This strand investigates earthquakes to better understand geological activity and devise ways of making buildings safer with seismic engineering. Earthquakes caused nearly 750,000 deaths globally, with more than half of all deaths related to all-natural disasters between 1998 and 2017. This number, and the many more injured or displaced by such events, as well as the financial losses, is growing with increased urbanisation. To quote the late Nick Ambrasseys, "earthquakes do not kill people, buildings do". One way of tackling this problem is to calculate the likely strong ground motion that buildings and infrastructure are likely to experience during their lifetimes so that the relevant authorities can set and regulate appropriate building standards and structural engineers can design accordingly. The process of calculating strong ground motions starts with identifying likely seismic sources and quantifying the frequency-magnitude distribution expected in the future, including the likelihood of future extreme events being larger than those recorded so far in the comparatively short time period of instrumentally recorded earthquakes. We can extend this to historically documented earthquakes, after suitable calibration, and use independent information such as maps of fault location, slip and strain rates, including from satellite data as constraints on where and how large such events can be. We are also active in estimating the laws governing the attenuation of seismic waves using scenario earthquakes, hence improving ground motion prediction equations used to translate earthquake likelihoods to likelihoods of strong ground motion at different locations. Deterministic earthquake prediction remains one of the great unsolved research challenges of our time. It may never be achievable in practice due to the absence of reliable precursors and the critical-state dynamics and complexity of the underlying processes. Nevertheless, this complexity and sensitivity does allow the possibility of lower-probability operational earthquake forecasting that may nevertheless prove useful in communicating and managing the risk during seismic sequences. Discover more about deterministic earthquake prediction on *ERE Find out more about operational earthquake forecasting on *ERE Increasingly we collaborate with colleagues in the social sciences and humanities in joint research programmes aimed at reducing the risk from earthquakes. We aim to go beyond mere quantification of hazard to a more complete understanding of what leads to human vulnerability and hence the overall risk. This work also includes engagement with a range of relevant stakeholders, from local community groups to government organisations. We also work with the Crust to Core and Geoenergy research groups, on the underlying processes that control the seismogenic Earth. Please visit our Crust to Core research group for information about deforms at multiple scales, from microscopic fractures to large faults and earthquakes. For more details relating to the understanding of induced seismicity from geothermal energy projects, you can visit our Geoenergy research group. Visit our Crust to Core research group Visit our Geoenergy research group Current projects Tomorrow’s Cities - UKRI GCRF Multi-Hazard Urban Disaster Risk Hub, 2019-2024 Tomorrow’s Cities is the UK Research and Innovation (UKRI) Global Challenges Research Fund (GCRF) Urban Disaster Risk Hub, led by Professor John McCloskey. It is a major international project that involves a wide range of partners in the UK and in the developing world and aims to catalyse a transition from crisis management to multi-hazard risk-informed planning and decision-making, for cities in low-and-middle-income countries. We are one of 12 UKRI GCRF Hubs funded as part of the UK AID strategy, putting research at the heart of efforts to deliver the United Nation’s Sustainable Development Goals (SDGs). Visit the Tomorrow's Cities website Earthquake risk reduction for a resilient Europe (RISE) 2019-2022 RISE is a collaborative project, led by Professor Stefan Wiewer from Eidgenössische Technische Hochschule Zurich ETH and is funded by EU Horizon 2020. This project aims to roll out an operational earthquake forecasting capability of southern Europe. Our researchers contribute to work packages involving the innovation of new methods, where we act as task leaders, improving forecasting models, and appropriate objective testing of new ones. This includes working with colleagues at the British Geological Survey (BGS) on improved models for forecasting earthquakes during seismic sequences using the concept of triggering earthquakes through stress transferred from previous ones. A full description of the approach being developed to combine the datasets described above to improve forecasting models can be found on the project website. Visit the RISE website Large collaborative projects completed in the period 2016-2021 The central Apennines earthquake cascade – under a new microscope 2018-2021 This research was led by Dr Margarita Segou, British Geological Society (BGS) and Honorary Research Fellow, and was a collaboration with Stanford University, funded by the Natural Environmental Research Council (NERC) - National Science Foundation (NSF). We used state of the art data processing techniques, including waveform cross-correlation and artificial intelligence to find new small earthquakes in whole waveform data. It has already generated several new earthquake catalogues that are at least an order of magnitude bigger than previously possible and is being used to improve our understanding of source fault architecture and to develop forecasting models for the Norcia-Amatrice sequence in Italy. Further details on this project can be found on *ERE Probability and Uncertainty in Risk Estimation and Communication (PUREC) 2016-2019 Led by Professor Ian Main and Professor Xiaofei Chen of Peking University, China, this project formed part of the Newton fund programme ‘Increasing Resilience to Natural Hazards in Earthquake Prone Regions in China (IRNHiC) a UK-China collaboration’. It was funded by the Natural Environmental Research Council (NERC), Economic and Social Research Council (ESRC), and the National Science Foundation of China, with partners Professor Richard Chandler of University College London and Dr Susanne Sargeant at the British Geological Society (BGS). We developed new statistical methods to improve the estimate of the boundaries of zones of the historically estimated intensity of ground motion, and hence estimated the felt area used after calibration with modern data to estimate and update the likely magnitude of past historical earthquakes and their uncertainties. We also tested the hypothesis that very large earthquakes can have significantly long-lived aftershock sequences, on the order of a few hundreds of years, by comparing historical data with estimates of a seismic intensity metric designed to estimate the current level of seismic stress concentration in the lithosphere from modern records. Further details on this project can be found on *ERE Prospective aftershock forecasting of the Norcia 2016 earthquake sequence, Central Appenines, Italy 2017-2018 This project was led by Dr Margarita Segou, British Geological Society (BGS) and Honorary Research Fellow, and was funded as an urgency grant by the Natural Environmental Research Council (NERC). The research was funded to exploit the rapid deployment of UK seismometers within one week of the 24 August 2016 magnitude 6.0 Amatrice earthquake in Abruzzo, Italy, which led to 299 deaths and triggered an extensive sequence, including the magnitude 6.5 Norcia earthquake and Mw 5.9 Visso earthquake. The deployment was funded during the emergency response to this event by the UK cabinet office and is described in the documentary ‘Chasing quakes’. Visit the 'Chasing quakes' website Publications * Affiliated members highlighted in bold (2021) An automatically generated high-resolution earthquake catalogue for the 2016–2017 Central Italy seismic sequence, including P and S phase arrival times. Geophysical Journal International, 225, 1, p.555-571 Authors: Spallarossa, D., Cattaneo, M., Scafidi, D., Michele, M., Chiaraluce, L., Segou, M., Main, I. G. View publication (2020) Data-driven optimization of seismicity models using diverse data sets: generation, evaluation and ranking using inlabru. Geophysical Journal International. 125, 11. Authors: Bayliss, K., Naylor, M., Illian, J., Main, I. View publication (2019) Probabilistic identification of earthquake clusters using rescaled nearest neighbour distance networks. Geophysical Journal International. 217, 1, 487-503. Authors: Bayliss, K., Naylor, M., Main, I. View publication (2017) Earthquake clustering in modern seismicity and its relationship with strong historical earthquakes around Beijing, China. Geophysical Journal International. Authors: Wang, J., Main, I., Musson, R. View publication (2016) Detection of change points in underlying earthquake rates, with application to global mega-earthquakes. Geophysical Journal International. Authors: Touati, S., Naylor, M., Main, I. View publication Key staff Kirsty Bayliss Andrew Bell Ian Main John McCloskey Mark Naylor Margarita Segou * Edinburgh Research Explorer (ERE) is the University's research information system and is managed by Library and University Collections. This article was published on 2024-07-01
