Data Quality Indicators during Data Collection in TRDI SxS Pro

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In this video, we will discuss some of the important data quality indicators you can use when collecting data in the TRDI SxS Pro software. Note: Use of trade names is for descriptive purposes only, and does not imply endorsement by the USGS. For additional videos in this series, visit the following link: https://www2.usgs.gov/humancapital/ecd/hydrotube/hydrotube-ADCP.html
 

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Image Dimensions: 480 x 360

Date Taken:

Length: 00:04:24

Location Taken: Augusta, ME, US

Transcript

Hi, my name is Nick Stasulis and I work with the Maine Office of the New England Water Science Center.  In this video, we will discuss some of the important data quality indicators you can use when collecting data in the TRDI SxS Pro software.

Both during data collection and in the summary for each vertical there are several important data quality indicators that should be reviewed before moving onto the next vertical. Obviously, you should monitor both the profile plot and the contour plot while data is collecting. The profile plot will indicate large differences in intensity between the four beams, while the contour plot is an easy way to identify possible errors in depth, velocity, and flow angle.

Tabular data on the left of the screen updates continuously during data collection and we’ll review some of the fields here. Ensuring you have at least 2 good depth cells is important, and having a minimum of three to five is ideal. In addition, make sure you are collecting a reasonable number of good ensembles. For example, if you are collecting for 40 seconds, and your unit pings once a second, you’d expect 40 ensembles or so per vertical. If 30 of the attempted ensembles are bad, you’d only be left with 10 valid ensembles and you should identify and address the cause of the issue, if possible, or extend the data collection duration to collect more valid ensembles. A minimum of 30 ensembles per vertical is recommended.

The velocity coefficient of variation compares the velocity values from each ensemble and computes the variation as a percentage. This value can be used to determine if the ADCP is stable during data collection. While the value may start out high, it should decrease and stabilize as data collection continues. Velocity CV values around 10-15% are typical, but it’s important to analyze this value against the mean velocity for the station and the discharge for the station versus the discharge of the entire measurement. For example, here we see a Velocity CV of 10.12%, and if we apply this to the mean velocity of 1.72 ft/s, we see a range of velocity from 1.89 ft/s to 1.55 ft/s, which results in a range of discharge for the vertical from 14.7 to 12.0 cfs. You can see that a range of 2.7 cfs out of a total discharge of 360 cfs is not a significant source of potential error.

The mean direction is the direction of the flow in the vertical based on the measured velocity, and is computed differently based on the velocity method you choose. For magnitude, it is the angle between the east and north velocity component, while it is the difference between the X and Y velocity component when using y-velocity. These numbers are not used for flow computation, but do provide an indication of variation in flow direction through the cross section. Ideally, the values would be relatively consistent. If there are large variations in this value when using magnitude as the velocity reference, you would likely expect to see a flow angle entered by the user. Also, consider that a flow angle of 8 degrees equates to a 0.99 correction factor.

The standard deviation for flow direction shows the variation of flow direction within a vertical. If this number is greater than 20 degrees, it is a good indication that there is high potential for boat rotation, and that you should attempt to stabilize the ADCP. In a unit without a compass, rotation could result in a low bias to the velocity. ADCPs with a compass can account for this rotation, but large lateral movements could result in acceleration or deceleration of the compass and lead to errors. As you can see, it’s important to minimize movement of the ADCP on the end of the line, both rotation and movement side to side.

Once data collection at a vertical is complete, the summary shows the velocity CV, the direction SD, the number of valid ensembles and might show some warnings as well. Be sure to scan these values and ensure the data is valid before accepting a vertical and moving on.