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ORIGINAL RESEARCH

Comparison of Models for Indirect Estimation of Water Retention and Available Water in Surface Soils

^a George E. Brown, Jr. Salinity Laboratory, USDA, ARS, 450 W. Big Springs Road, Riverside, CA 92507
^b Research Institute for Soil Science and Agricultural Chemistry of the Hungarian Academy of Sciences, Herman Ottó u. 15, H-1525 Budapest, Hungary, currently at USDA-ARS Hydrology and Remote Sensing Laboratory, USDA, ARS, 10300 Baltimore Ave., Bldg. 007, BARC-West, Beltsville, MD 20705
^* Corresponding author (mschaap{at}ussl.ars.usda.gov)

Received 9 April 2004.

Quantitative knowledge of the unsaturated soil hydraulic properties is required in most studies involving water flow and solute transport in the vadose zone. Unfortunately, direct measurement of such properties is often difficult, expensive and time-consuming. Pedotransfer functions (PTFs) offer a means to estimate soil hydraulic properties based on predictors like texture, bulk density, and other soil variables. In this study, we focus on PTFs for water retention and show that systematic errors in five existing PTFs can be reduced by using water content–based objective functions, instead of parameter value–based objective functions. The alternative analysis was accomplished by establishing offset and slope coefficients for each estimated hydraulic parameter. Subsequently we evaluated these and six other PTFs for estimating water retention parameters using the NRCS soils database. A total of 47435 records containing 113970 observed water contents were used to test the PTFs for mean errors and root mean square errors. No overall superior model was found. Models with many calibration parameters or more input variables were not necessarily better than more simple models. All models underestimated water contents, with values ranging from –0.0086 to –0.0279 cm³ cm^–3. Average root mean square errors ranged from 0.0687 cm³ cm^–3 for a PTF that provided textural class average parameters to 0.0315 cm³ cm^–3 for a model that also used two water retention points as predictors. Available soil water content for vegetation was estimated with errors ranging from 0.058 to 0.080 cm³ cm^–3, depending on the model and the definition of available water.

Abbreviations: AWC, available water content • COS1, Cosby PTF based on univariate regression • COS2, Cosby PTF based on bivariate regression • ME, mean error • PTF, pedotransfer function • RBC, Rawls and Brakensiek PTF with Brooks–Corey parameters • RMSE, root mean square residual • RVG, Rawls and Brakensiek PTF with van Genuchten parameters • URMSE, unbiased root mean square residual • VER, Vereecken PTF • WOE, Wösten PTF

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