The R-factor –rainfall erosivity– is defined as the capacity of rainfall to cause soil loss by water. The R-factor is one of the six factors in the Universal Soil Loss Equation-USLE (Wischmeier and Smith, 1978) and its revised versions. Due to the irregular distribution of precipitation, in time and space, rainfall erosivity (R-factor) can be computed and mapped. Thus, a rainfall event is considered an erosive one when the rainfall is effective in terms of sediment yield. Soil degradation studies show that sediment load transported by natural streamflow is closely linked to rainfall erosivity and that the 12.7 mm threshold presented by Wischmeier and Smith (1978) is often excessive. Denis et al. (2013) adopted an erosive rainfall threshold of 2.5 mm for a semiarid region in India. Mannaerts and Gabriels (2000) have used a threshold of 9 mm to characterize erosive rainfall in Cape Verde, and Xie et al. (2016) have estimated the threshold at 9.7 mm for China. According to McGregor et al. (1995) and Xie et al. (2002), a decrease in the erosive rainfall threshold generates an insignificant increase in the quantification of sediment production.
Wischmeier and Smith (1978) and Renard and Freimund (1994) have shown that R is strongly linked to soil loss worldwide. The USLE is the most widely used equation worldwide to calculate soil loss. The R term in this equation represents the mean total annual of the rainfall erosivity index (EI30). Estimation of this index requires long series of short-term rain gauge measurements. For each rainfall event, EI30 is calculated as the product of the kinetic energy of rainfall (E) and the maximum intensity over 30 min. To estimate R, many relationships based on annual or monthly rainfall, and on the Fournier index or modified Fournier index, have been developed.
Added to that, a few computer programs capable to assist on the computation of rainfall erosivity: Chuveros, NetErosividade, Climate Generator (CLIGEN), Rainfall Intensity Summarization Tool (RIST), and Web ERosivity Module (WERM).
Northern Algeria is characterized by high spatial-temporal variability in erosion intensity in response to sparse vegetation and irregular and aggressive climate. In addition to the climate irregularity, the disparity observed between the various rainfall erosivity estimates quoted in the literature review is mainly due to the large panoply of approaches and models used to estimate such parameter. Furthermore, most of the models used were elaborated for distant sites and adapted to local studies, neglecting soil and climate conditions.
Faced with this situation and all these formulas and models for calculating the R erosivity-coefficient, several questions arise:
1- What is the best model that can properly estimate the R coefficient taking into account soil and climate conditions;
2- What rain period (over how many years) should be chosen for the results to be representative;
3- How many rain stations (density) must exist in an area where this coefficient will be calculated?
This factor represents the combined effect
of rainfall and runoff on soil erosion. EI30 was the
original R factor used in the USLE. Studies
conducted afterward introduced other
erosivity factors, some of them were
superior to the EI30 index.
At the present time, all storms were
included in the calculation of EI30 in the US Pacific
coast characterized by low intensity
rainfall. In other parts of the US and
the World, a threshold concept is
often used.
Recording rain gauge records for
sufficient period of time (usually more than 20 years)
are needed to calculate a representative EI30 index.
Such data base may not always be available
especially in developing countries. For this case,
a reasonsble approximation for the long term
average EI30 was derived from general rainfall
records.
The erosivity density approach was developed
to estimate R-values and their monthly distribution
for RUSLE1and RUSLE2. Erosivity density is the
ratio of rainfall erosivity to precipitation amount.
It measures the erosivity per unit rainfall depth (mm)
and is expressed in MJ/(ha.mm).
Dear Mohammad H Hussein;
Thank you so much for your precious response
Yes we can well use the density of precipitation and we can also compare the results obtained with those of other methods but is it necessary to have a set number of rain gauges in the study area Or we just take an average value
Dear Kaushik Ghosal
Thank you very much for your response
According to your article, for the Mediterranean areas we must have the hourly, daily rains... ,
otherwise we are obliged to use the MFI as an estimator of the R
Cordially
Rainfall erosivity is the power of rainfall to cause soil erosion by water. The rainfall erosivity index for a rainfall event (energy-intensity values – EI30) is calculated from the total kinetic energy and maximum 30 min intensity of individual events. However, these data are often unavailable in many areas of the world. Have a look at this global scale analysis:
Article Global rainfall erosivity assessment based on high-temporal ...
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