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Drinking Water Treatability Database (TDB)
The Drinking Water Treatability Database (TDB) presents referenced information on the control of contaminants in drinking water. It allows drinking water utilities, first responders to spills or emergencies, treatment process designers, research organizations, regulators and others to access referenced information gathered from thousands of literature sources on regulated and unregulated contaminants.
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Fate of Contaminants of Emerging Concern and Potential for Human Exposure Resulting from De Facto Water Reuse Dataset
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Dataset summarizes the results of a study to examine de facto reuse of contaminants of emerging concern
Information Collection Rule Federal Database
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The Information Collection Rule (ICR) Federal database includes research data from an 18-month study of disinfection byproducts and microbial contaminants.
Information Collection Rule Federal Database
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The Information Collection Rule (ICR) Federal database includes research data from an 18-month study of disinfection byproducts and microbial contaminants.
National Water Quality Standards Database (NWQSD)
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The National Water Quality Standards Database (WQSDB) provides access to EPA and state water quality standards (WQS) information in text, tables, and maps. This data source was last updated in December 2007 and will no longer be updated.
Connecticut Water Quality
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Data on drinking water in Connecticut. Drinking water is a potentially significant route of exposure to contaminants. Today’s regulatory programs are designed to monitor public drinking water supplies across the United States to assure public health protection from drinking water contaminants. The presence of contaminants in water can lead to adverse health effects, including gastrointestinal illness, reproductive problems, and neurological disorders.
Risk-based Decision Support Tool (DST) for TMDL analysis and Watershed Health assessment demonstration dataset (Upper Mississippi River Basin, Ohio River Basin, Maumee River Basin)
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The data set is composed of inputs and outputs of the DST demonstration and application to risk-based TMDLs and water quality risk assessment in Midwest river basins (Upper Mississippi River, Ohio River, and Maumee River). Portions of this dataset are inaccessible because: Too large. They can be accessed through the following means: The data is available in this directory: C:\Users\MHantush\OneDrive - Environmental Protection Agency (EPA)\ScienceHUB\Risk-Based WH-TMDL Tool\gis_files. Format: GIS data files. This dataset is associated with the following publication: Mallya, G., A. Gupta, M.M. Hantush, and R.S. Govindaraju. Uncertainty quantification in reconstruction of sparse water quality time series: Implications for watershed health and risk-based TMDL assessment. ENVIRONMENTAL MODELLING AND SOFTWARE. Elsevier Science Ltd, New York, NY, USA, 131: 104735, (2020).
Risk-based Decision Support Tool (DST) for TMDL analysis and Watershed Health assessment demonstration dataset (Upper Mississippi River Basin, Ohio River Basin, Maumee River Basin)
공공데이터포털
The data set is composed of inputs and outputs of the DST demonstration and application to risk-based TMDLs and water quality risk assessment in Midwest river basins (Upper Mississippi River, Ohio River, and Maumee River). Portions of this dataset are inaccessible because: Too large. They can be accessed through the following means: The data is available in this directory: C:\Users\MHantush\OneDrive - Environmental Protection Agency (EPA)\ScienceHUB\Risk-Based WH-TMDL Tool\gis_files. Format: GIS data files. This dataset is associated with the following publication: Mallya, G., A. Gupta, M.M. Hantush, and R.S. Govindaraju. Uncertainty quantification in reconstruction of sparse water quality time series: Implications for watershed health and risk-based TMDL assessment. ENVIRONMENTAL MODELLING AND SOFTWARE. Elsevier Science Ltd, New York, NY, USA, 131: 104735, (2020).
Safe Drinking Water Information System - State System (SDWIS/State)
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SDWIS/State is a data system that EPA is developing for states that will improve the quality of drinking water information.
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