This is the dataset presented in the following manuscript: The Surface Water Chemistry (SWatCh) database: A standardized global database of water chemistry to facilitate large-sample hydrological research, which is currently under review at Earth System Science Data. Openly accessible global scale surface water chemistry datasets are urgently needed to detect widespread trends and problems, to help identify their possible solutions, and determine critical spatial data gaps where more monitoring is required. Existing datasets are limited in availability, sample size/sampling frequency, and geographic scope. These limitations inhibit the answering of emerging transboundary water chemistry questions, for example, the detection and understanding of delayed recovery from freshwater acidification. Here, we begin to address these limitations by compiling the global surface water chemistry (SWatCh) database. We collect, clean, standardize, and aggregate open access data provided by six national and international agencies to compile a database containing information on sites, methods, and samples, and a GIS shapefile of site locations. We remove poor quality data (for example, values flagged as “suspect” or “rejected”), standardize variable naming conventions and units, and perform other data cleaning steps required for statistical analysis. The database contains water chemistry data for streams, rivers, canals, ponds, lakes, and reservoirs across seven continents, 24 variables, 33,722 sites, and over 5 million samples collected between 1960 and 2022. Similar to prior research, we identify critical spatial data gaps on the African and Asian continents, highlighting the need for more data collection and sharing initiatives in these areas, especially considering freshwater ecosystems in these environs are predicted to be among the most heavily impacted by climate change. We identify the main challenges associated with compiling global databases – limited data availability, dissimilar sample collection and analysis methodology, and reporting ambiguity – and provide recommended solutions. By addressing these challenges and consolidating data from various sources into one standardized, openly available, high quality, and trans-boundary database, SWatCh allows users to conduct powerful and robust statistical analyses of global surface water chemistry.

The code used to generate the SWatCh database is published on Github: https://github.com/LobkeRotteveel/SWatCh