An improved RUSLE/SDR model for the evaluation of soil erosion

The accurate assessment of soil erosion is key to assess environmental parameters, such as the reduction in soil fertility, the increase in flood risk, the loss of nutrients, and degradation of water quality. In this study, we developed a methodology using the Revised Universal Soil Loss Equation (RUSLE) with the sediment delivery ratio (SDR) to estimate the annual amount of soil erosion and sediment yield in the Nozhian watershed (western Iran). The weighted total least-squares (WTLS) algorithm was applied to generate the rainfall–runoff erosivity surface using rainfall data and a digital elevation model (DEM) instead of traditional interpolation methods. The results demonstrated that the obtained sediment yield by the RUSLE/SDR model was approximately 802,000 tons per year. More than half of the watershed (61.6%) belonged to the high and severe erosion classes (20–100 t/ha year), and the mean soil erosion rate in the study area was 89.32 t/ha year. Several landslides extracted using a Google Earth map by expert interpretation were exactly consistent with areas that had high erosion rates based on the RUSLE results. This compatibility implies the compatibility between the results and reality. According to the statistical analysis, topographic features, especially slope steepness, had the greatest effect on the rate of soil erosion in the region. The results of our RUSLE/SDR analysis were also compared with the reported results from the Modify Pacific Southwest Interagency Committee (MPSIAC), Erosion Potential method (EPM), and Hydrophysical model. In situ data from the measured annual sediment yield during a 40-year interval from a hydrometric station were used for the accuracy analysis. The comparison indicated improvement in the accuracy of our approach by up to 65% in comparison to other reported results. These results can surely aid in the implementation of soil management and conservation practices to reduce soil erosion in the Nozhian watershed.