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United States Department of Agriculture

Agricultural Research Service


item Nemes, Attila
item Rawls, Walter

Submitted to: Elsevier
Publication Type: Book / Chapter
Publication Acceptance Date: 5/27/2004
Publication Date: 12/15/2004
Citation: Nemes, A., Rawls, W.J. 2004. Soil texture and particle distribution as estimation of soil hydrology. Elsevier Development in Soil Sciences. Amsterdam, The Netherlands: Elsevier. 30(4):47-64.

Interpretive Summary:

Technical Abstract: Soil texture represents the relative proportion of soil particles with different sizes, which is a fundamental physical property of soils, correlated to just any other soil property. Soil hydraulic properties are difficult to determine, especially for large areas of land. Predictive models to estimate soil hydraulic properties ' mostly termed pedotransfer functions (PTFs) 'usually use soil texture and/or particle-size data as their most basic input. Most commonly, the particle-size distribution (PSD) is represented in a texture diagram based on the sand, silt and clay content of a soil. However, different standards exist and are in use to characterize and describe soil texture as well as soil PSD. In the following, we give an overview on how soil texture can be characterized and described, how those data are considered in different PTFs and what methods are known that can be used to fill in missing data required by some PTFs. We also show a study that compares different representations of soil PSD in estimating soil water retention.Overall, we could not point at one particular representation of the PSD that would clearly provide better results in estimating the selected soil hydraulic properties. Results are extremely heterogeneous. Although results in general were not considerably worse, instances for largest RMSRs were found while water content at '10 and '33 kPa were estimated. This can partly be explained by the wider range of water contents at these matric potentials. Another reason is that soil hydraulic properties at these matric potentials are largely affected by soil structure, which is not accounted for in any of our models. We found no evidence suggesting that using interpolated data would reduce the accuracy of the estimation of these soil hydraulic properties. Our study suggests that using interpolated data ' which of course carries a certain magnitude of interpolation error - poses fewer risks in a PTF than using measured data with the wrong silt/sand boundary.

Last Modified: 10/19/2017
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