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Most computational hydrology is not reproducible, so is it really science?

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)7548–7555
Number of pages8
JournalWater Resources Research
Issue number10
Early online date19 Oct 2016
DateAccepted/In press - 24 Sep 2016
DateE-pub ahead of print - 19 Oct 2016
DatePublished (current) - Oct 2016


Reproducibility is a foundational principle in scientific research. Yet in computational hydrology, the code and data that actually produces published results is not regularly made available, inhibiting the ability of the community to reproduce and verify previous findings. In order to overcome this problem we recommend that re-useable code and formal workflows, which unambiguously reproduce published scientific results, are made available for the community alongside data, so that we can verify previous findings, and build directly from previous work. In cases where reproducing large-scale hydrologic studies is computationally very expensive and time-consuming, new processes are required to ensure scientific rigour. Such changes will strongly improve the transparency of hydrological research, and thus provide a more credible foundation for scientific advancement and policy support.

    Research areas

  • Hydrology, Reproducibility, Software, Code, Verification, Workflows

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    Accepted author manuscript, 363 KB, PDF document

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    Rights statement: This is the final published version of the article (version of record). It first appeared online via Wiley at Please refer to any applicable terms of use of the publisher.

    Final published version, 887 KB, PDF document


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