Earthquake forecasting clues unearthed in strange precariously balanced
rocks

Date:
October 1, 2020
Source:
Imperial College London
Summary:
Naturally formed balancing boulders could be used to help scientists
to forecast large earthquakes more precisely.



FULL STORY ========================================================================== Precariously balanced rocks (PBRs) are formations found throughout the
world where a slender boulder is balanced precariously on a pedestal
boulder. They form as blocks preserved on cliffs, or when softer
rocks erode and leave the harder rocks behind. They can also form when landslides or retreating glaciers deposit them in strange positions.


========================================================================== Despite their delicate balancing act, many PBRs -- like the Brimham
Rocks in Yorkshire, or Chiricahua National Monument in Arizona -- have
survived earthquake shaking over thousands of years. They can therefore
tell us the upper limit of earthquake shaking that has occurred since
they were first formed -- shaking that, were it strong enough, would
have caused them to topple.

By tapping into ancient geological data locked within Californian PBRs, Imperial College London researchers have broken ground on a new technique
to boost the precision of hazard estimates for large earthquakes by up
to 49 per cent.

Earthquake hazard models estimate the likelihood of future earthquakes
in a given location. They help engineers decide where bridges, dams,
and buildings should be built and how robust they should be -- as well
as informing earthquake insurance prices in high-risk areas.

The findings are published today in AGU Advances.

Lead author Anna Rood, from Imperial's Department of Civil and
Environmental Engineering, said: "This new approach could help us work
out which areas are most likely to experience a major earthquake. PBRs
act like inverse seismometers by capturing regional seismic history that
we weren't around to see, and tell us the upper limit of past earthquake
shakes simply by not toppling. By tapping into this, we provide uniquely valuable data on the rates of rare, large-magnitude earthquakes."
Current earthquake hazard estimates rely largely on observations like
proximity to fault lines and how seismically active a region has been
in the past.

However, estimates for rarer earthquakes that have occurred over periods
of 10,000 to 1,000,000 years are extremely uncertain due to the lack
of seismic data spanning those timescales and subsequent reliance on
rocky assumptions.



==========================================================================
By counting rare cosmic ray-generated atoms in PBRs and digitally
modelling PBR-earthquake interactions, Imperial researchers have created
a new method of earthquake hazard validation that could be built into
existing models to finetune their precision.

Rock clocks To tap into the seismology of the past, the researchers set
out to determine the fragility (likelihood of toppling due to ground
shaking) and age of PBRs at a site near to the Diablo Canyon Nuclear
Power Plant in coastal California.

They used a technique called cosmogenic surface exposure dating --
counting the number of rare beryllium atoms formed within rocks by
long-term exposure to cosmic rays -- to determine how long PBRs had
existed in their current formation.

They then used 3D modelling software to digitally recreate the PBRs
and calculate how much earthquake ground shaking they could withstand
before toppling.



==========================================================================
Both the age and fragility of the PBRs were then compared with current
hazard estimates to help boost their certainty.

They found that combining their calculations with existing models
reduced the uncertainty of earthquake hazard estimates at the site
by 49 per cent, and, by removing the 'worst-case-scenario' estimates,
reduced the average size of earthquakes estimated to happen once every
10,000 years by 27 per cent. They also found that PBRs can be preserved
in the landscape for twice as long as previously thought.

They conclude that this new method reduces the amount of assumptions,
and therefore the uncertainty, used in estimating and extrapolating
historic earthquake data for estimates of future risk.

Study co-author Dr Dylan Rood, of Imperial's Department of Earth Science
and Engineering, said: "We're teetering on the edge of a breakthrough in
the science of earthquake forecasting. Our 'rock clock' techniques have
the potential to save huge costs in seismic engineering, and we see them
being used broadly to test and update site-specific hazard estimates
for earthquake-prone areas -- specifically in coastal regions where
the controlling seismic sources are offshore faults whose movements are inherently more difficult to investigate." The team are now using their techniques to validate hazard estimates for southern California -- one
of the most hazardous and densely populated regions of the United States.

Anna said: "We're now looking at PBRs near major earthquake faults
like the San Andreas fault near Los Angeles. We're also looking at how
to pinpoint which data -- whether it be fault slip rates or choice of
ground shaking equations - - are skewing the results in the original
hazard models. This way we can improve scientists' understanding of big earthquakes even more."

========================================================================== Story Source: Materials provided by Imperial_College_London. Original
written by Caroline Brogan. Note: Content may be edited for style
and length.


========================================================================== Journal Reference:
1. A. H. Rood, D. H. Rood, M. W. Stirling, C. M. Madugo,
N. A. Abrahamson,
K. M. Wilcken, T. Gonzalez, A. Kottke, A. C. Whittaker, W. D. Page,
P. J.

Stafford. Earthquake Hazard Uncertainties Improved Using
Precariously Balanced Rocks. AGU Advances, 2020; 1 (4) DOI:
10.1029/2020AV000182 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/10/201001113628.htm

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