<?xml version='1.0' encoding='utf-8'?>
<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>Lee Slater</dc:contributor>
  <dc:contributor>Frederick D. Day-Lewis</dc:contributor>
  <dc:contributor>Mehrez Elwaseif</dc:contributor>
  <dc:contributor>Carole D. Johnson</dc:contributor>
  <dc:creator>Kisa Mwakanyamale</dc:creator>
  <dc:date>2012</dc:date>
  <dc:description>Characterization of groundwater-surface water exchange is essential for improving understanding of contaminant transport between aquifers and rivers. Fiber-optic distributed temperature sensing (FODTS) provides rich spatiotemporal datasets for quantitative and qualitative analysis of groundwater-surface water exchange. We demonstrate how time-frequency analysis of FODTS and synchronous river stage time series from the Columbia River adjacent to the Hanford 300-Area, Richland, Washington, provides spatial information on the strength of stage-driven exchange of uranium contaminated groundwater in response to subsurface heterogeneity. Although used in previous studies, the stage-temperature correlation coefficient proved an unreliable indicator of the stage-driven forcing on groundwater discharge in the presence of other factors influencing river water temperature. In contrast, S-transform analysis of the stage and FODTS data definitively identifies the spatial distribution of discharge zones and provided information on the dominant forcing periods (≥2 d) of the complex dam operations driving stage fluctuations and hence groundwater-surface water exchange at the 300-Area.</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>10.1029/2011GL050824</dc:identifier>
  <dc:language>en</dc:language>
  <dc:publisher>Wiley</dc:publisher>
  <dc:title>Spatially variable stage-driven groundwater-surface water interaction inferred from time-frequency analysis of distributed temperature sensing data</dc:title>
  <dc:type>article</dc:type>
</oai_dc:dc>