Preprints
https://doi.org/10.5194/hess-2021-605
https://doi.org/10.5194/hess-2021-605
 
01 Dec 2021
01 Dec 2021
Status: a revised version of this preprint was accepted for the journal HESS and is expected to appear here in due course.

Large-sample assessment of spatial scaling effects of the distributed wflow_sbm hydrological model shows that finer spatial resolution does not necessarily lead to better streamflow estimates

Jerom P.M. Aerts1, Rolf W. Hut1, Nick C. van de Giesen1, Niels Drost2, Willem J. van Verseveld3, Albrecht H. Weerts4,5, and Pieter Hazenberg6 Jerom P.M. Aerts et al.
  • 1Water Resources Section, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628 CN Delft, the Netherlands
  • 2Netherlands eScience Center, Science Park 140, 1098 XG Amsterdam, the Netherlands
  • 3Catchment and Urban Hydrology, Department of Inland Water Systems, Deltares, P.O. Box 177, 2600MH Delft, The Netherlands
  • 4Operational Water Management, Department of Inland Water Systems, Deltares, P.O. Box 177, 2600MH Delft, The Netherlands
  • 5Hydrology and Quantitative Water Management Group, Wageningen University and Research, P.O. Box 47, 6700AA Wageningen, The Netherlands
  • 6Applied Research Center, Florida International University, FL 33174, Miami, the United States of America

Abstract. Distributed hydrological modelling moves into the realm of hyper-resolution modelling. This results in a plethora of scaling related challenges that remain unsolved. In light of model result interpretation, finer resolution output might implicate to the user an increase in understanding of the complex interplay of heterogeneity within the hydrological system. Here we investigate spatial scaling in the realm of hyper-resolution by evaluating the streamflow estimates of the distributed wflow_sbm hydrological model based on 454 basins from the large-sample CAMELS data set. Model instances were derived at 3 spatial resolutions, namely 3 km, 1 km, and 200 m. The results show that a finer spatial resolution does not necessarily lead to better streamflow estimates at the basin outlet. Statistical testing of the objective function distributions (KGE score) of the 3 model instances show only a statistical difference between the 3 km and 200 m streamflow estimates. However, results indicate strong locality in scaling behaviour between model instances expressed by differences in KGE scores of on average 0.22. This demonstrates the presence of scaling behavior throughout the domain and indicates where locality in results is strong. The results of this study open up research paths that can investigate the changes in flux and state partitioning due to spatial scaling. This will help further understand the challenges that need to be resolved for hyper resolution hydrological modelling.

Jerom P.M. Aerts et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-605', Anonymous Referee #1, 18 Jan 2022
    • AC1: 'Reply on RC1', Jerom Aerts, 14 Mar 2022
  • RC2: 'Review of “Large-sample assessment of spatial scaling effects of the distributed wflow_sbm hydrological model shows that finer spatial resolution does not necessarily lead to better streamflow estimation” by Aerts et al., 2021', Shervan Gharari, 21 Feb 2022
    • AC2: 'Reply on RC2', Jerom Aerts, 14 Mar 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-605', Anonymous Referee #1, 18 Jan 2022
    • AC1: 'Reply on RC1', Jerom Aerts, 14 Mar 2022
  • RC2: 'Review of “Large-sample assessment of spatial scaling effects of the distributed wflow_sbm hydrological model shows that finer spatial resolution does not necessarily lead to better streamflow estimation” by Aerts et al., 2021', Shervan Gharari, 21 Feb 2022
    • AC2: 'Reply on RC2', Jerom Aerts, 14 Mar 2022

Jerom P.M. Aerts et al.

Jerom P.M. Aerts et al.

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Short summary
Gridded hydrological modelling moves into the realm of hyper-resolution modelling. In this study we investigate the effect of varying grid cell sizes for wflow_sbm hydrological model. We used a large-sample of basins from CAMELS data set to test the effect that varying grid cell sizes has on the simulation of streamflow at the basin outlet. Results show that there is no single best grid cell size for modelling streamflow for the whole domain.