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1 March 2019

US101 at Brookings: an interesting, disruptive landslide

US101 at Brookings: an interesting, disruptive landslide

On Tuesday, significant movement occurred on a large landslide in Oregon, closing the important US101 highway near to the coastal town of Brookings.  This landslide (location 42.219, -124.374), which seems to have been triggered by heavy rainfall, is captured very nicely in a drone image Tweeted by Tidewater Contractors:-

US101

The major landslide on US101 at Brookings. Image via Tidewater Contractors on Twitter

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Tidewater Contractors have also tweeted this rather splendid image of the main part of the landslide:-

US101

The main body of the US101 landslide near to Brookings in Oregon. Image tweeted by Tidewater Contractors.

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This appears to be a large, moderately deep earthflow.  Note the very clear scarps at the crown of the landslide and the beautiful array of tension cracks in the area in which the landslide mass steepened.  Note also the very clear lateral scarps on the lower slopes towards the highway.  The disruption to the road is very significant; Tidewater Contractors have tweeted a drone video showing the road damage, whilst the image  below shows the impacts in more detail:-

US101

Road damage on Highway 101 near to Brookings caused by the large earthflow on Tuesday. Image tweeted by Tidewater Contractors.

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There is an interesting article on Willamette Week that examines these types of landslide in Oregon in the context of climate change, drawing upon recent studies and expert knowledge.  They note that these areas are being affected by both increases in groundwater level and by increased erosion of the coastal bluffs due to increased wave energy.  This is the Google Earth imagery of the US101 landslide, with the image dated 3rd July 2016:-

US101

Google Earth imagery from July 2016 showing the site of the US101 landslide near to Brookings in Oregon.

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The landslide is clearly identifiable in the Google Earth imagery, and there is evidence that movement has disrupted the road.  The image demonstrates that the toe of the landslide is being eroded by wave action, leaving the slope more susceptible to the effects of increased groundwater levels.

The road is set to be closed for at least a month.

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28 February 2019

Triggering and Propagation of Rapid Flow-like Landslides – The Proceedings of the Second JTC-1 Workshop

flow-like landslides

The 2012 Giyari landslide near to the Siachen glacier in northern Pakistan.

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Triggering and Propagation of Rapid Flow-like Landslides – The Proceedings of the Second JTC-1 Workshop

Back in December JTC-1 organised a workshop, held in Hong Kong, on the Triggering and Propagation of Rapid Flow-like Landslides.  This was a fascinating event, with a host of excellent presentations and some very interesting discussion.  It included a benchmarking exercise that examined the state-of-the-art capability to model rapid and long run out flows.

The organisers of the conference have now placed the proceedings of the meeting, including the extended (four page) abstracts, online as a free resource.  These are bundled into one PDF (warning – it is 65 MB), which represents a really useful resource.

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26 February 2019

Two interesting new landslide videos from the Himalayas

Two interesting new landslide videos from the Himalayas

Heavy rainfall and snow over the Himalayas in recent days has triggered extensive landslides, with many roads being blocked.  A couple of videos have emerged showing landslide events, both of which are quite interesting.  The first for which there is little information, reportedly occurred in the Sainj Valley.  It appears to show a debris flow passing across a road, with a trapped pick up truck.  The vehicle is eventually lost to the flow:-

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The flow is quite interesting in terms of a constant flow of fairly coarse sediment, although the flow rate appears to increase with time:-

Sainj valley debris flow in the Himalayas

The debris flow in the Sainj valley. Still from a video from Youtube.

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The second video is an unusual collapse in a slope that combines weathered bedrock and a large unweathered block, which is undermined by the ongoing failure:-

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The sequence of images below shows the evolution of movement of the large unweathered block, which starts by sliding, with a strong element of ploughing of the debris down slope, before the block starts to topple forward, at which point it rapidly fragments:-

Himalayas

The evolution of the larges, less weathered block in the landslide in the Himalayas. Still from a video posted to Youtube

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The video shows the complex movement mechanisms of this types of slide. Interestingly, it is very unlikely that this would have been evident from the landslide scar and debris pile, which illustrates the challenges of back analysis of landslides without evidence of the morphology of the slope before the failure occurred.

Meanwhile, there has been a number of landslides in the US in recent days, including this example from WV-112, Ingleside Road in West Virginia:-

Sainj landslide

The landslide at Mercer County in West Virginia. Image from wdbj7.

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This will take some effort to clear.

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25 February 2019

The Baige landslide, Tibet: analysing seismic data to determine mass movement behaviour

The Baige landslide, Tibet: analysing seismic data to determine mass movement behaviour

Back in October 2018, a large landslide occurred in Tibet, temporarily blocking the valley.  This landslide, which is located at 31.081, 98.706, and which I termed at the time the Jomda County rockslide, involved 24.5 million m³ of material, sliding over a distance of 1,400 metres. This was a bedrock landslide that created a debris pile 2 km long and 450 m wide, with a height of about 160 m.  In one of my original posts about the landslide I included the following Planet Labs image:-

Baige landslide

The major valley-blocking landslide at Baige in Tibet. Planet Labs 3-band PlanetScope scene collected on 12th November 2018, used with permission.

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In a new paper just published in the journal Landslides, Zhang et al. (2019) have analysed the seismic signals generated by this large rockslope failure.  This is the latest example of the use of seismic data to understand mass movement processes, an area of development that is very exciting at the moment.  The analysis suggests that the initial failure occurred as a sliding block with a volume of about 7.8 million cubic metres.  In the paper, Zhang et al. (2019) suggest that this was a block at the crown of the landslide, as per the diagram below:-

Baige landslide in Tibet

Interpretation of the behaviour of the Baige landslide in Tibet. Diagram from Zhang et al. (2019).

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The seismic data suggest that the landslide then fragmented to form granular debris; within 50 seconds of initiation the block had completely disaggregated.  The landslide eroded and entrained debris further down the slope, and the northern flank of the landslide (marked as the entrainment area above) also mobilised.  The landslide movement was complete after 89 seconds.  Interestingly, the material in the source area initially accelerated to 22 metres per second (about 80 km per hour, or 50 mph), but slowed slightly to about 18 metres per second when it encountered the resistance from the initially unfailed material on the lower slope.  Thereafter it accelerated again to about 20 metres per second.

This is a fascinating study that demonstrates the ways in which seismic data can be  used to understand the landslide processes.  In the paper, Zhang et al. (2019) make the point that initial reports indicated that the landslide occurred in the morning of 11th October 2018, whilst the seismic data demonstrates definitively that the slide happened late in the evening of the previous day.

Reference

Zhang, Z., He, S., Liu, W. et al. 2019.  Source characteristics and dynamics of the October 2018 Baige landslide revealed by broadband seismograms. Landslides. https://doi.org/10.1007/s10346-019-01145-3

Planet Team (2019). Planet Application Program Interface: In Space for Life on Earth. San Francisco, CA. Planet.com

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22 February 2019

Longjing village: successful prediction of a significant rockslide

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:-

Longjing

The Longjing village landslide in Guizhou village, China. Image via SKLGP.

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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:-

Longjing village landslide

The Longjing village landslide prior to the February 2019 failure. Image via SKLGP.

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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:-

Longjing village landslide

The movement record of the Longjin landslide as it accelerated to failure. Data provided by SKLGP, used with permission.

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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.

 

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19 February 2019

New on EarthArXiv: a first analysis of the flank failure of the Anak Krakatau volcano

New on EarthArXiv: a first analysis of the flank failure of the Anak Krakatau volcano

A paper has recently been posted to the open source repository EarthArXiv that provides a first analysis of the flank failure of Anak Krakatau volcano on 22 December 2018, which generated a tsunami that killed 431 people.  The paper, Williams et al. (2019), uses a combination of remote sensing and eyewitness accounts to examine the sequence of events that generated the tsunami.  Regular readers of the blog will remember that at the time it was quite difficult to untangle the sequence as volcanic eruptions before and after the collapse changed the topography quickly.

Williams et al. (2019) provide a particularly interesting perspective on the radar imagery collected over that period.  Interestingly there is an animation of the radar sequence on Youtube, which also includes some initial interferometric analysis by reader funkenbeachin.  InSAR is very difficult in a massif that has undergone so much change, but the radar sequence is very revealing:-

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Williams et al. (2019) note that Sentinel-1A captured an image about 8 hours after the initial collapse event.  This is shown in Panel C in the image from the paper below:-

Anak Krakatau

Satellite imagery of the series of events before and after the flank collapse at Anak Krakatau on 22 December 2018. Imagery from Sentinel-1A and Sentinel-2A

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Williams et al. (2019) propose that the initial failure event consisted of an approximately 100 million cubic metre submarine failure, with a comparatively small (4 million cubic metre) terrestrial component.  They suggest that the main part of the flank collapsed completely to generate the tsunami, with a smaller block, higher on the island, partially failing in a rotational manner to generate the approximately north-south orientated plane visible in the imagery.  The failure decompressed the plumbing of the volcano to allow a new magma pathway to open, allowing the subsequent eruptive activity.

I am intrigued by  the fate of this smaller partially failed block – if I was a referee I would want this to be considered more directly.  This block does not appear in image D above, suggesting that it has failed in a second event.  Did this occur in one movement or was it eroded away during the subsequent eruptive activity?  The question of sequencing of flank failures is really important to understand likely tsunami generation, so this feels like a key issue.

Perhaps the most important part of this paper is this section:-

“We show that the flank failure was unexceptional, meaning that an extraordinary event was not required to trigger the tsunami, yet it had catastrophic consequences…The volume of the flank failure was small, compared to predicted collapse volumes and flank collapses at 25 other volcanoes, yet it generated a tsunami as large as and faster than modelled with a significantly larger collapse…this study also highlights that existing hazard assessments at volcanic islands are very likely underestimating the risks from volcanogenic tsunamis due to small (<0.25 km³) failures.”

That feels to me to be a very important set of conclusions from a very interesting and useful initial analysis.

Reference

Williams, R., Rowley, P., & Garthwaite, M. C. 2019. Reconstructing the Anak Krakatau flank collapse that caused the December 2018 Indonesian tsunami. EarthArXiv. https://doi.org/10.31223/osf.io/u965c

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18 February 2019

The giant Daguangbao landslide: superheated steam and hot carbon dioxide

The giant Daguangbao landslide: superheated steam and hot carbon dioxide

It has long been known that extremely large landslides are able to travel surprisingly large distances – a phenomenon sometimes known as hyper-mobility – which implies that there must be very low levels of friction operating at the base of slide.  Numerous methods have been proposed to account for this behaviour, but trying to gain evidence to support them or refute them is challenging.

The largest non-volcanic, terrestrial rockslide in recent years was the huge Daguangbao landslide, triggered by the 2008 Wenchuan earthquake.  This is a true giant, with a volume of just over a cubic kilometre, which moved over a distance of about 3 km, as shown in the Google Earth image below:-

Daguangboa landslide

Google Earth image of the Dagunagbao landslide. The label marks the crown of the rear scarp of the landslide. The bare rock in the source area is also clear, as is the huge debris deposit.

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The mechanisms of this complex event, and in particular the processes that occurred in the basal region during its movement, are extensively explored in a new paper just published in the journal Earth and Planetary Science Letters (Hu et al. 2019). The cross section from the paper, shown below, illustrates the extraordinary scale of the landslide:-

Daguangbao landslide

The geological cross section of the Daguangbao landslide. Diagram from Hu et al. (2019).

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The statistics of this landslide are remarkable – for example, the debris in the deposit area is, in places, 500 m thick. This landslide would undoubtedly have traveled a great deal further had the topography allowed.

Hu et al. (2019) used a rotary shear machine to explore the processes operating at the base of the landslide as it moved.  Samples of the basal dolomite were sheared at rates similar to those in the slide, and the strength was measured.  The samples were then chemically and physically analysed to see if changes had occurred as a result of the deformation. During shearing,the resistance of the basal surface was found to drop as the rate of shearing increased.  This is a neat self-reinforcing mechanism, which has been seen before.  Basically, the earthquake initiated sliding and, as the landslide accelerated the friction in the base dropped, allowing the slide to accelerate further, which in turn further reduced the friction.  That such a mechanism was operating is no great surprise.

But what is interesting here is that two processes were operating simultaneously to generate this very low friction.  In both cases these are associated the very high temperatures caused by the shearing under such high pressure conditions.  These were found to exceed 800°C, at which point carbon dioxide started to be released by the shear zone rocks as they decomposed under the high temperatures.  This carbon dioxide coated the shear surface in a supercritical fluid (and there would have been superheated steam present too), which in effect increased the pore fluid pressure, reducing the friction.

Analysis of the rocks after the experiments found evidence for the decomposition of the dolomite rocks (described above), but also of dynamic recrystallization, which provides the second mechanism.  This dynamic recrystallization formed a very thin layer on the shear surface, just o.1 mm thick, whose viscous resistance was found to be very low.  As such, this dynamically recrystallized layer would have generated very low frictional resistance.

So, in the case of the Daguangbao landslide, two process operating in tandem generated the rapid drop in friction that gave this huge mass of rock the ability to travel at high speeds.  Such mechanisms can only operate in very thick slides, and thus do not explain the hyper-mobility seen in other cases.

But this study shows that the behaviour of a 2 billion tonne landslide might have been controlled by a layer that is just 0.1 mm thick, which seems remarkable.

Reference

Hu,W., Huang, R., McSaveney, M., Yao, L., Xu, Q., Feng, M. and Zhang, X. 2019. Superheated steam, hot CO2 and dynamic recrystallization from frictional heat jointly lubricated a giant landslide: Field and experimental evidence. Earth and Planetary Science Letters, 510, 85-93. https://doi.org/10.1016/j.epsl.2019.01.005.

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15 February 2019

Sausalito: a mudslide damages houses in California

Sausalito: a mudslide damages houses in California

Heavy rain in California, brought by an atmospheric river event, triggered a significant mudslide in Sausalito yesterday.  ABC7 News has a report on the incident:-

“At least 50 homes remain evacuated after a massive mudslide struck a neighborhood in Sausalito on Crescent Avenue and Sausalito Boulevard.  One of the homes on Crescent Avenue slid into a home on Sausalito Boulevard. A woman was inside the home that slid. She was taken to the hospital and has been released. The other home was not occupied at the time.  When firefighters first arrived they evacuated the 50 homes over concerns that the hill could continue to give. Officials were also concerned that a gas line had ruptured and power lines were down.”

The image below shows the aftermath of the landslide.  In Hong Kong the initial event would be classed as an open hillslope failure, with the debris transitioning into a channelised flow.  There are reports that this slope has suffered failures previously:-

Sausalito

The aftermath of the mudslide in Sausalito on 14th February 2019. Image from ABC7 News.

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ABC7 News also has a drone video of the aftermath of the landslide. The site of the mudslide in Sausalito is shown in the Google Earth image below:-

Sausalito mudslide

Google Earth imagery of the site of the mudslide in Sausalito on 14th February 2019

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Note the smaller landslide scar above the road; this was not the site of the failure on this occasion.

The steeper slopes of California have a long track record of landslides, resulting from the combination of the topography built from active tectonic processes, the geological materials and the occurrence of both heavy rainfall events and earthquakes. It remains a surprise to see the number of houses that are built in geomorphologically-active areas, such as channels. It is unsurprising that there is frequent landslide damage in these areas during heavy rainfall.

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13 February 2019

Pre-failure movement analysis of the Su Village (Sucun) landslide in China

Pre-failure movement analysis of the Su Village (Sucun) landslide in China

Back in April 2018 I wrote about an analysis of the Su Village (also known as Sucun) landslide in Zhejiang Province, China in 2016.  This landslide, which was caught on video, killed 27 people.  The analysis in Landslides published last year  (Ouyang et al. 2018) indicated that some pre-failure deformation of the landslide had been detected.  A new paper, also published in Landslides (Ouyang et al. 2019), examines this aspect of the landslide in more detail, considering in particular the degree to which pre-failure deformation could be detected using satellite imagery.

The paper includes the image below of the landslide, showing clearly the source zone for the failure (marked with the green arrows), the landslide track (yellow) and the deposition zone (in green again).  The area in which the landslide impacted upon the village can be seen in the lower left corner of the image:-

Su Village landslide

Annotated sketch of the Su Village (Sucun) landslide in Zhejiang Province, China. Image from Ouyang et al. (2019).

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The authors used Sentinel-1A SAR (radar) imagery to investigate pre-failure deformation of the Su Village landslide, based upon an analysis of the 36 images using Persistent Scatterer Interferometry.  The image below shows the points that were analysed across the landslide and its adjacent slopes, with the colours indicating the magnitude of the movement detected:-

Su Village (Sucun) landslide

Analysis of the pre-failure deformation of the Su Village (Sucun) landslide using PSI. Image from Ouyang et al. (2019).

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My interpretation of the is that the yellow and green dots show no movement beyond error in the technique, whereas the orange and red dots show detectable deformation.  The failure initiated in the source area shown in the first image, which then caused the rest of the slope to collapse, so it is reassuring that the detectable pre-failure deformation is situated high in the slope.  The highest rates are in the section of the slope that collapsed, close to the crown of the landslide.  But note also that significant deformation is seen in adjacent slopes that, at the time of analysis, had not failed.  Thus, the InSAR results do not give a spatial indication of the likely form of the final failure (whilst also suggesting that there may be other hazardous areas on this slope).

The displacement – time series graph also shows the results of this analysis, based on the points shown in the image above:-

Su village landslide

Time series analysis of the pre-failure deformation of the Su Village (Sucun) landslide using PSI. Graph from Ouyang et al. (2019).

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There is a mixed picture here.  The good news is that statistically significant movement was detected in the areas that failed, whilst the unfailed areas displayed no trend (with some noise).  But the detected movement is linear with time in all three points with above-error deformation, meaning that no inferences could be drawn to indicate time of failure.  Thus, whilst the analysis shows that the slope was creeping, it could not be used as a warning system.

This paper is another very useful contribution towards the use of InSAR data for rock slope failure detection in natural slopes.  But, once again, it shows that this is a very complex and challenging problem, and that our satellite based systems do not yet have the maturity to be used operationally in many cases as yet.

References

Ouyang, C., Zhao, W., Xu, Q. et al. 2018. Failure mechanisms and characteristics of the 2016 catastrophic rockslide at Su village, Lishui, China. Landslides. https://doi.org/10.1007/s10346-018-0985-1

Ouyang, C., Zhao, W., An, H. et al. 2018. Early identification and dynamic processes of ridge-top rockslides: implications from the Su Village landslide in Suichang County, Zhejiang Province, China. Landslides. https://doi.org/10.1007/s10346-018-01128-w.

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12 February 2019

Cuajone mine in Peru: reports of landslide damage, and a fatality, caused heavy rain

Cuajone mine in Peru: reports of landslide damage, and a fatality, caused heavy rain

Cuajone mine in Peru is a giant mine and smelter located at an elevation of 3,400 metres in the Andes.  The mine, which uses open pit excavation to extract copper ore from an enormous deposit, is owned by Southern Copper.  The Google Earth image below gives an idea of the scale of the mine:-

Cuajone mine

Google Earth image of the Cuajone mine in Peru.

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This area of Peru has suffered unusual, very heavy, rainfall in the last few days.  At least 10 people have been killed in various incidents, with mudslides and rockfalls being widely reported.  Southern Copper has reported that production at Cuajone mine has been reduced for three to five days as a result of damage inflicted upon its infrastructure by the heavy rains.  It is reported that a worker has been killed by a mudslide, reportedly in a ravine.

Whilst the picture is uncertain, there are various reports about fears that there has been a tailings failure at Cuajone mine.  The basis of these reports appears to be observed contamination of the river downstream of Cuajone mine.  This report is from CNBC:-

“Peru’s environmental regulator OEFA has been investigating a potential tailings spill at Southern Copper’s Cuajone mine, after being alerted by local residents of a “greenish solution” that started streaming into a nearby river.”

Whilst Southern Copper denies that there has been a tailings spill, this event is being taken sufficiently seriously that OEFA have a statement on their website confirming that it is being investigated.  At present this does not appear to be a tailings dam failure, and there is no obvious signs of this type of event on the satellite imagery of the last few days.  However, these reports of landslides at Cuajone mine are likely to raise concerns about the management of tailings at large mine sites, and once again reiterates the problems that the mining industry is facing with safe slope management.

Meanwhile, there has been yet another mining related landslide in the Hpakant area of Myanmar, this time killing six people.  This is the latest of the long and desperate recent history of jade mining landslides in Kachin state.  The death toll in 2019 is already at least ten people, this will inevitably increase substantially in the months ahead.

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