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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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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 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...
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 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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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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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 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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Highway runoff is a source of chemical constituents to downstream waterbodies that can be managed with the use of stormwater-control measures that reduce sediment loads. The use of open-graded friction course (OGFC) pavement has been identified as a method to reduce loads from highway runoff because it retains sediment in pavement voids. Few datasets are available, though, in New England to characterize runoff quality from OGFC pavement. To meet this data need, the U.S. Geological Survey, in cooperation with the Massachusetts Department of Transportation, conducted a field study from October 2018 through September 2021 (water years [WYs] 2019-21) to monitor highway runoff from a section of traditional dense-graded...
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This data release documents the data and models used to assess flows, concentrations, and loads of highway and urban runoff and of stormwater within receiving streams in southern New England. There are more than 48,000 locations in southern New England where roads cross streams and many more locations where runoff from developed areas may discharge to receiving streams; information about runoff discharges and the quantity and quality of stormflow upstream and downstream of discharge points is needed to inform resource-management decisions. This analysis was done with a version 1.1.1 of the Stochastic Empirical Loading and Dilution Model (SELDM) that was populated with regional statistics for southern New England....


    map background search result map search result map 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 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 Flows, Concentrations, and Loads of Highway and Urban Runoff and Receiving-Stream Stormwater in Southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM) Highway-Monitoring Data from Segments of Open-Graded Friction Course and Dense-Graded Hot-Mix Asphalt Pavement in Eastern Massachusetts, 2018-2021 Highway-Monitoring Data from Segments of Open-Graded Friction Course and Dense-Graded Hot-Mix Asphalt Pavement in Eastern Massachusetts, 2018-2021 Model Archive for Analysis of Flows, Concentrations, and Loads of Highway and Urban Runoff and Receiving-Stream Stormwater in Southern New England with the Stochastic Empirical Loading and 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 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 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