Most computational hydrology is not reproducible, so is it really science?
Most computational hydrology is not reproducible, so is it really science?
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DOI：
10.1002/2016wr019285
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发表时间：
2016-10
影响因子：
5.4
通讯作者：
C. Hutton;Thorsten Wagener;J. Freer;Dawei Han;C. Duffy;B. Arheimer
中科院分区：
文献类型：
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作者：
C. Hutton;Thorsten Wagener;J. Freer;Dawei Han;C. Duffy;B. Arheimer
可重复性是科学研究的一个基本原则。然而，在计算水文学中，实际产生已发表结果的代码和数据并不是定期提供的，这抑制了科学界复制和验证先前发现的能力。为了克服这个问题，我们建议将可重用的代码和正式的工作流程与数据一起提供给社区，这样我们就可以验证以前的发现，并直接从以前的工作中构建。在再现大规模水文研究在计算上非常昂贵和耗时的情况下，需要新的过程来确保科学的严谨性。这些变化将有力地提高水文研究的透明度，从而为科学进步和政策支持提供更可靠的基础。
Reproducibility is a foundational principle in scientific research. Yet in computational hydrology the code and data that actually produces published results are 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 reuseable 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 rigor. Such changes will strongly improve the transparency of hydrological research, and thus provide a more credible foundation for scientific advancement and policy support.