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Parameter Uncertainty Analysis of Common Infiltration Models

Dep. of Land, Air and Water Resources, Univ. of California, Davis, CA 95616

J. L. Starr

USDA-ARS, Beltsville, MD 20705

*Corresponding author (jwhopmans{at}ucdavis.edu).

ABSTRACT

Water infiltration is a driving force influencing crop growth, soil erosion, and chemical leaching processes. Knowledge of the relative precision and accuracy of infiltration models is needed for best characterization of the infiltration parameters. The two-parameter Green-Ampt and Philip, three-parameter Horton, Mezencev, Swartzendruber, and Parlange et al., and four-parameter Barry et al. infiltration models were compared for their precision and accuracy of estimated parameter confidence intervals using simulated infiltration reference data. To account for potential levels of uncertainty, three levels of measurement error were included using a Monte Carlo analysis. Reference data were generated for a clay and a sandy loam soil using an adaptive-grid finite-element code. Results show that extending the measurement period provided parameter estimates with higher confidence, a more precise estimate of that confidence, and better defined minima in the objective function. The empirical Horton model resulted in the worst fits due to model bias, which also prevented estimation of parameter uncertainty for this model. The semianalytical Swartzendruber and the physically based Parlange et al. and Barry et al. models provided the best fits. Considering all selected criteria, the Swartzendruber model was a reasonable compromise under the conditions imposed in this study.

Received for publication September 29, 1997.

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