Modification and optimization of DRASTIC model using the salinity factor for vulnerability assessment of SARKHON plain aquifer

One of the important indicators of the quality status of groundwater is electrical conductivity. Increase in electrical conductivity reduces water and soil quality and as a result agriculture product. Vulnerability is arrival inclination or probability of pollutant to a certain place of aquifer after producing in earth surface. Vulnerability assessment as a suitable method is very important in managerial decisions. In this study among the popular models, DRASTIC model was used due to its power in combining effective hydrologic and hydro-geological parameters on transfer or lack of transfer of pollution.. Salinity is assumed as one of the important and effective factors on water quality which is weighted and rated as pollution index. It is also used as one of the required layers for drawing modified drastic index map. Fuzzy logic system as a more realistic ranking comparison of overlap-index methods (Bolin logic) offers a suitable method to solve problems related to the high levels of boundary classified returns. Hence, fuzzy logic was used to refine and modify ranking quantity parameters of DRASTIC model and EC factor. Results of the simulation of DRASTIC model with using artificial neural network showed high correlation of artificial neural network' output and modified DRASTIC model index.