2020
DOI: 10.1016/j.epsl.2020.116313
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Modeling repeated coseismic slip to identify and characterize individual earthquakes from geomorphic offsets on strike-slip faults

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Cited by 22 publications
(17 citation statements)
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“…The rupture ranges of different earthquakes are not necessarily the same; therefore, it is more reasonable to analyze each rupture segment individually [50][51][52]. The offset distribution of the four rupture segments falls into multiple separate clusters (Figure 8).…”
Section: Offset Distribution Andmentioning
confidence: 99%
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“…The rupture ranges of different earthquakes are not necessarily the same; therefore, it is more reasonable to analyze each rupture segment individually [50][51][52]. The offset distribution of the four rupture segments falls into multiple separate clusters (Figure 8).…”
Section: Offset Distribution Andmentioning
confidence: 99%
“…Recent studies have distinguished seismic events from dense offset data sets by calculating the COPD to identify clusters in the frequency distribution of seismic events, thereby revealing the rupture history and recurrence patterns of strong earthquakes and providing valuable information about the potential future behavior of faults [54,55]. Lin et al [52] concluded that the interpretation of paleoearthquake events by COPD should ensure the following three points: (1) original historical coseismic slip data are used; (2) the coefficient of variation (CoV) value is relatively low; (3) there are sufficient offset measurement data. In this study, the coseismic offset of the Fuyun fault caused by the 1931 earthquake is well recorded, the CoV value is used to evaluate the regularity of cumulative offsets, and the global historical coseismic surface rupture segments have an average CoV value of approximately 0.58 [52,56].…”
Section: Cumulative Offset and Coseismicmentioning
confidence: 99%
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“…However, even with these sampling distributions informed by field measurements, the ordering of events is not necessarily predicted by CV of sampling distributions, nor of individual paths, alone (Figures 7a and 8a). Previous compilations of single event displacement suggest that single-event displacement is less variable than recurrence interval with a global CV of ∼0.5-0.6 (e.g., Hecker et al, 2013;Lin et al, 2020;Nicol et al, 2016), but understanding these relationships through time can prove challenging with poorer and less certain recovery of per-event displacement for older and older events. With more detailed and longer records of both recurrence and single-event displacement collected along faults and within fault systems, a potential relationship may emerge to aid in understanding the true independence of recurrence and single-event displacement through time (e.g., Shimazaki & Nakata, 1980;Weldon et al, 2004).…”
Section: Implications For Geologistsmentioning
confidence: 99%
“…Single event displacement and recurrence interval distribution constraints for Wallace Creek are derived from field studies at the Bidart Fan, <10 km to the southeast. Ludwig et al (2010) showed 15.9 m of offset accrued in the last five earthquakes at the nearby Bidart Fan site, producing a mean displacement of 3.2 m. Using this mean value, we construct a Gaussian distribution with a mean of 3.2 m and standard deviation of 1.9 m (CV of SED distribution ∼0.6; Hecker et al, 2013;Lin et al, 2020;Nicol et al, 2016) evaluated over 0.1 and 10 m. Truncating the distribution to prevent negative SED values induces a right-hand skew to the distribution while honoring the field observations incorporated in the pre-truncated parameterization of the SED distribution. Therefore, the SED sampling distribution mean and standard deviation are adjusted prior to truncation to maintain a mean of 3.2 m in the SED sampling distribution after truncation (CV of final distribution remains ∼0.6).…”
Section: San Andreas Fault Datamentioning
confidence: 99%