Paper No. 33-1
Presentation Time: 5:35 PM
LINKING FIELD DATA, STRESS MODELLING AND COSMOGENIC ANALYSES TO UNDERSTAND FAULT INTERACTION AND HISTORICAL EARTHQUAKES IN THE ITALIAN APENNINES (Invited Presentation)
MILDON, Zoe K.1, ROBERTS, Gerald P.2, FAURE-WALKER, Joanna3, TODA, Shinji4, IEZZI, Francesco2, SGAMBATO, Claudia3, BECK, Joakim5, PAPANIKOLAOU, Ioannis6 and MICHETTI, Alessandro7, (1)School of Geography, Earth and Environmental Sciences, University of Plymouth, Drakes Circus, Plymouth, PL4 8AA, United Kingdom, (2)Research School of Earth Sciences, UCL/Birkbeck, University of London, Gower Street, London, WC1E 6BT, United Kingdom, (3)Institute for Risk and Disaster Reduction, University College London, London, WC1E 6BT, United Kingdom, (4)International Research Institute of Disaster Science, Tohoku University, Aoba, Sendai, 980-0845, Japan, (5)King Abdullah University of Science and Technology, Thuwal, 23955, Saudi Arabia, (6)Agricultural University of Athens, Athens, 118 55, Greece, (7)Università degli Studi dell’Insubria, Como, 21100, Italy
Combining observations from different data sets is an important approach to understand fundamental earthquake processes and the associated seismic hazard. In the central and southern Apennines, the normal faults are well-exposed at the surface as carbonate bedrock scarps that have been formed since the demise of the Last Glacial Maximum (15 ± 3 kyrs). Because of the excellent exposure, we have a wealth of data, including the geometry of faults, the throw since the LGM, a detailed record of historical earthquakes, and the slip history over the last 15 ± 3 kyrs from cosmogenic dating. These data sets allow us to explore fault interaction, the historical earthquake sequence and effect of fault geometry on earthquakes.
Using these data sets gives us a range of novel insights into how these faults interact together and what the past occurrence of earthquakes can tell us about future earthquakes (or not!). Studying the cumulative stress changes associated with historical earthquakes can tell us that the way faults interact and behave is dependent on the geometry of the fault array and that considering the cumulative stress is more insightful that considering single coseismic stress changes. Indeed, the pattern of cumulative stress may have controlled the magnitude and order of the 2016 earthquake sequence (3 M>5.9 earthquakes from August – October 2016). Looking over longer time periods, we hypothesise that earthquake clustering may also be controlled by changes in stress induced by slip on neighbouring faults. The geometry of the faults is highly variable, with changes in strike, dip and slip vector recorded along fault systems. These variations can tell us about rupture segmentation and may explain the scatter in Dmax/fault length scaling relationships. Ultimately, the question becomes what do our findings mean for seismic hazard assessment and how might they be utilised?
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