Understanding streamflow generation and its dependence on catchment characteristics requires large spatial datasets and is often limited by convoluted effects of multiple variables. Here we circumvent such limitation using data-informed physics-based hydrologic modeling in catchments with similar vegetation and climate but different topography, size, and soils derived from gray shale (Shale Hills, SH, 0.08 km2) and sandstone (Garner Run, GR, 1.34 km2). We tested the hypothesis: the influence of topographic characteristics (a flatter slope, longer slope length, and larger riparian zone) is more significant than that of soil properties and catchment size, leading to a dampened streamflow response and a linear S-Q relationship at GR compared to SH. Transferring calibration coefficients from the previously-calibrated SH model to GR cannot reproduce monthly discharge until after incorporating measured boulder distribution at GR. Model calibration underscored the importance of soil properties (porosity, van Genuchten parameters, and boulder characteristics) in reproducing daily discharge. Virtual experiments that swapped topography, soil properties, and catchment size one at a time to disentangle their influence, showed that clayey SH soils led to high nonlinearity and threshold behavior. With the same soil and topography, changing from SH to GR size consistently increased dynamic water storage (Sd) from ~0.12 m to ~0.17 m. All analyses accentuated the predominant control of soil properties, therefore rejecting the hypothesis. The results illustrate the use of physics-based modelling for illuminating mechanisms, and underscore the importance and challenges for subsurface characterization as we move toward hydrological Prediction in Ungauged Basins (PUB).