@article{HainzlZoellerBrietzkeetal.2013,
  author    = {Hainzl, Sebastian and Z{\"o}ller, Gert and Brietzke, Gilbert B. and Hinzen, Klaus-G.},
  title     = {Comparison of deterministic and stochastic earthquake simulators for fault interactions in the Lower Rhine Embayment, Germany},
  series = {Geophysical journal international},
  volume    = {195},
  journal   = {Geophysical journal international},
  number    = {1},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  issn      = {0956-540X},
  doi       = {10.1093/gji/ggt271},
  pages     = {684 -- 694},
  year      = {2013},
  abstract  = {Time-dependent probabilistic seismic hazard assessment requires a stochastic description of earthquake occurrences. While short-term seismicity models are well-constrained by observations, the recurrences of characteristic on-fault earthquakes are only derived from theoretical considerations, uncertain palaeo-events or proxy data. Despite the involved uncertainties and complexity, simple statistical models for a quasi-period recurrence of on-fault events are implemented in seismic hazard assessments. To test the applicability of statistical models, such as the Brownian relaxation oscillator or the stress release model, we perform a systematic comparison with deterministic simulations based on rate- and state-dependent friction, high-resolution representations of fault systems and quasi-dynamic rupture propagation. For the specific fault network of the Lower Rhine Embayment, Germany, we run both stochastic and deterministic model simulations based on the same fault geometries and stress interactions. Our results indicate that the stochastic simulators are able to reproduce the first-order characteristics of the major earthquakes on isolated faults as well as for coupled faults with moderate stress interactions. However, we find that all tested statistical models fail to reproduce the characteristics of strongly coupled faults, because multisegment rupturing resulting from a spatiotemporally correlated stress field is underestimated in the stochastic simulators. Our results suggest that stochastic models have to be extended by multirupture probability distributions to provide more reliable results.},
  language  = {en}
}
@article{SudibyoEiblHainzletal.2022,
  author    = {Sudibyo, Maria R. P. and Eibl, Eva P. S. and Hainzl, Sebastian and Hersir, Gylfi P{\´a}ll},
  title     = {Eruption Forecasting of Strokkur Geyser, Iceland, Using Permutation Entropy},
  series = {Journal of geophysical research : Solid earth},
  volume    = {127},
  journal   = {Journal of geophysical research : Solid earth},
  number    = {10},
  publisher = {American Geophysical Union},
  address   = {Washington},
  issn      = {2169-9313},
  doi       = {10.1029/2022JB024840},
  pages     = {15},
  year      = {2022},
  abstract  = {A volcanic eruption is usually preceded by seismic precursors, but their interpretation and use for forecasting the eruption onset time remain a challenge. A part of the eruptive processes in open conduits of volcanoes may be similar to those encountered in geysers. Since geysers erupt more often, they are useful sites for testing new forecasting methods. We tested the application of Permutation Entropy (PE) as a robust method to assess the complexity in seismic recordings of the Strokkur geyser, Iceland. Strokkur features several minute-long eruptive cycles, enabling us to verify in 63 recorded cycles whether PE behaves consistently from one eruption to the next one. We performed synthetic tests to understand the effect of different parameter settings in the PE calculation. Our application to Strokkur shows a distinct, repeating PE pattern consistent with previously identified phases in the eruptive cycle. We find a systematic increase in PE within the last 15 s before the eruption, indicating that an eruption will occur. We quantified the predictive power of PE, showing that PE performs better than seismic signal strength or quiescence when it comes to forecasting eruptions.},
  language  = {en}
}