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 identify 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, available on Zenodo (DOI: https://doi.org/10.5281/zenodo.4559696) We collect, clean, standardize, and aggregate open access data provided by six national and international agencies to compile a database consisting of three relational datasets: sites, methods, and samples, and one GIS shapefile of site locations. We remove poor quality data (for example, values flagged as suspect), standardize variable naming conventions and units, and perform other data cleaning steps required for statistical analysis. The database contains water chemistry data across seven continents, 17 variables, 38,598 sites, and over 9 million samples collected between 1960 and 2019. We identify critical spatial data gaps in the equatorial and arid climate regions, 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 recommendations to address them. 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.
Highlights
159 million people are reliant on untreated surface water, with only one in three people having access to safelymanaged drinking water services (World Health Organization and United Nations Children’s Fund, 2017)
Datasets likely missed by this approach include those hosted on servers or websites without Search Engine Optimization (SEO); that is, those which have not been optimized with keywords identifiable by search engines to provide results (Google, 2020)
Sites in SWatCh are located across the globe, but are concentrated in North America, South America, and Europe, and encompass a variety of bedrock and land use types (Figure 2)
Summary
159 million people are reliant on untreated surface water, with only one in three people having access to safelymanaged drinking water services (World Health Organization and United Nations Children’s Fund, 2017). One of the main obstacles to achieving this goal is a lack of openly available, high quality, transboundary data (World Health Organization and United Nations Children’s Fund, 2017). Existing large-sample water quality datasets have: 1) limited availability, for example, raw data may not be published with journal articles (Alsheikh-Ali et al, 2011); 2) limited sample size, for example, datasets may only include one water body type (Hartmann et al, 2014); or 3) limited geographic scope, for example, national datasets only include data for one. Ecosystem acidification and associated elevated aluminium (Al) concentrations are responsible for the loss of economicallysignificant fish species (Committee on the Status of Endangered Wildlife in Canada, 2011; Dennis and Clair, 2012), reductions in crop success (Collignon et al, 2012), reduced forest health
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