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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2602.00023 |
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Table of Contents:
- Groundwater vulnerability is a major concern in arid regions worldwide, where population growth and intensive agriculture increase the risks of depletion and contamination. This study proposes a hybrid groundwater vulnerability assessment framework that improves the conventional DRASTIC model by integrating land-use data and applying advanced weighting techniques, namely the Analytical Hierarchy Process (AHP) and its fuzzy logic variant (Fuzzy AHP). This method makes expert-based weighting less subjective, better captures anthropogenic effects, and facilitates adaptation to challenging situations and limited data. Four vulnerability maps were produced using Geographic Information Systems (GIS): DRASTIC, DRASTIC_LU, AHP DRASTIC_LU, and Fuzzy AHP DRASTIC_LU. We used nitrate levels from 70 wells to verify our work. We found that agricultural areas, especially those above the alluvial aquifer, were the most vulnerable. The ROC curve analysis showed that the model improved over time, with the area under the curve (AUC) values of 0.812 for DRASTIC, 0.864 for DRASTIC_LU, 0.875 for AHP DRASTIC_LU, and 0.951 for fuzzy AHP DRASTIC_LU. These results show that fuzzy AHP DRASTIC_LU makes groundwater risk assessments much more. The GIS-based hybrid models offer a scalable and transferable method for mapping vulnerability, but they also provide local and regional water resource managers with useful information.