Search results for " USLE-M"
showing 8 items of 8 documents
Verifica sperimentale del fattore L della USLE-MM nell’area di Sparacia
2012
Stima dell'erosione idrica parcellare in due siti sperimentali italiani
2011
Predicting soil loss in central and south Italy with a single USLE-MM model
2018
Purpose: The USLE-MM estimates event normalized plot soil loss, Ae,N, by an erosivity term given by the runoff coefficient, QR, times the single-storm erosion index, EI30, raised to an exponent b1> 1. This modeling scheme is based on an expected power relationship, with an exponent greater than one, between event sediment concentration, Ce, and the EI30/Pe(Pe= rainfall depth) term. In this investigation, carried out at the three experimental sites of Bagnara, Masse, and Sparacia, in Italy; the soundness of the USLE-MM scheme was tested. Materials and methods: A total of 1192 (Ae,N, QREI30) data pairs were used to parameterize the model both locally and considering all sites simultaneously. …
Sulla stima del fattore colturale della USLE-MM per coperture forestali ad eucalitto
2011
Il fattore colturale C della Universal Soil Loss Equation (USLE) esprime l’efficacia antierosiva della copertura vegetale nei riguardi del suolo. Per il caso di terreni coltivati esso varia con la rotazione colturale, con le pratiche agronomiche, con il livello di produttività del suolo, con la durata delle varie fasi vegetative e con la distribuzione temporale delle precipitazioni. Nell’ambito di suoli caratterizzati da copertura forestale il fattore C risulta legato, oltre che alle precipitazioni, anche alla percentuale di suolo effettivamente coperto, alla presenza o meno di pascolo, alle pratiche selvicolturali (tagli), al verificarsi di danni a seguito di incendi o fitopatologie, all’e…
Testing the Universal Soil Loss Equation-MB equation in plots in Central and South Italy
2019
Planning soil conservation strategies requires predictive techniques at event scale because a large percentage of soil loss over a long-time period is due to relatively few large storms. Considering runoff is expected to improve soil loss predictions and allows relation of the process-oriented approach with the empirical one, furthermore, the effects of detachment and transport on soil erosion processes can be distinguished by a runoff component. In this paper, the empirical model USLE-MB (USLE-M based), including a rainfall-runoff erosivity factor in which the event rainfall erosivity index EI30 of the Universal Soil Loss Equation (USLE) multiplies the runoff coefficient QR raised to an ex…
Statistical check of USLE-M and USLE-MM to predict bare plot soil loss in two Italian environments
2018
The USLE-M and the USLE-MM estimate event plot soil loss. In both models, the erosivity term is given by the runoff coefficient, QR, times the single-storm erosion index, EI30. In the USLE-MM, QREI30is raised to an exponent b1> 1 whereas b1= 1 is assumed in the USLE-M. Simple linear regression analysis can be applied to parameterize both models, but logarithmically transformed data have to be used for USLE-MM. Parameterizing the USLE-MM with nonlinear regression of untransformed data could be a more appropriate procedure. A statistical check of the two suggested models (USLE-M and USLE-MM), considering two alternative parameterization procedures for the USLE-MM, was carried out for the Mass…
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…