Sensitivity analysis of point and parametric pedotransfer functions for estimating water retention of soils in Algeria

Abstract

Improving the accuracy of pedotransfer functions (PTFs) requires studying how prediction uncertainty can be apportioned to different sources of uncertainty in inputs. In this study, the question addressed was as follows: which variable input is the main or best complementary predictor of water retention, and at which water potential? Two approaches were adopted to generate PTFs: multiple linear regressions (MLRs) for point PTFs and multiple nonlinear regressions (MNLRs) for parametric PTFs. Reliability tests showed that point PTFs provided better estimates than parametric PTFs (root mean square error, RMSE: 0.0414 and 0.0444 cm3 cm−3, and 0.0613 and 0.0605 cm3 cm−3 at −33 and −1500 kPa, respectively). The local parametric PTFs provided better estimates than Rosetta PTFs at −33 kPa. No significant difference in accuracy, however, was found between the parametric PTFs and Rosetta H2 at −1500 kPa with RMSE values of 0.0605 cm3 cm−3 and 0.0636 cm3 cm−3, respectively. The results of global sensitivity analyses (GSAs) showed that the mathematical formalism of PTFs and their input variables reacted differently in terms of point pressure and texture. The point and parametric PTFs were sensitive mainly to the sand fraction in the fine- and medium-textural classes. The use of clay percentage (C %) and bulk density (BD) as inputs in the medium-textural class improved the estimation of PTFs at −33 kPa.