Data assimilation study of the DCSM model using full ...

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XVI International Conference on Computational Methods in Water Resources (CMWR-XVI) Ingeniørhuset

Data assimilation study of the DCSM model using full measurement
Paper
Author:Julius Harry Sumihar <j.h.sumihar@ewi.tudelft.nl> (Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Applied Mathematics, Delft University of Technology, Delft, Netherlands)
Martin Verlaan <m.verlaan@rikz.rws.minvenw.nl> (Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Applied Mathematics, Delft University of Technology, Delft, Netherlands and Rijkswaterstaat, Rijksinstituut voor Kust en Zee (RIKZ), Netherlands)
Presenter:Julius Harry Sumihar <j.h.sumihar@ewi.tudelft.nl> (Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Applied Mathematics, Delft University of Technology, Delft, Netherlands)
Date: 2006-06-18     Track: Special Sessions     Session: Data assimilation in water resources modelling
DOI:10.4122/1.1000000510
DOI:10.4122/1.1000000511

The operational water level prediction method in the Netherlands is based on the decomposition of water level into the astronomical tides and the surge. While the astronomical components are analysed and predicted by using Harmonic Analysis, the surge is predicted by using numerical hydrodynamics model named Dutch Continental Shelf Model, DCSM. Using this approach the nonlinear interaction between the components is not well accomodated. Moreover, the performance of the system now seems to have reached its limit. Hence, as an attempt to further improve the prediction we are going to apply data assimilation using the DCSM model with the full water level measurements without any decomposition. In the first step of the study we use the steady-state Kalman filter as the method for data assimilation. Selection of measurement locations is also discussed to find the best configuration. As the success of data assimilation depends largely on the error representation, we are also going to work with new error representation for the boundary condition. In the new representation, a colored noise process, modelled using AR(1), is assigned to each harmonic parameters defining the water level boundary conditions. This choice is made based on the fact that the harmonic parameters of the astronomical tides are in fact slowly varying in time. We are going to present and discuss some results of this study. ~