降雨、库水位变化是滑坡发生的主要外在诱发因素,降雨和库水位变化的滞后性和周期性是滑坡变形的重要作用特征。考虑降雨及库水位变化的滞后性和周期性对滑坡累积位移的影响,直接将降雨和库水位变化作为滑坡变形位移预测的影响变量,建立多元时序模型。以三峡库区秭归县白水河滑坡为例,首先用灰色模型提取趋势项位移,然后利用滞后的降雨量和滞后的库水位的变化量预测当期的周期项位移,最后将趋势项位移与周期项位移叠加,得到滑坡累积位移的预测值。结果显示,此方法能够很好地反映滑坡诱发因素对滑坡变形的动态影响,预测的平均绝对误差为1.97%,预测精度较高。
Abstract
Rainfall and reservoir water level variation are major external factors inducing landslide. Hysteresis and periodicity of rainfall and reservoir water level variation are important influence factors of landslide displacement. In this paper, a multivariate time series model with rainfall and reservoir water level variation as impact factors of displacement prediction was established. The effect of hysteresis and periodicity of rainfall and reservoir water level variation on the cumulative displacement of landslide was considered. Baishuihe landslide in Three Gorges Reservoir area was taken as a case study. Firstly, gray model was employed to extract the trend term displacement; and then the lagged variations of rainfall and reservoir water level were used to predict the displacement of the periodic term; finally, the predicted value of accumulative displacement is obtained by superposing the displacements of the trend term and the periodic term. Results prove that the dynamic effects of inducing factors on the cumulative displacement of landslide could be well reflected by this model. It has high prediction accuracy, with the average absolute error 1.97%.
关键词
滑坡 /
诱发因素 /
滞后性 /
周期性 /
变形预测 /
多元时序模型
Key words
landslide /
inducing factor /
hysteresis /
periodicity /
displacement prediction /
multivariate time series model
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基金
国家自然科学基金项目(41230637);国家重点基础发展计划资助“973”计划项目(2011CB710605)
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