Using sound pressure to estimate reaeration in streams

Morse, Nathaniel B.; Bowden, William B.; Hackman, Alexander M.; Pruden, Celia; Steiner, Erin; Berger, Elliott H.

doi:10.1899/0887-3593(2007)26[28:uspter]2.0.co;2

Cited by 34 publications

(27 citation statements)

References 33 publications

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“…Genereux and Hemond, 1992;Wallin et al, 2011). The alternative use of sound in streams with standing broken waves (Morse et al, 2007) is ingenious as it relates perhaps better to stream turbulence at the airewater interface. Direct continuous measurements of turbulence at the watereair interface for gas transfer studies are at the core of several recent studies (e.g.…”

Section: Theoretical Versus Empirical Equations and Direct Measuremenmentioning

confidence: 99%

Temperature dependence of stream aeration coefficients and the effect of water turbulence: A critical review

Demars

Manson

2013

Water Research

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Section: Theoretical Versus Empirical Equations and Direct Measuremenmentioning

confidence: 99%

Temperature dependence of stream aeration coefficients and the effect of water turbulence: A critical review

Demars

Manson

2013

Water Research

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“…Underwater acoustic recordings have also been used for estimating sediment transport (Rouse 1994;Rickenmann 1997;Mason et al 2007), and substrate size distributions (Nitsche et al 2004), analyzing rainfall events and drop size distribution (Nystuen 2001;, monitoring internal solitary waves produced in the ocean (Apel et al 2007), and for measuring water temperature through differences in sound speed and propagation in the ocean (Terrill and Melville 1997;Vagle and Burch 2005). In addition, acoustic techniques were applied above the water surface for estimating reaeration (Morse et al 2007). …”

Section: Introductionmentioning

confidence: 99%

A flume experiment to examine underwater sound generation by flowing water

et al. 2009

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The hydrogeomorphology and ecology of rivers and streams has been subject of intensive research for many decades. However, hydraulically-generated acoustics have been mostly neglected, even though this physical attribute is a robust signal in fluvial ecosystems. Physical generated underwater sound can be used to quantify hydro-geomorphic processes, to differentiate among aquatic habitat types, and it has implications on the behavior of organisms. In this study, acoustic signals were quantified in a flume by varying hydrogeomorphic drivers and the related turbulence and bubble formation. The acoustic signals were recorded using two hydrophones and analyzed using a signal processing software, over 31 third-octave bands (20 Hz-20 kHz), and then combined in 10 octave bands. The analytical method allowed for a major improvement of the signal-to-noise ratio, therefore greatly reducing the uncertainty in our analyses. Water velocity, relative submergence, and flow obstructions were manipulated in the flume and the resultant acoustic signals recorded. Increasing relative submergence ratio and water velocity were important for reaching a turbulence threshold above which distinct sound levels were generated. Increases in water velocity resulted in increased sound levels over a wide range of frequencies. The increases in sound levels due to relative submergence of obstacles were most pronounced in midrange frequencies (125 Hz-2 kHz). Flow obstructions in running waters created turbulence and air bubble formation, which again produced specific sound signatures.

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“…Especially in small, turbulent streams, the reaeration term can be larger than GPP and ER, thus making estimates of metabolism unreliable. Many methods have been developed to measure the reaeration coefficient: tracer gases (Rathbun et al, 1978;Wanninkhof et al, 1990), empirical formulae based on channel hydraulics (Genereux & Hemond, 1992), the night-time drop of oxygen concentration (Hornberger & Kelly, 1975), the time lag between noon and the peak of oxygen concentration (Chapra & DiToro, 1991;McBride, 2002), estimation through sound pressure (Morse et al, 2007), and through non-linear fitting to the entire diel dissolved oxygen curve (Atkinson et al, 2008), among others. The choice of the most appropriate method depends on the type and size of river to be studied, as well as on time and budget constraints.…”

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Comparison of several methods to calculate reaeration in streams, and their effects on estimation of metabolism

2009

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Metabolism is an integrative measurement of stream and river ecosystem functioning, and thus, could be used to assess impairment. Stream metabolism is measured by different methods which often yield contrasting results. Furthermore, open-channel measurements of metabolism, which offer the best potential for continuous monitoring of stream functioning, rely on calculations of gas exchange with the atmosphere, for which a plethora of methods exists. Therefore, to incorporate metabolism in stream monitoring programs, it is necessary to determine which methods yield comparable results under a given set of environmental conditions. We studied 21 streams in the Basque Country (northern Spain), ranging widely in physical characteristics and water quality. We calculated reaeration during summer baseflows using three different approaches: the night-time drop in oxygen, the lag between noon and peak oxygen concentration, and ten empirical equations relating depth and velocity with reaeration coefficients obtained from the literature. Differences among methods were very large, especially at the shallower sites. The results obtained with most empirical equations were highly correlated, but showed little agreement with the night-time and peak lag methods. We then analyzed the response of reaeration rate to river stage: reaeration calculated by the nighttime method during 1 year of continuous monitoring was regressed against discharge at each site, and the resulting model was compared to the results of empirical equations, using software HecRas 2.2 to model hydraulic conditions at different river stages. The shape of reaeration-discharge plots differed greatly and in a sitedependent manner, and there was little agreement between methods. Finally, we investigated the effects of reaeration rate on estimates of metabolism. The choice of method greatly affected the estimates of both primary production and respiration. The empirical equations, except E 7 and E 10, yielded the most unrealistic estimations of stream metabolism. Overall, the night-time method, especially when regressed against discharge, seems to be the most robust and reliable among those tested, with the energy dissipation method (E 10 ) appearing to be a viable alternative when the nighttime method does not work.

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Using sound pressure to estimate reaeration in streams

Cited by 34 publications

References 33 publications

Temperature dependence of stream aeration coefficients and the effect of water turbulence: A critical review

Temperature dependence of stream aeration coefficients and the effect of water turbulence: A critical review

A flume experiment to examine underwater sound generation by flowing water

Comparison of several methods to calculate reaeration in streams, and their effects on estimation of metabolism

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