Electrical Resistivity Imaging (ERI), a geophysical method based on resistivity contrasts between different media and their sensitivity to water, has become a vital tool for investigating subsurface structures in shallow aquatic environments such as rivers and lakes. Known for its non-invasive nature, environmental friendliness, and high-resolution imaging capabilities, ERI is particularly effective in mapping sediment layers and subsurface strata. However, the complexity of aquatic environments, influenced by factors such as water depth, resistivity, flow velocity, and sediment properties, poses significant challenges in obtaining high-resolution data. To address these challenges, this study explores the performance of ERI in two distinct aquatic settings: the Xinbian River, an artificial river in Suzhou, and the Qingshui Lake, a small inland lake in Yinchuan. This study established five ERI profiles using both suspended and floating electrode configurations. Key prior information, including water depth and resistivity, was integrated as constraints during the inversion process to enhance the accuracy of the resistivity distributions. The results delineated detailed spatial distributions of water, sediment layers, and subsurface formations. In the Xinbian River, the upstream section exhibited a relatively uniform depth with thicker sediment layers and a higher groundwater level compared to the downstream section. The downstream area, significantly affected by seasonal flooding, showed increased riverbed scouring, resulting in thinner sediment layers and a groundwater level approximately 1 meter lower than upstream. In Qingshui Lake, the maximum water depth reached 6 meters, with minimal bottom undulation and an average sediment thickness of about 1 meter. The sediments primarily consisted of clay layers, acting as aquicludes, with a distinct lens body identified in the western region. The underlying sand layer exhibited high water content but showed no significant groundwater activity. The findings underscore the effectiveness of ERI in resolving fine-scale sedimentary and subsurface structural features in shallow aquatic environments. The method excels in identifying sediment thickness, fine-grained lithological distributions, and their physical properties, offering high-resolution imaging without the need for invasive techniques such as drilling. The incorporation of prior information as inversion constraints significantly improves reliability while reducing uncertainties. This study demonstrates the broad applicability of ERI in investigating shallow rivers, lakes, and other aquatic systems, providing critical technical support for pollution monitoring, groundwater research, and hydrogeological and ecological restoration efforts. Future research could focus on optimizing electrode configurations and developing advanced inversion algorithms to further improve the resolution and reliability of ERI in complex aquatic environments.