A comprehensive analysis of Universal Soil Loss Equation‐based models at the Sparacia experimental area

Abstract

Improving Universal Soil Loss Equation (USLE)‐based models has large interest because simple and reliable analytical tools are necessary in the perspective of a sustainable land management. At first, in this paper, a general definition of the event rainfall‐ runoff erosivity factor for the USLE‐based models, REFe = (QR)b1(EI30)b2, in which QR is the event runoff coefficient, EI30 is the single‐storm erosion index, and b1 and b2 are coefficients, was introduced. The rainfall‐runoff erosivity factors of the USLE (b1 = 0 and b2 = 1), USLE‐M (b1 = b2 = 1), USLE‐MB (b1 ≠ 1 and b2 = 1), USLE‐MR (b1 = 1 and b2 ≠ 1), USLE‐MM (b1 = b2 ≠ 1), and USLE‐M2 (b1 ≠ b2 ≠ 1) can be defined using REFe. Then the different expressions of REFe were simultaneously tested against a data set of normalized bare plot soil losses, AeN, collected at the Sparacia (south Italy) site. As expected, the poorest AeN predictions were obtained with the USLE. The observed tendency of this model to overestimate small AeN values and underestimate high AeN values was reduced by introducing in the soil loss prediction model both QR and an exponent for the erosivity term. The fitting to the data was poor with the USLE‐MR as compared with the USLE‐MB and the USLE‐MM. Estimating two distinct exponents (USLE‐M2) instead of a single exponent (USLE‐MB, USLE‐MR, and USLE‐MM) did not appreciably improve soil loss prediction. The USLE‐MB and the USLE‐MM were recognized to be the best performing models among the possible alternatives, and they performed similarly with reference to both the complete data set and different sub‐data sets, only including small, intermediate, and severe erosion events. In conclusion, including the runoff coefficient in the soil loss prediction model is important to improve the quality of the predictions, but a great importance has to be paid to the mathematical structure of the model.

Modelling the event‐based hydrological response of olive groves on steep slopes and clayey soils under mulching and tillage management using the SCS‐CN, Horton and USLE‐family models

“…More specifically, Biddoccu et al (2020), applying the RUSLE model to the soils with permanent cover crops, predicted soil losses that were lower or close to soil formation rate in Europe. Bagarello et al (2017, 2020), using the USLE‐M model, reported an underestimation of soil loss for lower‐intensity events.…”

Is marginalised cultivated land on the Tibetan Plateau suitable for production or ecology? An example from the northeastern Tibetan Plateau

“…The MGSLE is one of the most widely used methods for evaluating soil conservation functions, with the advantages of a simple and clear calculation process, easy access to data and high applicability (Bagarello et al, 2020; Kumar et al, 2020). Therefore, this method was used in this study to find the value of the soil conservation function of cultivated land in terms of the difference between the potential soil loss and the actual soil loss, which is the amount of soil conserved.…”

Entropy-Based Temporal Downscaling of Precipitation as Tool for Sediment Delivery Ratio Assessment

“…To estimate gross erosion in the catchments we used the universal soil loss equation (Equation ( 10 )—[ 46 , 54 ]). A more detailed description of each factor and the values for the study areas can be found in the supplements to this paper.…”