Using thermal tracers to estimate flow velocities of shallow flows: laboratory and field experiments

Lima, Rui Leal Pedroso de; Abrantes, João R.C.B.; Lima, João L.M.P. de; Lima, M. Isabel P. de

doi:10.1515/johh-2015-0028

Cited by 27 publications

(18 citation statements)

References 19 publications

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“…infrared video camera). Thermal tracers were tested as instruments to measure flow velocities (Schuetz et al, 2012;de Lima and Abrantes, 2014b;de Lima et al, 2015;Bonner et al, 2017), as well as for assessing microrelief (Abrantes and de Lima, 2014; de Lima and Abrantes 2014a), permeability (de Lima et al, 2014b), macroporosity (de Lima et al, 2014a,c) and repellency of the soil surface (Abrantes et al, 2016(Abrantes et al, , 2017.…”

Section: Introductionmentioning

confidence: 99%

Comparison of thermal, salt and dye tracing to estimate shallow flow velocities: Novel triple-tracer approach

Abrantes

Moruzzi

Silveira

et al. 2018

Journal of Hydrology

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The accurate measurement of shallow flow velocities is crucial to understand and model the dynamics of sediment and pollutant transport by overland flow. In this study, a novel triple-tracer approach was used to re-evaluate and compare the traditional and well established dye and salt tracer techniques with the more recent thermal tracer technique in estimating shallow flow velocities. For this purpose a triple tracer (i.e. dyed-salted-heated water) was used. Optical and infrared video cameras and an electrical conductivity sensor were used to detect the tracers in the flow. Leading edge and centroid velocities of the tracers were measured and the correction factors used to determine the actual mean flow velocities from tracer measured velocities were compared and investigated. Experiments were carried out for different flow discharges (32-1813 ml s À1) on smooth acrylic, sand, stones and synthetic grass bed surfaces with 0.8, 4.4 and 13.2% slopes. The results showed that thermal tracers can be used to estimate shallow flow velocities, since the three techniques yielded very similar results without significant differences between them. The main advantages of the thermal tracer were that the movement of the tracer along the measuring section was more easily visible than it was in the real image videos and that it was possible to measure space-averaged flow velocities instead of only one velocity value, with the salt tracer. The correction factors used to determine the actual mean velocity of overland flow varied directly with Reynolds and Froude numbers, flow velocity and slope and inversely with flow depth and bed roughness. In shallow flows, velocity estimation using tracers entails considerable uncertainty and caution must be taken with these measurements, especially in field studies where these variables vary appreciably in space and time.

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Section: Introductionmentioning

confidence: 99%

Comparison of thermal, salt and dye tracing to estimate shallow flow velocities: Novel triple-tracer approach

Abrantes

Moruzzi

Silveira

et al. 2018

Journal of Hydrology

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“…Tracking reliability is much lower in these textureless regions. Note that reliability of thermal image‐based flow velocity measurement is influenced by the amount and location of the inserted hot water (Lima et al, ). For example, velocity results at M7 could not be retrieved during image sequence 2, because the location of the hot water insertion was too far away from the measurement area, which lead to missing textures.…”

Section: Resultsmentioning

confidence: 99%

“…A comparison of our results with previously published work is conducted, focusing on the utilization of thermal data. Lima et al (2015) observed that standard deviation values vary between 0.004 and 0.018 m/s for velocities between 0.08 and 0.2 m/s using the method of leading edge estimation in laboratory experiments with an acoustic Doppler velocimeter as reference device. Thus, the coefficient of variation, which is defined by the ratio of standard deviation to mean, fluctuates from 5% to 9%.…”

Section: 1029/2018wr024507mentioning

confidence: 99%

“…Schuetz et al () took advantage of injected heated water as an artificial tracer in thermal imagery to describe the spatial distribution of flow paths in an experimentally constructed wetland. Lima and Abrantes () used heated dye to measure the velocities of overland and rill flow using leading edge estimation in laboratory setups and then extended their technique to field experiments (Lima et al, ). In contrast, Tauro and Grimaldi () utilized cold temperature signatures with ice dice as thermal tracers in combination with cross‐correlation algorithm to monitor the flow velocity of a stream.…”

Section: Introductionmentioning

confidence: 99%

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Evaluating Image Tracking Approaches for Surface Velocimetry With Thermal Tracers

Lin

Grundmann

Eltner

2019

Water Resources Research

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In this paper an automatic approach is proposed to measure flow velocity with an uncooled thermal camera. Hot water is used as thermal tracer. The introduced tracking algorithm utilizes the pyramidal Lucas‐Kanade method and is especially suitable for thermal image data. The performance of the new tool is compared to traditional image‐based tracking tools, that is, PIVlab and PTVlab. Experiments are performed in the laboratory for three different flow velocities and tests are conducted in a small stream to illustrate the suitability of the tool for field measurements. Results of the laboratory experiments as well as of the field experiments show that our tracking algorithm, applied to imagery from a thermal camera, outperforms commonly used tracking methods. Our tool provides velocity fields with very high resolution and is in close agreement with reference measurements, whereas PTVlab and PIVlab tend to overestimate and underestimate flow velocities, respectively.

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“…There are many low-cost options of high-resolution optical cameras that can observe up to hundreds of square kilometres (Aschenwald, Leichter, Tasser, & Tappeiner, 2001;Salvatori et al, 2011). Thermal cameras of similar resolution are usually significantly more expensive, and they are commonly used for smaller areas of a few square metres (de Lima, Abrantes, de Lima, & de Lima, 2015;de Lima, Abrantes, Silva, de Lima, & Montenegro, 2014;Röper, Greskowiak, & Massmann, 2014) when used in a terrestrial mode.…”

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confidence: 99%

Potential of time‐lapse photography for identifying saturation area dynamics on agricultural hillslopes

Silasari

Parajka

Ressl

et al. 2017

Hydrological Processes

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Mapping saturation areas during rainfall events is important for understanding the dynamics of overland flow. In this study, we evaluate the potential of high temporal resolution time‐lapse photography for mapping the dynamics of saturation areas (i.e., areas where water is visually ponding on the surface) on the hillslope scale during natural rainfall. We take 1 image per minute over a 100 × 15 m2 depression area on an agricultural field in the Hydrological Open Air Laboratory, Austria. The images are georectified and classified by an automated procedure, using grey intensity as a threshold to identify saturation area. The optimum threshold T is obtained by comparing saturation areas from the automated analysis with the manual analysis of 149 images. T is found to be highly correlated with an image brightness characteristic defined as the greyscale image histogram mode M (Pearson correlation r = 0.91). We estimate T as T = M + C where C is a calibration parameter assumed to be constant during each event. The automated procedure estimates the total saturation area close to the manual analysis with mean normalized root mean square error of 9% and 21% if C is calibrated for each event and taken constant for all events, respectively. The spatial patterns of saturation are estimated with a geometric mean accuracy index of 94% as compared to the manual analysis of the same photos. The patterns are tested against field observations for one date as a preliminary demonstration, which yields a root mean square error of the shortest distance between the measured boundary points and the automatically classified boundary as 23 cm. The usefulness of the patterns is illustrated by exploring run‐off generation processes of an example event. Overall, the proposed classification method based on grey intensity is found to process images with highly varying brightnesses well. It is more efficient than the manual tracing for a large number of images, which allows the exploration of surface flow processes at high temporal resolution.

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Using thermal tracers to estimate flow velocities of shallow flows: laboratory and field experiments

Cited by 27 publications

References 19 publications

Comparison of thermal, salt and dye tracing to estimate shallow flow velocities: Novel triple-tracer approach

Comparison of thermal, salt and dye tracing to estimate shallow flow velocities: Novel triple-tracer approach

Evaluating Image Tracking Approaches for Surface Velocimetry With Thermal Tracers

Potential of time‐lapse photography for identifying saturation area dynamics on agricultural hillslopes

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