The TIERRAS project is an open-access platform that compiles a database of more than 400 tracer injection experiments in rivers and streams, sourced from previously published studies and reports. It also includes interactive features that allow users to explore, download, and contribute new data. The goal is to provide a centralized and accessible repository for researchers, environmental managers, and anyone interested in water quality, hydrological modeling, and stream solute dynamics.   These experiments were collected from various sources, including published studies, unpublished data, and technical reports from different authors. The original data were in diverse formats and units; all data were curated and standardized to a consistent format and to the Imperial (U.S. customary) units.   Visit TIERRAS at https://www.tierras.org/ Cite: Rodríguez, L., Tunby, P., Abusang, A., Tartakovsky, A., Carroll, K., Ginn, T., & González-Pinzón, R. (2025). TIERRAS Tracer Injection Experiments in RiveRs And Streams (2.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15794259 
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                            The National Eutrophication Survey: lake characteristics and historical nutrient concentrations
                        
                    
    
            Abstract. Historical ecological surveys serve as a baseline and provide context for contemporary research, yet many of these records are not preserved in a way that ensures their long-term usability. The National Eutrophication Survey (NES) database is currently only available as scans of the original reports (PDF files) with no embedded character information. This limits its searchability, machine readability, and the ability of current and future scientists to systematically evaluate its contents. The NES data were collected by the US Environmental Protection Agency between 1972 and 1975 as part of an effort to investigate eutrophication in freshwater lakes and reservoirs. Although several studies have manually transcribed small portions of the database in support of specific studies, there have been no systematic attempts to transcribe and preserve the database in its entirety. Here we use a combination of automated optical character recognition and manual quality assurance procedures to make these data available for analysis. The performance of the optical character recognition protocol was found to be linked to variation in the quality (clarity) of the original documents. For each of the four archival scanned reports, our quality assurance protocol found an error rate between 5.9 and 17%. The goal of our approach was to strike a balance between efficiency and data quality by combining entry of data by hand with digital transcription technologies. The finished database contains information on the physical characteristics, hydrology, and water quality of about 800 lakes in the contiguous US (Stachelek et al.(2017), https://doi.org/10.5063/F1639MVD). Ultimately, this database could be combined with more recent studies to generate meta-analyses of water quality trends and spatial variation across the continental US. 
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                            - PAR ID:
- 10073385
- Date Published:
- Journal Name:
- Earth System Science Data
- Volume:
- 10
- Issue:
- 1
- ISSN:
- 1866-3516
- Page Range / eLocation ID:
- 81 to 86
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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