Skip to main content
Log in

Aquifer vulnerability assessment using GIS and fuzzy system: a case study in Tehran–Karaj aquifer, Iran

  • Original Article
  • Published:
Environmental Geology

Abstract

Aquifer vulnerability assessment techniques have been developed to predict which areas are more likely than others to become contaminated as a result of activities at or near the land surface. This research focuses on the evaluation of groundwater vulnerability to pollution in an urban area. Among several assessment methods, DRASTIC has been selected for this study. ArcGIS has been used to overlay and calculate different layers and obtain the vulnerability map. In order to show the importance of fuzzy algorithms in classification, both Boolean and fuzzy algorithms were used and compared. The fuzzy algorithm could recognize the areas with low and negligible vulnerability potentials whereas the Boolean model classified them as moderate. Two sensitivity tests, the map removal sensitivity analyses and single-parameter sensitivity analysis, were performed to show the importance of each parameter in the index calculation.

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

Access this article

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
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  • Aller L, Bennet T, Lehr JH, Petty RJ, Hackett G (1987) DRASTIC: a standardized system for evaluating groundwater pollution potential using hydrogeological settings. EPA/600/2–87/035. US Environmental Protection Agency, USA

  • Al-Zabet T (2002) Evaluation of aquifer vulnerability to contamination potential using the DRASTIC method. Environ Geol 43:203–208

    Article  Google Scholar 

  • Babiker IS, Mohamed MAA, Hiyama T, Kato K (2005) A GIS-based DRASTIC model for assessing aquifer vulnerability in Kakamigahara Heights, Gifu Prefecture, Central Japan. Sci Total Environ 345:127–140

    Article  Google Scholar 

  • Barber C, Bates LE, Barron R, Allison H (1993) Assessment of the relative vulnerability of groundwater to pollution: a review and background paper for the conference workshop on vulnerability assessment. J Aust Geol Geophys 14:1147–1154

    Google Scholar 

  • Chen WP, Lee CH (2003) Estimation groundwater recharge from streamflow records. J Environ Geol 44:257–265

    Article  Google Scholar 

  • Cox E (1999) The fuzzy systems handbook: a practitioner’s guide to building, using, and maintaining fuzzy systems. AP Professional, San Diego

    Google Scholar 

  • Di Martino F, Sessa S, Loia V (2004) A fuzzy-based tool for modelization and analysis of the vulnerability of aquifers: a case study. Int J Approx Reason 38:99–111

    Article  Google Scholar 

  • Dixon B, Scott HD, Steele KF, Dixon JC (2002) Prediction of aquifer vulnerability to pesticides using fuzzy rule-based models at the regional scale. Phys Geogr 23:130–153

    Article  Google Scholar 

  • Hashimoto T, Stedinger JR, Loucks DP (1982) Reliability, resiliency, and vulnerability criteria for water resources system performance evaluation. Water Resour Res 18:14–20

    Article  Google Scholar 

  • Kasabov NK (1996) Foundations of neural networks, fuzzy systems, and knowledge engineering. MIT Press, Cambridge

    Google Scholar 

  • Lee S, Choi S (1997) Groundwater pollution susceptibility assessment of Younggwang area using GIS technique (in Korean). J Korean Soc Groundw Environ 4:223–230

    Google Scholar 

  • Lodwick WA, Monson W, Svoboda L (1990) Attribute error and sensitivity analysis of map operations in geographical information systems: suitability analysis. Int J Geogr Inf Syst 4:413–428

    Article  Google Scholar 

  • Lynch SD, Reynders AG, Schulze RE (1997) A DRASTIC approach to groundwater vulnerability in South Africa. South African J Sci 93:59–60

    Google Scholar 

  • Merchant JW (1994) GIS-based groundwater pollution hazard assessment: a critical review of the DRASTIC model. Photogramm Eng Remote Sens 60:1117–1127

    Google Scholar 

  • Napolitano P, Fabbri AG (1996) Single-parameter sensitivity analysis for aquifer vulnerability assessment using DRASTIC and SINTACS. IAHS Conference: HydroGIS96, Vienna, pp 559–566

  • Plymale CL, Angle MP (2002) Groundwater pollution potential of Fulton County, Ohio. Report No. 45. Ohio Department of Natural Resources, Water Resources Section

  • Silvert W (1997) Ecological impact classification with fuzzy sets. Ecol Modell 96:1–10

    Article  Google Scholar 

  • Wright KA, Xu Y (2000) A water balance approach to the sustainable management of groundwater in South Africa. J Water SA 26:167–170

    Google Scholar 

  • Yuan-Yuan M, Xue-gang Z, Lian-Sheng W (2006) Fuzzy pattern recognition method for assessing groundwater vulnerability to pollution in the Zhangji area. J Zhejiang Univ 7:1917–1922

    Article  Google Scholar 

  • Zadeh LT (1965) Fuzzy sets. Inform. Control 8:338–353

    Article  Google Scholar 

Download references

Acknowledgments

The authors would like to thank the Research Department of the Ministry of Energy of Iran for financial support of this research.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kourosh Mohammadi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Mohammadi, K., Niknam, R. & Majd, V.J. Aquifer vulnerability assessment using GIS and fuzzy system: a case study in Tehran–Karaj aquifer, Iran. Environ Geol 58, 437–446 (2009). https://doi.org/10.1007/s00254-008-1514-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00254-008-1514-7

Keywords

Navigation