<p>Conventional sand filtration monitoring is often treated as a non-transparent process with limited ability to resolve internal clogging. This study investigates the use of Electrical Resistivity Tomography (ERT) for non-invasive, real-time characterization of clogging dynamics in sand filtration systems. By incorporating prior knowledge of porous media conductivity based on Archie’s Law, resistivity variations can be related to changes in pore structure and fluid transport. A comparison of electrode configurations shows that a stainless-steel Wenner array provides stable measurements, with a root mean square (RMS) error of 2.9%. Experimental results indicate that ERT can detect internal heterogeneities caused by different types of obstructions, including air entrapment (18.4% increase in resistivity) and solid inclusions, through their effects on flow distribution. Time-resolved measurements during 12-hour filtration experiments reveal the gradual development of clogging zones, with particle movement influenced by coupled diffusive and advective processes. Saline tracer tests further demonstrate that ERT can track fluid movement and ion transport within the filter bed. After backwashing, ERT identifies residual air pockets and localized particle redistribution that conventional pressure-based monitoring fails to detect. These observations, together with effluent particle size analysis, suggest that ERT can provide useful information for assessing clogging conditions and filtration performance. Crucially, integrating ERT with Archie’s Law to quantitatively interpret clogging-induced resistivity shifts represents a significant advancement over previous qualitative or spatially averaged ERT applications in filtration. Moreover, the systematic comparison between single- and triple-electrode configurations, as well as Wenner and Schlumberger arrays, provides actionable engineering guidance for future ERT deployments in shallow porous media.</p>