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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:contributor>David J. Wald</dc:contributor>
  <dc:contributor>Charles Worden</dc:contributor>
  <dc:creator>Eric Thompson</dc:creator>
  <dc:date>2014</dc:date>
  <dc:description>&lt;p&gt;&lt;span&gt;For many earthquake engineering applications, site response is estimated through empirical correlations with the time‐averaged shear‐wave velocity to 30&amp;nbsp;m depth (&lt;/span&gt;&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;&lt;i&gt;S&lt;/i&gt;30&lt;/sub&gt;&lt;span&gt;). These applications therefore depend on the availability of either site‐specific&amp;nbsp;&lt;/span&gt;&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;&lt;i&gt;S&lt;/i&gt;30&lt;/sub&gt;&lt;span&gt;&amp;nbsp;measurements or&amp;nbsp;&lt;/span&gt;&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;&lt;i&gt;S&lt;/i&gt;30&lt;/sub&gt;&lt;span&gt;&amp;nbsp;maps at local, regional, and global scales. Because&amp;nbsp;&lt;/span&gt;&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;&lt;i&gt;S&lt;/i&gt;30&lt;/sub&gt;&lt;span&gt;&amp;nbsp;measurements are sparse, a proxy frequently is needed to estimate&amp;nbsp;&lt;/span&gt;&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;&lt;i&gt;S&lt;/i&gt;30&lt;/sub&gt;&lt;span&gt;&amp;nbsp;at unsampled locations. We present a new&amp;nbsp;&lt;/span&gt;&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;&lt;i&gt;S&lt;/i&gt;30&lt;/sub&gt;&lt;span&gt;&amp;nbsp;map for California, which accounts for observational constraints from multiple sources and spatial scales, such as geology, topography, and site‐specific&amp;nbsp;&lt;/span&gt;&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;&lt;i&gt;S&lt;/i&gt;30&lt;/sub&gt;&lt;span&gt;measurements. We apply the geostatistical approach of regression kriging (RK) to combine these constraints for predicting&amp;nbsp;&lt;/span&gt;&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;&lt;i&gt;S&lt;/i&gt;30&lt;/sub&gt;&lt;span&gt;. For the&amp;nbsp;&lt;/span&gt;&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;&lt;i&gt;S&lt;/i&gt;30&lt;/sub&gt;&lt;span&gt;&amp;nbsp;trend, we start with geology‐based&amp;nbsp;&lt;/span&gt;&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;&lt;i&gt;S&lt;/i&gt;30&lt;/sub&gt;&lt;span&gt;&amp;nbsp;values and identify two distinct trends between topographic gradient and the residuals from the geology&amp;nbsp;&lt;/span&gt;&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;&lt;i&gt;S&lt;/i&gt;30&lt;/sub&gt;&lt;span&gt;&amp;nbsp;model. One trend applies to deep and fine Quaternary alluvium, whereas the second trend is slightly stronger and applies to Pleistocene sedimentary units. The RK framework ensures that the resulting map of California is locally refined to reflect the rapidly expanding database of&amp;nbsp;&lt;/span&gt;&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;&lt;i&gt;S&lt;/i&gt;30&lt;/sub&gt;&lt;span&gt;&amp;nbsp;measurements throughout California. We compare the accuracy of the new mapping method to a previously developed map of&amp;nbsp;&lt;/span&gt;&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;&lt;i&gt;S&lt;/i&gt;30&lt;/sub&gt;&lt;span&gt;&amp;nbsp;for California. We also illustrate the sensitivity of ground motions to the new&amp;nbsp;&lt;/span&gt;&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;&lt;i&gt;S&lt;/i&gt;30&lt;/sub&gt;&lt;span&gt;&amp;nbsp;map by comparing real and scenario ShakeMaps with&amp;nbsp;&lt;/span&gt;&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;&lt;i&gt;S&lt;/i&gt;30&lt;/sub&gt;&lt;span&gt;&amp;nbsp;values from our new map to those for existing&lt;/span&gt;&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;&lt;i&gt;S&lt;/i&gt;30&lt;/sub&gt;&lt;span&gt;&amp;nbsp;maps.&lt;/span&gt;&lt;/p&gt;</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>10.1785/0120130312</dc:identifier>
  <dc:language>en</dc:language>
  <dc:publisher>Seismological Society of America</dc:publisher>
  <dc:title>A V&lt;sub&gt;S30&lt;/sub&gt; map for California with geologic and topographic constraints</dc:title>
  <dc:type>article</dc:type>
</oai_dc:dc>