Variations in soil erodibility (K-factor) for the Chernozems depending on the method of texture determination

Soil erodibility (K-factor) is an important parameter in erosion modeling, is one of five factors of the Revised Universal Soil Loss Equation (RUSLE), and generally represents the soil's response to rainfall and run-off erosivity. The erodibility could be determined based on direct measurements of soil properties and mathematical calculations. In this study, the K-factor was calculated based on a formula from RUSLE, proposed by Renard et al. (1997). All input parameters: soil organic carbon (SOC), soil structure, and permeability classes were measured by one method, but particle size distribution - in two ways by sedimentation and laser diffraction methods to assess the impact the K-factor variability and the values of soil erosion rates. The 107 soil samples of Chernozems from Kursk Oblast (Russia) were studied. The texture for the most of samples was classified as silty loam in both analyses. However, the laser diffraction underestimates the clay content by an average of 13.2 % compared to the pipette method. The average K-factor estimated based on laser diffraction data was 0.050, and 0.034 t ha h ha^-1 MJ^-1 mm^-1 - sedimentation method. Thus, depending on the method of soil texture analysis, the RUSLE calculated soil loss could underestimated/overstated by 32 % (or 4 t ha^-1 yr^-1 on average in the study site). Therefore, we propose a regression equation-based conversion method of laser diffraction data to sedimentation method data for Chernozems.•The Laska-TM laser analyzer measured on ∼ 13 % less clay fraction (more on ∼ 8 % silt and ∼ 5 % fine sand) compared with sedimentation method data.•For erosional researchers/modelers it is suggested to state the method of soil texture analysis (based on sedimentation law or laser diffraction) was used for RUSLE K-factor calculations.•To convert K-factor values (for Chernozems) calculated and based on data of the sedimentation method to laser sedimentation - it suggested utilize the coefficient 1.47 (0.68 - vice versa).