Pedotransfer functions: bridging the gap between available basic soil data and missing soil hydraulic characteristics

Water retention and hydraulic conductivity are crucial input parameters in any modelling study on water flow and solute transport in soils. Due to inherent temporal and spatial variability in these hydraulic characteristics, large numbers of samples are required to properly characterise areas of land. Hydraulic characteristics can be obtained from direct laboratory and field measurements. However, these measurements are time consuming which makes it costly to characterise an area of land. As an alternative, analysis of existing databases of measured soil hydraulic data may result in pedotransfer functions. In practise, these functions 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. Actual development of pedotransfer functions is demonstrated by describing a practical case study. Examples are presented of pedotransfer function for predicting other than hydraulic characteristics. Accuracy and reliability of pedotransfer functions are demonstrated and discussed. In this respect, functional evaluation of pedotransfer functions proves to be a good tool to assess the desired accuracy of a pedotransfer function for a specific application.