Integrating Geographic Information Systems and Multi-Criteria Decision Analysis for Evaluating Artificial Groundwater Recharge
Metadatos
Mostrar el registro completo del ítemAutor
Eghbali Lord, Zahra; Rasoulzadeh, Ali; Abedi, Armin; Alikhani, Sharare; Fernández Gálvez, JesúsEditorial
Springer Nature
Materia
Groundwater management Multi-Criteria Decision Making Decision Support System
Fecha
2025-04-02Referencia bibliográfica
Z. 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/s11269-025-04131-8
Patrocinador
Universidad de Granada/CBUA; University of Mohaghegh Ardabili, IranResumen
The 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.