One-dimensional solute transport modeling to simulate experimental tracer releases in rivers is common practice. However, few studies have investigated the effect of experiment type (slug injection versus constant rate injection) on model parameter sensitivity and identifiability. We conducted slug injection and constant-rate experiments in a low-gradient, alluvial, headwater tundra stream in northern Alaska. Each experimental data set was simulated with the one-dimensional transport with inflow and storage (OTIS) model and analyzed with Monte Carlo-based techniques to investigate differences in global sensitivity and time-varying identifiability of the model parameters. We found that the longitudinal dispersion parameter exhibited relatively high sensitivity for the slug injection data, while the storage zone area parameter exhibited relatively high sensitivity for the constant rate injection data. The storage zone area and storage zone - main channel exchange rate parameters show heightened sensitivity during rising and tailing portions of the constant rate injection breakthrough curve, whereas for the slug injection data, increased identifiability for these parameters is only observed during the tailing portion of the breakthrough curve. Results demonstrate that selection of slug injection or constant rate experiment type impacts parameter sensitivity and time-varying identifiability and that experimental data can easily be analyzed to understand the relative information content associated with each parameter of a 1-D transient storage model.