Assessment of groundwater vulnerability based on the modified DRASTIC model: A case study in Baicheng City, China

Abstract Accurate assessment of groundwater vulnerability objectively reflects an area’s potential for groundwater pollution and provides a reference basis for pollution control and prevention. The main objective of this study was to modify the original DRASTIC model to improve the consistency of groundwater vulnerability assessment results with regard to the actual conditions of the study area. To optimize the assessment objectivity, two additional factors that are influenced by human activities (land use and degree of groundwater extraction) were added to form the DRASTICLE model. Then, based on the correlation between all factors and measured nitrate concentrations, the improved three-scale analytic hierarchy process (AHP) and the weights of evidence (WOE) methods were used to reassign the factor weights of the original DRASTIC model. The area under the receiver operating characteristic (ROC) curve, denoted as AUC, was used to quantitatively evaluate the accuracy of all five models (original DRASTIC model AUC: 0.62). By modifying the factors and weights, the four new models showed better performance, AUC values were 0.75, 0.76, 0.85, and 0.78 for the AHP-DRASTIC, AHP-DRASTICLE, WOE-DRASTIC, and WOE-DRASTICLE models, respectively. This indicates that the modified models could more accurately convey groundwater vulnerability in the study area. The WOE-DRASTIC model, which had the best performance, was then used to assess groundwater vulnerability in 2000 and 2010. In 2000, 2010, and 2018, the proportion of areas with very high groundwater vulnerability increased from 5.14–6.34% to 7.93%, respectively. Meanwhile, the proportion of areas with very low vulnerability also increased, from 72.63–75.07% to 81.60%; demonstrating a situation of extremes. Findings of this study are expected to provide a new theoretical basis for the Baicheng municipal government in China to better manage and exploit groundwater resources.