Articles | Volume 17, issue 22
https://doi.org/10.5194/bg-17-5787-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-17-5787-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Nov 2020
Research article |
| 24 Nov 2020
| 24 Nov 2020
Estimates of tree root water uptake from soil moisture profile dynamics
Conrad Jackisch
CORRESPONDING AUTHOR
Institute of Water and River Basin Management, Karlsruhe Institute of Technology (KIT),
Kaiserstraße 12, 76131 Karlsruhe, Germany
Department of Landscape Ecology and Environmental Systems Analysis, Institute of Geoecology,
Technische Universität Braunschweig, Langer Kamp 19c, 38106 Braunschweig, Germany
Faculty of Geosciences, Geoengineering and Mining, Technische Universität Bergakademie Freiberg,
Agricolastraße 22, 09599 Freiberg, Germany
Samuel Knoblauch
Institute of Water and River Basin Management, Karlsruhe Institute of Technology (KIT),
Kaiserstraße 12, 76131 Karlsruhe, Germany
Department of Biology, University of Greifswald, Friedrich-Ludwig-Jahn-Straße 15, 17489 Greifswald, Germany
Theresa Blume
Hydrology Section, GFZ German Research Centre for Geosciences, Helmholtz Centre Potsdam,
Telegrafenberg C4, 14473 Potsdam, Germany
Erwin Zehe
Institute of Water and River Basin Management, Karlsruhe Institute of Technology (KIT),
Kaiserstraße 12, 76131 Karlsruhe, Germany
Sibylle K. Hassler
Institute of Water and River Basin Management, Karlsruhe Institute of Technology (KIT),
Kaiserstraße 12, 76131 Karlsruhe, Germany
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Anne Hartmann, Markus Weiler, Konrad Greinwald, and Theresa Blume
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Manuscript not accepted for further review
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Samuel Schroers, Olivier Eiff, Axel Kleidon, Jan Wienhöfer, and Erwin Zehe
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-79, https://doi.org/10.5194/hess-2021-79, 2021
Manuscript not accepted for further review
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In this study we ask the basic question why surface runoff forms drainage networks and confluences at all and how structural macro form and micro topography is a result of thermodynamic laws. We find that on a macro level hillslopes should tend from negative exponential towards exponential forms and that on a micro level the formation of rills goes hand in hand with drainage network formation of river basins. We hypothesize that we can learn more about erosion processes if we extend this theory.
Nicolas Björn Rodriguez, Laurent Pfister, Erwin Zehe, and Julian Klaus
Hydrol. Earth Syst. Sci., 25, 401–428, https://doi.org/10.5194/hess-25-401-2021, https://doi.org/10.5194/hess-25-401-2021, 2021
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Different parts of water have often been used as tracers to determine the age of water in streams. The stable tracers, such as deuterium, are thought to be unable to reveal old water compared to the radioactive tracer called tritium. We used both tracers, measured in precipitation and in a stream in Luxembourg, to show that this is not necessarily true. It is, in fact, advantageous to use the two tracers together, and we recommend systematically using tritium in future studies.
Ralf Loritz, Markus Hrachowitz, Malte Neuper, and Erwin Zehe
Hydrol. Earth Syst. Sci., 25, 147–167, https://doi.org/10.5194/hess-25-147-2021, https://doi.org/10.5194/hess-25-147-2021, 2021
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This study investigates the role and value of distributed rainfall in the runoff generation of a mesoscale catchment. We compare the performance of different hydrological models at different periods and show that a distributed model driven by distributed rainfall yields improved performances only during certain periods. We then step beyond this finding and develop a spatially adaptive model that is capable of dynamically adjusting its spatial model structure in time.
Anne Hartmann, Markus Weiler, and Theresa Blume
Earth Syst. Sci. Data, 12, 3189–3204, https://doi.org/10.5194/essd-12-3189-2020, https://doi.org/10.5194/essd-12-3189-2020, 2020
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Hydrol. Earth Syst. Sci., 24, 5713–5744, https://doi.org/10.5194/hess-24-5713-2020, https://doi.org/10.5194/hess-24-5713-2020, 2020
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We investigated the interactions between streams and their adjacent hillslopes in terms of water flow. It could be revealed that soil structure has a strong influence on how hillslopes connect to the streams, while the groundwater table tells us a lot about when the two connect. This observation could be used to improve models that try to predict whether or not hillslopes are in a state where a rain event will be likely to produce a flood in the stream.
Nils Hinrich Kaplan, Theresa Blume, and Markus Weiler
Hydrol. Earth Syst. Sci., 24, 5453–5472, https://doi.org/10.5194/hess-24-5453-2020, https://doi.org/10.5194/hess-24-5453-2020, 2020
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In recent decades the demand for detailed information of spatial and temporal dynamics of the stream network has grown in the fields of eco-hydrology and extreme flow prediction. We use temporal streamflow intermittency data obtained at various sites using innovative sensing technology as well as spatial predictors to predict and map probabilities of streamflow intermittency. This approach has the potential to provide intermittency maps for hydrological modelling and management practices.
Benjamin Fersch, Till Francke, Maik Heistermann, Martin Schrön, Veronika Döpper, Jannis Jakobi, Gabriele Baroni, Theresa Blume, Heye Bogena, Christian Budach, Tobias Gränzig, Michael Förster, Andreas Güntner, Harrie-Jan Hendricks Franssen, Mandy Kasner, Markus Köhli, Birgit Kleinschmit, Harald Kunstmann, Amol Patil, Daniel Rasche, Lena Scheiffele, Ulrich Schmidt, Sandra Szulc-Seyfried, Jannis Weimar, Steffen Zacharias, Marek Zreda, Bernd Heber, Ralf Kiese, Vladimir Mares, Hannes Mollenhauer, Ingo Völksch, and Sascha Oswald
Earth Syst. Sci. Data, 12, 2289–2309, https://doi.org/10.5194/essd-12-2289-2020, https://doi.org/10.5194/essd-12-2289-2020, 2020
Uwe Ehret, Rik van Pruijssen, Marina Bortoli, Ralf Loritz, Elnaz Azmi, and Erwin Zehe
Hydrol. Earth Syst. Sci., 24, 4389–4411, https://doi.org/10.5194/hess-24-4389-2020, https://doi.org/10.5194/hess-24-4389-2020, 2020
Short summary
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In this paper we propose adaptive clustering as a new method for reducing the computational efforts of distributed modelling. It consists of identifying similar-acting model elements during the runtime, clustering them, running the model for just a few representatives per cluster, and mapping their results to the remaining model elements in the cluster. With the example of a hydrological model, we show that this saves considerable computation time, while largely maintaining the output quality.
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Short summary
We developed software to calculate the root water uptake (RWU) of beech tree roots from soil moisture dynamics. We present our approach and compare RWU to measured sap flow in the tree stem. The study relates to two sites that are similar in topography and weather but with contrasting soils. While sap flow is very similar between the two sites, the RWU is different. This suggests that soil characteristics have substantial influence. Our easy-to-implement RWU estimate may help further studies.
We developed software to calculate the root water uptake (RWU) of beech tree roots from soil...
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