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On doing hydrology with dragons: Realizing the value of perceptual models and knowledge accumulation

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Abstract 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
(a) The Fra Mauro world map (Italy, 1459) shows seemingly complete knowledge of the world. However, on closer inspection, maps like this one included statements like HIC SUNT LEONES and images of monsters in unexplored regions. (b) The Salviati Planisphere is a world map (Spain, 1525) without imagined representations, highlighting knowledge gaps. Source: Wikipedia, https://en.wikipedia.org/wiki/World_map (accessed March 2020)
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Number of papers listed in Web of Science (March 2021) for the different journals. Papers are accumulated by decade from the 1960s to the 2010s (even if the journal started sometime during a decade). Asterisk shows that the year 2020 only reflects that year. The journals and their individual decadal numbers are as follows: Water Resources Research (119, 202, 227, 338, 385, 563, 647), Journal of Hydrology (−, 103, 166, 231, 359, 735, 1266), Advances in Water Resources (−, 23, 26, 36, 115, 195, 234), Hydrological Science Journal (−, −, 72, 52, 79, 150, 217), Hydrological Processes (−, −, 21, 83, 281, 358, 306), Hydrology and Earth System Sciences (−, −, −, 60, 94, 306, 315). Hydrological Sciences Journal was searched as “Hydrological Sciences Journal – Journal des Sciences Hydrologiques”
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Two perceptual models of large‐scale hydrologic models are shown at the top. On the left are four perceptual models of the carbonate rock regions across Europe/North Africa/Middle East by Hartmann et al. (2015). The different perceptual models are derived based on the expected differences between carbonate rock regions, including relative differences in the degree of karstification and the amount of storage present. The top right figure is the perceptual model underlying the global hydrological model PCR‐GLOBWB (©Marc Bierkens). The bottom graphs shows how the differences in perceptual models propagate into differences in recharge predictions of the simulation models (Hartmann et al., 2015)
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We suggest moving the perceptual model from its often implicit side‐role, to an explicit central role for both experimentalists and modelers, that is, for both deciding where and what to measure, as well as how to simplify reality in our simulation models (Perceptual model picture taken from Loritz et al., 2017; reality picture taken by Fabian Nippgen; model image from Cherkauer et al., 2003; character icons are by iconify obtained from iconfinder.com under the creative commons license)
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Science of Water > Hydrological Processes
Engineering Water > Planning Water

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