Displacement characteristics and prediction of Baishuihe landslide in the Three Gorges Reservoir

doi:10.1007/s11629-019-5470-3

CORC > 成都山地灾害与环境研究所 > 中国科学院水利部成都山地灾害与环境研究所 > Journal of Mountain Science > Journal of Mountain Science-2019 > Vol16 No.9

	Displacement characteristics and prediction of Baishuihe landslide in the Three Gorges Reservoir
	Li De-ying; Sun Yi-qing; Yin Kun-long; Miao Fa-sheng; Glade, Thomas; Leo, Chin
刊名	JOURNAL OF MOUNTAIN SCIENCE
	2019
卷号	16 期号:9 页码:2203-2214
关键词	Landslide Three Gorges Reservoir Impoundment process Displacement prediction
ISSN号	1672-6316
DOI	10.1007/s11629-019-5470-3
文献子类	Article
英文摘要	In order to reach the designated final water level of 175 m, there were three impoundment stages in the Three Gorges Reservoir, with water levels of 135 m, 156 m and 175 m. Baishuihe landslide in the Reservoir was chosen to analyze its displacement characteristics and displacement variability at the different stages. Based on monitoring data, the landslide displacement was mainly influenced by rainfall and drawdown of the reservoir water level. However, the magnitude of the rise and drawdown of the water level after the reservoir water level reached 175 m did not accelerate landslide displacement. The prediction of landslide displacement for active landslides is very important for landslide risk management. The time series of cumulative displacement was divided into a trend term and a periodic term using the Hodrick-Prescott (HP) filter method. The polynomial model was used to predict the trend term. The extreme learning machine (ELM) and least squares support vector machine (LS-SVM) were chosen to predict the periodic term. In the prediction model for the periodic term, input variables based on the effects of rainfall and reservoir water level in landslide displacement were selected using grey relational analysis. Based on the results, the prediction precision of ELM is better than that of LS-SVM for predicting landslide displacement. The method for predicting landslide displacement could be applied by relevant authorities in making landslide emergency plans in the future.
电子版国际标准刊号	1993-0321
语种	英语
WOS记录号	WOS:000485301000017
内容类型	期刊论文
源URL	[http://ir.imde.ac.cn/handle/131551/46583]
专题	Journal of Mountain Science_Journal of Mountain Science-2019_Vol16 No.9
推荐引用方式 GB/T 7714	Li De-ying,Sun Yi-qing,Yin Kun-long,et al. Displacement characteristics and prediction of Baishuihe landslide in the Three Gorges Reservoir[J]. JOURNAL OF MOUNTAIN SCIENCE,2019,16(9):2203-2214.
APA	Li De-ying,Sun Yi-qing,Yin Kun-long,Miao Fa-sheng,Glade, Thomas,&Leo, Chin.(2019).Displacement characteristics and prediction of Baishuihe landslide in the Three Gorges Reservoir.JOURNAL OF MOUNTAIN SCIENCE,16(9),2203-2214.
MLA	Li De-ying,et al."Displacement characteristics and prediction of Baishuihe landslide in the Three Gorges Reservoir".JOURNAL OF MOUNTAIN SCIENCE 16.9(2019):2203-2214.