ABSTRACT Advances in open data science serve large-scale model developments and, subsequently, hydroclimate services. Local river flow observations are key in hydrology but data sharing remains limited due to unclear quality, or to political, economic or infrastructure reasons. This paper provides methods for quality checking openly accessible river-flow time series. Availability, outliers, homogeneity and trends were assessed in 21 586 time series from 13 data providers worldwide. We found a decrease in data availability since the 1980s, scarce open information in southern Asia, the Middle East and North and Central Africa, and significant river-flow trends in Africa, Australia, southwest Europe and Southeast Asia. We distinguish numerical outliers from high-flow peaks, and integrate all investigated quality characteristics in a composite indicator. We stress the need to maintain existing gauging networks, and highlight opportunities in extending existing global databases, understanding drivers for trends and inhomogeneity, and in innovative acquisition methods in data-scarce regions.

中文翻译：

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从检查全球可公开获取的河流流量数据的质量中吸取的经验教训

摘要 开放数据科学的进步服务于大规模模型的开发，以及随后的水文气候服务。当地河流流量观测是水文学的关键，但由于质量不明确或政治、经济或基础设施方面的原因，数据共享仍然有限。本文提供了对可公开访问的河流流量时间序列进行质量检查的方法。在来自全球 13 个数据提供商的 21 586 个时间序列中评估了可用性、异常值、同质性和趋势。我们发现自 1980 年代以来数据可用性下降，南亚、中东和北非和中非的公开信息稀少，非洲、澳大利亚、欧洲西南部和东南亚的河流流量趋势显着。我们将数值异常值与高流量峰值区分开来，并将所有调查的质量特征整合到一个综合指标中。我们强调需要维护现有的测量网络，并强调在扩展现有全球数据库、了解趋势和非同质性的驱动因素以及在数据稀缺地区采用创新的采集方法方面的机会。