Abstract
AbstractThe 2016–2017 Central Apennines earthquake sequence is a recent example of how damages from subsequent aftershocks can exceed those caused by the initial mainshock. Recent studies reveal that physics‐based aftershock forecasts present comparable skills to their statistical counterparts, but their performance remains a controversial subject. Here we employ physics‐based models that combine the elasto‐static stress transfer with rate‐and‐state friction laws, and short‐term statistical Epidemic Type Aftershock Sequence (ETAS) models to describe the spatiotemporal evolution of the earthquake cascade. We then track the absolute and relative model performance using log‐likelihood statistics for a 1‐year horizon after the 24 August 2016Mw= 6.0 Amatrice earthquake. We perform a series of pseudoprospective experiments by producing seven classes of Coulomb rate‐state (CRS) forecasts with gradual increase in data input quality and model complexity. Our goal is to investigate the influence of data quality on the predictive power of physics‐based models and to assess the comparative performance of the forecasts in critical time windows, such as the period following the 26 October Visso earthquakes leading to the 30 OctoberMw= 6.5 Norcia mainshock. We find that (1) the spatiotemporal performance of the basic CRS models is poor and progressively improves as more refined data are used, (2) CRS forecasts are about as informative as ETAS when secondary triggering effects fromM3+ earthquakes are included together with spatially variable slip models, spatially heterogeneous receiver faults, and optimized rate‐and‐state parameters. After the Visso earthquakes, the more elaborate CRS model outperforms ETAS highlighting the importance of the static stress transfer for operational earthquake forecasting.
Highlights
Earthquake cascades with multiple moderate to large magnitude events over weeks, months, or years expand the damage zone extensively causing disruption to livelihoods
Our goal is to investigate the influence of data quality on the predictive power of physics‐based models and to assess the comparative performance of the forecasts in critical time windows, such as the period following the 26 October Visso earthquakes leading to the 30 October Mw = 6.5 Norcia mainshock
We find the main differences between Epidemic Type Aftershock Sequence (ETAS) and Coulomb rate‐state (CRS)‐7 in the high clustering region around Mount Bove, where the former expects more than 1 order of magnitude higher rates than its stress‐based counterpart, and in the near epicentral area, where the aftershock rates predicted by the ETAS model are approximately 2–3 times lower than CRS‐7 (Figure 3i)
Summary
Earthquake cascades with multiple moderate to large magnitude events over weeks, months, or years expand the damage zone extensively causing disruption to livelihoods. For the last 30 years, statistical Epidemic Type Aftershock Sequence (ETAS) forecasts (Ogata, 1988, 1998) have shown considerable skills in capturing the clustering characteristics of triggered seismicity. These models offer limited insight into the physics of earthquake nucleation and fault interaction in terms of continuum mechanics. The implementation of laboratory‐derived friction laws describing the seismicity response to an earthquake perturbation (Dieterich, 1994) is the basis of many physics‐based forecasts known as Coulomb rate‐state (CRS) models (Cattania et al, 2018; Cocco et al, 2010; Parsons et al, 2012, 2014; Segou, 2016; Toda & Enescu, 2011; Toda et al, 2005, among others). The limitation for an operational use of CRS models is that their parametrization goes beyond a mere earthquake catalog and requires representations of earthquake sources and nearby receiver faults that are unlikely to be available immediately after a major event
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