American Institute of Mathematical Sciences

June  2009, 4(2): 409-430. doi: 10.3934/nhm.2009.4.409

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, United States 2 Environmental Engineering, Civil and Environmental Engineering, 604 Davis Hall, Berkeley, CA 94720-1710, United States 3 Systems Engineering, Civil and Environmental Engineering, Berkeley Water Center, 413 O’Brien Hall, Berkeley, CA 94720-1710, United States 4 Systems Engineering, Civil and Environmental Engineering, 711 Davis Hall, Berkeley, CA 94720-1710, United States

Received  November 2008 Revised  February 2009 Published  June 2009

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. Networks and Heterogeneous Media, 2009, 4 (2) : 409-430. doi: 10.3934/nhm.2009.4.409
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