You have decided to embark on a flow metering project in your sewer system, perhaps to develop design peak flows or to perform an I&I analysis. Flow metering can be expensive and mother nature does not always cooperate with providing good rainfall events. So it is critical that the meters are generating good data when that large storm hits. This article outlines some best practices for flow meter data QA/QC review that will help ensure that you collect good data from your flow metering program.
This article focuses on meter data QA/QC for area-velocity flow meters such as those made by ISCO, ADS and Hach. However, the principles and processes can be applied to other meter types including flumes, mag meters, transmit time meters and depth only sensors. Many flow metering networks are comprised of a mixture of technologies and these best practices can be applied successfully to these networks as well.
Raw Data Review
Ensuring that flow meters are generating good data starts with raw data review. It is best to look at the raw data early and often to make sure that the meter is working well. Don’t wait to look at the data for the first time until after a big storm – by then it may be too late if a meter was having issues. Here are some raw data review best practices:
- At installation – Have the meter installation crew examine the data being collected in the field to verify the meter is working well. Spot check the meter recordings against the depth and velocity from a portable velocity probe.
- A few days after installation – Examine the data collected within a day or two of the meter being installed to verify that the meter is working properly. The first few days after installation are very important to look at data to make sure the meter is working and the site is suitable for metering. This gives time to move the meter if there is an issue before that large rain hits.
- Regular data reviews – Just because the meters were working at installation does not mean they will be working during the next big rain. These are sensors installed in a very challenging environment and they can and do fail from sedimentation, ragging, fouling, or even getting knocked by a rock rolling downstream. Glance at the data at least once every couple of weeks, and more often if you have telemetry. A tool like H2Ometrics can make looking at a lot of data fast and easy.
Continuous Data Review
Once you know that the meter is working and collecting data, next it is time to use some engineering tools and examine whether the meter is generating consistent and accurate data. There are several good continuous data review best practices for that:
- Long-term period breaks – Occasionally a meter will experience a sudden and drastic shift in the flow that it is recording. This may be due to debris knocking the sensor or a meter servicing that shifted the recording regime of the sensor. It is important to review the pattern of the flow to ensure that it is consistent over time. Below is a screenshot of some data in H2Ometrics with a significant period break. Issues like this can be corrected by editing the data in H2Ometrics.
- Dry weather trends – Adding a dry weather trend line is a great way to detect more subtle period breaks that may not be so obvious. Here is a video that shows the concept using H2Ometrics. A dry weather pattern can be very helpful to gauge and detect small shifts in the meter performance.
- Wet weather trends – Reviewing meter performance during wet weather or with significantly shifting seasonal dry weather infiltration requires a tool like a meter correlation to an adjacent or nearby meter. A meter correlation is an estimate of the flow computed with a scale (multiplying) and an offset (adding) from another meter. Here is a video that shows the concept using H2Ometrics.
A scatter plot is a plot of the depth versus the velocity (or flow) recorded by a meter. This is a useful diagnostic tool to evaluate how the meter is performing. An example scatter plot from H2Ometrics is shown below and here is a link to a video that shows the H2Ometrics scatter plot tool.
The Manning’s curve shown in red on the scatter plot represents how the depth and flow relate under “normal” or “uniform” flow conditions in the pipe – that is the flow condition in which there are no obstructions, backwater effects or other unusual flow conditions in the pipe. When the scatter plot deviates from the Manning’s line, it may indicate that the system is operating in a flow condition outside of “normal” or “uniform” flow. This can use useful for identifying and diagnosing sewer performance issues.
ADS has a nice series of scatter plot examples that walk through several different scatter plots types and what each one might be indicating in the sewer system. These can be helpful for diagnosing sewer issues from scatter plot data. You can even contact them and they will send you a free poster of the scatter plots.
Mass Flow Balance
Mass Flow Balance (MFB) is a process that compares the flows from upstream meters to downstream meters to check the continuity of the flows in the metering network. This is done by performing the network meter math to compute the flow from incremental areas, which are the flow contributions from the areas in between the meters. An example is shown below from the H2Ometrics MFB tool in which the incremental area (Meter #1 inc – depicted as a square) is computed from the upstream flows (meters 2 & 3) subtracted from the downstream flow (meter 1).
The metered flows and incremental flows can then be unitized by population or service area to verify that the network is balanced and the meters are recording within expected ranges. Here is a link to a video that shows the H2Ometrics MFB tool and how meter data can be adjusted to balance the network and identify problematic meters.
Dye testing is an accurate methodology of measuring instantaneous flows in a sewer. A fluorescent dye is injected into the system at a known flow rate and concentration. Then, a sample is measured at a downstream point in the system where the dye is thoroughly mixed. The concentration of the dye in the downstream sample can be measured accurately, and the flow rate in the pipe is proportional to the dye dilution rate. Dye testing is generally considered to produce flow measurements that are within a few percentage points of the actual flows.
Dye testing is a good method to check the accuracy of a flow meter and correct for repeatable, systematic biases in a flow measurement. A dye test factor can be used to adjust the meter flow in a mass flow balance.Most often, dye testing is used when meter data is being used for billing purposes. An example of adjusting metered flow with a a dye test factor is shown below. Because there are inaccuracies in dye tests as well, it is common to conduct at least two dye tests to establish a correction factor for a billing meter.
As a final note on best practices for flow meter data QA/QC, I want to highlight the people side and the importance of working as a team. You can only go so far in identifying and diagnosing a metering issue solely from just looking at the data in the office. More often, it is necessary to include many teammates in the process that may include:
- Engineers processing the data
- Feld technician maintaining the meters
- Utility staff who operate and maintain the sewer system
- A representative from the flow meter manufacturer or contractor
- Staff or contractors performing dye tests (if applicable)
When troubleshooting a metering issue, it is often necessary to engage multiple parties from the team to understand the issue and investigate it in the field.