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Incorporate some programmatic checks into the program that allow for qa/qc of the final data, prior to it being entered into the database.
significant change in rolling variance in the time series - we have been having a lot of issues with null units in many of our transducer downloads; if the processing misinterprets these units, it can cause a huge difference in the observable variance of the time series.
water level above the casing top elevation - keep in mind that at a few locations, this is possible (ex. transducer in a piezometer that can become completely submerged in a pool)
a check for negative, null, or unrealistic water elevation values
I found that temperature can be used to eliminate spikes caused by freezing conditions or situations where the instrument is out of water
a way to easily identify gaps in the record.
check in correlation between output columns
The text was updated successfully, but these errors were encountered:
Incorporate some programmatic checks into the program that allow for qa/qc of the final data, prior to it being entered into the database.
The text was updated successfully, but these errors were encountered: