Towards Consistent Multi-Scale Flood Modelling Using an Integrated Hydrological–Hydrodynamic Framework

Representing hydrological and hydraulic processes consistently across spatial scales remains a major challenge for large-scale flood modelling. Besides using simplified routing schemes that struggle to accurately represent in-channel river flow dynamics, most large-scale hydrological models adopt a Cartesian-grid discretization scheme due to their compatibility with widely available gridded datasets. However, this grid-based structure poorly captures river geometry and oversimplifies natural drainage boundaries, leading to scale-dependent biases in runoff production and streamflow simulations, commonly referred to as the “catchment size problem”. In contrast, hydrodynamic models implement more physically-based routing schemes with fine-scale geometric representation of river channels, but face important parametrization challenges at larger scales. To address these challenges, we introduce an integrated hydrological–hydrodynamic (H&H) modelling framework that enables a seamless coupling between coarse-resolution gridded hydrological modelling and fine-scale vector-based river routing, leveraging a sub-grid representation of the river network derived from high-resolution topography. Notably, sub-grid information is propagated into the hydrological model by replacing regular grid-cell areas with realistic drainage areas derived from sub-grid topography, thereby addressing the aforementioned “catchment size problem”. The integrated H&H framework is implemented within the SMASH modelling platform (Spatially distributed Modelling and ASsimilation for Hydrology, https://smash.recover.inrae.fr/). For this application, we coupled the grid-based conceptual hydrological model GR4 to a vector-based hydrodynamic model solving a simplification of the 1D shallow water equations without convective acceleration terms. We evaluated this framework over the Garonne River catchment (France, ~50,000 km²) using the MERIT digital elevation model (resampled at 100 m) and the reference national river network BD TOPAGE®. We conducted H&H simulations across three spatial resolutions: 1 km, 5 km, and 10 km, where we considered the 1 km configuration as a baseline and kept the same hydrological and hydrodynamic parametrization across resolutions (no recalibration): semi-distributed hydrological parameters, uniform channel friction, and simplified rectangular channel geometry where widths and depths are estimated from geomorphological relationships, and bathymetry is subsequently derived from geomorphological depths and elevation. Results show that the sub-grid river representation maintains a consistently high spatial accuracy across spatial scales, with mean separation distance from the reference hydrography of around 25 m and minimal omission of the mapped network (<6%). This geometric accuracy consistency is further supported by H&H simulations showing robust preservation of flow timing across scales. Furthermore, H&H simulations demonstrate improved consistency across spatial scales when leveraging sub-grid drainage areas, compared to the conventional grid-based delineation method that shows scale-dependent volume bias. This bias reflects the impact of drainage area misrepresentation as resolution is coarsened, which results in biased precipitation volumes and propagates into runoff production. Overall, these results highlight the potential of the proposed integrated H&H framework to enable scalable hydrological–hydrodynamic modeling at large scales and provide a flexible foundation for leveraging increasingly available multi-source water surface observations, such as satellite altimetry (e.g., SWOT, ICESat-2), to infer key H&H model parameters and enhance modeling accuracy in data-sparse regions.