VALIDATION OF RAINFALL EROSIVITY ESTIMATORS FOR MAINLAND CHINA

作者:Zhu, Z (Zhu, Z.)[ 1 ] ; Yu, B (Yu, B.)[ 2 ]

TRANSACTIONS OF THE ASABE

卷: 58  期: 1  页: 61-71

出版年: 2015

摘要

Methods are needed to estimate R-factor values and their seasonal distribution from daily rainfall totals in regions with little or no sub-daily rainfall intensity data. This study used calculated R-factor values for a 29-year period (1956-1984) for 22 locations in mainland China to evaluate two estimators of rainfall erosivity for large-scale application of the Universal Soil Loss Equation (USLE) or the Revised USLE (RUSLE), one for an R-factor estimated from mean annual precipitation and another for event erosivity from daily rainfall. This study shows that as a first approximation, the mean annual precipitation is non-linearly related to the R-factor, and that the relationship can be used to predict the R-factor for mainland China locations (Nash-Sutcliffe model efficiency E-c = 0.88, RMSE = 28% of the mean). The nonlinear relationship for China is quite similar to those reported in other studies for Australia and the U.S. The study also shows that a daily rainfall erosivity model using average parameter values previously applied for Australia can satisfactorily estimate the seasonal variation in rainfall erosivity in addition to the R-factor for the mainland China locations (E-c = 0.90, RMSE = 25% of the mean). Once calibrated, model estimates of the R-factor and its monthly distribution from daily rainfall for the mainland China locations improved noticeably (E-c = 0.99, RMSE <10% of the mean). The daily rainfall erosivity model and a gridded daily precipitation dataset (the China Gridded Daily Precipitation Product) with a 0.25 degrees (similar to 25 km) resolution were then used to produce a concurrent daily rainfall erosivity map for the mainland China locations (E-c = 0.96, RMSE = similar to 23% of the mean) for a 5-year period from April 2008 to March 2013. This study shows that: (1) mean annual precipitation can be used to estimate the R-factor for mainland China, Australia, and the U.S.; and (2) a calibrated daily rainfall erosivity model performed well in estimating the seasonal and interannual variations in rainfall erosivity, in addition to the R-factor, for large-scale erosion monitoring and assessments in China.

通讯作者地址: Yu, B (通讯作者)

Griffith Univ, Sch Engn, Nathan Campus,170 Kessels Rd, Nathan, Qld 4111, Australia.

地址:

[ 1 ] Beijing Normal Univ, State Key Lab Remote Sensing Sci, Sch Geog, Beijing 100875, Peoples R China

[ 2 ] Griffith Univ, Sch Engn, Nathan, Qld 4111, Australia