Application of DWQI for comprehensive evaluation of drinking water quality

Document Type : Research Article


1 MSc Student, Department of Geology, Urmia University, Urmia, Iran

2 Assistant Professor, Department of Soil Science, Urmia University, Urmia, Iran

3 Associate Professor, Department of Geology, Urmia University, Urmia, Iran


Water quality is considered as one of the most important factors in development of the civilizations and sustainability of human activities. Water quality can be evaluated by comparing each of the chemical properties in water samples with their reference values. The single parameter comparison method is characterized by some limitations and a comprehensive evaluation of  water quality is not possible using this method. Thus, water quality indices have been developed during the last 3 decades. The aim of this study was to comprehensively evaluate the water quality in Ardabil aquifer with a newly proposed drinking water quality index (DWQIProposed). The DWQIProposed  was also compared with the conventional water quality indices including DWQIA and DWQIG. Water samples were collected from 60 wells in Ardabil aquifer during the September 2014 and analyzed for 21 different physical, chemical, and biological properties. DWQIProposed were computed in four steps including parameter selection, parameter categorization, development of sub-index with regression statistics, and aggregation of the sub indices. Based on the obtained results, although there was a quantitative difference between the DWQIProposed and DWQIG, their probability distribution functions reflect a similar pattern. DWQIProposed and DWQIA have similar values for samples with excellent water quality. ANOVA results indicated that the mean difference between three indices is significant (P<0.05) but there was a high correlation between these three indices (r=0.98-0.99, P<0.001). Among the health related properties, Nitrate has the highest correlation coefficient with water quality indices (r=0.712-0.815, P<0.001) which emphasizes the effect of nitrate on water quality at the region. Water quality indices are considered to have strong spatial dependence and their kriging maps clearly showed the declining trend in water quality when moved from north-eastern parts of the region to the south-western parts.


Main Subjects

  1. منابع

    1. Khadam IM, Kaluarachchi JJ. Water quality modeling under hydrologic variability and parameter uncertainty using erosion-scaled export coefficients. Journal of Hydrology. 200; 330(1):354-67.
    2. Ramesh S, Sukumaran N, Murugesan AG, Rajan MP. An innovative approach of drinking water quality index- A case study from Southern Tamil Nadu, India. Ecological Indicators. 2010; 10(4):857-68.
    3. Cude CG. Oregon water quality index a tool for evaluating water quality management effectiveness1. Journal of American Water Resource Association. 2001; 37(1): 125-137.
    4. Horton RK. An index number system for rating water quality. Journal of the Water Pollution Control Federation. 1965; 37(3): 300–306.
    5. Ott WR. Water Quality Indices: A Survey of Indices used in the United States. US EPA Office of Research and Development, Washington, DC, 1978; p. 128
    6. Nasirian M. A new water quality index for environmental contamination contributed by mineral processing: A case study of Amang (Tin Tailing) processing activity. Journal of applied sciences. 2007; 7(20): 2977-2987.
    7. Kannel PR, Lee S, Lee YS, Kanel SR, KhanSP. Application of water quality indices and dissolved oxygen as indicators for river water classification and urban impact assessment. Environmental Monitoring and Assessment. 2007; 132(1-3): 93-110.
    8. Sargaonkar A, Deshpande V. Development of an overall index of pollution for surface water based on a general classification scheme in Indian context. Environmental monitoring and assessment. 2003; 89(1): 43-67.
    9. Singh RP, Nath S, Prasad SC, Nema AK. Selection of suitable aggregation function for estimation of aggregate pollution index for River Ganges in India. Journal of environmental Engineering. 2008; 134(8):689-701.

    10. Nagels JW, Davies-Colley RJ, Smith DG. A water quality index for contact recreation in New Zealand. Water Science and Technology. 2001; 43(5): 285-292.

    11. Liou SM, Lo SL, Wang SH. A generalized water quality index for Taiwan. Environmental Monitoring and Assessment. 2004; 96(1-3): 35-52.

    12. Ocampo-Duque W, Ferré-Huguet N, Domingo JL, Schuhmacher M. Assessing water quality in rivers with fuzzy inference systems: A case study. Environment International. 2006; 32(6): 733-742.

    13. World Health Organization. Guidelines For Drinking Water Quality. second addendum. Vol. 1, Recommendations. 3rd ed. ISBN 978 92 4 154760 4. 2008; World Health Organization.

    14. Institute of Standards and Industrial Research of Iran. Drinking water - Physical and chemical specifications.ISIRI, 1053. 2008; 5th Revision.

    15. Devi R, Alemayehu E, Singh V, Kumar A. Removal of fluoride, arsenic and coliform bacteria by modified homemade filter media from drinking water.Bioresource Technology. 2008; 99: 2269-2274.

    16. Gupta AK, Gupta SK, Patil RS. A comparison of water quality indices for coastal water. Journal of Environmental Science and Health, Part A. 2003; 38(11): 2711-2725.

    17. Gulis G, Czompolyova M, Cerhan J R. An ecologic study of nitrate in municipal drinking water and cancer incidence in TrnavaDistrict, Slovakia. Environmental research. 2002; 88(3): 182-187.

    18. Yazdanbod E, Samadi F, Malekzade R, Babaie M, Iranparvar M, Azami A. Four-Year Survival Rate of Patients with Upper GI Cancer in Ardabil. Journal of Ardabil University of Medical Sciences. 2005; 5 (2):180-184.

    19. Bødtker G,Thorstenson T, Lillebø BLP, Thorbjørnsen, BE, Ulvøen RH, Sunde E, TorsvikT. The effect of long-term nitrate treatment on SRB activity, corrosion rate and bacterial community composition in offshore water injection systems. Journal of industrial microbiology & biotechnology. 2008; 35(12): 1625-1636.

    20. Cambardella CA, MoormanAT, Novak JM, ParkinTB, Karlen DL, Turco RF. Field-scale variability of soil properties in central Iowa soils. Soil Science Society of America Journal. 1994; 58:1501–1511

    21. Fu W, Zhao K, Zhang C, Wu J, Tunney H. Outlier identification of soil phosphorus and its implication for spatial structure modeling. Precision Agriculture. 2016; 17(2): 121-135

Volume 4, Issue 2
June 2017
Pages 421-436
  • Receive Date: 18 December 2016
  • Revise Date: 19 January 2017
  • Accept Date: 19 January 2017
  • First Publish Date: 22 June 2017
  • Publish Date: 22 June 2017