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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 12 Mar 2019

Research article | 12 Mar 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Integrating large-scale hydrology and hydrodynamics for nested flood hazard modelling from the mountains to the coast

Jannis M. Hoch1,2,a, Dirk Eilander2,3,a, Hiroaki Ikeuchi3,4,a, Fedor Baart2, and Hessel C. Winsemius2,5 Jannis M. Hoch et al.
  • 1Department of Physical Geography, Utrecht University, P.O. Box 80115, 3508 TC Utrecht, the Netherlands
  • 2Deltares, P.O. Box 177, 2600 MH Delft, the Netherlands
  • 3Institute for Environmental Studies, VU Amsterdam, 1081 HV Amsterdam, the Netherlands
  • 4Department of Civil Engineering, University of Tokyo, Tokyo, 153-8505, Japan
  • 5Department of Civil Engineering, TU Delft, 2628 CN Delft, the Netherlands
  • aEqual author contribution

Abstract. Fluvial flood events were, are, and will remain a major threat to people and infrastructure. Typically, flood hazard is driven by hydrologic or river routing and floodplain flow processes. Since they are often simulated by different models, coupling these models may be a viable way to increase the physicality of simulated inundation estimates. To facilitate coupling different models and integrating across flood hazard processes, we here present GLOFRIM 2.0, a globally applicable framework for integrated hydrologic-hydrodynamic modelling. We then tested the hypothesis that smart model coupling can advance inundation modelling in the Amazon and Ganges basins. By means of GLOFRIM, we coupled the global hydrologic model PCR-GLOBWB with the hydrodynamic models CaMa-Flood and LISFLOOD-FP. Results show that replacing the kinematic wave approximation of the hydrologic model with the local inertia equation of CaMa-Flood greatly enhances accuracy of peak discharge simulations as expressed by an increase of NSE from 0.48 to 0.71. Flood maps obtained with LISFLOOD-FP improved representation of observed flood extent (critical success index C = 0.46), compared to downscaled products of PCR-GLOBWB and CaMa-Flood (C = 0.30 and C = 0.25, respectively). Results confirm that model coupling can indeed be a viable way forward towards more integrated flood simulations. However, results also suggest that the accuracy of coupled models still largely depends on the model forcing. Hence, further efforts must be undertaken to improve the magnitude and timing of simulated runoff. Besides, flood risk is, particularly in delta areas, driven by coastal processes. A more holistic representation of flood processes in delta areas, for example by incorporating a tide and surge model, must therefore be a next development step of GLOFRIM, making even more physically-robust estimates possible for adequate flood risk management practices.

Jannis M. Hoch et al.
Interactive discussion
Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Jannis M. Hoch et al.
Model code and software

GLOFRIM 2.0 J. Hoch, D. Eilander, H. Ikeuchi, F. Baart, J. Neal, P. Bates, H. Winsemius, R. van Beek, and M. Bierkens

Jannis M. Hoch et al.
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Publications Copernicus
Short summary
Flood events are often complex in their origin and dynamics which should be represented in models aiming at simulating past and future events. However, it is often the case that models are designed for one specific purpose, hampering holistic flood simulations. To overcome this, we developed GLOFRIM 2.0 which allows the user to combine several models in a plug-and-play manner. It is then possible to couple models depending on the envisaged purpose and with varying complexity.
Flood events are often complex in their origin and dynamics which should be represented in...