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The Best Management Practices Statistical Estimator (BMPSE) was developed by the U.S. Geological Survey (USGS), in cooperation with the Federal Highway Administration (FHWA) Office of Project Delivery and Environmental Review to provide planning-level information about the performance of structural best management practices for decision makers, planners, and highway engineers to assess and mitigate possible adverse effects of highway and urban runoff on the Nation's receiving waters (Granato 2013, 2014; Granato and others, 2021a,b). The BMPSE was used to calculate statistics and create input files for fitting the trapezoidal distribution to data from studies documenting the performance of individual structural stormwater...
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Impervious runoff-discharge to receiving streams is widely recognized as one of the leading factors contributing to ecological degradation in such streams. Although there are many factors that contribute to ecological degradation with increasing development adverse effects caused by runoff quality is widely recognized as a contributing factor. The objective of this study was to simulate the flows concentrations and loads of impervious-area runoff and stormflows from an undeveloped area over a range of impervious percentages and drainage areas to examine potential relations between these variables and the quantity and quality of downstream flows. Stormwater runoff in a hypothetical stream basin that represents hydrologic...
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 Highway-Runoff Database (HRDB) was developed by the U.S. Geological Survey (USGS), in cooperation with the Federal Highway Administration (FHWA) Office of Project Delivery and Environmental Review to provide planning-level information for decision makers, planners, and highway engineers to assess and mitigate possible adverse effects of highway runoff on the Nation's receiving waters (Granato and Cazenas, 2009; Granato, 2013; Granato and others, 2018). The HRDB was assembled by using a Microsoft Access database application to facilitate use of the data and to calculate runoff-quality statistics with methods that properly handle censored-concentration data. The HRDB was first published as version 1.0 in cooperation...
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This data release documents the location of intersections between roads and streams, referred to as road crossings, and associated basin characteristics to support highway-runoff mitigation analyses using the Stochastic Empirical Loading and Dilution Model (SELDM, Granato, 2013) in Connecticut, Massachusetts, and Rhode Island. The data set of road crossings was generated from the intersections of the U.S. Geological Survey (USGS) National Transportation Dataset (roads) and the StreamStats modified National Hydrography Dataset (streams) and in addition to the three-state study area, includes areas of New York, Vermont, and New Hampshire that are within drainages that cover the three states. Pertinent basin characteristics...
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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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The Stochastic Empirical Loading and Dilution Model (SELDM) was developed by the U.S. Geological Survey (USGS), in cooperation with the Federal Highway Administration (FHWA) Office of Project Delivery and Environmental Review to transform complex scientific data into meaningful information about the risk of adverse effects of runoff on receiving waters, the potential need for mitigation measures, and the potential effectiveness of such management measures for reducing these risks (Granato 2013; Granato and Jones, 2014). SELDM is a stochastic model because it uses Monte Carlo methods to produce the random combinations of input variable values needed to generate the stochastic population of values for each component...
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In 2016, non-interpretive streamflow statistics were compiled for streamgages located throughout the Nation and stored in the StreamStatsDB database for use with StreamStats and other applications. Two previously published USGS computer programs that were designed to help calculate streamflow statistics were updated to better support StreamStats as part of this effort. These programs are named “GNWISQ” (Get National Water Information System Streamflow (Q) files) and “QSTATS” (Streamflow (Q) Statistics). Statistics for 20,438 streamgages that had 1 or more complete years of record during water years 1901 through 2015 were calculated from daily mean streamflow data; 19,415 of these streamgages were within the conterminous...
Municipal Separate Storm Sewer System (MS4) permitees including the California Department of Transportation need information about potential loads and yields (loads per unit area) of constituents of concern in stormwater runoff. These entities also need information about the potential effectiveness of stormwater best management practices (BMPs) used to mitigate the effects of runoff. This information is needed to address total maximum daily load (TMDL) regulations. This model archive describes approaches used by the U.S. Geological Survey in cooperation with CalTrans for assessing long-term annual yields of highway and urban runoff in selected areas of California with version 1.1.0 of the Stochastic Empirical Loading...
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The Highway-Runoff Database (HRDB) was developed by the U.S. Geological Survey (USGS), in cooperation with the Federal Highway Administration (FHWA) to provide planning-level information for decision makers, planners, and highway engineers to assess and mitigate possible adverse effects of highway runoff on the Nation's receiving waters. The HRDB was assembled by using a Microsoft Access database application to facilitate use of the data and to calculate runoff-quality statistics with methods that properly handle censored-concentration data. This data release provides highway-runoff data, including information about monitoring sites, precipitation, runoff, and event-mean concentrations of water-quality constituents....
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The InterpretSELDM program is a graphical post processor designed to facilitate analysis and presentation of stormwater modeling results from the Stochastic Empirical Loading and Dilution Model (SELDM), which is a stormwater model developed by the U.S. Geological Survey in cooperation with the Federal Highway Administration. SELDM simulates flows, concentrations, and loads in stormflows from upstream basins, the highway, best management practice outfalls, and in the receiving water downstream of a highway. SELDM is designed to transform complex scientific data into meaningful information about (1) the risk of adverse effects from stormwater runoff on receiving waters, (2) the potential need for mitigation measures,...
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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 Streamflow statistics calculated from daily mean streamflow data collected during water years 1901–2015 for selected U.S. Geological Survey streamgages 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 Highway-Runoff Database (HRDB) Version 1.0.0b Highway-Runoff Database (HRDB) Version 1.1.0 InterpretSELDM version 1.0 The Stochastic Empirical Loading and Dilution Model (SELDM) output interpreter Model archive for analysis of the effects of impervious cover on receiving-water quality with the Stochastic Empirical Loading Dilution Model (SELDM) 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) Best Management Practices Statistical Estimator (BMPSE) Version 1.2.0 Basin characteristics and point locations of road crossings in Connecticut, Massachusetts, and Rhode Island for highway-runoff mitigation analyses using the Stochastic Empirical Loading and Dilution Model Model archive for analysis of long-term annual yields of highway and urban runoff in selected areas of California with the Stochastic Empirical Loading and Dilution Model (SELDM) Stochastic Empirical Loading and Dilution Model (SELDM) software archive Model archive for analysis of the effects of impervious cover on receiving-water quality with the Stochastic Empirical Loading Dilution Model (SELDM) Basin characteristics and point locations of road crossings in Connecticut, Massachusetts, and Rhode Island for highway-runoff mitigation analyses using the Stochastic Empirical Loading and Dilution Model 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 Model archive for analysis of long-term annual yields of highway and urban runoff in selected areas of California with the Stochastic Empirical Loading and Dilution Model (SELDM) Stochastic Empirical Loading and Dilution Model (SELDM) software archive InterpretSELDM version 1.0 The Stochastic Empirical Loading and Dilution Model (SELDM) output interpreter Highway-Runoff Database (HRDB) Version 1.0.0b Highway-Runoff Database (HRDB) Version 1.1.0 Streamflow statistics calculated from daily mean streamflow data collected during water years 1901–2015 for selected U.S. Geological Survey streamgages Statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM) Best Management Practices Statistical Estimator (BMPSE) Version 1.2.0