**Spatial Analysis of ADCP Data in Streams**

Randal L. Dinehart, U.S. Geological Survey, Sacramento, CA
(rldine@usgs.gov)

**Keywords**: acoustic Doppler current profiler, velocity, backscatter
intensity, sediment transport

**Abstract**

Procedures to display data from acoustic Doppler current profilers
(ADCPs) in spatial maps have been developed for surface-water hydrology.
The procedures were designed for rapid processing of repeated ADCP
surveys of channel reaches and junctions. Using only ADCP data, vectors
that define the velocity field of a channel can be displayed in
perspective over detailed bathymetry. In addition, the backscatter
intensity recorded with ADCP velocity data provides a sediment-transport
indicator. The prevalence of ADCPs and their ability to measure velocity
fields encourages the exploitation of backscatter-intensity values for
sediment-transport studies. At present, spatial ADCP data from channel
surveys have been interpolated to volumetric vector grids to show flow
and sediment dynamics through time animation. These visualizations have
highlighted some discrepancies between expected flow properties and
analyses of ADCP data, and field experiments are suggested to identify
their origin. Examples are given in this paper using spatial ADCP data
collected in the Sacramento and San Joaquin Rivers, California, during
2001 and 2002.

**introduction**

The water-quality data files of the U.S. Geological Survey (USGS)
contain instantaneous sediment concentrations measured by sampling water
at multiple points across streams. Hydrologists recognize that
concentrations represent brief samples of a constituent that fluctuates
with turbulence and changing discharge. To compensate for this
uncertainty, we use statistical adjustments and smoothing techniques to
approximate an average concentration for a given period. Standard
analyses can produce crude sediment-discharge totals from these values,
but water sampling does not resolve fluctuations in sediment transport
that are exhibited at macroturbulent scales (tens of seconds, usually).
Sediment suspension also varies spatially in relation to local sediment
sources and hydrodynamics. Turbulent fluctuations and spatial variations
both increase the uncertainty in sediment-transport quantities, and a
record of the fluctuations and their location will at least identify,
and perhaps reduce, the uncertainty inherent with sediment sampling.

Spatial-analysis procedures have been developed for data collected with
the ADCPs that are presently used by the USGS for discharge
measurements. ADCPs have the potential to provide data on sediment
suspension at numerous points in the vertical column, for time intervals
on the order of 1 second. An ADCP transmits sonar signals and calculates
velocity from the Doppler shift in the frequency of the signals returned
from multiple depths beneath the device. From the same depths, the ADCP
software records backscatter intensity, which is the intensity of
acoustic backscatter from solid particles suspended in the flow. By
recording ADCP data when crossing a stream, we acquire
sediment-transport indicators over the flow depth every 1 to 4 seconds,
with a lateral spacing of a few meters. If the cross-stream distribution
of backscatter intensity is graphed, sediment suspension in the stream
is indicated for the period of crossing. For that period, the
backscatter intensity provides better spatial indication of
suspended-sediment distribution than can be obtained from sediment
sampling at each of five points during a period of 20 to 30 minutes. By
mapping backscatter-intensity contours along stream crossings or complex
survey paths, we can infer changes in suspended-sediment distribution at
intervals of a few minutes.

Although the backscatter intensity recorded by ADCPs may not be an ideal
indicator of sediment concentration (Gartner, 2002), spatial analyses
exploit existing ADCPs for velocity mapping and indications of sediment
transport, to show that some good data are better than no excellent
data. New strategies have been tested to interpret backscatter-intensity
contours as maps of suspended-sediment distribution. These strategies
employ techniques used to map flow fields and interpolate velocity data
to three-dimensional grids (Dinehart and Burau, 2003).

Flow-field mapping and interpolation allow spatial analysis of changes
in vector fields and suspended-sediment distributions from one ADCP
survey to the next. The streambed is the local source of much suspended
sediment, and multiple ADCP surveys obtain sufficient data to map
streambed bathymetry from individual beam depths (Dinehart and Burau,
2003). By superimposing maps of backscatter intensity on the streambed
bathymetry, the correspondence of spatial variations in suspended
sediment with transient bed features becomes apparent. By plotting
velocity vectors with color contours for backscatter intensity, the
relation between local flow conditions and suspended sediment can be
analyzed.

"Channel mapping" is a collective term chosen for the data processing
and visualization of velocity, backscatter intensity, and bathymetry
data from ADCPs in streams. The purpose of this short paper is to
provide background on channel mapping so that some discrepancies between
ADCP data and expected flow properties can be noted. Resolution of these
discrepancies by experimental investigations will reduce the uncertainty
associated with flow-field interpolations and enhance eventual
calculations of sediment discharge from ADCP data.

**Data acquisition and processing**

Operational characteristics of ADCPs have been described in technical
manuals by RD Instruments (Gordon, 1996). Simpson and Oltmann (1993)
adapted ADCPs from oceanographic applications to measure discharge in
tidal channels with moving boats. The adaptation was accomplished by
extensive testing in the Delta of the Sacramento and San Joaquin Rivers
by the USGS (Simpson, 2001). The methods presented here were developed
from analysis of ADCP surveys made in the Delta of the Sacramento and
San Joaquin Rivers during 2000-2003, by the Bay-Delta Hydrodynamics
Project of USGS (California District, supervised by Jon Burau), and by
the author on behalf of the CalFed Sedimentation Project. The example
data of ADCP surveys come from various broadband models manufactured by
RD Instruments.

To obtain the ADCP surveys, flow-defining patterns were first drawn
digitally on maps of reaches to be surveyed. The surveyed reaches were
at tidal rivers and sloughs with sand beds and slow velocities (\~1
meter per second or less). Navigational positions were provided by input
from receivers for differential Global Positioning System (GPS) data.
Pilots steered along patterns on the maps while watching their boat's
position plotted continuously by GPS. Tidal channels were surveyed
repeatedly during daylight or through a diurnal tidal cycle. Data from
multiple crossings at various distances along the reach were used to
create three-dimensional vector grids over channel bathymetry. An
alternate source of ADCP surveys for spatial analysis was obtained from
routine ADCP discharge measurements made to calibrate ultrasonic
velocity meters installed at gaging stations. Although the paths of the
discharge measurements were too closely spaced in the channel to show
longitudinal variations, the lateral resolution of velocity at the cross
section was much higher than obtained by traditional stream-gaging
methods. Time resolution also was much higher, as each measurement was
completed in a few minutes, and repeated for as many as 12 hours.

Data-processing programs were written initially to analyze and display
hundreds of ADCP surveys made at a channel junction of the Sacramento
River (Dinehart and Burau, 2003). The programs (DopplerMacros) allowed
channels to be surveyed repeatedly with ADCPs with minimal
post-processing of survey data. Two commercial software programs were
used together to extract and view output files from WinRiver (RD
Instruments), a propriety software program for data acquisition and
review of ADCP data. Program algorithms for processing ADCP data were
written in Microsoft Excel with Visual Basic for Applications. Graphical
procedures for spatial analysis were designed using Tecplot by Amtec,
Inc.

Each vector of a velocity ensemble was measured by the ADCP at one of
multiple depth cells. In the post-processing phase, velocity-ensemble
data are inspected and filtered with several passes. The first pass
through an ADCP survey removes empty ensembles and gross outliers near
the bed. A second pass removes additional outliers at the bottom of each
ensemble, which are usually attributed to ambiguity errors (Gordon,
1996). An optional third pass performs the only numerical changes to
original velocity data. Vector components exceeding the mean of the
ensemble by 2.5σ (standard deviation) are interpolated to the value of
their nearest neighbors. This operation is followed by a centered,
three-point average applied to all interior points of each ensemble
(Fig. 1). As a final option, vectors in the velocity profile can be
extrapolated from the remaining, bottom velocities to zero at the
bathymetric surface. Outliers in ensembles of backscatter values were
less common, and no special filtering is applied to them at this stage,
although values can be extended linearly to the bed.

After ADCP data are registered to geographic coordinates and filtered,
program scripts produced by Visual Basic for Applications automate the
import of velocity and bathymetric data to Tecplot. Local bathymetry was
mapped in Tecplot by interpolation of individual beam depths to regular
mesh grids (Dinehart and Burau, 2003). The bathymetric data from ADCP
surveys were sufficiently dense for definition of channel topography.
With Tecplot, a shaded bathymetric surface can be displayed in the
background while the overlying ADCP surveys are varied through time.
Velocities were visualized over bathymetry by displaying vector
ensembles colored according to vector magnitude or backscatter
intensity. Alternatively, the vector origins were connected in vertical,
curved planes and superimposed on bathymetry. When colored for
backscatter intensity, the contoured planes over bathymetry indicated
regions of sediment suspension or scour (Fig. 2). From these
visualizations, users can assess the influence of flow conditions and
streambed topography on mapped velocity vectors and backscatter
intensity.

**Discrepancies noted by Spatial analyses**

By comparing expected flow properties with spatial analyses of ADCP
surveys, a number of discrepancies have been noted. They may come from
the intrinsic ADCP operation or from the subsequent interpolations, but
field research is necessary to resolve them before channel-mapping
procedures become reliable for sediment-transport studies.

*Mean velocity-vector components*: To fill the gaps along flow
directions between survey paths, velocity vectors were interpolated to
mesh grids that conformed to local bathymetry and water surface
(Dinehart and Burau, 2003). In this process, the interpolated flow
directions were more coherent at adjacent nodes when the velocity
ensembles were smoothed by the optional three-point average. However,
velocity ensembles are collected over durations that can be an order of
magnitude less than macroscale turbulence. Therefore, the uncertainty in
vector directions is not necessarily reduced by smoothing these
short-duration samples.

A central assumption of velocity measurement by ADCP is that scatterers
in the flow move at the same horizontal velocity through all four sonar
beams. Exceptions to this assumption are more substantial in alluvial
channels than in the ocean because of the ubiquity of sediment
suspension by macroscale turbulence throughout the water column. Mapping
velocity while rapidly crossing a turbulent flow field, therefore,
invites high uncertainty in vector components. This uncertainty
increases when velocity ensembles recorded with single pings are used
(Gordon, 1996).

Although velocity ensembles derived from multiple pings may mask the
inclusion of ambiguity velocities, the net effect is that vector
directions become more uniform. The spatial distance between transmitted
ensembles does not increase proportionally with more internal averaging
because ping intervals are short, relative to data-transmission
intervals. The preference for single-ping ensembles in discharge
measurements does not seem to be appropriate for flow mapping, because
the high standard deviation induced by macroturbulence affects mean
vector components. An accurate measure of vector components is essential
when sediment flux is to be calculated with normal vectors at
cross-sectional planes of interpolated grids. For these reasons, the
various aspects of ADCP surveys that affect mean vector components
require experimental investigation.

*Backscatter intensity*: A gross, direct correlation between backscatter
and mean velocity can be documented for changes in river discharge from
flood to ebb tide and from common to storm flows. This observation is
consistent with expected sediment-transport relations. However, direct
correlations are less apparent at shorter time scales, from 5 seconds to
a few minutes. Instead, occasional increases in backscatter are often
correlated with decreases in longitudinal velocity. The inverse
correlations may originate from sediment suspended by upward bursts that
have lower horizontal velocity. Accordingly, vector directions
determined from movement of large, suspended scatterers may include
effects of eddy boundaries, particle settling, and particle inertia.

As noted previously, discharge measurements by ADCP provide repeated
cross-sectional views of velocity and backscatter distribution in a
channel. Each measurement records a set of velocity ensembles that can
be rotated to a linear cross section for grid analyses. Using color
contours, the corresponding set of backscatter-intensity values can be
displayed for each ADCP crossing (Fig. 3). Backscatter intensity varies
widely across the section, and the distribution varies gradually through
time. Zones where backscatter intensity is consistently higher are
visible in the time series of crossings. Close examination shows that
varying backscatter intensity is often associated with small, lateral
gradients in vector components. This implies that backscatter intensity
also may vary in response to macroscale turbulence. Evidence of spatial
changes in sediment concentration to explain the backscatter variations
is presently unavailable. Independent, high-frequency measurements of
flow velocity and sediment concentration in the vicinity of ADCP beams
can determine the dominant contributions to backscatter intensity
recorded in natural streams.

**future directions**

A specialized software environment is being developed for processing and
visualization of ADCP data. Time series of vector grids, based on ADCP
surveys, are easily acquired at channel locations away from gaging
stations, and should prove valuable to agencies. To help complete
multiple surveys, data processing will be simplified for general users
so that ADCP data can be visualized to compatible standards. Those
standards will guide the filtering of errors from ADCP data, the
preferred geographic coordinates to apply, the formats for data storage,
and will assure compatibility of results from different ADCP surveys.
Research on mapping velocity during rapid passage through macroscale
turbulence will validate flow-field interpretations of ADCP data for
velocity and sediment flux. Ultimately, calibrated relations (Deines,
1999; Gartner, 2002) may be derived for the interpolated grids of
velocity and backscatter, from which sediment discharge can be computed.
Deriving sediment discharge from interpolated ADCP data depends on the
success of current research in calibration techniques (Gartner, 2002),
and the experimental resolution of discrepancies between ADCP data and
expected flow properties.

**References**

Deines, K.L., 1999, Backscatter estimation using broadband acoustic
Doppler current profilers, in: Proceedings of the IEEE Sixth Working
Conference on Current Measurements, San Diego, CA, March 11-13, 1999,
pp. 249-253.

Dinehart, R.L. and J.R. Burau, 2003, Repeated surveys by acoustic
Doppler current profiler for flow and sediment dynamics at Delta Cross
Channel (abstract), in: Proceedings of CalFed Science Conference,
January 2003, Sacramento, CA, p. 43.

Gartner, J.W., 2002, Estimation of suspended solids concentrations based
on acoustic backscatter intensity: theoretical background: paper
presented at Turbidity and Other Sediment Surrogates Workshop, April
30-May 2, 2002, Reno, NV, 4 pp.

Gordon, Lee, 1996, Acoustic Doppler current profiler---Principles of
operation: A practical primer: RD Instruments, San Diego, CA, 41 pp.

Simpson, M.R., 2001, Discharge measurements using a broad-band acoustic
Doppler current profiler: U.S. Geological Survey Open-File Report 01-1,
at http://pubs.water.usgs.gov/ofr0101

Simpson, M.R. and R.N. Oltmann, 1993, Discharge-measurement system using
an acoustic Doppler current profiler with application to large rivers
and estuaries: U.S. Geological Survey Water-Supply Paper 2395, 34 pp.

The use of trade, product, industry, or firm names in this report is for
descriptive purposes only and does not constitute endorsement of
products by the U.S. Government.

![](media/image1.png){width="6.5in" height="2.8291666666666666in"}

Figure 1. Oblique view showing velocity ensembles before (A) and after
(B) outlier filtering. Velocity magnitudes range from 40 to 60 cm/s over
mid-ensemble. Lateral distance between ensembles is about 1 to 2 m.
Vertical distance between vector components is 0.25 m. Study site is
Sacramento River at Walnut Grove, California, November 1, 2001.

![](media/image2.png){width="6.5in" height="5.082638888888889in"}

Figure 2. Oblique view showing backscatter intensity in planar contours
over bathymetry. Backscatter intensity indicates regions of sediment
suspension or eddy production. Colors are assigned to indicate range of
backscatter intensity in decibels. Study site is False River at San
Joaquin River, California, May 1, 2002. The bathymetry layer was
interpolated from several ADCP surveys of area during study period.

![](media/image3.png){width="5.995833333333334in" height="8.14375in"}

Figure 3. Elevation view showing sequence of backscatter-intensity plots
from ADCP dischage measurements. Colors are assigned to indicate range
of backscatter intensity in decibels. Study site is San Joaquin River at
Jersey Point, California, March 14, 2001. Tidal flow ranges from ebb
tide at top (toward viewer), to slack tide at 14:12, to flood tide at
bottom (away from viewer).