Publication Date:
2019
Description:
Abstract
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 address this knowledge gap using data‐informed physics‐based hydrologic modelling in two catchments with similar vegetation and climate but different lithology (Shale Hills, SH, Shale, 0.08 km2 and Garner Run, GR, Sandstone, 1.34 km2), which influences catchment topography and soil properties. The sandstone catchment, Garner Run, is characterized by lower drainage density, extensive valley fill, and boulder soils. We tested the hypothesis that the influence of topographic characteristics is more significant than that of soil properties and catchment size. 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 were used to swap topography, soil properties, and catchment size one at a time to disentangle their influence. They 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).
Print ISSN:
0043-1397
Electronic ISSN:
1944-7973
Topics:
Architecture, Civil Engineering, Surveying
,
Geography
