Search results for "soil loss prediction"

showing 4 items of 4 documents

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

2020

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 t…

USLE-type erosion modelssoil erosion010504 meteorology & atmospheric sciencesevent soil lo0207 environmental engineeringsoil loss prediction02 engineering and technology01 natural sciencesPlot (graphics)Term (time)Data setUniversal Soil Loss EquationStatisticsExponentErosionSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-Forestali020701 environmental engineeringSurface runoff0105 earth and related environmental sciencesWater Science and TechnologyEvent (probability theory)Mathematics
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Comment on “Determining soil erodibility for the USLE-MM rainfall erosion model by P.I.A. Kinnell”

2018

Abstract The measurements units of the USLE-MM soil erodibility factor are dependent on the exponent of the erosivity term. This circumstance prevents to compare soil erodibility values of sites differing by the value of this exponent. To overcame this problem, Kinnell (2018) suggested to relate the soil erodibility factor of the USLE-MM with that of USLE-M by a linear relationship with the objective to obtain a soil erodibility factor independent of the power of the erosivity term. The USLE-MB, which is a recently proposed model, has also a soil erodibility factor having measurement units common to USLE modelling environment. Kinnell (2018) also showed that the relationship between the pow…

Linear relationshipSoil loss prediction0208 environmental biotechnologyErosionSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliSoil science02 engineering and technologyErosion plot020801 environmental engineeringMathematicsEarth-Surface Processes
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A Comprehensive Check of Usle-Based Soil Loss Prediction Models at the Sparacia (South Italy) Site

2020

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, b2 = 1), USLE-M (b1 = b2 = 1), USLE-MB (b1 ≠ 1, b2 = 1), USLE-MR (b1 = 1, 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 dataset of normalized bare plot soil losses, AeN, collected at the Sparacia (south Italy) site. As expected, the poorest AeN predict…

Runoff coefficientUSLE-type erosion modelsSoil lossSoil loss predictionStatisticsExponentEvent soil loSoil erosionSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliPredictive modellingPlot (graphics)MathematicsEvent (probability theory)
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Predicting event soil loss from bare plots at two Italian sites

2013

Abstract Including runoff in USLE-type empirical models is expected to improve plot soil loss prediction at the event temporal scale and literature yields encouraging signs of the possibility to simply estimate runoff at these spatial and temporal scales. The objective of this paper was to develop an estimating procedure of event soil loss from bare plots (length = 11–44 m, slope steepness = 14.9–16.0%) at two Italian sites, i.e. Masse, in Umbria, and Sparacia, in Sicily, having a similar sand content (5–7%) but different silt (33% at Sparacia, 59% at Masse) and clay (62% and 34%, respectively) contents. A test of alternative erosivity indices for the Masse station showed that the best perf…

HydrologyEmpirical modellingSoil scienceSiltSoil water erosion Soil loss prediction Empirical models USLE-MUSLE-MMSoil lossEmpirical modelSoil loss predictionEmpirical modelsErosionSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliUSLE-MUSLE-MMEnvironmental scienceSoil water erosionTemporal scalesSurface runoffScale (map)Earth-Surface ProcessesEvent (probability theory)CATENA
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