Remote monitoring of volumetric discharge based on surface mean and turbulent metrics

Johnson, Erika; Cowen, Edwin A.

doi:10.1201/b17133-259

Cited by 4 publications

(9 citation statements)

References 2 publications

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“…If PTV is applied instead of PIV, then single tracer pathlines could be smoothed by de-spiking similar to the methodology of Goring & Nikora (2002), and spatial resolution could be refined as well. Once all these optimizations are fulfilled, volumetric discharge could be estimated via turbulence length scales without directly determining the actual water depth, as tested by Johnson & Cowen (2014) under laboratory conditions.…”

Section: Discussionmentioning

confidence: 99%

A low-cost airborne velocimetry system: proof of concept

Detert

Weitbrecht

2015

Journal of Hydraulic Research

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This Technical Note proves the applicability of a low-cost airborne velocimetry system to measure large-scale surface velocity fields. The measurement equipment consists of an ultra-light action-cam and a ready-to-fly low-cost quadrocopter. Video recordings were performed from heights between 45-74 m covering a total reach length of 310 m, while spruce chips were added as tracer particles. Each lens-corrected frame was automatically ortho-rectified to riparian ground reference points. The positional error of each point was computed to be within 0.17-0.39 m, so that the magnitude of the related descaling error was below ± 2%, and the error of apparent ground velocity is approximately 0.03 m s −1 . These values describe the uncertainty added to the subsequently calculated particle image velocity field. The final raster resolution was 1.0 × 1.0 m 2 with 50% overlap. A comparison with the velocity profiles measured by a 3D acoustic Doppler current profiler indicates that the proposed new type of velocimetry system is capable of measuring with relatively high accuracy.

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Section: Discussionmentioning

confidence: 99%

A low-cost airborne velocimetry system: proof of concept

Detert

Weitbrecht

2015

Journal of Hydraulic Research

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“…Understanding the mechanisms behind the apparently random nature of free surface fluctuations could unlock the potential to predict the free surface pattern for a given flow condition. Furthermore, the understanding of free surface dynamics may enable non-intrusive characterization of flow conditions and hydraulic energy losses based solely on measured free surface behaviour (Fujita, Furutani, & Okanishi, 2011;Horoshenkov, Nichols, Tait, & Maximov, 2013;Johnson & Cowen, 2014).…”

Section: Introductionmentioning

confidence: 99%

A model of the free surface dynamics of shallow turbulent flows

Nichols

Tait

Horoshenkov

et al. 2016

Journal of Hydraulic Research

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Understanding the dynamic free surface of geophysical flows has the potential to enable direct inference of the flow properties based on measurements of the free surface. An important step is to understand the inherent response of free surfaces in depth-limited flows. Here a model is presented to demonstrate that free surface oscillatory spatial correlation patterns result from individual surface features oscillating vertically as they advect over space and time. Comparison with laboratory observations shows that these oscillating surface features can be unambiguously explained by simple harmonic motion, whereby the oscillation frequency is controlled by the root-mean-square water surface fluctuation, and to a lesser extent the surface tension. This demonstrates that the observed "complex" wave pattern can be simply described as an ensemble of spatially and temporally distributed oscillons. Similarities between the oscillon frequency and estimated frequency of near-bed bursting events suggest that oscillon behaviour is linked with the creation of coherent flow structures.

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“…Johnson and Cowen [] also showed that the length scale normalized by the flow depth is linearly dependent on the turbulent Reynolds number (

R e_{T} = \frac{U L}{ν}

, where U is the current speed). The Hudson River data (cf.…”

Section: Discussionmentioning

confidence: 99%

“…They report the transverse and stream wise length scale as 0.5D and 2.5D, respectively for water depth ranging from 10 to 30 cm. Johnson and Cowen [2014] also showed that the length scale normalized by the flow depth is linearly dependent on the turbulent Reynolds number (Re T 5 UL m , where U is the current speed). The Hudson River data (cf.…”

Section: 1002/2015jc010746mentioning

confidence: 96%

Riverine skin temperature response to subsurface processes in low wind speeds

et al. 2016

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Both surface and subsurface processes modulate the surface thermal skin and as such the skin temperature may serve as an indicator for coastal, estuarine, and alluvial processes. Infrared (IR) imagery offers the unique tool to survey such systems, allowing not only to assess temperature variability of the thermal boundary layer, but also to derive surface flow fields through digital particle image velocimetry, optical flow techniques, or spectral methods. In this study, IR time‐series imagery taken from a boat moored in the Hudson River estuary is used to determine surface flow, turbulent kinetic energy dissipation rate, and characteristic temperature and velocity length scales. These are linked to subsurface measurements provided by in situ instruments. Under the low wind conditions and weak stratification, surface currents and dissipation rate are found to reflect subsurface mean flow (r2 = 0.89) and turbulence (r2 = 0.75). For relatively low dissipation rates, better correlations are obtained by computing dissipation rates directly from wavenumber spectra rather than when having to assume the validity of the Taylor hypothesis. Furthermore, the subsurface dissipation rate scales with the surface length scales (L) and mean flow (U) using ε ∝ U3L (r2 = 0.9). The surface length scale derived from the thermal fields is found to have a strong linear relationship (r2 = 0.88) to water depth (D) with (D/L) ∼ 13. Such a relation may prove useful for remote bathymetric surveys when no waves are present.

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Remote monitoring of volumetric discharge based on surface mean and turbulent metrics

Cited by 4 publications

References 2 publications

A low-cost airborne velocimetry system: proof of concept

A low-cost airborne velocimetry system: proof of concept

A model of the free surface dynamics of shallow turbulent flows

Riverine skin temperature response to subsurface processes in low wind speeds

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