Our ability to fully and reliably observe and simulate the terrestrial hydrologic cycle is limited, and in-depth experimental studies cover only a tiny fraction of our landscape. On medieval maps, unexplored regions were shown as images of dragons—displaying a fear of the unknown. With time, cartographers dared to leave such areas blank, thus inviting explorations of what lay beyond the edge of current knowledge. In hydrology, we are still in a phase where maps of variables more likely contain hydrologic dragons than blank areas, which would acknowledge a lack of knowledge. In which regions is our ability to extrapolate well developed, and where is it poor? Where are available data sets informative, and where are they just poor approximations of likely system properties? How do we best identify and acknowledge these gaps to better understand and reduce the uncertainty in characterizing hydrologic systems? The accumulation of knowledge has been postulated as a fundamental mark of scientific advancement. In hydrology, we lack an effective strategy for knowledge accumulation as a community, and insufficiently focus on highlighting knowledge gaps where they exist. We propose two strategies to rectify these deficiencies. Firstly, the use of open and shared perceptual models to develop, debate, and test hypotheses. Secondly, improved knowledge accumulation in hydrology through a stronger focus on knowledge extraction and integration from available peer-reviewed articles. The latter should include metadata to tag journal articles complemented by a common hydro-meteorological database that would enable searching, organizing and analyzing previous studies in a hydrologically meaningful manner. This article is categorized under: Engineering Water > Planning Water Science of Water > Hydrological Processes Science of Water > Methods.