Surface volume and gravity changes due to significant earthquakes occurred in central Italy from 2009 to 2016

Riguzzi, Federica; Tan, Hongbing; Shen, Chongyang

doi:10.1007/s00531-019-01748-0

Cited by 3 publications

(3 citation statements)

References 56 publications

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“…The global co-seismic impact on the local gravity field generated by the elevation changes due to the 2009 and 2016 earthquakes in central Italy has recently been modeled. The model shows that the area affected by gravity changes was approximately 140 km long and approximately 57 km wide, parallel to the Apennines, with a maximum positive gravity change of approximately +170 µGal [43]. Hence, the medium-long-term gravity and ground deformation variations related to pre-and post-seismic (i.e., compression/relaxation) were also expected in the stations of the network we measured.…”

Section: Discussionsupporting

confidence: 54%

“…Nevertheless, the results of the long-term gravity (1995-2010) variation at LNGS UND do not appear to be in agreement with the model because, specifically in the area around the L'Aquila city, they show that the effect of the co-seismic elevation changes was a maximum of +40 µGal which rapidly decreased, such that at the LNGS it was only −1/−2 µGal [43].…”

Section: Discussionmentioning

confidence: 75%

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Insights into Seismogenetic Areas in Central Italy from Combined Absolute Gravity and GNSS Measurements

2021

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In this study we present and discuss gravity and ground deformation variations, at different time scales, observed in a wide mesh absolute gravity and GNSS network set up in central Italy. The network was installed in the area affected by the 2009 (L’Aquila; Mw 6.1) and 2016 (Amatrice-Norcia; Mw 6.0 and 6.5) seismic activity, in order to verify if gravity and ground deformation variations could be related to seismic effects. The new network includes 5 stations distributed between the Lazio, Umbria, and Abruzzo regions. From 2018 to 2020 three campaigns were carried out using the transportable Micro-g LaCoste FG5#238 and the portable Micro-g LaCoste A10#39 absolute gravimeters and completed with two simultaneous GNSS measurements. Topographic instruments, measurement and analysis techniques enabling accurate measurements in the positioning of the stations and to control their variations over time were applied. The high reliability and accuracy of the absolute gravity data gathered, after being corrected for known effects, showed a negative short-term (2018–2020) pattern throughout the area, up to −30 µGal. Since some stations of the new network coincided with benchmarks already measured in the past, an analysis of long-term gravity changes was carried out and a fair degree of stability was observed in two stations, while positive large variations, of approximately 70 and 157 µGal, were recorded in the other two stations in the time intervals 1954–2020 and 2005–2010, respectively. On the other hand, variations highlighted by GNSS height measurements were all below 3 cm. Here, the first long-lasting gravity measurements carried out with absolute gravimeters in a seismic area in Italy are presented, providing meaningful geophysical information. The obtained results, in terms of availability of a combined absolute gravity and GNSS network, definition of data acquisition and analysis procedures, as well as creation of a high quality data archive, lay the foundations for a multidisciplinary approach towards improving the knowledge of this seismogenetic area of Italy.

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Section: Discussionsupporting

confidence: 54%

Section: Discussionmentioning

confidence: 75%

Insights into Seismogenetic Areas in Central Italy from Combined Absolute Gravity and GNSS Measurements

2021

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“…Nevertheless, earthquakes and their consequences are among the most life-changing events in the history of humanity. Seismic activities and their aftermath disasters been the cause of more human life loss than all other natural hazards combined during the past two decades [8] because many countries are located in highly seismically active zones [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Modelling and Feature Engineering in Seismology Experiment

Брыков

Petryshynets

Pruncu

et al. 2020

Sensors

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This article aims to discusses machine learning modelling using a dataset provided by the LANL (Los Alamos National Laboratory) earthquake prediction competition hosted by Kaggle. The data were obtained from a laboratory stick-slip friction experiment that mimics real earthquakes. Digitized acoustic signals were recorded against time to failure of a granular layer compressed between steel plates. In this work, machine learning was employed to develop models that could predict earthquakes. The aim is to highlight the importance and potential applicability of machine learning in seismology The XGBoost algorithm was used for modelling combined with 6-fold cross-validation and the mean absolute error (MAE) metric for model quality estimation. The backward feature elimination technique was used followed by the forward feature construction approach to find the best combination of features. The advantage of this feature engineering method is that it enables the best subset to be found from a relatively large set of features in a relatively short time. It was confirmed that the proper combination of statistical characteristics describing acoustic data can be used for effective prediction of time to failure. Additionally, statistical features based on the autocorrelation of acoustic data can also be used for further improvement of model quality. A total of 48 statistical features were considered. The best subset was determined as having 10 features. Its corresponding MAE was 1.913 s, which was stable to the third decimal point. The presented results can be used to develop artificial intelligence algorithms devoted to earthquake prediction.

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Gravity and crustal dynamics in Italy

Riguzzi

Doglioni

2020

Rend. Fis. Acc. Lincei

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Surface volume and gravity changes due to significant earthquakes occurred in central Italy from 2009 to 2016

Cited by 3 publications

References 56 publications

Insights into Seismogenetic Areas in Central Italy from Combined Absolute Gravity and GNSS Measurements

Insights into Seismogenetic Areas in Central Italy from Combined Absolute Gravity and GNSS Measurements

Machine Learning Modelling and Feature Engineering in Seismology Experiment

Gravity and crustal dynamics in Italy

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