کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4525333 | 1625622 | 2016 | 13 صفحه PDF | دانلود رایگان |
• Shock capturing data assimilation algorithm for SWEs is proposed.
• Model simulates SWEs with unknown initial conditions and parameter values.
• Model captures the truth and gives a posteriori bounding set enclosing the truth.
We propose a new data assimilation algorithm for shallow water equations in one dimension. The algorithm is based upon Discontinuous Galerkin spatial discretization of shallow water equations (DG-SW model) and the continuous formulation of the minimax filter. The latter allows for construction of a robust estimation of the state of the DG-SW model and computes worst-case bounds for the estimation error, provided the uncertain parameters belong to a given bounding set. Numerical studies show that, given sparse observations from numerical or physical experiments, the proposed algorithm quickly reconstructs the true solution even in the presence of shocks, rarefaction waves and unknown values of model parameters. The minimax filter is compared against the ensemble Kalman filter (EnKF) for a benchmark dam-break problem and the results show that the minimax filter converges faster to the true solution for sparse observations.
Journal: Advances in Water Resources - Volume 88, February 2016, Pages 198–210