Foreshocks and short-term hazard assessment of large earthquakes usingcomplex networks: the case of the 2009 L'Aquila earthquake

Abstract. The monitoring of statistical network properties could be useful for the short-term hazard assessment of the occurrence of mainshocks in the presence of foreshocks. Using successive connections between events acquired from the earthquake catalog of the Istituto Nazionale di Geofisica e Vulcanologia (INGV) for the case of the L'Aquila (Italy) mainshock (Mw = 6.3) of 6 April 2009, we provide evidence that network measures, both global (average clustering coefficient, small-world index) and local (betweenness centrality) ones, could potentially be exploited for forecasting purposes both in time and space. Our results reveal statistically significant increases in the topological measures and a nucleation of the betweenness centrality around the location of the epicenter about 2 months before the mainshock. The results of the analysis are robust even when considering either large or off-centered the main event space windows.

[1]  Luciano Telesca,et al.  Precursory signatures in the visibility graph analysis of seismicity: An application to the Kachchh (Western India) seismicity , 2015 .

[2]  Alessandro Vespignani,et al.  Dynamical Processes on Complex Networks , 2008 .

[3]  Peter Bormann,et al.  From Earthquake Prediction Research to Time-Variable Seismic Hazard Assessment Applications , 2011 .

[4]  Funabashi,et al.  Scale-free network of earthquakes , 2002 .

[5]  L. de Arcangelis,et al.  Spatial organization of foreshocks as a tool to forecast large earthquakes , 2012, Scientific Reports.

[6]  D. Sornette,et al.  Positive feedback, memory, and the predictability of earthquakes , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[7]  Rita Di Giovambattista,et al.  Accelerating moment release revisited: Examples of application to Italian seismic sequences , 2015 .

[8]  G. Cianchini,et al.  Magnetic transfer function entropy and the 2009 M w = 6.3 L'Aquila earthquake (Central Italy) , 2012 .

[9]  K. Tiampo,et al.  Analysis of complex networks associated to seismic clusters near the Itoiz reservoir dam , 2009 .

[10]  J. Dieterich.  A constitutive law for rate of earthquake production and its application to earthquake clustering , 1994 .

[11]  C. Siettos,et al.  Analysing the topology of seismicity in the Hellenic arc using complex networks , 2013, Journal of Seismology.

[12]  S. Barani,et al.  Did the 6 April 2009 L'Aquila Earthquake Fill a Seismic Gap? , 2011 .

[13]  Danijel Schorlemmer,et al.  Common dependence on stress for the two fundamental laws of statistical seismology , 2009, Nature.

[14]  K. Mogi.  Some Discussions on Aftershocks, Foreshocks and Earthquake Swarms : the Fracture of a Semi-infinite Body Caused by an Inner Stress Origin and Its Relation to the Earthquake Phenomena (Third Paper) , 1963 .

[15]  Per Bak,et al.  The Discovery of Self-Organized Criticality , 1996 .

[16]  Y. Ogata.  Space-Time Point-Process Models for Earthquake Occurrences , 1998 .

[17]  Philip G. Meredith,et al.  A reinterpretation of the precursory seismic b-value anomaly from fracture mechanics , 1989 .

[18]  G. Papadopoulos,et al.  Foreshocks and b Value: Bridging Macroscopic Observations to Source Mechanical Considerations , 2013, Pure and Applied Geophysics.

[19]  T. Utsu.  On the nature of three Alaskan aftershock sequences of 1957 and 1958 , 1962 .

[20]  Per Bak,et al.  How Nature Works: The Science of Self-Organised Criticality , 1997 .

[21]  L. Telesca.  A non‐extensive approach in investigating the seismicity of L’Aquila area (central Italy), struck by the 6 April 2009 earthquake (ML = 5.8) , 2010 .

[22]  S. Hainzl.  Seismicity patterns of earthquake swarms due to fluid intrusion and stress triggering , 2004 .

[23]  G. Papadopoulos.  Long-term accelerating foreshock activity may indicate the occurrence time of a strong shock in the Western Hellenic Arc , 1988 .

[24]  David J. Varnes,et al.  Predictive modeling of the seismic cycle of the Greater San Francisco Bay Region , 1993 .

[25]  Mark Newman,et al.  The structure and function of networks , 2002 .

[26]  Jiancang Zhuang,et al.  Properties of the probability distribution associated with the largest event in an earthquake cluster and their implications to foreshocks. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[27]  J. Kurths,et al.  Similar power laws for foreshock and aftershock sequences in a spring‐block model for earthquakes , 1999 .

[28]  G. Fagiolo.  Clustering in complex directed networks. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[29]  Gerassimos A. Papadopoulos,et al.  OPERATIONAL EARTHQUAKE FORECASTING. State of Knowledge and Guidelines for Utilization , 2011 .

[30]  L. da F. Costa,et al.  Characterization of complex networks: A survey of measurements , 2005, cond-mat/0505185.

[31]  Gerassimos A. Papadopoulos,et al.  A Global Overview of Short-Term Foreshocks and Their Predictive Value , 2014 .

[32]  L. Crescentini,et al.  Limits on earthquake nucleation and other pre‐seismic phenomena from continuous strain in the near field of the 2009 L'Aquila earthquake , 2010 .

[33]  B. Gutenberg,et al.  Frequency of Earthquakes in California , 1944, Nature.

[34]  Mark E. J. Newman,et al.  The Structure and Function of Complex Networks , 2003, SIAM Rev..

[35]  Lucile M. Jones,et al.  Prediction Probabilities From Foreshocks , 1991 .

[36]  Y. Ogata,et al.  The Centenary of the Omori Formula for a Decay Law of Aftershock Activity , 1995 .

[37]  T. Utsu.  Representation and Analysis of the Earthquake Size Distribution: A Historical Review and Some New Approaches , 1999 .

[38]  G. Ventura,et al.  Normal faults and thrusts reactivated by deep fluids: The 6 April 2009 Mw 6.3 L'Aquila earthquake, central Italy , 2010 .

[39]  Kiyoo Mogi,et al.  Study of Elastic Shocks Caused by the Fracture of Heterogeneous Materials and its Relations to Earthquake Phenomena , 1962 .

[40]  A. Rovelli,et al.  Transient anomaly in fault zone‐trapped waves during the preparatory phase of the 6 April 2009, Mw 6.3 L'Aquila earthquake , 2015 .

[41]  B. Papazachos.  Foreshocks and earthquake prediction , 1975 .

[42]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

[43]  G. Papadopoulos,et al.  Strong foreshock signal preceding the L'Aquila (Italy) earthquake ( M w 6.3) of 6 April 2009 , 2010 .

[44]  C. Lomnitz.  Global tectonics and earthquake risk , 1974 .

[45]  Laura Beranzoli,et al.  The Gutenberg-Richter law and Entropy of earthquakes: two case studies in Central Italy , 2011 .

[46]  Jiancang Zhuang,et al.  Long-term earthquake forecasts based on the epidemic-type aftershock sequence (ETAS) model for short-term clustering , 2012 .

[47]  M. Baiesi,et al.  Scale-free networks of earthquakes and aftershocks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[48]  Davide Piccinini,et al.  Temporal variation of seismic velocity and anisotropy before the 2009 MW 6.3 L'Aquila earthquake, Italy , 2010 .

[49]  A. Frepoli,et al.  The 2009 L'Aquila (Central Italy) seismic sequence as a chaotic process , 2010 .

[50]  M. Wyss,et al.  Variations in earthquake-size distribution across different stress regimes , 2005, Nature.

[51]  Per Bak,et al.  How Nature Works: The Science of Self‐Organized Criticality , 1997 .

[52]  T. Prescott,et al.  The brainstem reticular formation is a small-world, not scale-free, network , 2006, Proceedings of the Royal Society B: Biological Sciences.

[53]  Maya Paczuski,et al.  Complex networks of earthquakes and aftershocks , 2004, physics/0408018.

[54]  Luciano Telesca,et al.  Analysis of seismic sequences by using the method of visibility graph , 2012 .

[55]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[56]  Kiyoo Mogi.  The Fracture of a Semi-infinite Body Caused by an Inner Stress Origin and Its Relation to the Earthquake Phenomena (Second Paper) : The Case of the Materials Having Some Heterogeneous Structures , 1963 .

[57]  James Jackson,et al.  The 2009 L'Aquila earthquake (central Italy): A source mechanism and implications for seismic hazard , 2009 .

[58]  Warner Marzocchi,et al.  Real‐time forecasting following a damaging earthquake , 2009 .

[59]  S. Abe,et al.  Dynamical evolution of clustering in complex network of earthquakes , 2007 .

[60]  Naoshi Hirata,et al.  Decade‐scale decrease inb value prior to the M9‐class 2011 Tohoku and 2004 Sumatra quakes , 2012 .

[61]  F. Visini,et al.  Fault-Based Earthquake Rupture Forecast in Central Italy: Remarks after the L'Aquila Mw 6.3 Event , 2011 .

[62]  T. Utsu,et al.  42 - A List of Deadly Earthquakes in the World: 1500–2000 , 2002 .

[63]  T. Yamashita.  Simulation of seismicity due to fluid migration in a fault zone , 1998 .

[64]  Jamieson H Steidl,et al.  Report on the August 2012 Brawley Earthquake Swarm in Imperial Valley, Southern California , 2013 .

[65]  Lucile M. Jones,et al.  Some characteristics of foreshocks and their possible relationship to earthquake prediction , 1979 .

[66]  I. Main.  A damage mechanics model for power-law creep and earthquake aftershock and foreshock sequences , 2000 .

[67]  Aitaro Kato,et al.  The preparatory phase of the 2009 Mw 6.3 L'Aquila earthquake by improving the detection capability of low‐magnitude foreshocks , 2014 .

[68]  Yan Y. Kagan,et al.  Statistical study of the occurrence of shallow earthquakes , 1978 .

[69]  G. Molchan,et al.  Immediate foreshocks: time variation of the b-value 1 In memoriam A.G. Peozorov. 1 , 1999 .

[70]  Stefan Wiemer,et al.  Short‐term probabilistic earthquake risk assessment considering time‐dependent b values , 2016 .

[71]  Arnaud Mignan,et al.  Retrospective on the Accelerating Seismic Release (ASR) hypothesis: Controversy and new horizons , 2011 .

[72]  D. Karlis,et al.  Identification of temporal patterns in the seismicity of Sumatra using Poisson Hidden Markov models , 2014 .