USING THE GREGSON ONE-PARAMETER MODEL TO ESTIMATE THE SOIL-WATER RETENTION.

Authors: Williams, Robert; Ahuja, Lajpat

Submitted to: Soil Dynamics International Conference Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 10/1/1999
Publication Date: 3/26/2000
Citation: Williams, R.D., Ahuja, L.R. 2000. Using the gregson one-parameter model to estimate the soil-water retention. In: Proc. 4th Intl. Conf. on Soil Dynamics (ICSD-IV), Adelaide, South Australia. CD-ROM.

Interpretive Summary: Computer models for complex soil-water process and crop growth have demonstrated potential for improving management. However, these models require knowledge of the soil water retention curve. This curve is the relationship between the soil matric potential and the volumetric water content. Basically it tells us how much water is available for plant growth as the soil progresses from a 'wet' to a 'dry' condition. The soil water retention curve varies from soil to soil and even within a soil. It is difficult to measure; the measurement are both tedious and time consuming. Therefore, to use the models for soil-water movement or crop growth, we need accurate methods to predict the curve from soil texture or other easily measured soil properties. The one-parameter model is based on the log-log form of the water retention curve. The model requires one known water content value, which can be estimated using soil texture and bulk density, and a generalized slope-intercept relationship. Here it is shown that the slope-intercept relationship can be based on textural values of bubbling pressure and soil porosity that are readily available in the literature. This makes the model simple to use. It can be easily incorporated into various soil-water or crop models.

Technical Abstract: The one-parameter model is based on the log-log form of the soil water retention curve below the air-entry matric potential, requires one known value of soil matric potential (psi) and volumetric water content (theta), and a generalized slope-intercept relationship (p and q). This provides the general form of the model: ln(psi) = p + b(ln(theta)+q). Given p and q values for a soil or group of soils, the known ( ) value is used to calculate the only unknown parameter, b. Recently it was demonstrated that p equals the natural log of the air-entry pressure (ln(psi-sub "b")) and q equals the natural log of the saturated water content (ln(theta-sub "sat"). Here we demonstrate the use of these p and q values on ten U.S. soils with a wide range of textures. Overall the model estimates the volumetric water content quite well. Calculated mean errors and root-mean-square errors, regardless of matric potential, ranged from 0.001 to 0.052 m^3/m^3 (absolute value) and 0.019 to 0.089 m^3/m^3, respectively. The soils which produced the larger estimations errors with the model were Commerce (loam), Bangor (silt loam), Sequoia (silty clay) and Dunmore (clay). However, even in these cases the errors and scatter around the 1:1 line were no worse than those found when regression models based on texture, bulk density and organic matter are used to estimate soil water content.