Comparison of two data assimilation algorithms for shallow water flows

Issam S. Strub; Julie Percelay; Olli-Pekka Tossavainen; Alexandre M. Bayen

doi:10.3934/nhm.2009.4.409

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2009, Volume 4, Issue 2: 409-430. Doi: 10.3934/nhm.2009.4.409

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Comparison of two data assimilation algorithms for shallow water flows

1.
Systems Engineering, Civil and Environmental Engineering, 604 Davis Hall, University of California, Berkeley, CA 94720-1710
2.
Environmental Engineering, Civil and Environmental Engineering, 604 Davis Hall, Berkeley, CA 94720-1710
3.
Systems Engineering, Civil and Environmental Engineering, Berkeley Water Center, 413 O’Brien Hall, Berkeley, CA 94720-1710
4.
Systems Engineering, Civil and Environmental Engineering, 711 Davis Hall, Berkeley, CA 94720-1710

Received: October 31, 2008

Revised: January 31, 2009

Published: May 2009

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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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Mathematics Subject Classification: Primary: 58F15, 58F17; Secondary: 53C35.

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