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Automating the quality screening of acoustic Doppler current profiler data

Acoustic Doppler Current Profiler (ADCP) measurements employ a large number of sensors and are deployed in a complex environment. Because of the complexity of the instrument and the environment it is sensing, its measurements are subject to a large number of factors that can potentially corrupt the resulting measurements synthesized from those sensor data. Therefore, the need to perform Quality Assurance (QA) and Quality Control (QC) processing of the data has long been recognized. Historically these techniques have been disparate and highly dependent on the instrument, deployment environment, and individuals processing the data. More recently there have been efforts to standardize the parameters and techniques used in the QA and QC screening of data. As these parameters for quality screening and assessment become more standardized, they become more and more amenable to automated processing. In this paper we provide an overview of the current standards and best practices for quality assurance of ADCP data, and generalize these standards and best practices into a high-level flow for processing data and assessing the quality of the resultant output data product. We provide an overview of a software package that automates the closely related problem of performing Quality Assurance on ADCP data collected for the purposes of measuring river discharge, and provide an overview of how this software solution could be adapted to satisfy the needs of the oceanographic community.