Rainfall Erosivity in Urban Zone of Chongqing Municipality
重庆市主城区降雨侵蚀力特征分析

Rainfall erosivity is an important factor for predicting soil loss quantitatively. The paper studied on rainfall erosivity (R) and its characteristics in the Shapingba area of Chongqing city, based on the rainfall data from 1954 to 2001. The method for calculating rainfall erosivity factor (R) is based on the RUSLE(revised universal soil loss equation). Results show that the values of single rainfall erosivity change greatly; the contribution rate caused by several maximum rainfall erosivity is significant for total rainfall erosivity; the maximum value of single rainfall erosivity is 2.36% of the total value of rainfallerosivity among 48 years; the monthly rainfall erosivity mainly concentrated from May to September; the rainfall erosivity of this period is 91.13% of annual rainfall erosivity; the values of rainfall erosivity per year change greatly too. the paper used two indicators to describe the change of annual rainfall erosivity: the coefficient of changed trend r and the coefficient of variation Cv. By calculation, the coefficient of changed trend r is 0.061, the coefficient of variation Cv is 0.65. So the whole trend of the yearly erosivity value among 48 years is balanced. The single rainfall and single rainfallerosivity, the monthly rainfall and monthly rainfall erosivity are in exponential function relation, but the yearly rainfall and yearly rainfall erosivity is in index relation, the determinate coefficient R2 is 0.9687, 0.8921 and 0.4822 respectively. The paper, under the insufficient rainfall information simplify the calculation process and make use of the rainfall data and results in research area through correlated analysis to conclude two kinds of the simple arithmetic about rainfall erosivity finally, according to the results of determinate coefficient R2 and mean absolute percentage error (MAPE). For using the daily and the monthly rainfall to calculate the annual rainfall erosivity, the determinate coefficient R2 is 0.9181 and 0.8300 respectively, the calculated MAPE is 8.35% and 22.28%, which are obviously better than the others simple means.