This additional thesis project is performed as preliminary research for a bigger project that they are going to start at Lund University, to investigate whether the use of a different interpolation methods, to link the precipitation data to the sub-basins centers of the HYPE model, lead to improved model performance. In this report, previously performed research is summarised and the limitations in researching this question with the HYPE model are described. A start is made with investigating this question, by answering the question whether different interpolation methods result in a different discharge when it is assumed that all fallen precipitation ends up as discharge. This is investigated for the PO basin in Italy with 4 interpolation ...
The objective in this study is to explore a solution to the question whether model input data having...
The availability of good and reliable rainfall data is fundamental for most hydrological analyses an...
Triggering hydrological simulations with climate change gridded datasets is one of the prevailing ap...
The aim of this study was to form a method and find the highest model resolution for which the cell ...
Ground-based precipitation data are still the dominant input type for hydrological models. Spatial v...
Accurate assessment of spatial and temporal precipitation is crucial for simulating hydrological pro...
Grid transformations are common postprocessing procedures used in numerical weather prediction to tr...
This report presents an evaluation of three different methods for estimation of areal precipitation ...
peer reviewedThe design values of the areal precipitation are needed for engineer to manage vital el...
This paper examines the sensitivity of a hydrological model to several methods of spatial interpolat...
Open data make it possible to set up multi-basin models for large domains across environmental, clim...
Many fields of hydrology, water resources management and environmental sciences require climate info...
Hydrological forecasts are a useful and cost-effective tool to aid decision making. Hydrological for...
The representation of rainfall in space is important for hydrological modelling. Accurate estimation...
Water is an essential resource for human society. Numerous approaches have been developed in order t...
The objective in this study is to explore a solution to the question whether model input data having...
The availability of good and reliable rainfall data is fundamental for most hydrological analyses an...
Triggering hydrological simulations with climate change gridded datasets is one of the prevailing ap...
The aim of this study was to form a method and find the highest model resolution for which the cell ...
Ground-based precipitation data are still the dominant input type for hydrological models. Spatial v...
Accurate assessment of spatial and temporal precipitation is crucial for simulating hydrological pro...
Grid transformations are common postprocessing procedures used in numerical weather prediction to tr...
This report presents an evaluation of three different methods for estimation of areal precipitation ...
peer reviewedThe design values of the areal precipitation are needed for engineer to manage vital el...
This paper examines the sensitivity of a hydrological model to several methods of spatial interpolat...
Open data make it possible to set up multi-basin models for large domains across environmental, clim...
Many fields of hydrology, water resources management and environmental sciences require climate info...
Hydrological forecasts are a useful and cost-effective tool to aid decision making. Hydrological for...
The representation of rainfall in space is important for hydrological modelling. Accurate estimation...
Water is an essential resource for human society. Numerous approaches have been developed in order t...
The objective in this study is to explore a solution to the question whether model input data having...
The availability of good and reliable rainfall data is fundamental for most hydrological analyses an...
Triggering hydrological simulations with climate change gridded datasets is one of the prevailing ap...