RESUMO
Groundwater is a crucial natural resource for providing reliable and long-lasting water supplies across the globe. The integrated approach used in the current study involved the use of multiple techniques to assess groundwater potential zones (GWPZs) and identify suitable areas for artificial recharge sites. The methods used in the study were a combination of geographic information system (GIS), analytic hierarchy process (AHP), and fuzzy analytic hierarchy process (Fuzzy-AHP) to accomplish this goal. The study considered multiple thematic maps, such as drainage density, elevation, geomorphology, slope, curvature, topographic wetness index (TWI), geology, distance from the river, land use and land cover (LULC), and rainfall, to determine the GWPZs. AHP and Fuzzy-AHP were used to weight thematic maps based on their relative importance in controlling groundwater availability and recharge, and then a weighted overly analysis in a GIS environment was utilized to derive the final GWPZs map. After completing the weighting of thematic maps, both AHP and Fuzzy-AHP models categorized GWPZs into low, moderate, and high categories in the study area. In this study area, GWPZs were classified as poor, moderate, and high using both the AHP and Fuzzy-AHP models. According to the AHP model, 5.41% of the area's GWPZs were categorized as poor, 70.68% as moderate, and 23.91% as high. The Fuzzy-AHP model, on the other hand, categorized 4.92% as poor, 69.75% as moderate, and 25.33% as high. To validate these results, the receiver operating characteristic curve (ROC) and area under the curve (AUC) were used to explore the prediction accuracy, resulting in an accuracy rate of 70.1% for AHP and 71% for Fuzzy-AHP. These findings suggest that the Fuzzy-AHP model is effective in accurately identifying GWPZs in this area. Additionally, using remote sensing (RS) and GIS, the current study created a map by overlaying the lineament and drainage maps to determine suitable locations for artificial recharge. One-hundred-forty suitable locations for artificial recharge sites were identified based on Fuzzy-AHP. The study's reliable findings assist decision-makers and water users in the research area to use groundwater resources sustainably. This information aids in sustainable planning and management of groundwater resources, ensuring their availability and sustainability for future generations.