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SEO NFOUR Seismic Nuard Inputs <br /> and seismogenic of 1.0 (Table 1). Exceptions include faults that may be secondary and <br /> dependent on other faults (e.g., the unnamed faults near Leadville and the unnamed faults in <br /> Williams Fork Valley), faults or fault features that may have a non-seismogenic origin (e.g., <br /> unnamed faults near Burns), and faults that may be too short (_< 10 km) to independently <br /> generate significant earthquakes (e.g., unnamed faults in Granby basin). The probability of <br /> activity for faults that do not show evidence for repeated Quaternary activity was individually <br /> judged based on the available data and the criteria explained above. The probability of activity <br /> values range from 0.2 to 1.0(Table 1). <br /> All of the faults are assumed to be dominantly normal-slip faults, although some show <br /> components of oblique or possible reverse slip. All faults are modeled as single, independent, <br /> planar sources extending the full extent of the seismogenic crust, with the exception of the <br /> unnamed faults in Granby basin and unnamed faults near Leadville (Table 1). These faults are <br /> modeled as zones with multiple parallel planes within defined zone boundaries. Additionally, <br /> due to their proximities to the sites, we used a curvilinear surface model for the WFMF and <br /> Mosquito fault in the analyses. This better represents their curved geometry and results in more <br /> accurate calculations of distances. To model the curvilinear nature of normal faults,we digitized <br /> the primary, most active fault trace and projected these curves down-dip using a weighted mean <br /> strike. This method eliminates the overlap created at concavities and fills. The gaps created at <br /> convexities when creating the down-dip projection. It results in a smoothed curvilinear surface <br /> that generally mimics the trend of the fault trace. Our model assumes constant dip with depth <br /> and listric geometries are not considered. <br /> Based on an analysis of Front Range seismicity(Bolt et al.,2003),we model the thickness of the <br /> seismogenic crust as 20 t 5 km with the best estimate given a weight of 0.6 and 0.2 weight given <br /> to the one sigma values. Fault dips are assumed averages throughout the entire seismogenic <br /> crust. Dips range from 35'to 90'(Table 1)and are based on available data and consideration of <br /> the relationship of the faults to other structures(e.g. intrabasin faults are generally assumed to be <br /> steeper). However, subsurface data is generally lacking and so default dips of 50' ±15' were <br /> assumed for many range-bounding faults, including the WFMF (Table 1). This distribution is <br /> consistent with the dip inferred by Kellogg et al.(2011) of the WFMF in their cross section,and <br /> is the default distribution recommended by the Basin and Range Province Earthquake Working <br /> Group 11 to the USGS for use in the 2014 National Seismic Hazard Maps (Lund,2012;see Issue <br /> G4). It is noteworthy, however, that fault dips often appear steeper in the northern Rio Grande <br /> rift than typical faults in the rest of the Basin and Range Province, perhaps due to the complex <br /> geometries of reactivating older reverse faults that were active in the Laramide orogeny, and the <br /> Mosquito fault is a good example of this(Table 1). <br /> Preferred characteristic (or maximum) magnitudes (weighted 0.6) were estimated using two <br /> empirical relationships weighted equally: (1) Wells and Coppersmith (1994) for surface rupture <br /> length (SRL) and all types of faults; and (2) the "censored" relation of Stirling et al. (2002) for <br /> SRL. Although the Wells and Coppersmith (1994)relation is somewhat outdated (Sirling et al., <br /> 2012), it is well-established and based on a well-documented dataset. However, many <br /> paleoseismic studies of normal faults have noted a discrepancy between displacement-based <br /> magnitudes and SRL-based magnitudes from the Wells and Coppersmith (1994) relation (e.g., <br /> Olig et al., 1994; Mason, 1996; Carpenter, et al., 2012; DuRoss et al., 2015), with the latter <br /> being consistently lower. Unfortunately,displacement per event data is not available for most of <br /> the faults in this study. Therefore, we also used the Stirling et al.'s (2002) censored relation, <br /> '274MR.18N 11 <br />