ETH Swiss Federal Institute of Technology Zürich

Transcription

1 Swiss Federal Institute of Technology Zürich Earthquake Statistics using ZMAP Recent Results Danijel Schorlemmer, Stefan Wiemer Zürich, Swiss Seismological Service, Switzerland Contributions by: Matt Gerstenberger ( Zürich), Max Wyss (WAPMERR, Geneva)

2 Contents Part 1 Basics ZMAP b-values Catalogs and Quality Part 2 Applications Volcanoes Local Recurrence Time Hypothesis Seismicity Rate Changes Probabilistic Forecast of Earthquakes

3 ZMAP at a Glance Interactive data exploration - ZMAP is designed to help seismologists analyze catalog data - It combines many standard and advanced seismological analyses tools - Identify and evaluate spatial and temporal variations in seismicity Mapping seismicity parameters - Create dense spatial grids and sample overlapping volumes of circular (2D) or spherical shape (3D) - Catalog quality assessment (artifacts, completeness, explosion contamination) - Map various seismicity parameters such as seismicity rate changes, b-values, p-values, stress tensor orientations and the magnitude of completeness - Interactively view the source of seismicity parameter

4 ZMAP at a Glance Open Source - Written in the commercial software language of Matlab. - The ZMAP code is entirely open. - ZMAP runs on all platforms Matlab runs on (e. g. UNIX, LINUX, Windows and MAC OS).

5 b-values Frequency-Magnitude Distribution Frequency-Magnitude Distribution log(n) = a bm N: cumulative number M: magnitude Mc: magnitude of completeness a: productivity b: event size distribution

6 b-values Physics of b-values High b-value - low stress - high heterogeneity - high thermal gradient N magnitude of completeness mean magnitude Evidence from - laboratory studies - mines - numerical simulations - tectonic regimes N low b high b M

7 Quality of Earthquake Catalogs Quality Assessment - Rate changes due to recording quality - Explosion contamination - Completeness of reporting - Magnitude shifts Etc.

8 Quality Recording Quality Cumulative Number Detect rate changes due to recording quality changes 4 x 10 5 Cumulative Number INGV catalog Time in years 2010

9 Quality Explosion Contamination The daytime to nighttime ratio of events (Rq) mapped out over the study region can identify explosion contamination in earthquake catalogs. Explosions 12 Rq = 3 A 8 A 4 0 Normal B 20 B Rq = Hour of the day 20

10 Quality Mapping of Mc - Aid in optimizing seismic networks. - Define the study region and suitable magnitude range for seismicity and hazard related studies. B Mc A 100 B A

11 Quality Global Mc Global map of completeness in magnitude reporting, Mc, for the Harvard moment magnitude catalog ( ).

12 Contents Part 1 Basics ZMAP b-values Catalogs and Quality Part 2 Applications Volcanoes Local Recurrence Time Hypothesis Seismicity Rate Changes Probabilistic Forecast of Earthquakes

13 Volcanoes Mount St. Helens, Washington A

14 Volcanoes b-values b-value cross-section N S A 1 Catalog: Depth [km] 2 3 A A b ~ B B b ~ 1.5 B C C 1 2 C 100 b ~ D 1 b ~ Magnitude 8 9 D 1 2 Distance [km]

15 Volcanoes 3D b-value Mapping Mount St. Helens dimensional analysis of the frequency-magnitude distribution b-value

16 Volcanoes Mount Etna Studied by M. Murru, C. Montuori, M. Wyss and E. Privitera Evidence for a deep magma reservoir 2 km east of the summit at 10 3 km

17 Volcanoes Subduction Tohoku area, Japan Cross-sections: - AB used for b-value mapping (Catalog from ) - CD for seismic tomography C A D B

18 Volcanoes Subduction Volumes with a velocity slower than 2% are shown in gray Open arrows: Flow direction in the mantle wedge Red arrows: Flow in ascending plume A B C D

19 Volcanoes Conclusions - Volcanic regions do not simply show a high b-value, but contain pockets of high b embedded in an average background. - High b-value anomalies correlate with the location of the main magma reservoir and the depth of vesiculation at Mount St. Helens. - b-value tomography is a powerful new technique to study volcanic systems. - The b-value in volcanic areas varies spatially from b ~ 0.6 to b > 2. - Near a seismically active magma chamber b is found to be always high (b > 1.5). - High b-values in subduction zones indicate the location of dehydration of the slab

20 Local Recurrence Time Hypothesis Assumption: TL(M) = dt/10 (a-bm) Observation 1: a varies strongly on a scale of few km. Observation 2: b varies strongly on a scale of few km (0.5<b<2). Conclusion 1: TL varies strongly on a scale of few km (20<TL<100,000 years). Conclusion 2: Bulk estimates of Tr may be inaccurate. Hypothesis Minima in local recurrence time map asperities.

21 Local Recurrence Time Model A new recurrence time model Cumulative Number Gutenberg-Richter model? Characteristic earthquake model? (Wesnousky 1994) Asperity b-value model? Data Extrapolation b~1 b ~ Magnitude Ma Mmax

22 Local Recurrence Time Study Area SF LA San Jacinto-Elsinore fault zones

23 Local Recurrence Time Results San Jacinto Fault Zone Elsinore Fault Zone San Jacinto Temescal Valley Buck Ridge Anza Salada Wash Vallecito Mountain Catalog Earthquake Valley

24 Local Recurrence Time Conclusion Minima in local recurrence times map asperities Why are recurrence time estimates based on the GutenbergRichter power law too long? (A) Asperities under high stress with a low b-value (B) Surrounding volumes that have a much higher b-value 100 Cumulative Number Because different populations are mixed: A b ~ 0.5 B 10 b ~ Magnitude 5

25 Seismicity Rate Changes Landers 1992 event significantly changed seismicity in surrounding regions In 1999, the Hector Mine main shock occurred north of Landers Can seismicity rate changes and changes in b-values indicate changes in probability of future earthquake occurrence?

26 Seismicity Rate Changes z-value Seismicity z-value Hector Mine Landers Rate decrease Big Bear Before Landers After Landers Aftershocks Before/After Landers Rate increase

27 Seismicity Rate Changes b-value Changes in b-values Locked patch Stress release

28 Seismicity Rate Changes Probability Changes Hector Mine occurred in the area near the highest increases in earthquake probability. Hector Mine Log Probability increase (M5+) Log Probability decrease

29 Probabilistic Forecast of Earthquakes Hypothesis Probabilistic forecast of earthquakes using spatially variable bvalues (as well as a-values) significantly improves the forecast accuracy. Null hypothesis Model with spatially variable productivities (a-values) but constant b-value equal to the overall b-value. Successful testing would have considerable implications for earthquake hazard assessment.

30 Probabilistic Forecast Study Area Parkfield segment of the San Andreas Fault - Asperity and creeping segment (high b-value contrast) - Best monitored seismic volume - Many studies have been performed SF Parkfield LA

31 Probabilistic Forecast Stationary b-values 1966 Rupture Cumulative Number NW 103 SE Asperity Magnitude Magnitude Magnitude Creeping Part

32 Probabilistic Forecast Quality Assessment Assessment - Calculate the likelihoods of every single magnitude bin - Sum of all log-likelihoods Model 1-2 Model 2-4 Log-likelihood - Poissonian distribution Number Assumption Magnitude 6 7

33 Probabilistic Forecast Results Splitting Time: 1991 Radius: 5km Min. Number: 50 Splitting Time Minimum Number Radius km km km 100

34 Probabilistic Forecast Conclusions Conclusions - We can reject the null hypothesis at a significance level <0.01%. - Using spatially variable b-values significantly improves probabilistic forecasts of earthquakes in the Parkfield region. In Progress - We are extending this test to all of California - We plan to implement a real-time hypothesis test.

35 ZMAP Conclusions - Most useful for exploring seismicity data in an interactive way - Bad data as input Bad results - About 100 users worldwide, about 50 publications based on ZMAP analysis.

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