Debris-flow volumes can increase due to the incorporation of sediment into the flow as a consequence of channel-bed erosion along the flow path. This study describes a sensitivity analysis of the recently introduced RAMMS (Rapid Mass Movements) debris-flow entrainment model, which is intended to help solve problems related to predicting the runout of debris flows. The entrainment algorithm predicts the depth and rate of erosion as a function of basal shear stress based on an analysis of erosion measurements at the Illgraben catchment, Switzerland (Frank et al., 2015). Starting with a landslide-Type initiation in the RAMMS model, the volume of entrained sediment was calculated for recent well-documented debris-flow events at the Bondasca and the Meretschibach catchments, Switzerland. The sensitivity to the initial landslide volume was investigated by systematically varying the initial landslide volume and comparing the resulting debris-flow volume with estimates from the field sites. In both cases, the friction coefficients in the RAMMS runout model were calibrated using the model, whereby the entrainment module was (1) inactivated to find plausible values for general flow properties by adjusting both coefficients (3/4 and μ) and then (2) activated to further refine coefficient μ, which controls erosion (patterns). The results indicate that the model predicts plausible erosion volumes in comparison with field data. By including bulking due to entrainment in runout models, more realistic runout patterns are predicted in comparison to starting the model with the entire debris-flow volume (initial landslide plus entrained sediment). In particular, lateral bank overflow - not observed during these events - is prevented when using the sediment entrainment model, even in very steep (≈60-65%) and narrow (4-6 m) torrent channels. Predicted sediment entrainment volumes are sensitive to the initial landslide volume, suggesting that the model may be useful for both reconstruction of historical events and the modeling of scenarios as part of a hazard analysis.