22 April 2020
Zongling: an area of intense landslide activity in Guizhou Province, China
A very nice, open access paper (Wang et al. 2020) has just been published in the journal Landslides exploring a new technique for the analysis of InSAR data for measuring the deformation of mass movements. As I have noted previously, InSAR is one of the most exciting areas of landslide science at the moment, providing the opportunity to both detect potentially dangerous slopes and to monitor their movement remotely. Wang et al. (2020) describe a new approach, an improved Interferometric Point Target Analysis (IPTA) method, to analyse these complex datasets, demonstrating that for the study sites at least it is able to provide detailed information about the behaviour of the slope.
The site for this study is Zongling in Guizhou Province, China. The article describes a very interesting set of landslides – the location is 21.718, 105.265 – go and take a look on Google Earth:-
This ridge with multiple landslides consists of interbedded limestones, siltstones and mudstones, with a thick layer of limestone towards the crest of the slope. Wang et al. (2020) note that failure occurs as a result of the collapse of these thick limestone layers, which then induces movement and entrainment of materials below. As the image shows, these collapses have come perilously close to the town.
Whilst one’s eye is drawn to the section of slope in which collapses have already occurred at Zongling, the authors’ attention is on the unfailed portions of the slope. In the paper they demonstrate that there is substantial levels of movement across much of the slope. The InSAR data shows that the slopes creep continuously, but that accelerated periods of deformation occur in periods of heavy rainfall. The graphs below show the movement history of three areas of active deformation, plotted along with the precipitation, which appears to show that more movement occurs in periods of heavier (seasonal) rainfall::-
I urge caution in interpreting this graph though as something very odd is going on with the time series. The intervals between the x-axis labels are highly non-linear – for example there are four tick marks for data in 2018 and only one for 2016. So on first inspection the data appears to be a linear time series, but is not. I don’t think that data should be presented like this, and I’m surprised it got through the refereeing process in this form, but the episodic movement of the landslides appears to be evident.
But there is another factor in play here too. Wang et al. (2020) describe extensive coal mining in the Zongling area, including extraction over the last 25 years of coal from galleries located directly below the slopes. The InSAR data suggests that there is extensive deformation occurring on the lower portions on the slopes, suggesting that a key factor in these landslides might be disturbance caused by the mining.
Wang, J., Wang, C., Xie, C. et al. 2020. Monitoring of large-scale landslides in Zongling, Guizhou, China, with improved distributed scatterer interferometric SAR time series methods. Landslides. https://doi.org/10.1007/s10346-020-01407-5.