Estuaries and tidal inlets are often characterised by the presence of both cohesive and non-cohesive sediments. Knowledge of the sedimentation behaviour of sand-mud mixtures is therefore crucial to the understanding and prediction of the time-dependent structure (i.e. mixed or segregated), composition and erodibility of sediment bed deposits developing within these environments. In the current study, a series of settling column tests are conducted to investigate the hindered settling and initial bed consolidation phases of a range of sandclay mixtures to determine the parametric conditions under which bed segregation occurs. A new, non-invasive, electrical resistivity measurement technique is employed to capture both temporal and spatial changes in the density, porosity and composition of the evolving sand-clay bed deposits, complimented by time-lapsed images of the sedimentation process within the column. The results show that the formation of segregated (sand-clay) bed layers with bed deposits is largely controlled by the initial fractional composition (i.e. relative sand and clay concentrations). Specifically, mixtures with low clay contents are shown to form well-defined (sandclay) layer segregation within the resulting deposits, while higher clay contents result in more transitional segregation patterns or no layer segregation (for very high clay concentrations). The physical mechanisms under which these different segregation types can be generated are illustrated through predictions from an existing polydisperse hindered settling model. This model indicates that the degree of bed segregation, and time scale over which this occurs, correlates well with the difference in predicted hindered settling characteristics and upward displacements associated with the sand and clay fractions, respectively. In this regard, the new experimental dataset provides validation for the polydisperse model (for the first time), with the combined data and model predictions providing new insight into mixed (sand-clay) sedimentation processes.