The Surface Water Chemistry (SWatCh) database: a standardized global database of water chemistry to facilitate large-sample hydrological research

Abstract

Abstract. Openly accessible global-scale surface water chemistry datasets are urgently needed to detect widespread trends and problems, to help identify their possible solutions, and to determine critical spatial data gaps where more monitoring is required. Existing datasets are limited with respect to availability, sample size and/or sampling frequency, and geographic scope. These limitations inhibit researchers from tackling emerging transboundary water chemistry issues – 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, available on Zenodo (https://doi.org/10.5281/zenodo.6484939; Rotteveel and Heubach, 2021). We collect, clean, standardize, and aggregate open-access data provided by six national and international programs and research groups (United Nations Environment Programme; Hartmann et al., 2019; Environment and Climate Change Canada; the United States of America National Water Quality Monitoring Council; the European Environment Agency; and the United States National Science Foundation McMurdo Dry Valleys Long-Term Ecological Research Network) in order to compile a database containing information on sites, methods, and samples, and a geospatial information system (GIS) shapefile of site locations. We remove poor-quality data (e.g., 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 that 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 transboundary database, SWatCh allows users to conduct powerful and robust statistical analyses of global surface water chemistry.

Uncertainty in Environmental Micropollutant Modeling

“…To provide applicable approaches, different water quality datasets must be combined such that they all have similar structures in terms of metadata, geographical description, and the actual time series data on water quality measurements. Recently, many research projects have been aimed at producing such datasets (Klingler et al 2021, Kratzert et al 2023, and more recently, some steps have been taken toward producing such data for chemical variables (Rotteveel et al 2022, Ebeling et al 2022, NORMAN 2023. Although LSH is able to make predictions for multiple spatiotemporal scales, it does not provide superior performance over other ML models for unseen data as is typical for surprising events and weather extremes, that are likely to become more popular due to the climate change (Stott 2016).…”

Title: Addition of Alkalinity to Rivers: a new CO2 Removal Strategy

“…Human activities, such as fossil fuel burning and fertilizer application, have reduced base cation concentrations in soils and lowered pH and alkalinity of inland waters. Currently many rivers remain acidified with low alkalinity and pH 22 , despite reductions in acid emissions 23,24 . This lack of recovery is due to both the continued exceedance of critical loads of acid deposition and the slow recruitment of critical base cations in catchment soils 25,26 .…”