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For a long time I've been curious about predicting the acoustic power spectrum of river sound from hydrodynamic measurements.

What got me started thinking about this topic was repeatedly observing the band-limited energy of powerful rivers when looking at spectrograms of audio recordings: Spectrogram from the Toe of the Tokositna

It's apparent that most of the energy of this river is contained between the 200 Hz and 2000 Hz bands. Removing the time axis (by taking a median) makes it easier to see that the energy is actually distributed around a few central bands (500 or 630 Hz):

enter image description here

A similar pattern (with varied bandwidth) has appeared at dozens of measurement locations near alpine rivers.


I believe this observation has the same peaked quality as spectra described theoretically by He et al. 2004, Figure 1, pg. 3 and observed empirically by Lockheed-Georgia Co. 1976.

From He et al. 2004: energy spectrum of turbulence as a function of wavenumber

and from Lockheed-Georgia Co. 1976: SPL as a function of 1/3rd octave band frequency


Of course there are possible environmental factors - such as terrain attenuation or atmospheric effects - that could be producing such a peaked spectrum. For the sake of a simpler answer, let's assume the receiver position is above the river pointed at the flow and that the receiver is in the far field.

enter image description here


Is there a theory that predicts such a peaked acoustic power spectrum in terms of measurable hydrodynamic properties?


I'm assuming that most of this energy is either coming from resistance in the form of rocks (on the bed or sticking up in the flow) or from the sound of turbulence, itself.

In the former case I thought Johnson-Nyquist noise might be helpful (by analogy), and in the latter perhaps Kolmogorov's length microscales? I've also considered explanations derived from Sir James Lighthill's aeroacoustic analogy.

I'm especially interested in theory that could be coupled to practical hydrology measurements such as slope, discharge, or grain size.

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    $\begingroup$ First and foremost, I don't know very much, if anything, about this field, but it occurred to me that you can't really ask for an easier experiment than putting rocks into a flow of water. Is it then possible to correlate the spectrum(s) produced with the physical setups you could create under controlled conditions, and attempt prediction based on that? Apologies if this just shows my ignorance, no need to answer. $\endgroup$ – user175021 Nov 11 '17 at 8:25
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    $\begingroup$ Since this measurement was done in open-air conditions how can you be sure that the noise is due to flow only? $\endgroup$ – Deep Nov 12 '17 at 3:34
  • $\begingroup$ You make a good point, of course. On the spectrogram you can see all sorts of fading phenomena. And I'm beginning to expect I've chosen a poor example because that notch between the 50 Hz and 200 Hz bands makes me suspicious of interference. (?) Still, I know that energy is due to water from listening to the audio, and seeing this same pattern at dozens of sites with rapidly flowing rivers nearby. I've been out many times to record the sound of water (and dabble with the hydrology side.) If it's helpful to the solution I can add more spectrograms? $\endgroup$ – D. Betchkal Nov 12 '17 at 19:08
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    $\begingroup$ Please don't make posts look like edit histories $\endgroup$ – Kyle Kanos Jan 7 '18 at 3:42
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    $\begingroup$ Using Kolmogorov theory, assuming mean flow velocity $v\sim1 m s^{-1}$, granularity of river bed at $d \sim 1-10 cm$ and normal values for viscosity water you get the "external driving" of turbulence at $10^0-10^1 Hz$ and the viscous scale at $10^4-10^5 Hz$. At $10^4 Hz$ things get also mixed up with acoustic waves but let's just ignore that. What is between, the "inertial range" should look like a nice $ \omega^{-5/3}$ in Kolmogorov theory, but it does not. I think that Kolmogorov theory might still apply in the flow, but this is still filtered by some nonlinear surface resonance. $\endgroup$ – Void Jan 12 '18 at 15:55
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With the lack of any other answers to this question I'll provide the best I've come up with.


Acoustic spectra of turbulent flows have a peaked form due to the various subranges where different processes dominate energy dissipation. This is shown conceptually in Tavoularis 2002:

enter image description here

The author continues by providing approximate wavenumber bounds for each subrange, and a corresponding formula for each. For the peaked energy-containing subrange:

"The range of energy containing eddies, having wave numbers comparable to $k_{\ell} = \frac{1}{\ell}$. In homogenous and isotropic turbulence there is no production and these eddies simply lose their energy as they pass it to smaller eddies. However, in shear flows, the energy containing eddies would continuously receive energy from the mean flow. An empirical expression is the von Kármán interpolation formula."

Which they give as:

$$E(k) = \frac{A \epsilon^{2/3} k^{4}}{{[k^2 + \ {k_0}^2]}^{17/6}}$$


I wanted to see how the shape of the von Kármán interpolation formula compared to the empirically observed spectrum.


Using

  • $A \approx 1.7$ (given by the authors as typical)
  • $\epsilon = 6 \times 10^{-8} \frac{m^2}{s^3}$
  • $k_0 = 9.2$ (equivalent to the $f = 500 Hz$ peak that we already saw on the empirical plot - a dissatisfying circular choice)


We can make the following comparison:

Observed Sound Pressure Level and Theoretical Prediction For Energy-Containing Subrange

I'm not sure how to get the final energy dissipation spectrum into Sound Pressure Level units, but the peaked spectrum appears at least roughly similar to the summertime conditions. I've also added the winter conditions (dashed line on upper plot) from the same location to show how much less pressure energy exists in the environment when the river is frozen.

Additionally, neither $A$, $\epsilon$, nor $k_0$ are easily quantified in the field.

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