Identifying the Susceptible Area of Malikan Plain Aquifer to contamination using Fuzzy Methods

Lack of proper recognition about the susceptible area to contamination in aquifers, may cause the contamination in these resources, and it may happen that these resources cannot be used. Groundwater resources in the Malikan region strongly affected by nitrate fertilizers leachates, due to the presence of grape gardens and intensive agriculture. So in this area, identifying the vulnerable area with the proper method is very important. In this study, Improved DRASTIC methods using fuzzy logic and catastrophe theory were used to vulnerability assessment of Malikan plain aquifer. For optimization, DRASTIC parameters which including seven hydrogeological parameters and the value of the vulnerability index respectively are defined as the input and output of the models. Validation of the models was performed using nitrate concentration data and correlation coefficient with the vulnerability index in the region. The results of models showed that the improved DRASTIC model using catastrophe theory with higher correlation index (CI) with nitrate concentration has provided a better result than the fuzzy logic for the aquifer vulnerability assessments. Based on catastrophe theory, the 56, 23, 21% of aquifer respectively located in low, medium and high vulnerability area, and central parts of plain was identified as a high vulnerable zones.