Skip to main content
SpringerLink
Log in

Variable Fuzzy Set Theory to Assess Water Quality of the Meiliang Bay in Taihu Lake Basin

  • Published:
Water Resources Management Aims and scope Submit manuscript

Abstract

The water quality assessment is a fuzzy concept with multiple indicators and classes. Because of subjectivity in determining index weight and assessment standard as point forms in water quality assessment, evaluation results are often incompatible and independent, and sometimes with unreliable conclusions. An assessment model is developed, based on the variable fuzzy set and the information entropy theory. The model is applied to assess the water quality status of the Meiliang Bay of the Taihu Lake in China. Results show that the proposed model can determine the water quality level and provide an acceptable alternative based on optimized objectivity in determining water quality level. This study could provide a scientific basis for analyzing and evaluating the water quality for environment management.

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.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Chang N, Chen HW, King SK (2001) Identification of river water quality using the fuzzy synthetic evaluation approach. J Environ Manage 63:293–305

    Article  Google Scholar 

  • Charkhabi AH, Sakizadeh M (2006) Assessment of spatial variation of water quality parameters in the most polluted branch of the Anzali Wetland, Northern Iran. Pol J Environ Stud 15(3):395–403

    Google Scholar 

  • Chau KW, Wu CL, Li YS (2005) Comparison of several flood forecasting models in Yangtze River. J Hydrol Eng ASCE 10(6):485–491

    Article  Google Scholar 

  • Chen S (1998) Engineering fuzzy set theory and application. Natl Def Ind Press, Beijing (in Chinese)

  • Chen W, Chau KW (2006) Intelligent manipulation and calibration of parameters for hydrological models. Int J Environ Pollut 28(3–4):432–447

    Article  Google Scholar 

  • Chen SY, Guo Y (2006) Variable fuzzy sets and its application in comprehensive risk evaluation for flood-control engineering system. Fuzzy Optim Decis Ma 5:153–162

    Article  Google Scholar 

  • Chen S, Chai H, Su Y (2007) Variable fuzzy sets methods and application on land suitability evaluation. Transactions of the CSAE 23(3):95–97 (in Chinese with English abstract)

    Google Scholar 

  • Chen FZ, Song XL, Hu YH, Liu ZW, Qin BQ (2009) Water quality improvement and phytoplankton response in the drinking water source in Meiliang Bay of Lake Taihu, China. Ecol Eng 35:1637–1645

    Article  Google Scholar 

  • Chinese Environmental Protection Agency (2002a) Technical specifications requirements for monitoring of surface water and waste water (HJ/T91-2002). China Environment Press, Beijing (in Chinese)

    Google Scholar 

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

    Google Scholar 

  • Croke BEW, Ticehurst JL, Letcher RA, Norton JP, Newham LTH, Jakeman AJ (2007) Integrated assessment of water resources: Australian experiences. Water Resour Manage 21:351–373

    Article  Google Scholar 

  • Dahiya S, Singh B, Gaur S, Garg VK, Kushwaha HS (2007) Analysis of groundwater quality using fuzzy synthetic evaluation. J Hazard M 147:938–946

    Article  Google Scholar 

  • Dökmen F, Aslan Z (2013) Evaluation of the parameters of water quality with wavelet techniques. Water Resour Manage 27(14):4977–4988

    Article  Google Scholar 

  • Guleda OE, Ibrahim D, Halil H (2004) Assessment of urban air quality in Istanbul using fuzzy synthetic evaluation. Atmos Environ 38(23):3809–3815

    Article  Google Scholar 

  • Hussain M, Ahmed SM, Abderrahman W (2008) Cluster analysis and quality assessment of logged water at an irrigation project, eastern Saudi Arabia. J Environ Manage 86(1):297–307

    Article  Google Scholar 

  • Icaga Y (2007) Fuzzy evaluation of water quality classification. Ecol Indic 7:710–718

    Article  Google Scholar 

  • Karmakar S, Mujumdar PP (2006) Grey fuzzy optimization model for water quality management of a river system. Adv Water Resour 29:1088–1105

    Article  Google Scholar 

  • Karmeshu J (2003) Entropy measures, maximum entropy principle and emerging applications. Springer-Verlag, Berlin

    Book  Google Scholar 

  • Kirchner JW (2006) Getting the right answers for the right reasons: Linking measurements, analyses, and models to advance the science of hydrology. Water Resour Res 42:W03S04. doi:10.1029/2005WR004362

    Article  Google Scholar 

  • Koklu R, Sengorur B, Topal B (2010) Water quality assessment using multivariate statistical methods—a case study: Melen River system (Turkey). Water Resour Manage 24(5):959–978

    Article  Google Scholar 

  • Lin CH, Huang TH, Shaw D (2010) Applying water quality modeling to regulating land development in a watershed. Water Resour Manage 24(4):629–640

    Article  Google Scholar 

  • Liou YT, Lo SL (2005) A fuzzy index model for trophic status evaluation of reservoir waters. Water Res 39:1415–1423

    Article  Google Scholar 

  • Liu L, Zhou JZ, An XL (2010) Using fuzzy theory and information entropy for water quality assessment in three Gorges region, China. Expert Syst Appl 37:2517–2521

    Article  Google Scholar 

  • Liu WC, Yu HL, Chung CE (2011) Assessment of water quality in a subtropical alpine lake using multivariate statistical techniques and geostatistical mapping: a case study. Int J Environ Res Public Health 8(4):1126–1140

    Article  Google Scholar 

  • Lu RS, Lo SL, Hu JY (1999) Analysis of reservoir water quality using fuzzy synthetic evaluation. Stoch Env Res Risk A 13(5):327–336

    Article  Google Scholar 

  • Mon DL, Cheng CH, Lin JC (1994) Evaluating weapon system using fuzzy analysis hierarchy process based on entropy weight. Fuzzy Set Syst 62:287–296

    Article  Google Scholar 

  • Muttil N, Chau KW (2006) Neural network and genetic programming for modelling coastal algal blooms. Int J Environ Pollut 28(3–4):223–238

    Article  Google Scholar 

  • Park SS, Lee YS (2002) A water quality modeling study of the Nakdong River, Korea. Ecol Model 152(1):65–75

    Article  Google Scholar 

  • Qin BQ, Xu PZ, Wu QL (2007) Environmental issues of Lake Taihu, China. Hydrobiologia 581:3–14

    Article  Google Scholar 

  • Simeonov V, Stratis JA, Samara C, Zachariadis G, Vouts D, Anthemidis A, Sofoniou M, Kouimtzis T (2003) Assessment of the surface water quality in Northern Greece. Water Res 37(17):4119–4124

    Article  Google Scholar 

  • Sudheer KP, Chaubey I, Garg V (2006) Lake water quality assessment from landsat thematic mapper data using neural network: an approach to optimal band combination selection. J Am Water Resour As 42:1683–1695

    Article  Google Scholar 

  • Taormina R, Chau KW, Sethib R (2012) Artificial Neural Network simulation of hourly groundwater levels in a coastal aquifer system of the Venice lagoon. Eng Appl Artif Intel 25(8):1670–1676

    Article  Google Scholar 

  • Wang HY (2002) Assessment and prediction of overall environmental quality of Zhuzhou City, Hunan Province, China. J Environ Manage 66(3):329–340

    Google Scholar 

  • Wang D, Singh VP, Zhu YS (2007) Hybrid fuzzy and optimal modeling for water quality evaluation. Water Resour Res 43, W05415. doi:10.1029/2006WR005490

    Google Scholar 

  • Wang YK, Wang D, Wu JC (2011) A variable fuzzy set assessment model for water shortage risk: two case studies from China. Hum Ecol Risk Assess 17:631–645

    Article  Google Scholar 

  • Wu CL, Chau KW, Li YS (2009) Predicting monthly streamflow using data-driven models coupled with data-preprocessing techniques. Water Resour Res 45, W08432. doi:10.1029/2007WR006737

    Article  Google Scholar 

  • Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338–353

    Article  Google Scholar 

  • Zhao R, Chen S (2008) Application of fuzzy variable set model to evaluation of rural hydro-modernization. J China Hydraul Eng 39(2):218–223 (in Chinese with English abstract)

    Google Scholar 

  • Zhu GW (2008) Eutrophic status and causing factors for a large, shallow and subtropical Lake Taihu, China. J Lake Sci 20(1):21–26 (in Chinese with English abstract)

    Google Scholar 

Download references

Acknowledgments

This project was supported by the National Natural Science Fund of China (No. 51309131, 41071018 and 41030746), the Skeleton Young Teachers Program and Excellent Disciplines Leaders in Midlife-Youth Program of Nanjing University. We appreciate the thorough and insightful comments by the editor and anonymous reviewers.

Author information

Authors and Affiliations

  1. Key Laboratory of Surficial Geochemistry, Ministry of Education, Department of Hydrosciences, School of Earth Sciences and Engineering, Nanjing University, Nanjing, 210093, People’s Republic of China

    Yuankun Wang, Dong Wang & Jichun Wu

  2. Hunan Water Resources and Hydropower Research Institute, Changsha, 410007, People’s Republic of China

    Dong Sheng

  3. Shandong Electric Power Engineering Consulting Institute Corp, LTD, Jinan, 250013, People’s Republic of China

    Huiqun Ma

  4. Monitoring Bureau of Hydrology and Water Resources, Taihu Basin Authority, Wuxi, 214024, People’s Republic of China

    Feng Xu

Authors
  1. Yuankun Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dong Sheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dong Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Huiqun Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jichun Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Feng Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yuankun Wang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wang, Y., Sheng, D., Wang, D. et al. Variable Fuzzy Set Theory to Assess Water Quality of the Meiliang Bay in Taihu Lake Basin. Water Resour Manage 28, 867–880 (2014). https://doi.org/10.1007/s11269-014-0521-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11269-014-0521-6

Keywords

Search

Navigation