Displacement prediction of landslide in Three Gorges Reservoir area based on H-P filter, ARIMA and VAR models

被引:0
|
作者
Meng Meng [1 ,2 ]
Chen Zhi-qiang [3 ]
Huang Da [1 ,2 ]
Zeng Bin [2 ]
Chen Ci-jin [4 ]
机构
[1] Chongqing Univ, State Key Lab Coal Mine Disaster Dynam & Control, Chongqing 400044, Peoples R China
[2] Chongqing Univ, Coll Civil Engn, Chongqing 400045, Peoples R China
[3] 107 Team Chongqing Geol Exploring Bur, Chongqing 401120, Peoples R China
[4] Geol Disaster Control Ctr Wushan Cty, Chongqing 404700, Peoples R China
基金
中国国家自然科学基金;
关键词
landslide; displacement prediction; time series; H-P filter method; auto-regressive integrated moving average (ARIMA) model; vector auto-regressive (VAR) model;
D O I
10.16285/j.rsm.2016.S2.070
中图分类号
P5 [地质学];
学科分类号
0709 ; 081803 ;
摘要
Landslide displacement in Three Gorges Reservoir area is of periodicity due to water level change, rainfall and so on. Based on the time series analysis, landslide displacement can be divided into the trend displacement reflecting the long-term trend of landslide, which is the response of geologic structure; and the periodic displacement reflecting the volatility of landslide, which is mainly affected by external factors such as rainfall. Taking Taping landslide in Three Gorges Reservoir area for example and considering the influences of water level change and rainfall, the trend displacement and periodic displacement are evaluated by Hodrick-Prescott (H-P) filter forecasting method. Difference auto-regressive integrated moving average (DARIMA) model is utilized to smooth the curve of trend displacement, and then compute the predicted value of trend displacement. Vector auto-regressive (VAR) model is used to predict the periodic displacement. The overall predicted displacement is obtained by adding the predicted values of trend displacement and periodic displacement, which is compared with the monitoring displacement and one predicted by other forecasting methods. The results show that the predicted displacements by this proposed method are in better agreement with the monitoring data; the proposed comprehensive model can better reflect the trend and volatility of landslide displacement.
引用
收藏
页码:552 / 560
页数:9
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