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A ONE-PARAMETER RELATIONSHIP BETWEEN UNSATURATED HYDRAULIC CONDUCTIVITY AND WATER RETENTION

Pachepsky, Yakov1; Rawls, Walter1; Timlin, Dennis2

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Estimating unsaturated hydraulic conductivity often relies on using water retention characteristics. Because the water retention curves do not provide information about the pore connectivity, an empirical correction is used in capillary bundle models that are fitted to unsaturated hydraulic conductivity data. The majority of authors have applied the macroscopic correction expressed as a function of water content. A microscopic correction term expressed as a power function of a pore radius was proposed in the literature but was not tested with a large representative soil data set. The purpose of this work was to apply the "hydraulic conductivity-water retention" model with the microscopic connectivity correction to a large data set to see what accuracy can be achieved and whether it is possible to relate the connectivity parameters to some readily available soil properties. Data for 147 soil horizons were extracted from the unsaturated soil hydraulic database UNSODA. Water retention and hydraulic conductivity data were in the range of capillary pressures >5 kPa and from 5 to 200 kPa, respectively. The model provided an accurate approximation, and root mean square error (RMSE) in estimated log10k was 0.21. Two parameters of the model appeared to be correlated closely so that using only one connectivity parameter was sufficient. Reducing the number of parameters from two to one and refitting the one-parametric model to data decreased the accuracy of the estimates. The RMSE increased from 0.21 to 0.31. That only one empirical parameter was needed to describe the unsaturated hydraulic conductivity helps to reduce the number of measurements of this hydraulic property because a single parameter can be estimated from a limited number of observations.

1USDA-ARS Hydrology Laboratory, Bldg. 007, Rm. 104, BARC-WEST, Beltsville, MD 20705. Dr. Papchesky is corresponding author. E-mail: ypachepsky@asrr.arsusda.gov or ypachep@hydrolab.arsusda.gov

2USDA-ARS Remote Sensing and Modeling Laboratory, Bldg. 007, Rm. 116, Beltsville, MD 20705

Received March 15, 2000, accepted Aug. 9, 2000.

© 2000 Lippincott Williams & Wilkins, Inc.