Skip to main content

Fuzzy Logic Water Quality Index (FWQI) Model in Determining the Water Quality Status of River in Penang Island

  • Conference paper
  • First Online:
Charting the Sustainable Future of ASEAN in Science and Technology

Abstract

The benchmark of water quality status of a river or any other water suppliers is difficult to determine. Thus, it is essential to have a good model in determining the status of water quality. The conventional water quality used by Development of Environment (DOE) has some limitations, by which many researchers have developed and used varieties of water quality measurements, but the value of water quality index (WQI) is still not accurate. In recent years, the methods of fuzzy logic have been proved where it is suitable to deal with the vagueness in environmental issues. Therefore, in this study, the development of a new index which is called the fuzzy logic water quality index (FWQI) is proposed to determine the water quality status of rivers in Penang Island, which are at Juru River, Pinang River and Dondang River by using six parameters, namely dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), total suspended solid (TSS), ammoniacal nitrogen (NH3-N) and pH value. FWQI is a suitable model to be used in determining the status of water quality since the overall rate of accuracy is high. The result from this study shows that the status of the rivers for both stations at Juru River and Pinang River are polluted, while the status is slightly polluted for Dondang River.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Babaei SF, Hassani AH, Torabian A, Hosseinzadeh LF (2011) Water quality index development using fuzzy logic: a case study of the Karoon River of Iran. Afr J Biotechnol, 10(50):10125–10133

    Google Scholar 

  • Gharibi H, Mahvi AH, Nabizadeh R, Arabalibeik H, Yunesian M, Sowlat MH (2012) A novel approach in water quality assessment based on fuzzy logic. J Environ Manage 112:87–95

    Article  Google Scholar 

  • Hndoosh R, Saroa M, Kumar S (2012) Fuzzy and adaptive neuro-fuzzy inference system of washing machine. Eur J Sci Res 86(3): 443–459. ISSN 1450-216X

    Google Scholar 

  • Horton RK (1965) An index number system for rating water quality. J Walter Poll Cont Fed 37(3):300–306

    Google Scholar 

  • Kiurski-Milosevic J, Vojinovic-Miloradov M, Ralevic N (2015) Fuzzy model for determination and assessment of groundwater quality in the city of Zrenjanin, Serbia. 69(1):17–28

    Article  Google Scholar 

  • Nasir MFM, Zali MA, Juahir H, Hussain H, Zain SM, Ramli N (2012) Application of receptor models on water quality data in source apportionment in Kuantan River Basin. Iran J Environ Health Sci & Eng 9(1):18

    Article  Google Scholar 

  • Salmiati NZA, Salim MR (2017) Integrated approaches in water quality monitoring for river health assessment: scenario of Malaysian River

    Google Scholar 

  • Sellitto MA, Balugani E, Gamberini R, Rimini B (2018) A fuzzy logic control application to the cement industry. IFAC-PapersOnLine 51(11):1542–1547

    Article  Google Scholar 

  • Suratman S, Awang M, Loh AL, Mohd Tahir N (2009) Water quality index study in Paka River Basin, Terengganu (in Malay). Sains Malays 38:125–131

    Google Scholar 

  • Suratman S, Sailan MM, Hee YY, Latif MT (2015) A preliminary study of water quality index in Terengganu River Basin, Malaysia (Kajian Awal Indeks Kualiti Air di Lembangan Sungai Terengganu, Malaysia). Sains Malays 44(1):67–73

    Google Scholar 

  • UNEP G (2007) Global drinking water quality index development and sensitivity analysis report. Water Programme Office, Ontario, Canada

    Google Scholar 

  • Zadeh LA (1973) Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans Syst, Man, Cybern 3(1):28–44

    Article  Google Scholar 

  • Zainudin Z (2010) Benchmarking river water quality in Malaysia. Jurutera, 12–15

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Siti Nor Nadrah Muhamad .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Muhamad, S.N.N., Idris, M.F.I.M., Wahab, N.I.H., Shahidan, W.N.W. (2020). Fuzzy Logic Water Quality Index (FWQI) Model in Determining the Water Quality Status of River in Penang Island. In: Alias, N., Yusof, R. (eds) Charting the Sustainable Future of ASEAN in Science and Technology . Springer, Singapore. https://doi.org/10.1007/978-981-15-3434-8_34

Download citation

  • DOI: https://doi.org/10.1007/978-981-15-3434-8_34

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-3433-1

  • Online ISBN: 978-981-15-3434-8

  • eBook Packages: Social SciencesSocial Sciences (R0)

Publish with us

Policies and ethics