资源环境科技发展态势分析平台

Understanding streamflow generation and its dependence on catchment characteristics requires large spatial data sets and is often limited by convoluted effects of multiple variables. Here we address this knowledge gap using data-informed, physics-based hydrologic modeling in two catchments with similar vegetation and climate but different lithology (Shale Hills [SH], shale, 0.08 km(2), and Garner Run [GR], sandstone, 1.34 km(2)), which influences catchment topography and soil properties. The sandstone catchment, GR, is characterized by lower drainage density, extensive valley fill, and bouldery 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 (S-d) from 0.12 to similar 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 modeling for illuminating mechanisms and underscore the importance of subsurface characterization as we move toward hydrological prediction in ungauged basins.