Dredging is performed for various reasons, including port development, coastal defense and land reclamation. The economic and social importance of such projects is widely acknowledged, but there are growing concerns about the possible environmental impact of the dredge plumes that form as a temporary by-product of these activities. Suspended sediment blocks sunlight, and sediment that settles on the seabed buries coral and other organisms. These effects accumulate over the duration of a dredging project, and should be minimized. An important step towards this goal is predicting plume formation and development. Here, we focus on an overflow plume from a trailer suction hopper dredger (TSHD). Although this subject has been studied for years, much is still unknown, due to the complex interaction of the processes involved. Because of this complexity, it is not uncommon in the industry to use rules of thumb, derived from empirical studies. One such rule of thumb, based on an influential publication by Becker et al. (2015), relates to the fraction of the overflow plume that is still (or again) in suspension once the developing plume moves from the dynamic near-field to the passive far-field. This source term fraction (STF) is important, because the large-scale area models that model plume development in the far-field require information about the characteristics of the plume entering the far-field zone. Becker et al. (2015) presented a realistic range of 0-20% for the source term fraction. This range is based on a combination of measurements and expert opinions. Although Becker et al. (2015) recommend characterization monitoring at the start of a dredging project to determine whether the 0-20% range needs adjusting, this is not always done in practice, due to time pressure, costs, complexity or lack of necessity. Building on the work by Becker et al., this thesis aims to support a more informed implementation of TSHD source terms on the computational grid of far-field models. In order to explore the behavior of SHD dredge plumes, numerical simulations were carried out using computational fluid dynamics model TUDflow3D. In these simulations, the values of three model input parameters – the water depth, the overflow density and the crossflow velocity – were varied to gain insight into the behavior of the plume under the conditions studied. For each of the three parameters, three representative values were chosen on the basis of expert advice, and all combinations were tested, leading to 27 numerical simulations. The results of the numerical simulations show that the amount of sediment in the plume has reduced to less than 20% of the sediment in the overflow plume at 11-42 minutes of plume development, corresponding to a distance of 0-1895 m from the dredging location (500-3800 m from the moving vessel), depending on the specific conditions. It is important to note that (only) three conditions were varied in this study. These conditions were all steady state (e.g. no tidal flows). In real-life situations, many more (combinations of) conditions and hence a wider range of results are possible. Conditions where the plume was found to travel relatively long and far into the far-field, are a high ambient current, a low water depth and low overflow densities. The effect of these factors corresponds with existing studies. The contribution of this work lies in the broad characterization of the developing plume under these various conditions: not only the magnitude of the plume is investigated, but also its vertical and lateral distribution. Specifically, the contribution of the bottom 6-13 % of the water column to the total plume flux is highlighted. This is particularly of interest, as this zone is typically not included in ADCP measurements. This increases insight in the processes underlying plume development and supports the appropriate determination and implementation of the far-field source term, including a more informed use of the 0-20% source term fraction range proposed by Becker et al. (2015).