Prediction of the penetrometer resistance of soils with models with few parameters

The objective of this paper is to determine to what extent pedotransfer functions, PTFs, can be developed that have few coefficients and which are insensitive to soil type. The use of non-linear PTFs to predict penetrometer resistance of soils from their water status (matric potential, ψ and degree of saturation, S) and bulk density, ρ, appears to require that some other soil property, such as sand content, is known. The use of a logarithmic transformation on the dependent variable, Q and the independent variables, either ψ or Sψ has two effects. Firstly, it linearizes the data and secondly it removes the increasing trend in the residuals of Q. A pedotransfer function derived from fitting log10 Q to log10 Sψ and ρ had 3 parameters that were insensitive to soil type. However, to predict Q on its natural scale, back-transformed values require correction for bias. There is evidence that Sψ is a better descriptor of soil water status than ψ alone with respect to predicting penetrometer resistance. We show that the use of Sψ is preferable for both statistical and physically based reasons. However, we also show that matric potential can work well when using PTFs to predict the strength of soil in the field given the variability in field measurements. We demonstrate how a PTF can be used to predict values of the strength of field soil measured independently.