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Study region: Yoyo river basin, Méiganga, Adamawa region, Cameroon. Study focus: The study aimed firstly to delineate and classify groundwater prospective zones in granito-gneissic terrain using advanced applications of remote sensing and geographical information systems through the integration of analytical hierarchy process (AHP), frequency ratio (FR) and Shannon entropy (SE). Secondly to compare the performance of these models to ensure effectiveness in computation. Thirteen groundwater influencing factors were adopted and weights were assigned to each thematic layer based on their relationship and characteristic with groundwater occurrence. Overlay weighted linear combination analysis tool in Arcgis environment was applied for groundwater prospect maps constructed. New hydrological insights for the region: Groundwater maps was classified into four categories:I poor, moderate, good and excellent. These maps analysis revealed that AHP have performed well for good and excellent classes with percentage of coved area of 23.73% and 23.75% respectively. These areas are localised in central, south-eastern, north-western and southern parts of the basin. Validation of outputs maps using wells location showed that AHP have higher accuracy (Kappa= 79.53%, AUC (predicted) = 82.40%, AUC (success) = 87.09%), compared to FR (Kappa= 74.62%, AUC (predicted) = 76.68%, AUC (success) = 77.21%) and to SE (Kappa= 77.75%, AUC (predicted) = 70.61.40%, AUC (success) = 75.78%). These results are reliable and useful for various decision-making processes and sustainable management of groundwater resources in the Yoyo river basin.

Exploration and production of groundwater, a vital and precious resource, is a challenging task in hard rock, which exhibits inherent heterogeneity. A geophysical survey was conducted in Méiganga, Mbéré department, in the Adamawa region, Cameroon. High-resolution electrical resistivity tomography (ERT) and self-potential (SP) dataset were collected in a gneissic terrain to solve the groundwater problem as people are facing acute shortage of drinking water in the study area. The analysis and interpretations based on resistivity models revealed substantial resistivity contrast between the altered gneiss that might contain water and massive gneiss and delineated five deeper groundwater prospects zones located at Yelwa, Ngoa-Ekélé, Sabongari, Ngassiri, and Gbakoungué, respectively. Nevertheless shallow groundwater zones (