NDLI: Comparative Evaluation of the Rainfall Erosivity in the Rieti Province, Central Italy, Using Empirical Formulas and a Stochastic Rainfall Generator

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Comparative Evaluation of the Rainfall Erosivity in the Rieti Province, Central Italy, Using Empirical Formulas and a Stochastic Rainfall Generator

Content Provider	MDPI
Author	Petroselli, Andrea Apollonio, Ciro Luca, Davide Luciano De Salvaneschi, Pietro Pecci, Massimo Marras, Tatiana Schirone, Bartolomeo
Copyright Year	2021
Description	Soil erosion caused by intense rainfall events is one of the major problems affecting agricultural and forest ecosystems. The Universal Soil Loss Equation (USLE) is probably the most adopted approach for rainfall erosivity estimation, but in order to be properly employed it needs high resolution rainfall data which are often unavailable. In this case, empirical formulas, employing aggregated rainfall data, are commonly used. In this work, we select 12 empirical formulas for the estimation of the USLE rainfall erosivity in order to assess their reliability. Moreover, we used a Stochastic Rainfall Generator (SRG) to simulate a long and high-resolution rainfall time series with the aim of assessing its application to rainfall erosivity estimations. From the analysis, performed in the Rieti province of Central Italy, we identified three equations which seem to provide better results. Moreover, the use of the selected SRG seems promising and it could help in solving the problem of hydrological data scarcity and consequently guarantee major accuracy in soil erosion estimation.
Starting Page	171
e-ISSN	23065338
DOI	10.3390/hydrology8040171
Journal	Hydrology
Issue Number	4
Volume Number	8
Language	English
Publisher	MDPI
Publisher Date	2021-11-19
Access Restriction	Open
Subject Keyword	Hydrology Soil Erosion Soil Loss Rainfall Erosivity R-factor Rieti Province Synthetic Rainfall Generator Usle
Content Type	Text
Resource Type	Article

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