Document Type : Original Article
Authors
1
Department of Water resources research, Water research institute, Ministry of energy, Tehran, Iran.
2
Water Research Institute, Ministry of Energy, Tehran, Iran
3
Technical Studies and Engineering Assessment Office, Engineering and Development Deputy, National Water and Wastewater Engineering Company (NWWEC), Tehran, Iran
4
Department of Civil Engineering, Islamic Azad University, Tehran, Iran
5
Water Research Institute, Tehran, Iran
10.22077/jaaq.2026.11635.1149
Abstract
In this study, site selection and prioritization of suitable areas for artificial recharge in the Azghand aquifer were carried out using an integrated AHP–GIS approach and a numerical model. Eight influential criteria—including water quantity, water quality, hydraulic conductivity, land use, geological formations, slope, exploitation status, and proximity to groundwater resources—were selected and classified within the GIS environment. Criterion and sub‑class weights were determined using the Analytic Hierarchy Process, and the artificial recharge potential map was generated. Based on the site‑selection results, five candidate locations were identified for artificial recharge implementation. Subsequently, a numerical groundwater flow model of the Azghand aquifer was developed using MODFLOW. After calibration, the model was applied to evaluate the impact of each proposed site on groundwater levels. To compare the performance of the candidate sites, an aquifer improvement index was defined, representing the ratio of the average annual rise in groundwater level under artificial recharge conditions to the average annual decline under natural (no‑recharge) conditions. According to this index, Site 1 (2.24) ranked first, Site 4 (2.03) ranked second, and Sites 2, 3, and 5—with values of 1.64, 1.21, and 1.12, respectively—were placed in subsequent priority levels. The findings demonstrate that integrating AHP–GIS site selection with numerical modeling enables a transition from purely potential‑based zoning to effectiveness‑based prioritization.
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