The predictability of shallow landslides: lessons from a natural laboratory

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Rupert Bainbridge, Michael Lim, Stuart Dunning, Mike Winter, Alejandro Diaz-Moreno, James Martin, Hamdi Torun, Bradley Sparkes, Muhammad Khan, Nanlin Jin


Shallow landslides are a significant hillslope erosion mechanism and can transform into destructive debris-flows. Limited understanding of the controls on debris-flow initiation, development and deposition results in persistent risk and high impacts where linear infrastructure is affected. Here, we analyse steep slopes above a key road, the A83 Rest and be Thankful, Scotland, where near-real-time rain gauge data, time-lapse camera deformation tracking and seismics allow us to define thresholds for increased debris-flow risk, examine long-term slope creep and, detect debris-flow occurrence. We show the patterns and development of channelized and hillslope debris-flows that act as a key geomorphic agent, accounting for 58% of landslide source volume over 13-years. On-slope rainfall data allow us to quantify the effect of antecedent rainfall and storm intensity-duration on landslide triggering and develop new local thresholds over which landslides are likely to occur. To better equip asset managers, we use time-lapse imagery vector tracking to detect slope instabilities, and deformation rates to calculate inverse-velocity values to indicate if failure is imminent. Low-cost seismometers are used to detect when a debris-flow has occurred and locate the source area. The suite of sensors has provided vital information both prior to failure, and during debris-flows to support operational decision-making for authorities dealing with complex slope hazards.



Physical Sciences and Mathematics


Risk, Debris-flow, Infrastructure, Hazard


Published: 2020-11-23 11:50

Last Updated: 2020-11-23 19:50


CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:

Data Availability (Reason not available):
Intended to be available via the BGS landslide database in the near future.

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