Sharing perceptual models of uncertainty: On the use of soft information about discharge data

Abstract

Many hydrologists face the situation of having little or no information about the uncertainty in the hydrometeorological data they are using (e.g., Addor et al., 2020). Data uncertainty is rarely communicated by monitoring agencies and data providers-and is often not available on request. This means that data users typically treat data as if they are error-free, whereas in reality there can be large uncertainties and errors (McMillan et al., 2012). A striking example is that 50% of 1523 site-months of discharge data were found to be unreliable in a recent evaluation of the National Ecological Observatory Network streamflow estimates