Abstract
Abstract. We here present GLOFRIM, a globally applicable computational framework for integrated hydrological–hydrodynamic modelling. GLOFRIM facilitates spatially explicit coupling of hydrodynamic and hydrologic models and caters for an ensemble of models to be coupled. It currently encompasses the global hydrological model PCR-GLOBWB as well as the hydrodynamic models Delft3D Flexible Mesh (DFM; solving the full shallow-water equations and allowing for spatially flexible meshing) and LISFLOOD-FP (LFP; solving the local inertia equations and running on regular grids). The main advantages of the framework are its open and free access, its global applicability, its versatility, and its extensibility with other hydrological or hydrodynamic models. Before applying GLOFRIM to an actual test case, we benchmarked both DFM and LFP for a synthetic test case. Results show that for sub-critical flow conditions, discharge response to the same input signal is near-identical for both models, which agrees with previous studies. We subsequently applied the framework to the Amazon River basin to not only test the framework thoroughly, but also to perform a first-ever benchmark of flexible and regular grids on a large-scale. Both DFM and LFP produce comparable results in terms of simulated discharge with LFP exhibiting slightly higher accuracy as expressed by a Kling–Gupta efficiency of 0.82 compared to 0.76 for DFM. However, benchmarking inundation extent between DFM and LFP over the entire study area, a critical success index of 0.46 was obtained, indicating that the models disagree as often as they agree. Differences between models in both simulated discharge and inundation extent are to a large extent attributable to the gridding techniques employed. In fact, the results show that both the numerical scheme of the inundation model and the gridding technique can contribute to deviations in simulated inundation extent as we control for model forcing and boundary conditions. This study shows that the presented computational framework is robust and widely applicable. GLOFRIM is designed as open access and easily extendable, and thus we hope that other large-scale hydrological and hydrodynamic models will be added. Eventually, more locally relevant processes would be captured and more robust model inter-comparison, benchmarking, and ensemble simulations of flood hazard on a large scale would be allowed for.
Highlights
In the latter half of the last century, losses due to riverine floods increased greatly, leading to economic losses of more than USD 1 billion and 220 000 casualties since 1980 (Munich Re, 2013; Visser et al, 2012)
Besides being openly accessible and adaptable and extendable to the user’s preferences or individual modelling requirements, GLOFRIM contains a number of additional advantages: first, by having PCR-GLOBWB, or any other global hydrological model, as the hydrological output creator, the framework can be applied anywhere on the globe given a hydrodynamic schematization; second, models to be coupled may be selected depending on their local performance, possibly capturing more relevant processes; third, the spatially explicit coupling scheme can be extended to a full feedback loop between hydrology and hydrodynamic steps, incorporating important groundwater infiltration and evaporation processes; fourth, by guaranteeing identical hydrological forcing, applying the computational framework facilitates benchmarking of hydrodynamic models by eliminating sources of difference, potentially supporting hydrodynamic ensemble modelling approaches
It was concluded that for applications with low Froude numbers (Fr 0.5), such as the synthetic test case used here, no significant differences occur between models solving the local inertia equations (LIEs) and those solving the full dynamics of the shallowwater equation (SWE)
Summary
In the latter half of the last century, losses due to riverine floods increased greatly, leading to economic losses of more than USD 1 billion and 220 000 casualties since 1980 (Munich Re, 2013; Visser et al, 2012). No validation of simulated inundation extent was performed as Hoch et al (2017a) already showed good agreement of results obtained with DFM for the same study domain This openly available computational framework makes a valuable contribution to current inundation modelling on the large scale by enhancing the integration of hydrological and hydrodynamic model processes, which eventually may lead to improved decision-making and planning of adaption and mitigation measures
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