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Filters: partyWithName: Gregory E Granato (X) > partyWithName: U.S. Geological Survey (X)

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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...
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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 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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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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This software release provides the database application that runs the Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE) computer program (version 1.0). The CT SSWUE was developed by the U.S. Geological Survey, in cooperation with the Connecticut Department of Energy and Environmental Protection, to provide a planning-level decision-support tool designed to help decision makers estimate daily mean streamflows and selected streamflow statistics that can be used to assess sustainable water use at ungaged sites in Connecticut. The CT SSWUE provides estimates of unaltered streamflow (which is assumed to include effects of minimal human development but not the effects of instream regulation or water...
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This software release provides the database application that runs the Massachusetts Sustainable-Yield Estimator (MA SYE) computer program (version 2.0). The MA SYE was developed by the U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, to provide a planning-level decision-support tool designed to help decision makers estimate daily mean streamflows and selected streamflow statistics that can be used to assess sustainable water use at ungaged sites in Massachusetts. The MA SYE provides estimates of unaltered streamflow (which is assumed to include effects of minimal human development but not the effects of instream regulation or water use), net streamflow alterations...


    map background search result map search result map Connecticut Streamflow and Sustainable Water Use Estimator (CTSSWUE Version 1.0) application software Massachusetts Sustainable-Yield Estimator (MASYE) application software (version 2.0) Highway-Runoff Database (HRDB) Version 1.1.0 Model archive for analysis of the effects of impervious cover on receiving-water quality with the Stochastic Empirical Loading Dilution Model (SELDM) 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 Connecticut Streamflow and Sustainable Water Use Estimator (CTSSWUE Version 1.0) application software Massachusetts Sustainable-Yield Estimator (MASYE) application software (version 2.0) 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 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 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