多元非平稳时间序列分析的滑坡变形预测研究

Landslide Deformation Prediction by Analysis of Multivariate Non-stationary Time Series

目前滑坡变形预测的时间序列模型为单变量模型,仅考虑时间-位移关系,未能考虑诱发因素对滑坡位移的影响,因此,建立多变量的时间序列模型十分必要。应用多元非平稳时间序列分析方法,建立了滑坡变形趋势的误差修正模型(ECM),实现了滑坡诱发因素和位移动态变化的综合分析。以三峡库区秭归县白水河滑坡为例,取监测点ZG93为代表,建立了基于多元时间序列分析的误差修正预测模型,并计算预测误差,结果显示,除个别数据点之外,预测误差均在±2.3%以内。

At present,time series model for landslide deformation prediction has been univariate model which failed to take the inducing factors of landslide displacement into account. To establish multivariate time series model is necessary. An error correction model( ECM) for landslide deformation trend prediction was established by using multivariate non-stationary time series to comprehensively analyze the landslide's inducing factors and dynamic displacement changes. The monitoring point ZG93 of Baishuihe landslide in Three Gorges Reservoir area was taken as an example to calculate the prediction errors. Results showed that except for several points,the prediction errors are all controlled in the range of ± 2. 3%.