Dangerous degree forecast of soil and water loss on highway slopes in mountainous areas using RUSLE model
Authors: Li Yue , Qi Shi , Liang Bin , Ma Junming , Cheng Baihan , Ma Cong , Qiu Yidan , Chen Qinyan 
Published: November 2017

Abstract. Many high and steep slopes have been formed by special topographic and geomorphic types and mining activities during the construction of mountain expressways. Severe soil erosion may occur under heavy rainfall conditions and pose a serious threat to road safety and the lives of residents. Therefore, the prediction of soil and water loss on highway slopes is important for the protection of infrastructure and human life. This work studies Xinhe Expressway, which is in the southern edge of Yunnan Guizhou Plateau, as the research area. The revised universal soil loss equation is selected as the prediction model of soil and water loss on slopes. Moreover, geographic information system, remote sensing technology, field survey, runoff plot observation test, cluster analysis, and cokriging are adopted. The partition of the prediction units of soil and water loss on the expressway slope in the mountain area and the spatial distribution model of the linear highway rainfall are studied. In view of the particularity of the expressway slope in the mountain area, the model parameter factor is modified and the risk of soil and water loss along the mountain expressway is simulated and predicted under 20-year and one-year rainfall return periods. The results are as follows. (1) Considering natural watershed as the prediction unit of slope soil erosion can represent the actual situation of soil and water loss of each slope. The spatial location of soil erosion unit is realized, the accuracy of soil and water loss prediction results is improved, and the convenience of data management and maintenance in the later stage is guaranteed. (2) Analysis of the actual observation data show that the overall average absolute error of the monitoring area is 33.24 t · km−2, the overall average relative error is 33.96 %, and the overall root mean square error is between 20.95 and 65.64, all of which are within acceptable limits. The Nash efficiency coefficient is 0.67, thereby showing that the prediction accuracy of the model satisfies the requirements. (3) Under the condition of one-year rainfall, we find through risk classification that the percentage of prediction units with no risk of erosion is 78 % and that with mild soil erosion risk is 15.92 %. Results show that soil erosion risk is low and thereby does not affect road traffic safety. Under the 20-year rainfall condition, the percentage of units with high and extremely high risk is 7.11 %. In these areas, the risk of soil erosion is relatively large and mainly distributed on K109 + 500 − K110 + 500 and K133 − K139 + 800 sections. Even if only part of the sediment is deposited on the road, road safety will be affected. The prediction results can help adjust the layout of water and soil conservation measures in these units. This study provides not only a scientific basis for soil erosion prevention and control in mountain expressways but also a reference for the application of water and soil loss prediction and soil conservation planning.