Groundwater vulnerability mapping in the Maze Zenti catchment, Ethiopia: Integrating the DRASTIC model with an entropy-weighted modification in a GIS environment

Groundwater vulnerability mapping is a vital tool for sustainable water resource management, especially in regions where agriculture is the primary means of livelihood. In such areas, groundwater is highly susceptible to contamination due to the slow natural attenuation of pollutants and the limited feasibility of artificial remediation. This study aims to assess the spatial vulnerability of groundwater to contamination in the Maze–Zenti catchment of the Omo Basin, Southern Ethiopia. To achieve this, the study utilized four overlay index models: DRASTIC, Modified DRASTIC, Entropy-DRASTIC, and Entropy-Modified DRASTIC. The study integrated the Shannon Entropy technique to optimize parameter weighting and improve the accuracy of vulnerability mapping. It used observed nitrate concentrations to validate groundwater vulnerability to pollution. The results revealed that the DRASTIC and modified DRASTIC models classified the study area into five vulnerability zones: very low, low, moderate, high, and very high. In contrast, the entropy-weighted models grouped the area into four classes: very low, low, moderate, and high groundwater vulnerability to pollution. The DRASTIC and Modified DRASTIC models indicate that a significant portion of the area, 1868.23 km² (79.85 %) and 1743.58 (74.52 %), respectively, falls within very low to moderate groundwater pollution vulnerability zones. According to the DRASTIC and modified DRASTIC models, only a small fraction of the area is classified under high to very high pollution vulnerability, covering 471.77 km² (20.15 %) and 596.42 km² (25.48 %). The Entropy-modified DRASTIC model classified 78.58 % (1838.74 km²) of the area as having very low to moderate vulnerability, while categorizing 21.42 % (501.34 km²) as highly vulnerable. Validation using nitrate (NO₃⁻) concentrations confirmed a strong correlation with the Entropy-modified DRASTIC model, indicating its greater predictive capability of groundwater vulnerability to pollution. Furthermore, the integration of land use/land cover (LULC) data significantly improved model performance by refining the delineation of vulnerable zones. The Entropy-modified DRASTIC model demonstrates higher accuracy and reliability for groundwater vulnerability assessment. Its application can support informed decision-making for sustainable groundwater protection and land use planning.