A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves
Agroecosystem models, regional and global climate models, and numerical weather prediction models require adequate parameterization of soil hydraulic properties. These properties are fundamental for describing and predicting water and energy exchange processes at the transition zone between solid...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2017-07-01
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| Series: | Earth System Science Data |
| Online Access: | https://www.earth-syst-sci-data.net/9/529/2017/essd-9-529-2017.pdf |
| _version_ | 1811314095360573440 |
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| author | C. Montzka M. Herbst L. Weihermüller A. Verhoef H. Vereecken H. Vereecken |
| author_facet | C. Montzka M. Herbst L. Weihermüller A. Verhoef H. Vereecken H. Vereecken |
| author_sort | C. Montzka |
| collection | DOAJ |
| description | Agroecosystem models, regional and global climate models, and numerical
weather prediction models require adequate parameterization of soil hydraulic
properties. These properties are fundamental for describing and predicting
water and energy exchange processes at the transition zone between solid
earth and atmosphere, and regulate evapotranspiration, infiltration and
runoff generation. Hydraulic parameters describing the soil water retention
(WRC) and hydraulic conductivity (HCC) curves are typically derived from soil
texture via pedotransfer functions (PTFs). Resampling of those parameters for
specific model grids is typically performed by different aggregation
approaches such a spatial averaging and the use of dominant textural
properties or soil classes. These aggregation approaches introduce
uncertainty, bias and parameter inconsistencies throughout spatial scales due
to nonlinear relationships between hydraulic parameters and soil texture.
Therefore, we present a method to scale hydraulic parameters to individual
model grids and provide a global data set that overcomes the mentioned
problems. The approach is based on Miller–Miller scaling in the relaxed form
by Warrick, that fits the parameters of the WRC through all sub-grid WRCs to
provide an effective parameterization for the grid cell at model resolution;
at the same time it preserves the information of sub-grid variability of the
water retention curve by deriving local scaling parameters. Based on the
Mualem–van Genuchten approach we also derive the unsaturated hydraulic
conductivity from the water retention functions, thereby assuming that the
local parameters are also valid for this function. In addition, via the
Warrick scaling parameter <i>λ</i>, information on global sub-grid scaling
variance is given that enables modellers to improve dynamical downscaling of
(regional) climate models or to perturb hydraulic parameters for model
ensemble output generation. The present analysis is based on the ROSETTA PTF
of Schaap et al. (2001) applied to the SoilGrids1km data set of Hengl et
al. (2014). The example data set is provided at a global resolution of
0.25° at <a href="https://doi.org/10.1594/PANGAEA.870605" target="_blank">https://doi.org/10.1594/PANGAEA.870605</a>. |
| first_indexed | 2024-04-13T11:05:52Z |
| format | Article |
| id | doaj.art-b721b7dd191b4710a6da80e1b047ebe1 |
| institution | Directory Open Access Journal |
| issn | 1866-3508 1866-3516 |
| language | English |
| last_indexed | 2024-04-13T11:05:52Z |
| publishDate | 2017-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Earth System Science Data |
| spelling | doaj.art-b721b7dd191b4710a6da80e1b047ebe12022-12-22T02:49:17ZengCopernicus PublicationsEarth System Science Data1866-35081866-35162017-07-01952954310.5194/essd-9-529-2017A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curvesC. Montzka0M. Herbst1L. Weihermüller2A. Verhoef3H. Vereecken4H. Vereecken5Forschungszentrum Jülich GmbH, Institute of Bio- and Geosciences: Agrosphere (IBG-3), Jülich, GermanyForschungszentrum Jülich GmbH, Institute of Bio- and Geosciences: Agrosphere (IBG-3), Jülich, GermanyForschungszentrum Jülich GmbH, Institute of Bio- and Geosciences: Agrosphere (IBG-3), Jülich, GermanyUniversity of Reading, Department of Geography and Environmental Science, Reading, UKForschungszentrum Jülich GmbH, Institute of Bio- and Geosciences: Agrosphere (IBG-3), Jülich, GermanyInternational Soil Modeling Consortium, Jülich, GermanyAgroecosystem models, regional and global climate models, and numerical weather prediction models require adequate parameterization of soil hydraulic properties. These properties are fundamental for describing and predicting water and energy exchange processes at the transition zone between solid earth and atmosphere, and regulate evapotranspiration, infiltration and runoff generation. Hydraulic parameters describing the soil water retention (WRC) and hydraulic conductivity (HCC) curves are typically derived from soil texture via pedotransfer functions (PTFs). Resampling of those parameters for specific model grids is typically performed by different aggregation approaches such a spatial averaging and the use of dominant textural properties or soil classes. These aggregation approaches introduce uncertainty, bias and parameter inconsistencies throughout spatial scales due to nonlinear relationships between hydraulic parameters and soil texture. Therefore, we present a method to scale hydraulic parameters to individual model grids and provide a global data set that overcomes the mentioned problems. The approach is based on Miller–Miller scaling in the relaxed form by Warrick, that fits the parameters of the WRC through all sub-grid WRCs to provide an effective parameterization for the grid cell at model resolution; at the same time it preserves the information of sub-grid variability of the water retention curve by deriving local scaling parameters. Based on the Mualem–van Genuchten approach we also derive the unsaturated hydraulic conductivity from the water retention functions, thereby assuming that the local parameters are also valid for this function. In addition, via the Warrick scaling parameter <i>λ</i>, information on global sub-grid scaling variance is given that enables modellers to improve dynamical downscaling of (regional) climate models or to perturb hydraulic parameters for model ensemble output generation. The present analysis is based on the ROSETTA PTF of Schaap et al. (2001) applied to the SoilGrids1km data set of Hengl et al. (2014). The example data set is provided at a global resolution of 0.25° at <a href="https://doi.org/10.1594/PANGAEA.870605" target="_blank">https://doi.org/10.1594/PANGAEA.870605</a>.https://www.earth-syst-sci-data.net/9/529/2017/essd-9-529-2017.pdf |
| spellingShingle | C. Montzka M. Herbst L. Weihermüller A. Verhoef H. Vereecken H. Vereecken A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves Earth System Science Data |
| title | A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves |
| title_full | A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves |
| title_fullStr | A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves |
| title_full_unstemmed | A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves |
| title_short | A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves |
| title_sort | global data set of soil hydraulic properties and sub grid variability of soil water retention and hydraulic conductivity curves |
| url | https://www.earth-syst-sci-data.net/9/529/2017/essd-9-529-2017.pdf |
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