A strategy for quality controlling hourly rainfall observations and its impact on hourly streamflow simulations

Abstract

Real-time streamflow forecasts are often produced at hourly and shorter time steps. To calibrate the hydrological models used to generate forecasts, archives of streamflow and rainfall observations are essential. The collection and archiving of sub-daily rain gauge observations is typically automated. Errors in rainfall observations can arise for many reasons and may manifest as anomalously high or low values for a single observation or longer periods of time. Quality control of sub-daily rainfall is onerous because of the large volume of data, and sub-daily rainfall data are frequently not quality-controlled when the data are archived in real-time. Errors in rainfall observations used to ca..