LAUSR

Abstract Accurate assessment of soil loss caused by rainfall is essential for natural and agricultural resources management. Soil erosion directly affects the environment and human sustainability. In this work, the empirical and contemporary model of revised universal soil loss equation (RUSLE) was applied for simulating the soil erosion rate in a karst catchment using remote sensing data and geographical information systems. A scheme of alterative sub-models was adopted to calculate the rainfall erosivity ( R ), soil erodibility ( K ), slope length and steepness ( LS ), cover management ( C ) and conservation practice ( P ) factors in the geographic information system (GIS) environment. A map showing the potential of soil erosion rate was produced by the RUSLE and it indicated the severe soil erosion in the study area. Six classes of erosion rate are distinguished from the map: 1) minimal, 2) low, 3) medium, 4) high, 5) very high, and 6) extremely high. The RUSLE gave a mean annual erosion rate of 30.24 Mg ha −1 yr −1 from the 1980s to 2000s. The mean annual erosion rate obtained using RUSLE is consistent with the result of previous research based on in situ measurement from 1980 to 2009. The high performance of the RUSLE model indicates the reliability of the sub-models and possibility of applying the RUSLE on quantitative estimation. The result of the RUSLE model is sensitive to the slope steepness, slope length, vegetation factors and digital elevation model (DEM) resolution. The study suggests that attention should be given to the topographic factors and DEM resolution when applying the RUSLE on quantitative estimation of soil loss.