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Velocity, Conductivity and Temperature, Temperature Profile, Water-Depth (Shark River Slough)

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Frequently-anticipated questions:


What does this data set describe?

Title:
Velocity, Conductivity and Temperature, Temperature Profile, Water-Depth (Shark River Slough)
Abstract:
Flow-velocity, water-temperature, and conductivity data were collected at five locations in Shark River Slough in Everglades National Park (ENP), Florida, from July 1999 to July 2003 to document the temporal and spatial variability of sheet-flow conditions. These data serve to define the range of sheet-flow conditions in various vegetative communities in the wetlands and to identify internal and external factors that affect sheet-flow behavior.

The data were collected in Shark River Slough, ENP, during the 2000-01, 2001-02, and 2002-03 wet seasons and during part of the 1999-2000 wet season.

  1. How should this data set be cited?

    Raymond Schaffranek (retired) Amy Riscassi (no longer with USGS), 2004, Velocity, Conductivity and Temperature, Temperature Profile, Water-Depth (Shark River Slough):.

    Online Links:

    Other_Citation_Details: The data are from USGS Data Series 110
    This is part of the following larger work.

    Schaffranek, Raymond W. Riscassi, Ami L., 2004, Flow velocity, water temperature, and conductivity at selected locations in Shark River Slough, Everglades National Park, Florida: July 1999 - July 2003: USGS Digital Data Series 2004-110, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details: accessed as of 4/26/2011

  2. What geographic area does the data set cover?

    West_Bounding_Coordinate: -80.85
    East_Bounding_Coordinate: -80.7
    North_Bounding_Coordinate: 25.67
    South_Bounding_Coordinate: 25.47

  3. What does it look like?

    <https://sofia.usgs.gov/exchange/schaffranek/locationflowshark.html> (GIF)
    location of Shark River Slough data collection sites

  4. Does the data set describe conditions during a particular time period?

    Beginning_Date: Jul-1999
    Ending_Date: Jul-2003
    Currentness_Reference: ground condition

  5. What is the general form of this data set?

    Geospatial_Data_Presentation_Form: maps and data

  6. How does the data set represent geographic features?

    1. How are geographic features stored in the data set?

      Indirect_Spatial_Reference: Shark River Slough
      This is a Point data set. It contains the following vector data types (SDTS terminology):
      • Point (5)

    2. What coordinate system is used to represent geographic features?

      Grid_Coordinate_System_Name: Universal Transverse Mercator
      Universal_Transverse_Mercator:
      UTM_Zone_Number: 17
      Transverse_Mercator:
      Scale_Factor_at_Central_Meridian: 0.9996
      Longitude_of_Central_Meridian: -81
      Latitude_of_Projection_Origin: 0
      False_Easting: 500000
      False_Northing: 0

      Planar coordinates are encoded using Coordinate Pair
      Abscissae (x-coordinates) are specified to the nearest 1
      Ordinates (y-coordinates) are specified to the nearest 1
      Planar coordinates are specified in meters

      The horizontal datum used is North American Datum of 1983.
      The ellipsoid used is Geodetic Reference System 80.
      The semi-major axis of the ellipsoid used is 6378137.
      The flattening of the ellipsoid used is 1/298.257.

  7. How does the data set describe geographic features?

    Entity_and_Attribute_Overview:
    Velocity Files

    The following parameters are included in each file: Station Description

    Station name Easting, in Universal Transverse Mercator (UTM) coordinates, North American Datum 1983 (NAD 83), Zone 17, meters (m) Northing, in Universal Transverse Mercator (UTM) coordinates, North American Datum 1983 (NAD 83), Zone 17, meters (m) Sample volume height above the top of the plant-litter layer, in centimeters (cm)

    Data

    Burst #, year, month, day, hour, minute Velocity for each component (east, north, and up), in centimeters per second (cm/s) Correlation for each component (east, north, and up), in percent (%) Amplitude for each component (east, north, and up), in counts Signal-to-noise (SNR) ratio for each velocity component (east, north, and up), in dB units Horizontal flow speed, in centimeters per second (cm/s) Horizontal flow direction, in degrees clockwise from magnetic north (° CW from MN) Number of samples passing the automated filter

    Files from the 1999-2000 wet season include additional parameters of standard deviations for the east and north velocity components, as indicated in the column headings.

    Conductivity and Temperature Files

    The following parameters are included in each file: Station Description

    Station name Easting, in Universal Transverse Mercator (UTM) coordinates, North American Datum 1983 (NAD 83), Zone 17, meters (m) Northing, in Universal Transverse Mercator (UTM) coordinates, North American Datum 1983 (NAD 83), Zone 17, meters (m) Sample volume height above the top of the plant-litter layer, in centimeters (cm)

    Data

    Burst #, year, month, day, hour, minute Temperature, in degrees Celsius (deg C) Conductivity, in Siemens per meter (S/m) Salinity, in parts per thousand (ppt) Specific conductance, in microSiemens per centimeter (mS/cm at 25 deg C)

    Temperature-Profile Files

    The following worksheets are included in each temperature-profile data file:

    Station Description - station name, easting and northing in Universal Transverse Mercator (UTM) coordinates, North American Datum 1983 (NAD 83), Zone 17, meters (m), instrumentation, and vegetation type Measurement Notes - parameter units, instrument specifications, and equation used to convert measured resistance to temperature Deployment Settings - list of deployment dates, recording intervals, and measurement locations Water Depths - dates, times, and depths at the site Data Files - temperature, in degrees Celsius (deg C) at 11 locations in the water column, air, and (or) on the water surface (Data are compiled in separate spreadsheets by wet season and changes in set-up parameters)

    Water-Depth Files

    The following parameters are included:

    Date and time Water depth at the ADV meter or thermistor string

    Entity_and_Attribute_Detail_Citation:
    Schaffranek, R. W. And Riscassi, A. L., 2004, Flow Velocity, water temperature, and conductivity at selected locations in Shark River Slough, Everglades National Park, Florida, July 1999 - July 2003; U.S. Geological Survey Data Series 110


Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)

    • Raymond Schaffranek (retired)

  2. Who also contributed to the data set?

    This project was conducted as part of the USGS Priority Ecosystems Science Initiative. Gordon Anderson, USGS, provided stage data from the SH1 hydrologic monitoring station and Kevin Kotun, National Park Service (NPS)/ENP, provided stage data from the NP202, NP203, P33, and P36 hydrologic monitoring stations. Daniel Nowacki (contractor no longer at USGS) developed the HTML for the report.

  3. To whom should users address questions about the data?

    Eric D. Swain
    U.S. Geological Survey
    3110 SW 9th Avenue
    Ft. Lauderdale, FL 33315
    USA

    954 377-5925 (voice)
    954 377-5901 (FAX)
    edswain@usgs.gov


Why was the data set created?

A major objective of Everglades restoration, as defined in the Comprehensive Everglades Restoration Plan (CERP), (accessed February 28, 2011, at <http://www.evergladesplan.org/pub/restudy_eis.aspx>) is to restore sheet-flow behavior in the Everglades to a more natural pre-drainage condition. This effort requires scientific insight into hydrologic and hydraulic factors that affect sheet-flow behavior for restoration planning as well as background knowledge of sheet-flow conditions for restoration assessment, identified as a critical need in the CERP Monitoring and Assessment Plan (MAP) (accessed February 28, 2011, at <http://www.evergladesplan.org/pm/recover/recover_map_2004.aspx>). Moreover, knowledge of sheet-flow behavior is essential for the development and use of models to evaluate and compare restoration scenarios for implementation, refinement, and evaluation of the CERP.


How was the data set created?

  1. From what previous works were the data drawn?

  2. How were the data generated, processed, and modified?

    Date: 2000 (process 1 of 3)
    Three stations (SH1, GS-203, and GS-33) were established in 1999 and 2000 to monitor flows and related hydrologic conditions in differing vegetative communities within Shark River Slough. Flow velocities, water and air temperatures, and conductivities were monitored from July 1999 through August 2001. At all three sites, water and air temperatures were monitored at 5- or 30-minute intervals in 5- or 10-cm increments above the plant-litter layer using thermistors (thermally sensitive resistors) cabled together in a string. At two of the sites, velocities were monitored hourly or bi-hourly at a fixed point in the water column using acoustic Doppler velocity (ADV) meters. At one of the two ADV monitoring sites, conductivities and water temperatures were monitored bi-hourly near the plant-litter layer using a water-quality meter.

    MEASUREMENT TECHNIQUES Acoustic Doppler Velocity (ADV) Meter:

    Flow velocities were measured using SonTek ADVField units (SonTek, 2001) that consist of a processing module and a conditioning module with an attached three-dimensional (3-D) acoustic probe. A 10 MHz probe with a 5-cm distance from the transmitter to the cylindrical sampling volume (0.25 cm3) was used. Local water temperature and salinity data were used to compute site-specific sound speed, which is needed to convert Doppler frequency shift to flow velocity. The ADV meter records 3-D velocity components at a user-specified sampling rate to a resolution of 0.1 mm/s with an accuracy of 1% of measured velocity (SonTek, 2001). The internal magnetic compass and tilt sensor allow the instrument processor to internally convert Cartesian coordinate (XYZ) velocity components to Geodetic East, North, and Up (ENU) coordinates.

    Conductivity/Temperature Meter:

    Conductivity and temperature data were measured using a MicroCAT model SBE 37-SI meter developed by Sea-Bird Electronics (1999). The MicroCAT meter measures conductivity to a 0.1 mS/cm (microSeimen/centimeter) resolution with an accuracy of 3.0 mS/cm and temperature to a 0.0001 degrees C resolution with an accuracy of 0.002 deg C (Sea-Bird Electronics, 1999). Conductivity and temperature data measured by the MicroCAT meter were integrated into the data set recorded by the ADV unit.

    Thermistor String:

    Water and air temperatures were measured using glass-encapsulated thermistors made by Yellow Springs Instruments (YSI) having a standard 10K ohm resistance at 25 deg C and an accuracy (as defined by interchangeability) of ±0.1 deg C over 0 to 70 deg C (Yellow Springs Instruments, 1998). The thermistors were individually molded and cabled together in a string. Ten thermistors were grouped together in two sets of five individually spaced 10 cm apart. The two sets were spaced 1 m apart to facilitate overlapping the cable to achieve 5-cm spacing between thermistors. An eleventh thermistor was attached at the end of the string on a 1-m length of cable or thin TV-type 2-conductor wire. The eleventh thermistor was either deployed at a fixed elevation in the air above the plant-litter layer or encapsulated in styrofoam to float on the water surface. The thermistor string was wired to a Campbell Scientific Instruments (CSI) CR10X datalogger programmed to sample the thermistors at pre-determined intervals and perform the resistance to temperature conversions. Measured resistances were converted to temperatures in the datalogger program using the Steinhart and Hart equation (Yellow Springs Instruments, 1998).

    Flow-monitoring sites:

    Stations GS-203 and GS-33 were near established ENP hydrologic monitoring stations, NP-203 and P33, and SH1 is co-located with an existing USGS hydrologic monitoring station. Thermistor strings were deployed at all three sites. ADV units were deployed at GS-203 and SH1. The ADV unit at GS-203 included an integrated MicroCAT conductivity/temperature meter.

    Each station was established within a different vegetative community. The SH1 ADV probe and thermistor string were deployed in an area dominated by spikerush (Eleocharis cellulosa) on the edge of a sawgrass (Cladium jamaicense) stand. The GS-203 ADV probe and thermistor string were deployed in an area of medium-density sawgrass. The GS-33 thermistor string was deployed in a spikerush community with a heavy periphyton concentration.

    DEPLOYMENT TECHNIQUES AND PARAMETER SETTINGS

    The ADV conditioning module with attached 3-D probe was suspended vertically from a rigid frame with the acoustic sampling volume at a fixed position in the water column above the plant-litter layer. A pair of stainless steel rods, used to secure the conditioning module to the frame, readily permitted vertical re-positioning (raising or lowering) of the probe in the water column during field visits in response to changing water depths. Software programs were executed during probe installation and during subsequent field visits to set site-specific parameters that initiate data collection, protect data integrity, verify meter performance, and ensure the collection of high-quality data. Parameter settings are user-specified values input to the ADV processor that assign the duration and frequency of sampling as well as specify the sound speed required for velocity determinations.

    The MicroCAT meter, integrated into the GS-203 ADV unit, measures and records data at the same frequency as the ADV meter and therefore has no unique user-specified parameter settings. The MicroCAT meter was deployed immediately above the plant-litter layer near the ADV probe.

    The temperature-string deployment techniques and parameter settings consisted of specification of the thermistor-spacing increment and the recording interval. The resistance-to-temperature conversion equation and the recording interval were stored in the CR10X datalogger using the PC208W (V 3.0) communication and storage module software (Campbell Scientific Inc., 1999).

    ADV-Meter Deployment Procedures and Programs:

    The setting of data-collection parameters and initiation of the ADV-meter deployment were typically accomplished in the field by connecting the processor unit to the serial port of a laptop computer. A set of software programs provided with each ADV unit facilitated design of the sampling strategy, assignment of acoustic signal-processing parameters, initiation of the data-collection sequence, and subsequent downloading of data from the datalogger. Prior to deployment of the ADV probe at each site, the ADV compass was calibrated in accordance with the manufacturer’s instructions and the ADFcheck diagnostic program (SonTek, 2001) was executed. The ADFcheck program is used to verify meter performance and to identify hardware problems, such as a bent probe or malfunctioning transmitter, which can cause the loss or corruption of data. The ADFcheck program produces a plot of the signal strength for the three acoustic receivers and a tabular summary of diagnostic parameters that are useful in post-processing analyses. Prior to probe deployment, a log file was created on the laptop to record all parameter settings assigned during field initiation of the ADV meter. This included recording of output from configuration, setup, system, deployment, and sensor commands.

    During field visits, the water depth at the probe location was measured, the signal pathway between the acoustic transmitter and sampling volume was inspected and cleared of vegetation, if necessary, and the acoustic probe was cleared of any biological growth.

    To reduce memory requirements and conserve battery power, all autonomous deployments use a burst, rather than a continuous, sampling strategy. A burst is a collection of samples taken over a programmable time or ‘burst’ interval. Individual samples are stored for subsequent analysis. During all deployments at both ADV measurement sites, velocities were sampled at 10 Hz in one-minute bursts yielding 600 individual 3-D component velocity samples at hourly or bihourly intervals.

    Representative constant salinity and temperature values were input to the ADV processor for sound-speed calculation for each deployment. Although there is a deployment option to use time-varying water temperatures measured by the internal sensor of the ADV meter to compute sound speed, the end cap of the conditioning module housing the temperature probe was never submerged during the deployments. Therefore, an externally measured constant temperature was specified.

    During deployment initiation, the coordinate system was set to either XYZ for recording 3-D velocity component data in Cartesian coordinates relative to the fixed probe position or to ENU, which signals the ADV unit to use data from the internal compass and tilt sensor to transform the velocity data to Earth coordinates. Any data initially recorded in XYZ coordinates during the deployments were converted to ENU coordinates in post-processing.

    Statistical correlations of the individual acoustic pings within a sample were used extensively in editing and analyzing the velocity data as discussed subsequently. The default settings for recording this additional information vary for each option and are identified in the manufacturer’s documentation (SonTek, 2001). For these deployments all available statistical information was recorded for post-processing and analyses.

    METHODS OF DOWNLOADING DATA

    Downloading of the ADV dataloggers was typically accomplished using the manufacturer-provided software after retrieving the processing module from the field. Due to the large quantity of data generated during each deployment, downloading of files (up to 40 mb in size) required 4 to 5 hours, which would have made downloading in the field problematic and impractical. After the data were downloaded and the datalogger was formatted, the processing module was returned to the field site for re-deployment. Temperature-string data files (< 3 mb in size) were downloaded on site via a laptop computer using the PC208W communication and storage module software

    ADV DATA REDUCTION AND PROCESSING TECHNIQUES

    A preliminary data-inspection process, a pre-editing data-conversion process, two complementary automated data-editing processes, and a visual qualitative inspection process were used to edit, verify, and otherwise process the recorded flow-velocity, signal-quality, statistical-correlation, and ancillary data downloaded from the ADV datalogger. The entire set of ADV data post-processing techniques consisted of the following steps: 1. inspection of the downloaded data set to identify periods when the probe was known to be out of the water or disturbed followed by appropriate truncation of the data file; 2. pre-editing sound-speed correction and coordinate-system conversion using the manufacturer’s software; 3. automated filtering based on statistical correlation and number of samples per burst, flagging of suspect bursts based on percent difference and maximum value, and initial calculation of burst-averaged 3-D component and horizontal velocities and daily mean horizontal flow speeds and directions including flagged values, using USGS-developed software; 4. visual qualitative inspection of flow velocities using meteorological data and other available information and subsequent flagging of additional suspect bursts; and 5. automated recalculation of burst-averaged 3-D component and horizontal velocities and daily mean horizontal flow speeds and directions excluding flagged suspect bursts, using USGS-developed software.

    Prior to initiating the automated data-editing process, data were scrutinized to identify any values that might have been recorded before the conditioning module and probe were cabled to the processing module or the probe was submerged. Several situations occurred where it was necessary to initiate an ADV meter for deployment using the program software prior to gaining access to the field site to position the probe. Data recorded during site visits, when flow velocities were affected by onsite arrival, departure, or cleaning of the acoustic probe also were identified. Affected data were removed in an initial pre-data-editing process by appropriately assigning an exclusive burst range for the exporting of time-series and header text files discussed subsequently. (Alternatively, affected data could have been removed subsequently from the fully exported time-series and header files using a text editor.) Data collected when the probe was suspected of intermittently being out of the water during the deployment period due to low water levels were initially retained for further inspection by automated and qualitative means to ensure that no valid measurements were errantly discarded.

    The first data-processing technique, utilizing software provided by the manufacturer, consisted of pre-processing data at the sample level. Data remaining after known initial bad values were eliminated were first pre-processed with the SonTek ViewHydra (V 2.71) program to re-compute velocities in ENU coordinates, if necessary, and to substitute more representative temperature and salinity values for sound-speed calculation, if appropriate. Velocities were converted to ENU coordinates in the ViewHydra program either by selecting the appropriate velocity-coordinate-system option or by entering an applicable probe axis rotation for the specific deployment. (User-specified input of the probe rotation was necessary for those ADV meter deployments that were initiated prior to gaining access to the field site). The speed of sound was recalculated based on constant mean temperature and salinity values determined from time-varying temperature and conductivity data measured by the MicroCAT meter or obtained from nearby hydrologic stations.

    Using the new sound-speed parameters, burst statistics were recomputed and control, time-series, and header ASCII text files were exported by the ViewHydra program. The control file contains the water-quality parameters and instrument-specific information used to compute velocity components and site-specific data for identification purposes; it is not used in filter processing. The time-series file contains 3-D velocity, signal strength, and correlation component values for each sample. The correlation value is a general data-quality parameter expressed as a percent that can identify poor velocity data resulting from a variety of factors, such as an instrument malfunction or a fouled probe. Signal strength values are a measure of the intensity of the reflected acoustic signal and can be converted to signal-to-noise ratios (SNR) by subtracting the ambient noise and converting to units of decibels (dB). The header file contains the mean 3-D velocity component values for each measurement, or ‘burst’ interval, and all date and time information associated with each burst.

    The USGS-developed data-processing technique, described herein, consisted of automated data editing and processing at both sample and burst levels. This technique involved use of a filtering program, ADVFilter1.pl, (available for downloading from <https://sofia.usgs.gov/time/software/advfilter.php>). The filter can be used with any ADV time-series and header text files exported by the ViewHydra program from the binary data file recorded by the ADV processing unit or extracted by other SonTek programs. The ADVFilter1 program contains statistical-correlation, percent-difference, and maximum-value functions with control parameters that can be set by the user based on individual ADV data attributes. The program computes burst-averaged 3-D velocity components, horizontal magnitudes, and flow directions and also optionally calculates the value difference between successive velocity magnitudes. The statistical-correlation function consists of two processes that remove 3-D velocity component samples and bursts from the exported data file. The first process removes all 3-D velocity component samples composed of pings that have a statistical correlation less than a specified minimum percentage for either their East/West or North/South component.

    The second process removes any burst having less than a specified minimum number of samples that pass the statistical-correlation filter. The optional percent-difference and maximum-value functions also flag data bursts for subsequent validation or elimination from the exported data file. The pre-processed data files generated by the ADVFilter1 program subsequently can be reprocessed to exclude flagged values from applicable computations, such as the evaluation of burst-averaged and daily mean velocities.

    The six output files, three of which are optional, created by the ADVFilter1 program contain the following: 1. velocity samples and associated correlation, amplitude, and SNR (optional) values for each 3-D component; 2. burst-averaged velocity and associated correlation, amplitude and SNR (optional) values for each 3-D component; 3. daily mean horizontal velocity magnitude and flow direction plus water temperature, conductivity, salinity, and specific conductance, if optional MicroCAT meter integrated with ADV unit; 4. burst-averaged temperature, conductivity, salinity, and specific conductance, if optional MicroCAT meter integrated with ADV unit; 5. percent differences between successive burst-averaged horizontal velocity magnitudes (optional); and 6. value differences between successive burst-averaged 3-D velocity components (optional).

    A visual, qualitative inspection of burst-velocity magnitudes and flow directions in conjunction with ancillary stage, rain, and other meteorological data, also was conducted as a final processing technique to isolate any additional suspect velocity data that might have been affected by sporadic perturbations in the water column or otherwise contaminated. Upon inspection of the data, anomalous velocities were identified and evaluated for potential correlation to a meteorological event. If no meteorological event could be attributed to an anomalous value, individual samples within the suspect burst were inspected and the burst was flagged if the samples were found to exhibit inexplicable fluctuations in velocity magnitude and (or) flow direction.

    Flagged data, including those identified by percent difference or maximum value filters as well as by qualitative inspection, optionally are removed from the final data set using a second automated filter program ADVFilter2.pl, (also developed by the USGS and available at <https://sofia.usgs.gov/time/software/advfilter.php>). This program re-generates burst-averaged 3-D velocity components excluding bursts that have been flagged in the initial data set and re-calculates daily mean horizontal flow speeds and directions with the reduced number of bursts.

    PROCESSING ADV, CONDUCTIVITY AND TEMPERATURE DATA

    The editing and filtering criteria used to process the ADV data included those suggested by the manufacturer to detect suspect data attributed to poor signal quality (SonTek, 2001) and those developed during the processing and concurrent analysis of the flow-velocity data.

    ADV data:

    SNR values were computed for each burst and included with the filtered data made available for downloading from the SOFIA website; however, they were not used as a filter-editing criterion.

    The initial automated data-editing process consisted of the application of two filter criteria based on minimal statistical correlations and minimum number of valid samples per burst. A minimum correlation value of 70 % was used as the statistical-filtering criterion.

    A second criterion was employed subsequently to evaluate the statistical-correlation-filtered data based on a specified minimum number of valid samples required to compute a representative burst-averaged horizontal flow velocity. The minimum number of samples required per burst to produce a burst-averaged velocity was determined by examination and assessment of differences found using various filter criteria on data sets from both SH1 and GS-203. The filter initially was applied using criteria of 600, 500, 400, 300, 200, 100, and 1 minimum samples per burst. Differences between daily mean horizontal flow velocities computed using the strictest samples-per-burst filter (all 600 samples must pass) and three others (400, 200, and 1) were minimal.

    A secondary qualitative processing technique included the generation of plots of filtered data to detect any remaining anomalous horizontal flow speeds and directions. Data found to exhibit such anomalies were examined in conjunction with stage, wind, and other available meteorological data. In most cases, suspect bursts were not found to coincide with any identified meteorological event. These bursts were analyzed further by inspection of individual velocity samples within the suspect and surrounding bursts. Bursts containing anomalies found to be a result of inconsistent velocity samples were flagged and removed from the data set. If the individual samples within a burst showing evidence of a flow anomaly were found to be consistent, the burst was not removed from the data set.

    Conductivity/temperature data:

    The primary intent of integration of the external MicroCAT conductivity/temperature meter with the ADV unit was to accommodate use of the instruments in saline environments where time-varying salinity and temperature measurements are needed for site-specific sound-speed calculations. A secondary use of the MicroCAT temperature data at the GS-203 site was as a reference check for the thermistor data. Temperatures measured by the MicroCAT meter near the top of the plant-litter layer at GS-203 were compared to temperatures measured by the thermistor in the temperature string located approximately 8-9 cm above the litter layer. Good agreement was found between the two sets of data for all deployments. No anomalies were found in the MicroCAT temperature data; therefore, the data are made available as originally recorded.

    Conductivity data measured by the MicroCAT meter were compared to conductivity measurements taken with a hand-held portable meter during field visits. No suspect conductivity readings were detected during field visits.

    Temperature profile data:

    All temperature profile data from the thermistor strings were plotted and inspected for anomalies. No suspect data were found. Times when all thermistors were out of the water, thus measuring only air temperatures, are identified.

    Any use of trade, product, or firm names is for descriptive purposes only and does not constitute endorsement by the U.S. Government

    Date: 2003 (process 2 of 3)
    The ADV unit installed at GS-33 in August 2001 was intended to provide flow-velocity data to supplement water and air temperature profiling initiated at the site during the 2000-2001 wet season. In August 2001, a thermistor string was deployed at the ENP NP202 hydrologic station to monitor the temperature profile in an area of dense cattails.

    Temperatures were monitored at 5-, 15- or 30-minute intervals throughout the water column at all four sites, 3-D component flow velocities were monitored bi-hourly at a fixed point in the water column at SH1, GS-203, and GS-33, and conductivities and temperatures were monitored bi-hourly near the top of the plant-litter layer at GS-203 and GS-33.

    All measuring and processing steps are identical to those used in the 1999-2000 wet seasons.

    Date: 2004 (process 3 of 3)
    In July 2002, an ADV unit and thermistor string were deployed at site GS-36 to monitor flow velocities, conductivities, and temperature profiles in an area of sparse spikerush approximately midway between established flow-monitoring stations SH1 and GS-33. The GS-36 site was located near the NPS P36 hydrologic monitoring station to provide water-level data for flow analyses.

    Temperatures were monitored at 15-minute intervals throughout the water column at all five sites, 3-D flow-velocity components were monitored bi-hourly at a fixed point in the water column at SH1, GS-203, GS-33, and GS-36, and conductivities and temperatures were monitored bi-hourly near the top of the plant-litter layer at GS-203, GS-33, and GS-36.

    Measurement and data reduction methods were identical to those used in the 1999-2000 and 2001-2002 deployments.

    Person who carried out this activity:

    Eric D. Swain
    U.S. Geological Survey
    3110 SW 9th Avenue
    Ft. Lauderdale, FL 33315
    USA

    954 377-5925 (voice)
    954 377-5901 (FAX)
    edswain@usgs.gov

  3. What similar or related data should the user be aware of?

    Riscassi, Ami L. Schaffranek, Raymond, 2002, Flow velocity, water temperature, and conductivity in Shark River Slough, Everglades National Park, Florida: July 1999-August 2001: USGS Open-File Report OFR 02-159, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details: accessed as of 5/25/2011
    Riscassi, Ami L. Schaffranek, Raymond W., 2003, Flow velocity, water temperature, and conductivity in Shark River Slough, Everglades National Park, Florida: August 2001 - June 2002: USGS Open-File Report 2003-358, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details: accessed as of 5/25/2011
    Riscassi, Ami L. Schaffranek, Raymond W., 2004, Flow velocity, water temperature, and conductivity in Shark River Slough, Everglades National Park, Florida: June 2002 - July 2003: USGS Open-File Report 2004-1233, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details: accessed as of 5/25/2011
    Campbell Scientific, Inc., 1999, PC208Wdatalogger support software instruction manual: Campbell Scientific, Inc., Logan, UT.

    Other_Citation_Details: software manual
    Sea-Bird Electronics, Inc, 1999, SBE 37-SI MicroCAT conductivity and temperature recorder with RS-232 interface: User's Manual 010, Sea-Bird Electronics, Inc., Bellevue, WA.

    Other_Citation_Details: user's manual
    SonTek, 2001, SonTek ADV Acoustic Doppler velocimeter: SonTek, San Diego, CA.

    Other_Citation_Details: technical documentation
    Instruments, Yellow Springs , 1998, YSI precision thermistors and probes: Yellow Springs Instruments, Yellow Springs, OH.

    Other_Citation_Details: user's manual


How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?

    Flow velocities were measured bi-hourly at a fixed location in the water column using 10 MHz acoustic Doppler velocity (ADV) meters. The ADV meter measures flow velocity to a resolution of 0.1 mm/s with an accuracy of 1 percent of measured velocity (SonTek, 2001). Velocity samples were filtered and edited according to criteria suggested by the instrument manufacturer and developed in processing and concurrent analysis of the flow data. Both quantitative filters and qualitative editing methods were used to quality check and verify data accuracy. Data that did not pass the filtering and editing criteria are not included in this dataset.

    Conductivities and temperatures were measured bi-hourly at a fixed location near the plant litter layer using MicroCAT model SBE 37-SI meters. The MicroCAT meter measures conductivity to a resolution of 0.1 mS/cm with an accuracy of 3.0 mS/cm and temperature to a resolution of 0.0001 deg C with an accuracy of 0.002 deg C (Sea-Bird Electronics, 1999).

    Temperatures were measured at 5-, 15-, or 30-minute intervals at 5- or 10-cm depth increments throughout the water column, on the water surface, and in the air immediately above the water surface using glass-encapsulated thermistors manufactured by Yellow Springs Instruments (YSI). The YSI thermistor measures temperature to an accuracy of 0.1 deg C over a 0 to 70 deg C range (Yellow Springs Instruments, 1998).

    Continuous water depths at the monitoring stations were determined by correlating local water depths measured during intermittent site visits to stages continuously recorded at nearby USGS and NPS hydrologic-monitoring stations. Negative values indicate water levels below ground surface.

  2. How accurate are the geographic locations?

    unavailable

  3. How accurate are the heights or depths?

  4. Where are the gaps in the data? What is missing?

    Velocity, water-depth, and temperature profile data are available for all sites. In addition conductivity and temperature were collected at sites GS-203, GS-33, and GS-36. The data were collected in Shark River Slough, ENP, during the 2000-01, 2001-02, and 2002-03 wet seasons and during part of the 1999-2000 wet season.

    Valid flow-velocity data were not obtained from five ADV deployments during the 2000-2001 wet season (two at GS-203 and three at SH1). For the initial ADV deployment at GS-203 on August 17, 2000, the acoustic probe was subsequently determined to be out of the water during the majority of the deployment period due to unexpected low water levels); therefore, no valid velocity data were recorded. During the second deployment at GS-203 on September 6, 2000, the velocity range setting for the ADV meter reverted to the instrument default of ±250 cm/s, instead of a more appropriate setting of ±10 cm/s, making the probe less sensitive to detecting the very small velocities at the GS-203 site. As a consequence, no valid data are available from this deployment. During three consecutive deployments at SH1, the ADV unit failed to record data due to an instrument malfunction, a real-time clock failure, or a communication error between the laptop and the unit during initiation; no data are available for these three periods.

    Valid flow-velocity data were not obtained from two ADV deployments at GS-33 during the 2001-2002 wet season. During the first two deployments at GS-33 the velocity range setting for the ADV meter reverted to the instrument default of ±250 cm/s, instead of a more appropriate setting of ±10 cm/s, making the probe less sensitive to detecting very small velocities. As a consequence, no valid velocity data are available from these two deployments.

  5. How consistent are the relationships among the observations, including topology?

    Flow-velocity, water-temperature, and conductivity data were collected during the 4-year timeframe of this study. The data were collected in Shark River Slough, ENP, during the 2000-01, 2001-02, and 2002-03 wet seasons and during part of the 1999-2000 wet season. All data have been processed, quality-checked, and edited.


How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?

Access_Constraints: none
Use_Constraints: none

  1. Who distributes the data set? (Distributor 1 of 1)

    Heather S. Henkel
    U.S. Geological Survey
    600 Fourth St. South
    St. Petersburg, FL 33701
    USA

    727 803-8747 ext 3028 (voice)
    727 803-2030 (FAX)
    hhenkel@usgs.gov

  2. What's the catalog number I need to order this data set?

    Shark River Slough Data

  3. What legal disclaimers am I supposed to read?

    The data have no guarantees explicit or implied

  4. How can I download or order the data?


Who wrote the metadata?

Dates:
Last modified: 03-Jun-2011
Metadata author:
Heather Henkel
U.S. Geological Survey
600 Fourth Street South
St. Petersburg, FL 33701
USA

727 803-8747 ext 3028 (voice)
727 803-2030 (FAX)
sofia-metadata@usgs.gov

Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)


This page is <https://sofia.usgs.gov/metadata/sflwww/flowshark.faq.html>

U.S. Department of the Interior, U.S. Geological Survey
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