Groundwater quality assessment for drinking water using fuzzy inference model (case study: Marvdasht Plain)

Document Type : Research Article


1 Assistant Professor, Faculty of New Sciences & Technologies, University of Tehran

2 null


According to the capabilities of fuzzy method and its applications in a variety of engineering problems and decision-making under uncertainty, in this study, we compared the conventional methods is definitive and Mamdani fuzzy inference model. In this study, data from 30 deep and semi-deep wells in the year 1390 _ 1389 to assess the water quality of drinking plain water is used. And design a Fuzzy Inference System using membership functions and combines these functions according to the rules "if-then" fuzzy final quality of drinking water is determined. And later extended to the fuzzy and deterministic values, zoning groundwater quality index showed. The largest area dedicated to unacceptable quality for fuzzy inference method and 50.83 percent to 51.45 percent, is the definitive method. The desirable category in the definitive method and fuzzy 28.76 and 26.85 percent respectively and floor acceptable in certain ways and fuzzy, respectively, 19.79, 22.32 percent respectively. Fuzzy inference can be drawn that a suitable alternative method for assessing water quality associated with the uncertainty that has been taken into account.


Main Subjects

[1]. Rahbar., A., Estimation of Hydrological Parameters of Enclosed Aquifers with Fuller Methods of Cooper Jacob and Fuzzy Linear Regressions Modified, Master's Degree at Tehran Teacher Training University,2008, [Persian].
[2]. Zamani, oh And r Mahmoudi A Survey on Application of Synthetic Earth-Amar and Optimized Synthetic Neural Network Using Genetic Algorithm for Groundwater Leveling, MSc., Shahid Chamran University of Ahvaz,2012; 122 p, [Persian].
[3]. Kia, M.,. Fuzzy logic in MATLAB. Kian Publication Green, 2010, 240 p, [Persian].
[4]. Hashemi, A., F, Taheri, M. And Ghareh Chay, AS, Quality assessment of 9 cities of Isfahan province for drinking using fuzzy inference system, Journal of Iranian Water Resources Research, No.2010, Volume 6, pp. 25-34, [Persian].
[5]. Akgun, A., Sezer, E.A., Nefeslioglu, H.A., Gokceoglu, C., and Pradhan, B. An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm. Computers & Geosciences, Article in press, 2011.
[6]. Lindang, Herman Umbau. "Assessing water quality index in river basin: Fuzzy inference system approach.", 2017, pp. 27-31.
[7]. Leelavathy, K. R., V. Nirmala, and V. Nageshwaran. "RIVER WATER QUALITY ANALYSIS BY FUZZY APPROACH-A CASE STUDY OF CHUNNAMBAR RIVER PONDICHERRY." Int J Adv Engg Tech/Vol. VII/Issue II/April-June, 2016, pp. 955-958.
[8]. Kung, H.T. Ying, L.G. and Liu, Y.C. “A complementary tool to WQI: Fuzzy clustering analysis.”J. of Water Resources Bulletin,1992, Volume 28(2), pp. 525-533.
[9]. Sii, H.I. Sherreard, J.H. and Wilson, T.E. “A water quality index based on fuzzy sets theory.” Proc.of the 1993 Joint ASCE-CSCE National Conference on Environmental Engineering, Montreal, Quebec,Canada, 1993, pp. 253-259.
[10].            Ocampo-Duque, W. Ferre-Huguet, N. Domingo, J.L. and Schuhmacher, M. “Assessing water quality in rivers with fuzzy inference systems: A case study.” J. of Environment International,2006, Volume 32, pp. 733-742.
[11].            Nakhaei, M. Vadie, m. Application of Fuzzy Inference Model for Assessing the Quality of Aquatic Water for Drinking and Agricultural Use (Case Study: Tehran Province). Advanced Journal of Advanced Geology, 2012, Volume 3, pp. 18-31. [Persian].
[12].            Muhammetoglu A, Yardimci A, A Fuzzy Logic Approach to Assess Groundwater Pollution Levels Below Agricultural Fields. Environmental Monitoring and Assessment. 2006, Volume 118, pp. 337-354.
[13].            Dahiya, S. B., Singh, S., Gaur, V., Garg, K., and Kushwaha, H. S.,Analysis of Groundwater Quality Using Fuzzy Synthetic Evaluation, Journal of Hazardous Material, 2007, Volume 147, pp. 938-946.
[14].            Monjezi, M. and Rezaei, M. Developing a new fuzzy model to predict burden from rock geomechanical properties. Expert Systems with Applications.2011, Volume 38, pp. 9266-9273. [Persian].
[15].            Dindarlo, K., Farshidfar, Gh. Chemical quality of drinking water in Bandarabbas city. Hormozgan Medical Journal. 2006, Volume 10 (1), pp. 57-65.
[16].            Isaaks E. H., and Srinivasta R. M. Applied Geostatistics. Oxford University Press:Oxford, 1989.
[17].            Nasseri.M. Tajrishy.M. Mohammad reza Nikoo. Jamal Zaherpour Recognition and Spatial Mapping of Multivariate Groundwater Quality Index using Combined Fuzzy Method. Water and Wastewater. 2011, pp. 22- 36. [Persian].
[18].            Hassani Gh, Mahvi A.H, Nasseri S, Arabalibeik H, Yunesian M,Gharibi H.Designing Fuzzy-Based Ground Water Quality Index. Ardabil Health Journal. 2012, pp. 18-31. [Persian].
Volume 5, Issue 2
July 2018
Pages 663-673
  • Receive Date: 22 July 2017
  • Revise Date: 07 April 2018
  • Accept Date: 04 January 2018
  • First Publish Date: 22 June 2018
  • Publish Date: 22 June 2018