Hydrological Modelling for Assessing Climate Change Impacts at different Scales
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Expected main project results

Expected main project results

The project will develop new methodologies and tools that enable easier and more accurate use of regional scale climate and hydrological models to address local scale water resources problems. The expected main project results are:

  • A migration of two state-of-the-art model codes (HIRHAM and MIKE SHE) to the OpenMI standards and establishment of a full dynamic coupling between the two model codes. Making the two codes OpenMI compatible ensures that the coupling can survive future regular developments of the two codes and it enables both model codes to be easily coupled with other model codes.
  • A coupled climate-hydrological model for Denmark comprising DMI’s regional climate model (HIRHAM) and GEUS’ national hydrological model (DK-model) that is based on the MIKE SHE code. This will improve our ability to make more reliable climate and land-use change assessment.
  • A methodology and software tool for statistical downscaling of precipitation from a regional climate model grid to hydrological model grids. This will be implemented as part of the coupled model for Denmark.
  • A methodology and tool for assessing and downscaling of precipitation from remote sensing datasets in areas where orographic effects are important.
  • Improved facilities in MIKE SHE for grid refinements, so that regional scale hydrological models can easier be used with finer grids at local scale.
  • Improved methods for handling complex geological environments, particularly aiming at situations where a local scale groundwater model is built on the basis of a regional model, and where the local model can resolve much more of the geological complexity than the regional model.
  • An analysis of the uncertainty of hydrological change predictions at local scale. This will include an assessment of how much the individual sources of uncertainty, such as climate scenarios, model structure, geological interpretation, model parameters and adaptation strategies, contribute to the total prediction uncertainty.
  • An improved methodology for assessing the effects of geological uncertainty on hydrological model predictions.
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Last modified : February 4, 2008
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