Ensemble-based data assimilation for operational flood forecasting – On the merits of state estimation for 1D hydrodynamic forecasting through the example of the “Adour Maritime” river

•Ensemble-based data assimilation for state-estimation in 1D hydraulic modeling in the context of flood forecasting.•Inflated Ensemble Kalman Filter (IEnKF) to increase ensemble spread when uncertainty is related to hydrological forcing data.•Characterization of the ensemble in terms of consistency, reliability and accuracy.•Performance of IEnKF for real case study over the Adour catchment in forecast mode.