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TID: hpt/lnx 1.9.0-cur 2019-01-08
 Creating a tsunami early warning system using artificial intelligence
 Real-time classification of underwater earthquakes based on acoustic
signals enables earlier, more reliable disaster preparation 

  Date:
      April 25, 2023
  Source:
      American Institute of Physics
  Summary:
      Researchers develop an early warning system that combines acoustic
      technology with AI to immediately classify earthquakes and determine
      potential tsunami risk. They propose using underwater microphones,
      called hydrophones, to measure the acoustic radiation produced
      by the earthquake, which carries information about the tectonic
      event and travels significantly faster than tsunami waves. The
      computational model triangulates the source of the earthquake
      and AI algorithms classify its slip type and magnitude. It then
      calculates important properties like effective length and width,
      uplift speed, and duration, which dictate the size of the tsunami.


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FULL STORY
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Tsunamis are incredibly destructive waves that can destroy coastal
infrastructure and cause loss of life. Early warnings for such natural
disasters are difficult because the risk of a tsunami is highly dependent
on the features of the underwater earthquake that triggers it.

In Physics of Fluids, by AIP Publishing, researchers from the University
of California, Los Angeles and Cardiff University in the U.K. developed an
early warning system that combines state-of-the-art acoustic technology
with artificial intelligence to immediately classify earthquakes and
determine potential tsunami risk.

Underwater earthquakes can trigger tsunamis if a large amount of water is
displaced, so determining the type of earthquake is critical to assessing
the tsunami risk.

"Tectonic events with a strong vertical slip element are more likely to
raise or lower the water column compared to horizontal slip elements,"
said co-author Bernabe Gomez. "Thus, knowing the slip type at the
early stages of the assessment can reduce false alarms and enhance the
reliability of the warning systems through independent cross-validation."
In these cases, time is of the essence, and relying on deep ocean wave
buoys to measure water levels often leaves insufficient evacuation
time. Instead, the researchers propose measuring the acoustic radiation
(sound) produced by the earthquake, which carries information about
the tectonic event and travels significantly faster than tsunami
waves. Underwater microphones, called hydrophones, record the acoustic
waves and monitor tectonic activity in real time.

"Acoustic radiation travels through the water column much faster than
tsunami waves. It carries information about the originating source and its
pressure field can be recorded at distant locations, even thousands of
kilometers away from the source. The derivation of analytical solutions
for the pressure field is a key factor in the real-time analysis,"
co-author Usama Kadri said.

The computational model triangulates the source of the earthquake from the
hydrophones and AI algorithms classify its slip type and magnitude. It
then calculates important properties like effective length and width,
uplift speed, and duration, which dictate the size of the tsunami.

The authors tested their model with available hydrophone data and found
it almost instantaneously and successfully described the earthquake
parameters with low computational demand. They are improving the model by
factoring in more information to increase the tsunami characterization's
accuracy.

Their work predicting tsunami risk is part of a larger project to enhance
hazard warning systems. The tsunami classification is a back-end aspect
of a software that can improve the safety of offshore platforms and ships.

    * RELATED_TOPICS
          o Earth_&_Climate
                # Tsunamis # Natural_Disasters # Earthquakes # Water
          o Computers_&_Math
                # Computer_Modeling # Computational_Biology #
                Mathematical_Modeling # Software
    * RELATED_TERMS
          o Tsunami o Megatsunami o Earthquake o Great_Chilean_Earthquake
          o Seismic_wave o Earthquake_liquefaction o
          2004_Indian_Ocean_earthquake o 2005_Kashmir_earthquake

==========================================================================
Story Source: Materials provided by American_Institute_of_Physics. Note:
Content may be edited for style and length.


==========================================================================
Journal Reference:
   1. Bernabe Gomez and Usama Kadri. Numerical validation of an effective
      slender fault source solution for past tsunami scenarios. Physics
      of Fluids, 2023 DOI: 10.1063/5.0144360
==========================================================================

Link to news story:
https://www.sciencedaily.com/releases/2023/04/230425111152.htm

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