Rainfall erosivity map for Brazil
Introduction
The universal soil loss equation (USLE) is a mathematical model to predict soil loss (Wischmeier and Smith, 1978). It has widely been used to estimate the soil loss and/or to estimate the numerical values of the different components of the erosive process. The USLE is:where A is the rate of soil loss (t ha−1 year−1), R is a factor for annual rainfall erosivity (MJ mm ha−1 h−1 year−1), K is a factor for soil erodibility (t ha h ha−1 MJ−1 mm−1), L is a factor for slope length, S is a factor for slope steepness, C is a factor for cover management, and P is a factor for supporting practices. The last four factors are dimensionless Wischmeier and Smith, 1978, Renard and Freimund, 1994.
The concept of rainfall erosivity presented by Hudson (1971) and Wischmeier and Smith (1978) describes the erosivity as an interaction between kinetic energy of raindrops and the soil surface. This can result in a greater or lower degree of detachment and down-slope transport of soil particles according to the amount of energy and intensity of rain by considering the same soil type, the same topographic conditions, soil cover, and management.
The original method to calculate the erosivity values (R factor) for a storm event requires pluviographical records (Wischmeier and Smith, 1978). This kind of information is difficult to obtain in many parts of the world, and its processing is time-consuming and hardworking (Bertoni and Lombardi Neto, 1990).
In addition, other equations can also estimate, with good accuracy, monthly and/or annual values of rainfall erosivity by using pluviometric records, such as annual and monthly rainfall averages Bertoni and Lombardi Neto, 1990, Renard and Freimund, 1994. For instance, the Fournier index presented in Eq. (2) represents an equation widely used for this purpose.where Cc is the Fournier index, M is monthly value of precipitation (mm) for month x, and P is the annual value of precipitation (mm).
On the one hand, various authors have found good relationships between the Fournier index and annual values of rainfall erosivity Bertoni and Lombardi Neto, 1990, Lombardi Neto and Moldenhauer, 1992, De Oliveira and Medina, 1990, Morais et al., 1991, Val et al., 1986, Oduro-Afriyie, 1996. According to Bertoni and Lombardi Neto (1990), the ideal condition is to compute a data set of at least 20-year rainfall, but it is possible to determine the erosivity using 10-year rainfall records (Lombardi Neto, 2000). Mannaerts and Gabriels (2000) studied rainfall erosivity for Cape Verde Islands by means of 7-year rainfall pluviometric records.
On the other hand, for some regions of the Brazilian territory, some authors have found good relationships with linear or exponential equations (respectively: y=ax+b or y=axb, where x is the storm amount, y is the R factor of the USLE, and a and b are constant) by using also pluviometric data De Oliveira, 1988, Leprun, 1981, Rufino et al., 1993. For Cape Verde Islands, Mannaerts and Gabriels (2000) calculated significant relations with exponential equation by considering storms greater than 9 mm (erosive storms).
After calculation of erosivity values for a region, erosivity maps, named Isoerodent maps, can be established by interpolating the data and application of GIS technology. For instance, Wischmeier and Smith (1978) published the Isoerodent map for the USA, Leprun (1981) developed the Isoerodent map for the Brazilian northeastern region, Bertoni and Lombardi Neto (1990) for Sao Paulo state (Brazil), and Qi et al. (2000) for the Republic of Korea.
The Isoerodent map represents an important source of information about the potential of erosion for a region. According to Pereira et al. (1994), some guidelines have been established for Brazil to generate standardized information about erosion, more specifically, about soil erodibility, rainfall erosivity, and other factors linked to erosion. Regarding rainfall erosivity, Pereira et al. (1994) also stated that it is important “to study and evaluate the patterns of distribution of the rainfall erosivity and the possible effects about its variability and competence to cause soil erosion.”
Erosivity maps can be useful for soil conservationists and agronomists to get knowledge about rainfall erosivity potential for certain locations in order to implement the necessary precautions to minimize soil erosion in those areas. Civil and construction engineers may also utilize the map for the design and construction of buildings, roads, dams, and pipelines (Oduro-Afriyie, 1996).
Based on these considerations, the goal of this paper was to create a rainfall erosivity map for Brazil and to study some spatial and temporal characteristics of rainfall erosivity within the study area.
Section snippets
Materials and methods
Pluviometric records were obtained from 1600 weather stations in Brazil. The record lengths were at least 10 years, but most of the stations had a continuous recording more than 20 years.
The equations used to determine the monthly/annual erosivity values were obtained by literature (Fig. 1). Some relationships use the Fournier index, while others use linear or exponential equations. The regions whereupon the equation was applied were chosen according to geographic distribution of the annual
Results and discussion
Fig. 2 shows both annual pluviometric and the annual erosivity maps. The pluviometric map corresponds to the map created at the Brazilian Institute for Meteorology (2003) and was used to allow the comparison between spatial distribution of the annual rainfall depth and the geographic distribution of annual rainfall erosivity.
The annual rainfall erosivity map shows a range of 3116 to 20,035 MJ mm ha−1 h−1 year−1. The region with the lowest values is represented by the northeastern region, while
Conclusion
The annual rainfall erosivity in Brazil ranged from 3116 to 20,035 MJ mm ha−1 h−1 year−1, whereupon the northwestern region presented the highest values of annual erosivity, while the northeastern region showed the lowest annual values. The major part of the study area (68.8%) revealed annual erosivity values classified as strong or very strong. The maps presented are useful to illustrate how rainfall erosivity influences soil erosion and to deliver an important source of information for
Acknowledgements
The author is grateful for all who contributed to send rainfall data sets of the regions of Brazil. He is also grateful to Cleber Salimon (CENA-USP) and the Uwe Herpin (NUPEGEL-USP) for corrections and suggestions.
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