The Seismic Hazard Harmonization in Europe (SHARE) project, which began in June 2009, aims at establishing new standards for probabilistic seismic hazard assessment in the Euro-Mediterranean region. In this context, a logic tree for ground-motion prediction in Europe has been constructed. Ground-motion prediction equations (GMPEs) and weights have been determined so that the logic tree captures epistemic uncertainty in ground-motion prediction for six different tectonic regimes in Europe. Here we present the strategy that we adopted to build such a logic tree. This strategy has the particularity of combining two complementary and independent approaches: expert judgment and data testing. A set of six experts was asked to weight pre-selected GMPEs while the ability of these GMPEs to predict available data was evaluated with the method of Scherbaum et al. (Bull Seismol Soc Am 99:3234-3247, 2009). Results of both approaches were taken into account to commonly select the smallest set of GMPEs to capture the uncertainty in ground-motion prediction in Europe. For stable continental regions, two models, both from eastern North America, have been selected for shields, and three GMPEs from active shallow crustal regions have been added for continental crust. For subduction zones, four models, all non-European, have been chosen. Finally, for active shallow crustal regions, we selected four models, each of them from a different host region but only two of them were kept for long periods. In most cases, a common agreement has been also reached for the weights. In case of divergence, a sensitivity analysis of the weights on the seismic hazard has been conducted, showing that once the GMPEs have been selected, the associated set of weights has a smaller influence on the hazard
The 2016–2017 central Italy seismic sequence occurred on an 80 km long normal-fault system. The sequence initiated with the Mw 6.0 Amatrice event on 24 August 2016, followed by the Mw 5.9 Visso event on 26 October and the Mw 6.5 Norcia event on 30 October. We analyze continuous data from a dense network of 139 seismic stations to build a high-precision catalog of ∼900,000 earthquakes spanning a 1 yr period, based on arrival times derived using a deep-neural-network-based picker. Our catalog contains an order of magnitude more events than the catalog routinely produced by the local earthquake monitoring agency. Aftershock activity reveals the geometry of complex fault structures activated during the earthquake sequence and provides additional insights into the potential factors controlling the development of the largest events. Activated fault structures in the northern and southern regions appear complementary to faults activated during the 1997 Colfiorito and 2009 L’Aquila sequences, suggesting that earthquake triggering primarily occurs on critically stressed faults. Delineated major fault zones are relatively thick compared to estimated earthquake location uncertainties, and a large number of kilometer-long faults and diffuse seismicity were activated during the sequence. These properties might be related to fault age, roughness, and the complexity of inherited structures. The rich details resolvable in this catalog will facilitate continued investigation of this energetic and well-recorded earthquake sequence.
The 2016–2017 Central Italy seismic sequence ruptured overlapping normal faults of the Apennines mountain chain, in nine earthquakes with magnitude Mw > 5 within a few months. Here we investigate the structure of the fault system using an extensive aftershock data set, from joint permanent and temporary seismic networks, and 3‐D Vp and Vp/Vs velocity models. We show that mainshocks nucleated on gently west dipping planes that we interpret as inverted steep ramps inherited from the late Pliocene compression. The two large shocks, the 24 August, Mw = 6.0 Amatrice and the 30 October, Mw = 6.5 Norcia occurred on distinct faults reactivated by high pore pressure at the footwall, as indicated by positive Vp/Vs anomalies. The lateral extent of the overpressurized volume includes the fault patch of the Norcia earthquake. The irregular geometry of normal faults together with the reactivated ramps leads to the kinematic complexity observed during the coseismic ruptures and the spatial distribution of aftershocks.
The 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 2016 Mw = 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 October Mw = 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 from M3+ 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.
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