Evaluation of hydroacoustics for monitoring suspended-sediment transport in rivers Scott Wright (CA WSC) and David Topping (GCMRC) Special acknowledgement to Cory Williams (CO WSC) and Molly Wood (ID WSC) for data and assistance OSW Webinars, - PowerPoint PPT Presentation

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Evaluation of hydroacoustics for monitoring suspended-sediment transport in rivers Scott Wright (CA WSC) and David Topping (GCMRC) Special acknowledgement to Cory Williams (CO WSC) and Molly Wood (ID WSC) for data and assistance OSW Webinars,

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Title: Evaluation of hydroacoustics for monitoring suspended-sediment transport in rivers Scott Wright (CA WSC) and David Topping (GCMRC) Special acknowledgement to Cory Williams (CO WSC) and Molly Wood (ID WSC) for data and assistance OSW Webinars,


1
Evaluation of hydroacoustics for monitoring
suspended-sediment transport in rivers Scott
Wright (CA WSC) and David Topping
(GCMRC) Special acknowledgement to Cory Williams
(CO WSC) and Molly Wood (ID WSC) for data and
assistance OSW Webinars, 29-Sep-09, 2-Oct-09
2
Outline
  • Brief background on the project
  • Basic theory and approach (single frequency)
    Colorado River
  • Applications on other rivers - Gunnison,
    Clearwater
  • Analysis of historical sediment data using
    acoustics theory
  • Summary, limitations, publications, FAQs, future
    work

3
Project background
  • Exploratory deployments of side-looking ADCPs
    along the Colorado River in Grand Canyon in 2002,
    by Ted Melis and David Topping, yielded some
    interesting results and new methods
  • Given the increasing popularity of side-lookers
    at gaging stations and the potential to monitor
    sediment flux (i.e. discharge and concentration)
    with a single instrument, it was desired to
    evaluate these new methods in a broader context
  • We submitted a proposal to FISP/OSW to do this,
    and received funding in FYs 2008 and 2009
  • The main goal of the project is to develop a
    manual for using hydroacoustics to monitor
    suspended-sediment transport, drawing from our
    experience on the Colorado, from other available
    datasets, and from acoustics theory and
    historical sediment data

Nortek EZQ
4
Basic theory and approach
Transducer emits sound waves and records what
comes back (i.e. listens to the echo) profilers
use range-gating to bin the data (e.g. velocity
profiles) The amount of sound returned to the
transducer (backscatter) depends on - The
concentration, size, shape, and density of the
stuff suspended in the beam path (i.e.
targets or scatterers) - The distance from
the transducer, because there are transmission
losses along the beam (beam spreading,
absorption) Once corrected for transmission
losses, standard theory suggests that
a 0.1 b is an instrument-specific constant
Lots and lots of literature on this approach for
uniform, sand-sized particles, developed
primarily for coastal applications
5
Example profiles raw data
Raw data from the instrument (counts) Blue
profile reaches the noise floor Red profile
encounters an object (river bottom)
6
Transmission loss corrections
Along-beam transmission losses occur due to beam
spreading, absorption by the fluid, and
potentially, attenuation by the sediment First
step is to remove the spreading and fluid
absorption, as follows
FCB denotes the fluid corrected backscatter MB
is the measured backscatter (i.e. what the
instrument records) R is the slant range
(along-beam distance from transducer) ?f is the
fluid absorption coefficient (dependent on
temperature and salinity)
For some environments (coastal, tidal rivers),
these are the only corrections required
Wall, G.R., Nystrom, E.A., and Litten, Simon,
2006, Use of an ADCP to compute
suspended-sediment discharge in the tidal Hudson
River, New York USGS Scientific Investigations
Report 2006-5055, 16 p.
7
Application to Colorado River
Colorado River FCB profiles suggested that the
silt-and-clay fraction was causing additional
along-beam attenuation, with little or no
influence on overall backscatter level (1st
bin) 1000 kHz Nortek EZQ
8
Application to Colorado River
FCB profiles also suggested that the sand
fraction was causing large changes in
backscatter, but little to no along-beam
attenuation Previous acoustics work had focused
on narrow size distributions, sand only (coastal
applications) rivers have more complicated size
distributions
Can a single frequency be used to monitor
silt-and-clay and sand concentrations?
9
Why? Backscatter Attenuation theory
Theory and experimental results support our
observations on the Colorado River For typical
ADCP frequencies and for sizes typically in
suspension in rivers, backscatter and attenuation
trend in opposite directions Attenuation is much
greater for clay than sand, while backscatter is
much greater for sand than clay
1000 kHz frequency
10
Sediment attenuation coefficient
Sediment attenuation coefficient can be computed
from the slope of the linear regression between
FCB and R
11
Silt-and-clay vs Attenuation
For the Colorado River in Grand Canyon,
attenuation coefficients are very highly
correlated with silt-and-clay concentrations Line
ar relation and slope are consistent with theory
and experimental observations (for 5-10 µm
particles) Result is consistent for several
sites in 400 km reach
12
Sand vs Backscatter
Backscatter profiles can then be corrected for
sediment attenuation
For calibration with sand concentration, SCB
profiles can be averaged, or individual bins can
be used For Colorado River in Grand Canyon,
results are consistent with theory and across
multiple sites
13
Methods summary
  1. Correct measured backscatter profiles for beam
    spreading and fluid absorption (FCB) remove data
    below noise floor
  2. Apply linear regression to FCB profiles to
    compute sediment attenuation coefficients (is
    sediment attenuation important for your site?)
  3. Calibrate sediment attenuation coefficients to
    silt-and-clay concentrations should be roughly
    linear
  4. Further correct backscatter profiles for sediment
    attenuation (SCB)
  5. Calibrate backscatter level (average over the
    range or use individual bins) to sand
    concentration roughly log-linear with slope 0.1

Methods were developed using data from the
Colorado River in Grand Canyon. How general are
they?
14
Outline
  • Brief background on the project
  • Basic theory and approach (single frequency)
    Colorado River
  • Applications on other rivers - Gunnison,
    Clearwater
  • Analysis of historical sediment data using
    acoustics theory
  • Summary, limitations, publications, FAQs, future
    work

15
Gunnison River, CO
Concurrent sediment and side-looking ADCP data
collected by CO WSC in 2007, provided to our
project by Cory Williams Gunnison River near
Grand Junction, CO - 09152500 1500 kHz SonTek
SL Sediment dynamics are similar to the Colorado
(its a tributary), high silt-and-clay during
summer storms
16
Gunnison River example
Raw data profiles generally look good, no
obstructions
17
Gunnison River example
Correct for beam spreading and absorption, then
compute attenuation from linear regression
18
Gunnison River example
Correct for sediment attenuation, then average
SCB over the range of good data (i.e. above noise)
19
Gunnison River example
Silt-and-clay calibration similar to CO
River Non-linear relation tends to work better
for low concentrations
20
Gunnison River example
Sand calibration also similar to Colorado River,
slightly higher slope Not as many samples as for
silt-and-clay, pump samples not representative
for sand
21
Gunnison River example
GCLAS was used to estimate daily total sediment
loads (daily pump samples) Comparison is good
at high and low loads, some discrepancy at medium
loads Over all days (109), total load from
acoustics was 7 greater than from GCLAS
Williams, C.A., Gerner, S.J., and Elliott, J.G.
(2009). Summary of fluvial sediment collected at
selected sites on the Gunnison River in Colorado
and the Green and Duchesne Rivers in Utah, water
years 20052008, U.S. Geological Survey Data
Series 409, 123 pp.
22
Clearwater River, ID
Concurrent sediment and side-looking ADCP data
collected by ID WSC in 2008-2009, provided to our
project by Molly Wood Clearwater River at
Spalding, ID 13342500 500, 3000 kHz SonTek
SLs Sediment dynamics are quite different from
Colorado and Gunnison, more water less
sediment, silt-and-clay and sand track more
closely with each other and Q
23
Clearwater River example
Raw data profiles generally look good, no
obstructions
3000 kHz instrument
24
Clearwater River example
Correct for beam spreading and absorption, then
compute attenuation from linear regression
3000 kHz instrument
25
Clearwater River example
Correct for sediment attenuation, then average
SCB over the range of good data (i.e. above noise)
3000 kHz instrument
26
Clearwater River example
Silt-and-clay calibration looks OK, slope is
lower than for the Colorado and Gunnison,
indicating coarser sediment (more silt, less
clay) Non-zero attenuation at very low
concentrations, not sure why, maybe organics?
3000 kHz instrument
27
Clearwater River example
Sand calibration is quite similar to other river
applications
3000 kHz instrument
28
Clearwater River example
500 kHz instrument Silt-and-clay calibration
(not shown) is not very good attenuation rates
are less for lower frequencies and difficult to
measure over the extended range, unless
concentrations are very high Sand calibration
looks OK Higher frequencies appear to be better
for low sediment supply rivers
29
Outline
  • Brief background on the project
  • Basic theory and approach (single frequency)
    Colorado River
  • Applications on other rivers - Gunnison,
    Clearwater
  • Analysis of historical sediment data using
    acoustics theory
  • Summary, limitations, publications, FAQs, future
    work

30
Evaluation of historical sediment data
In the absence of acoustic data, method can be
evaluated from theoretical-empirical relations
and sediment data Relative backscatter and
attenuation computed (from eqs underlying figure
at right) from concentration and particle size
data To do this, we compiled a sediment database
for a range of large rivers from NWIS
31
River Date range N SSC range (mg/L) Range in silt-and-clay USGS gage and name
Arkansas Jun-48 Sep-81 15 200 5,900 73 - 98 07152500 Arkansas Rv at Ralston OK 07164500 Arkansas Rv at Tulsa OK
Brazos Feb-66 Jun-86 119 15 9,440 59 - 100 08114000 Brazos Rv at Richmond TX
Canadian May-49 Jul-50 16 135 141,000 60 - 100 07227500 Canadian Rv nr Amarillo TX 07228500 Canadian Rv at Bridgeport OK
Colorado (Texas) Dec-69 Apr-73 16 278 3,630 83 - 100 08161000 Colorado Rv at Columbus TX
Copper Aug-54 Sep-86 39 183 3,900 53 - 82 15212000 Copper Rv nr Chitina AK
Gila Aug-60 Mar-86 95 175 200,000 40 -100 09474000 Gila Rv at Kelvin AZ
Kansas Jun-48 Aug-50 97 270 33,000 56 - 100 06892500 Kansas Rv at Bonner Springs KS
Kuskokwim Jun-66 Sep-86 15 93 880 43 - 87 15304000 Kuskokwim Rv at Crooked Creek AK
Mississippi Apr-60 Jun-73 41 143 2,080 52 - 96 07010000 Mississippi Rv at St. Louis MO
Missouri Mar-73 Feb-76 16 676 2,390 53 - 87 06807000 Missouri Rv at Nebraska City NE 06610000 Missouri Rv at Omaha NE
Ohio Nov-79 Jun-82 24 261 908 72 - 98 03294500 Ohio Rv at Louisville KY
Pecos Oct-60 May-89 277 55 20,300 62 - 100 08396500 Pecos Rv nr Artesia NM
Platte Mar-73 Jun-93 37 561 14,100 39 - 99 06805500 Platte Rv at Louisville NE
Red Nov-79 Jun-81 7 1,070 8,720 38 - 98 07316000 Red Rv near Gainesville TX
Rio Grande Apr-66 Feb-83 62 366 7,000 69 - 100 08475000 Rio Grande nr Brownsville TX
Sacramento Feb-58 Mar-80 98 20 1,970 35 - 98 11447500 Sacramento Rv at Sacramento CA
San Joaquin Jul-67 Sep-89 85 42 424 54 - 100 11303500 San Joaquin Rv nr Vernalis CA
Stikine Jun-76 Jul-86 26 144 1,290 34 - 81 15024800 Stikine Rv nr Wrangell AK
Susitna Jul-75 Jul-86 14 257 1,490 41 - 81 15294350 Susitna Rv at Susitna Station AK
Susquehanna Aug-79 Feb-84 23 17 359 97 - 100 01578310 Susquehanna Rv at Conowingo MD
Tanana May-66 Jun-83 19 411 2,680 16 - 89 15515500 Tanana Rv at Nenana AK
Yellowstone Apr-83 Jun-91 21 173 8,770 67 - 100 06329500 Yellowstone Rv near Sidney MT
Yukon Jun-75 Sep-86 13 141 997 59 - 93 15565447 Yukon Rv at Pilot Station AK
32
Evaluation of historical sediment data
Lots of sediment finer than 2 µm Computed
attenuation dominated by clay sized
particles Computed backscatter dominated by 62
250 µm sand
33
Evaluation for other rivers
Relative contributions to backscatter and
attenuation were summed for silt-and-clay and
sand sizes Results support previous findings
Silt-and-clay dominates attenuation Sand
dominates backscatter
34
Outline
  • Brief background on the project
  • Basic theory and approach (single frequency)
    Colorado River
  • Applications on other rivers - Gunnison,
    Clearwater
  • Analysis of historical sediment data using
    acoustics theory
  • Summary, limitations, publications, FAQs, future
    work

35
Summary single frequency
  • Side-looking acoustic profilers can
    simultaneously measure two quantities related to
    suspended sediment 1) attenuation and 2)
    backscatter
  • For size distributions typical of rivers, and for
    typical ADCP frequencies, theory suggests that
    attenuation should be dominated by the
    silt-and-clay fraction while backscatter should
    be dominated by the sand fraction
  • Concurrent ADCP and sediment data from the
    Colorado, Gunnison, and Clearwater Rivers support
    the theory need more sites for a more
    comprehensive assessment
  • Historical sediment data from a large database,
    analyzed in the context of acoustics theory, also
    support the theory and field-based findings, and
    suggest that the approach should be generally
    applicable
  • There are limitations

36
Limitations
  • The silt-and-clayattenuation and
    sandbackscatter dependencies can break down
    under certain conditions, for example when one
    fraction is present in much, much greater
    quantities than the other (i.e. if silt-and-clay
    concentrations are high and there is no sand,
    then silt-and-clay contributes to backscatter)
    corrections can be developed, but data are needed
    to do so
  • Changes in particle size distributions can affect
    calibrations because backscatter and attenuation
    depend on particle size multiple frequency
    applications can help, but increases complexity
  • The technique is more complicated than other
    surrogates (e.g. turbidity, laser-diffraction),
    it requires processing and editing of large
    datasets, and an understanding of the theory is
    helpful to interpret strange results we can
    provide basic guidelines, but each site will be
    different

37
Multi-frequency
Because the backscatter-attenuation-concentration-
size relations depend on frequency, adding
frequencies adds new information on the
suspension Two different approaches have been
used 1) ratio of backscatter at two frequencies
is used to get mean size (coastal applications)
2) assigning different frequencies to different
sand size ranges (CO River) These applications
are still in the experimental phase, and depend
on the specifics of your application Does the
need justify the additional cost and complexity
involved?
38
Multi-frequency
In Grand Canyon, were interested in monitoring
the median sand size 3 frequencies are used, and
each is calibrated to a separate fraction of the
sand size range
2000 kHz very fine sand 1000 kHz fine
sand 600 kHz medium sand D50 computed from
the 3 size fractions
39
Publications
  • Series of conference papers on Colorado River
    work, most recent is
  • Topping, D.J., Wright, S.A., Melis, T.S., and
    Rubin, D.M. (2007). High-resolution measurements
    of suspended-sediment concentration and grain
    size in the Colorado River in Grand Canyon using
    a multi-frequency acoustic system, in
    Proceedings of the 10th International Symposium
    on River Sedimentation. Aug 14, Moscow, Russia.
    Volume III.
  • Article in review at Journal of Hydraulic
    Engineering
  • Wright, S.A., and Topping, D.J., in review.
    Evaluation of acoustic profilers for
    discriminating silt-and-clay from suspended-sand
    in rivers J. Hyd. Eng.
  • Comprehensive USGS Techniques and Methods report
    on the Colorado River applications (and maybe
    others), first-authored by Topping, due by the
    end of this calendar year
  • Some sort of technical memorandum with basic
    guidelines for people who want to apply the
    technology, with answers to FAQs such as

40
Future work
  • Finish writing for this project
  • More data! The most important next step is to
    expand the number of sites collecting concurrent
    ADCP and sediment data we cant do much more
    without more data from a range of sites
  • Software development For the methods to become
    general use, a software package for editing and
    developing the calibrations would be helpful
  • Coordination and support Until the methods are
    more fully tested, it would be helpful to have an
    ongoing national USGS project tasked with
    expanding the data network, coordinating the
    effort, and providing support to WSCs for
    deployments and data analysis

41
Frequently asked questions
  • What frequency should I use?
  • 1000-1500 kHz seems to be a good, all-purpose
    frequency for low concentrations, high frequency
    is better for high concentrations, low frequency
    is better
  • Should I analyze raw counts or signal-to-noise
    ratio (SNR)?
  • Both theoretically either should work but weve
    seen at least one example where SNR noise level
    changes confounded the calibrations best to try
    both, at least initially
  • Which beam should I use?
  • All analyze data from all beams separately,
    then combine at the last step if desired
  • What blanking and cell configuration should I
    use?
  • Use the minimum blanking allowed more, smaller
    cells is better (can average later)
  • What power settings should I use?
  • For high silt-and-clay concentrations, high
    power is best if backscatter is getting pegged
    at the top of the instruments range, reducing
    the power may help
  • What sediment data should I collect and how
    should it be processed?
  • All samples should be processed for silt/sand
    split, with a subset processed for full size
    distribution if possible the method is empirical
    in nature and thus only as good as the sediment
    data, so its important to get samples over a
    range of concentrations

42
Questions? Scott Wright, sawright_at_usgs.gov,
916-278-3024
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