evalhyd v0.1.1: a polyglot tool for the evaluation of deterministic and probabilistic streamflow predictions

evalhyd v0.1.1: a polyglot tool for the evaluation of deterministic and probabilistic streamflow predictions
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evalhyd v0.1.1:用于评估确定性和概率性水流预测的多语言工具

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发表时间:
2023
期刊:
影响因子:
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通讯作者:
V. Andréassian
V. Andréassian
中科院分区:
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文献类型:
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作者:
T. Hallouin;F. Bourgin;C. Perrin;M. Ramos;V. Andréassian

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对径流预报的评估构成了文献中发表的大多数水文模型研究的重要组成部分。评估过程通常涉及一些评估指标的计算,但也可能涉及预测的预处理和计算的指标的后处理。为了使已发表的水文学研究具有可重复性,作者需要仔细记录这些步骤。使用一种工具来执行所有这些任务将简化作者的文档编制工作,但也会降低读者的可重复性。然而,这5要求这种工具是多语种的(即可在各种编程语言中使用),并可公开使用,以便水文界的每个人都能使用。为此,我们开发了一个名为valhyd的新工具,它提供了用于评估确定性和概率径流预测的指标和功能。它是开放源码的,可以在Python、R、C++或作为命令行工具使用。本文描述了该工具,并以全球洪水预警系统(GloFAS)对法国的再预报为例说明了它的功能。10
The evaluation of streamflow predictions forms an essential part of most hydrological modelling studies published in the literature. The evaluation process typically involves the computation of some evaluation metrics, but it can also involve the pre-processing of the predictions and the post-processing of the computed metrics. In order for published hydrological studies to be reproducible, these steps need to be carefully documented by the authors. The availability of a single tool performing all of these tasks would simplify the documentation by the authors, but also the reproducibility by the readers. However, this 5 requires for such a tool to be polyglot (i.e. usable in a variety of programming languages) and openly accessible, so that it can be used by everyone in the hydrological community. To this end, we developed a new tool named evalhyd that offers metrics and functionalities for the evaluation of deterministic and probabilistic streamflow predictions. It is open source and it can be used in Python, in R, in C++, or as a command line tool. This article describes the tool and illustrates its functionalities using Global Flood Awareness System (GloFAS) reforecasts over France as an example data set. 10
来自正在运行的全球洪水意识系统的每日整体河流流量重新预测和实时预报
DOI: 10.5194/hess-27-1-2023
发表时间: 2023
影响因子: 6.3
作者:
Harrigan S
通讯作者: Harrigan S
DOI: 10.1038/sdata.2019.30
发表时间: 2019-02-26
期刊: SCIENTIFIC DATA
影响因子: 9.8
作者:
Stagge, James H.;Rosenberg, David E.;James, Ryan
通讯作者: James, Ryan