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Taking a Landslide's Temperature to Avert Catastrophe:

The disaster Veveakis is referring to occurred at the Vajont Dam, one of the tallest in the world at 860 feet, in northern Italy in 1963. After years of attempting to mitigate a slow, incremental landslide of roughly an inch per day in the adjoining mountainside by lowering the water level of the lake behind the dam, the landslide suddenly accelerated without warning. Nearly 10 billion cubic feet of rock plummeted down the gorge and into the lake at almost 70 miles per hour. That created a tsunami more than 800 feet tall that crashed over the dam, completely wiping out several small towns below and killing nearly 2,000 people.

Before the catastrophe occurred, scientists did not believe any potential landslide would result in a tsunami more than 75 feet tall.

[...] In 2007, Veveakis put the pieces together and developed a model that fit the scientific observations of the disaster. It showed how water seeping into rock above an unstable layer of clay caused a creeping landslide, which in turn heated up and further destabilized the clay in a feedback loop until it rapidly failed.

"Clay is a very thermally sensitive material and it can create a shear band that is very susceptible to friction," said Carolina Segui, a PhD candidate in Veveakis's laboratory and first author of the new paper. "It's the worst material to have in such a critical place and is a nightmare for civil engineers constructing anything anywhere."

[...] In the new study, Veveakis, Segui and Hadrien Rattez, a postdoctoral researcher in Veveakis's laboratory, plug the old model's holes and provide the ability to incorporate a combination of time-dependent external loading and internal degradation. The resulting model is able to recreate and predict observations taken from very different, deep-seated landslides.

"Traditional landslide models have a static internal material strength, and if you exceed it the landslide fails," said Veveakis. "But in examples such as these, the landslide is already moving because its strength has already been exceeded, so those models don't work. Others have tried to use machine learning to fit the data, which has worked sometimes, but it doesn't explain the underlying physics. Our model incorporates the properties of soft materials, allowing it to be applied to more landslides with different loading characteristics and provide an operational stability criterion by monitoring its basal temperature."

Besides using the model to recreate the movements of the Vajont slide and explaining the mechanisms underpinning its motion for more than two years, Veveakis and Segui show that their model can accurately recreate and predict the movements from the Shuping landslide, another slow-moving landslide at the Three Gorges Dam in China, the largest dam in the world.

Journal Reference:
C. Seguí, H. Rattez, M. Veveakis. On the stability of deep‐seated landslides. The cases of Vaiont (Italy) and Shuping (Three Gorges Dam, China), Journal of Geophysical Research: Earth Surface (DOI: 10.1029/2019JF005203)