Rezaei, F., Safavi, H.R., Ahmadi, A. (2013). Groundwater vulnerability assessment using fuzzy logic: A case study in the Zayandehrood aquifers, Iran. Environmental Management, Vol;. 51,
Groundwater Vulnerability Assessment Using Fuzzy Logic: A Case Study in Zayandehrood Aquifers, Iran
Farshad Rezaei: M.Sc. of Water Resources, Dept. of Civil Engineering, Isfahan University of Technology, Isfahan, Iran.
Hamid R. Safavi: Associate Professor, Dept. of Civil Engineering, Isfahan University of Technology, Isfahan, Iran.
Azadeh Ahmadi: Assistant Professor, Dept. of Civil Engineering, Isfahan University of Technology, Isfahan, Iran.
Abstract Groundwater is considered as an important resource of water especially in arid and semi-arid regions where the surface water is scarce. Hence, contamination of groundwater has become a major concern in these regions. On the other hand, the control and also removal of pollution from groundwater resources are very difficult and expensive. So, the vulnerable zones must be detected and then must be prevented from being contaminated. One of the commonest methods in order to evaluate the groundwater contamination is DRASTIC method. In this method the Boolean logic is used to classify and rate the parameters involved in the method. But in order to eliminate some problems occurs in this method due to application of the Boolean logic, in this paper the fuzzy logic has been used and three critical cases of minimum, maximum and mean values have been considered for the net recharge parameter. This process has been performed on Zayandherood river basin aquifers. The provided fuzzy-DRASTIC vulnerability map indicated that generally the western areas have maximum pollution potential and then the areas located in the east have considerable pollution potential. But the central areas of the study area have too low pollution potential. Finally, two sensitivity analyses were performed to show the importance of each case of net recharge parameter in the vulnerability index calculation.
Keywords Groundwater, Vulnerability, Sensitivity analysis, DRASTIC method, Fuzzy logic