Soil erodibility and its prediction in semi-arid regions

Abstract

Pedotransfer functions (PTFs) have been used to save time and cost in predicting certain soil properties, such as soil erodibility (<i>K</i>-factor). The main objectives of this study were to develop appropriate PTFs to predict the <i>K</i>-factor, and then compare new PTFs with Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE) <i>K</i>-factor models. The <i>K</i>-factor was measured using 40 erosion plots under natural rainfall in Simakan Watershed, an area of 350 km² in central of Iran. The Regression Tree (RT) and Multiple Linear Regression (MLR) were used to develop PTFs for predicting the <i>K</i>-factor. The result showed that the mean of measured <i>K</i> was 0.01 t h MJ⁻¹ mm⁻¹. The mean <i>K</i> value predicted by USLE and RUSLE was 2.08 and 2.84 times more than the measured <i>K</i>, respectively. Although calcium carbonate was not considered in the original USLE and RUSLE <i>K</i>-factors, it appeared in the advanced PTFs due to its strong positive significant impact on aggregate stability and soil infiltration rate, resulting in decreased <i>K</i>-factor. The results also showed that the RT with R² = 0.84 had higher performance than developed MLR, USLE and RUSLE for the <i>K</i> estimation.