<![CDATA[The analytical hierarchy process (AHP) model has been deemed by researchers with various backgrounds as an alternative solution due to the rapid, flexible, cost-effective, and high accuracy of groundwater potential assessment based on expert judgment, especially in complex geological settings. This paper specifically reviews research trends, key influence factors, model techniques, and validation process in AHP for groundwater availability assessment using bibliometric mapping and systematic literature review (SLR). The result reveals that AHP has been consistently utilized over the past decade (2015-2024), commonly combined, and integrated with statistical and machine learning models to enhance accuracy. Thirty-eight influence factors were observed and categorized into 5 groups (geology, hydrogeology, geomorphology, hydrology, and socio-environmental). The five most influential factors with significant normalized weight values are lithology, geomorphology, drainage density, rainfall, and lineament density, respectively. Well yield and groundwater level are most validation data using receiver operating characteristic (ROC) and area under curve (AUC) approach to evaluate the model. Considering hydrogeological insight, multicollinearity, validation, and sensitivity analysis are crucial to reduce bias and enhance better understanding of site-specific factors.]]>
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