Dangerous degree forecast of soil loss on highway slopes in mountainous areas of the Yunnan-Guizhou Plateau (China) using the Revised Universal Soil Loss Equation

摘要

Many high and steep slopes are comprised of special topographic and geomorphic types and formed through mining activities during the construction of mountain expressways. Severe soil erosion may also occur under heavy rainfall conditions. Therefore, predicting soil loss on highway slopes is important in protecting infrastructure and human life. In this study, we investigate Xinhe Expressway located at the southern edge of the Yunnan-Guizhou Plateau. The Revised Universal Soil Loss Equation (RUSLE) is used as the prediction model for soil and water loss on slopes. Geographic information systems, remote sensing technology, field surveys, run-off plot observation testing, cluster analysis and co-kriging calculations are also utilised. The partition of the prediction units of soil loss on the expressway slope in the mountainous area and the spatial distribution of rainfall on a linear highway are studied. Given the particularity of the expressway slope in the mountainous area, the model parameter is modified, and the risk of soil loss along the mountain expressway is simulated and predicted under 20- and 1-year rainfall return periods. The following results are obtained. (1) Natural watersheds can be considered for the prediction of slope soil erosion to represent the actual situation of soil loss on each slope. Then, the spatial location of the soil erosion unit can be determined. (2) Analysis of actual observation data shows that the overall average absolute error of the monitoring area is 0.39 t ha(-1), the overall average relative error is 33.96% and the overall root mean square error is between 0.21 and 0.66, all of which are within acceptable limits. The Nash efficiency coefficient is 0.67, indicating that the prediction accuracy of the model satisfies the requirements. (3) Under the 1-year rainfall return period condition, we find through risk classification that the percentage of prediction units with no risk of erosion is 78 %. The soil erosion risk is low and