Post-processing and quality control

This guide will highlight the individual steps required to analyze a dataset recovered by an ADCP and discuss necessary as well as optimal measures of quality control. Examples highlighting unique user cases are given together with methods for recovering impacted data as well as means of preventing further data loss in the future.

Sensor data check

Sensor data check

When starting the analysis of a dataset, the sensors can give a first indication of the quality of data retrieved. Their observations can be used to judge the true positioning and orientation of the instrument as well as identify if sudden and unplanned movement occurred. Relying on these sensors requires a successful execution of a Function test prior to the deployment.

Data quality parameters

Data quality parameters

This section discusses how to gain a better understanding of the environmental conditions during the deployment and determine the range up to which high quality data was obtained, by studying the received signal using amplitude and correlation.

Range

Range
Velocities

Velocities

This section describes how to assess the quality of velocity data by comparing measured currents to expected conditions and identifying anomalies in vertical and horizontal velocity profiles.
Waves

Waves
Common sources of data loss

Common sources of data loss

This section describes the most frequent causes of data loss in ADCP measurements, ranging from physical blockages and bio-fouling to dynamic issues such as drag down or tidal burial, that can reduce data quality or eliminate valid returns.
Special applications

Special applications