Uncertainty in interpolation of rainfall erosivity data and its effects on the results of soil erosion modeling.

The uncertainty in interpolation of rainfall erosivity data can directly influence the results and predicting accuracy of soil erosion modeling. In this paper, the daily rainfall data of past five years obtained from 51 automatic weather stations in Jinhua, Zhejiang Province of eastern China was used to explore the uncertainty, which was caused by interpolation methods, output grid size, station density, etc. On this basis, the effects of uncertainty on soil erosion modeling were analyzed. The results showed that: 1)for the automatic weather stations which were densely distributed, station density was much more important to the interpolation of rainfall erosivity data than interpolation methods and output grid size; 2)the absolute error of soil erosion modeling result caused by the uncertainty of Rfactor was more than 200 t/(hm2•a) under standard unit plot condition, which made it difficult to tell apart the noneroded and light erosion area in redyellow soil region; 3) the effects of error addition and accumulation should be considered in modeling soil erosion. On condition that the relative error for any of the other erosion factor was 10%, the maximum relative error for soil erosion modeling may reach more than 40% when 36 weather stations were used for interpolation.