EGU2020-6788, updated on 12 Jun 2020
https://doi.org/10.5194/egusphere-egu2020-6788
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Coupling of the global hydrodynamic CaMa-Flood model with the ECMWF land surface model HTESSEL.

Emanuel Dutra1, Dai Yamazaki2, and Cinzia Mazzetti3
Emanuel Dutra et al.
  • 1Instituto Dom Luiz, Faculty of Sciences, University of Lisbon, Lisbon, Portugal (endutra@fc.ul.pt)
  • 2Institute of Industrial Science, University of Tokyo, Tokyo, Japan (yamadai@rainbow.iis.u-tokyo.ac.jp)
  • 3European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom (Cinzia.Mazzetti@ecmwf.int)

Rivers are a key component of the land hydrological cycle and are crucial in many societal activities and natural hazards. Historically, hydrological modeling has not been tightly associated with numerical weather prediction (NWP) due to the different communities involved, requirements and underlying processes. The increased skill of NWP has led to the uptake of weather forecasts in hydrological models, in particular for flood forecasting. At the same time, developments of Earth System Models (ESM), mainly driven by the climate community have lead to a tight integration of the land hydrological cycle. River discharge is a key quality indicator of the integrated water budget, and its use as a forecast skill metric of NWP has a large potential. Freshwater input to the ocean is also important for the ocean circulation, which becomes increasingly relevant with the current atmosphere-ocean coupling in NWP. Considering all these points, the representation of rivers and floodplains dynamics and their associated impact on inland water evolution is of interest for a wide range of applications currently addressed by global NWP. 

In this study we present the key technical developments to achieve a 1-way and 2-way coupling between the global hydrodynamic CaMa-Flood model and the land surface component of the European Center for Medium-Range Weather Forecasts (ECMWF) HTESSEL. The models coupling followed a single executable strategy, i.e. avoiding external couplers. A coupling interface was developed for CaMa-Flood that is independent from the driving model, while keeping the stand-alone configuration. The coupling is flexible, allowing both models to run at different spatial resolutions. The implementation allows for a flexible integration of the models and independent development, and can be applied to other models.  

The current representation of inland water bodies in HTESSEL (lakes) was driven by their impact in NWP, but without the representation of rivers it was not possible to have a consistent water budget. The coupling of CaMa-Flood allows for an integrated earth system model approach. Several options for the 2-way interaction between CaMa-Flood flooded areas in HTESSEL inland water bodies were investigated. Despite the consistent results, several challenges are identified in the representation of inland water bodies, their variability and impact on water cycle.

How to cite: Dutra, E., Yamazaki, D., and Mazzetti, C.: Coupling of the global hydrodynamic CaMa-Flood model with the ECMWF land surface model HTESSEL., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6788, https://doi.org/10.5194/egusphere-egu2020-6788, 2020

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  • AC1: Chat discussion, Emanuel Dutra, 04 May 2020

    For future reference, the chat discussion (questions in bold)

    Emanuel Dutra IDL_LISBON (author) (08:21)Good Morning all,

    In this work we present the Coupling of the global hydrodynamic CaMa-Flood model with the ECMWF land surface model HTESSEL for an integrated earth system modeling approach. 1-way (runoff & inland water evaporation) and 2-way coupling (floodplains): tradeoffs between code flexibility, computational time, and processes representation.

    Luis Samaniego, UFZ (convener) (08:22) Are you planning to include lareg dams in your model?

    Hi Luis, the model has a simple module for that, so it is possible, but the problem to have information globally.

    JannisHoch (08:23) Hi Emanual, interesting work! I was wondering, how generic is your model coupling approach and how easily can CaMa-Flood be coupled with other LSM/HMs?

    Hi Jannis, We did our best to be as generic as possible, so it should be easy to couple to other LSMs (if the model is in fortran would be even easier)

    Sina Khatami UNIMELB (convener) (08:25) Thanks Emanuel for the slides. (slide 11) KGE metric already includes correlation and percent bias, wouldn't be informative for your work to look at the other component of the KGE as well, i.e. percent of variability error?

    Thanks Sina, yes of course. Those last results are mainly a generic evaluation (and hide many problems)

    Luis Samaniego, UFZ (convener) (08:25) IN slide 7, there is a drop in the timse series, what does it mean?

    Good question Luis, it's a drop in global flooded area, would need to investigate it in more detail

    JannisHoch (08:26) Hi Emanual, thanks. So I would need to implement other models into the (Fortran-based) executable?  And how much re-coding would be required then?

    No need to re-code your existing model to fortran. The interface routines to CaMa-Flood are only available in fortran (as the model is written in fortran), but it’s possible to write interfaces in other languages (C, C++, or even python).