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地理研究  2007 

Calculation of rainfall erosivity by using hourly rainfall data
用小时降雨资料估算降雨侵蚀力的方法

Keywords: breakpoint data,hourly rainfall data,rainfall event energy,maximum 30-min rainfall intensity,rainfall erosivity index
降雨过程资料
,小时降雨资料,次降雨动能,最大30,min雨强,降雨侵蚀力指标

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Abstract:

Rainfall erosivity shows the potential ability of the soil loss caused by rainfall and it is a very important factor for predicting soil loss from agricultural hillslopes. EI30 is a widely used index for quantifying rainfall erosivity. 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 gauge charts, however, in many places in China the detailed chart-recorded rain gauge data relative to storm intensities are not readily available. Obviously, the more detail of the rainfall data was used, the more accurate of EI values were given. In order to take advantage of hourly rainfall data in automatic meteorological observation stations and improve the precision of EI values. A total of 456 storm events in 5 soil conservation stations over eastern China were used to determine if EI values could be calculated by using hourly rainfall data (60-min interval data). Results indicated that the values of EI30 based on the 60 min 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 60 min interval data) for the five stations are 1.105 for the estimation of E values, 1.668 for I30 values, and 1.730 for EI30 values. The differences between two kinds of EI values based on breakpoint data and hourly rainfall data are mainly caused by maximum 30-min rainfall intensity. Hourly rainfall data can be used to accurately determine the rainfall erosion index values by using this function:(EI30)bp=1.730(EI30)60.The result could be used to improve the estimation of rainfall erosivity indices, and hence prediction of soil erosion in China.

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