As part of the data verification and quality assurance process, all data points on the Water Measurement Information System (WMIS) are assigned a quality code to indicate the reliability of the data.
Historical data
Some monitoring sites on WMIS have incredibly long periods of record, with some having data as far back as the late 1800s. In many cases, the exact methodology of how this data was collected and quality checked is uncertain.
Telemetered data
Some monitoring sites and bores telemeter data directly into our system and appear on WMIS prior to data verification. A specific quality code is assigned automatically by the system to inform WMIS users that the data has not yet been checked or edited.
Instrument calibration
The verification of time series data generally starts with the hydrographer or field technician downloading data from loggers in the field and comparing this data to field observations taken at the same time. If the logged data and field observations align, then minimal data editing is required, and the data is considered reliable. If there is a significant difference between the logged data and field observations, the sensor is recalibrated, and the data is edited and quality coded appropriately.
External influences
Sometimes external influences will affect the quality of the data. Examples of external influences are:
- siltation, tree roots and other environmental factors
- bore casing blocked or perforated
- water diversions/pumping
- vandalism
- floods
Quality codes explain the quality of measurement recorded. For example, quality code 96 is used when the daily read records have been substituted for continuous record lost due to natural cause/vandalism.
Data infilling
Where data has been lost, data infilling can occur from correlations with nearby stations.
Data aggregation
When aggregating data (e.g. daily mean or totals), the calculated value is still assigned a quality code to indicate data reliability. This quality code is assigned by looking at all the points to be aggregated and taking the highest (worst) quality code associated with them. Even if only one of the data points has a bad quality code, it is important to remember that your aggregated value is only as reliable as your worst quality data point for that period.
Why does it seem like there are gaps in the data?
There are several reasons why there may appear to be gaps in the data record:
• Intermittent monitoring
• Monitoring station may be offline
• Rating tables suspended or exceeded
• Dry sites – sometime water quality samples are not collected if a site is dry.
• Equipment has broken down
How current is your data?
Some monitoring stations are no longer active
Data is downloaded by hydrographers or field technicians at site visits. The frequency of these visits varies depending on the purpose of monitoring at a site.
Reviewed 11 June 2024