DATALOGGER WATER LEVEL MEASUREMENT

ERRORS2014 ©HydroG Resources Group Inc.

Professionals using dataloggers to collect water level measurements are sometimes confronted with unusual

(erroneous) data.

This course discusses the source of some of these errors, and, how to

avoid erroneous data.

• Recognizing Errors1

• Case Study2

• Methods to avoid errors3

Course Outline

Knowledge Base

We are assuming you are familiar with :• accurately obtaining manual water level

measurements.• how dataloggers are installed and used to

obtain water level measurements.• concepts of quality control and quality

assurance.For simplicity all our examples deal with the water table in an unconfined aquifer.

RECOGNIZING ERRORS

Example Programs

The following examples combine:• a theoretical program illustrating

common problems that result in errors in continuous data sets, and,

• data from an actual monitoring program illustrating real life problems as encountered.

Theoretical Site• Study requirement to monitor fluctuation in water

table within an unconfined aquifer.• Standard 2” PVC water table observation well

chosen for monitoring. • Monitoring well also used to collect water quality

samples.• Datalogger hung on “off the shelf” cable from local

hardware store, tied in place at well head using some string/rope.

• Barometric logger also located on site.

Looks Like This:• Datalogger installed on

October 15th, “looking great” thinks the hydrogeologist!

• They plan on water level measurements and downloads every second month.

• That takes them to mid-December, lets see what happens….

First Problem – Frozen Fingers!

Graph The Data

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First Download Example - December 9th

Datalogger Data

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First Question

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Datalogger Data

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The data looks like it might be “good”, but how do you tell?

Data QA/QC Check

The data looks like it might be “good”, but how do you tell?

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Datalogger Data

Manual Measurements

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You need add in the manual measurements and compare.

Program Status – A1

All the data matches up – everything is looking good at this point.

Project Hydrogeologist says “Let the client know everything is under control – the compliance monitoring program is right on track”.

After three months they remember to get back out to check the logger and download more data.

First Real Problem

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Datalogger DataManual Measurements

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0.56 m

Something happened in January, and there is now a 0.56 m difference between the datalogger and manual water level data.

What Can You Do Now?

Check your notes, and with others – who visited the well and what activities occurred between visits?

Pull the date out of the data – what happened on January the 5th at 12 pm?

You find out that the water quality sampling team was there at that time – they pulled the datalogger out of the well, used the inertial pump, and replaced the datalogger.

Solve the Data Problem.

In your notes you recorded that the poly tubing came up when you pulled the datalogger – the cable was wrapped around the tubing.

Maybe when the sampling team replaced the datalogger it did not return to the original depth setting (it was at a higher level in the well)?

Then the datalogger “experienced” less pressure over that period, and the calculated water level (setting minus pressure reading) was off by 0.56 m.

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Original Datalogger DataManual MeasurementsCorrected Data

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Modify (“Correct”) Your Equation

Over the period in question change the depth setting to reflect the 0.56 m difference. (water level = depth setting – pressure reading)

Looks like problem solved.

Program Rolls On!

Looks like that little issue with the sampling team was solved easily enough.

The project hydrogeologist is really busy, asks the field technicians to keep up the monitoring schedule and send over the data when it is available.

After the first year of monitoring maybe it’s time to take a look at the data?

So the data is compiled, air pressure compensation completed and a graph is produced.

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Download Example: Full Year of Data

Original Datalogger DataManual Measurements

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Multiple Issues – What Happened?

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Original Datalogger DataManual Measurements

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Check Your Notes!The cable corroded through: datalogger fell to bottom of well.

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Original Datalogger DataManual Measurements

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Drill Down Into The Data!The datalogger was overpressured, sensor is damaged,readings drift.

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Original Datalogger DataManual Measurements

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Some Things Cannot Be Corrected.The datalogger fails, no data or no communication, was it the battery?

Program Status - Ouch.

After a year of monitoring you have about 6 months of usable datalogger data, and some of that could be questioned.

Failure to plan, track, use quality installation materials and methods, or implement a QA/QC program has left you with little data and a dead datalogger (at the expense of the project).

What do you tell your boss, your client and the regulatory agency now?

CASE STUDY

Site and Monitoring Objectives

• Contaminated site near a municipal well field.• Monitoring program tacks water table

fluctuation between site and pumping well.• Assessing:

seasonal fluctuationsevidence of pumping influencechanges in flow direction

Program Challenges• Deep monitoring wells in confined aquifer, various well

diameters and materials.• Depth to water over 45 metres in one monitoring well.• Monitoring wells also used for water quality sampling,

other equipment installed (inertial or bladder pumps).• Monitoring program required long-term (>5 years). • Access difficult during winter months. • Accurate and dependable datalogger data critical for

site understanding and compliance.

Project Implementation

• Non-vented dataloggers chosen, likely price and availability main criteria considered.

• Dataloggers installed on various types of cable, rope and wire.

• No direct-read cables used, dataloggers needed to be removed at each download.

• Barologger located in monitoring well on site.

Expectation: Easy Valid Data

The Reality? Things Go Wrong.

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Datalogger dataManual measurements

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MW1 Actual Reported Data.• several datalogger failures and

replacements• two different models used• datalogger lost down well once• discrepancies in barometric

compensation• data correction unsuccessful

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Datalogger dataManual measurements

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MW2 Actual Reported Data.

exact same datalogger problems and responses

Results of 3 Year Monitoring Program

• Datalogger data riddled with errors and drift.• None of the datalogger water level

measurements can be used with confidence. • None of the objectives of the datalogger

monitoring program were achieved.• Large waste of time, effort and resources.

Directly attributable to poor project planning and implementation.

Revised Program• Clearly defined the purpose, objectives, and

acceptable limits for the monitoring results.• Equipment options examined and compared.• Datalogging equipment chosen to best match the

program objectives (now and in the future).• Installation details planned, managed and recorded,

quality materials chosen.• Datalogger data reviewed regularly for DRIFT.• Data verified and valid results reported.

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Datalogger dataManual measurements

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MW1 Actual Reported Data.• highly accurate vented datalogger installed• datalogger options and range matched to

conditions at monitoring well• QA/QC program in place with regular maintenance

and data review• result is accurate verifiable data

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Datalogger dataManual measurements

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MW2 Actual Reported Data.Detailed data can now be used to assess recharge response, potential pumping response, compared easily between wells to examine flow direction shifts, etc.

METHODS TO AVOID ERRORS

Try To Avoid These Situations!(mistakes we have already made, or found, in the field)

confusion(poor planning)

unanticipated conditions(that were in fact predictable)

(more mistakes ….)

installations that really don’t measure anything

(can you tell why?)

messy installations(again, poor planning)

Case Study Lessons Learned

1. Site-specific issues such as access, depth to water and installed sampling equipment made the original datalogging equipment a poor choice for the site.

2. The objectives of the monitoring program required that a high degree of data accuracy and reliability was needed from the datalogging equipment.

3. Equipment type and costs must be weighed against meeting monitoring program objectives.

4. Field and Data QA/QC programs are needed to minimize data errors.

Things To Consider1. Is the datalogger appropriate for the application?2. Is the datalogger being used appropriately? (beyond listed

range, sufficient accuracy, corrosive water, etc.)3. How is the datalogger installed in the well? (cable used,

properly secured at the well head, other equipment in well, expected water level changes, etc.)

4. Is the monitoring / maintenance appropriate? (frequency, methods, overlapping measurements, any calibration needed or completed)

5. Will the equipment selected meet your monitoring program objectives for data accuracy?

Like everything – the care you take in your Datalogger installation and use will reflect the accuracy of your data.

Planning the installation, and recording as much information as possible in the process, helps immensely.

Regularly review your data and learn to recognize drift and other data problems.

Additional Information

For more detailed help to eliminate datalogger use and installation errors see our selection of online courses.

hydrogresources.com

Response tests are completed at two wells at the same time using separate Dataloggers.

When you are trying to do 10 things at once…….

Some consistency helps!

WE HOPE YOU ENJOYED THIS COURSE – PLEASE ALSO

SEE OUR COURSES ON ELIMINATING DATALOGGER

ERRORS2014 ©HydroG Resources Group Inc.