Assessing rainfall erosivity indices through synthetic precipitation series and artificial neural networks

作者：Cecilio Roberto A^*; Moreira Michel C; Pezzopane Jose Eduardo M; Pruski Fernando F; Fukunaga Danilo C

来源：Anais da Academia Brasileira de Ciencias, 2013, 85(4): 1523-1535.

DOI：10.1590/0001-3765201398012

• interpolation
• rainfall generator
• soil conservation
• universal soil loss equation

The rainfall parameter that expresses the capacity to promote soil erosion is called rainfall erosivity (R), and is commonly represented by the indexes EI30 and KE>25. The calculations of these indexes requires pluviographical records, that are difficult to obtain in Brazil. This paper describes the use of synthetic rainfall series to compute EI30 and KE>25 in Espirito Santo State (Brazil). Artificial neural networks (ANNs) were also developed to spatially interpolate R values in Espirito Santo. EI30 and KE>25 indexes values were close to those calculated on a homogeneous area according to the similarity of rainfall distribution; indicating the applicability of the use of synthetic rainfall series to estimate the R factor. ANNs had a better performance than Inverse Distance Weighted and Kriging to spatially interpolate rainfall erosivity values in the State of Espirito Santo.

• 出版日期2013-12