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

• Published in: Hydrological processes 2020-03, Vol.34 (7), p.1545-1557
• Main Authors: Bagarello, Vincenzo, Ferro, Vito, Pampalone, Vincenzo
• Format: Article
• Language: English
• Subjects: Coefficients; Data; Datasets; event soil loss; Land management; Mathematical models; Prediction models; Rain; Rainfall; Runoff; Runoff coefficient; Soil; Soil analysis; Soil erosion; Soil improvement; Soil loss; soil loss prediction; Soils; Storms; Sustainability management; USLE‐type erosion models
• ISSN: 0885-6087; 1099-1085
• DOI: 10.1002/hyp.13681

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. Improving USLE‐based soil loss prediction models has large interest because simple and reliable analytical tools are necessary for a sustainable land management. The event rainfall‐ runoff erosivity factor 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 tested by data collected at the Sparacia site (Sicily, South Italy) on plots of 11 to 44 m in length and 9% to 26% in steepness. The USLE‐MB and the USLE‐MM, among the possible alternatives, were recognized to be the best performing models.