Preprints
https://doi.org/10.5194/hess-2020-582
https://doi.org/10.5194/hess-2020-582

  24 Nov 2020

24 Nov 2020

Review status: a revised version of this preprint is currently under review for the journal HESS.

A hydrography upscaling method for scale invariant parametrization of distributed hydrological models

Dirk Eilander1,2, Willem van Verseveld2, Dai Yamazaki3, Albrecht Weerts2,4, Hessel C. Winsemius2,5, and Philip J. Ward1 Dirk Eilander et al.
  • 1Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
  • 2Deltares, Delft, The Netherlands
  • 3Institute of Industrial Sciences, the University of Tokyo, Tokyo, Japan
  • 4Hydrology and Quantitative Water Management Group, Wageningen University & Research, Wageningen, The Netherlands
  • 5Dar Es Salaam Resilience Academy, Dar Es Salaam, Tanzania

Abstract. Distributed hydrological models rely on hydrography data such as flow direction, river length, slope and width. For large-scale applications, many of these models still rely on a few flow-direction datasets, which are often manually derived. We propose the Iterative Hydrography Upscaling (IHU) method to upscale high-resolution flow direction data to the typically coarser resolutions of distributed hydrological models. The IHU aims to preserve the upstream-downstream relationship of river structure, including basin boundaries, river meanders and confluences, in the D8 format, which is commonly used to describe river networks in models. Additionally, it derives sub-grid river attributes such as drainage area, river length, slope and width. We derived the multi-resolution MERIT Hydro IHU dataset at resolutions of 30 arcsec (~1 km), 5 arcmin (~10 km) and 15 arcmin (~30 km) by applying IHU to the recently published 3 arcsec MERIT Hydro data. Results indicate improved accuracy of IHU at all resolutions studied compared to other often applied methods. Furthermore, we show that using IHU-derived hydrography data minimizes the errors made in timing and magnitude of simulated peak discharge throughout the Rhine basin compared to simulations at the native data resolutions. As the method is fully automated, it can be applied to other high-resolution hydrography datasets to increase the accuracy and enhance the uptake of new datasets in distributed hydrological models in the future.

Dirk Eilander et al.

 
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Dirk Eilander et al.

Data sets

MERIT Hydro IHU Dirk Eilander, Willem van Verseveld, Dai Yamazaki, Albrecht Weerts, Hessel C. Winsemius, and Philip J. Ward https://doi.org/10.5281/zenodo.4138776

Model code and software

pyflwdir Dirk Eilander and Willem van Verseveld https://doi.org/10.5281/zenodo.4287338

Dirk Eilander et al.

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Short summary
Digital elevation models and derived flow directions are crucial for distributed hydrological modelling. As the spatial resolution of models is typically coarser than these data we need methods to upscale flow direction data while preserving the river structure. We propose the Iterative Hydrography Upscaling (IHU) method and show it outperforms other often applied methods. In addition we derive the MERIT Hydro IHU hydrography dataset including sub-grid river attributes such as length and slope.