Group C, Poster #029, Seismology
A semi-automated process to identify turbidity currents within the Cascadia Subduction Zone in Barkley Canyon
Poster Image:
Poster Presentation
2022 SCEC Annual Meeting, Poster #029, SCEC Contribution #12189 VIEW PDF
loor cabled array operated by Ocean Networks Canada (ONC; 2009-present, 2016-present in Barkley Canyon) provides an opportunity to examine concurrent seismic, turbidity, and other oceanographic data from one of the more seismically active portions of the margin.
Assessing if shaking from regional and local large earthquakes correlates with an increase in turbidity currents requires a robust catalog of turbidity current occurrences (all sizes above the noise floor). Here, we focus on data from Barkley Canyon oceanographic sensors and design a semi-automated process to identify the signature of turbidites within continual data streams. A turbidity current signal is easier to identify than a seismic P- and S-wave waveform, as the turbidity signal is typically a single pulse with a sharp rise time followed by an exponential decay. To identify these signals, we first apply a short-term average/long-term average (STA/LTA) algorithm to detect elevated levels of turbidity, or “triggers.” We then examine data within ±1 hour of each trigger and require an exponential decay follows the maximum value within the data snippet. For the 2019 data, the exponential decay requirement successfully eliminates many of the signals that are not of interest, reducing the number of triggers from ~1400 to 40. Human review of the 40 triggers classified 17 as true turbidity signals. Initial work suggests a seasonal effect in that more turbidity activity is found in the months October through February. This seasonal effect should be accounted for when assessing correlations between large regional and local earthquakes and turbidity behavior.
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Assessing if shaking from regional and local large earthquakes correlates with an increase in turbidity currents requires a robust catalog of turbidity current occurrences (all sizes above the noise floor). Here, we focus on data from Barkley Canyon oceanographic sensors and design a semi-automated process to identify the signature of turbidites within continual data streams. A turbidity current signal is easier to identify than a seismic P- and S-wave waveform, as the turbidity signal is typically a single pulse with a sharp rise time followed by an exponential decay. To identify these signals, we first apply a short-term average/long-term average (STA/LTA) algorithm to detect elevated levels of turbidity, or “triggers.” We then examine data within ±1 hour of each trigger and require an exponential decay follows the maximum value within the data snippet. For the 2019 data, the exponential decay requirement successfully eliminates many of the signals that are not of interest, reducing the number of triggers from ~1400 to 40. Human review of the 40 triggers classified 17 as true turbidity signals. Initial work suggests a seasonal effect in that more turbidity activity is found in the months October through February. This seasonal effect should be accounted for when assessing correlations between large regional and local earthquakes and turbidity behavior.
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Lightning Talk
Citation: Kilb, D., Sahakian, V. J., Chaknova, M., De Leo, F. C., Walczak, M., & Hill, J. (2022, 09). A semi-automated process to identify turbidity currents within the Cascadia Subduction Zone in Barkley Canyon. Poster Presentation at 2022 SCEC Annual Meeting.
Keywords: Turbidity, Cascadia, Subduction
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