22 February 2019
Longjing village: successful prediction of a significant rockslide
Posted by Dave Petley
Longjing village: successful prediction of a significant rockslide
On 17th February 2019 a significant and potentially hazardous rockslide occurred in Longjing village, in Xingyi, Guizhou province, Southwest China. This landslide, which is formed primarily from dolomite, had a volume of about 1.4 million cubic metres. The landslide is shown below:-
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This landslide was initially triggered in 2013 by cutting of the toe of the slope during road construction . The image below shows the state of the slope before the February 2019 landslide:-
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The image shows a 270 metre long sliding surface with a steep scarp at the crown. It is unsurprising that there was potential further instability in this area, and the sliding surface clearly meant that the debris could impact the road. Investigations by SKLGP suggested that movement was facilitated on a 2 to 5 cm thick layer of clay between the dolomite bands, a situation that is often hazardous.
On June 2018 a 0.9 m wide tension crack was observed above the existing landslide crown, suggesting that further instability was developing. Over the next few months further deformation was observed. The local government worked with Professor Nengpan Ju and Professor Qiang Xu from SKLGP to install a real-time monitoring system on the landslide. This system is based on the analysis of patterns of deformation of the landslide (see Xu et al. 2017), and in particular it uses artificial intelligence to identify accelerating trends in movement data, sending an alert message when key thresholds were met. In this case, the system identified such a trend over the day preceding the landslide, issuing a “caution” (yellow) warning on 13th February and a “vigilance” (orange) warning on 15th February. Early in the morning on 17th February 2019 a red alert was issued, allowing 400 people from the area around the slope to be evacuated. The slope failed later that day.
The image below shows the movement record of the landslide:-
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In the main graph the green triangles show the displacement of a sensor on the landslide with time, showing the characteristic hyperbolic acceleration to failure. The blue stars represent the analytical approach used to trigger the alerts, which are shown in the bar chart at the foot of the image.
This is not the first time that this system has been successfully deployed. In 2017 SKLGP report that it was used to predict the failure of two loess landslides in Gansu province, at Heifangtai in Yongjing County.
The development of warning systems for landslides continues to be a challenging but exciting area, and there is little doubt that in certain circumstances they can be a useful tool. In this case the system has played a major role in increasing public safety, which is very welcome.
Reference
Xing Zhu, Qiang Xu, Xing Qi, Hanxiang Liu. 2017. A Self-adaptive Data Acquisition Technique and Its Application in Landslide Monitoring. In WLF 2017: Advancing Culture of Living with Landslides pp 71-78. https://link.springer.com/chapter/10.1007%2F978-3-319-53487-9_7
Acknowledgement
Thanks to Professor Xuanmei Fan at SKLGP, Chengdu University of Technology, for providing information and the images that are the basis for this post.
Any idea how many draw-wire displacement sensors were deployed?
This is very good news for that village and others. Is the Green triangle the data reading for the 24 Hour period?
This would typify a near real-time, at best system. Equally of value for safety. I am interested to know how often and from what “sensor: the data is from? A TDR cable? Extensometer? Active monitoring is important, no matter how often or in what (time) domain the data are plotted.
With the road-cut destabilizing the relatively shallow topography immediately adjacent to it, I’m curious if the resultant rockslide scarp advanced an instability uphill, perhaps to a greater degree? It appears much buttressing was removed from the base of the more steeply walled middle promontory (without transmission tower). The surrounding slope’s angle of repose suggests high relief isn’t tolerated for long. From the road construction’s trigger, could successive wasting continue ascending to the far right peak, with the eventual collapse of the entire massif?
Better keep Professors Ju and Xu’s real-time monitoring up-&-running!
……….(and move those high-transmission lines)
Definitely the prediction of landslide is challenging and exciting field of geotechnical engineering. This techniques will be very helpful in many road side slopes of the mountainous roads of Nepal.