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Mallants, Dirk1; Mohanty, Binayak P.2; Jacques, Diederik1; Feyen, Jan1

Technical Article

Unsaturated hydraulic properties of field soils are needed for water flow and solute transport calculations in variably saturated soils. The purpose of this study was to quantify the spatial variability and spatial crosscorrelation of estimated parameter values of a flexible retention model that was fitted to measured retention data. Moisture retention characteristic (MRC) curves were measured on 100-cm3 undisturbed soil cores collected at 180 locations along a 31-m-long transect in a three-layered soil profile at depths of 0.1, 0.5, and 0.9 m. Sampling intervals in the horizontal direction were, alternately, 0.1 and 0.9 m. Saturated hydraulic conductivity (Ks) was determined on the same soil cores using a constant head permeameter. The drying part of the MRC curves was described by the four-parameter retention model of van Genuchten with fitting parameters, namely θr, θs, α, and n. Spatial variability of the five parameters, θr, θs, α, n, and Ks, was investigated for the three horizons using conventional statistics and geostatistical techniques. Maximum coefficient of variation (CV) was found for Ks, i.e., 599%, 322%, and 897% for the 0.1-, 0.5-, and 0.9-m soil depths, respectively. Macropores and small sampling volume contributed to this large variability of Ks. When all three soil depths are considered, residual water content (θr) and shape factor α showed moderate heterogeneity with a maximum CV of 156 and 53%, respectively. Small spatial heterogeneity was observed for shape factor n and saturated water content θs, with a maximum CV of 22 (for 0.1-m depth) and 8% (for 0.9-m depth), respectively. Most hydraulic parameters at different layers exhibited convex experimental semivariograms that could be described by means of spherical models, with a spatial range between 4 and 7 m. The correlation scales for cross-semivariograms for pairs of cross-correlated parameters were found to be of similar magnitude to those pertaining to the direct semivariograms of correlated variables.

1 Institute for Land and Water Management, Faculty of Agricultural and Applied Biological Sciences, Katholieke Universiteit Leuven, Leuven, Belgium. Dr. Mallants is corresponding author. E-mail:

2 U.S. Salinity Laboratory, USDA-ARS, Riverside, California.

Received July 10, 1995; accepted Nov. 30, 1995.

© Williams & Wilkins 1996. All Rights Reserved.