Skip to main content
Log in

Fuzzy Logic Interference for Characterization of Surface Water Potability in Ikare Rural Community, Nigeria

  • Published:
Journal of Geovisualization and Spatial Analysis Aims and scope Submit manuscript

Abstract

The availability of potable surface water in Nigeria, a typical developing nation, is low, and this information is not readily available to local residents in the country. Therefore, we carried out a low-cost Fuzzy Logic Inference characterization on the quality of surface water in a rural community (with 12 catchment areas) of Ikare, Ondo State of Nigeria. From the numerous water samples taken from the river that runs across the catchment areas, twenty (20) representative water samples were chosen and subjected to physical (temperature, pH), chemical (such as TDS, DO, BOD, metal ion concentrations), and biological (fecal and total coliform) characterizations. Further, five fuzzy sets and Mamdani fuzzy inference system method were used to normalize the parameters for pollution susceptibility analysis. We adopted GIS environment to provide a synoptic and high temporal information about the distribution of the surface water quality, indicating the areas susceptible to pollution. When compared with World Health Organization (WHO) and Nigeria Industrial Standards, we found the waters were generally unsuitable for drinking. Only 8.3% of the studied water samples were moderate for drinking while in linguistic terms for pollutant levels, 16.7%, 50%, and 25% fell in the categories of high, very high, and extremely high, respectively. Through statistical correlation (p < 0.05), we identified the notable water pollutants as fecal coliform, heavy metal, K+, and total dissolved solids. Therefore, we infer that direct excretion into the water channels, dumping of spent oil from mechanic workshop, and effluents from domestic and agricultural wastes are the major sources of the pollutants. Consequently, fuzzy logic analysis proved to be a readily available and reliable method for water potability assessment, especially in rural areas of developing nations.

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

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Instant access to the full article PDF.

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

Similar content being viewed by others

References

  • Aboyeji OS, Stephen FE (2016) Evaluations of groundwater contamination by leachates around Olusosun open dumpsite in Lagos metropolis, southwest Nigeria. J Environ Manag 1-9

  • Akomolafe C (1976) Akoko under British rule 1900-1935. M.Phil thesis, University of Ife.

  • Alkins-Koo M, Lucas F, Maharaj L, Maharaj S, Phillip D, Rostant W, Surujdeo-Maharaj S (2003) Water resources and aquatic biodiversity conservation: a role for ecological assessment of rivers in Trinidad and Tobago. Department of Life Sciences, University of the West Indies, St Augustine

    Google Scholar 

  • Areola O (1991) Ecology of natural resources in Nigeria. Avebury Academic Publishing Group, Aldreshot

    Google Scholar 

  • Berkan RC, Trubatch SL (1997) Fuzzy systems design principles. IEEE Press, New York

    Google Scholar 

  • Bisi-Johnson M, Adediran K, Akinola S, Popoola E, Okoh A (2017) Comparative physicochemical and microbiological qualities of source and stored household waters in some selected communities in Southwestern Nigeria. Sustainability 9:454

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Chapman D, Kimstach V (1996) Water quality assessment: a guide to biota, sediment and water in environmental monitoring. UNESCO/WHO/UNEP 2:73–130

    Google Scholar 

  • Chen Q, Mei K, Dahlgren RA, Wang T, Gong J, Zhang M (2016) Impact of land use and population on seasonal surface water quality using a modified geographically weighted regression. Sci Total Environ 572:450–466

    Article  Google Scholar 

  • Edokpayi JN, Odiyo JO, Olasoji SO (2014) Assessment of heavy metal contamination of Dzindi River, in Limpopo Province, South Africa. Int J Nat Sci Res 2(10):185–194

    Google Scholar 

  • Edokpayi J, Odiyo J, Popoola O, Msagati T (2016) Assessment of trace metals contamination of surface water and sediment: a case study of Mvudi River, South Africa. Sustainability:1–13

  • Faboyede O (2015) Akokoland before colonial rule: earliest times to 1900. AFRREV IJAH 4(1):46–65

    Google Scholar 

  • Gharibi H, Sowlat MH, Mahvi AH, Mahmoudzadeh H, Arabalibeik H, Keshavarz M, Karimzadeh N, Hassani G (2012) Development of a dairy cattle drinking water quality index (DCWQI) based on Fuzzy Inference Systems. Ecol Indic 20:228–237

    Article  Google Scholar 

  • Habeeb R, Gupta Y, Chinwan H, Barker E (2019) Assessing Demographic and Water Sensitivities Arising due to Urban Water Insecurity in Haldwani, Uttarakhand (India): a GIS-Based Spatial Analysis. J Geovisual Spatial Anal 3:8

  • HACH (2018) Coliforms, Total and E. coli. Hach Company/Hach Lange GmbH, Loveland Edition 11, pp 1–7

    Google Scholar 

  • Huang F, Wang XQ, Lou LP (2010) Spatial variation and source apportionment of water pollution in Qiantang River (China) using statistical techniques. Water Res 44(5):1562–1572

    Article  Google Scholar 

  • Ince M, Bashir D, Oni OOO, Awe EO, Ogbechie V, Korve K, Adeyinka MA, Olufolabo AA, Ofordu F, Kehinde M (2004) Rapid assessment of drinking-water quality in the federal republic of Nigeria. World Health Organization and UNICEF, Country report of the pilot project implementation in (2005, 2010), pp 10–30

  • Ip WC, Hu BQ, Wong H, Xia J (2009) Applications of grey relational method to river environment quality evaluation in China. J Hydrol 379(3):284–290

    Article  Google Scholar 

  • Ishaku JM (2011) Assessment of groundwater quality index for Jimeta-Yola area, Northeastern Nigeria. J Geo Min Res Vol 3(9):219–231

    Google Scholar 

  • Joseph B, Justin SR, Edwin TB, Sankarganesh P, Jeevitha MV, Ajisha SU, Sheeja SR (2010) Toxic effect of heavy metals on aquatic environment. Int J Biol Chem Sci 4(4):939–952

    Google Scholar 

  • Kevin RC, William B III, William DW, Scott RR (1998) Occurrence of male-specific bacteriophage in feral and domestic animal wastes, human feces, and human-associated wastewaters. American Society for Microbiology, Washington, D.C.

    Google Scholar 

  • Li P, Wu J, Hui Q (2012) Groundwater quality assessment based on rough sets attribute reduction and TOPSIS method in a semi-arid area, China. Environ Monit Assess 184:4841–4854

    Article  Google Scholar 

  • Li R, Zou Z, An Y (2016) Water quality assessment in Qu River based on fuzzy water pollution index method. J Environ Sci:1–6

  • MATLAB Documentation (2013). MathWorks R2013a. https://www.mathworks.com/help/index.html?s_tid=CRUX_lftnav

  • Martz LW, Garbrecht J (1999) An outlet breaching algorithm for the treatment of closed depressions in a raster DEM. Comput Geosci 25(7):835–844

    Article  Google Scholar 

  • Monarca S, Donato F, Zerbini I, Calderon RL, Craun GF (2006) Review of epidemiological studies on drinking water hardness and cardiovascular diseases. Euro J Cardio Pre Rehab 13(4):496–506

    Google Scholar 

  • Montgomery HAC, Thom NS, Cockburn A (1964) Determination of dissolved oxygen by the winkler method and the solubility of oxygen in pure water and sea water. J Appl Chem 14(7):280–296

    Article  Google Scholar 

  • Nair HC, Padmalal D, Joseph A, Vinod PG (2017) Delineation of groundwater potential zones in river basins using geospatial tools—an example from southern western Ghats, Kerala, India. J Geovis Spat Anal:1–16

  • Nigerian Industrial Standard (NIS-554) (2015) Nigerian standard for drinking water quality, pp 1721

  • Ocampo-Duque W, Juraske R, Kumar V, Nadal M, Domingo JL., Schuhmacher MA (2012) Concurrent neuro-fuzzy inference system for screening the ecological risk in rivers. Environ Sci. Pollut. Res (19): 983–999

  • Ocampo-Duque W, Osorio C, Piamba C, Schuhmacher M, Domingo JL (2013) Water quality analysis in rivers with non-parametric probability distributions and fuzzy inference systems: Application to the Cauca River, Colombia. Environ Int 52:17–28

    Article  Google Scholar 

  • Odiyo JO, Phangisa JI, Makungo R (2012) Rainfall–runoff modelling for estimating Latonyanda River flow contributions to Luvuvhu River downstream of Albasini Dam. Phys Chem Earth 50–52:5–13

    Article  Google Scholar 

  • Okpoli CC (2013) Application of 2D electrical resistivity tomography in landfill site: a case study of Iku, Ikare Akoko, Southwestern Nigeria. J Geo Res 2013

  • Olabode OF (2019) Potential groundwater recharge sites mapping in a typical basement terrain: a GIS methodology approach. J Geovisual Spatial Anal 3(1):5

    Article  Google Scholar 

  • Oladimeji MO, Abata E, Dawodu MO, Ipeaiyeda AR (2009) Effect of refuse dumps on the physicochemical chemical properties of surface water, Ondo state, Nigeria. Toxicol Environ Chem:1–11

  • Pringle CM, Scatena FN, Paaby-Hanson P, Nuenz Ferrera M (2000) River conservation in Latin America and Carribbean, pp 44–77

  • Qiu W (2002) Management decision and applied entropy. China Machine Press, Beijing, pp 193–196

    Google Scholar 

  • Qiu ML, Liu LH, Zou XW, Wu LX (2013) Comparison of water quality evaluation standards and evaluation methods between at home and abroad. J China Inst Water Resour Hydropower 403 Res 11(3):176–182

    Google Scholar 

  • Ramakrishnaiah CR, Sadashivaiah C, Ranganna G (2009) Assessment of water quality index for groundwater in Tumkur Taluk, Karnataka State, India. E-J Chem 6(2):523–530

    Article  Google Scholar 

  • Ross T (2004) Fuzzy logic with engineering applications. Wiley, New York

    Google Scholar 

  • Sharma P, Meher PK, Kumar A, Gautam PY, Mishra KP (2014) Changes in water quality index of Ganges river at different locations in Allahabad. Sustain Water Qual Eco:1–23

  • Shi JP, Li X, Wang W (2012) Study on space–time variety of water environment quality based on gray relational model. Guangdong Agric Sci 39(4):111–117

    Google Scholar 

  • Shrestha S, Kazama F (2006) Assessment of surface water quality using multivariate statistical techniques: a case study of the Fuji River basin, Japan. Environ Model Softw 22:464–475

    Article  Google Scholar 

  • Tian R, Wu J (2019) Groundwater quality appraisal by improved set pair analysis with game theory weightage and health risk estimation of contaminants for Xuecha drinking water source in a loess area in Northwest China. Human Ecolog Risk Assess: An Internatl J 25(1–2):132–157

  • Taiwo AM, Olujimi OO, Bamgbose O, Arowolo TA (2012) In: Voudouris (ed) ISBN: 978-953-51-0486-5Surface water quality monitoring in Nigeria: situational analysis and future management strategy, water quailty monitoring and assessment. InTech, London

    Google Scholar 

  • Vadiati M, Asghari-Moghaddam A, Nakhaei M, Adamowski J, Akbarzadeh AH (2016) A fuzzy-logic based decision-making approach for identification of groundwater quality based on groundwater quality indices. J Environ Manag 1-16

  • WHO (2006a) Guidelines for drinking-water quality. World Health Organization incorporating first addendum, vol 1, 3rd edn, pp 1–25

  • WHO (2006b) Hardness in drinking-water (background document for development of WHO Guidelines for drinking-water quality). Guidelines for drinking-water quality, 2nd edn, vol 2, WHO/SDE/WSH/03.04/06

  • Yan H, Zou Z, Wang H (2010) Adaptive neuro fuzzy inference system for classification of water quality status. J Environ Sci 22(12):1891–1896

    Article  Google Scholar 

  • Yi W, Yu Q (2003) Discussion about water quality evaluation index method in drinking water source. Environ Monit China 19(5):43–47

    Google Scholar 

  • Yusuff AS, John W, Oloruntoba AC (2014) Review on prevalence of waterborne diseases in Nigeria. J Adv Med Life Sci 1:1–3

    Google Scholar 

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

    Article  Google Scholar 

Download references

Acknowledgements

We are grateful to Adediran Kehinde for helping with the microbial analysis of this work. We are grateful to the entire community of Ikare-Akoko for granting us the permission to carry out this research on their waters. Also, candid appreciation goes to Morgan Johnson for providing moral support for the lead author.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Adedeji A. Adelodun.

Ethics declarations

This article does not contain any studies involving humans or animals performed by any of the authors.

Conflict of Interest

The authors declare that they have no conflicts of interest.

Ethical Approval

This article does not contain any studies with animals or humans by any of the authors.

Informed Consent

Informed consent was obtained from all parties (local authorities) included in the study.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Oladipo, J.O., Aboyeji, O.S., Akinwumiju, A.S. et al. Fuzzy Logic Interference for Characterization of Surface Water Potability in Ikare Rural Community, Nigeria. J geovis spat anal 4, 1 (2020). https://doi.org/10.1007/s41651-019-0044-z

Download citation

  • Published:

  • DOI: https://doi.org/10.1007/s41651-019-0044-z

Keywords

Navigation