Identification of potential managed aquifer recharge sites in hyper-arid environment using GIS and analytical hierarchy process

Abstract Utilizing aquifers as groundwater storage reservoirs is an effective strategy for water management in water scare regions. The success of managed aquifer recharge (MAR) relies on the assessment and modeling of site-specific hydrogeological characteristics, including groundwater salinity, transmissivity, storativity, slope, soil properties, proximity to water recharge networks and road accessibility, etc. This study employs a GIS-based multi-criteria evaluation technique, integrating both ground and remote sensing datasets. The results indicate that a significant portion of the total land area, approximately 7,414.11 km 2 (64%), can potentially be utilized for MAR practices, while the remaining 36% is restricted due to various constraints, such as built-up areas, roads, agricultural lands and nationally protected areas for conservation. The available 64% of land is further categorized into subclasses ranging from highly suitable to least suitable areas. Most of the highly and moderately suitable regions are located in the northern central parts of the country where seasonal surplus treated wastewater and desalinated water may be used to recharge groundwater. Furthermore, MAR technology can also be used to tackle saltwater intrusion in the coastal areas by injecting seasonal surplus desalinated and treated wastewater. These findings suggest that MAR technology has a high potential to facilitate aquifer water storage and recovery in the country, which can contribute to sustainable water resources.

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Institutions

Publication Details

Journal
Applied Water Science
Published
2025-04-18
DOI
https://doi.org/10.1007/s13201-025-02431-3
Citations
7
Primary Topic
Groundwater and Watershed Analysis
Type
article
Field-Weighted Citation Impact
5.59

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article

Identification of potential managed aquifer recharge sites in hyper-arid environment using GIS and analytical hierarchy process

Mohammad Mahdi Rajabi, Chefi Triki, Slim Zekri, Ali K. Al-Maktoumi et al.
7 citations
Applied Water Science
Groundwater and Watershed Analysis
5.59
article

Identification of potential managed aquifer recharge sites in hyper-arid environment using GIS and analytical hierarchy process

Mohammad Mahdi Rajabi, Chefi Triki, Slim Zekri, Ali K. Al-Maktoumi, Rajesh Govindan, Hazrat Bilal, Wiem Harrathi
article en
7 citations

Abstract

Abstract Utilizing aquifers as groundwater storage reservoirs is an effective strategy for water management in water scare regions. The success of managed aquifer recharge (MAR) relies on the assessment and modeling of site-specific hydrogeological characteristics, including groundwater salinity, transmissivity, storativity, slope, soil properties, proximity to water recharge networks and road accessibility, etc. This study employs a GIS-based multi-criteria evaluation technique, integrating both ground and remote sensing datasets. The results indicate that a significant portion of the total land area, approximately 7,414.11 km 2 (64%), can potentially be utilized for MAR practices, while the remaining 36% is restricted due to various constraints, such as built-up areas, roads, agricultural lands and nationally protected areas for conservation. The available 64% of land is further categorized into subclasses ranging from highly suitable to least suitable areas. Most of the highly and moderately suitable regions are located in the northern central parts of the country where seasonal surplus treated wastewater and desalinated water may be used to recharge groundwater. Furthermore, MAR technology can also be used to tackle saltwater intrusion in the coastal areas by injecting seasonal surplus desalinated and treated wastewater. These findings suggest that MAR technology has a high potential to facilitate aquifer water storage and recovery in the country, which can contribute to sustainable water resources.

Applied Water ScienceVol. 15(5)
Tarbiat Modares University (IR), University of Kent (GB), Hamad bin Khalifa University (QA), Sultan Qaboos University (OM), Qatar Foundation (QA)
Qatar Foundation, Hamad Bin Khalifa University, Khalifa University of Science, Technology and Research, Qatar National Research Fund, Qatar National Library
Openalex Percentile: Top 4%
Groundwater and Watershed Analysis
5.59
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