Incorporating space, time, and magnitude measures in a network characterization of earthquake events

Janer, C. D.; Biton, D. C.; Batac, R. C.

doi:10.1007/s11600-017-0100-3

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Tytuł artykułu

Incorporating space, time, and magnitude measures in a network characterization of earthquake events

Autorzy

Janer C. D. , Biton D. C. , Batac R. C.

Wybrane pełne teksty z tego czasopisma

https://www.springer.com/journal/11600

Identyfikatory

DOI

10.1007/s11600-017-0100-3

Warianty tytułu

Języki publikacji

Abstrakty

We investigate the structural properties of a spatio-temporal network of earthquake events that incorporates magnitude information between the connected events. The network creates temporally directed links from an origin event towards a later event if it breaks the record closest distance from the origin among all the events in the catalog so far. Additionally, the links are conditionally classified based on the magnitude difference between connected events: “up” (“down”) connections point from a weaker (stronger) to a stronger (weaker) event. Using earthquake records from the Philippines from 1973 to 2012 and southern California from 1982 to 2012, we observe that the out-degree distributions show slight deviations from the corresponding Poisson distribution of the same mean. The space and time separations of connected earthquakes both show power-law regimes, suggesting spatio-temporal (self)organization. More importantly, the conditional distributions of “up” and “down” connections in space, time, and network structure point to a higher likelihood of a stronger event triggering a nearby weaker event for the first few connections, as in the case of aftershocks. The results are captured by a sandpile-based model where a small but finite probability of preferentially targeting the most susceptible grid site is introduced. Our analysis, coupled with the discrete model analog, provides a quantitative picture of the spatio-temporal and magnitude organization of seismicity beyond just the successive events. The technique may be extended to further characterize similar long-period earthquake records to yield a more complete picture of the underlying processes involved in seismicity.

Słowa kluczowe

earthquakes spatiotemporal analysis spatio-temporal network

trzęsienia ziemi analiza czasowo-przestrzenna sieć czasoprzestrzenna

Wydawca

Instytut Geofizyki PAN
Springer

Czasopismo

Acta Geophysica

Rocznik

2017

Tom

Vol. 65, no. 6

Strony

1153--1166

Opis fizyczny

Bibliogr. 41 poz.

Twórcy

autor

Janer C. D.

National Institute of Physics, University of the Philippines, Diliman, Quezon City, Philippines

autor

Biton D. C.

National Institute of Physics, University of the Philippines, Diliman, Quezon City, Philippines

autor

Batac R. C.

rcbatac@up.edu.ph

National Institute of Physics, University of the Philippines, Diliman, Quezon City, Philippines

Bibliografia

1. Abe S, Suzuki N (2007) Dynamical evolution of clustering in complex network of earthquakes. Eur Phys J B 59(1):93–97. https://doi.org/10.1140/epjb/e2007-00259-3
2. Albert R, Barabási AL (2002) Statistical mechanics of complex networks. Rev Modern Phys 74(1):47. https://doi.org/10.1103/RevModPhys.74.47
3. Baiesi M, Paczuski M (2004) Scale-free networks of earthquakes and aftershocks. Phys Rev E 69(6):066106. https://doi.org/10.1103/PhysRevE.69.066106
4. Bak P, Tang C (1989) Earthquakes as a self-organized critical phenomenon. J Geophys Res 94:15635–15637. https://doi.org/10.1029/JB094iB11p15635
5. Bak P, Christensen K, Danon L, Scanlon T (2002) Unified scaling law for earthquakes. Phys Rev Lett 88:178501. https://doi.org/10.1103/PhysRevLett.88.178501
6. Batac RC (2016) Statistical properties of the immediate aftershocks of the 15 October 2013 magnitude 7.1 earthquake in Bohol, Philippines. Acta Geophys 64(1):15–25. https://doi.org/10.1515/acgeo-2015-0054
7. Batac RC, Kantz H (2014) Observing spatio-temporal clustering and separation using interevent distributions of regional earthquakes. Nonlinear Processes Geophys 21(4):735–744. https://doi.org/10.5194/npg-21-735-2014
8. Batac RC, Paguirigan AA Jr, Tarun AB, Longjas AG (2017) Sandpile-based model for capturing magnitude distributions and spatiotemporal clustering and separation in regional earthquakes. Nonlinear Processes Geophys 24(2):179–187. https://doi.org/10.5194/npg-24-179-2017
9. Davidsen J, Baiesi M (2016) Self-similar aftershock rates. Phys Rev E 94(2):022314. https://doi.org/10.1103/PhysRevE.94.022314
10. Davidsen J, Paczuski M (2005) Analysis of the spatial distribution between successive earthquakes. Phys Rev Lett 94:048501. https://doi.org/10.1103/PhysRevLett.94.048501
11. Davidsen J, Grassberger P, Paczuski M (2006) Earthquake recurrence as a record breaking process. Geophys Res Lett 33(11):L11304. https://doi.org/10.1029/2006GL026122
12. Davidsen J, Grassberger P, Paczuski M (2008) Networks of recurrent events, a theory of records, and an application to finding causal signatures in seismicity. Phys Rev E 77(6):066104. https://doi.org/10.1103/PhysRevE.77.066104
13. Efstathiou A, Tzanis A, Vallianatos F (2017) On the nature and dynamics of the seismogenetic systems of North California, USA: an analysis based on non-extensive statistical physics. Phys Earth Planet Inter 270:46–72. https://doi.org/10.1016/j.pepi.2017.06.010
14. Frohlich C, Davis SD (1993) Teleseismic b values; or, much ado about 10. J Geophys Res Solid Earth 98(B1):631–644. https://doi.org/10.1029/92JB01891
15. Gu C, Schumann AY, Baiesi M, Davidsen J (2013) Triggering cascades and statistical properties of aftershocks. J Geophys Res Solid Earth 118:4278–4295. https://doi.org/10.1002/jgrb.50306
16. Gutenberg B, Richter CF (1954) Seismicity of the earth and associated phenomena, 2nd edn. Princeton University Press, Princeton
17. Hayakawa M, Hobara Y (2010) Current status of seismoelectromagnetics for short-term earthquake prediction. Geomatics Nat Hazards Risk 1(2):115–155. https://doi.org/10.1080/19475705.2010.486933
18. Helmstetter A, Kagan YY, Jackson DD (2005) Importance of small earthquakes for stress transfers and earthquake triggering. J Geophys Res 110(B5):2156–2202. https://doi.org/10.1029/2004JB003286
19. Ito K, Matsuzaki M (1990) Earthquakes as self-organized critical phenomena. J Geophys Res 95:6853–6860. https://doi.org/10.1029/JB095iB05p06853
20. Jagla EA (2013) Forest-fire analogy to explain the b value of the Gutenberg-Richter law for earthquakes. Phys Rev Lett 111(23):238501. https://doi.org/10.1103/PhysRevLett.111.238501
21. Keilis-Borok V, Soloviev AA (eds) (2013) Nonlinear dynamics of the lithosphere and earthquake prediction. Springer Science and Business Media, Berlin
22. Landes FP, Lippiello E (2016) Scaling laws in earthquake occurrence: disorder, viscosity, and finite size effects in Olami-Feder-Christensen models. Phys Rev E 53:051001. https://doi.org/10.1103/PhysRevE.93.051001
23. Livina VN, Havlin S, Bunde A (2005) Memory in the occurrence of earthquakes. Phys Rev Lett 95(20):208501. https://doi.org/10.1103/PhysRevLett.95.208501
24. Marekova E (2014) Analysis of the spatial distribution between successive earthquakes occurred in various regions in the world. Acta Geophys 62(6):1262–1282. https://doi.org/10.2478/s11600-014-0234-5
25. Narteau C, Byrdina S, Shebalin P, Schorlemmer D (2009) Common dependence on stress for the two fundamental laws of statistical seismology. Nature 462:642–645. https://doi.org/10.1038/nature08553
26. Olami Z, Feder HJS, Christensen K (1992) Self-organized criticality in a continuous, nonconservative cellular automaton modeling earthquakes. Phys Rev Lett 68(8):1244. https://doi.org/10.1103/PhysRevLett.68.1244
27. PDE (1973-2012), Preliminary determination of epicentres catalogue. http://earthquake.usgs.gov/earthquakes/eqarchives/epic. Last access: December 2012
28. Saichev A, Sornette D (2006) “Universal” distribution of interearthquake times explained. Phys Rev Lett 97(7):078501. https://doi.org/10.1103/PhysRevLett.97.078501
29. SCEDC (1982-2012), Southern California earthquake data center. http://www.data.scec.org/eq-catalogs/date_mag_loc.php, last access: December 2012
30. Schoenball M, Davatzes NC, Glen JM (2015) Differentiating induced and natural seismicity using space-time-magnitude statistics applied to the Coso Geothermal field. Geophys Res Lett 42(15):6221–6228. https://doi.org/10.1002/2015GL064772
31. Scholz CH (2015) On the stress dependence of the earthquake b value. Geophys Res Lett 42(5):1399–1402. https://doi.org/10.1002/2014GL062863
32. Schorlemmer D, Wiemer S, Wyss M (2005) Variations in earthquake-size distribution across different stress regimes. Nature 437:539–542. https://doi.org/10.1038/nature04094
33. Spada M, Tormann T, Wiemer S, Enescu B (2013) Generic dependence of the frequency-size distribution of earthquakes on depth and its relation to the strength profile of the crust. Geophys Res Lett 40:709–714. https://doi.org/10.1029/2012GL054198
34. Tarun AB, Paguirigan AA, Batac RC (2015) Spatiotemporal recurrences of sandpile avalanches. Phys A 436:293–300. https://doi.org/10.1016/j.physa.2015.05.016
35. Telesca L (2007) Time-clustering of natural hazards. Nat Hazards 40(3):593–601. https://doi.org/10.1007/s11069-006-9023-z
36. Touati S, Naylor M, Main IG (2009) Origin and nonuniversality of the earthquake interevent time distribution. Phys Rev Lett 102(16):168501. https://doi.org/10.1103/PhysRevLett.102.168501
37. Tzanis A, Vallianatos F, Efstathiou A (2013) Multidimensional earthquake frequency distributions consistent with non-extensive statistical physics: the interdependence of magnitude, interevent time and interevent distance in North California. Bulletin Geol. Soc. Greece 47(3):1326–1337. https://doi.org/10.12681/bgsg.10914
38. Zaliapin I, Ben-Zion Y (2013a) Earthquake clusters in southern California I: identification and stability. J Geophys Res 118:2847–2864. https://doi.org/10.1002/jgrb.50179
39. Zaliapin I, Ben-Zion Y (2013b) Earthquake clusters in southern California II: classification and relation to physical properties of the crust. J Geophys Res 118:2865–2877. https://doi.org/10.1002/jgrb.50178
40. Zaliapin I, Ben-Zion Y (2015) Artefacts of earthquake location errors and short-term incompleteness on seismicity clusters in southern California. Geophys J Int 202:1949–1968. https://doi.org/10.1093/gji/ggv259
41. Zaliapin I, Gabrielov A, Keilis-Borok V, Wong H (2008) Clustering analysis of seismicity and aftershock identification. Phys Rev Lett 101:018501. https://doi.org/10.1103/PhysRevLett.101.018501

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018)

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-de00b297-4a42-49f5-b4ba-2b6b059d9190