Newer versions of this data can be found here: https://doi.org/10.5281/zenodo.5097436

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 would 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 16 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.