A Hybrid Approach towards the Assessment of Groundwater Quality for Potability: A Fuzzy Logic and GIS Based Case Study of Tiruchirappalli City, India
Natarajan Venkat Kumar, Samson Mathew, Ganapathiram Swaminathan
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DOI: 10.4236/jgis.2010.23022   PDF    HTML     6,549 Downloads   11,677 Views   Citations

Abstract

The present study aims to develop a new hybrid Fuzzy Simulink model to assess the groundwater quality levels in Tiruchirappalli city, South India. Water quality management is an important issue in the modern times. The data collected for Tiruchirappalli city have been utilized to develop the approach. This is illustrated with seventy nine groundwater samples collected from Tiruchirappalli city Corporation, South India. The characteristics of the groundwater for this plain were monitored during the years 2006 and 2008. The quality of groundwater at several established stations within the plain were assessed using Fuzzy Logic (FL) and GIS maps. The results of the calculated FL and GIS maps with the monitoring study have yielded good agreement. Groundwater quality for potability indicated high to moderate water pollution levels at Srirangam, Ariyamangalam, Golden Rock and K. Abisekapurm zones of the study area, depending on factors such as depth to groundwater, constituents of groundwater and vulnerability of groundwater to pollution. Fuzzy logic simulation approach has shown to be a practical, simple and useful tool to assess groundwater quality assessment for potability. This approach is capable of showing and updating the water quality assessment for drinking.

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N. Kumar, S. Mathew and G. Swaminathan, "A Hybrid Approach towards the Assessment of Groundwater Quality for Potability: A Fuzzy Logic and GIS Based Case Study of Tiruchirappalli City, India," Journal of Geographic Information System, Vol. 2 No. 3, 2010, pp. 152-162. doi: 10.4236/jgis.2010.23022.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] R. D. Deshpande and S. K. Gupta, “Water for India in 2050: First Order Assessment of Available Options,” Current Science, Vol. 86, No. 9, 2004, pp. 12161224.
[2] Z. Chen, G. H. Huan and A. Chakma, “Hybrid Fuzzy Stochastic Modeling Approach for Assessing Environmental Risks at Contaminated Groundwater Systems,” Journal of Environmental Engineering, Vol. 129, No. 1, 2003, pp. 7988.
[3] C. O. Cude, “Water Quality Index: A Tool for Evaluation Water Quality Management Effectiveness,” Journal of the American Water Resources Association, Vol. 37, No. 1, 2001, pp. 125137.
[4] S. Dahyia, D. Datta and H. S. Kushwaha, “A Fuzzy Synthetic Evaluation Approach for Assessment of Physio Chemical Quality of Groundwater for Drinking Purp oses,” Environmental Geology, Vol. 8, No. 12, 2005, pp. 158165.
[5] S. M. Liou, S. L. Lo and S. H. Wang, “Generalized Water Quality Index for Taiwan,” Environmental Monitoring and Assessment, Vol. 96, No. 13, 2004, pp. 3552. http:// www.springerlink.com/content/t425516215118557/
[6] K. Sivasankar and R. Gomathi, “Fluoride and other Quality Parameters in the Groundwater Samples of Pettaivai thalai and Kulithalai Areas of Tamil Nadu, Southern India,” Water Quality Exposure Health, Vol. 1, 2009, pp. 123134.
[7] T. Subramani, L. Elango and S. R. Damodarasamy, “Groundwater Quality and its Suitability for Drinking and Agricultural Use in Chithar River Basin, Tamil Nadu, India,” Environmental Geology, Vol. 47, No. 8, 2005, pp. 10991110.
[8] N. V. Kumar, S. Mathew and G. Swaminathan, “Fuzzy Information Processing for Assessment of Groundwater Quality,” International Journal of Soft Computing, Vol. 4, No. 1, 2009, pp. 19. http://www.medwelljjournals.com/ fulltext/ijsc/2009/19.pdf
[9] American Public Health Association, “Standard Method for Examination of Water and Waste Water,” 21st Edition, American Public Health Association, Washington, D.C., 2005.
[10] Bureau of Indian Standard, “Indian Standard Specification for Drinking Water,” BIS Publication No. IS: 10501, New Delhi, 1991.
[11] World Health Organization, “Guidelines for Drinking Water Quality Recommendation,” 3rd Edition, World Health Organization, Geneva, Vol. 1, 2008.
[12] Z. Sen, “Fuzzy Groundwater Classification Rule Derivation from Quality Maps,” Water Quality Exposure Health, Vol. 1, No. 1, 2009, 115112.
[13] S. Liou and S. L. Lo, “A Fuzzy Index Model for Tropic Status Evolution of Reservoir Waters,” Water Research, Vol. 96, No. 1, 2004, 3552.
[14] N. Chang, H. W. Chen and S. K. King, “Identification of River Water Quality Using the Fuzzy Synthetic Evaluation Approach,” Journal of Environmental Management, Vol. 63, No. 3, November 2001, pp. 293305.
[15] L. Zadeh, “Knowledge Representation in Fuzzy Logic,” IEEE Transactions on Knowledge and Data Engineering, Vol. 1, No. 1, 1989, pp. 89100.
[16] M. F. Dahab, Y. W. Lee and I. Bogardi, “A Rule Based FuzzySet Approach to Risk Analysis of Nitrate Contami nated Groundwater,” Water Science and Technology, Vol. 30, No. 7, 1994, pp. 4552.
[17] K. Schulz and B. Howe, “Uncertainty and Sensitivity Analysis of Water Transport Modeling in a Layered Soil Profile Using Fuzzy Set Theory,” Journal of Hydro informatics, Vol. 1, No. 2, 1999, pp. 127138.
[18] E. M. Mamdani, “Advances in the Linguistic Synthesis of Fuzzy Controllers,” International Journal of ManMachine Studies, Vol. 8, No. 6, 1976, pp. 669678.
[19] N. V. Kumar, S. Mathew and G. Swaminathan, “A Preliminary Investigation for Groundwater Quality and Health Effects—A Case Study,” Asian Journal of Water, Environment and Pollution, Vol. 5, No. 4, 2008, pp. 99107.http://iospress.metapress.com/content/a11884502 w687x74/.

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