Point Pedotransfer Functions (PPTF) for Estimating Soil Water Retention Curve by Multiple Linear Regression Methods

Abstract

Abstract The aim of this study was to derive and find the best Point Pedotransfer Functions (PPTF) for estimating SWRC for Iraqi soils using the multiple regression methods. Soil samples were collected from 30 different sites of Iraqi soil at two depths: 0-0.3 m and 0.3-0.6 m, in order to obtain the required database for the derivation of PTF, which includes the soil particle size distribution, carbonate minerals, bulk density, particles density, organic matter, saturated hydraulic conductivity, capillary height and the boundaries of available water. Measured characteristics were considered as explanatory variables (EV). Volumetric water content was measured at suctions 0, -5, -10, -33, -500, -100, -500, -1000, and -1500 kPa and considered as response variables (RV). PPTF was derived using SAS statistical software based on multiple linear regression. Three methods for fitting the PPTF to EV were Maximum R2 Improvement (MR), Backward Elimination (BW) and Forward selection (FW). The prediction accuracy was evaluated through Mean Bias Error (MBE), Mean Absolute Error (MAE), root mean squared error (RMSE) and Coefficient Of Determination (R2). The results showed that all EVs were included in the PPFT derivation by MR method, while in the BW and FW methods the significant level of entery (SLENTRY) of EV was 0.1. It was also found that variables w1, capillary height, available water, bulk density, and porosity were included in the derivation of most of the models using the BW and FW method. Besides no statistically significant differences were found among the values of MBE, MAE, RMSE, and R2 of the PPTF although the number of selected EV are different.