EGU21-15869, updated on 04 Mar 2021
https://doi.org/10.5194/egusphere-egu21-15869
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Advancements in the mesoscale Hydrologic Model at the global scale

Oldrich Rakovec, Maren Kaluza, Rohini Kumar, Robert Schweppe, Pallav Shrestha, Stephan Thober, Sebastian Mueller, Sabine Attinger, and Luis Samaniego
Oldrich Rakovec et al.
  • Helmholtz Centre for Environmental Research GmbH - UFZ, CHS, Leipzig, Germany (oldrich.rakovec@ufz.de)

This study synthesizes the advancements made in the setup of the mesoscale Hydrologic Model (mHM; [1,2,3]) at the global scale. Underlying vegetation and geophysical characteristics are provided at ≈200m, while the mHM simulates water fluxes and states between 10 km and 100 km spatial resolution. The meteorologic forcing data are derived from the readily available, near-real time ERA-5 dataset [4]. The total of 50 global parameters of the Multiscale Parameter Regionalization (MPR) are constrained in two modes: (1) streamflow only across 3054 gauges, and (2) streamflow across 3054 gauges and simultaneously with FLUXNET ET and GRACE TWSA across 258 domains consisting of ≈10° x 10° blocks. Model performance is finally evaluated against a range of observed and reference data since 1985. 

The single best parameter set evaluated across 3054 GRDC global streamflow station yield median performance of 0.47 daily KGE (0.55 monthly KGE). This performance varies strongly between continents. For example, median daily KGE across Europe is around 0.55 (N basins=972) and across northern America around 0.5 (N basins=1264). So far, the worst model performance is observed across Africa, with median KGE of 0 (N basins=202), using the same globally constrained parameter set. The deterioration of model performance based on seamless parameterization can be explained by the quality of the underlying data, which corresponds to areas, where water balance closure error is the biggest. Additionally, missed model processes play an important role as well. Finally, there remains a large gap between the onsite calibrations and global calibrations and ongoing research is being done to narrow down these differences. This work is the fundament for building skillful global seasonal forecasting system ULYSSES [6], which provides hindcasts and operational seasonal forecasts of hydrologic variables using four state of the art hydrologic/land surface models with lead time of 6 months.

  • [1] https://www.ufz.de/mhm
  • [2] https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2008WR007327
  • [3] https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2012WR012195
  • [4] https://rmets.onlinelibrary.wiley.com/doi/10.1002/qj.3803
  • [5] https://www.ufz.de/ulysses

How to cite: Rakovec, O., Kaluza, M., Kumar, R., Schweppe, R., Shrestha, P., Thober, S., Mueller, S., Attinger, S., and Samaniego, L.: Advancements in the mesoscale Hydrologic Model at the global scale, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15869, https://doi.org/10.5194/egusphere-egu21-15869, 2021.

Corresponding displays formerly uploaded have been withdrawn.