ABSTRACT
Groundwater plays a vital role in supporting water for the different needs of domestic, agricultural, and industrial sectors, and its vulnerability assessment to pollution is a valuable tool for establishing protective and preventive management. DRASTIC is a well-known GIS-based model for assessing groundwater vulnerability to pollution, which uses seven parameters including depth-to-water level, net recharge, aquifer media, soil media, topography, the impact of the vadose zone, and hydraulic conductivity. The predefined weights of DRASTIC parameters have made a barrier to its applicability for different regions with different hydroclimatic conditions. To overcome this problem, it has been suggested to apply analytic hierarchy process (AHP) method for modifying the model by adjusting the weights of the parameters. AHP is a widely used method to elicit experts' judgments about different involving parameters through constructing pairwise comparison matrixes (PCMs). Since AHP calculates the weights by performing pairwise comparisons between the parameters, achieving consistent comparisons is difficult when the number of parameters increases. The objective of this research is to modify the DRASTIC model by integrating the connecting path method (CPM) and AHP. The proposed methodology involves asking experts to perform a number of pairwise comparisons between the parameters and then construct an incomplete PCM using the obtained information. To complete the missing values in the PCM, CPM is employed. The CPM is an effective approach that not only estimates missing judgments but also ensures minimal geometric consistency. The proposed method along with DRASTIC and pesticide DRASTIC models is applied to Khoy County, which is located in the northwest part of Iran. The efficiency of the proposed method was further confirmed through the results of the Pearson coefficient test conducted on nitrate concentrations. The test revealed correlation values of 0.47, 0.27, and 0.57 for DRASTIC, pesticide DRASTIC, and modified DRASTIC, respectively. These results demonstrated that the proposed method provides a more precise evaluation of groundwater vulnerability.
