Block Models, Cluster Analysis and Space Geodetic Data Needs to Better Estimate Fault Slip and Intra-Block Strain Rates in South

Block Models, Cluster Analysis and! Space Geodetic Data Needs to Better Estimate ! Fault Slip and Intra-block Strain Rates in Southern California" Wayne Thatcher, Bob Simpson and Jim Savage U.S. Geological Survey, Menlo Park California

Assumed California GPS Block Geometry (Parsons, Johnson et al, 2012)

Block Geometry Derived from Mojave GPS Cluster Analysis 30 (Savage & Simpson, JGR, in review, 2012 ) 33 32

27 31

26 23 29

24 Central Walker Lane 20 SF 21 25

Bay Area 22 28

17 18 19

16 15 13 11 12 14 34 E Mojave 10 9 8 Region 4 3

7 6 1 2 5

Legend 0 55 110 220 UCERF3_GPS stations UCERF3_Block_model_2011_06_29 Kilometers But GPS Velocity Field Alone Constrains Locaon of Major Acve Fault Boundaries

>1400 edited velocity vectors

Courtesy of T. Herring, MIT, to UCERF3 Schemac Illustraon of Cluster Analysis Method

Ve Cluster Analysis of GPS Vectors Idenﬁes Major Tectonic Elements of California

• No subjecve assumpon of block geometry • Simple, intuive analysis method • Major acve tectonic features delineated: - faults of San Andreas system - Mojave Desert faults - Sierra Nevada-Great Valley microplate - Western boundary of Basin & Range - Cascadia subducon zone boundary Cluster Analysis with Four GPS Clusters Determined Four San Francisco Bay Area Blocks Clearly Idenﬁed Solely by Cluster Analysis

See Graymer & Simpson G23B-931 Poster This Aernoon Simpson, Thatcher & Savage GRL, 2012 Cluster Analysis Applied to Mojave Desert GPS with UCERF3 Block Boundaries (Grey Lines) & GPS Sites (Dots)

Savage & Simpson, 2012, JGR, submied 5 Stascally Signiﬁcant Clusters are Spaally Coherent

Main Features Map of 5 Clusters

• Cluster Distribuon Similar to UCERF3 Block Geometry

• However, Some Diﬀerences too

• Garlock Fault Not “Seen” by Cluster Analysis

• Existence of Smaller Blocks Not Precluded by Cluster Analysis

• Large Block Rotaon in NEMD Does Not Contaminate Analysis

Savage & Simpson, 2012 JGR, submied Data Needs for Beer Modeling of Steady-State Surface Velocity Field in Southern California

• Beer Precision in GPS Velocies Everywhere (e.g. Beer Deﬁne Clusters in Cluster Analysis)

• Beer Spaal Density for Measuring Intra-Block Strain (InSAR?, Sandwell, pers. comm. 2013) (More GPS sites too!) ADVANTAGES OF CLUSTER ANALYSIS

Oﬀers simple, visual, ﬁrst-step reconnaissance to organize GPS velocies

Provides an objecve method for idenfying major block boundaries

Works best where Euler poles are distant and blocks ~translate

Stascal tests of block-like behavior of clusters build conﬁdence in results

Fault slip rates esmated by diﬀerence in mean velocity between adjacent clusters

Applicaon to other regional GPS data & including block rotaons now underway

LIMITATIONS

Only a relavely small number of stascally signiﬁcant clusters, typically 5 or less

Even random data can appear clustered, so use method with appropriate cauon!

Smaller blocks not precluded & cannot yet be conﬁdently idenﬁed by cluster analysis

GPS precision & spaal density limit cluster resoluon & can cause spurious clusters

Large rotaons of blocks with nearby Euler poles may contaminate analysis

Other space geodec data (e.g. InSAR) not yet incorporated into method

San Francisco Bay Area Velocity Field

Simpson, Thatcher & Savage GRL, 2012 San Francisco Bay Area Velocity Field

12 mm/yr

50 mm/yr

Simpson, Thatcher & Savage GRL, 2012 Analysis with 5 Stascally Signiﬁcant Clusters

Velocity Field Map

Velocity Proﬁles N31˚W & N59˚E

Savage & Simpson, 2012 JGR, submied Cluster Analysis Applied to Central Walker Lane GPS with UCERF3 Block Boundaries (Grey Lines)

UNR MAGNET GPS Net

Savage & Simpson, 2012, in prep. Analysis with 4 Stascally Signiﬁcant Clusters

Velocity Field Map

Velocity Proﬁles N35˚W & N55˚E

Savage & Simpson, 2012, in prep.