Predictability of Landslide Timing From Quasi‐Periodic Precursory Earthquakes
Accelerating rates of geophysical signals are observed before a range of material failure phenomena. They provide insights into the physical processes controlling failure and the basis for failure forecasts. However, examples of accelerating seismicity before landslides are rare, and their behavior...
Saved in:
Published in | Geophysical research letters Vol. 45; no. 4; pp. 1860 - 1869 |
---|---|
Main Author | |
Format | Journal Article |
Language | English |
Published |
Washington
John Wiley & Sons, Inc
28.02.2018
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Accelerating rates of geophysical signals are observed before a range of material failure phenomena. They provide insights into the physical processes controlling failure and the basis for failure forecasts. However, examples of accelerating seismicity before landslides are rare, and their behavior and forecasting potential are largely unknown. Here I use a Bayesian methodology to apply a novel gamma point process model to investigate a sequence of quasiperiodic repeating earthquakes preceding a large landslide at Nuugaatsiaq in Greenland in June 2017. The evolution in earthquake rate is best explained by an inverse power law increase with time toward failure, as predicted by material failure theory. However, the commonly accepted power law exponent value of 1.0 is inconsistent with the data. Instead, the mean posterior value of 0.71 indicates a particularly rapid acceleration toward failure and suggests that only relatively short warning times may be possible for similar landslides in future.
Key Points
A large landslide in Greenland was preceded by a rapid power law acceleration in earthquake rates, faster than existing models predict
Earthquake characteristics indicate repeated quasiperiodic activation of single source, driven by accelerated loading
New Bayesian gamma point process method was successfully used to model data and offer improved probabilistic forecasts of future landslides |
---|---|
ISSN: | 0094-8276 1944-8007 |
DOI: | 10.1002/2017GL076730 |