Rule-Based Fuzzy System for Assessing Groundwater Vulnerability
Publication: Journal of Environmental Engineering
Volume 133, Issue 5
Abstract
Parallel to industrial growth and ever increasing use of agrichemicals, environmental resources have been affected and deteriorated by generated pollutants. Groundwater, an important source of fresh water, has not been immune from contamination. Recognition of groundwater vulnerability to pollution will help in managing groundwater quality conflicts. The DRASTIC model (where D=depth to groundwater; R=net recharge; A=aquifer media; S=soil type; T=topography; I=impact of vadose zone; and C=hydraulic conductivity of the aquifer) has been used extensively for assessing the vulnerability of groundwater. It employs a linear combination of some intrinsic properties of aquifers to develop a vulnerability index. As there is no clear boundary for the set of vulnerable aquifers, groundwater vulnerability can be addressed through fuzzy set theory instead of classical set theory. In this study, benefiting from a fuzzy system and a conscious knowledge base, a regional-scale model is developed for groundwater vulnerability assessment that employs DRASTIC parameters. A comparison between the output of the fuzzy model and the DRASTIC index is accomplished. The ability of the fuzzy system to cope with the modeling of a nonlinear system and presentation of the output of the fuzzy system in the framework of a geographical information system are highlighted.
Get full access to this article
View all available purchase options and get full access to this article.
References
Aller, L., Bennet, T., Lehr, J. H., and Petty, R. J. (1987). “DRASTIC: A standardized system for evaluating groundwater pollution potential using hydrogeologic settings.” US EPA Rep. 600/2-85/018, U.S. Environmental Protection Agency, Washington, D.C.
Barber, C., Bates, L. E., Barron, R., and Allison, H. (1994). “Comparison of standardized and region-specific methods assessment of the vulnerability of groundwater to pollution: A case study in an agricultural catchment.” Proc., 25th IAH Congress Water Down Under, Melbourne, Australia, Vol. 1, 279–283.
Bardossy, A., and Duckstein, L. (1995). “Fuzzy rule-based modeling with application to geophysical, biological, and engineering systems.” CRC, Boca Raton, Fla.
Burkart, M. R., Kolpin, D., and James, E. (1999). “Assessing groundwater vulnerability to agrichemical contamination in the Midwest U.S.” Water Sci. Technol., 39(3), 103–124.
Dubrovin, T., Jolma, A., and Turunem, E. (2002). “Fuzzy model of real-time reservoir operation.” J. Water Resour. Plann. Manage., 128(1), 66–73.
Ebtehaj, M. (2002). “Rule-based fuzzy systems for assessing groundwater vulnerability.” MS thesis, Iran Univ. of Science and Technology, Tehran, Iran.
Lynch, S. D., Reyndeac, A. G., and Schulze, R. E. (1997). “A DRASTIC approach to groundwater vulnerability in South Africa.” S. Afr. J. Sci., 93, 59–65.
Russel, S. J., and Norvig, P. (1995). “Artificial intelligence: A modern approach.” Prentice-Hall, Englewood Cliffs, N.J.
Shouyu, C., and Guangtao, F. (2003). “A DRASTIC-based fuzzy pattern recognition methodology for groundwater vulnerability evaluation.” Hydrol. Sci. J., 48(2), 211–220.
Sotornikova, R., and Vrba, J. (1987). “Some remarks on the concept of vulnerability maps, in vulnerability of soil and ground water to pollution.” Proc., Int. Conf. on the Vulnerability of Soil and Groundwater to Pollutants, The Hague, The Netherlands, 471–476.
MATLAB. (1999). “Language of technical computing.” Fuzzy logic toolbox user’s guide, Mathworks, Natick, Mass.
National Research Council (NRC). (1993). Groundwater assessment; contamination potential under conditions of uncertainty, National Research Council, National Academy Press, Washington, D.C.
Villumsen, A., Jacobsen, O. S., and Sonderskov, C. (1982). “Mapping the vulnerability of groundwater reservoirs with regard to surface pollution.” Yearbook 1982, Geological Survey of Denmark, Copenhagen, Denmark, 17–38.
Wang, L. X. (1997). “A course in fuzzy systems and control.” Prentice-Hall, Upper Saddle River, N.J.
Zadeh, L. A. (1965). “Fuzzy sets.” J. Inf. Control, 8, 338–353.
Zhou, H. C., Wang, G. L., and Yang, Q. (1999). “A multiobjective fuzzy pattern recognition model for assessing ground water vulnerability based on the DRASTIC system.” Hydrol. Sci. J., 44(4), 611–618.
Information & Authors
Information
Published In
Copyright
© 2007 ASCE.
History
Received: Oct 28, 2005
Accepted: Jun 22, 2006
Published online: May 1, 2007
Published in print: May 2007
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.