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Community Workflows to Advance Reproducibility in Hydrologic Modeling: Separating model-agnostic and model-specific configuration steps in applications of large-domain hydrologic models
  • +9
  • Wouter Johannes Maria Knoben,
  • Martyn P. Clark,
  • Jerad Bales,
  • Andrew Bennett,
  • S. Gharari,
  • Christopher B Marsh,
  • Bart Nijssen,
  • Alain Pietroniro,
  • Raymond J Spiteri,
  • David Gavin Tarboton,
  • Andrew W Wood,
  • Guoqiang Tang
Wouter Johannes Maria Knoben
University of Saskatchewan, University of Saskatchewan, University of Saskatchewan

Corresponding Author:[email protected]

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Martyn P. Clark
University of Saskatchewan Centre for Hydrology, Canmore Coldwater Laboratory, University of Saskatchewan Centre for Hydrology, Canmore Coldwater Laboratory, University of Saskatchewan Centre for Hydrology, Canmore Coldwater Laboratory
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Jerad Bales
Unknown, Unknown, Unknown
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Andrew Bennett
University of Washington, University of Washington, University of Washington
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S. Gharari
University of Saskatchewan Coldwater Laboratory, University of Saskatchewan Coldwater Laboratory, University of Saskatchewan Coldwater Laboratory
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Christopher B Marsh
University of Saskatchewan, University of Saskatchewan, University of Saskatchewan
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Bart Nijssen
University of Washington, University of Washington, University of Washington
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Alain Pietroniro
University of Calgary, University of Calgary, University of Calgary
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Raymond J Spiteri
University of Saskatchewan, University of Saskatchewan, University of Saskatchewan
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David Gavin Tarboton
Utah State University, Utah State University, Utah State University
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Andrew W Wood
National Center for Atmospheric Research (UCAR), National Center for Atmospheric Research (UCAR), National Center for Atmospheric Research (UCAR)
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Guoqiang Tang
University of Saskatchewan, University of Saskatchewan
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Abstract

Despite the proliferation of computer-based research on hydrology and water resources, such research is typically poorly reproducible. Published studies have low reproducibility due to incomplete availability of data and computer code, and a lack of documentation of workflow processes. This leads to a lack of transparency and efficiency because existing code can neither be quality controlled nor re-used. Given the commonalities between existing process-based hydrological models in terms of their required input data and preprocessing steps, open sharing of code can lead to large efficiency gains for the modeling community. Here we present a model configuration workflow that provides full reproducibility of the resulting model instantiations in a way that separates the model-agnostic preprocessing of specific datasets from the model-specific requirements that models impose on their input files. We use this workflow to create large-domain (global, continental) and local configurations of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) hydrologic model connected to the mizuRoute routing model. These examples show how a relatively complex model setup over a large domain can be organized in a reproducible and structured way that has the potential to accelerate advances in hydrologic modeling for the community as a whole. We provide a tentative blueprint of how community modeling initiatives can be built on top of workflows such as this. We term our workflow the “Community Workflows to Advance Reproducibility in Hydrologic Modeling’‘ (CWARHM; pronounced “swarm”).