Abstract

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 km2, and Garner Run [GR], sandstone, 1.34 km2), 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 (Sd) from ~0.12 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.

Original languageEnglish (US)
Pages (from-to)9234-9257
Number of pages24
JournalWater Resources Research
Volume55
Issue number11
DOIs
StatePublished - Nov 1 2019

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streamflow
soil property
lithology
topography
catchment
shale
boulder
physics
sandstone
calibration
valley fill
soil
water storage
spatial data
nonlinearity
modeling
porosity
drainage
vegetation
climate

All Science Journal Classification (ASJC) codes

  • Water Science and Technology

Cite this

@article{e708db91438e4db4ac3f939b1f8a3e67,
title = "Streamflow Generation From Catchments of Contrasting Lithologies: The Role of Soil Properties, Topography, and Catchment Size",
abstract = "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 km2, and Garner Run [GR], sandstone, 1.34 km2), 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 (Sd) from ~0.12 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.",
author = "Dacheng Xiao and Yuning Shi and Brantley, {Susan L.} and Brandon Forsythe and Roman DiBiase and Kenneth Davis and Li Li",
year = "2019",
month = "11",
day = "1",
doi = "10.1029/2018WR023736",
language = "English (US)",
volume = "55",
pages = "9234--9257",
journal = "Water Resources Research",
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publisher = "American Geophysical Union",
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TY - JOUR

T1 - Streamflow Generation From Catchments of Contrasting Lithologies

T2 - The Role of Soil Properties, Topography, and Catchment Size

AU - Xiao, Dacheng

AU - Shi, Yuning

AU - Brantley, Susan L.

AU - Forsythe, Brandon

AU - DiBiase, Roman

AU - Davis, Kenneth

AU - Li, Li

PY - 2019/11/1

Y1 - 2019/11/1

N2 - 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 km2, and Garner Run [GR], sandstone, 1.34 km2), 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 (Sd) from ~0.12 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.

AB - 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 km2, and Garner Run [GR], sandstone, 1.34 km2), 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 (Sd) from ~0.12 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.

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SN - 0043-1397

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