Submitted to: Journal of Hydrology
Publication Type: Peer reviewed journal
Publication Acceptance Date: 8/15/2001
Publication Date: 9/1/2001
Citation: RAWLS, W.J., PACHEPSKY, Y.A. TESTING THE MUUF PEDOTRANSFER FUNCTIONS WITH THE SOUTHERN PLAIN DATABASE. JOUNAL OF HYDROLOGY. V. 251. P. 177-185. Interpretive Summary: Soil hydraulic properties have often to be estimated rather than measured. Such estimates are made using pedotransfer functions (PTFs), i.e. regression equations relating soil hydraulic properties to soil basic properties. Soil mineralogical composition was proposed as a valuable input variable for PTFs. To characterize the effect of soil minerals on soil hydraulic properties, the clay activity ratio was defined as the ratio of the cation exchange capacity of soil mineral fraction to the clay content in soil. This ratio was utilized in PTFs built from about 18000 national soil characterization database and incorporated in the MUUF software. The MUUF software uses soil name and textural class to generate soil water retention and hydraulic conductivity estimates. Our objective was to test these PTFs with an independent representative data set and to see whether the estimates could be improved by using actual texture instead of the average texture for the textural class. We evaluated the accuracy of estimating water content at matric potentials of 33 kPa and 1500 kPa. The overall accuracy of the MUUF PTFs was better than average as compared with other PTFs found in literature. Soil name and textural class provided sufficient information for PTFs in topsoil, so that using the actual texture did not improve the estimates. In subsoil, the estimates were improved significantly when the actual texture was used. MUUF algorithms provide an efficient tool for estimating soil hydraulic properties to use in applications in hydrology, meteorology, agronomy, and contaminant geochemistry.
Technical Abstract: Soil hydraulic properties have often to be estimated rather than measured. Such estimates are made using pedotransfer functions (PTFs), i.e. regression equations relating soil hydraulic properties to soil basic properties. Soil mineralogical composition may be a valuable input variable for PTFs. The MUUF software was developed to use soil series name and textural class of the uppermost soil horizon to estimate soil water retention. This software contains PTFs that have been developed from about 18000 national soil characterization data base and used the clay activity ratio along with textural components. The objective of this study was twofold: (a) to test the MUUF with Southern Plains data base, and (b) to see whether the MUUF PTFs will be more accurate with actual soil texture data as compared with the soil texture data for the representative pedon of the soil series. The accuracy of estimating water content at 33 kPa and 1500 kPa capillary pressures was evaluated. The root-mean-square error (RMSE) of the MUUF estimates in the uppermost horizon was about 0.04 m3m-3 when only textural class and soil names were used. The accuracy did not change when the actual soil texture was entered in PTFs. In deeper horizons, the RMSE was about 0.065 m3m-3 when only soil name and textural classes were used. The accuracy improved significantly as the actual texture was used instead of the texture derived from the representative pedon. As compared with PTFs found in literature, the MUUF algorithms provide an average or better accuracy of water retention estimates in the uppermost soil horizons from the soil series name and textural class.