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Soil erosion is mainly affected by the rainfall characteristics and land cover conditions, and soil erosion modelling is important for evaluating land degradation status. The revised Universal Soil Loss Equation (RUSLE) have been widely used to simulate soil loss rate. Previous studies usually considered the general rainfall characteristics and direct effect of runoff with the event rainfall erosivity factor (Re) to produce event soil loss (Ae), whereas the fluctuation of rainfall intensity within the natural rainfall profile has rarely been considered. In this study, the relative amplitude of rainfall intensity (Ram) was proposed to generalize the features of rainfall intensity fluctuation under natural rainfall, and it was incorporated in a new Re (Re=RamEI30) to develop the RUSLE model considering the fluctuation of rainfall intensity (RUSLE-F). The simulation performance of RUSLE-F model was compared with RUSLE-M1 model (Re=EI30) and RUSLE-M2 model (Re=QREI30) using observations in field plots of grassland, orchard and shrubland during 2011–2016 in a loess hilly catchment of China. The results indicated that the relationship between Ae and RamEI30 was well described by a power function with higher R2 values (0.82–0.96) compared to QREI30 (0.80–0.88) and EI30 (0.24–0.28). The RUSLE-F model much improved the accuracy in simulating Ae with higher NSE (0.55–0.79 vs −0.11∼0.54) and lower RMSE (0.82–1.67 vs 1.04–2.49) than RUSLE-M1 model. Furthermore, the RUSLE-F model had better simulation performance than RUSLE-M2 model under grassland and orchard, and more importantly the rainfall data in the RUSLE-F model can be easily obtained compared to the measurements or estimations of runoff data required by the RUSLE-M2 model. This study highlighted the paramount importance of rainfall intensity fluctuation in event soil loss prediction, and the RUSLE-F model contributed to the further development of USLE/RUSLE family of models.