Runoff from agricultural watersheds can carry a number of agricultural pollutants and pathogens; often associated with the sediment fraction. Deposition of this sediment can impact water quality and the ecology of the river, and the re-suspension of such sediment can become sources of contamination for reaches downstream. In this paper a modelling framework to predict sediment and associated microbial erosion, transport and deposition is proposed for the South Nation River, Ontario, Canada. The modelling framework is based on empirical relationships (deposition and re-suspension fluxes), derived from laboratory experiments in a rotating circular flume using sediment collected from the river bed. The bed shear stress governing the deposition and re-suspension processes in the stream was predicted using a one dimensional mobile boundary flow model called MOBED. Counts of live bacteria associated with the suspended and bed sediments were used in conjunction with measured suspended sediment concentration at an upstream section to allow for the estimation of sediment associated microbial erosion, transport and deposition within the modelled river reach. Results suggest that the South Nation River is dominated by deposition periods with erosion only occurring at flows above approximately 250 m(3) s(-1) (above this threshold, all sediment (suspended and eroded) with associated bacteria are transported through the modelled reach). As microbes are often associated with sediments, and can survive for extended periods of time, the river bed is shown to be a possible source of pathogenic organisms for erosion and transport downstream during large storm events. It is clear that, shear levels, bacteria concentrations and suspended sediment are interrelated requiring that these parameters be studied together in order to understand aquatic microbial dynamics. It is important that any management strategies and operational assessments for the protection of human and aquatic health incorporate the sediment compartments (suspended and bed sediment) and the energy dynamics within the system in order to better predict the concentration of indicator organism.