- Ground-motion model is [based on base model of Abrahamson and Silva (1997, 2008)]: where Y is in cm∕s2, a1 = 8.92418, a2 = -0.513, a3 = -0.695, a4 = -0.18555, a5 = -1.25594,
a6 = 0.18105, a7 = 7.33617, a8 = -0.02125, a9 = 0.01851, σ = 0.6527 (intra-event), τ = 0.5163
(inter-event) and σTot = = 0.8322 and blin = -0.36, b1 = -0.64 and b2 = -0.14 [taken from
Boore and Atkinson (2008)]. Fix c1 = 6.5. pga4nl is predicted PGA in g for V s,30 = 760m∕s. See Boore
and Atkinson (2008) for bnl, c and d [not repeated by Akkar and Çağnan (2010)].
- Characterise sites using V s,30 and use the site response terms of Boore and Atkinson (2008) because of
their simplicity and fairly good performance for data (demonstrated by intra-event residual plots and their
distributions that do not show clear trends, except perhaps for V s,30 > 720m∕s). Majority of records from
NEHRP C (360 ≤ V s,30 ≤ 760m∕s) and D (180 ≤ V s,30 < 360m∕s) sites with very few from sites with
V S30 ≥ 760m∕s. All sites have measured V s,30 values.
- Use three faulting mechanisms:
- FN = 1, FR = 0. 28% of records.
- FN = 0, FR = 0. 70% of records.
- FN = 0, FR = 1. 2% of records.
- Focal depths between about 0 and 50km with most between 5 and 20km.
- Use data from the recently compiled Turkish strong-motion database (Akkar et al., 2010), for which the
independent parameters were carefully reassessed.
- Note that there are many singly-recorded earthquakes.
- Vast majority of data from Mw < 6 and rjb > 10km.
- Explore several functional forms (not shown). Try to keep balance between rigorous model (for meaningful
and reliable estimations) and a robust expression (for wider implementation in engineering applications).
- Data from 102 mainshocks (346 records) and 35 aftershocks (88 records).
- Bandpass filter records using method of Akkar and Bommer (2006).
- Compare PGAs from unfiltered and filter records and find negligible differences.
- Note that aim of study is not to promote the use of poorly-constrained local models.
- Use pure error analysis (Douglas and Smit, 2001) to investigate magnitude-dependence of σ. Find strong
dependence of results on binning strategy (including some bins that suggest increase in σ with magnitude)
and, therefore, disregard magnitude dependency.
- Derive GMPEs using data with minimum thresholds of Mw3.5, Mw4.0, Mw4.5 and Mw5.0 to study
influence of small-magnitude data on predictions. Find that equation using Mw5.0 threshold overestimates
PGAs derived using lower thresholds; however, ranking of predictions from GMPEs using thresholds of
Mw3.5, Mw4.0 and Mw4.5 is not systematic.
- Note that due to limited records from reverse-faulting earthquakes, the coefficient a9 needs refining using
- Examine inter-event residuals for PGA, 0.2s and 1s w.r.t. Mw and intra-event residuals w.r.t. rjb and
V s,30. Fit straight lines to residuals and also compute bias over ranges of independent variables. Test
significance of trends at 5% level. Find no significant bias w.r.t. Mw nor w.r.t. rjb. For V s,30 for 1s find
significant overestimation for V s,30 > 450m∕s, which relate to linear site term. Suggest linear site term
needs adjustment using Turkish data.
- Compute inter-station residuals and identify 9 outlier stations, which are those with residuals mainly
outside range generally observed.
- Examine bias of residuals for mainshock and aftershock records. Find weak evidence for overestimation of
aftershock motions but this is not significant at the 5% level.
- Combine Turkish and Italian data from ITACA (1004 records) and derive GMPEs using same functional
form, except using site classes rather than V s,30 directly, to test observed differences between local and
- Compare focal depth distributions, using histograms with intervals of 5km, of the datasets for various
GMPEs. Compute mean and standard deviations of Mw for each depth bin. Find that records from Turkey
and Italian are on average deeper than those for other GMPEs, which seems to explain lower observed
motions. Conclude that focal depth can be important in explaining regional differences.