| Volumes and Issues Contents of Issue 5 |
www.nonlin-processes-geophys.net/17/405/2010/
doi:10.5194/npg-17-405-2010
© Author(s) 2010. This work is distributed
under the Creative Commons Attribution 3.0 License.
Nonlinear chaotic model for predicting storm surges
1Department of Hydroinformatics and Knowledge Management, UNESCO-IHE Institute for Water Education, Delft, The Netherlands
2Water Resources Section, Delft University of Technology, The Netherlands
Abstract. This paper addresses the use of the methods of nonlinear dynamics and chaos theory for building a predictive chaotic model from time series. The chaotic model predictions are made by the adaptive local models based on the dynamical neighbors found in the reconstructed phase space of the observables. We implemented the univariate and multivariate chaotic models with direct and multi-steps prediction techniques and optimized these models using an exhaustive search method. The built models were tested for predicting storm surge dynamics for different stormy conditions in the North Sea, and are compared to neural network models. The results show that the chaotic models can generally provide reliable and accurate short-term storm surge predictions.
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Citation: Siek, M. and Solomatine, D. P.: Nonlinear chaotic model for predicting storm surges, Nonlin. Processes Geophys., 17, 405-420, doi:10.5194/npg-17-405-2010, 2010. Bibtex EndNote Reference Manager XML
