Sediment transport is a key process that affects the morphology and ecological habitat diversity of rivers. As part of a gravel augmentation program to mitigate sediment deficit below a dam, gravel mobility in the Ain River in Eastern France was investigated by tracking of a large amount (n = 1063) of PIT-tagged gravels in the field, conducting a probabilistic approach based on published tracer studies, and performing two-dimensional (2D) numerical modeling of flow and bedload transport. This study highlights the strengths, weaknesses, and complementary aspects of the three approaches to the understanding of river gravel mobility. Thanks to recent technological improvements, PIT-tagged gravels provide an increasingly reliable and accurate representation of the bedload movement in the field, although it remains limited in spatio-temporal resolution. Based on an exponential distribution, the probabilistic approach correctly reproduces the average trend in travel distances by the different classes of particles over hydrological periods, including one or several significant floods. The 2D numerical modeling accounts for the variability of local hydrodynamic conditions and can simulate realistic displacement distributions for the different classes of particles with high spatio-temporal resolution. Numerical modeling is a very encouraging approach, which makes our study original because it is the first time that the estimation of mean travel distances, the application of an exponential distribution, and the comparison with a hydrodynamic model are combined. A more effective modeling strategy involves incorporating a probabilistic transport model in the 2D numerical model to reproduce the observed scatter of the individual particle trajectories.