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2014
- handle: 10670/1.j3ktbt
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Level, Water Water--Level Water--Levels Water level Levels, Water Analysis (Mathematics) Pattern ModelCiter ce document
Sébastien Barthélémy et al., « Data Assimilation with an Ensemble Kalman Filter Algorithm on an Operational Hydraulic Network », Journées de l'hydraulique, ID : 10670/1.j3ktbt
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This study describes the implementation and the merits of an Ensemble Kalman Filter algorithm (EnKF) on the 1Dshallow water model MASCARET for the representation of the hydrodynamics of the " Adour maritime" river in south west France. The first part of this work is dedicated to a detailed analysis of the background error covariance functions that are stochastically estimated on an ensemble of MASCARET integrations forced by perturbed upstream boundary conditions. It is shown that the geometric characteristics of the network have a significant impact on the shape of these functions and thus on the data assimilation correction. The data assimilation algorithm is validated in the framework of Observating System Simulation Experiment ; it is shown that the assimilation of in-situ water level observations allows to improve water level and discharge over the entire hydraulic network, where no data are available. Finally, the method is applied in the context of real data experiments for recent major flood events of the Adour catchment. The algorithm provides a corrected hydraulic state that can be used as an initial condition for further forecast as well as an input for 1D/ 2D model coupling.