Integrated Hydraulic-Hydrological Assimilation Chain: Towards Multisource Data Fusion from River Network to Headwaters

In a context of climate change and potential intensification of the hydrological cycle, improving representation of water fluxes within river basins is of paramount importance both for hydrological sciences and operational forecasts. New integrated approaches are required for exploring synergies between spatially distributed flow models and datasets, combining in situ observations with high-resolution hydro-meteorology and satellite data. To take advantage of this unprecedented observations of the critical zone, innovative approaches integrating hydraulic-hydrological modeling and multivariate assimilation methods are needed. They should enable ingesting spatially distributed forcings, physiographic descriptors hydrodynamic signatures from remotely-sensed and in situ observables, and tackle calibration problems in integrated hydraulic-hydrological models. Crucially, the pertinence of the information assimilation relies on model-data coherence: water surface observables are valuable to constrain hydraulic models of river reaches [12] and references therein and complex river network portions, forced by spatially distributed inflows [23] (Malou et al. under redaction). Since hydraulic modeling at the scale of a river basin can be computationally costly, a combination of effective 1D and 2D representations, complemented by hydrological modules, may be useful. Complex river-floodplain interaction zones may be modeled in 2D zooms, while 1D approaches can fit simpler reaches. This contribution presents the development of a complete hydraulic-hydrological toolchain based on the 2D hydraulic model and variational data assimilation platform DassFlow ( http://www.math.univ-toulouse.fr/DassFlow ). A 1D effective modeling approach based on a 2D shallow water model is tested. Then, the implementation of hydrological modules within the DassFlow VDA framework is presented.