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Integrating Multiple Sources of Information for Improving Hydrological Modelling: An Ensemble Approach
Group: IHE Delft, Hydroinformatics
Promotor: Professor Dimitri Solomatine
Co-promotor: Dr. Schalk Jan van Andel
Availability of Earth observation (EO) and numerical weather prediction data for hydrological modelling and water management has increased significantly, creating today a situation that for the same variable, estimates may be available from two or more sources of information. Yet, in hydrological modelling, usually, a particular set of catchment characteristics and input data is selected, possibly ignoring other relevant data sources. In this thesis, therefore, a framework is being proposed to enable effective use in hydrological modelling of multiple data sources.
In this framework, each available data source, e.g. concerning land use, soil type, precipitation, and evapotranspiration, is used to derive catchment parameter values or input time series. Each unique combination of catchment and input data sources thus leads to a different hydrological simulation result, which together form an ensemble of hydrological simulations. By following this approach, all available data sources are used effectively and their information is preserved.
By September we will present an overview of SENSE dissertations on this page, with links to the full texts of the dissertations.