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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2019-150
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-150
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model description paper 14 Jun 2019

Submitted as: model description paper | 14 Jun 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

A distributed simple dynamical systems approach (dS2 v1.0) for computationally efficient hydrological modelling

Joost Buitink1, Lieke A. Melsen1, James W. Kirchner2,3,4, and Adriaan J. Teuling1 Joost Buitink et al.
  • 1Hydrology and Quantitative Water Management Group, Wageningen University, Wageningen, The Netherlands
  • 2Department of Environmental Systems Science, ETH Zurich, Zurich, 8092, Switzerland
  • 3Swiss Federal Research Institute WSL, Birmensdorf, 8903, Switzerland
  • 4Department of Earth and Planetary Science, University of California, Berkeley, California, 94720, USA

Abstract. In this paper, we introduce a new numerically robust distributed rainfall runoff model for computationally efficiency simulation at high (hourly) temporal resolution: the distributed simple dynamical systems (dS2) model. The model is based on the simple dynamical systems approach as proposed by Kirchner (2009), and the distributed implementation allows for spatial heterogeneity in the parameters and/or model forcing fields for instance as derived from precipitation radar data. The concept is extended with snow and routing modules, where the latter transports water from each pixel to the catchment outlet. The sensitivity function, which links changes in storage to changes in discharge, is implemented by a new 3-parameter equation that is able to represent the widely observed downward curvature in log-log space. The simplicity of the underlying concept allows the model to calculate discharge in a computationally efficient manner, even at high temporal and spatial resolution, while maintaining proven model performance at high temporal and spatial resolution. The model code is written in Python in order to be easily readable and adjustable while maintaining computational efficiency. Since this model has short run times, it allows for extended sensitivity and uncertainty studies with relatively low computational costs. A test application shows a good and constant model performance across scales ranging from 3 to over 1700 km2.

Joost Buitink et al.
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Joost Buitink et al.
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The distributed simple dynamical systems (dS2) model J. Buitink, L. A. Melsen, J. W. Kirchner, and A. J. Teuling https://doi.org/10.4121/uuid:cc8e0008-ab1f-43ee-b50d-24de01d2d0be

Joost Buitink et al.
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Latest update: 21 Oct 2019
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Short summary
This paper presents a new distributed hydrological model: the distributed simple dynamical systems (dS2) model. The model is built with a focus on computational efficiency, and is therefore able to simulate basins at high spatial and temporal resolution at a low computational cost. Despite the simplicity of the model concept, it is able to reach good performance in both small and mesoscale basins.
This paper presents a new distributed hydrological model: the distributed simple dynamical...
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