Quantifying streambed deposition and scour from stream and hyporheic water temperature time series

Tonina, Daniele; Luce, Charles H.; Gariglio, Frank

doi:10.1002/2013wr014567

Cited by 29 publications

(45 citation statements)

References 27 publications

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“…If a smaller k e was assumed from literature values, modeled groundwater discharge would have underestimated true discharge velocity, particularly at the upper end of the range measured at the Quashnet River (3 m d −1 ).Fine‐scale streambed scour and deposition has traditionally been a difficult process to accurately evaluate automatically. When k e is measured based on deeper or nearby vertical temperature profiles, dynamic fluctuations in streambed thickness between two sensors can be estimated by rearranging the k e equation [ Tonina et al ., ]. This worked well at smaller‐flux Locations 2 and 21 (Figure ) where modeled scour compared well with point‐in‐time visual inspection.…”

Section: Discussionmentioning

confidence: 99%

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Combined use of thermal methods and seepage meters to efficiently locate, quantify, and monitor focused groundwater discharge to a sand‐bed stream

Rosenberry

Briggs

Delin

et al. 2016

Water Resources Research

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Quantifying flow of groundwater through streambeds often is difficult due to the complexity of aquifer‐scale heterogeneity combined with local‐scale hyporheic exchange. We used fiber‐optic distributed temperature sensing (FO‐DTS), seepage meters, and vertical temperature profiling to locate, quantify, and monitor areas of focused groundwater discharge in a geomorphically simple sand‐bed stream. This combined approach allowed us to rapidly focus efforts at locations where prodigious amounts of groundwater discharged to the Quashnet River on Cape Cod, Massachusetts, northeastern USA. FO‐DTS detected numerous anomalously cold reaches one to several m long that persisted over two summers. Seepage meters positioned upstream, within, and downstream of 7 anomalously cold reaches indicated that rapid groundwater discharge occurred precisely where the bed was cold; median upward seepage was nearly 5 times faster than seepage measured in streambed areas not identified as cold. Vertical temperature profilers deployed next to 8 seepage meters provided diurnal‐signal‐based seepage estimates that compared remarkably well with seepage‐meter values. Regression slope and R2 values both were near 1 for seepage ranging from 0.05 to 3.0 m d−1. Temperature‐based seepage model accuracy was improved with thermal diffusivity determined locally from diurnal signals. Similar calculations provided values for streambed sediment scour and deposition at subdaily resolution. Seepage was strongly heterogeneous even along a sand‐bed river that flows over a relatively uniform sand and fine‐gravel aquifer. FO‐DTS was an efficient method for detecting areas of rapid groundwater discharge, even in a strongly gaining river, that can then be quantified over time with inexpensive streambed thermal methods.

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Section: Discussionmentioning

confidence: 99%

“…If k e is known, a similar equation can be solved for Δ z between thermal sensors [ Luce et al ., ]. Therefore, under the assumption that the stream functions as a mixed thermal signal, if there is bed scour that exposes the upper sensor, the new streambed thickness above the lower (still buried) sensor can be determined [ Tonina et al ., ].…”

Section: Methodsmentioning

confidence: 99%

Combined use of thermal methods and seepage meters to efficiently locate, quantify, and monitor focused groundwater discharge to a sand‐bed stream

Rosenberry

Briggs

Delin

et al. 2016

Water Resources Research

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“…An area of recent discussion is the nonstationarity of signal filtering (the transfer functions) because of changes in the vertical flux, which is important to monitor over time (e.g., Rau et al, ). Bed scour and sediment transport are important geomorphological and ecological processes (e.g., Goode et al, ; Tonina et al, ), and these equations have been applied for monitoring such processes as well (Bray & Dunne, ; DeWeese et al, ; Luce et al, ; Sebök et al, ; Tonina et al, ). Such changes in the bed also induce nonstationarity in the transfer functions (Tonina et al, ).…”

Section: Discussionmentioning

confidence: 99%

“…Bed scour and sediment transport are important geomorphological and ecological processes (e.g., Goode et al, ; Tonina et al, ), and these equations have been applied for monitoring such processes as well (Bray & Dunne, ; DeWeese et al, ; Luce et al, ; Sebök et al, ; Tonina et al, ). Such changes in the bed also induce nonstationarity in the transfer functions (Tonina et al, ). Equation does not include terms with time derivatives of advective thermal velocity, diffusivity, or thickness, so flux changes and bed scour and deposition do not affect the solution, and the derivation is unaltered, even during such changes.…”

Section: Discussionmentioning

confidence: 99%

“…If changes are nearly linear over time, the average may seem to track well. However if the change in flux rate or elevation is sudden or nonlinear within the window span, there will be apparent “smearing” of flux and depth estimates across the window (e.g., DeWeese et al, ; Rau et al, ; Tonina et al, ). A concern noted for tracking bed scour is that such changes often occur as head in the river changes and fluid fluxes may shift simultaneously (Rau et al, 2015), furthermore nonsinusoidal, even sudden, surface temperature changes may accompany rapid hydrograph changes.…”

Section: Discussionmentioning

confidence: 99%

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Was That Assumption Necessary? Reconsidering Boundary Conditions for Analytical Solutions to Estimate Streambed Fluxes

Luce

Tonina

Applebee

et al. 2017

Water Resources Research

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Two common refrains about using the one‐dimensional advection diffusion equation to estimate fluid fluxes and thermal conductivity from temperature time series in streambeds are that the solution assumes that (1) the surface boundary condition is a sine wave or nearly so, and (2) there is no gradient in mean temperature with depth. Although the mathematical posing of the problem in the original solution to the problem might lead one to believe these constraints exist, the perception that they are a source of error is a fallacy. Here we develop a mathematical proof demonstrating the equivalence of the solution as developed based on an arbitrary (Fourier integral) surface temperature forcing when evaluated at a single given frequency versus that derived considering a single frequency from the beginning. The implication is that any single frequency can be used in the frequency‐domain solutions to estimate thermal diffusivity and 1‐D fluid flux in streambeds, even if the forcing has multiple frequencies. This means that diurnal variations with asymmetric shapes or gradients in the mean temperature with depth are not actually assumptions, and deviations from them should not cause errors in estimates. Given this clarification, we further explore the potential for using information at multiple frequencies to augment the information derived from time series of temperature.

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Assessing the accuracy of 1‐D analytical heat tracing for estimating near‐surface sediment thermal diffusivity and water flux under transient conditions

et al. 2015

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Amplitude decay and phase delay of oscillating temperature records measured at two vertical locations in near-surface sediments can be used to infer water fluxes, thermal diffusivity, and sediment scour/deposition. While methods that rely on the harmonics-based analytical heat transport solution assume a steady state water flux, many applications have reported transient fluxes but ignored the possible violation of this assumption in the method. Here we use natural heat tracing as an example to investigate the extent to which changes in the water flux, and associated temperature signal nonstationarity, can be separated from other influences. We systematically scrutinize the assumption of steady state flow in analytical heat tracing and test the capabilities of the method to detect the timing and magnitude of flux transients. A numerical model was used to synthesize the temperature response to different step and ramp changes in advective thermal velocity magnitude and direction for both a single-frequency and multifrequency temperature boundary. Time-variable temperature amplitude and phase information were extracted from the model output with different signal-processing methods. We show that a worst-case transient flux induces a temperature nonstationarity, the duration of which is less than 1 cycle for realistic sediment thermal diffusivities between 0.02 and 0.13 m 2 /d. However, common signal-processing methods introduce erroneous temporal spreading of advective thermal velocities and significant anomalies in thermal diffusivities or sensor spacing, which is used as an analogue for streambed scour/deposition. The most time-variant spectral filter can introduce errors of up to 57% in velocity and 33% in thermal diffusivity values with artifacts spanning ±2 days around the occurrence of rapid changes in flux. Further, our results show that analytical heat tracing is unable to accurately resolve highly time-variant fluxes and thermal diffusivities and does not allow for the inference of scour/depositional processes due to the limitations of signal processing in disentangling flux-related signal nonstationarities from those stemming from other sources. To prevent erroneous interpretations, hydrometric data should always be acquired in combination with temperature records.

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Quantifying streambed deposition and scour from stream and hyporheic water temperature time series

Cited by 29 publications

References 27 publications

Combined use of thermal methods and seepage meters to efficiently locate, quantify, and monitor focused groundwater discharge to a sand‐bed stream

Combined use of thermal methods and seepage meters to efficiently locate, quantify, and monitor focused groundwater discharge to a sand‐bed stream

Was That Assumption Necessary? Reconsidering Boundary Conditions for Analytical Solutions to Estimate Streambed Fluxes

Assessing the accuracy of 1‐D analytical heat tracing for estimating near‐surface sediment thermal diffusivity and water flux under transient conditions

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