Developing Pedotransfer Functions for Predicting FC and PWP

ABSTRACT

Using pedotransfer functions (PTF) is a useful way for field capacity (FC) and permanent wilting point (PWP) prediction. The aim of this study was to model PTF to estimate FC and PWP using regression tree (RT) and stepwise multiple linear regressions (SMLR). For this purpose, 165 and 45 soil samples from UNSODA and HYPRES datasets were used for development and validation of new PTFs, respectively. %Clay, geometric mean diameter (dg), and bulk density (BD) were selected as predictor variables due to the highest correlation and lowest multicollinearity. The results showed that clay percentage with W* = 0.89 and dg with W* = −0.57 were the most effective variables to predict PWP and FC, respectively. The RT method had a better performance (R² = 0.80, ME = −0.002 cm³cm⁻³, RMSE = 0.05 cm³cm⁻³ for FC and R² = 0.85, ME = 0.003 cm³cm⁻³, RMSE = 0.03 cm³ cm⁻³ for PWP) than SMLR in estimation of FC and PWP.

KEYWORDS:

• HYPRES
• regression tree
• stepwise multiple linear regression
• UNSODA

Acknowledgments

We would like to acknowledge Dr. Meysam Zare and Dr. Hadi Taleb for helping us in providing data.