NSFGEO-NERC: The central Apennines earthquake cascade under a new microscope
Lead Research Organisation:
British Geological Survey
Department Name: Earth Hazards & Observatories
Abstract
Three strongly felt earthquakes of magnitude M>5.9 occurred within a 50 km source zone along the Central Apennines mountain chain in a period of just over 2 months. The first, on the 24th August M=6.0 earthquake killed 297 people, leaving the medieval villages of Amatrice, Accumoli and Pescara di Tronto devastated. On 26th October two large shocks of M=5.4 and M=5.9 (32 minutes after) struck ~30 km further north in the same region as the 1997 M=6.0 Colfiorito earthquake. The largest (M=6.5) event to date that occurred only four days later, on 30th October, caused severe damage to buildings at Norcia, including the historical cathedral of San Benedetto. The area has been struck by destructive earthquakes of significant magnitude in historical and modern times. This is the third catastrophic sequence to occur in the Central Apennines, with preceding sequences to the north (M=6.0 Colfiorito) and south (M=6.1 L'Aquila) in 1997 and 2009, respectively. Cultural heritage sites including word-famous medieval churches near Amatrice village, have suffered severe damage and total collapse in many cases.
Within this post-disaster environment there is a clear need to improve our understanding behind the evolution of such sequences and to develop tools that can support informed decision-making in the future. Our research will be based on a unique high quality dataset that is a product of on-going UK-Italian collaboration involving the deployment of more than 85 seismic sensors at the affected area since last fall. This unprecedented observational capability enables us to capture the "breadth and depth" of seismicity leading to the large events within the sequence. Based on this dataset we will develop innovative methods to translate measurements into testable physical models for the underlying processes. We aim at developing a comprehensive earthquake catalog that includes precise locations, source parameters and focal mechanisms derived from algorithms that are able detect, locate and characterize even the smallest events. This new 'microscope' provides information that is crucial for unravelling the physical processes that underlie sequences such as the extended 2016 Amatrice/Norcia earthquakes in Italy. We will then use the high-accuracy catalog to formulate and test alternative earthquake triggering hypotheses and integrate those in the development and validation of testable forecast models using empirical and physics based models to ensure high predictability.
The project brings together world-experts on earthquake detection, seismic source characterization, earthquake triggering and forecasting from US, UK and Italy in an effort to develop breakthrough approaches to address current challenges that not only impede our understanding behind earthquake processes but also weaken our scientific response in any post-earthquake disaster environment. In the course of our research we will involve further international initiatives such as CSEP (Collaboratory for the Study of Earthquake Predictability) to ensure transparent testing of our forecast models, and EPOS (European Plate Observation System) to maximize knowledge exchange and the scientific impact of the project in other countries. The new observational capability to detect, locate and characterize even the smallest magnitude events within few hours will find application to induced, geothermal and volcanic activity areas in US and Europe. We anticipate that the application of our research framework especially in high seismic hazard sites worldwide will enable future decision making with the same scientific standards across different operational and cultural environments.
Within this post-disaster environment there is a clear need to improve our understanding behind the evolution of such sequences and to develop tools that can support informed decision-making in the future. Our research will be based on a unique high quality dataset that is a product of on-going UK-Italian collaboration involving the deployment of more than 85 seismic sensors at the affected area since last fall. This unprecedented observational capability enables us to capture the "breadth and depth" of seismicity leading to the large events within the sequence. Based on this dataset we will develop innovative methods to translate measurements into testable physical models for the underlying processes. We aim at developing a comprehensive earthquake catalog that includes precise locations, source parameters and focal mechanisms derived from algorithms that are able detect, locate and characterize even the smallest events. This new 'microscope' provides information that is crucial for unravelling the physical processes that underlie sequences such as the extended 2016 Amatrice/Norcia earthquakes in Italy. We will then use the high-accuracy catalog to formulate and test alternative earthquake triggering hypotheses and integrate those in the development and validation of testable forecast models using empirical and physics based models to ensure high predictability.
The project brings together world-experts on earthquake detection, seismic source characterization, earthquake triggering and forecasting from US, UK and Italy in an effort to develop breakthrough approaches to address current challenges that not only impede our understanding behind earthquake processes but also weaken our scientific response in any post-earthquake disaster environment. In the course of our research we will involve further international initiatives such as CSEP (Collaboratory for the Study of Earthquake Predictability) to ensure transparent testing of our forecast models, and EPOS (European Plate Observation System) to maximize knowledge exchange and the scientific impact of the project in other countries. The new observational capability to detect, locate and characterize even the smallest magnitude events within few hours will find application to induced, geothermal and volcanic activity areas in US and Europe. We anticipate that the application of our research framework especially in high seismic hazard sites worldwide will enable future decision making with the same scientific standards across different operational and cultural environments.
Planned Impact
The primary aim of this NSFGEO-NERC proposal is the exploration of the physics in complex earthquake sequences by producing high resolution earthquakes catalogs and using those to develop and test increasingly sophisticated earthquake forecasting models. While our focus remains on discovery science, there are only few areas of solid earth science which have more resonance with the needs of stakeholders in earthquake prone regions worldwide or in areas prone to seismicity induced by industrial activity. Currently, the possibility of providing relevant forecasts of earthquake activity during a sequence and the operational management of induced seismicity is the subject of several research activities worldwide including important initiatives led by members of this team. The team includes members of organisations, such as INGV, BGS and USGS, with statutory responsibility for providing scientific information during emergencies and whose data and analyses are used to advise earthquake response worldwide. We have direct operational links with international NGOs, and a strong track record of engagement with the media worldwide. The current NSFGEO-NERC proposal has clear and immediate Pathways to Impact through these networks with which they are already fully engaged.
The team contribute to active NERC and NSF funded projects on operational issues of earthquake science which will directly benefit from the results of this project. We have direct influence in key government stakeholder organisations with global reach. The project lead, BGS, has a statutory responsibility to provide information to the UK Cabinet Office and the Foreign and Commonwealth Office during emergencies and are the main conduit for scientific advice to the UK government on the potential for induced seismicity due, for example, to fracking. The USGS is responsible for short-term earthquake advisories in the United States and the Southern California Earthquake Centre, with co-director Beroza (co-I here), has recently implemented forecast models which will be enhanced by the science planned in this project.
The INGV is the authoritative organization for the seismic and the volcanic monitoring in Italy and is directly involved in scientific communication to citizens. Moreover, the Seismic Hazard Centre (CPS; co-chaired by Marzocchi) is the INGV appointed group for releasing information on seismic hazard and earthquake forecasts to the Civil Protection agency.
The project results will be reported directly to several international NGOs, all of which are emergency responders following earthquakes and have on-going projects lead by members of this team. The entire project team has a strong record of interaction with the media and we will ensure regular press releases to inform the public of progress in this breakthrough project. It is our intention to host three outreach events in the UK, US and culminating with an international workshop hosted at INGV Rome. Finally, the team includes researchers and professors at leading universities and institutes in Europe and the US who will ensure that the project creates outstanding training opportunities for early career researchers and that its results are immediately reflected in the curricula of important graduate and undergraduate programs in natural Hazards sciences.
The team contribute to active NERC and NSF funded projects on operational issues of earthquake science which will directly benefit from the results of this project. We have direct influence in key government stakeholder organisations with global reach. The project lead, BGS, has a statutory responsibility to provide information to the UK Cabinet Office and the Foreign and Commonwealth Office during emergencies and are the main conduit for scientific advice to the UK government on the potential for induced seismicity due, for example, to fracking. The USGS is responsible for short-term earthquake advisories in the United States and the Southern California Earthquake Centre, with co-director Beroza (co-I here), has recently implemented forecast models which will be enhanced by the science planned in this project.
The INGV is the authoritative organization for the seismic and the volcanic monitoring in Italy and is directly involved in scientific communication to citizens. Moreover, the Seismic Hazard Centre (CPS; co-chaired by Marzocchi) is the INGV appointed group for releasing information on seismic hazard and earthquake forecasts to the Civil Protection agency.
The project results will be reported directly to several international NGOs, all of which are emergency responders following earthquakes and have on-going projects lead by members of this team. The entire project team has a strong record of interaction with the media and we will ensure regular press releases to inform the public of progress in this breakthrough project. It is our intention to host three outreach events in the UK, US and culminating with an international workshop hosted at INGV Rome. Finally, the team includes researchers and professors at leading universities and institutes in Europe and the US who will ensure that the project creates outstanding training opportunities for early career researchers and that its results are immediately reflected in the curricula of important graduate and undergraduate programs in natural Hazards sciences.
Organisations
- British Geological Survey (Lead Research Organisation)
- National Institute for Geophysics and Volcanology (INGV) (Collaboration)
- Columbia University (Collaboration, Project Partner)
- Stanford University (Collaboration)
- UNIVERSITY OF EDINBURGH (Collaboration)
- University of Bristol (Project Partner)
- Stanford University (Project Partner)
- United States Geological Survey (Project Partner)
- National Institute of Geophysics and Volcanology (Project Partner)
- European Plate Observing System (Project Partner)
Publications
Chiarabba C
(2018)
Faults Geometry and the Role of Fluids in the 2016-2017 Central Italy Seismic Sequence
in Geophysical Research Letters
Mancini S
(2019)
Improving Physics-Based Aftershock Forecasts During the 2016-2017 Central Italy Earthquake Cascade
in Journal of Geophysical Research: Solid Earth
Zhang M
(2019)
Rapid Earthquake Association and Location
in Seismological Research Letters
Chiarabba C
(2020)
Seismic velocity precursors to the 2016 Mw 6.5 Norcia (Italy) earthquake
in Geology
Mancini S
(2020)
The Predictive Skills of Elastic Coulomb Rate-and-State Aftershock Forecasts during the 2019 Ridgecrest, California, Earthquake Sequence
in Bulletin of the Seismological Society of America
Spallarossa D
(2021)
An automatically generated high-resolution earthquake catalogue for the 2016-2017 Central Italy seismic sequence, including P and S phase arrival times
in Geophysical Journal International
Beroza GC
(2021)
Machine learning and earthquake forecasting-next steps.
in Nature communications
Zhang X
(2021)
Real-Time Earthquake Early Warning With Deep Learning: Application to the 2016 M 6.0 Central Apennines, Italy Earthquake
in Geophysical Research Letters
| Description | The principle objective of our work in the 1st year of the project has been to test existing earthquake detection, association, timing and location algorithms on the agreed subset of data.We found that existing methods for aggregating seismic arrivals during times of extremely high activity to form events were inadequate to the task for this sequence. A new association method, Rapid Earthquake Association and Location (REAL) has been developed to associate noisy and uncertain seismic phase identifications into events and locate them rapidly with high precision. The objective of our work in the 2nd year of research of the project has been to build statistical tools that can inform us about the clustering properties of earthquakes based on the seismic catalogs provided from the 1st year of the project that resulted mainly from enhanced but otherwise traditional waveform processing techniques and continue towards the development of Artificial Intelligence-based catalogs for the full time period of the temporary deployment. The objective of the 3rd year is to progress with event characterization and fault identification motivated by the new catalogs that are now available. The new inputs datasets will be provided in such a format to forecast modellers that will be easily integrated into forward experiments. The later research course will allow quantifying the improvements that machine learning catalogs will bring into operational earthquake forecasting. Few months (6) following the end of the project (Sep. 2021) team members are working on 4 publications employing high-resolution standard and, machine-learning catalogs that are expected to be the first comparison under an experimental framework of traditional vs. machine-learning-based forecasts, the usefulness of statistical evaluation metrics and more importantly perhaps the physical mechanisms that control triggering potential. We will understand effectively for the first-time how earthquake sequences stop to expand in space and time. |
| Exploitation Route | (1) Non-academic: Our findings support the development of a new workflow for seismological analysis that can be applied to induced seismicity, related with fracking operations, but also natural seismicity in a variety of environments. Therefore, we can identify that operators, regulatory bodies, and government will be stakeholders outside of the academic community that will be interested for this breakthrough results. We have already included the new computational capabilities in ongoing discussions with hazard experts and this will likely result in a new international collaboration that builds upon the implementation of our workflow in other global settings of induced and natural seismicity. (2) Training Opportunities: (a) The great majority of the work in this year has been performed by postdoctoral scholar Miao Zhang. He has built the processing pipeline based on his previous experience and recognized the need to rethink the event association problem. He developed the the REAL algorithm and wrote the paper describing the method, its differences from other associators and its success with analysis of the very high activity period of the Amatrice sequence in mid October, 2017. (b) The PhD student Simone Mancini continued with doctorate thesis including an experiment from the earthquake sequence under study. His work was focused in the realisation of Earth's complexity as expressed by geological features and seismological evidence. He benefitted from attending discussions with world-known experts and by presenting his work during the recent NERC-NSF meeting. (c) The majority of the work in this year has been performed by the postdoctoral scholar Ye Joe from the US part of the collaborative award. We compared the performance of the machine-learning-based phase picker PhaseNet (Zhu and Beroza, 2018) against manual picking and other automatic picking methods on various dataset including a 5-day test period from Amatrice, by using cross-correlation-derived relative arrival times as benchmarks. We find that PhaseNet has comparable performance as manual picking. We also quantified the expected pick error for different PhaseNet output pick probabilities which is used to weigh the picks during the earthquake location step.We ran PhaseNet on one year of continuous data from 139 seismic stations that are publicly available from INGV and BGS. We then associate the P and S-picks into events using the associator REAL (Zhang et al., 2019) before locating the events with Hypoinverse (Klein, 2002). This resulted in a catalog of ~1.4 million events with at least 6 arrivals. We then relocated events with at least 7 P-picks using the double-difference method (Waldhauser and Ellsworth, 2000), resulting in a catalog of 570,000 events. A comparison of the two catalogs are as follow: We are in the process of relocating the ~1.2 million events with at least 4 P-picks, calculating the local magnitudes of the events, and picking the first-motion polarities for focal mechanism determination. (d) Statistical analysis was also performed by the postdoctoral scholar Kirsty Bayliss at the University of Edinburgh. The new high-resolution catalogue resulting from enhanced techniques does not just extend the frequency-magnitude distributions from the standard catalogue to lower magnitudes with the same scaling. They also affect the slope of the frequency-magnitude distribution and resultant estimations of hazard from rare large events. The lower magnitude thresholds of the high-resolution catalogues also allow a greater proportion of overlapping aftershock sequences, making it more difficult to identify background from correlated events with standard spatiotemporal 'de-clustering' techniques. (e)We constructed the catalog using a deep-neural-network-based phase picker [Zhu and Beroza, 2019] combined with high-precision double-difference relative relocation. The resulting one-year catalog contains 900,058 events, more than a 10-fold increase compared to the INGV routine catalog, and is complete for earthquakes of ML > 0.3. Our catalog reveals rich details regarding the complex fault structures that were activated during the sequence. Although the development of the catalog was done post-event, all of the processes and procedures can be run in real-time, opening the possibility of creating such deep catalogs as part of routine network operations. One of the major outcomes is the realization of machine learning earthquake catalogs that are used in various ways to understand better and predict future seismicity. These datasets will be soon open freely to the public after being accepted in peer-reviewed journals. The paper describing the 900,000 event catalogs published at the Open-Access journal, The Seismic Record. The complete catalog is included with the supplementary material. This automatic processing workflow, utilising the deep-learning detection of Zhu and Beroza (2019), for catalog development can be combined with a real-time forecast development workflow to enhance seismic monitoring and decision-making during times of seismic crises. |
| Sectors | Energy,Environment,Other |
| Description | (a)The overarching goals of the project are to improve the speed and accuracy of assessing significant earthquake sequences while they are still in progress. We are, at this stage in the work, developing the processing pipeline that will yield high-accuracy earthquake locations and magnitudes that will be used by other participants in the NERC/NSF project to develop statistical and physics-based forecasts of the hazard as the sequence unfolds. Current methods are hampered by the slow deliveray and inadequate resolution of seismici data, unresolved questions about which models should be applied and large uncertainties in the forecast. (b)We have hosted a special focus workshop to coincide with our 1st Annual Working Meeting in Edinburgh to discuss the application of such new seismological analysis method to current challenges related with induced seismicity in UK and US. Induced seismicity often occurs in low seismicity areas with high industrial noise; the new methodology offers ways to detect and characterise small magnitude events. Therefore, operators, private sector that was invited to our workshop, and officials that we are discussing our course of research will be benefitted from our current breakthroughs. (c)The output of the joint NERC/NSF project with the participation of our INGV partners in Italy will be of interest to the Italian Department of Civil Protection who are responsible for disaster management in Italy. The shortcomings of the existing methods of forecasting hazard are well known from experiences in the 1997 Colfiorito, 2011 L'Auqila and now unfortunately in the 2017 Amatrice/Norcia earthquakes as well. (d) The ground breaking research revealing the advantages for teaching the evolution of the physical earthquake system motivates the development of statewide Italian, and perhaps pan-European, forecast models based on our methodology within the framework of the EU project RISE with the PI Segou leading this component of research. Additional statistical work on potential new statistical approaches is also pursued by University of Edinburgh team, lead by Ian Main. (e) Within our 2nd annual NSFGEO-NERC meeting we will provide a half-to-full day of presentation open to the academic and potentially non-academic community introducing the audience to our results from the first two years. At this moment we have postponed this meeting amid the international concern about the coronavirus outbreak since the meeting was originally set to be in Rome, Italy the last week of March. A mid-2020 might be possible depending on the conditions. The plan and goals of the meeting will continue to be close monitored by the UK-US PI in arranged teleconferences including all team members. (d) We continue the discussion about what the legacy of the project will be especially related to the global progress behind the application of AI in the development of earthquake catalogs. Our project aims in a peer-reviewed paper within the coming year to increase the visibility of our results. We constructed the catalog using a deep-neural-network-based phase picker [Zhu and Beroza, 2019] combined with high-precision double-difference relative relocation. The resulting one-year catalog contains 900,058 events published as Tan et al. (2021), more than a 10-fold increase compared to the INGV routine catalog, and is complete for earthquakes of ML > 0.3. Our catalog reveals rich details regarding the complex fault structures that were activated during the sequence. Although the development of the catalog was done post-event, all of the processes and procedures can be run in real-time, opening the possibility of creating such deep catalogs as part of routine network operations. The deep-learning catalog has now profound implications for the automatic processing of earthquake data and earthquake forecasting (Beroza et al., 2021). It has motivated several manuscripts that are now under preparation for the development of Deep-Learning-based Earthquake Forecasts and their statistical evaluation. The deep earthquakes catalogs will shed light on the underlying characteristics of small-magnitude events that control their triggering potential. Furthermore, team members are now developing deep-learning forecasts of non-parametric nature that could reduce the response time of preliminary earthquake forecasts in times of seismic crises. The latest publication, Mancini et al. (2022), is the first of its kind paper to compare short-term earthquake forecast models using state-of-the-art standard catalogs that correspond to the input data for these predictive models against models based on deep-learning catalogs. We anticipate that the publication will contribute toward shaping the next steps in aftershock forecasting and the discovery of new earthquake triggering mechanisms. |
| First Year Of Impact | 2018 |
| Sector | Energy,Environment,Other |
| Impact Types | Societal,Policy & public services |
| Description | Special Workshop with focus on UK-US induced seismicity |
| Geographic Reach | National |
| Policy Influence Type | Influenced training of practitioners or researchers |
| Description | Earthquake rIsk reduction for a ReSilient Europe (RISE) |
| Amount | € 8,000,000 (EUR) |
| Organisation | European Union |
| Sector | Public |
| Country | European Union (EU) |
| Start | 09/2019 |
| End | 08/2022 |
| Title | A new generation of forecast model using high-resolution and deep-learning datasets |
| Description | Modern enhanced seismicity catalogs provide an unprecedented picture of how earthquake sequences evolve. These next-generation catalogs will be released and updated in real time conditions soon. Therefore, we ask whether the extra information they provide can be exploited to boost the performance of current popular models of short-term earthquake forecasting, namely, physical models of fault-to-fault stress interactions and purely statistical models. We use three enhanced catalogs for the 2016-2017 Central Italy earthquake sequence to develop physical and statistical forecasts for the first 6 months of M3+ seismicity. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | By means of well-established tests, we quantify the predictive skill of the models and benchmark them against forecasts developed using real-time data sets only. We find that both physical and statistical forecasts benefit from gradually incorporating the triggering contributions from the many small, newly revealed events reported in the enhanced catalogs, but their overall performance does not convincingly improve compared to their respective real-time realizations. Sensitivity tests show how future experimental setups should consider that (a) even small variations in the basic components of different catalogs can affect the performance of the resulting forecasts and (b) the typically adopted model spatial resolutions are too coarse to capture small-scale triggering patterns described by enhanced catalogs. |
| URL | https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2022JB025202 |
| Title | New Seismological Analysis Workflow |
| Description | The method was established through a benchmark test using 5-days of continuous 24 hour waveforms from the joint collected seismic network during the 201-2017 sequence. We tested the performance of our waveform cross-correlation and double-difference relocation procedures on 5-days of data including 6,000 events out of the entire dataset of approximately 560,000 events. We evaluated the quality of the obtained correlation coefficients, in terms of the deviations from the catalog picks and other measures, and used the combined data set to obtain high-precision locations using the HypoDD code. The results show detailed structures and geometry of faults that were active during the 5 days in an accuracy that is unforeseen. Relative location errors in the few tens of meters are achieved. The improvement over the initial locations obtained with a traditional grid search method is substantial. Specifically, we have achieved a 28-fold increase in the number of earthquakes detected when compared with the aforementioned traditional methodology. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2019 |
| Provided To Others? | No |
| Impact | The product will lead in changes of seismological practice with global impact. The team is working on publication to make this new method of analysis known to the academic community and the public. |
| Title | Rate-and-State Friction Law combined with Static Stress Transfer hypothesis |
| Description | We elaborated a timeline to pseudo-prospectively test some preliminary forecasts applied to the afore-mentioned Italian sequence. In particular, we were interested in testing the effect of data quality on models performance: in fact, when only real-time catalogues and preliminary earthquake sources descriptions are available the forecasting efforts can be hampered. To this end, we developed two scenarios: a preliminary set of physics-based forecast models based on data products available within minutes to hours after a main event, and a more informed one based on data products available within few weeks from the mainshock occurrence. For the preliminary models, we estimated the stress perturbation at depths between 2 km and 12 km after each of the nine earthquakes of the Italian sequence with M = 5.0, using preliminary data on location, magnitude and fault geometry made available by the INGV (Istituto Nazionale di Geofisica e Vulcanologia) from minutes to few hours after each event. Moreover, at this stage we approximated a simple uniform slip distribution on the selected source faults and fixed the geometry of the receiver faults using the same orientation of the respective source, which is a valid assumption when we do not know much about the complex structures of the neighbouring faults (Segou et al., 2013). In order to improve the forecast performance, we calculated the stress changes for the same events using definitive values of moment magnitude and depth, as well as fault dimensions published on peer reviewed journal articles. Moreover, we requested from our INGV project partners to provide the best-available slip models. For both forecast scenarios, we then translated the computed stress changes into expected seismicity rates applying the Rate-State friction law (Dieterich, 1994). We first computed the reference seismicity for Central Apennines using a catalogue (http://iside.rm.ingv.it/iside) spanning from 1990 to 2016 with magnitude of completeness MC = 2.5. Especially, for the preliminary scenario, we set the Rate-and-State parameters from the available peer-review literature for the study area (e.g. Catalli et al., 2008). On the contrary, Rate-and-State parameters for the second class were progressively and adaptively fitted after each forecast window (one day) by comparing the daily forecast results against the observed unfolding seismicity, in order to retrieve a more realistic set of values. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2018 |
| Provided To Others? | No |
| Impact | A manuscript is under preparation to be submitted in a peer-review journal within the next 6 months. |
| Title | Statistical Clustering for Earthquakes |
| Description | The probabilistic method of Bayliss et al 2019 (funded by an EPSRC studentship) was modified to identify sequences and investigate the significance of small events within earthquake clusters in the case of high-resolution catalogues. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2019 |
| Provided To Others? | No |
| Impact | We anticipate that alternative approaches that enhance current statistical models of earthquake clustering to be critical tools for testing existing protocols as new enhanced AI earthquake catalogs will be available in the near future. |
| Description | Memorandum of Understanding between the British Geological Survey (BGS), Istituto Nationale Geofisica e Volcanologia (INGV-Rome) and the University of Edinburgh (UoE) |
| Organisation | National Institute for Geophysics and Volcanology (INGV) |
| Country | Italy |
| Sector | Public |
| PI Contribution | This collaboration is grounded on the joint BGS-INGV deployment of a temporary seismic network in the epicentral area of the 2016-17 Central Apennines earthquake sequence. The UK seismic instruments were an urgent loan from the Geophysical Equipment Facility (FEG) provided through SEIS-UK following an application from BGS PI (Application Number 1067) including BGS and UoE scientists. The deployment is supported by direct funds provided by the National Environmental Research Council (NERC). |
| Collaborator Contribution | INGV is the Italian organization responsible for providing nearly real time scientific information to the Department of Civil Protection in times of earthquakes disasters occurring on the Italian territory. To this end, running 24h per day seismic monitoring services based on real-time data collected by more than 300 permanent seismic station deployed on the Italian territory, providing earthquake detection and rapid evaluation both in terms of location and magnitude for the earthquakes occurring on the country is a statutory responsibility of INGV. |
| Impact | The aim of this collaboration based on the emergency scientific and technical response is to improve our understanding of aftershock sequences over the next 3 years under a new project funded by NERC-NSF that builds upon the current project team and expands it involving overseas partners. The unparalleled data collection is expected to shed light on how earthquakes nucleate and trigger earthquake cascades and enhance the future earthquake forecast models. The invaluable dataset (See Also Databases section in this report) and the work plan put forward within this international collaboration aims in improving our understanding of the seismogenic structures focusing on unravelling the anatomy of active faults, the interaction pattern and the complexity of normal fault systems in the Apennines. The above is the first crucial element towards a robust seismic hazard assessment and contributes towards the development of testable statistical and physics-based forecast models for aftershock occurrence. We will investigate under which conditions seismic activity migrates to neighbouring faults as well as the geometry of the seismogenic structure to achieve a better description of the underlying physical processes within the earthquake sequence. The collaboration aims strongly supported the institutional responsibilities of the participating institutes (BGS, INGV) and promotes risk reduction strategies at an international level. |
| Start Year | 2016 |
| Description | Memorandum of Understanding between the British Geological Survey (BGS), Istituto Nationale Geofisica e Volcanologia (INGV-Rome) and the University of Edinburgh (UoE) |
| Organisation | University of Edinburgh |
| Department | Earth Science |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | This collaboration is grounded on the joint BGS-INGV deployment of a temporary seismic network in the epicentral area of the 2016-17 Central Apennines earthquake sequence. The UK seismic instruments were an urgent loan from the Geophysical Equipment Facility (FEG) provided through SEIS-UK following an application from BGS PI (Application Number 1067) including BGS and UoE scientists. The deployment is supported by direct funds provided by the National Environmental Research Council (NERC). |
| Collaborator Contribution | INGV is the Italian organization responsible for providing nearly real time scientific information to the Department of Civil Protection in times of earthquakes disasters occurring on the Italian territory. To this end, running 24h per day seismic monitoring services based on real-time data collected by more than 300 permanent seismic station deployed on the Italian territory, providing earthquake detection and rapid evaluation both in terms of location and magnitude for the earthquakes occurring on the country is a statutory responsibility of INGV. |
| Impact | The aim of this collaboration based on the emergency scientific and technical response is to improve our understanding of aftershock sequences over the next 3 years under a new project funded by NERC-NSF that builds upon the current project team and expands it involving overseas partners. The unparalleled data collection is expected to shed light on how earthquakes nucleate and trigger earthquake cascades and enhance the future earthquake forecast models. The invaluable dataset (See Also Databases section in this report) and the work plan put forward within this international collaboration aims in improving our understanding of the seismogenic structures focusing on unravelling the anatomy of active faults, the interaction pattern and the complexity of normal fault systems in the Apennines. The above is the first crucial element towards a robust seismic hazard assessment and contributes towards the development of testable statistical and physics-based forecast models for aftershock occurrence. We will investigate under which conditions seismic activity migrates to neighbouring faults as well as the geometry of the seismogenic structure to achieve a better description of the underlying physical processes within the earthquake sequence. The collaboration aims strongly supported the institutional responsibilities of the participating institutes (BGS, INGV) and promotes risk reduction strategies at an international level. |
| Start Year | 2016 |
| Description | Publication with Project Partner INGV |
| Organisation | Columbia University |
| Department | Lamont Doherty Earth Observatory |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | The PI Dr. Margarita Segou has worked together with Dr. Claudio Chiarabba and Dr. Pasquale De Gori in the analysis of data and synthesis of the results that are described in the paper below, Chiarabba, C., P. De Gori, M. Cattaneo, M Segou. (2018). Faults geometry and the role of fluids in the 2016-2017 Central Italy seismic sequence, Geoph. Res. Lett. 45, https://doi.org/10.1029/2018GL077485 We have increasing presence in international fora of geosciences such as the American Geophysical Union Fall Meeting (2018, 2019). Here are few abstracts that exhibit that the collaboration is still very active and fruitful: (a)Bayliss, K., Naylor, M., & Main, I.G. (2019). Spatio-Temporal Clustering of Earthquakes in the Italian Central Apennines Sequence, Poster presented at: 2019 Fall Meeting, AGU, San Francisco, CA, 9-13 Dec. (b)Di Stefano, R., L. Chiaraluce, M. Michele and F. Waldhauser, Towards an improved earthquake catalog for Italy: the seismicity of the Central Italy area as a case study, Abstract S21E-0563, Fall Meeting, AGU, San Francisco, 9-13 Dec, 2019. (c)Michele, M., F. Waldhauser, and L. Chiaraluce, High resolution relocation of 450,000 automatically detected earthquakes of the 2016-17 Central Italy seismic sequence: The structure and behaviour of a complex normal fault system, Abstract S24A-06, Fall Meeting, AGU, San Francisco, 9-13 Dec, 2019. (d)Zhang, Miao, W.L. Ellsworth, G. Beroza, F. Waldhauser, L. Chiaraluce, M. Michele, M. Segou, Toward rapid characterization of the 2016 Central Apennines, Italy earthquake sequence: a case study, Abstract S31F-0581, Fall Meeting, AGU, Washington, DC, 10-14 Dec, 2018. |
| Collaborator Contribution | As described above. |
| Impact | We have submitted now for publication an extension of the work above with the same scientific collaborators in a high-impact journal. |
| Start Year | 2017 |
| Description | Publication with Project Partner INGV |
| Organisation | Stanford University |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | The PI Dr. Margarita Segou has worked together with Dr. Claudio Chiarabba and Dr. Pasquale De Gori in the analysis of data and synthesis of the results that are described in the paper below, Chiarabba, C., P. De Gori, M. Cattaneo, M Segou. (2018). Faults geometry and the role of fluids in the 2016-2017 Central Italy seismic sequence, Geoph. Res. Lett. 45, https://doi.org/10.1029/2018GL077485 We have increasing presence in international fora of geosciences such as the American Geophysical Union Fall Meeting (2018, 2019). Here are few abstracts that exhibit that the collaboration is still very active and fruitful: (a)Bayliss, K., Naylor, M., & Main, I.G. (2019). Spatio-Temporal Clustering of Earthquakes in the Italian Central Apennines Sequence, Poster presented at: 2019 Fall Meeting, AGU, San Francisco, CA, 9-13 Dec. (b)Di Stefano, R., L. Chiaraluce, M. Michele and F. Waldhauser, Towards an improved earthquake catalog for Italy: the seismicity of the Central Italy area as a case study, Abstract S21E-0563, Fall Meeting, AGU, San Francisco, 9-13 Dec, 2019. (c)Michele, M., F. Waldhauser, and L. Chiaraluce, High resolution relocation of 450,000 automatically detected earthquakes of the 2016-17 Central Italy seismic sequence: The structure and behaviour of a complex normal fault system, Abstract S24A-06, Fall Meeting, AGU, San Francisco, 9-13 Dec, 2019. (d)Zhang, Miao, W.L. Ellsworth, G. Beroza, F. Waldhauser, L. Chiaraluce, M. Michele, M. Segou, Toward rapid characterization of the 2016 Central Apennines, Italy earthquake sequence: a case study, Abstract S31F-0581, Fall Meeting, AGU, Washington, DC, 10-14 Dec, 2018. |
| Collaborator Contribution | As described above. |
| Impact | We have submitted now for publication an extension of the work above with the same scientific collaborators in a high-impact journal. |
| Start Year | 2017 |
| Description | 1st Annual NERC-NSF Working Meeting, Edinburgh 4-5 January 2019 |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | We have held the 1st Annual Working meeting in Edinburgh, hosted by the British Geological Survey with team participants but we have considerably extended the engagement by (1) inviting undergraduate and postgraduate students from local universities and institutes to participate, and (2) inviting well known for their innovative practices international researchers to increase the participation of our benchmarking tests that were the focus of the first year of research. |
| Year(s) Of Engagement Activity | 2019 |
| Description | Final Meeting and Kick-Off Meeting of the 2016-2017 Central Apennines earthquake sequence |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | The final meeting of the current project, featuring the results from the first year of research, was planned to coincide with the kick-off meeting of the NERC-NSF funded research project with title "The Central Apennines earthquake sequence under a new microscope". The event was well attended by UK scientists from the British Geological Survey, the University of Edinburgh, University of Bristol, US scientists from University of Stanford, Lamont-Doherty Earth Observatory in collaboration with US Geological Survey and scientists from Italian Universities such as the University of Sapienza (Rome) and a plethora of local scientists, our project partners, from Institute Geofisica e Volcanologia. The event was hosted in Rome at the grounds of the geophysical institute to enhance international collaboration. The first year of research results have been presented jointly and an activity plan was formed for our future research within the 3-year NERC-NSF Standard Grant. Under/postgrad students had the opportunity to discuss their research with top scientists enhancing in that way their professional networks. |
| Year(s) Of Engagement Activity | 2018 |