Comparison of two data assimilation algorithms for shallow water flows
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1.
Systems Engineering, Civil and Environmental Engineering, 604 Davis Hall, University of California, Berkeley, CA 94720-1710
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2.
Environmental Engineering, Civil and Environmental Engineering, 604 Davis Hall, Berkeley, CA 94720-1710
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3.
Systems Engineering, Civil and Environmental Engineering, Berkeley Water Center, 413 O’Brien Hall, Berkeley, CA 94720-1710
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4.
Systems Engineering, Civil and Environmental Engineering, 711 Davis Hall, Berkeley, CA 94720-1710
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Received:
01 November 2008
Revised:
01 February 2009
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Primary: 58F15, 58F17; Secondary: 53C35.
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This article presents the comparison of two algorithms for data assimilation of two
dimensional shallow water flows. The first algorithm is based on a
linearization of the model equations and a quadratic programming (QP)
formulation of the problem. The second algorithm uses Ensemble
Kalman Filtering (EnKF) applied to the non-linear two dimensional
shallow water equations. The two methods are implemented
on a scenario in which boundary conditions and Lagrangian
measurements are available. The performance of the methods is
evaluated using twin experiments with experimentally measured
bathymetry data and boundary conditions from a river located in the
Sacramento Delta. The sensitivity of the algorithms to the number of
drifters, low or high discharge and time sampling frequency is
studied.
Citation: Issam S. Strub, Julie Percelay, Olli-Pekka Tossavainen, Alexandre M. Bayen. Comparison of two data assimilation algorithms for shallow water flows[J]. Networks and Heterogeneous Media, 2009, 4(2): 409-430. doi: 10.3934/nhm.2009.4.409
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Abstract
This article presents the comparison of two algorithms for data assimilation of two
dimensional shallow water flows. The first algorithm is based on a
linearization of the model equations and a quadratic programming (QP)
formulation of the problem. The second algorithm uses Ensemble
Kalman Filtering (EnKF) applied to the non-linear two dimensional
shallow water equations. The two methods are implemented
on a scenario in which boundary conditions and Lagrangian
measurements are available. The performance of the methods is
evaluated using twin experiments with experimentally measured
bathymetry data and boundary conditions from a river located in the
Sacramento Delta. The sensitivity of the algorithms to the number of
drifters, low or high discharge and time sampling frequency is
studied.
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