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## Index-Velocity Rating Development

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### Index-Velocity Rating Development

Streamflow Record Computation using ADVMs and Index Velocity Methods

Office of Surface Water

Goals for This Presentation

- Provide an overview of the next steps in rating development:
- Make Q measurements over range of conditions
- Develop a rating “workbook”
- Organize Q measurement data
- Synchronize stage and velocity data with Q measurements
- Plot data
- Review plots before proceeding with rating analysis

How Many Q Measurements?

- Rule of thumb:
- Need minimum 10 measurements per explanatory variable used in the regression
- Example: In a simple relation between Vi and Vmean, Vi is the only explanatory variable, so need a minimum of 10 measurements before developing a rating
- But……measurements need to be over a range of hydrologic conditions!!

Measurement Considerations

- Strive to collect measurements over the complete range of discharge
- All ratings have uncertainties outside the range of discharge measurements

Proper Q Measurement Techniques

- Follow guidelines in:
- ADCP Measurements: T&M 3A-22 by Mueller and Wagner at: http://pubs.usgs.gov/tm/3a22/
- General Q Measurements: T&M 3A-8 by Turnipseedand Sauer at: http://pubs.usgs.gov/tm/tm3-a8/
- OSW Memoranda at: http://water.usgs.gov/osw/pubs/techmemos.html

Q Measurements

- Do a good job in the field!
- Your rating will reflect the quality of the collected data
- A rating error can be related to field data collection procedures
- Make the best discharge measurements possible

Is this a good idea?

Steady vs. Unsteady Flow

Review:

- Steady flow – negligible change in stage, velocity, or discharge
- Unsteady flow – continuous change in stage, velocity, or discharge

Unsteady Flow

- Exposure time rule (minimum 12 minutes) applies to steady flow; not to unsteady flow!
- For unsteady flow, if at all possible, collect reciprocal transects to average together to make a measurement
- In highly unsteady flow, it may be necessary to use a single transect as a measurement
- Subjective determination!

Unsteady Flow

- One example is tidally-affected flow
- Tidal cycle measurements: 7 to 13 hours
- How would you group transects in this example?

Unsteady Flow

- With very rapidly changing flows, compromises may need to be made – for example, running ADCP transects faster than recommended
- This can result in reduced data quality
- The record from such sites may be poor

2009 flood on the Red River at Grand Forks, ND

Data Collection For Rating Development

OR…..

- Record data to the ADVM internal recorder
- Disables SDI-12 communication withdata logger
- Can manually input regular sampling interval to data base

Reminder

- Check and, if needed, sync clocks in DCP, ADCP, and ADVM
- Within 1-2 seconds

Correct Time:

www.time.gov

http://tf.nist.gov/

Step 3: Organize Data

- One example as a starting point…

Compute Vmean

- For every Q measurement, compute Vmean:

Vmean = Q / Rated Area from Standard X-Section

NOTVmean output in your ADCP software

Rating Workbook Template

- We have developed a template
- Let’s do a demo…..

Step 4: Synchronizing Data

- Inaccurate synchronization of stage and velocity data with Q measurements can give you a headache when developing your rating!

Example

- Measurement on 6/1/12
- Start: 12:10:15
- End: 12:25:26
- What is the time of the FIRST velocity/stage data point that should be used in the average?
- What is the time of the LAST velocity/stage data point that should be used in the average?

Synchronizing 15-Minute Data

- If have Vi and/or Stage data at intervals other than 1 minute (most commonly 15 minutes)….
- Interpolate to the mid-time of the Q measurement

Example

- Measurement on 6/1/12
- Start: 12:10:15
- End: 12:25:26
- What is the measurement mid-time?
- What is the approx. interpolated stage at the mid-time?

Rating Workbook Template

- The provided template automatically synchronizes GH and Vi data to your measurements
- You have to add GH and Vi data and enter averaging interval/measurement period

Rating Workbook Template

- Document your analysis in the workbook!!!
- Otherwise you will forget your logic, and others who check your work will be confused!

Data Synchronized With Q Measurements

- Data synchronized
- Now what?

Scatter Plots

- In Excel, highlight x and y data and go to Insert-Scatter (under Charts)
- Let’s do some scatter plots together in Excel….

Multi-cell Plots

- Look for which cells or combination of cells have the best relation with Vmean
- Also look for any abnormalities – some cells (or the range-averaged cell) should be excluded from the rating

Multi-cell Plots

- The best relation with Vmean may be an average of multiple cells’ Vx
- Experiment with and plot different explanatory variables!

Stage vsVmean

A relatively “flat” velocity profile --change in position of mean velocity with respect to the instrument is insignificant

Note that for the flatter profile, measuring any place between positions A and B, the difference between measured and mean velocity could be negligible – whereas the difference is significant with the more curved profile

A

B

Outliers

- If you see outliers in your plots, first check that all date and time synchronizations are correct!
- Also check raw data files
- Beams obstructed?
- Changing cell end?
- Affected by biofouling?
- Don’t exclude a measurement unless you can document a reason it is erroneous

Rating Development

- Ratings can be based on single or multiple parameters:
- Velocity
- Stage
- Velocity (x,y) and stage
- Uncommon: Velocity (x,y), stage, and Velocity (x,y)2

Rating Development

- For bi-directional flow sites (i.e. tidal), the rating might need to be separated into positive andnegative flow directions (compound rating)
- Velocity
- Stage
- Velocity and stage
- Velocity (x,y), stage, and Velocity (x,y)2
- Wind?
- Specific Conductance?

Rating Development

- The rating should:
- Be the best fit of the field data
- Make hydraulic sense for the site
- Be expressible as one or more mathematical equations

Rating Types

- Simple Linear
- 1 explanatory variable
- Find best relation with Vmean
- Compound
- 2 or more simple linear regressions
- Group data based on slope changes
- Multiple Linear
- 2 or more explanatory variables

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