Gomez peer zone alternative code#

In this context, the identification and characterization of active faults as seismogenic sources able to produce all the range of earthquake magnitudes become critical tasks in the PSHA of moderate active regions.Р”Р‡or this reason, in accordance with the increasing availability and refinement of paleoseismic and geological studies, the incorporation of fault data in PSHA has become an important part of the source modeling aiming to estimate earthquake activity beyond the coverage of seismic catalogs. However, there is increasing awareness of the fact that low-to-moderate magnitude events (Mw 4.0РІР‚вЂњ6.0) are also able to produce significant damage, especially at sites located on top or very close to fault sources (e.g., 2011 Mw 5.2 Lorca earthquake in SE Spain Alguacil et al., 2014). Maximum events usually have a very low impact in seismic hazard for the return periods considered in conventional building (e.g., 475Р’В years) and so this type of fault-based PSHA has been regarded in studies interested in long return periods (e.g., critical infrastructures). Traditionally, geological data and fault data have been used to characterize the occurrence of major, maximum or characteristic events ( Wesnousky, 1986 Schwartz and Coppersmith, 1984). This is a very short time window for characterizing the occurrence of major events in regions of moderate seismic activity, even in areas where the catalogs extend for more than 1,000Р’В years such as SE Spain or Portugal ( GarcР“Вa-Mayordomo, 2005 Vilanova and Fonseca, 2007, respectively). The use of geological data in probabilistic seismic hazard assessment (PSHA) has become increasingly important, since seismic catalogs do not usually extend for more than a few centuries. This, together with epistemic uncertainties concerning the background seismicity, are key discussion points in the present study, having an impact on further research and aiming to serve as a case example for other low-to-moderate seismicity regions worldwide. Fault data, mainly slip rates, and its uncertainties have a clear impact on the seismic hazard and, for some faults, the lack of detailed paleoseismic studies can compromise the reliability of the hazard estimations.

Gomez peer zone alternative code#

For the return period of 475Р’В years and near-fault locations, our models are more consistent with the ground motion values reached in the 2011 Mw 5.2 Lorca event than the building code or national seismic hazard map, which suggest that our fault system-based model performs more accurate estimations for this return period. The seismic hazard is dependent on the fault slip rates as peak ground accelerations and territorial extension of the fault influence appear higher around the Alhama de Murcia and Carboneras faults, while lower slip rate faults (Palomares Fault) show minor contribution to the hazard. The results show a clear control of the EBSZ faults in the seismic hazard for all return periods, increasing drastically the hazard levels in the regions close to the fault traces and influencing up to 20Р’В km farther with respect to the area source PSHA. We compare the hazard levels with those from an area source PSHA and a previous fault-based approach.

In contrast with previous studies in Spain, earthquake occurrence of the EBSZ system is modeled considering different hypotheses of multi-fault ruptures at the whole fault system scale and weighted in a logic tree.

We present a PSHA for the Southeastern Spain obtained by including the faults of a moderate seismicity region, the Eastern Betics Shear Zone (EBSZ) in SE Spain, as the main seismogenic sources in two separate source models, one considering background seismicity. Moreover, the occurrence of earthquakes in multi-fault ruptures has evidenced the need to understand faults as interacting systems rather than independent sources. Including faults as seismogenic sources in probabilistic seismic hazard assessments (PSHA) has turned into a common practice as knowledge of active faults is improving.

3Hazard Team, Global Earthquake Model Foundation, Pavia, Italy.

2Departamento de Riesgos GeolР“С–gicos, Instituto GeolР“С–gico y Minero de EspaР“В±a, Tres Cantos, Spain.

1RISKNAT Group, Geomodels Research Institute, Departament de DinР“В mica de La Terra I de LРІР‚в„ўOceР“В , Facultat de CiР“РЃncies de La Terra, Universitat de Barcelona, Barcelona, Spain.

Octavi GР“С–mez-Novell 1*, JuliР“РЋn GarcР“Вa-Mayordomo 2, MarР“Вa OrtuР“В±o 1, EulР“В lia Masana 1 and Thomas Chartier 3