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Spatio-temporal evolution of seismic clusters in southern and central California. Ilya Zaliapin. Department of Mathematics and Statistics University of Nevada, Reno. Yehuda Ben-Zion Department of Earth Sciences University of Southern California. SAMSI workshop “ Dynamics of Seismicity ” - PowerPoint PPT Presentation
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Ilya ZaliapinDepartment of Mathematics and Statistics
University of Nevada, Reno
SAMSI workshop “Dynamics of Seismicity”Thursday, October 10, 2013
Yehuda Ben-ZionDepartment of Earth Sciences
University of Southern California
Spatio-temporal evolution of seismic clusters in southern and central California
Earthquake clusters: existence, detection, stability
Clusters in southern California
1
2
3
1
2
3
Outline
o Main types of clusterso Topological cluster characterization
Evolution of clustering with relation to large events44
Cluster type vs. physical properties of the lithosphere
Data
•Southern California catalog: Hauksson, Yang, Shearer (2012) available from SCEC data center; 111,981 earthquakes with m ≥ 2
•Heat flow data from www.smu.edu/geothermal
Baiesi and Paczuski, PRE, 69, 066106 (2004)Zaliapin et al., PRL, 101, 018501 (2008)
Zaliapin and Ben-Zion, GJI, 185, 1288–1304 (2011)Zaliapin and Ben-Zion, JGR, 118, 2847-2864 (2013)Zaliapin and Ben-Zion, JGR, 118, 2865-2877 (2013)
10 , 0ibmdr
(Fractal) dimension of epicenters
Intercurrence time Spatial distance Gutenberg-Richter law
[M. Baiesi and M. Paczuski, PRE, 69, 066106 (2004)]
/2 /2Rescaled time 10 , Rescaled distance 10i ibm bmdT R r
[Zaliapin et al., PRL, 101, 018501 (2008)]
, log log logTR T R
Distance from an earthquake j to an earlier earthquake i :
Definition:
Property:
Separation of clustered and background parts in southern California
Earthquake jPa
rent (n
eares
t neig
hbor)
i
Zaliapin and Ben-Zion, JGR (2012)Zaliapin et al., PRL
(2008)
Background and clustered parts in models
Zaliapin and Ben-Zion, JGR (2013)Zaliapin et al., PRL
(2008)
Homogeneous Poisson process ETAS model
Separation of clustered and background parts in southern CaliforniaBackground = weak links
(as in stationary, inhomogeneous Poisson
process)
Clustered part = strong links (events are much closer to each
other than in the background part)
Zaliapin and Ben-Zion, JGR (2013)Zaliapin et al., PRL
(2008)
weak linkstrong link
Cluster #3
Cluster #2
Cluster #1
Identification of clusters: data driven
Time
Foreshocks
Aftershocks
Mainshock
Identification of event types: problem driven
Time
Single
ETAS declustering: Example
29,671 events
9,536 mainshocks
① Burst-like clusters Represent brittle fracture. Large b-value (b=1), small number of events,
small proportion of foreshocks, short duration, small area, isotropic spatial distribution.
Tend to occur in regions with low heat flow, non-enhanced fluid content, relatively large depth => increased effective viscosity.
② Swarm-like clusters Represent brittle-ductile fracture. Small b-value (b=0.6), large number of
events, large proportion of foreshocks, long duration, large area, anisotropic channel-like spatial pattern.
Tend to occur in regions with high heat flow, increased fluid content, relatively shallow depth => decreased effective viscosity.
③ Singles Highly numerous in all regions; some but not all are related to catalog
resolution.
④ Clusters of the largest events Most prominent clusters; object of the standard cluster studies. Not
representative of the majority of clusters (mixture of types 1-2).
M5.75
M5.51
M5.51 M5.75
L= 417, tree depth = 9, ave. depth = 3.8 L= 572, tree depth = 44, ave. depth = 30.3
Swarm vs. burst like clusters:Topologic representation
Burst-like Swarm-like
Tim
e
Tim
e
Average leaf depth (number of generations from a leaf to the root):Bimodal structure
HYS (2012), mM ≥ 2
Large topological depth:Swarm-like clusters
Small topological depth:Burst-like clusters
ETAS model
Heat flow in southern Californiahttp://www.smu.edu/geothermal
Preferred spatial location of burst/swarm like clusters 195 clusters with m ≥ 4, N ≥ 10; spatial average within 50 km
Moment of foreshocks relative to that of mainshock 195 clusters with m ≥ 4, N ≥ 10; spatial average within 50 km
Family size 112 Δ- clusters with m ≥ 4, N ≥ 10; spatial average within 50 km
X-zone
X-zone
D-zone
D-zone
Time
Spa
ce
N-zone
Statistical analysis of premonitory patterns: zero-level approach
D = 2 years, X = 1 year, R = 200 km, M=6.5mainshocks with m>3 are examined
All mainshocks
Topological depth (average leaf depth)
Δ = X = 3 years, R = 100km m > 3, N > 20
ANOVA p =7x10-7 : Significant difference
Large families, N > 20
Topological depth (average leaf depth)
Δ = X = 2 years, R = 100km m > 3
All mainshocks
Proportion of families
Δ = X = 2 years, R = 100km m > 3, N >1
Families (N > 1)
Proportion of large families (N>=5)
Large earthquakes in California, M6.5
2) Landers, M7.3, 1992
4) Hector Mine, M7.1, 1999
1) Superstition Hills, M6.6, 1987
5) El Mayor Cucapah, M7.2, 2010
3) Northridge, M6.7, 1994
L
EMCL
“San Jacinto Fault”
SH
EMC
LN
HM
Families with 3 < m < 4
Families with size L > 10
“San Jacinto Fault”
SH EMC
L N HM
Topological depth d > 6, mainshock m< 5
100 km from Superstition Hills, M6.6 of 1987
SH EMCL N HM
Salton Trough
Average leaf depth > 1, Family size > 5
SH EMCL N HM
Salton Trough
Baja California
Average leaf depth > 1, Family size > 5
Baja California
SH EMCL N HM
Average leaf depth > 1, Family size > 5
R < 5 km
R < 20 km
R < 100 km
R < 300 km
El Mayor Cucapah, M7.2
Topological depth d > 5
20 km from Landers, M7.3 of 1992
In this region: 613 mainshocks; 139 families; 11 mainshocks/10 families with m>3.5
Remote aftershock of Superstition Hill, M6.6 of 1987
Landers, M7.3 of 1992
Remote foreshock to Hector Mine, M7.1 of 1999
SH EMCL N HM
Seismic clusters in southern California1
2
3
1
2
3
Summary
o Four types of clusters:• Burst-like clusters• Swarm-like clusters• Singles• Largest regional clusters
o Topological cluster characterization
o Swarm-like clusters <-> decreased effective viscosityo Burst-like clusters <-> increased effective viscosity
Spatial variability: Relation to physical properties of the crust
Temporal variability: Relation to large events