Fluvial sediment transport is caused by a complex interaction of interdependent grain and fluid processes many of which are stochastic in nature and cannot be adequately represented by deterministic equations. Random variable analysis has been used previously but limited data are available to describe the variability of grain resistance combined with particle arrangements, and thus validate such analysis. In this study low to medium bed load transport tests were carried out in a flume where sediment movement was monitored using a three-camera 3D PIV system. Simultaneous grain motion and flow velocity measurements were made on a plane located slightly above and parallel to the sediment bed. Detailed statistical velocity information was acquired to model the velocity distribution at the bed level. This was combined with the joint probabilistic distribution of particle exposures and grain resistance to motion, which were obtained from discrete particle modeling (DPM) simulations. DPM simulations were used to provide a stochastic mathematical description of the risk that a stationary particle is entrained by the flow. Predictions from the stochastic model equations replicated the observed pulsation in sediment transport. This demonstrates that it is possible to simulate sediment entrainment and transport at a high resolution by adequately modeling all the sub-processes. A number of flow patterns were identified that caused large fluctuations of the entrainment rate. These all exhibit high velocity flow structures, but they selectively cause the dislodgement of individual particles located at different positions. This selective behavior follows from the variability of the interaction between the near-bed flow and the particles having different exposure.