基于成灾条件的滑坡危险性评价串并联模型与应用
Series and parallel model of landslide hazard evaluation based on disaster conditions and application
查看参考文献25篇
文摘
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首先对基于成灾条件的滑坡危险性评价串并联模型进行了研究。通过对滑坡发生原理的分析,将滑坡成灾条件划分为触发因素系统(充分条件)和内部因素系统(必要条件)两类,滑坡只有在触发因素系统(充分条件)和内部因素系统(必要条件)共同作用下才会发生,建立了滑坡危险性评价的概念模型;通过分析电路三要素(电压、电阻与电流)与滑坡成灾条件的关系,首次建立了基于滑坡成灾条件的滑坡危险性评价串并联数学模型并定义了其算法。研究结果表明:模型能在结构和功能上表征滑坡的发生原理。然后,运用所建立的模型对研究区5·12汶川地震条件下滑坡危险性进行了评价。通过分析地震滑坡成灾条件,借助arcgis软件实现了对研究区地震条件下滑坡危险性的定量评价,并用遥感解译和实地调查的5·12汶川地震触发的滑坡数据对评价结果进行了检验。研究结果表明:73.56%地震滑坡位于极高危险区与高危险区,发生率也以极高度危险区与高度危险区较大,分别为0.319 4和0.185 0,滑坡发生率总体上随危险性等级的增加而增大,说明这种评价方法得出的危险等级与实际滑坡发生情况吻合。 |
其他语种文摘
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Firstly,series and parallel model of landslide hazard evaluation based on disaster conditions are investigated.The disaster conditons of landslide is divided into trigger system (sufficient condition) and internal factors (necessary condition) according to the analysis of landslide occurrence principle.Landslide can occur only when the triggering factor system (sufficient condition) and the internal factor system (necessary condition) are combined together.A conceptual model for landslide hazard assessment is established.According to the analysis of three essential circuit elements (voltage,resistance and current) relationship with landslide conditions,a series and parallel mathematical model of landslide hazard evaluation is established for the first time based on disaster conditions and the definition of the algorithm.The model can characterize the occurrence principle of landslide in structure and function.Then,using the established model,the hazard of landslide in the study area is evaluated under the condition of 5·12 Wenchuan Earthquake.Quantitative evaluation of landslide hazard in the study area is carried out through the conditons analysis of landslide triggered by 5·12 Wenchuan Earthquake and the aid of Arc-GIS software.The evaluation results are tested by the data of landslide triggered by 5·12 Wenchuan Earthquake,which is acquired by remote sensing interpretation and field survey.The test results show that 73.56% earthquake landslide is located in extremely high risk area or high risk area,and larger ratio of landslide area to evaluation area is also in extremely high risk area(0.319 4) and high risk area(0.185 0),and the ratio increases with the increase of risk level in general.In a word,the evaluation results are reasonable. |
来源
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自然灾害学报
,2018,27(2):52-58 【扩展库】
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DOI
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10.13577/j.jnd.2018.0206
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关键词
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成灾条件
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串并联模型
;
危险性评价
;
滑坡
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地址
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1.
西南科技大学土木工程与建筑学院, 四川, 绵阳, 621010
2.
中国科学院水利部成都山地灾害与环境研究所, 四川, 成都, 610041
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语种
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中文 |
文献类型
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研究性论文 |
ISSN
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1004-4574 |
学科
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灾害及其防治;安全科学 |
基金
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四川省科技支撑计划项目
;
国家自然科学基金项目
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文献收藏号
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CSCD:6251301
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参考文献 共
25
共2页
|
1.
Ohlmacher G C. Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas,USA.
Engineering Geology,2003,69(s3/4):331-343
|
被引
71
次
|
|
|
|
2.
Thiery Y. Landslide susceptibility assessment by bivariate methods at large scales: application to a complex mountainous environment.
Geomorphology,2007,92(1):38-59
|
被引
9
次
|
|
|
|
3.
李秀珍. DDA法和Fisher判别法在潜在滑坡判识中的应用比较.
岩土力学,2011,32(1):186-192
|
被引
6
次
|
|
|
|
4.
夏元友. 系统加权聚类法及其在滑坡稳定性预测中的应用.
自然灾害学报,1997,6(3):85-90
|
被引
7
次
|
|
|
|
5.
桂蕾. 基于聚类分析的滑坡灾害危险性区划研究.
水文地质工程地质,2013,40(1):100-105
|
被引
10
次
|
|
|
|
6.
高克昌. 基于地理信息系统和信息量模型的滑坡危险性评价——以重庆万州为例.
岩石力学与工程学报,2006,25(1):991-995
|
被引
62
次
|
|
|
|
7.
乔建平. 贡献权重叠加法的滑坡危险度区划研究.
自然灾害学报,2011,20(2):8-13
|
被引
3
次
|
|
|
|
8.
阮沈勇. 基于GIS的信息量法模型在地质灾害危险性区划中的应用.
成都理工学院学报,2001,28(1):89-92
|
被引
68
次
|
|
|
|
9.
李军霞. 基于组合赋权-未确知测度理论的滑坡危险性评价.
岩土力学,2013,34(2):468-474
|
被引
17
次
|
|
|
|
10.
谭龙. 人工神经网络在滑坡敏感性评价中的应用.
兰州大学学报(自然科学版),2014,50(1):15-20
|
被引
23
次
|
|
|
|
11.
Melchiorre C. Artificial neural networks and cluster analysis in landslide susceptibility zonation.
Geomorphology,2008,94(3/4):379-400
|
被引
15
次
|
|
|
|
12.
Ermini L. Artificial neural networks applied to landslide susceptibility assessment.
Geomorphology,2005,66(1):327-343
|
被引
24
次
|
|
|
|
13.
Conforti M. Evaluation of prediction capability of the artificial neural networks for mapping landslide susceptibility in the Turbolo river catchment(northern Calabria,Italy).
Catena,2014,113:236-250
|
被引
21
次
|
|
|
|
14.
易顺民. 滑坡定量预测的非线性理论方法.
地学前缘,1996,3(1/2):77-85
|
被引
15
次
|
|
|
|
15.
邱海军. 基于关联维数的黄土滑坡空间分布结构及其成因分析.
岩石力学与工程学报,2015,34(3):546-555
|
被引
12
次
|
|
|
|
16.
Yokoi Y. Fractal character of landslides.
Environmental and Engineering Geoscience,1995,1(1):75-81
|
被引
5
次
|
|
|
|
17.
Zuo R. Fractal characterization of the spatial distribution of geological point processes.
International Journal of Applied Earth Observation and Geoinformation,2009,11(6):394-402
|
被引
5
次
|
|
|
|
18.
国家防汛抗旱总指挥部办公室.
山洪泥石流滑坡灾害及防治,1994:251-252
|
被引
1
次
|
|
|
|
19.
Cui P. The 12 May Wenchuan earthquake-induced landslide lakes: distribution and preliminary risk evaluation.
Landslides,2009,6(3):209-223
|
被引
84
次
|
|
|
|
20.
Xu X W. The Ms 8.0 Wenchuan earthquake surface ruptures and its seismogenic structure.
Seismology and Geology,2008,30(3):597-629
|
被引
29
次
|
|
|
|
|