基于斜坡单元的山区城镇滑坡灾害易发性评价：以康定为例

Landslide susceptibility assessment based on slope units of mountainous cities and towns: A case study of Kangding city

关键词:  易发性  斜坡单元  证据权模型  治理工程  山区城镇

Key words:  Susceptibility  slope units  weight of evidence  treatment projects  mountainous cities and towns

摘要:

山区地质灾害易发性评价对城镇地质灾害风险管理具有重要意义。本文以康定市为例，以斜坡单元为最小评价单元，选取高程、坡度、坡向、曲率、工程地质岩组、距道路距离、距断裂距离、距水系距离和斜坡结构等9个滑坡影响因子，根据各因子滑坡面积比曲线与证据权值曲线的突变点，划分滑坡影响因子二级状态，并对各影响因子进行相关性分析，剔除相关性较高的距道路距离因子，在此基础上，采用证据权模型进行滑坡易发性评价。对已有治理工程的斜坡单元，本文尝试利用折减系数法对其易发性进行进一步评价。结合现场调查，将研究区滑坡易发性程度划分为：极高易发、高易发、中等易发、低易发。评价结果表明，自然工况下极高易发区主要位于康定市炉城镇以及研究区北侧二道桥村一带，高易发区主要位于雅拉河、折多河与瓦斯沟河谷两侧，对治理工程所在的斜坡单元进行折减后，极高易发区面积由11.21%降至8.42%，滑坡比率由4.03降低至2.3，研究结果符合实际情况，模型精度达77.8%。评价结果较好地反映了康定市区的滑坡易发性分布情况，可为城镇精细化评价提供一定的参考依据。

Abstract:

Susceptibility assessment of geological hazard in mountainous areas plays an important role in geological hazard risk management. Taking Kangding city as the example, nine index factors including elevation, gradient, slope aspect, curvature, engineering geological information, distance to road, distance to rivers, distance to fault zones, and the direction and structure of slope were selected as the evaluation indexes based on slope unit. The critical values were selected from the catastrophe points of the landslide ratio curve and weight of evidence curve to determine the factor states on dividing the entire factors interval and the distance to road was removed because of correlation analysis for each influencing factor. Based on the weight of evidence, the Susceptibility assessment was developed. The method of reduction coefficient was used to evaluate the susceptibility accurately for slope units that already had treatment projects. Combine with field investigation results, the study area was classified into four zones with different levels of landslide susceptibility: landslide extremely high-prone area, landslide high-prone area, landslide moderate-prone area, and landslide low-prone area. The results show that extremely high-prone area were mainly distributed in the Lucheng Town of Kangding City and Erdaqiao village in the north. Meanwhile, high-prone areas were mainly distributed on the side of Yala River, Zheduo River, and Wasi Valley. After the reduction of the slope unit where the treatment projects are located, the area and landslide ratio of extremely high-prone areas decreased from 11.21% to 8.42% and from 4.03 to 2.3 respectively. The research results were in good agreement with the distribution of known landslides, and the accuracy of the assessment is about 77.8%. The landslide susceptibility assessment results obtained in this paper reflect the distribution of landslides in the study area, providing technical support for the refined risk assessment of mountainous cities and towns.