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Estimation of Water-Retention Function Using Scaling Theory and Soil Physical Properties

Dep. of Soil Science, Univ. of Reading, London Rd., Reading RG1 5AQ, England

James A. Robinson

Inst. for Irrigation and Salinity Research, Dep. of Agriculture and Rural Affairs, Private Bag, Tatura, Victoria 3616, Australia

Zhenhua Xiao

Inst. of Soil Science, Chinese Academy of Sciences, P.O. Box 821, Nanjing, China

* Corresponding author.

ABSTRACT

Estimation or measurement of water-retention functions is an important part of studies of water balance in soils. Characterization of a spatially variable water-retention function, S(h), where S is degree of saturation, is demonstrated here with a data set from a 2-ha watershed. The soil is classified as Shepparton fine sandy loam. Four common functional forms for S(h) were fitted to the data set using scaling theory and nonlinear regression. Initially, only one model parameter, associated with a scaling factor, was fitted independently to each core. This scaling approach accounts for most of the variability (e.g., r² = 0.975) and an estimate of the residual in S is within the accuracy of field measurement. Using nonlinear regression and fitting both parameters independently does improve r² (= 0.991), but only marginally. Using the scaling approach, an expression of soil physical properties was used in place of the independent parameter. The regression (r² = 0.967) gives values to the coefficients of physical properties in this expression, allowing scale factors to be calculated directly from physical properties. A jack-knife estimation technique was employed to show how well scale factors are calculated from physical properties alone. This methodology accounted for spatial variability adequately, offering a simple, computationally efficient representation in numerical simulation. Other data sets indicated that approach may be useful on a regional scale for clearly defined soil groups.

Received for publication July 5, 1989.