REAL-TIME QUALITY CONTROL OF STREAMFLOW DATA—A SIMULATION STUDY1

ABSTRACT: The problem of real-time quality control of streamflow data is addressed. Five methods are investigated via a Monte-Carlo simulation experiment based on streamflow data from Bird Creek basin in Oklahoma. The five methods include three deterministic approaches and two statistical approaches. The relative performance of the investigated methods is evaluated under hypothesized random mechanism generating isolated outliers. The deterministic method based on streamflow gradient analysis and the statistical method based on forecast residual analysis perform best in detecting such outliers.