Evaluation of groundwater vulnerability to pollution using DRASTIC, composite DRASTIC, and nitrate vulnerability models

Background: Groundwater protection against pollution is a very important issue. Groundwater vulnerability maps are useful tools for protecting aquifers and assessing the potential for contamination. Therefore, the purpose of this study was to prepare vulnerability maps and perform sensitivity analysis to identify the most influential factors in the vulnerability of the studied aquifer. Methods: In this study, groundwater vulnerability to pollution was evaluated using DRASTIC, composite DRASTIC, and nitrate vulnerability (NV) models. Drastic is an index for the systematic assessment of potential groundwater pollution. In this method, the drastic index was calculated from the total weight and rank of the factors. For this purpose, first the factors affecting the pollution transfer, were weighted, ranked, and merged using GIS software. Then, using the overlapping techniques and after applying the necessary weight coefficients on each layer, a map of the vulnerability area of the study aquifer was prepared. Results: It was revealed that there is a significant linear relationship between all three models with the distribution of nitrate concentration. Accordingly, it was the most efficient NV model, followed by the composite DRASTIC (CD) and DRASTIC models, respectively. Also, in the studied aquifer, the DRASTIC index was between ۱۴۷ and ۱۳۶, the combined DRASTIC index was between ۷۰ and ۱۹۰, and the nitrate index was between ۱۳ and ۱۳۲. Conclusion: Vulnerability assessment of the studied aquifer using DRASTIC, and combined DRASTIC, and NV indices shows that, according to the DRASTIC index, ۶۹.۷% of the studied aquifer was in the medium vulnerability class. Also, according to the combined DRASTIC index, the largest area (۵۳.۶۲%) has low vulnerability and ۳۱.۵۶% has moderate vulnerability. But according to the nitrate index, ۷۷.۱۶% of the aquifers had very low vulnerability.

کلیدواژه ها:

Environmental pollution ، Groundwater ، Geographic information systems ، Soil ، Nitrate