Characterizing coarse-resolution watershed soil moisture heterogeneity using fine-scale simulations
Watershed-scale hydrological and biogeochemical models are usually discretized at resolutions coarser than where significant heterogeneities in topography, abiotic factors (e.g., soil properties), and biotic (e.g., vegetation) factors exist. Here we report on a method to use fine-scale (220 m grid c...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2014-07-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | http://www.hydrol-earth-syst-sci.net/18/2463/2014/hess-18-2463-2014.pdf |
| _version_ | 1819063921940627456 |
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| author | W. J. Riley C. Shen |
| author_facet | W. J. Riley C. Shen |
| author_sort | W. J. Riley |
| collection | DOAJ |
| description | Watershed-scale hydrological and biogeochemical models
are usually discretized at resolutions coarser than where significant
heterogeneities in topography, abiotic factors (e.g., soil properties), and
biotic (e.g., vegetation) factors exist. Here we report on a method to use
fine-scale (220 m grid cells) hydrological model predictions to build
reduced-order models of the statistical properties of near-surface soil moisture at
coarse resolution (2<sup>5</sup> times coarser, ~7 km). We applied
a watershed-scale hydrological model (PAWS-CLM4) that has been previously
tested in several watersheds. Using these simulations, we developed simple,
relatively accurate (<i>R</i><sup>2</sup> ~0.7–0.8), reduced-order
models for the relationship between mean and higher-order moments of
near-surface soil moisture during the nonfrozen periods over five years.
When applied to transient predictions, soil moisture variance and skewness
were relatively accurately predicted (<i>R</i><sup>2</sup> 0.7–0.8),
while the kurtosis was less accurately predicted (<i>R</i><sup>2</sup> ~0.5). We also tested 16 system attributes hypothesized to explain the
negative relationship between soil moisture mean and variance toward the
wetter end of the distribution and found that, in the model, 59% of the
variance of this relationship can be explained by the elevation gradient
convolved with mean evapotranspiration. We did not find significant
relationships between the time rate of change of soil moisture variance and
covariances between mean moisture and evapotranspiration, drainage, or soil
properties, as has been reported in other modeling studies. As seen in
previous observational studies, the predicted soil moisture skewness was
predominantly positive and negative in drier and wetter regions,
respectively. In individual coarse-resolution grid cells, the transition
between positive and negative skewness occurred at a mean soil moisture of
~0.25–0.3. The type of numerical modeling experiments
presented here can improve understanding of the causes of soil moisture
heterogeneity across scales, and inform the types of observations required
to more accurately represent what is often unresolved spatial heterogeneity
in regional and global hydrological models. |
| first_indexed | 2024-12-21T15:22:22Z |
| format | Article |
| id | doaj.art-c93f1e0d9d9d46d78487171f7aa0606b |
| institution | Directory Open Access Journal |
| issn | 1027-5606 1607-7938 |
| language | English |
| last_indexed | 2024-12-21T15:22:22Z |
| publishDate | 2014-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Hydrology and Earth System Sciences |
| spelling | doaj.art-c93f1e0d9d9d46d78487171f7aa0606b2022-12-21T18:59:00ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382014-07-011872463248310.5194/hess-18-2463-2014Characterizing coarse-resolution watershed soil moisture heterogeneity using fine-scale simulationsW. J. Riley0C. Shen1Earth Systems Division, Climate and Carbon Department, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USADepartment of Civil and Environmental Engineering, The Pennsylvania State University, University Park, PA 16802, USAWatershed-scale hydrological and biogeochemical models are usually discretized at resolutions coarser than where significant heterogeneities in topography, abiotic factors (e.g., soil properties), and biotic (e.g., vegetation) factors exist. Here we report on a method to use fine-scale (220 m grid cells) hydrological model predictions to build reduced-order models of the statistical properties of near-surface soil moisture at coarse resolution (2<sup>5</sup> times coarser, ~7 km). We applied a watershed-scale hydrological model (PAWS-CLM4) that has been previously tested in several watersheds. Using these simulations, we developed simple, relatively accurate (<i>R</i><sup>2</sup> ~0.7–0.8), reduced-order models for the relationship between mean and higher-order moments of near-surface soil moisture during the nonfrozen periods over five years. When applied to transient predictions, soil moisture variance and skewness were relatively accurately predicted (<i>R</i><sup>2</sup> 0.7–0.8), while the kurtosis was less accurately predicted (<i>R</i><sup>2</sup> ~0.5). We also tested 16 system attributes hypothesized to explain the negative relationship between soil moisture mean and variance toward the wetter end of the distribution and found that, in the model, 59% of the variance of this relationship can be explained by the elevation gradient convolved with mean evapotranspiration. We did not find significant relationships between the time rate of change of soil moisture variance and covariances between mean moisture and evapotranspiration, drainage, or soil properties, as has been reported in other modeling studies. As seen in previous observational studies, the predicted soil moisture skewness was predominantly positive and negative in drier and wetter regions, respectively. In individual coarse-resolution grid cells, the transition between positive and negative skewness occurred at a mean soil moisture of ~0.25–0.3. The type of numerical modeling experiments presented here can improve understanding of the causes of soil moisture heterogeneity across scales, and inform the types of observations required to more accurately represent what is often unresolved spatial heterogeneity in regional and global hydrological models.http://www.hydrol-earth-syst-sci.net/18/2463/2014/hess-18-2463-2014.pdf |
| spellingShingle | W. J. Riley C. Shen Characterizing coarse-resolution watershed soil moisture heterogeneity using fine-scale simulations Hydrology and Earth System Sciences |
| title | Characterizing coarse-resolution watershed soil moisture heterogeneity using fine-scale simulations |
| title_full | Characterizing coarse-resolution watershed soil moisture heterogeneity using fine-scale simulations |
| title_fullStr | Characterizing coarse-resolution watershed soil moisture heterogeneity using fine-scale simulations |
| title_full_unstemmed | Characterizing coarse-resolution watershed soil moisture heterogeneity using fine-scale simulations |
| title_short | Characterizing coarse-resolution watershed soil moisture heterogeneity using fine-scale simulations |
| title_sort | characterizing coarse resolution watershed soil moisture heterogeneity using fine scale simulations |
| url | http://www.hydrol-earth-syst-sci.net/18/2463/2014/hess-18-2463-2014.pdf |
| work_keys_str_mv | AT wjriley characterizingcoarseresolutionwatershedsoilmoistureheterogeneityusingfinescalesimulations AT cshen characterizingcoarseresolutionwatershedsoilmoistureheterogeneityusingfinescalesimulations |