Quantitative Evalution of geohazards susceptibility based on GIS and information value model for Emeishan City, Sichuan
-
摘要: 以四川峨眉山市为研究区，选取坡度、坡高、坡向、岩土体类型、构造、河流侵蚀、地表覆被、降雨、工程切坡以及矿产开发10个影响因素作为评价因子，采用改进信息量法，在评价因子分级分析的基础上，利用GIS技术，对研究区地质灾害易发性进行了定量评价。结果表明：方法科学可靠，评价结果与实际基本相符；地质灾害在高陡斜坡区域、坚硬薄层-厚层状砂岩、粉砂岩夹白云岩、灰岩岩组、构造密集区最为发育，地形地貌、地质构造是地质灾害发育最主要的控制因素；地质灾害易发性划分为高易发、中易发、低易发、极低易发4个等级，分布面积分别为169.37km2、429.07km2、363.43km2和221.12km2。易发性评价精度74.80%。评价方法可为县域地质灾害易发性评价提供理论指导，评价结果可为该区域地质灾害防治工作提供科学依据。Abstract: Exemplified by Emeishan City, Sichuan, 10 factors are selected as the evaluation factors including slope gradient, slope height, slope direction, rock and soil type, geological structure, river erosion, surface cover, rainfall, engineering slope cutting and mineral exploration. On the basis of the grading analysis of the evaluation factors and GIS techniques, the geohazards susceptibility is evaluated for Emeishan City, Sichuan with the aid of the improved information value model. The results of research show that the information value model is scientific and reliable, and the evaluation results are in general agreement with the actual conditions. The geological hazards are best developed in high and steep slopes, hard thin-to thick-bedded sandstones, siltstone intercalated with dolostones, limestone formation and closely spaced structures. Topography, geomorphology and geological structures are believed to be the main factors controlling the geological hazards in this region. The susceptibility of the geological hazards may be classified into four grades:highly, moderately, low and extremely low susceptibility, with the covering areas of 169.37, 429.07, 363.43 and 221.12 km2, respectively. The precision of the susceptibility evaluation accounts for 74.80%. It can be seen that the evaluation method presented in this study may serve as a theorectical guide for the susceptibility evaluation of county-scale geological hazards, and the evaluation results may provide scientific data for the prevention and control of the geological hazards in the study area.
-
Keywords:
- geological hazard /
- susceptibility evaluation /
- information value model /
- GIS /
- Emeishan City
-
-
[1] 李媛,曲雪妍,杨旭东等. 中国地质灾害时空分布规律及防范重点[J]. 中国地质灾害与防治学报,2013,24(4):71-78. [2] 房浩,李媛,杨旭东等. 2010-2015年全国地质灾害发育分布特征分析[J]. 中国地质灾害与防治学报,2018,29(5):1-6. [3] 丁俊,魏伦武,秦建华等. 西南地区地质灾害调查工作的思考[J]. 沉积与特提斯地质,2006,26(3):77-80. [4] 杜国梁,张永双,高金川等. 基于GIS的白龙江流域甘肃段滑坡易发性评价[J]. 地质力学学报,2016,22(1):1-11. [5] 谭玉敏,郭栋,白冰心等. 基于信息量模型的涪陵区地质灾害易发性评价[J]. 地球信息科学学报,2015,27(12):1554-1562. [6] 张晓东,刘湘南,赵志鹏等. 信息量模型、确定性系数模型与逻辑回归模型组合评价地质灾害敏感性的对比研究[J]. 现代地质,2018,32(3):602-610. [7] 刘艳芳,方佳琳,陈晓慧等. 基于确定性系数分析方法的秭归县滑坡易发性评价[J]. 自然灾害学报,2014,23(6):209-217. [8] 王珂,郭长宝,马施民等. 基于证据权模型的川西鲜水河断裂带滑坡易发性评价[J]. 现代地质,2016,30(3):705-715. [9] 刘宇恒,邓辉,熊倩莹. 基于层次分析法的茂县斜坡地质灾害易发性评价[J]. 长江科学院院报,2017,34(5):31-35. [10] 王涛,吴树仁,石菊松等. 秦岭中部太白县地质灾害发育特征及危险性评估[J]. 地质通报,2013,32(12):1977-1983. [11] 殷坤龙,晏同珍. 滑坡预测及相关模型[J]. 岩石力学与工程学报,1996,15(1):1-8. [12] 殷坤龙,张桂荣. 地质灾害风险区划与综合防治对策[J]. 安全与环境工程,2003,10(1):32-35. [13] 孟庆华,孙炜锋,王涛. 陕西凤县滑坡易发性评价研究[J]. 地质调查与研究,2013,36(2):136-145. [14] 王佳佳,殷坤龙,肖莉丽. 基于GIS和信息量的滑坡灾害易发性评价-以三峡库区万州区为例[J]. 岩石力学与工程学报,2014,33(4):797-808. [15] 陈绪钰,李明辉,王德伟等. 采煤诱发地质灾害发育特征与成因机制[J]. 煤炭技术,2016,35(2):137-139.
计量
- 文章访问数: 300
- HTML全文浏览量: 2
- PDF下载量: 148
下载:
