A1 Journal article (refereed), original research

Using ensemble data assimilation to forecast hydrological flumes


Open Access publication

LUT Authors / Editors

Publication Details
Authors: Amour Idrissa, Mussa Zubeda, Bibov Aleksandr, Kauranne Tuomo
Publication year: 2013
Language: English
Related Journal or Series Information: Nonlinear Processes in Geophysics
Volume number: 20
Start page: 955
End page: 964
JUFO-Level of this publication: 1
Open Access: Open Access publication

Abstract
Data assimilation, commonly used in weatherforecasting, means combining a mathematical forecast of atarget dynamical system with simultaneous measurementsfrom that system in an optimal fashion. We demonstrate thebenefits obtainable from data assimilation with a dam breakflume simulation in which a shallow-water equation modelis complemented with wave meter measurements. Data assimilationis conducted with a Variational Ensemble KalmanFilter (VEnKF) algorithm. The resulting dynamical analysisof the flume displays turbulent behavior, features prominenthydraulic jumps and avoids many numerical artifacts presentin a pure simulation.

Last updated on 2017-22-03 at 16:15

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