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U.S. Salinity Lab., 4500 Glenwood Dr., Riverside, CA 92501
Dep. of Soil and Water Science, Univ. of Arizona, Tucson, AZ 85721
* Corresponding author.
ABSTRACT
A nonlinear least-squares optimization program, RETC, which uses empirical relationships for describing the water-retention curve and predictive models for characterizing the unsaturated hydraulic conductivity relationship was used to analyze 36 unsaturated hydraulic conductivity distributions obtained from the literature for 23 different soils. By comparing the measured, predicted, and estimated relative conductivity for the group of data, the efficiency and accuracy of this approach for characterizing the soil hydraulic properties was determined. The analysis consisted of comparing measured, predicted, and estimated conductivities using three predictive methods and two simultaneous methods (which include known values of the conductivity). The results indicate that for this group of data, the best method for determining the model parameters that will accurately describe both the water retention and unsaturated hydraulic conductivity relationships is to use a simultaneous approach with either five or six parameters. It was also found that the predictive approach introduces a bias into the estimates of the unsaturated hydraulic conductivity and a predictive approach with scaling did not significantly improve the estimates of the unsaturated hydraulic conductivity.
Received for publication September 18, 1990.
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