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This data release documents statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM)(Granato, 2013). The U.S. Geological Survey (USGS) developed SELDM and the statistics documented in this report in cooperation with the Federal Highway Administration (FHWA) to indicate the risk for stormwater flows, concentrations, and loads to be above user-selected water-quality goals and the potential effectiveness of mitigation measures to reduce such risks. In SELDM, three treatment variables, hydrograph extension, runoff volume reduction, and water-quality treatment are modeled by using the trapezoidal distribution and the rank...
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The purpose of this USGS data release is to publish NC SELDM streamflow statistics and summary statistics of physical and chemical data in support of the information provided in the above-referenced report. This data release consists of two data sets, "NC SELDM streamflow statistics..." and "NC SELDM summary statistics for physical and chemical data...". The tables that are uploaded for the "NC SELDM streamflow statistics for 266 streamgages across North Carolina" sub-section are primarily the support files for the StreamStatsDB update that was completed when the report was approved. These files were generated using the GNWISQ and QSTATS computer programs developed and described by Granato (2009, appendices 1 and...
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In 2013, the U.S. Geological Survey (USGS) in partnership with the U.S. Federal Highway Administration (FHWA) published a new national stormwater quality model called the Stochastic Empirical Loading Dilution Model (SELDM; Granato, 2013). The model is optimized for roadway projects but in theory can be applied to a broad range of development types. SELDM is a statistically-based empirical model pre-populated with much of the data required to successfully run the application (Granato, 2013). The model uses Monte Carlo methods (as opposed to deterministic methods) to generate a wide range of precipitation events and stormwater discharges coupled with water-quality constituent concentrations and loads from the upstream...
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The purpose of this USGS data release is to publish NC SELDM streamflow statistics and summary statistics of physical and chemical data in support of the information provided in the above-referenced report. This data release consists of two data sets, "NC SELDM streamflow statistics..." and "NC SELDM summary statistics for physical and chemical data...". The tables that are uploaded for the "NC SELDM streamflow statistics for 266 streamgages across North Carolina" sub-section are primarily the support files for the StreamStatsDB update that was completed when the report was approved. These files were generated using the GNWISQ and QSTATS computer programs developed and described by Granato (2009, appendices 1 and...


    map background search result map search result map North Carolina (NC) Stochastic Empirical Loading and Dilution Model (SELDM) streamflow statistics for 266 streamgages across North Carolina North Carolina (NC) Stochastic Empirical Loading and Dilution Model (SELDM) summary statistics for physical and chemical data at NC highway-runoff and bridge-deck sites Application of the North Carolina Stochastic Empirical Loading and Dilution Model (SELDM) to Assess Potential Impacts of Highway Runoff Statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM) North Carolina (NC) Stochastic Empirical Loading and Dilution Model (SELDM) streamflow statistics for 266 streamgages across North Carolina North Carolina (NC) Stochastic Empirical Loading and Dilution Model (SELDM) summary statistics for physical and chemical data at NC highway-runoff and bridge-deck sites Application of the North Carolina Stochastic Empirical Loading and Dilution Model (SELDM) to Assess Potential Impacts of Highway Runoff Statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM)