Influence of input data and model spatial resolutions on hydrological simulations (Jasper Schalla)

Motivation

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?

Methods

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

Supervision

Andreas Hartmann and Yan Liu

Contact

Andreas Hartmann or Yan Liu [andreas.hartmann@hydmod.uni-freiburg.de], [yan.liu@hydmod.uni-freiburg.de]

Sprache

English

Literatur

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. https://doi.org/10.1002/2015WR018247 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. https://doi.org/10.1029/2019jd031485