Previous experimental investigations showed that a large proportion of total plot soil erosion over a long time period is generally due to relatively few, large storms. Consequently, erosion models able to accurately predict the highest plot soil loss values have practical importance since they could allow to improve the design of soil conservation practices in an area of interest. At present USLE-based models are attractive from a practical point of view, since the input data are generally easy to obtain. The USLE was developed with specific reference to the mean annual temporal scale but it was also applied at the event scale. Other models, such as the USLE-M and the USLE-MM, appear in principle more suitable to predict soil loss at this last temporal scale, because they include event plot runoff as an additional variable. At first in this investigation, carried out by using plot data collected at the experimental station of Sparacia, in Sicily (length, λ = 11–44 m, slope steepness, s = 14.9–26.0%), the circumstance that a single event in the year was responsible of approximately the 75% of total erosion during that year was recognized. Then the suitability of the USLE-derived models to predict maximum annual values of event soil loss was tested by measured events in all experimental plots (570 soil loss values for the complete data set, and 57 values for the data set of the maximum annual soil loss), in the period January 2002–March 2015, at Sparacia experimental area. This analysis showed the best model performance of USLE-MM schemes (Nash and Sutcliffe index, NSEI > 0.70) to determine the annual maxima of event soil, compared with the classical parameterization of USLE (NSEI = 0.32). The development of methodologies widely applicable for estimating both the soil erodibility factor and the plot runoff coefficient will represent a step towards a diffuse application of this model.
|Number of pages||10|
|Publication status||Published - 2017|
All Science Journal Classification (ASJC) codes
- Earth-Surface Processes