A comprehensive analysis of Universal Soil Loss Equation‐based models at the Sparacia experimental area. Issue 7 (6th January 2020)

• Record Type: Journal Article
• Authors: Bagarello, Vincenzo; Ferro, Vito; Pampalone, Vincenzo
• Is Part Of: Hydrological processes. Volume 34:Issue 7(2020)
• Page Start: 1545
• Page End: 1557
• Publication Date: 2020-01-06
• Subjects: event soil loss -- soil erosion -- soil loss prediction -- USLE‐type erosion models; Hydrology -- Periodicals; Hydrology -- Research -- Periodicals; Hydrologic models -- Periodicals; Hydrological forecasting -- Periodicals; 631.432
• DOI: 10.1002/hyp.13681
• Languages: English
• ISSNs: 0885-6087

Abstract

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 = ( Q R ) b 1 ( EI 30 ) b 2, in which Q R is the event runoff coefficient, EI 30 is the single‐storm erosion index, and b 1 and b 2 are coefficients, was introduced. The rainfall‐runoff erosivity factors of the USLE ( b 1 = 0 and b 2 = 1), USLE‐M ( b 1 = b 2 = 1), USLE‐MB ( b 1 ≠ 1 and b 2 = 1), USLE‐MR ( b 1 = 1 and b 2 ≠ 1), USLE‐MM ( b 1 = b 2 ≠ 1), and USLE‐M2 ( b 1 ≠ b 2 ≠ 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, A eN, collected at the Sparacia (south Italy) site. As expected, the poorest A eN predictions were obtained with the USLE. The observed tendency of this model to overestimate small A eN values and underestimate high A eN values was reduced by introducing in the soil loss prediction model both Q R 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. Abstract : 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 = ( Q R ) b 1 ( EI 30 ) b 2, in which Q R is the event runoff coefficient, EI 30 is the single‐storm erosion index, and b 1 and b 2 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.