Forcing data and spatial resolution of a hydrological model affect simulations of the water balance and hydrodynamics. For the catchment-scale modeling, local data is easier to obtain. But for the regional and global scale, the availability of local data gets lower. The model spatial resolution influences the data demand to set up a model as well as the hydrological simulations. Investigating the model performance of settings with local/global data and different spatial resolutions can provide a basis for the regional-scale modeling.

Scopes of the BSc thesis

The aim of this work is to investigate: (1) Is there a decrease of model performance (water balance and hydrodynamics) when using global datasets and how large is this influence? (2) Does the model perform better with a finer spatial resolution?


Hydrological modeling, model performance analysis using Excel or R/Matlab/Python. Models and data are all available.


Andreas Hartmann and Yan Liu


Andreas Hartmann or Yan Liu [], []




Beck, H. E., van Dijk, A. I. J. M., de Roo, A., Miralles, D. G., McVicar, T. R., Schellekens, J., & Bruijnzeel, L. A. (2016). Global-scale regionalization of hydrologic model parameters. Water Resources Research, 52(5), 3599–3622. Beck, H. E., Pan, M., Lin, P., Seibert, J., Dijk, A. I. J. M., & Wood, E. F. (2020). Global fully‐distributed parameter regionalization based on observed streamflow from 4229 headwater catchments. Journal of Geophysical Research: Atmospheres.

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