Improvement of GIS-Based DRASTIC Model Using Step-Wise Weight Assessment Ratio Analysis (SWARA) and Two New Hybrid Frameworks (Iran)

Finding a robust groundwater vulnerability assessment framework for accurate identification of sustainable zones may provide more efficient policies and plans. This study proposes two hybrid modification of DRASTIC model using brand-new Multi-Criteria Decision-Making (MCDM) method, i.e., Step-wise Weight Assessment Ratio Analysis (SWARA) for modifying the ranges of rating besides Entropy (Ent) and Genetic Algorithm (GA) methods for changing relative weights of DRASTIC parameters. The nitrate concentration obtained from 50 observation wells in the agricultural study area is employed to DRASTIC index improvement. The overall performance of the models is evaluated using the appropriate datasets of new nitrate observation wells and by employing of Receiver Operating Characteristic (ROC) curve and area under the ROC curve (AUC). The methodology is implemented in Qazvin aquifer Iran and the results illustrated the better performance of DRASTIC model after modifying as AUC value increases from 0.58 for generic DRASTIC to 0.68 and 0.74 for SWARA-Ent and SWARA-GA, respectively.