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

Journal Article (2021)
Author(s)

Dirk Eilander (Vrije Universiteit Amsterdam, Deltares)

Willem van Verseveld (Deltares)

Dai Yamazaki (University of Tokyo)

Albrecht Weerts (Deltares, Wageningen University & Research)

Hessel C. Winsemius (Deltares, TU Delft - Water Resources)

Philip J. Ward (Vrije Universiteit Amsterdam)

Research Group
Water Resources
DOI related publication
https://doi.org/10.5194/hess-25-5287-2021
More Info
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Publication Year
2021
Language
English
Research Group
Water Resources
Issue number
9
Volume number
25
Pages (from-to)
5287-5313
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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 representative sub-grid river length and slope parameters, which are required for resolution-independent model results. 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 upscaling methods. Furthermore, we show that MERIT Hydro IHU minimizes the errors made in the timing and magnitude of simulated peak discharge throughout the Rhine basin compared to simulations at the native data resolutions. As the method is open source and 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.