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Discharge data for Tamiami Canal are also available for water years 1986-1999, 2000, and 2001.
For additional information about this project contact either: Eric Swain, firstname.lastname@example.org, 954 377-5925 or Chris Langevin, email@example.com, 954 377-5917
Schaffranek, R. W.
Parameters for velocity for 1997 and 1999 include depth, velocity, and flow direction.
Flow velocities in the C-111 wetlands were measured using portable Acoustic Doppler Velocity (ADV) meters that determine velocity components in the East, North, and Up directions (ENU). The ADV meter consists of a measuring probe attached to a signal-conditioning module, which is cabled to a processing unit equipped with a serial interface to a portable computer. The meter measures the frequency shift between a short acoustic pulse of known frequency and its reflectance from particles moving with the flow of water. The scattering strength of the acoustic signal is a function of particle size and concentration within the sampling volume. The particular ADV meter used (Sontek, 1997) operates internally at an acoustic frequency of 10 MHz with a programmable sampling rate ranging from 0.1 to 25 Hz, producing multiple individual velocity readings, referred to as velocity pings. The ADV meter measures the flow in a remote sampling volume, approximately 0.25 cm3, to a resolution of 0.1 mm/s. Water temperature and salinity, measured independently, are input to the ADV meter processor to compute the speed of sound, which is used to convert Doppler frequency shift to flow velocity. With an optional magnetic compass and tilt sensor, the instrument processor internally converts velocity measurements to an East, North, and Up coordinate system. Data conversion programs supplied by the instrument manufacturer (Sontek, 1997) produce four output text files from the binary data file recorded by the processing unit of the ADV meter: control, velocity, correlation, and signal to noise ratio (SNR) files. The control file contains the water-quality parameters and instrument-specific information used to calculate velocity components as well as site-specific data for identification purposes (fig. 2). The velocity file contains the velocity component values for each ping. A correlation value for each ping, which is a general data quality parameter expressed as a percent that can identify poor data resulting from a variety of factors, such as an instrument malfunction or a fouled probe, is output to the correlation file. The SNR file contains a value for each ping that identifies the signal strength during the measurement, calculated as signal amplitude subtracted from signal noise level and expressed in decibel (dB) units (Sontek, 1997).
In 1997, flow measurements generally were made at five locations spaced at variable intervals along nine transects oriented southwestward and perpendicular to the canal. In 1999, measurements were repeated at five of these transects and collected along one new transect, perpendicular to the canal at the S18-C control structure. Flow measurements also were made on two new transects along the ENP boundary to the south and west of C-111, one oriented north-south and the other east-west. In 1997, data were collected and recorded in the U.S. Customary System units whereas in 1999 International System (SI) units were used. For reader convenience and use, summary statistics for data collected in 1997 have been converted to SI units in this report. At all measurement sites, velocities generally were sampled at 10 Hz in two-minute bursts consisting of 1200 individual velocity pings. In September 1997, velocities were measured at 0.8d, 0.6d, and 0.2d, where d is total depth from the water surface to the top of the litter layer. In September 1999, velocities were measured at 0.8d, 0.5d, and 0.2d. At sites where the water depth was less than 15 cm, only a mid-depth velocity measurement was made. In 1997, temperature, salinity, dissolved oxygen, conductivity, and pH were measured, always at mid-depth. In 1999, only temperature, salinity, and conductivity were measured. In both years, visual observations of vegetation characteristics (type, density, and height) were noted and recorded at each site. These flow-velocity data were collected to analyze regional surface-water flow patterns in the C-111 wetlands and to compute discharge fluxes across basin boundaries. The data were processed, as described in this report, specifically for these purposes and are not intended, nor are they necessarily suitable, for use in other applications.
After the preliminary data reduction, two techniques were used to process the data. The first data-processing technique was the application of an automated filtering program to identify velocity pings of poor signal quality and the second technique was the visual inspection of plotted data and the analysis of velocity standard deviation. The filtering criteria used in the automated program are those suggested by the ADV meter manufacturer to identify suspect data due to poor signal quality (Sontek, 1997). The analysis of velocity standard deviation and visual inspection of plotted data were used as a secondary processing technique to identify additional suspect data presumably caused by perturbations in the water column rather than poor signal quality. The first data-processing technique, the automated filtering program, is designed to remove velocity pings with a correlation value less than 70% or SNR value less than 5 dB. (A correlation value above 70% and an SNR greater than 15 dB at 25 Hz and greater than 5 dB at 0.1 Hz are suggested indicators of good acoustic signal quality (Sontek, 1997).) The automated filtering program consists of two functions. The first function calculates component-averages of correlation and SNR values for each ping, whereas the second function uses single-component values for each ping. The first function identifies component-averaged correlation or SNR values that do not meet the above criteria, removes the three velocity components of that ping from the data set, and recalculates the component-velocity average and standard deviation. The second function of the filtering program identifies any single-component correlation or SNR value that does not meet the criteria, removes the identified velocity component of that ping from the data set, and recalculates the component-velocity average and standard deviation (see example in table 2). For the C-111 data processed herein, only results of the single-component filter are tabulated for comparison to values calculated from the raw data. (See Appendix A for data collected in 1997 and Appendix B for data collected in 1999). The second data-processing technique, designed for the C-111 data, combines the visual inspection of plots of component velocities and their 21-point running averages plotted at each depth with the analysis of velocity standard deviation. Inspection of the plots and velocity standard deviation can reveal the presence of large scatter or trends in the data generally not detected by the automated filtering process.
For both years, slightly more than half of the data sets included pings that did not pass the criteria of the single-component filter in the automated program. However, in many of those data sets only a few pings failed and the majority of the data sets evidenced little change in recalculated velocity magnitude and flow direction.
For flow-velocity analysis of the C-111 canal and adjacent wetlands, resultant velocity magnitude in the horizontal plane and vector-averaged flow direction, relative to magnetic north, were calculated for each site.
Water Quality data Collection Collection of flow data in the canal C-111 overbank and adjacent wetland area began in September 1997 near the conclusion of the spoil removal efforts. Data were collected along 9 to 12 transect lines covering the 7.1-km segment of C-111 beginning 1.1 km north of US Hwy 1 bridge and ending 2 km south of S-18C. Transects originate at locations on the southwest bank of the canal opposite culverts under the levee road on the northeast bank and extend normal to the canal approximately 1.5 km into the adjacent wetlands. Transects lines are numbered 1 through 9 beginning with the culvert nearest US Hwy 1 bridge. Measurement sites are spaced at variable-length intervals along the transect lines.
Five basic water-quality parameters (temperature, pH, specific conductance, dissolved oxygen, and salinity) were collected at each site having sufficient depth using a Hydrolab multi-parameter sensor positioned at mid-depth.
For a more complete description of data collection, processing, and analysis, see OFR 00-56, Flow-Velocity Data Collected in the Wetlands Adjacent to Canal C-111 in South Florida During 1997 AND 1999.
Parameters recorded for velocity data on all dates include depth (m), velocity (cm/s) and flow direction (from magnetic north)
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