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

Dirk Eilander,Philip J Ward,Dai Yamazaki,Willem Van Verseveld,Albrecht Weerts,Hessel C Winsemius

doi:10.5194/hess-25-5287-2021

Abstract

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.

Highlights

Large-scale distributed hydrological and land surface models are used to provide estimates of available water resources (Schewe et al, 2014; Wada et al, 2014), flood risk (Hirabayashi et al, 2013; Ward et al, 2013), drought risk (Veldkamp et al, 2017; Wanders et al, 2015) and food production (Kummu et al, 2014), among other applications
Much less compared to the effective area method (EAM) and double maximum method (DMM), erroneous Iterative Hydrography Upscaling (IHU) upscaled flow directions are still found in dry-land and icecovered areas where the actual flow directions are highly uncertain
To describe flow directions and sub-grid river parameters in distributed hydrological models of different resolutions based on hydrography datasets with increasingly higher resolutions, automatic upscaling methods are required

Summary

Introduction

Large-scale distributed hydrological and land surface models are used to provide estimates of available water resources (Schewe et al, 2014; Wada et al, 2014), flood risk (Hirabayashi et al, 2013; Ward et al, 2013), drought risk (Veldkamp et al, 2017; Wanders et al, 2015) and food production (Kummu et al, 2014), among other applications. These models contain a routing module to simulate streamflow, i.e., the lateral flow of water on the land surface. Streamflow is the only measurable integral signal of basin response and is widely used for model calibration (Beven, 2012; Bouaziz et al, 2021), underlining the importance of flow direction data in distributed hydrological models

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