• Training on automated QA/QC of water level

  • 09-Jun-2021 to 09-Jun-2021

  • Webinar ( starts at 7.30 pm)

  • National

  • Webniar Learning

  • Water Quality-Transport Modelling

  • World Bank

Overview

The quality control procedures were used to identify the following common errors: 1) multiple observations at the exact same time, 2) data points that are exceptionally larger or smaller than nearly all other observations at that station, 3) excessively rapid changes in river level data, and 4) river levels that are indicated to be constant for too long that are likely the result of a stuck gauge.

Objective

Raw river level gauge data can occasionally have errors, such as those shown in Figure 1. Therefore, it is important to have quality control (QC) procedures in place, to flag bad data, as well as identify suspicious data. We employed several quality control procedures on several months of data from over 300 river level gauges. The data from each station were used to develop quality control thresholds for its own data; this assumes that there is a sufficient amount of data (e.g., several months), and that most data at each station are accurate.

Reference Material