Comparative evaluation of multi-influence factor, Shannon Entropy, and frequency ratio techniques for groundwater potential mapping in the Maze and Zenti catchments, Omo Basin, Ethiopia.

Sustainable water resource management relies heavily on accurate groundwater potential mapping, especially in countries like Ethiopia, where groundwater is a primary drinking source. This study focuses on the Maze-Zenti catchments, located in the Omo Basin of Ethiopia and covering an area of 2340 square kilometers, which are highly dependent on groundwater resources. They aimed to identify groundwater potential zones using three advanced geospatial and statistical methods: Multi-Influence Factor (MIF), Shannon Entropy (SE), and Frequency Ratio (FR). These methods were selected for their demonstrated efficiency in groundwater potential mapping. A comprehensive geospatial database was created, incorporating slope, elevation, drainage density, lithology, soil type, aspect, Topographic Wetness Index (TWI), lineament density, rainfall, and land use. The results classified the area into four zones: low, moderate, high, and very high groundwater potential across all models. The ensemble model combining all three methods demonstrated strong predictive capability, with 35.04 % of the area classified as high and 22.48 % as very high potential. Separately, the frequency ratio (FR) model emphasized high (35.17 %) and very high (20.17 %) potential zones, while the Shannon entropy (SE) and multi-influencing factor (MIF) models also identified significant portions in the high and moderate classes. Validation using Receiver Operating Characteristic (ROC) curves established the frequency ratio (FR) model as the most reliable, achieving an Area under the Curve (AUC) of 0.851, followed by Shannon entropy (SE) (0.813) and multi-influencing factor (MIF) (0.784). A numerical comparison with actual well yields revealed a 77.5 % accuracy rate, further validating the model's reliability. The study highlights the critical role of groundwater mapping in regions with limited resources and offers a flexible framework adaptable to various hydrogeological conditions, making it valuable for well drillers, water managers, researchers, and other stakeholders in water resource management.