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 - 2023 contains a total of over 17 million observations for 43 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. GRQA data processing scripts are available at https://doi.org/10.5281/zenodo.5082147. Last update: 2025-05-04 Changes since GRQA_v1.3 The updated dataset now includes the observations from the latest versions of GEMStat and Waterbase. These additions extend the time series to 2023 in many sites, particularly in Europe. An overview of all the files in the dataset can be found in README_v1.4.md. Statistical overview of all 43 parameters is given in the data catalog file GRQA_data_catalog_v1.4.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, 13, 5483–5507, https://doi.org/10.5194/essd-13-5483-2021, 2021.