Quantifying Uncertainty in Streamflow Records

Uncertainty in hydrometric data is a fact of life. Basic assumptions about the nature of this uncertainty are necessary in every analysis of hydrometric data, and an understanding of the variability of uncertainty can facilitate the effective use of hydrologic information. For most of the twentieth century there has been little change in hydrometric methods and many analysts explicitly or implicitly assume that the uncertainty has not changed over the period of record. We argue that there is substantial variability in the magnitude of uncertainty in published streamflow records that is not transparent to data users. Quantifying uncertainty is particularly important in the context of the current changes in hydrometric technology and in the increasing integration of data sets from multiple providers. We recommend best practices for identifying uncertainty in field notes and propagating that observational uncertainty through the data production process. We suggest both field and reanalysis studies that could be undertaken to improve understanding of hydrometric uncertainty. We also recommend improvements in management practices, including preservation of relevant metadata and a suitable period of overlap for new and old observing systems to allow assessment of the effects of changing technology.