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United States Department of Agriculture

Agricultural Research Service


item Rawls, Walter
item Pachepsky, Yakov
item Wosten, Henk
item Nemes, Attila

Submitted to: International Soil Science Congress Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 11/2/2001
Publication Date: 8/14/2002
Citation: N/A

Interpretive Summary:

Technical Abstract: Water retention and hydraulic conductivity are crucial input parameters in any modeling study on water flow and solute transport in soils. Hydraulic characteristics can be obtained from direct laboratory and field measurements. However, these measurements are time consuming. As an alternative, analysis of existing databases of measured soil hydraulic data may result in pedotransfer functions that often prove to be good predictors for missing soil hydraulic characteristics. Examples are presented of different equations describing hydraulic characteristics and of pedotransfer functions used to predict parameters in these equations. Grouping of data prior to pedotransfer function development is discussed as well as the use of different soil properties as predictors. In addition to regression analysis, new techniques such as artificial neural networks, group methods of data handling, and classification and regression trees are increasingly being used for pedotransfer function development. Accuracy and reliability of pedotransfer functions are demonstrated and discussed. Functional evaluation of pedotransfer functions proves to be a good tool to assess the desired accuracy of a pedotransfer function for a specific application. Functional testing of uncertainty in the soil hydraulic input data reveals to what extent variability in calculated modelling results is explained by uncertainty in PTFs. Since PTFs offer sufficient accurate predictions for many model applications, it is recommended that large and reliable global databases of soil hydraulic data are being created.

Last Modified: 05/24/2017
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