Groundwater vulnerability assessment in semi-arid regions using GIS-based DRASTIC models and FUZZY AHP: South Chott Hodna
Lakhdar Seraiche, Mostafa Dougha, Messaoud Ghodbane, Tahar Selmane, Ahmed Ferhati, Djamal Eddine Djemiat

TL;DR
This study enhances groundwater vulnerability assessment in semi-arid regions by integrating land-use data and advanced weighting techniques into GIS-based DRASTIC models, significantly improving accuracy and decision-making.
Contribution
It introduces a hybrid framework combining DRASTIC with AHP and Fuzzy AHP, reducing subjectivity and better capturing anthropogenic effects in vulnerability mapping.
Findings
Fuzzy AHP DRASTIC_LU achieved the highest AUC of 0.951.
Agricultural areas above alluvial aquifers are most vulnerable.
Model accuracy improved with advanced weighting techniques.
Abstract
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…
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Taxonomy
TopicsGroundwater and Isotope Geochemistry · Groundwater and Watershed Analysis · Soil Geostatistics and Mapping
