Spatiotemporal deformation characteristics and triggering factors of Baijiabao landslide in Three Gorges Reservoir region, China

摘要

Variations of reservoir water level and seasonal precipitation have resulted in significant movement and destabilization of landslides in the Three Gorges Reservoir (TGR) region of China since reservoir impoundment in 2003. An example is the Baijiabao landslide, a large, actively creeping landslide located in the steep lower valley of the Xiangxi River, about 55 km upstream of the TGR dam in the Yangtze River. Twelve years of monthly monitoring at four GPS stations and routine, monthly field observations show cumulative GPS displacements as large as >1.5 m and widely developed ground cracks. GPS monitoring results show that most movement takes place in rapid steps that coincide with the rainy season and the period of annual reservoir drawdown, with particularly large steps in 2009, 2012 and 2015. This step-like pattern of displacement is also shown by daily data from an automatic monitoring system installed in 2017. The total period of acceleration shown by these daily data was about six weeks long, with rapid movement starting during rapid reservoir drawdown, and terminating when the reservoir began to rise again. In particular, most of the 2018 displacement occurred in only two weeks. Different subzones of the landslide move at different rates and exhibit different features of deformation. The neighborhood rough set theory is used to identify the triggering factors responsible for landslide deformation. The most important triggering factors vary between different sites, data types and the time interval used to define them. The surface deformation and ground crack widening are controlled by the combination of rainfall and variations in the reservoir water levels, whereas the deformation of the sliding zone is most sensitive to the latter. The results show that daily data are needed to capture important, short-term landslide responses. The neighborhood rough set theory for determination of triggering factors is suggested for deformation prediction, stability evaluation, and prevention and control of reservoir landslides in this and other regions. (C) 2019 Elsevier B.V. All rights reserved.