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United States Department of Agriculture

Agricultural Research Service


item Zeiliguer, Anatole
item Nemes, Attila
item Pachepsky, Yakov
item Rawls, Walter
item Wosten, J.

Submitted to: World Congress of Soil Science
Publication Type: Proceedings
Publication Acceptance Date: 4/1/2002
Publication Date: 8/14/2002
Citation: N/A

Interpretive Summary: Measuring parameters of soils' ability to retain and transport water is cost- and labor- intensive. Therefore, estimating those parameters from soil survey data becomes a common practice. Empirical regression equations developed for some regional database are used for the estimation. Unfortunately, such equations appear to be region-specific, and extrapolating them to other regions gives mixed results. Recently we developed physics-based 'additivity' estimation model that is not-region specific and does not contain empirical parameters. This model gave excellent results when tested with data on sandy soils from the multinational ARS database UNSODA. This work had an objective to see whether and what improvements are needed for soils that have substantial amounts of clay. We found that errors of the model were larger in clay soils than in sandy soils, although they remained at the lower end of the range of errors found with empirical regression equations. Patterns of the additivity model errors indicated the need of improving the component of the model responsible for the water retention in dry soils. The US National Soil Characterization data base was used to derive the dependence of the water content at wilting point on the contents of clay, organic carbon, and silt. This dependence allowed us to introduce a correction that gave a 20- 25% decrease in the model's errors in soils with substantial clay contents. Directions of further improvements are discussed. The present status of the additivity model warrants enough accuracy for various applications in hydrology, agrometeorology, agronomy, and contaminant hydrology.

Technical Abstract: One approach to soil water retention estimation is to compute soil water retention by accumulating water retention of pore subspaces associated with soil textural and/or structural components. We developed an 'additivity' model assuming that (a) water retention associated with a textural fraction can be measured on samples consisting exclusively of this fraction's particles, and (b) the additivity is applicable to gravimetric water contents in the range of soil water potentials from -1500 kPa to 0 kPa. This model does not have fitting parameters. The model was tested with data from the UNSODA database on nine textural classes ranging from fine sand to clay. The root mean square errors (RSMEs) of the volumetric water content estimates were at the lower end of the RMSE range for regression-based water retention estimates found in literature. At low water contents, a bias was detected that we attempted to correct assuming that the residual water content depends not only on proportion of clay but also on organic matter content. This correction resulted in RSME values in the range from 2.7 vol. % to 5.3 vol. %. The attained accuracy warrants testing the 'additivity' model with additional data and improving this model to accommodate effects of fine particles on water retention of coarse components.

Last Modified: 10/19/2017
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