Global River Water Quality Archive (GRQA)

A major problem related to large-scale water quality modeling has been the lack of available observation data with a good spatiotemporal coverage. This has affected the reproducibility of previous studies and the potential improvement of existing models. In addition to the observation data itself, insufficient or poor quality metadata has also discouraged researchers to integrate the already available datasets. Therefore, improving both the availability and quality of open water quality data woould increase the potential to implement predictive modeling on a global scale. We aim to address the aforementioned issues by presenting the new Global River Water Quality Archive (GRQA) by integrating data from five existing global and regional sources: Canadian Environmental Sustainability Indicators program (CESI), Global Freshwater Quality Database (GEMStat), GLObal RIver Chemistry database (GLORICH), European Environment Agency (Waterbase) and USGS Water Quality Portal (WQP). The resulting dataset covering the timeframe 1898 - 2020 contains a total of over 17 million observations for 42 different forms of some of the most important water quality parameters, focusing on nutrients, carbon, oxygen and sediments. Supplementary metadata and statistics are provided with the observation time series to improve the usability of the dataset. An overview of all the files in the dataset can be found in README.txt. Statistical overview of all 42 parameters is given in the data catalog file GRQA_data_catalog.pdf. For more information about the development of this dataset look for Virro, H., Amatulli, G., Kmoch, A., Shen, L., and Uuemaa, E.: GRQA: Global River Water Quality Archive, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2021-51, in review, 2021.大规模水质建模面临的核心难题之一，是缺乏具备良好时空覆盖度的可用观测数据。这一问题不仅制约了既往研究的可复现性，也限制了现有模型的性能提升潜力。除观测数据本身外，元数据（metadata）的不足或质量不佳，也阻碍了研究人员整合已有的公开数据集。因此，提升开放水质数据的可获取性与数据质量，将为全球尺度的预测建模工作拓展应用潜力。 本研究旨在通过整合五类现有全球及区域数据源，构建全新的全球河流水质档案库（Global River Water Quality Archive, GRQA），以解决上述问题。整合的数据源包括：加拿大环境可持续性指标计划（Canadian Environmental Sustainability Indicators program, CESI）、全球淡水水质数据库（Global Freshwater Quality Database, GEMStat）、全球河流化学数据库（GLObal RIver Chemistry database, GLORICH）、欧洲环境署（European Environment Agency, Waterbase）以及美国地质调查局水质门户（USGS Water Quality Portal, WQP）。本数据集的时间跨度为1898年至2020年，涵盖针对部分重要水质参数的42种不同形态的总计超1700万条观测记录，参数类型聚焦于营养盐、碳、溶解氧与沉积物。观测时序数据同步附带补充元数据与统计信息，以提升数据集的易用性。数据集全部文件的概览可于README.txt文件中查阅；42项参数的统计概览则收录于数据目录文件GRQA_data_catalog.pdf中。如需了解本数据集开发的更多细节，请参阅文献：Virro, H., Amatulli, G., Kmoch, A., Shen, L. 与Uuemaa, E. 发表的《GRQA：全球河流水质档案库》，Earth Syst. Sci. Data Discuss. [预印本]，https://doi.org/10.5194/essd-2021-51，2021年，正在审稿。