Optimizing the DRASTIC vulnerability approach to overcome the subjectivity: a case study from Shabestar plain, Iran

Abstract

Due to the seasonality of Shabestar plain rivers, most of the water demands for agricultural and drinking sectors are provided from groundwater. The existence of agricultural activities has expanded the use of chemical and animal fertilizers that are possible to infiltrate and contaminate the groundwater resources. The purpose of this study is to provide an optimized DRASTIC approach for assessing the vulnerability of the Shabestar plain aquifer located in East Azarbaijan Province, North West of Iran. The effective parameters in this method include the depth to groundwater, net recharge, aquifer media, soil media, impact of the vadose zone, topographic slope, and hydraulic conductivity, which are being provided in seven layers in the ArcGIS software environment. After ranking each of the input parameters and applying their equivalent weight coefficients, the DRASTIC vulnerability index for the study area ranged between 53.3 and 118.3. Nitrate concentration values at 66 water wells were used for the validation of the DRASTIC-based vulnerability maps. The r value between the DRASTIC indices and the concentration of nitrate is 0.38 indicating a low correlation. Sensitivity analysis results showed that the impact of the vadose zone and aquifer media is significant on the intrinsic vulnerability of the study area. The Wilcoxon rank-sum test (WRST) was used for rate modification. Also, the weights of the DRASTIC approach were optimized by using the ant colony optimization (ACO) and genetic algorithm (GA). All optimized models increased the r compared to the typical DRASTIC method. The results indicate that WRST and GA methods were most successful for optimization of the rates and weights, respectively, where the WRST-GA-DRASTIC model obtained an r of 0.63.