How geodesy can contribute to the understanding and prediction of earthquakes

📝 Abstract

Earthquakes cannot be predicted with precision, but algorithms exist for intermediate-term middle range prediction of main shocks above a pre-assigned threshold, based on seismicity patterns. Few years ago, a first attempt was made in the framework of project SISMA, funded by Italian Space Agency, to jointly use seismological tools, like CN algorithm and scenario earthquakes, and geodetic methods and techniques, like GPS and SAR monitoring, in order to effectively constrain priority areas where to concentrate prevention and seismic risk mitigation. We present a further development of integration of seismological and geodetic information, clearly showing the contribution of geodesy to the understanding and prediction of earthquakes. As a relevant application, the seismic crisis that started in Central Italy in August 2016 is considered in a retrospective analysis. Differently from the much more common approach, here GPS data are not used to estimate the standard 2D velocity and strain field in the area, but to reconstruct the velocity and strain pattern along transects, which are properly oriented according to the a priori information about the known tectonic setting. Overall, the analysis of the available geodetic data indicates that it is possible to highlight the velocity variation and the related strain accumulation in the area of Amatrice event, within the area alarmed by CN since November 1st, 2012. The considered counter examples, across CN alarmed and not-alarmed areas, do not show any comparable spatial acceleration localized trend. Therefore, we show that the combined analysis of the results of CN prediction algorithms, with those from the processing of adequately dense and permanent GNSS network data, may allow the routine highlight in advance of the strain accumulation. Thus it is possible to significantly reduce the size of the CN alarmed areas.

💡 Analysis

Earthquakes cannot be predicted with precision, but algorithms exist for intermediate-term middle range prediction of main shocks above a pre-assigned threshold, based on seismicity patterns. Few years ago, a first attempt was made in the framework of project SISMA, funded by Italian Space Agency, to jointly use seismological tools, like CN algorithm and scenario earthquakes, and geodetic methods and techniques, like GPS and SAR monitoring, in order to effectively constrain priority areas where to concentrate prevention and seismic risk mitigation. We present a further development of integration of seismological and geodetic information, clearly showing the contribution of geodesy to the understanding and prediction of earthquakes. As a relevant application, the seismic crisis that started in Central Italy in August 2016 is considered in a retrospective analysis. Differently from the much more common approach, here GPS data are not used to estimate the standard 2D velocity and strain field in the area, but to reconstruct the velocity and strain pattern along transects, which are properly oriented according to the a priori information about the known tectonic setting. Overall, the analysis of the available geodetic data indicates that it is possible to highlight the velocity variation and the related strain accumulation in the area of Amatrice event, within the area alarmed by CN since November 1st, 2012. The considered counter examples, across CN alarmed and not-alarmed areas, do not show any comparable spatial acceleration localized trend. Therefore, we show that the combined analysis of the results of CN prediction algorithms, with those from the processing of adequately dense and permanent GNSS network data, may allow the routine highlight in advance of the strain accumulation. Thus it is possible to significantly reduce the size of the CN alarmed areas.

📄 Content

How geodesy can contribute to the understanding and prediction of earthquakes

G. F. Panza1,2,3, A. Peresan3,4, F. Sansò2,5, M. Crespi6, A. Mazzoni6, A. Nascetti6

1Institute of Geophysics, China Earthquake Administration, Beijing, China 2Accademia Nazionale dei Lincei, Rome, Italy 3International Seismic Safety Organization (ISSO) - www.issoquake.org 4CRS – Istituto Nazionale di Oceanografia e Geofisica Sperimentale, Trieste, Italy 5DICA - Politecnico di Milano, Milan, Italy 6Geodesy and Geomatics Division – DICEA – University of Rome “La Sapienza”, Rome, Italy

Abstract

Earthquakes cannot be predicted with precision, but algorithms exist for intermediate-term middle range prediction of main shocks above a pre-assigned threshold, based on seismicity patterns. Few years ago, a first attempt was made in the framework of project SISMA, funded by Italian Space Agency, to jointly use seismological tools, like CN algorithm and scenario earthquakes, and geodetic methods and techniques, like GPS and SAR monitoring, in order to effectively constrain priority areas where to concentrate prevention and seismic risk mitigation. We present a further development of integration of seismological and geodetic information, clearly showing the contribution of geodesy to the understanding and prediction of earthquakes.
As a relevant application, the seismic crisis that started in Central Italy in August 2016 with the Amatrice earthquake and still going on, is considered in a retrospective analysis of both GPS and SAR data. Differently from the much more common approach, here GPS data are not used to estimate the standard 2D velocity and strain field in the area, but to reconstruct the velocity and strain pattern along transects, which are properly oriented according to the a priori information about the known tectonic setting. SAR data related to the Amatrice earthquake coseismic displacements are here used as independent check of the GPS results. Overall, the analysis of the available geodetic data indicates that it is possible to highlight the velocity variation and the related strain accumulation in the area of Amatrice event, within the area alarmed by CN since November 1st, 2012. The considered counter examples, across CN alarmed and not-alarmed areas, do not show any spatial acceleration localized trend, comparable to the one well defined along the Amatrice transect.
Therefore, we show that the combined analysis of the results of intermediate term middle range earthquake prediction algorithms, like CN, with those from the processing of adequately dense and permanent GNSS network data, possibly complemented by a continuous InSAR tracking, may allow the routine highlight in advance of the strain accumulation. Thus it is possible to significantly reduce the size of the CN alarmed areas.

Introduction

Earthquakes cannot be predicted with precision, but algorithms exist for intermediate-term middle range prediction of main shocks above a pre-assigned threshold, like M8 and CN. The alarms, which refer to areas with linear dimensions of hundred kilometres and having a duration of several months to years, are not compatible with evacuation or red alert, but can be very useful for many effective low key prevention actions (Kantorovich et al., 1974; Kantorovich and Keilis-Borok, 1991, Peresan et al., 2012). The formulation of the M8 and CN predictions satisfies the basic principle of science introduced by Karl Popper: a model to be scientific acceptable must be falsifiable. The statistical validity has been proven both at global and regional scale (Kossobokov, 2014; Kossobokov and Soloviev, 2015). Indeed “The proof of the pudding is in the eating…”
CN prediction experiment started in Italy in 1998 (Peresan et al., 2005). Since then nine strong earthquakes occurred in the territory monitored by CN and seven of them have been predicted in “real time” – the event occurred after the alarm was declared to a group of scientists and administrators – more than one hundred people - who routinely receive prediction results (Peresan, 2017).
At the meeting of the Commissione Grandi Rischi (CGR) of May 4th 2012, the reliability of CN alarm for “Northern (Italy) region” has been questioned, but the May 21st 2012 earthquake in Emilia tragically confirmed the alarm. Similar predictions have been made before the earthquakes of Amatrice and Norcia (DMG, 2017; IEPT, 2017).

Figure 1 - Regionalization used in the CN prediction experiment in Italy (Peresan, 2017 and references therein). The regionalization is composed by four partially overlapping regions, defined based on the seismotectonic model. The magnitude threshold identifying the target earthquakes is given for each region.

The probability gain of CN predictions is around 3, i.e. the occurrence probability of a target earthquake increases by a factor of 3 during the time interval occupied by the alarm, with r

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