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Spatially distributed rainfall erosivity and its seasonal distribution are needed to use the revised universal soil loss equation (RUSLE) for erosion risk assessment at large scale. An erosivity model and 20-year daily rainfall data at 0.05° resolution were used to predict the R- factor and its monthly distribution for RUSLE in Australia. Predicted R- factor values were compared with those previously calculated using pluviograph data for 132 sites around Australia. The daily erosivity model was further evaluated for 43 sites where long-term pluviograph data were available. Predicted and calculated monthly distributions of the R -factor were compared for these 43 sites. For the 132 sites where R- factor values were compiled from previous investigations, the model efficiency was 0.81 with root mean squared error (rmse) of 1832 MJ.mm/(ha.h.year), or 47.5% of the mean for the 132 sites. For the additional 43 sites, the coefficient of efficiency was 0.93 with a 12.7 mm rainfall threshold, and 0.94 when all storms were included in the calculations. The rmse was 908 MJ.mm/(ha.h.year), or 28.6% of the mean for the 43 sites with a zero rainfall threshold. The prediction error for monthly distribution of the R- factor was 2.3% with a zero threshold and 2.5% with 12.7mm threshold. This and previous studies have shown that the daily rainfall erosivity model can be used to accurately predict the R- factor and its seasonal distribution in Australia. Digital maps were produced showing the spatial and seasonal distribution of the R- factor at 0.05° resolution in Australia. These maps have been used to assess rill and sheet erosion rate at the continental scale.
Lu et al. (Wed,) studied this question.