NPG Nonlinear Processes in Geophysics NPG Nonlin. Processes Geophys. 1607-7946 Copernicus Publications Göttingen, Germany 10.5194/npg-20-955-2013 Using ensemble data assimilation to forecast hydrological flumes Amour I. 1 Mussa Z. 1 Bibov A. 1 Kauranne T. 1 Lappeenranta University of Technology, Lappeenranta, Finland 08 11 2013 20 6 955 964 Copyright: © 2013 I. Amour et al. 2013 This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/ This article is available from https://npg.copernicus.org/articles/20/955/2013/npg-20-955-2013.html The full text article is available as a PDF file from https://npg.copernicus.org/articles/20/955/2013/npg-20-955-2013.pdf

Data assimilation, commonly used in weather forecasting, means combining a mathematical forecast of a target dynamical system with simultaneous measurements from that system in an optimal fashion. We demonstrate the benefits obtainable from data assimilation with a dam break flume simulation in which a shallow-water equation model is complemented with wave meter measurements. Data assimilation is conducted with a Variational Ensemble Kalman Filter (VEnKF) algorithm. The resulting dynamical analysis of the flume displays turbulent behavior, features prominent hydraulic jumps and avoids many numerical artifacts present in a pure simulation.

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