|Yin, S. - BEIJING NORMAL UNIV.|
|Xie, Y. - BEIJING NORMAL UNIV.|
|Wamg, C. - BEIJING NORMAL UNIV.|
Submitted to: Catena
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: October 25, 2006
Publication Date: August 1, 2007
Citation: Yin, S., Xie, Y., Nearing, M.A., Wamg, C. 2007. Estimation of rainfall erosivity using 5 to 60 minute fixed-interval rainfall data from China. Catena. 70:306-312. Interpretive Summary: Rainfall erosivity is one of the six factors in the Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE) erosion prediction models. It quantifies the ability of rainfall to cause soil loss from hillslopes. Soil loss may be estimated using either the USLE or RUSLE by multiplying the rainfall erosivity factor, R, together with the other five factors: soil erodibility (K), slope length (L), slope steepness (S), crop type and management (C), and supporting conservation practices (P). Calculation of erosivity requires detailed rainfall intensity data that is not available in all parts of the world, including China. The objective of this study was to develop methods for determining rainfall erosivity using the quality of rainfall data that is more commonly available in China. The results will be used to improve the estimation of rainfall erosivity indices, prediction of soil erosion, and hence the conservation of soil in China and other parts of the world.
Technical Abstract: The 30-minute rainfall erosivity index (EI30) is commonly used in the Universal Soil Loss Equation for predicting soil loss from agricultural hillslopes. The 'E' portion of this value represents the rainfall energy, and the 'I30' portion represents the maximum, contiguous 30-minute rainfall intensity during the storm. Normally, EI30 values are calculated from breakpoint rainfall information taken from continuous recording rain gage charts, however, in many places in China and other parts of the world the detailed chart-recorded rain gage data relative to storm intensities are not readily available. The objective of this study was to assess the accuracy of EI30 estimations based on 5, 10, 15, 30, and 60 min time-resolution rainfall data as compared to EI30 estimations from breakpoint rainfall information. A total of 456 storm events from 5 soil conservation stations located in eastern China were used. Results indicated that the values of EI30 based on the fixed-time-interval data were less than those calculated from breakpoint data. The average conversion factors (ratio of values calculated from the breakpoint data to those from the fixed-interval data) for the five stations decreased from 1.105 to 1.009 for the estimation of E values, from 1.668 to 1.007 for I30 values, and from 1.730 to 1.014 for EI30 values as the time resolution increased from 60 to 5 min.