Soil hydraulic properties are necessary for many studies of water and solute transport but often cannot be measured because of practical and/or financial constraints. We describe a computer program, rosetta, which implements five hierarchical pedotransfer functions (PTFs) for the estimation of water retention, and the saturated and unsaturated hydraulic conductivity. The hierarchy in PTFs allows the estimation of van Genuchten water retention parameters and the saturated hydraulic conductivity using limited (textural classes only) to more extended (texture, bulk density, and one or two water retention points) input data. rosetta is based on neural network analyses combined with the bootstrap method, thus allowing the program to provide uncertainty estimates of the predicted hydraulic parameters. The general performance of rosetta was characterized with coefficients of determination, and root mean square errors (RMSEs). The RMSE values decreased from 0.078 to 0.044cm3cm−3 for water retention when more predictors were used. The RMSE for the saturated conductivity similarly decreased from 0.739 to 0.647 (dimensionless log10 units). The RMSE values for unsaturated conductivity ranged between 0.79 and 1.06, depending on whether measured or estimated retention parameters were used as predictors. Calculated mean errors showed that the PTFs underestimated water retention and the unsaturated hydraulic conductivity at relatively high suctions. rosetta's uncertainty estimates can be used as an indication of model reliability when no hydraulic data are available. The rosetta program comes with a graphical user interface that allows user-friendly access to the PTFs, and can be downloaded from the US Salinity Laboratory website: http://www.ussl.ars.usda.gov/.
原文链接
分享
引用
