Abstract
Abstract. Fluvial flood events are 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 integration of different physical drivers 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 in the Nash–Sutcliffe efficiency (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. In addition, 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.
Highlights
The number of exposed population and assets as well as casualties and economic damage due to flooding increased greatly in recent decades (Hirabayashi et al, 2013; Jongman et al, 2012; Ward et al, 2013; Winsemius et al, 2016)
We designed two separate test cases to achieve the research objectives: while in test A we assess the opportunities and challenges for advancing the simulation of flood wave propagation by coupling large-scale hydrology with a routing model, test B aims at investigating the benefit of nesting a high-resolution 1-D–2-D hydrodynamic model into large-scale models for improved local inundation mapping
PCR → CMF, in turn, is less biased compared to PCR-DynRout
Summary
The number of exposed population and assets as well as casualties and economic damage due to flooding increased greatly in recent decades (Hirabayashi et al, 2013; Jongman et al, 2012; Ward et al, 2013; Winsemius et al, 2016). GLOFRIM, a framework for integrated hydrologic–hydrodynamic modelling, was developed and applied recently (Hoch et al, 2017b, 2018) Both studies coupled the coarse-resolution global hydrologic model PCR-GLOBWB (Sutanudjaja et al, 2018) with the fine-resolution hydrodynamic models Delft3D Flexible Mesh (Kernkamp et al, 2011) and LISFLOOD-FP (Bates et al, 2010) set up for a fraction of the studied basin only. These studies showed that coupling hydrologic processes with more advanced hydrodynamic processes improves both representation of inundation along reaches as well as the simulation of flood wave propagation.
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