考虑监测离群值朱家店滑坡位移预测研究

滑坡位移预测预报是滑坡防灾减灾的重要组成部分,提高滑坡位移预测的准确性与精确度是该项研究的重点与难点。本文在滑坡位移预测中考虑了监测样本的离群值,通过忽略、指定与修正离群值3种方式,研究滑坡位移预测样本离群值的最优处理方式。以三峡库区朱家店滑坡为例,基于ARIMA(p,d,q)模型,分别对累积位移与位移速率时间序列开展了预测研究。研究结果表明:修正离群值的预测结果介于忽略和指定离群值两者之间,更适用于存在监测离群值的滑坡位移预测;对于ARIMA模型,更适合采用位移速率进行预测预报;使用位移速率时间序列ARIMA(1,0,1)并修正离群值的预测结果为:2016年和2017年6月份滑坡前缘GP3"阶跃"位移分别为79. 0 mm和70. 2 mm,截止2017年8月,GP3累积位移将达1647. 7 mm。

DISPLACEMENT PREDICTION OF THE ZHUJIADIAN LANDSLIDE WITH OUTLIERS

Landslide displacement prediction is one of important parts of landslide disaster prevention and mitigation. To improve the accuracy and precision of landslide displacement prediction is emphasis and difficulty. Outliers from monitoring samples are took into account in this research. By ignoring, reserving or correcting outliers to study on which is the best of three ways of landslide displacement prediction with outliers. The Zhujiadian Landslide in Three Gorges Reservoir Region is chosen as the case study on displacement prediction. Based on ARIMA(p, d, q) model, predictions are carried out using the accumulated displacement and the displacement rate time series, respectively. The research results show that: (1) The landslide prediction result with correcting outliers is between ignoring and reserving ones. (2)For ARIMA model, it is more suitable for using the displacement rate time series. (3)The prediction results of "step-like" displacement rates based on ARIMA(1, 0, 1) model for the displacement rate time series with correcting outliers are 79.0mm and 70.2mm in Jun. 2016 and 2017, and accumulated displacement is 1647.7mm until Aug. 2017.