- Ground-motion model is: where Y 1 is in cm∕s2, e1 = 0.210, e2 = 3.220, e3 = 0.036, c1 = -2.840, c2 = -0.361, c3 = 0.021,
hA = 13.452 and σt = 0.968 (total)for basic Phase 1 model; b1 = -2.558, b2 = 0.912, b3 = 0.952 and
σt = 0.896 for directivity model; a1 = -0.538, a2 = 0.130, a3 = 0.957 and σ = 0.852 for borehole damping
and fault zone amplification model; e1 = -6.822, e2 = 2.549, e3 = -0.121, c1 = -0.953, c2 = -0.138,
c3 = -0.013, d1 = 0.892, hA = 3.547 and σt = 0.924 for Phase 2 model; e1 = -7.532, e2 = 2.557,
e3 = -0.105, c1 = -1.121, c2 = -0.142, c3 = -0.008, d1 = 1.308, hA = 3.749 and σt = 0.985 for Phase
2 model using only stations in direction of rupture. In Phase 2 models model for Y 1 has additional term
- Select data from events in 45 × 125km2 rectangular area around the San Jacinto fault zone, a strike-slip
fault system, from 02/2010 to 05/2012 plus data from 3 moderate events: 03/2013 (ML5.1), 07/2010
(ML5.9) and 06/2005 (ML5.6), and their aftershocks.
- Data from 140 stations, including broadband instruments, from various networks within 90 × 275km
rectangle around fault zone. Broadband data converted to acceleration. Bandpass filter data using 1–30Hz
4th-order Butterworth filter. Prefer accelerometric data for M > 3 (to avoid saturation) and velocimetric
data for M < 3 (because of higher sensivity). Pick ground-motion parameters automatically using
signal-to-noise ratio algorithm.
- Derive two sets of models: Phase 1 (using data up to 05/2012, about 20000 records) and Phase 2 (including
03/2013 earthquake sequence).
- Focal depths between about 0 and 25km with peak between 5 and 20km.
- Vast majority of data from ML < 3.5 (only a handful of events have higher magnitudes).
- Find using repi and hA rather than rhypo results in slightly smaller σ.
- Derive series of models starting from one including only M and r and then adding site, directivity and
fault-zone amplification terms. Examine reduction in σ and residuals as additional terms added.
- Because of lack of V s,30 measurements for stations use various geological and topographical methods to
estimate V s,30. Find none of these approaches leads to significant reduction in σ. Hence neglect this factor.
- Find strong indication in residuals and reduction in σ of fault zone amplification (characterised by distance
normal to fault, D).
- Find strong impact of directivity (characterised by index, IDir) in residuals and reduction in σ.
- Derive final model by adding directivity and then fault zone amplification to basic model.
- Classify stations into: amplifiers, dampers, and good-fit, based on their average residuals within magnitude
bins. Examine residuals geographically and find amplifiers are often close to fault and dampers are often
in boreholes or posthole sites buried ≥ 10m below surface.
- Initial regression of Phase 2 dataset did not converge. Attempt various regressions of subsets and obtain
large σs. Conclude that additional directivity factor needs to be included in basic model.
- In Phase 2 exclude data from repi > 80km for M < 3, repi > 100km for 3 ≤ M < 5 and repi > 150km for
M ≥ 5 to decrease weight of small events at large distances.
- Examine σ for various subsets of Phase 1 and 2 data (e.g. only mainshocks or specific sequences).
- Examine geographical distribution of variance of total residuals per event binned into various magnitude
ranges. Find very high variances for 03/2013 dataset, which relate to combination of source characteristics
and new fault-zone stations.