GIS-based multi-criteria decision-making for identifying potential artificial groundwater recharge zones in the Tikurwuha watershed of Ethiopia

Groundwater extraction has increased significantly by over 30% in urbanizing areas globally due to increasing population growth. Approximately 2 billion people depend on groundwater as their primary source of drinking water, and urban population growth has resulted in aquifer depletion and environmental degradation. This problem also exists in most cities of Ethiopia, including the study area. This study identifies the potential artificial groundwater recharge zones (AGRZs) in the Tikurwuha watershed. A GIS-based multi-criteria decision-making method was used in ArcGIS 10.5 to identify potential artificial groundwater recharge zones. In this process, nine factors were chosen: rainfall, soil texture, geology, normalized difference vegetation index, slope, topographic position index, topographic wetness index, drainage density, and lineament density. The factors were created using rainfall data from national meteorological stations, soil texture data from the FAO soil database, and geology data from the Ethiopia Geological Survey, as well as Landsat images and digital elevation models within ArcGIS 10.5. The weights of all selected factors were derived using the Analytical Hierarchy Process after determining the relative importance between pairs of factors. Suitability classes were generated for all factors, and then a weighted overlay was performed in ArcGIS 10.5. The final output of potential AGRZs was categorized as extremely high (0.5625 hectares (0.001%)), high (20,003.7 hectares (30.959%)), moderate (42,428.17 hectares (65.665%)), poor (2,179.656 hectares (3.373%)), and very poor (1.312 hectares (0.002%)).The NDVI and TPI were the next most important parameters, after drainage density, slope, and rainfall. These factors have a major impact on the processes of groundwater recharge, infiltration, and runoff generation. With an Area Under the Curve of 77.45%, the study showed that it was very capable of using geospatial methodologies and validation against high-resolution data to properly estimate appropriate artificial groundwater recharge zones. Therefore, high-potential locations can be used to use artificial groundwater recharge techniques by decision-makers in charge of the sustainable management of groundwater resources.