EGU2020-7549, updated on 21 Aug 2020
https://doi.org/10.5194/egusphere-egu2020-7549
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Similarities and differences among fifteen global water models in simulating the vertical water balance

Camelia-Eliza Telteu1, Hannes Müller Schmied2, Wim Thiery3, Guoyong Leng4, Peter Burek5, Xingcai Liu4, Julien Eric Stanislas Boulange6, Lauren Paige Seaby7, Manolis Grillakis8, Yusuke Satoh6, Oldrich Rakovec9, Tobias Stacke10, Jinfeng Chang5,11, Niko Wanders12, Fulu Tao13,14,15, Ran Zhai13,14, Harsh Lovekumar Shah16, Tim Trautmann1, Ganquan Mao17, Aristeidis Koutroulis8, Yadu Pokhrel18, Luis Samaniego9, Yoshihide Wada5, Vimal Mishra16, Junguo Liu17, Simon Newland Gosling19, Jacob Schewe7, and Fang Zhao20
Camelia-Eliza Telteu et al.
  • 1Institute of Physical Geography, Goethe University Frankfurt, Frankfurt am Main, Germany (telteu@em.uni-frankfurt.de, hannes.mueller.schmied@em.uni-frankfurt.de, t.trautmann@em.uni-frankfurt.de)
  • 2Senckenberg Leibniz Biodiversity and Climate Research Center, Frankfurt am Main, Germany
  • 3Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel, Brussels, Belgium (wim.thiery@vub.be)
  • 4Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China (lenggy@igsnrr.ac.cn, xingcailiu@igsnrr.ac.cn)
  • 5International Institute for Applied Systems Analysis, Laxenburg, Austria (burek@iiasa.ac.at, changj@iiasa.ac.at, wada@iiasa.ac.at)
  • 6National Institute for Environmental Studies, Tsukuba, Japan (boulange.julien@nies.go.jp, satoh.yusuke@nies.go.jp)
  • 7Potsdam Institute for Climate Impact Research, Potsdam, Germany (seaby@pik-potsdam.de, jacob.schewe@pik-potsdam.de)
  • 8School of Environmental Engineering, Technical University of Crete, Chania, Greece (manolis@hydromech.gr, aris@hydromech.gr)
  • 9Helmholtz Centre for Environmental Research, Leipzig, Germany (oldrich.rakovec@ufz.de, luis.samaniego@ufz.de)
  • 10Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Geesthacht, Germany (tobias.stacke@hzg.de)
  • 11Laboratoire des Sciences du Climat et de l’Environnement, Gif-sur-Yvette, France
  • 12Department of Physical Geography, Utrecht University, Utrecht, Netherlands (n.wanders@uu.nl)
  • 13Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China (taofl@igsnrr.ac.cn, zhair.15b@igsnrr.ac.cn)
  • 14College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
  • 15Natural Resources Institute Finland, Helsinki, Finland
  • 16Indian Institute of Technology Gandhinagar, Palaj, Gandhinagar, India (harsh.lovekumar.shah@iitgn.ac.in, vmishra@iitgn.ac.in)
  • 17School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China (maogq@sustech.edu.cn, liujg@sustech.edu.cn)
  • 18Department of Civil and Environmental Engineering, Michigan State University, East Lansing, Michigan, United States of America (ypokhrel@egr.msu.edu)
  • 19School of Geography, University of Nottingham, Nottingham, United Kingdom of Great Britain and Northern Ireland (Simon.Gosling@nottingham.ac.uk)
  • 20School of Geographic Sciences, East China Normal University (fzhao@geo.ecnu.edu.cn)

Hydrological models have been developed in response to the need to understand the complex water cycle of the Earth and to assess its interaction with historical and future climate scenarios. In the global water sector of the Inter-Sectoral Impact Model Intercomparison Project phase 2b (ISIMIP2b), six land surface models (LSMs), eight hydrological models (GHMs), and one dynamic vegetation model (DGVM) are contributing with transient simulations spanning from 1660 to 2300. The model simulations follow a common protocol and are driven by common bias adjusted climate model outputs combined with plausible socio-economic scenarios and representative concentration pathways. The main goal of this study is to highlight similarities and differences among these models in simulating the vertical water balance. The main similarity of these models consists in the water cycle simulation, even if the models have been developed for different purposes such as energy cycle (LSMs), water cycle (GHMs), or vegetation cycle (DGVM) simulation. In particular, we address the following research question: 1) what equations are used to compute water storages and water fluxes; 2) how different are the equations among the models; 3) how the equations were adjusted; 4) how many parameters are used by the models; 5) how often the parameters are used; 6) how similar or different are the parameters among the models. To this end, we apply a standard writing style of the water storages and water fluxes included in the models, to easily identify the similarities and differences among them. Most of the models include in their structure the canopy, soil, and snow storages, and almost half of them include the groundwater storage. Furthermore, we find that: 1) a model needs a very good documentation, this would help to easily identify and understand the equations in the code; 2) some modelers teams use common approaches resulting in similar equations of water storages or water fluxes, but different models structures still lead to different models results; 3) collaboration and communication among the modelers are necessary, on the one hand, for the realization of the models standard writing style, and on the other hand, for a better understanding of the models themselves, especially their strengths, limitations and results. Overall, our results (i) help to better explain the different models results and to attribute these to the differences in simulating specific processes; (ii) contribute to the remarkable efforts in creating a common protocol and a common input datasets for well-defined simulations; (iii) foster a better understanding of how the models work and finding new ways of improvement and development.

How to cite: Telteu, C.-E., Müller Schmied, H., Thiery, W., Leng, G., Burek, P., Liu, X., Boulange, J. E. S., Seaby, L. P., Grillakis, M., Satoh, Y., Rakovec, O., Stacke, T., Chang, J., Wanders, N., Tao, F., Zhai, R., Shah, H. L., Trautmann, T., Mao, G., Koutroulis, A., Pokhrel, Y., Samaniego, L., Wada, Y., Mishra, V., Liu, J., Newland Gosling, S., Schewe, J., and Zhao, F.: Similarities and differences among fifteen global water models in simulating the vertical water balance, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7549, https://doi.org/10.5194/egusphere-egu2020-7549, 2020

How to cite: Telteu, C.-E., Müller Schmied, H., Thiery, W., Leng, G., Burek, P., Liu, X., Boulange, J. E. S., Seaby, L. P., Grillakis, M., Satoh, Y., Rakovec, O., Stacke, T., Chang, J., Wanders, N., Tao, F., Zhai, R., Shah, H. L., Trautmann, T., Mao, G., Koutroulis, A., Pokhrel, Y., Samaniego, L., Wada, Y., Mishra, V., Liu, J., Newland Gosling, S., Schewe, J., and Zhao, F.: Similarities and differences among fifteen global water models in simulating the vertical water balance, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7549, https://doi.org/10.5194/egusphere-egu2020-7549, 2020

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