Hybrid models for Hydrological Forecasting: integration of data-driven and conceptual modelling techniques

<p>This book presents the investigation of possibilities and different architectures of integrating hydrological knowledge and conceptual models with data-driven models for the purpose of hydrological flow forecasting. Models resulting from such integration are referred to as hybrid models. The book addresses the following specific topics: <br>A classification of different hybrid modelling approaches in the context of flow forecasting.<br>The methodological development and application of modular models based on clustering and baseflow empirical formulations.<br>The integration of hydrological conceptual models with neural network error corrector models and the use of committee models for daily streamflow forecasting.<br>The application of modular modelling and fuzzy committee models to the problem of downscaling weather information for hydrological forecasting.</p><p>The results of this research show the increased forecasting accuracy when modular models which integrate conceptual and data-driven models are considered. Committee machine modelling show to be able to manage increased lead time with an acceptable accuracy. </p>