Comparison of Geostatistical and Hierarchical Methods in Investigating the Quality of Groundwater in the Moghan Plain in Terms of Drinking Uses

Document Type : Research paper

Author

Department of Agricultural Engineering and Technology, Moghan College of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran.

Abstract

Groundwater resources play a critical role in supplying drinking water, particularly in arid and semi-arid regions. Therefore, accurate assessment of groundwater quality is essential for sustainable water resource management. In this study, groundwater quality in the Moghan Plain was evaluated and compared using the Water Quality Index (WQI), the Analytic Hierarchy Process (AHP), and geostatistical techniques within a Geographic Information System (GIS) framework. Water quality data from 29 exploitation wells, including pH, electrical conductivity (EC), total dissolved solids (TDS), total hardness (TH), calcium, magnesium, sodium, potassium, chloride, sulfate, bicarbonate, and nitrate, were analyzed. In the AHP approach, criterion weights were determined through pairwise comparisons and expert judgment, whereas geostatistical analysis was performed using variogram modeling and cokriging interpolation with electrical conductivity as an auxiliary variable. The results showed that the cokriging model with a coefficient of determination (R²) of 0.96 and a root mean square error (RMSE) of 0.2 was more accurate in estimating the WQI index than the hierarchical method with a coefficient of determination of 0.93 and a root mean square error of 0.3. The AHP results indicated that nitrate, total dissolved solids, and electrical conductivity were the most influential parameters affecting groundwater quality. Spatial distribution maps generated by both approaches revealed that the majority of the study area exhibited poor groundwater quality for drinking purposes, with more than 94% of the plain classified within the poor-quality category. Comparative analysis showed that while AHP is an effective tool for identifying the relative importance of water quality parameters, geostatistical methods provide more accurate spatial predictions due to their ability to account for spatial dependence and estimation uncertainty. Therefore, the integration of multi-criteria decision-making techniques and geostatistical approaches is recommended for groundwater quality assessment and management.

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References

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Hydrogeology
Volume 10, Issue 2
May 2026
Pages 22-43

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