基于敏感性制图和数值模拟的泥石流综合评价--以九绵高速公路沙尕沟为例

泥石流等地质灾害的评估对于公路选线和安全运营有着重要的意义。随着科技的发展,越来越准确的泥石流评价和预测体系亟待研究。通过现场勘测和无人机解译,利用自适应神经模糊推理系统(ANFIS)和基于学习优化算法的自适应神经模糊推理系统(TLOA-ANFIS)对泥石流沟进行敏感性评价,并对沙尕沟进行区域划分,结果显示沙尕沟沟口3.5 km范围内泥石流的敏感性评价等级最高。为了更加清楚的研究该范围泥石流的运移堆积情况,对沟内泥石流冲出范围进行数值模拟,结果表明:在降雨频率P=1%的条件下,沙尕沟泥石流流深可达8.76 m,对公路安全运营和基础设施建设有着重要影响,建议相关部门对其进行治理。同时,提供的敏感性制图评价与泥石流危害范围数值模拟结合的方法可以为国内外相似案例提供相关参考。

A comprehensive evaluation for debris flows based on susceptibility mapping and numerical simulation

The evaluation of debris flow and other geological disasters is of great significance for highway route selection and safe operation. With the development of science and technology, a collection of accurate debris flow evaluation and prediction system need to be studied. By field investigation and drone interpretation, Adaptive Neuro-Fuzzy Inference System (ANFIS) and Adaptive Neuro-Fuzzy Inference System based on Teaching-Learning Optimization Algorithm (TLOA-ANFIS) were used to evaluate the susceptibility of debris flow in the gully. The results obtained were zoned and showed that the susceptibility level of the debris flow was the highest within 3.5 km of the mouth of the Shaga gully. Numerical simulations of the debris flow runout range were carried out to provide a more comprehensive analysis of the debris flow transport and accumulation in this area. The results of the numerical simulation were analyzed and showed that the depth of debris flow in Shaga gully can reach 8.76 m when the precipitation probability is 1%. This will have important implications for the safety of the highway and infrastructure construction, and it is also recommended that the relevant authorities pay attention to this issue. The methodology, combining susceptibility mapping with numerical simulation of debris flow hazard provided in this paper, can be used as a reference for similar cases at home and abroad.