“…This phenomenon was earlier described for vertical groundwater flow [e.g. 4,16,35,38,42]. However, in these studies the objective was to determine percolation rates, given the porosity (which is the similar to 1 minus the fraction of rock clasts) of the medium.…”
Section: Storage Of Heat In the Rock Clastsmentioning
“…This phenomenon was earlier described for vertical groundwater flow [e.g. 4,16,35,38,42]. However, in these studies the objective was to determine percolation rates, given the porosity (which is the similar to 1 minus the fraction of rock clasts) of the medium.…”
Section: Storage Of Heat In the Rock Clastsmentioning
“…A comparison of V T with the propagation velocity of a conservative chemical tracer, V C , is possible by expanding as follows [ Blasch et al , 2007]: The propagation velocity of a conservative chemical tracer will thus exceed that of the temperature signal by a factor of about two, depending on the magnitude of the volumetric water content, θ. This has implications in tandem tracer analysis, as discussed below in section 8.…”
Section: Application Of Heat As a Tracer In Streambedsmentioning
confidence: 99%
“…[40] A comparison of V T with the propagation velocity of a conservative chemical tracer, V C , is possible by expanding equation (6) as follows [Blasch et al, 2007]:…”
[1] This work reviews the use of heat as a tracer of shallow groundwater movement and describes current temperature-based approaches for estimating streambed water exchanges. Four common hydrologic conditions in stream channels are graphically depicted with the expected underlying streambed thermal responses, and techniques are discussed for installing and monitoring temperature and stage equipment for a range of hydrological environments. These techniques are divided into direct-measurement techniques in streams and streambeds, groundwater techniques relying on traditional observation wells, and remote sensing and other large-scale advanced temperatureacquisition techniques. A review of relevant literature suggests researchers often graphically visualize temperature data to enhance conceptual models of heat and water flow in the near-stream environment and to determine site-specific approaches of data analysis. Common visualizations of stream and streambed temperature patterns include thermographs, temperature envelopes, and one-, two-, and three-dimensional temperature contour plots. Heat and water transport governing equations are presented for the case of transport in streambeds, followed by methods of streambed data analysis, including simple heat-pulse arrival time and heat-loss procedures, analytical and time series solutions, and heat and water transport simulation models. A series of applications of these methods are presented for a variety of stream settings ranging from arid to continental climates. Progressive successes to quantify both streambed fluxes and the spatial extent of streambeds indicate heat-tracing tools help define the streambed as a spatially distinct field (analogous to soil science), rather than simply the lower boundary in stream research or an amorphous zone beneath the stream channel.
“…To determine these fluxes, some researchers observed vertical subsurface temperature profiles, which, when coupled with a vertical advection-dispersion model gave flow rates and directions (Stallman, 1965;Lapham, 1989;Taniguchi and Sharma, 1990;Silliman et al, 1995;Constantz and Thomas, 1996;Constantz, 1998;Constantz et al, 2003;Becker et al, 2004;Niswonger et al, 2005;Blasch et al, 2007). However, these profiles were point measurements along the stream and obtained during steady state discharge conditions.…”
Abstract. Understanding the spatial distribution of discharge can be important for water quality and quantity modeling. Non-steady flood waves can, particularly as a result of short high intensity summer rainstorms, influence small headwater streams significantly. The aim of this paper is to quantify the spatial and temporal dynamics of stream flow in a headwater stream during a summer rainstorm. These dynamics include gains and losses of stream water, the effect of bypasses that become active and hyporheic exchange fluxes that may vary over time as a function of discharge. We use an advectiondispersion model coupled with an energy balance model to simulate in-stream water temperature, which we compare with high resolution temperature observations obtained with Distributed Temperature Sensing. This model was used as a learning tool to stepwise unravel the complex puzzle of instream processes subject to varying discharge. Hypotheses were tested and rejected, which led to more insight in the spatial and temporal dynamics in discharge and hyporheic exchange processes. We showed that, for the studied stream infiltration losses increase during a small rain event, while gains of water remained constant over time. We conclude that, eventually, part of the stream water bypassed the main channel during peak discharge. It also seems that hyporheic exchange varies with varying discharge in the first 250 m of the stream; while further downstream it remains constant. Because we relied on solar radiation as the main energy input, we were only able to apply this method during a small summer storm and low flow conditions. However, when additional (artificial) energy is available, the presented method is also applicable in larger streams, during higher flow conditions or longer storms.
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