Probabilistic analysis of soil water characteristic curves from sandy clay loam

Abstract

It is costly to measure the soil water characteristic curve. A first-order estimate from statistical generalization of experimental data belonging to soils with similar textural and structural properties is useful. A simple approach is to fit the data with a nonlinear function and model the curve-fitting parameters as a random vector. This approach is demonstrated using sandy clay loam data in UNSODA. It was found that the classical lognormal distribution is unable to reproduce the skewness and kurtosis of the curve-fitting parameters accurately. A simple four-term Hermite expansion was found to be more suitable. The Hermite coefficients are determined by minimizing lack-of-fit errors in the 25th, 50th, and 75th quantiles. Copyright ASCE 2008.