Print Email Facebook Twitter Hybrid models for hydrological forecasting: Integration of data-driven and conceptual modelling techniques Title Hybrid models for hydrological forecasting: Integration of data-driven and conceptual modelling techniques Author Corzo Perez, G.A. Contributor Solomatine, D.P. (promotor) Faculty Civil Engineering and Geosciences Department Watermanagement Date 2009-09-04 Abstract This book presents the investigation of different architectures of integrating hydrological knowledge and models with data-driven models for the purpose of hydrological flow forecasting. The models resulting from such integration are referred to as hybrid models. The book addresses the following topics: A classification of different hybrid modelling approaches in the context of flow forecasting. The methodological development and application of modular models based on clustering and baseflow empirical formulations. The integration of hydrological conceptual models with neural network error corrector models and the use of committee models for daily streamflow forecasting. The application of modular modelling and fuzzy committee models to the problem of downscaling weather information for hydrological forecasting. Subject Delft ClusterCT04.30veiligheid tegen overstromingensafety against floodsCT04.33.11consequences and societal acceptance of floodshybrid modelshydrologicalforecastinghybridmodelling To reference this document use: http://resolver.tudelft.nl/uuid:c4fc894f-aee4-466b-8811-7427ccebf697 Publisher CRC Press/Balkema ISBN 978-0-415-56597-4 Part of collection Institutional Repository Document type doctoral thesis Rights (c) 2009 Corzo Perez, G.A. Files PDF PHD_THESIS_CORZO-PEREZ1.pdf 6.03 MB Close viewer /islandora/object/uuid:c4fc894f-aee4-466b-8811-7427ccebf697/datastream/OBJ/view