Testing the Universal Soil Loss Equation‐MB equation in plots in Central and South Italy

Stefano, Costanza Di; Pampalone, Vincenzo; Todisco, Francesca; Vergni, Lorenzo; Ferro, Vito

doi:10.1002/hyp.13478

Cited by 10 publications

(15 citation statements)

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“…Finally, the possibility to describe soil erodibility as a combination of a steady and a hydrological component was discussed for both the USLE‐MB and the USLE‐MM according to Bagarello et al () and Di Stefano, Pampalone, Todisco, Vergni, and Ferro ().…”

Section: Methodsmentioning

confidence: 84%

“…According to Bagarello et al () and Di Stefano et al (), the USLE‐MB scheme allows to distinguish between a steady‐state and a hydrological component for the soil erodibility factor. Their premise was that the run‐off erosivity factor,

Q_{R}^{b_{1}}

( b 1 = exponent of the erosivity factor for the USLE‐MB, equal to 1.5202 in this investigation), can physically be related to the flow transport capacity that, according to the Water Erosion Prediction Project scheme (Ferro, ; Nearing, Foster, Lane, & Finkner, ), is proportional to the power 1.2 of the unit discharge (Zhang, Liu, Han, & Zhang, ).…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, using Q R as representative of the unit discharge in the USLE‐MB context, a value of the exponent greater than 1 can physically be explained. The USLE‐MB can then be written as (Bagarello et al, ; Di Stefano et al, ):

A_{eN} = ((), {EI}_{30} Q_{R}^{1.2}) ((), Q_{R}^{b_{1} - 1.2} K_{MB}) .

…”

Section: Discussionmentioning

confidence: 99%

“…A third data set was developed by considering the events yielding the 160 lowest and the 160 highest normalized soil losses, being the total sample size (N = 320) comparable with that of the previously considered low severity (N = 341) and intermediate to high severity (N = 300) sub-data sets. In other words, a comparison was established among calibration scenarios differing with reference to the experimental A eN range but not greatly in terms of sample size.Finally, the possibility to describe soil erodibility as a combination of a steady and a hydrological component was discussed for both the USLE-MB and the USLE-MM according to andDi Stefano, Pampalone, Todisco, Vergni, and Ferro (2019).…”

mentioning

confidence: 99%

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

Bagarello

Ferro

Pampalone

2020

Hydrological Processes

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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.

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Section: Methodsmentioning

confidence: 84%

Q_{R}^{b_{1}}

Section: Discussionmentioning

confidence: 99%

A_{eN} = ((), {EI}_{30} Q_{R}^{1.2}) ((), Q_{R}^{b_{1} - 1.2} K_{MB}) .

…”

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

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

Bagarello

Ferro

Pampalone

2020

Hydrological Processes

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“…Moreover, single, that is, with both site‐independent b 1 exponent and L x S x predictive relationship, USLE‐MM and USLE‐MB models were also successfully tested with reference to another (USLE‐MB, Di Stefano, Pampalone, Todisco, Vergni, & Ferro, ) or other two (USLE‐MM, Bagarello, Ferro, Pampalone, et al, ) stations in Central and Southern Italy with different soils. Each of these single models, which was developed by pooling data of two or three stations together, has a common b 1 exponent for different experimental stations and a site ‐ dependent erodibility factor.…”

Section: Introductionmentioning

confidence: 99%

Estimating soil loss of given return period by USLE‐M‐type models

Pampalone

Ferro

2020

Hydrological Processes

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Many field investigations have clearly shown that rare and severe events control total soil erosion occurring over a long time period with up to 92% of total soil erosion over a 7-year period resulting from just three daily events. Therefore, soil conservation strategies should be developed taking into account large events rather than longterm average erosion. From an engineering point of view, establishing the soil loss of a given return period is needed. This can be obtained by the frequency analysis of soil loss measurements or by suitable soil erosion models. The USLE-M modified and USLE-M based are two empirical Universal Soil Loss Equation-Modified (USLE-M) type models which were developed using runoff and soil loss measurements collected at the Sparacia (South Italy) station. According to USLE-M type models, the return period of the estimated soil loss coincides with that of the rainfall-runoff erosivity index. In this investigation, using the maximum annual values of event soil loss measured on bare plots at Sparacia, this hypothesis was recognized to be not valid. To overcame this limit, a parameterization method which imposes the coincidence of the two return periods was applied. The models, which were parameterized by the maximum annual values of event soil loss, produced only moderate improvements in the prediction of the soil loss of given return period as compared with their previously published versions, which were parameterized by all available measurements. This result induced to hypothesize that parameterization of the USLE-MM and the USLE-MB models useful to estimate the soil loss of given return period in other sites can be also performed with all available data, not only with the maximum annual event soil losses which would require a larger number of recording years to obtain a suitable sample size. However, the developed database should span a wide soil loss measurement range. In general, at Sparacia both USLE-MM and USLE-MB were able to yield accurate predictions for return period ranging from 4 to 20 years. K E Y W O R D Sannual maxima, plot measurements, return period, soil erosion, USLE-MB, USLE-MM

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Influence of the Rainfall Time Step on the Thresholds for Separating Erosive and Non-erosive Events

Vergni

Vinci

Todisco

2023

Lecture Notes in Civil Engineering

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Testing the Universal Soil Loss Equation‐MB equation in plots in Central and South Italy

Cited by 10 publications

References 58 publications

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

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

Estimating soil loss of given return period by USLE‐M‐type models

Influence of the Rainfall Time Step on the Thresholds for Separating Erosive and Non-erosive Events

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