2012
DOI: 10.1016/j.jhydrol.2012.07.006
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Observing temporal patterns of vertical flux through streambed sediments using time-series analysis of temperature records

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Cited by 65 publications
(77 citation statements)
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“…Therefore, inter‐seasonal changes in surface–subsurface exchange, driven by the relationship between stream stage and subsurface hydraulic gradients (Woessner, ) likely played a key role in governing T s differences among years. Similar hydrologic controls on T s have been observed at smaller temporal scales (Brown and Hannah, 2007), and our findings are supported with previous work showing seasonal variation of stream‐subsurface hydraulic gradients in response to hydrologic events (Sophocleous, ; Lautz, ). Indeed, the effect of surface–subsurface exchange has been the focus of recent studies demonstrating these exchanges are as important as atmospheric fluxes in governing T s patterns (Leach and Moore, ).…”
Section: Discussionmentioning
confidence: 98%
“…Therefore, inter‐seasonal changes in surface–subsurface exchange, driven by the relationship between stream stage and subsurface hydraulic gradients (Woessner, ) likely played a key role in governing T s differences among years. Similar hydrologic controls on T s have been observed at smaller temporal scales (Brown and Hannah, 2007), and our findings are supported with previous work showing seasonal variation of stream‐subsurface hydraulic gradients in response to hydrologic events (Sophocleous, ; Lautz, ). Indeed, the effect of surface–subsurface exchange has been the focus of recent studies demonstrating these exchanges are as important as atmospheric fluxes in governing T s patterns (Leach and Moore, ).…”
Section: Discussionmentioning
confidence: 98%
“…This pattern was most evident upstream and downstream of secondary riffles (Figures 3a and 3b), where shallow hyporheic flow paths are expected to start and end. This vertical pattern is not an artifact of the one-dimensional heat tracing method, which can measure the vertical component of oblique flow even under nonideal conditions [Lautz, 2010[Lautz, , 2012.…”
Section: Patterns Of Hyporheic Exchange Around Crossvanesmentioning
confidence: 92%
“…[, ], Molina‐Giraldo et al . [], and Lautz [] have modeled temporally variable streambed flux to evaluate spatiotemporal patterns in hyporheic heat transport. These models include dynamic harmonic regression to perform spectral decomposition of the heat signal or time series analysis to identify explicitly the time series signature of hyporheic temperature that is propagated by each frequency of temperature variation in the stream.…”
Section: Hyporheic Heat Transportmentioning
confidence: 99%