River forecasts require large amounts of weather and discharge data to support the modeling and communities. We currently monitor stream discharge and water level from 457 hydrometric stations and precipitation and air temperature from 387 weather stations. Data from all stations must be quality-controlled and assembled in a very short time, which is no small task considering the amount of data, data quality challenges, and the need to assemble multiple types of data across several data pipelines. To overcome them, we have developed both a Climate Data Management tool and a Hydrometric Data Quality Control tool using R Shiny App. Both tools provide automated corrections and allow users to conduct manual corrections using interactive, graphical interfaces. Users can then export the data for further modeling and monitoring. In terms of near real-time monitoring, we produce a return period map showing current streamflow conditions, which helps the team quickly identify stations at high flow conditions. Behind the scenes, several scripts run hourly to download and process data for multiple uses, such as the map table, observed hydrographs, and summarized statistics. Maps of daily air temperature and precipitation for both observed and forecasted values are updated on the web page. In addition, we have been monitoring the 24-h precipitation return period based on our own precipitation frequency analysis from fire weather stations and the results from the Environment and Climate Change Canada. All the above implemented new processes and tools have helped us to get reliable data or statistics in minutes.
