by matter element analysis. PLoS One 10(5):e0127535

    Article  Google Scholar 

  • Wong H, Hu BQ (2014) Application of improved extension evaluation method to water quality evaluation. J Hydrol 509:539–548

    Article  CAS  Google Scholar 

  • Yan F, Liu L, Li Y et al (2015) A dynamic water quality index model based on functional data analysis. Ecol Indic 57:249–258

    Article  CAS  Google Scholar 

  • Yan F, Liu L, Zhang Y et al (2016) The research of dynamic variable fuzzy set assessment model in water quality evaluation. Water Resour Manag 30(1):63–78

    Article  Google Scholar 

  • Zhang J, Wang K, Chen X et al (2011) Combining a fuzzy matter-element model with a geographic information system in eco-environmental sensitivity and distribution of land use planning. Int J Environ Res Public Health 8(4):1206–1221

    Article  Google Scholar 

  • Zhang Y, Liu X, Qin B (2016) Aquatic vegetation in response to increased eutrophication and degraded light climate in Eastern Lake Taihu: implications for lake ecological restoration. Sci Rep 6:23867

    Article  CAS  Google Scholar 

  • Zhou W, Yin K, Harrison PJ et al (2012) The influence of late summer typhoons and high river discharge on water quality in Hong Kong waters. Estuar Coast Shelf S 111:35–47

    Article  CAS  Google Scholar 

  • Zhu F, Zhong P, Xu B et al (2016) A multi-criteria decision-making model dealing with correlation among criteria for reservoir flood control operation. J Hydroinf 18(3):531–543

    Google Scholar 

  • Zou Z, Yi Y, Sun J (2006) Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment. J Environ Sci 18(5):1020–1023

    Article  CAS  Google Scholar 

Download references

Acknowledgments

This research was financially supported by the National Basic Research Program of China (973 Program) (Grant 2012CB417006) and the National Scientific Foundation of China (Grant 41571107 and 41601041). The authors would also like to thank the editor and reviewers for their extensive review that significantly improved the manuscript.

Author information

Authors and Affiliations

  1. Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China

    Bing Li, Guishan Yang & Rongrong Wan

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Bing Li

  3. Department of Hydrology and Water Resources Management, Institute of Natural Resource Conservation, Kiel University , 24118, Kiel, Germany

    Bing Li & Georg Hörmann

Authors
  1. Bing Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guishan Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rongrong Wan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Georg Hörmann
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Guishan Yang.

Additional information

Responsible editor: Marcus Schulz

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, B., Yang, G., Wan, R. et al. Dynamic water quality evaluation based on fuzzy matter–element model and functional data analysis, a case study in Poyang Lake. Environ Sci Pollut Res 24, 19138–19148 (2017). https://doi.org/10.1007/s11356-017-9371-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11356-017-9371-0

Keywords

Search

Navigation