The Unexploited Treasures of Hydrological Observations Beyond Streamflow for Catchment Modeling
Paul D. Wagner (Freie Universität Berlin, Christian-Albrechts-Universität zu Kiel)
Doris Duethmann (State Office for the Environment Rhineland-Palatinate, Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB))
Jens Kiesel (Christian-Albrechts-Universität zu Kiel, Stone Environmental)
Sandra Pool (University of Melbourne, Eawag - Swiss Federal Institute of Aquatic Science and Technology)
Markus Hrachowitz (TU Delft - Water Resources)
Serena Ceola (University of Bologna)
Anna Herzog (University of Potsdam)
Tobias Houska (Technische Universität Dresden, Justus Liebig University Giessen)
Ralf Loritz (Karlsruhe Institut für Technologie)
Diana Spieler (University of Calgary, Technische Universität Dresden)
Maria Staudinger (Universitat Zurich)
Larisa Tarasova (Helmholtz Centre for Environmental Research - UFZ)
Stephan Thober (Helmholtz Centre for Environmental Research - UFZ)
Nicola Fohrer (Christian-Albrechts-Universität zu Kiel)
Doerthe Tetzlaff (Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB), Humboldt-Universitat zu Berlin)
Thorsten Wagener (University of Potsdam)
Björn Guse (Christian-Albrechts-Universität zu Kiel)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
While measured streamflow is commonly used for hydrological model evaluation and calibration, an increasing amount of data on additional hydrological variables is available. These data have the potential to improve process consistency in hydrological modeling and consequently for predictions under change, as well as in data-scarce or ungauged regions. Here, we show how these hydrological data beyond streamflow are currently used for model evaluation and calibration. We consider storage and flux variables, namely snow, soil moisture, groundwater level, terrestrial water storage, evapotranspiration, and altimetric water level. We aim at summarizing the state-of-the-art and providing guidance for the use of additional hydrological variables for model evaluation and calibration. Based on a review of the current literature, we summarize observation methods and uncertainties of currently available data sets, challenges regarding their implementation, and benefits for model consistency. The focus is on catchment modeling studies with study areas ranging from a few km2 to ~500,000 km2. We discuss challenges for implementing alternative variables that are related to differences in the spatio-temporal resolution of observations and models, as well as to variable-specific features, for example, discrepancy between observed and simulated variables. We further discuss advancements required to deal with uncertainties of the hydrological data and to integrate multiple, potentially inconsistent datasets. The increased model consistency and improvement shown by most reviewed studies regarding the additional variables often come at the cost of a slight decrease in streamflow model performance.
help_outline