Rainfall erosivity,one of the factors in the Universal Soil Loss Equation.quantifies the effect of rainfall and runoffon soil erosion.High-resolution data are required to compute rainfall erosivity,but are not widely ...Rainfall erosivity,one of the factors in the Universal Soil Loss Equation.quantifies the effect of rainfall and runoffon soil erosion.High-resolution data are required to compute rainfall erosivity,but are not widely available in many parts of the world.As the temporal resolution of rainfall measurement decreases,computed rainfall erosivity decreases.The objective of the paper is to derive a series of conversion factors as a function of the time interval to compute rainfall erosivity so that the R factor computed using data at different time intervals could be converted to that computed using 1-min data.Rainfall data at 1-min intervals from 62 stations over China were collected to first compute the~ue'R factor values.Underestimation of the R factor was systematically evaluated using data aggregated at 5,6.10,15,20,30,and 60-min to develop conversion factors for the R factor and the 1-in-10-year storm EI30 values.Compared with true values,the relative error in R factor using data at fixed intervals of≤10min was<10%for at least 44 out of 62 stations.Errors increased rapidly when the time interval of the rainfall data exceeded 15 min.Relative errors were>10%using 15-min data for 66.1%of stations and>20%using 30-min data for 61.3%of stations.The conversion factors for the R factor,ranging from 1.051 to 1.871 for 5 to 60-min data,are higher than those for the 1-in-10-years storm EI30,ranging from 1.034 to 1.489 for the 62stations.展开更多
基金the Second Tibetan Plateau Scien tifc Expedition and Research Program(STEP)(No.2019QZKK0306)the National Key R&D Program(No.2018YFC0507006)Na tional Natural Science Foundation of China(No.41877068).
文摘Rainfall erosivity,one of the factors in the Universal Soil Loss Equation.quantifies the effect of rainfall and runoffon soil erosion.High-resolution data are required to compute rainfall erosivity,but are not widely available in many parts of the world.As the temporal resolution of rainfall measurement decreases,computed rainfall erosivity decreases.The objective of the paper is to derive a series of conversion factors as a function of the time interval to compute rainfall erosivity so that the R factor computed using data at different time intervals could be converted to that computed using 1-min data.Rainfall data at 1-min intervals from 62 stations over China were collected to first compute the~ue'R factor values.Underestimation of the R factor was systematically evaluated using data aggregated at 5,6.10,15,20,30,and 60-min to develop conversion factors for the R factor and the 1-in-10-year storm EI30 values.Compared with true values,the relative error in R factor using data at fixed intervals of≤10min was<10%for at least 44 out of 62 stations.Errors increased rapidly when the time interval of the rainfall data exceeded 15 min.Relative errors were>10%using 15-min data for 66.1%of stations and>20%using 30-min data for 61.3%of stations.The conversion factors for the R factor,ranging from 1.051 to 1.871 for 5 to 60-min data,are higher than those for the 1-in-10-years storm EI30,ranging from 1.034 to 1.489 for the 62stations.
