The primary goals of this research are to detect the spatial variation of the hydrogeological characteristics and evaluate the groundwater quality in the eastern Nile River, Khartoum state, Sudan, using geophysical and hydrochemical methods. Thirteen Vertical electrical soundings (VES), using Schlumberger configuration, were measured along three profiles to characterize the groundwater aquifer. VES findings denoted that the study area comprises two hydraulically connected aquifers. The upper aquifer of sand has an average thickness of 50 m, and the lower aquifer is composed of sandstone of a thickness of up to 300 m. The results of VES inversion were further used to measure aquifer characteristics, including transverse resistance, longitudinal conductance, hydraulic conductivity, and transmissivity. The detected average values of these parameters were 6690 Ωm2, 1.4 Ω−1, 264 m2/d and 4 m/day, respectively. In addition, regression analysis was performed to suggest local relationships for estimating aquifer characteristics within the study area. On the other hand, total longitudinal conductance was used to predict the protective strength of the hydrogeological columns, ranging from 1.7 to 5.8 Ω−1; as a result, the protective capacity of the aquifer ranged from good to very good, suggesting potable water quality. This result was subsequently confirmed by the groundwater quality index (GWQI) model. Eleven physiochemical parameters analyzed for nine boreholes were used in GWQI estimation to assess groundwater quality in the study area. The primary analysis of the hydrochemical parameters indicated that almost all parameters are below permissible limits prescribed by the World Health Organization (WHO). The computed GWQI varies between 34.8 and 148, and the majority of groundwater samples, precisely 55.5%, are good water types, while 22.2% of the samples are in an excellent quality state. This research concluded that the groundwater aquifer in the study area is ideal for groundwater exploitation. However, applying a detailed geophysical and hydrochemical survey is recommended to reduce the uncertainty of the resulting models.