EGU General Assembly 2021
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Large-sample based evaluation of the spatial resolution discretization of the wflow_sbm model for the CAMELS dataset

Jerom Aerts1, Albrecht Weerts2,3, Willem van Verseveld2, Pieter Hazenberg2, Niels Drost4, Rolf Hut1, and Nick van de Giesen1
Jerom Aerts et al.
  • 1Water Management, Delft University of Technology, Delft, The Netherlands
  • 2Deltares, Delft, The Netherlands
  • 3Hydrology and Quantitative Water Management Group, Wageningen University and Research, The Netherlands
  • 4Netherlands eScience Center, Amsterdam, The Netherlands

In this study, we investigate the effect of spatial resolution discretization at 3km, 1km, and 200m by evaluating the streamflow estimation of the model. A hypothesis driven approach is used to investigate why changes in states and fluxes are taking place at different spatial resolutions and how they relate to model performance. These changes are evaluated in the context of landscape and climate characteristics as well as hydrological signatures. Answering the research question: can landscape, climate and hydrological characteristics dictate appropriate spatial modelling resolution a priori?

We use a spatially distributed wflow_sbm model (Imhoff et al., 2020, code: together with the CAMELS dataset (Addor et al., 2017), covering the Continental United States. The wflow_sbm model is chosen due to flexibility in the spatial resolution of the watershed discretization while maintaining run time performance suitable for large-sample studies. The flexibility in spatial resolution is achieved by the use of point-scale (pedo)transfer functions (PTFs) with upscaling rules to global datasets to ensure flux matching across scales (Imhoff et al., 2020; Samaniego et al., 2010, 2017). The model relies on open datasets for parameter estimation and requires minimal calibration efforts as it is most sensitive to two model parameters, rooting depth and horizontal conductivity .

This study is carried out within the eWaterCycle framework; allowing for a FAIR by design research setup that is scalable in terms of case study areas and hydrological models.

How to cite: Aerts, J., Weerts, A., van Verseveld, W., Hazenberg, P., Drost, N., Hut, R., and van de Giesen, N.: Large-sample based evaluation of the spatial resolution discretization of the wflow_sbm model for the CAMELS dataset, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10680,, 2021.


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