EGU2020-5242, updated on 12 Jun 2020
https://doi.org/10.5194/egusphere-egu2020-5242
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Occurrence of earthquake doublets in the light of the ETAS model

Christian Grimm1, Martin Käser2,3, and Helmut Küchenhoff1
Christian Grimm et al.
  • 1Department of Statistics, Ludwig-Maximilians-Universität München, Munich, Germany
  • 2Department of Earth- and Environmental Sciences, Ludwig-Maximilians-Universität München, Munich, Germany
  • 3Section Georisks, Munich RE, Munich, Germany

While Probabilistic Seismic Hazard Assessment is commonly based on earthquake catalogues in a declustered form, ongoing seismicity in aftershock sequences is known to be able to add significant hazard, which can also increase the damage potential to already affected structures in risk assessment. Especially so-called earthquake doublets (multiplets), i.e. a cluster mainshock being followed or preceded by one (or more) events with a similarly strong magnitude occurring within pre-defined temporal and spatial limits, can cause loss multiplication effects to the insurance industry, which therefore has a pronounced interest in investigating the frequency of earthquake doublets to happen worldwide. A widely used method to analyse and simulate the triggering process of earthquake sequences is the Epidemic Type Aftershock Sequence (ETAS) model. We estimate the ETAS model parameters for some regional areas and produce synthetic catalogues, which are then analysed particularly with respect to the occurrence of earthquake doublets and compared to the observed history. Also, different seismic subduction-type regions in the world are pointed out to have shown differing relative frequencies of earthquake doublets. Regression models are used to study whether certain mainshock and local, geophysical properties such as magnitude, dip and rake angle, depth, distance to subduction plate interface and velocity of converging subduction plates nearby show explanatory power for the probability of a cluster containing an earthquake doublet.

How to cite: Grimm, C., Käser, M., and Küchenhoff, H.: Occurrence of earthquake doublets in the light of the ETAS model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5242, https://doi.org/10.5194/egusphere-egu2020-5242, 2020

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Presentation version 3 – uploaded on 04 May 2020
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  • CC1: Initial parameters, Corentin Gouache, 04 May 2020

    Thank you for this interesting work.
    Accordig to Abdollah Jalilian, the ETAS code you used is relatively sensitive to the choice of the 8 initial parameters. I wonder how did you choose these ones?

    • AC1: Reply to CC1, Christian Grimm, 05 May 2020

      Corentin, thanks for your nice comment! Two things:

      1) I changed (corrected?) the treatment of background rates in the R package "ETAS" (in the code, background rates were summed up from Gaussian kernel contributions of all catalog events, but scaled by the length of the shorter target time window). After modifying this, I found the model was running more stable, e.g. gradiants were decreasing more steadily in each iteration.

      2) I took Jalilians' standard set of initial parameters as I am rather new to ETAS and therefore lack deeper experience. I applied two changes:

      a) mu=1 because its only purpose is to balance out interactions between triggering parameters and background, correct? Any structural departure from mu=1 should rather scale up/down u(x,y) in the next iteration.

      b) alpha = 2 because in earlier discussions I found this is a somewhat desired range for alpha.

      What would you suggest as initial guesses to try out? And how do my parameter results look like? The community already pointed out to me the too low alpha estimates. But how about the others?

      Best, Christian (Christian.Grimm@stat.uni-muenchen.de)

      • CC2: Reply to AC1, Corentin Gouache, 05 May 2020

        Christian, 
        Your suggestions and results for mu and Omori parameters seem consistent. For the other parameters I'm not an expert since I'm also new to ETAS :)
        Actually, I guess alpha is the parameter to delve into especially because slight variations lead to large gaps on the aftershock number.
        Did you test ETAS on different time scales (shorter than 1966 - 2007) or on specific well known sequences? Are alpha higher in these cases?
        What is the alpha value range in other japanese works? Above 2?

        However I think initial parameters need to be set with attention and depend on study area. In my case (French mainland), seismicity is low and data are sparse so parameters are hard to choose.

        By the way, good work! It makes me want to apply ETAS on my study area.

        Best regards

        • AC2: Reply to CC2, Christian Grimm, 07 May 2020

          Hi Corentin,

          I think you point out very good questions to me:

          1) I checked the two time periods 1973-2009 and 1973-2019 (Run1 & Run2 in my slides). Run2, including the 2011 sequence(s), provides wider-spread temporal and spatial distributions. The alpha value increases rather moderately from 1.58 to 1.64.

          However, I have not yet analyzed specific sequences as the extraction of a particular sequence from an entire catalog is rather subjective. On the other hand I agree that it is a good comparison to check the overall dimensions of my estimates, as much as comparing more in depth with other ETAS Japan results in literature.

          Corentin, I am excited to learn about your French mainland study (especially your magnitude sampling by Bath law), I suggest that I contact you via email so we can arrange a video meeting?

          Best,

          Christian

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