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dc.contributor.authorEghbali Lord, Zahra
dc.contributor.authorRasoulzadeh, Ali
dc.contributor.authorAbedi, Armin
dc.contributor.authorAlikhani, Sharare
dc.contributor.authorFernández Gálvez, Jesús 
dc.date.accessioned2025-04-03T06:48:51Z
dc.date.available2025-04-03T06:48:51Z
dc.date.issued2025-04-02
dc.identifier.citationZ. Eghbali Lord et al. Integrating Geographic Information Systems and Multi-Criteria Decision Analysis for Evaluating Artificial Groundwater Recharge. Water Resour Manage (2025). https://doi.org/10.1007/s11269-025-04131-8es_ES
dc.identifier.urihttps://hdl.handle.net/10481/103412
dc.descriptionFunding for open access publishing: Universidad de Granada/CBUA. This work was supported by the University of Mohaghegh Ardabili, Iran. Funding for open access was pro- vided by the University of Granada/CBUA, Spain.es_ES
dc.description.abstractThe excessive exploitation of groundwater has led to a significant decline in water levels in recent years, emphasizing the need for sustainable water resource management strategies. Artificial groundwater recharge has emerged as an effective solution to address this challenge. This study integrates Geographic Information System (GIS) and Multi-Criteria Decision Analysis (MCDA) techniques to identify suitable areas for artificial groundwater recharge in the Ardabil plain, located in northwest Iran. Key parameters, including geology, slope, unsaturated zone thickness, soil texture, specific yield, drainage density, and land use, were analyzed. These parameters were weighted using three methodologies: Analytic Network Process (ANP), Analytic Hierarchy Process (AHP), and Fuzzy Analytic Hierarchy Process (FAHP). The final suitability map was developed by overlaying and combining the weighted information layers. The analysis revealed that 53.3%, 6%, and 42% of the plain area were classified as "very good" for artificial recharge according to the AHP, FAHP, and ANP methods, respectively. The southern part of the plain was consistently identified as a suitable area across all methods, characterized by pasture lands with young alluvial sediments, a deep unsaturated zone, gentle slopes, low drainage density, and high specific yield. To evaluate the performance of these methods, the results were cross-validated against natural recharge estimates, considering factors influencing water level fluctuations and recharge rates. Among the methods, ANP demonstrated the highest consistency with natural recharge estimates, making it the preferred approach.es_ES
dc.description.sponsorshipUniversidad de Granada/CBUAes_ES
dc.description.sponsorshipUniversity of Mohaghegh Ardabili, Iranes_ES
dc.language.isoenges_ES
dc.publisherSpringer Naturees_ES
dc.rightsAtribución-NoComercial 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectGroundwater managementes_ES
dc.subjectMulti-Criteria Decision Makinges_ES
dc.subjectDecision Support Systemes_ES
dc.titleIntegrating Geographic Information Systems and Multi-Criteria Decision Analysis for Evaluating Artificial Groundwater Rechargees_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1007/s11269-025-04131-8
dc.type.hasVersionVoRes_ES


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Atribución-NoComercial 4.0 Internacional
Except where otherwise noted, this item's license is described as Atribución-NoComercial 4.0 Internacional