Risk Assessment of Natural Disasters on Highway Caused by Soil Erosion
Based on RF-RUSLE Model: A Case Study of Banan District in Chongqing
MU Fengyun1，YANG Meng1，YU Qing2，LIU Zhentao3
(1. School of Architecture and Urban Planning, Chongqing Jiaotong University, Chongqing 400074, China;
2. School of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China;
3. Guizhou Science and Technology Information Center, Guiyang 550001, Guizhou, China)
Abstract：Six indicators including rainfall, soil type, vegetation coverage, slope, slope position and remediation intensity were selected to establish a risk indicator system, and a RF-RUSLE model was constructed to analyze the degree of soil erosion and the relationship between highway disasters and soil erosion in Banan district of Chongqing. Combined with the regional road network, the natural disaster risk of soil erosion highway in Banan district of Chongqing was evaluated and predicted, and the natural disaster risk level of soil erosion highway in the study area was classified. The factors causing natural disasters on highways in the study area were discussed. The results show that the soil and water conservation in Banan district of Chongqing is relatively better, but the rainfall erosion is serious, and the degree of soil erosion ranges from mild to moderate; the natural disaster risk grade of soil erosion highway in Banan district of Chongqing is generally medium risk, and the southern part and the southwestern part are high risk areas of highway disaster; at the junction of villages and towns, the prevention and control of highway disasters is weak, and the probability of natural disasters caused by soil erosion is extremely high. Rainfall and slope are the main disaster-causing factors, which need to be monitored and controlled.
牟凤云1，杨猛1，余情2，刘振涛3. 基于RF-RUSLE模型的水土流失性公路自然灾害风险评估——以重庆市巴南区为例[J]. 重庆交通大学学报（自然科学版）, 2020, 39(11): 114-121.
MU Fengyun1，YANG Meng1，YU Qing2，LIU Zhentao3. Risk Assessment of Natural Disasters on Highway Caused by Soil Erosion
Based on RF-RUSLE Model: A Case Study of Banan District in Chongqing. Journal of Chongqing Jiaotong University(Natural Science), 2020, 39(11): 114-121.
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2020, Vol. 39 
