Landslide displacement prediction based on time series analysis and data assimilation with hydrological factors

The displacement prediction of an active landslide is a complicated and challenging problem worldwide. Currently, most prediction experiments focus on the mechanism model and fail to integrate with the influence factors. In this paper, a method of landslide data assimilation is proposed to predict the landslide displacement, and real data tests are carried out to support the theoretical calculation. The obtained results show better performance of the proposed method compared with the general method. Data assimilation shows a relatively 40.32% improve in RMSE. This study can strongly confirm our proposed method presents a superior quality, improves the accuracy of landslide deformation prediction. And it is expected to be significant for the landslide displacement prediction in the future.