With the upcoming SWOT satellite mission, which should provide spatially dense river surface elevation, width and slope observations globally, comes the opportunity to assimilate such data into hydrodynamic models, from the reach scale to the hydrographic network scale. Based on the HiVDI (Hierarchical Variational Discharge Inversion) modeling strategy (Larnier et al. [1]), this study tackles the forward and inverse modeling capabilities of distributed channel parameters and multiple inflows (in the 1D Saint-Venant model) from multisatellite observations of river surface. It is shown on synthetic cases that the estimation of both inflows and distributed channel parameters (bathymetry-friction) is achievable with a minimum spatial observability between inflows as long as their hydraulic signature is sampled. Next, a real case is studied: 871 km of the Negro river (Amazon basin) including complex multichannel reaches, 21 tributaries and backwater controls from major confluences. An effective modeling approach is proposed using (i) WS elevations from ENVISAT data and dense in situ GPS flow lines (Moreira [2]), (ii) average river top widths from optical imagery (Pekel et al. [3]), (iii) upstream and lateral flows from the MGB large-scale hydrological model (Paiva et al. [4]). The calibrated effective hydraulic model closely fits satellite altimetry observations and presents real like spatial variabilities; flood wave propagation and water surface observation frequential features are analyzed with identifiability maps following Brisset et al. [5]. Synthetic SWOT observations are generated from the simulated flowlines and allow to infer model parameters (436 effective bathymetry points, 17 friction

Abstract. This contribution presents a novel multi-dimensional (multi-D) hydraulic-hydrological numerical model with variational data assimilation capabilities. It allows multi-scale modeling over large domains, combining in situ observations with high-resolution hydro-meteorology and satellite data. The multi-D hydraulic model relies on the 2D shallow water equations solved with a 1D2D adapted single finite volume solver. 1Dlike reaches are built through meshing methods that cause the 2D solver to degenerate into 1D. They are connected to 2D portions that act as local zooms, for modeling complex flow zones such as floodplains and confluences, via 1Dlike-2D interfaces. An existing parsimonious hydrological model, GR4H, is implemented and coupled to the hydraulic model. The forward-inverse multi-D computational model is successfully validated on academic and real cases of increasing complexity, including using the second order scheme version. Assimilating multiple observations of flow signatures leads to accurate inferences of multi-variate and spatially distributed parameters among bathymetry-friction, upstream/lateral hydrographs, and hydrological model parameters. This notably demonstrates the possibility for information feedback towards upstream hydrological catchments, that is backward hydrology. A 1Dlike model of part of the Garonne river is built and accurately reproduces flow lines and propagations of a 2D reference model. A multi-D model of the complex Adour basin network, inflowed by the semi-distributed hydrological model, is built. High resolution flow simulations are obtained on a large domain, including fine zooms on floodplains, with a relatively low computational cost since the network contains mostly 1Dlike reaches. The current work constitutes an upgrade of the Dassflow computational platform. The adjoint of the whole tool chain is obtained by automatic code differentiation.

Abstract. This contribution presents a novel multi-dimensional (multi-D) hydraulic–hydrological numerical model with variational data assimilation capabilities. It allows multi-scale modeling over large domains, combining in situ observations with high-resolution hydrometeorology and satellite data. The multi-D hydraulic model relies on the 2D shallow-water equations solved with a 1D–2D adapted single finite-volume solver. One-dimensional-like reaches are built through meshing methods that cause the 2D solver to degenerate into 1D. They are connected to 2D portions that act as local zooms, for modeling complex flow zones such as floodplains and confluences, via 1D-like–2D interfaces. An existing parsimonious hydrological model, GR4H, is implemented and coupled to the hydraulic model. The forward-inverse multi-D computational model is successfully validated on virtual and real cases of increasing complexity, including using the second-order scheme version. Assimilating multiple observations of flow signatures leads to accurate inferences of multi-variate and spatially distributed parameters among bathymetry friction, upstream and lateral hydrographs and hydrological model parameters. This notably demonstrates the possibility for information feedback towards upstream hydrological catchments, that is, backward hydrology. A 1D-like model of part of the Garonne River is built and accurately reproduces flow lines and propagations of a 2D reference model. A multi-D model of the complex Adour basin network, with inflow from the semi-distributed hydrological model, is built. High-resolution flow simulations are obtained on a large domain, including fine zooms on floodplains, with a relatively low computational cost since the network contains mostly 1D-like reaches. The current work constitutes an upgrade of the DassFlow computational platform. The adjoint of the whole tool chain is obtained by automatic code differentiation.