Groundwater Vulnerability Assessment Using a GIS-Based DRASTIC Method in the Garmsar Aquifer, Iran

Derakhshan, Hamideh; Malekian, Arash; Khalighi Sigaroodi, Shahram

doi:10.22059/jrwm.2025.395437.1833

Groundwater Vulnerability Assessment Using a GIS-Based DRASTIC Method in the Garmsar Aquifer, Iran

Document Type : Research Paper

Authors

Hamideh Derakhshan

Arash Malekian

Shahram Khalighi Sigaroodi

Department of Arid and Mountainous Regions Reclamation, Faculty of Natural Resources, University of Tehran, Karaj, Iran

10.22059/jrwm.2025.395437.1833

Abstract

Groundwater resources are of great importance as a vital source of water supply in many regions of the world. Due to its geographical and climatic characteristics, Garmsar Plain is highly dependent on groundwater resources, especially in providing agricultural and drinking water. In this study, the DRASTIC model was used to assess the potential for qualitative vulnerability of groundwater resources in Garmsar Plain. This model uses seven main parameters including groundwater depth, net recharge, aquifer environment, soil environment, topography, Impact of vadose zone, and hydraulic conductivity to comprehensively analyze the quality vulnerability of groundwater resources. By integrating the seven benchmark maps used in the DRASTIC model in a GIS environment using the overlap index method, the final vulnerability index of the studied aquifer was calculated. Accordingly, the final drastic vulnerability index was between 54 and 145. About nine percent of the study area has no pollution potential, 39 percent has very low potential, 30 percent has low potential, 17 percent has low to medium potential, and five percent has medium to high vulnerability potential. Sensitivity analysis was also used to examine the results more closely and identify the more effective components on the vulnerability of groundwater resources. Based on the results of the model sensitivity analysis using the parameter elimination and single parameter methods, the vadose zone effect parameter showed the highest sensitivity in both methods.

Keywords

Groundwater

Overlap index

Pollution potential

Sensitivity Analysis

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