Gregory Granato (Former Employee)
Science and Products
Transportation-Related Water Projects in New England
The New England Water Science Center collects data and does interpretive studies on hydrology, hydraulics, and water quality in cooperation with the Federal Highway Administration and State Departments of Transportation (DOTs) in New England and other states.
Transportation-Related Water Projects
The USGS has a long history of cooperative investigations with the Federal Highway Administration (FHWA) and state highway agencies to provide data and information to address various issues related to water resources and the Nation’s transportation infrastructure. These issues cover a wide spectrum and include items such as regional flow statistics, flood documentation, regional stream...
SELDM: Stochastic Empirical Loading and Dilution Model - Project page
Note: SELDM is now on version 1.1.1.
Stochastic Empirical Loading and Dilution Model (SELDM) Transportation Research Board Presentation
Note: SELDM is now on version 1.0.3 Please use the new version on the software support page here
National Highway Runoff Water-Quality Data and Methodology Synthesis (NDAMS)
Knowledge of the characteristics of highway runoff (concentrations and loads of constituents and the physical and chemical processes that produce this runoff) is important for decisionmakers, planners, and highway engineers to assess and mitigate possible adverse impacts of highway runoff on the Nation's receiving waters. This project was done by the U.S. Geological Survey (USGS) in cooperation...
FHWA 1990 "Driscoll" Model Pollutant Loadings and Impacts from Highway Stormwater Runoff
More info on the SELDM project web page. Click the link below.
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) 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)
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...
Application of the North Carolina Stochastic Empirical Loading and Dilution Model (SELDM) to Assess Potential Impacts of Highway Runoff Application of the North Carolina Stochastic Empirical Loading and Dilution Model (SELDM) to Assess Potential Impacts of Highway Runoff
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...
Model archive for Assessing long-term annual yields of highway and urban runoff in selected areas of California with the Stochastic Empirical Loading Dilution Model (SELDM) Model archive for Assessing long-term annual yields of highway and urban runoff in selected areas of California with the Stochastic Empirical Loading Dilution Model (SELDM)
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...
Statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM) Statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM)
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...
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 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
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...
Model archive for analysis of the effects of impervious cover on receiving-water quality with the Stochastic Empirical Loading Dilution Model (SELDM) Model archive for analysis of the effects of impervious cover on receiving-water quality with the Stochastic Empirical Loading Dilution Model (SELDM)
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...
Assessing Water Quality from Highway Runoff at Selected Sites in North Carolina with the Stochastic Empirical Loading and Dilution Model (SELDM) Assessing Water Quality from Highway Runoff at Selected Sites in North Carolina with the Stochastic Empirical Loading and Dilution Model (SELDM)
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). 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...
Highway-Runoff Database (HRDB) Version 1.0.0b Highway-Runoff Database (HRDB) Version 1.0.0b
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...
Streamflow statistics calculated from daily mean streamflow data collected during water years 19012015 for selected U.S. Geological Survey streamgages Streamflow statistics calculated from daily mean streamflow data collected during water years 19012015 for selected U.S. Geological Survey streamgages
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...
Filter Total Items: 63
Development of the North Carolina stormwater-treatment decision-support system by using the Stochastic Empirical Loading and Dilution Model (SELDM) Development of the North Carolina stormwater-treatment decision-support system by using the Stochastic Empirical Loading and Dilution Model (SELDM)
The Federal Highway Administration and State departments of transportation nationwide need an efficient method to assess potential adverse effects of highway stormwater runoff on receiving waters to optimize stormwater-treatment decisions. To this end, the U.S. Geological Survey, in cooperation with the Federal Highway Administration and the North Carolina Department of Transportation...
Authors
Gregory E. Granato, Charles C. Stillwell, J. Curtis Weaver, Andrew H. McDaniel, Brian S. Lipscomb, Susan C. Jones, Ryan M. Mullins
Approaches for assessing 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) Approaches for assessing 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)
The Stochastic Empirical Loading and Dilution Model (SELDM) was designed to help quantify 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. SELDM is calibrated using representative hydrological and water-quality input statistics. This report by the U...
Authors
Gregory E. Granato, Alana B. Spaetzel, Lillian C. Jeznach
Assessing potential effects of climate change on highway-runoff flows and loads in southern New England by using planning-level space-for-time analyses Assessing potential effects of climate change on highway-runoff flows and loads in southern New England by using planning-level space-for-time analyses
Transportation agencies need information about the potential effects of climate change on the volume, quality, and treatment of stormwater to mitigate potential effects of runoff on receiving waters. To address these concerns, the U.S. Geological Survey and the Federal Highway Administration used the Coupled Model Intercomparison Project tool and the Stochastic Empirical Loading and...
Authors
Lillian C. Jeznach, Gregory E. Granato, Daniel Sharar-Salgado, Susan C. Jones, Daniel Imig
Assessing the impact of chloride deicer application in the Siskiyou Pass, southern Oregon Assessing the impact of chloride deicer application in the Siskiyou Pass, southern Oregon
Chloride deicers have been applied by the Oregon Department of Transportation (ODOT) to Interstate Route 5 (I–5) from the Oregon-California border north to mile marker 10 for several years in the high-elevation area known as the Siskiyou Pass. Magnesium chloride (MgCl2) and sodium chloride (NaCl) are applied to keep the interstate highway safe for drivers and allow for efficient...
Authors
Adam J. Stonewall, Matthew C. Yates, Gregory E. Granato
Approaches for assessing long-term annual yields of highway and urban runoff in selected areas of California with the Stochastic Empirical Loading and Dilution Model (SELDM) Approaches for assessing long-term annual yields of highway and urban runoff in selected areas of California with the Stochastic Empirical Loading and Dilution Model (SELDM)
The California Department of Transportation, commonly known as CalTrans, and other municipal separate storm sewer system permittees in California as well as other State departments of transportation nationwide need information about potential loads and yields (loads per unit area) of constituents of concern in stormwater runoff and discharges from stormwater best management practices...
Authors
Gregory E. Granato, Paul J. Friesz
Statistical methods for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM) Statistical methods for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM)
This report documents statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM). The U.S. Geological Survey developed SELDM and the statistics documented in this report in cooperation with the Federal Highway Administration to indicate the risk for stormwater flows, concentrations, and loads to...
Authors
Gregory E. Granato, Alana B. Spaetzel, Laura Medalie
Comparison of SELDM simulated total-phosphorus concentrations with ecological impervious-area criteria Comparison of SELDM simulated total-phosphorus concentrations with ecological impervious-area criteria
Ecological studies indicate that impervious cover (IC) greater than approximately 5%–20% may have adverse effects on receiving-stream ecology. It is difficult to separate the effects of runoff quality from other effects of urbanization on receiving streams. This study presents the results of a numerical experiment to assess the effects of increasing IC on water quality using the...
Authors
Lillian C. Jeznach, Gregory E. Granato
Assessing potential effects of highway and urban runoff on receiving streams in total maximum daily load watersheds in Oregon using the stochastic empirical loading and dilution model Assessing potential effects of highway and urban runoff on receiving streams in total maximum daily load watersheds in Oregon using the stochastic empirical loading and dilution model
The Stochastic Empirical Loading and Dilution Model (SELDM) was developed by the U.S. Geological Survey (USGS) in cooperation with the Federal Highway Administration to simulate stormwater quality. To assess the effects of runoff, SELDM uses a stochastic mass-balance approach to estimate combinations of pre-storm streamflow, stormflow, highway runoff, event mean concentrations (EMCs) and...
Authors
Adam J. Stonewall, Gregory E. Granato, Kira M. Glover-Cutter
Assessing water quality from highway runoff at selected sites in North Carolina with the Stochastic Empirical Loading and Dilution Model (SELDM) Assessing water quality from highway runoff at selected sites in North Carolina with the Stochastic Empirical Loading and Dilution Model (SELDM)
In 2015, the U.S. Geological Survey (USGS) entered into a cooperative agreement with the North Carolina Department of Transportation (NCDOT) to develop a North Carolina-enhanced variation of the national Stochastic Empirical Loading and Dilution Model (SELDM) with available North Carolina-specific streamflow and water-quality data and to demonstrate use of the model by documenting...
Authors
J. Curtis Weaver, Gregory E. Granato, Sharon A. Fitzgerald
Simulating runoff quality with the highway-runoff database and the Stochastic Empirical Loading and Dilution Model Simulating runoff quality with the highway-runoff database and the Stochastic Empirical Loading and Dilution Model
Stormwater practitioners need quantitative information about the quality and volume of highway runoff to assess and mitigate potential adverse effects of runoff on the Nation’s receiving waters. The U.S. Geological Survey developed the Highway Runoff Database (HRDB) in cooperation with the FHWA to provide practice-ready information to meet these information needs on the local or national...
Authors
Gregory E. Granato, Susan C. Jones
User guide for the Massachusetts Sustainable-Yield Estimator (MA SYE—version 2.0) computer program User guide for the Massachusetts Sustainable-Yield Estimator (MA SYE—version 2.0) computer program
This report is a user guide for 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...
Authors
Gregory E. Granato, Sara B. Levin
Methods used to estimate daily streamflow and water availability in the Massachusetts Sustainable-Yield Estimator version 2.0 Methods used to estimate daily streamflow and water availability in the Massachusetts Sustainable-Yield Estimator version 2.0
The Massachusetts Sustainable-Yield Estimator is a decision support tool that provides estimates of daily unaltered streamflow, water-use-adjusted streamflow, and water availability for ungaged, user-defined basins in Massachusetts. Daily streamflow at the ungaged site is estimated for unaltered (no water use) and water-use scenarios. The procedure for estimating streamflow was developed...
Authors
Sara B. Levin, Gregory E. Granato
Non-USGS Publications**
Granato, G.E., Church, P.E., and Stone V.J., 1995, Mobilization of Major and Trace Constituents of Highway Runoff in Groundwater Potentially Caused by Deicing-Chemical Migration, Transportation Research Record 1483: Transportation Research Board, National Research Council, Washington D.C., p. 92-104
Church, P.E., and Granato, G.E., 1996, Bias in groundwater data caused by well-bore flow in long-screen wells: Groundwater, Vol. 34, No. 2, p. 262-273. https://dx.doi.org/10.1111/j.1745-6584.1996.tb01886.x
Granato, G.E., 1996, Deicing chemicals as a source of constituents in highway runoff: Transportation Research Record 1533, Transportation Research Board, National Research Council, Washington D.C., p. 50-58. https://doi.org/10.3141/1533-08
Bank, F.G., Cazenas P.A., Cutshall, C.D., Granato, G.E., Iyer B., Jongedyk, H., Palumbo, V.J., Prendergast G., Salter, J., Storey B., Young, G.K., 1997, Water Quality and Hydrology: in Environmental Research Needs in Transportation, Transportation Research Circular 469, Transportation Research Board, National Research Council, Washington D.C. p. 73-80.
Granato, G.E., and Smith, K.P., 1999, Robowell An automated process for monitoring groundwater quality using established sampling protocols. Groundwater Monitoring and Remediation, v. 19, no. 4, p. 81-89. https://dx.doi.org/10.1111/j.1745-6592.1999.tb00243.x
Buckler, D.R., and Granato, G.E., 1999, Assessing biological effects from highway-runoff constituents: U.S. Geological Survey Open File Report 99-240, 45 p. https://pubs.usgs.gov/of/1999/ofr99-240/
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Filter Total Items: 13
Stochastic Empirical Loading and Dilution Model (SELDM) software archive Stochastic Empirical Loading and Dilution Model (SELDM) software archive
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...
Best Management Practices Statistical Estimator (BMPSE) Version 1.2.0 Best Management Practices Statistical Estimator (BMPSE) Version 1.2.0
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...
InterpretSELDM version 1.0 The Stochastic Empirical Loading and Dilution Model (SELDM) output interpreter InterpretSELDM version 1.0 The Stochastic Empirical Loading and Dilution Model (SELDM) output interpreter
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...
Highway-Runoff Database (HRDB) Version 1.1 Highway-Runoff Database (HRDB) Version 1.1
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...
Connecticut Streamflow and Sustainable Water Use Estimator (CTSSWUE Version 1.0) application software Connecticut Streamflow and Sustainable Water Use Estimator (CTSSWUE Version 1.0) application software
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...
Massachusetts Sustainable-Yield Estimator (MASYE) application software (version 2.0) Massachusetts Sustainable-Yield Estimator (MASYE) application software (version 2.0)
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...
HyDroDSS: Hydrologic Drought Decision Support System - Software page HyDroDSS: Hydrologic Drought Decision Support System - Software page
The HyDroDSS is designed to provide water managers with risk-based information for balancing water-supply needs and aquatic-habitat protection goals to mitigate potential effects of hydrologic drought.
SELDM: Stochastic Empirical Loading and Dilution Model - Software page SELDM: Stochastic Empirical Loading and Dilution Model - Software page
Overview The Stochastic Empirical Loading and Dilution Model (SELDM) is designed 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.
HRDB: Highway Runoff DataBase - Software page HRDB: Highway Runoff DataBase - Software page
Overview The highway-runoff database (HRDB) was developed to serve as a data warehouse for current and future highway-runoff data sets. The database can be used by transportation agencies and researchers as a data warehouse to document information about a data set, monitoring site(s), highway-runoff data (including precipitation, runoff, and event mean concentrations).
SWQDM: Surface Water Quality Data Miner - Software page SWQDM: Surface Water Quality Data Miner - Software page
Overview The SWQDM database application was developed by the U.S. Geological Survey in cooperation with the Federal Highway Administration for use in the analysis of regional and national hydrologic data sets. The surface-water quality data miner (SWQDM) database application was developed to coordinate use of NWIS Web, NWiz, and the Kendall-Theil Robust Line analysis software.
Data mining and analysis software for USGS NWIS Web streamflow data Data mining and analysis software for USGS NWIS Web streamflow data
Overview Five computer programs were developed for obtaining and analyzing streamflow from the National Water Information System (NWISWeb). The programs were developed as part of a study by the U.S. Geological Survey, in cooperation with the Federal Highway Administration, to develop a stochastic empirical loading and dilution model.
KTRLine: Kendall-Theil Robust Line - Software page KTRLine: Kendall-Theil Robust Line - Software page
Overview The Kendall-Theil Robust Line software (KTRLine—version 1.0) is a Visual Basic program that may be used with the Microsoft Windows operating system to calculate parameters for robust, nonparametric estimates of linear-regression coefficients between two continuous variables.
Science and Products
Transportation-Related Water Projects in New England
The New England Water Science Center collects data and does interpretive studies on hydrology, hydraulics, and water quality in cooperation with the Federal Highway Administration and State Departments of Transportation (DOTs) in New England and other states.
Transportation-Related Water Projects
The USGS has a long history of cooperative investigations with the Federal Highway Administration (FHWA) and state highway agencies to provide data and information to address various issues related to water resources and the Nation’s transportation infrastructure. These issues cover a wide spectrum and include items such as regional flow statistics, flood documentation, regional stream...
SELDM: Stochastic Empirical Loading and Dilution Model - Project page
Note: SELDM is now on version 1.1.1.
Stochastic Empirical Loading and Dilution Model (SELDM) Transportation Research Board Presentation
Note: SELDM is now on version 1.0.3 Please use the new version on the software support page here
National Highway Runoff Water-Quality Data and Methodology Synthesis (NDAMS)
Knowledge of the characteristics of highway runoff (concentrations and loads of constituents and the physical and chemical processes that produce this runoff) is important for decisionmakers, planners, and highway engineers to assess and mitigate possible adverse impacts of highway runoff on the Nation's receiving waters. This project was done by the U.S. Geological Survey (USGS) in cooperation...
FHWA 1990 "Driscoll" Model Pollutant Loadings and Impacts from Highway Stormwater Runoff
More info on the SELDM project web page. Click the link below.
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) 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)
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...
Application of the North Carolina Stochastic Empirical Loading and Dilution Model (SELDM) to Assess Potential Impacts of Highway Runoff Application of the North Carolina Stochastic Empirical Loading and Dilution Model (SELDM) to Assess Potential Impacts of Highway Runoff
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...
Model archive for Assessing long-term annual yields of highway and urban runoff in selected areas of California with the Stochastic Empirical Loading Dilution Model (SELDM) Model archive for Assessing long-term annual yields of highway and urban runoff in selected areas of California with the Stochastic Empirical Loading Dilution Model (SELDM)
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...
Statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM) Statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM)
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...
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 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
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...
Model archive for analysis of the effects of impervious cover on receiving-water quality with the Stochastic Empirical Loading Dilution Model (SELDM) Model archive for analysis of the effects of impervious cover on receiving-water quality with the Stochastic Empirical Loading Dilution Model (SELDM)
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...
Assessing Water Quality from Highway Runoff at Selected Sites in North Carolina with the Stochastic Empirical Loading and Dilution Model (SELDM) Assessing Water Quality from Highway Runoff at Selected Sites in North Carolina with the Stochastic Empirical Loading and Dilution Model (SELDM)
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). 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...
Highway-Runoff Database (HRDB) Version 1.0.0b Highway-Runoff Database (HRDB) Version 1.0.0b
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...
Streamflow statistics calculated from daily mean streamflow data collected during water years 19012015 for selected U.S. Geological Survey streamgages Streamflow statistics calculated from daily mean streamflow data collected during water years 19012015 for selected U.S. Geological Survey streamgages
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...
Filter Total Items: 63
Development of the North Carolina stormwater-treatment decision-support system by using the Stochastic Empirical Loading and Dilution Model (SELDM) Development of the North Carolina stormwater-treatment decision-support system by using the Stochastic Empirical Loading and Dilution Model (SELDM)
The Federal Highway Administration and State departments of transportation nationwide need an efficient method to assess potential adverse effects of highway stormwater runoff on receiving waters to optimize stormwater-treatment decisions. To this end, the U.S. Geological Survey, in cooperation with the Federal Highway Administration and the North Carolina Department of Transportation...
Authors
Gregory E. Granato, Charles C. Stillwell, J. Curtis Weaver, Andrew H. McDaniel, Brian S. Lipscomb, Susan C. Jones, Ryan M. Mullins
Approaches for assessing 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) Approaches for assessing 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)
The Stochastic Empirical Loading and Dilution Model (SELDM) was designed to help quantify 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. SELDM is calibrated using representative hydrological and water-quality input statistics. This report by the U...
Authors
Gregory E. Granato, Alana B. Spaetzel, Lillian C. Jeznach
Assessing potential effects of climate change on highway-runoff flows and loads in southern New England by using planning-level space-for-time analyses Assessing potential effects of climate change on highway-runoff flows and loads in southern New England by using planning-level space-for-time analyses
Transportation agencies need information about the potential effects of climate change on the volume, quality, and treatment of stormwater to mitigate potential effects of runoff on receiving waters. To address these concerns, the U.S. Geological Survey and the Federal Highway Administration used the Coupled Model Intercomparison Project tool and the Stochastic Empirical Loading and...
Authors
Lillian C. Jeznach, Gregory E. Granato, Daniel Sharar-Salgado, Susan C. Jones, Daniel Imig
Assessing the impact of chloride deicer application in the Siskiyou Pass, southern Oregon Assessing the impact of chloride deicer application in the Siskiyou Pass, southern Oregon
Chloride deicers have been applied by the Oregon Department of Transportation (ODOT) to Interstate Route 5 (I–5) from the Oregon-California border north to mile marker 10 for several years in the high-elevation area known as the Siskiyou Pass. Magnesium chloride (MgCl2) and sodium chloride (NaCl) are applied to keep the interstate highway safe for drivers and allow for efficient...
Authors
Adam J. Stonewall, Matthew C. Yates, Gregory E. Granato
Approaches for assessing long-term annual yields of highway and urban runoff in selected areas of California with the Stochastic Empirical Loading and Dilution Model (SELDM) Approaches for assessing long-term annual yields of highway and urban runoff in selected areas of California with the Stochastic Empirical Loading and Dilution Model (SELDM)
The California Department of Transportation, commonly known as CalTrans, and other municipal separate storm sewer system permittees in California as well as other State departments of transportation nationwide need information about potential loads and yields (loads per unit area) of constituents of concern in stormwater runoff and discharges from stormwater best management practices...
Authors
Gregory E. Granato, Paul J. Friesz
Statistical methods for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM) Statistical methods for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM)
This report documents statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM). The U.S. Geological Survey developed SELDM and the statistics documented in this report in cooperation with the Federal Highway Administration to indicate the risk for stormwater flows, concentrations, and loads to...
Authors
Gregory E. Granato, Alana B. Spaetzel, Laura Medalie
Comparison of SELDM simulated total-phosphorus concentrations with ecological impervious-area criteria Comparison of SELDM simulated total-phosphorus concentrations with ecological impervious-area criteria
Ecological studies indicate that impervious cover (IC) greater than approximately 5%–20% may have adverse effects on receiving-stream ecology. It is difficult to separate the effects of runoff quality from other effects of urbanization on receiving streams. This study presents the results of a numerical experiment to assess the effects of increasing IC on water quality using the...
Authors
Lillian C. Jeznach, Gregory E. Granato
Assessing potential effects of highway and urban runoff on receiving streams in total maximum daily load watersheds in Oregon using the stochastic empirical loading and dilution model Assessing potential effects of highway and urban runoff on receiving streams in total maximum daily load watersheds in Oregon using the stochastic empirical loading and dilution model
The Stochastic Empirical Loading and Dilution Model (SELDM) was developed by the U.S. Geological Survey (USGS) in cooperation with the Federal Highway Administration to simulate stormwater quality. To assess the effects of runoff, SELDM uses a stochastic mass-balance approach to estimate combinations of pre-storm streamflow, stormflow, highway runoff, event mean concentrations (EMCs) and...
Authors
Adam J. Stonewall, Gregory E. Granato, Kira M. Glover-Cutter
Assessing water quality from highway runoff at selected sites in North Carolina with the Stochastic Empirical Loading and Dilution Model (SELDM) Assessing water quality from highway runoff at selected sites in North Carolina with the Stochastic Empirical Loading and Dilution Model (SELDM)
In 2015, the U.S. Geological Survey (USGS) entered into a cooperative agreement with the North Carolina Department of Transportation (NCDOT) to develop a North Carolina-enhanced variation of the national Stochastic Empirical Loading and Dilution Model (SELDM) with available North Carolina-specific streamflow and water-quality data and to demonstrate use of the model by documenting...
Authors
J. Curtis Weaver, Gregory E. Granato, Sharon A. Fitzgerald
Simulating runoff quality with the highway-runoff database and the Stochastic Empirical Loading and Dilution Model Simulating runoff quality with the highway-runoff database and the Stochastic Empirical Loading and Dilution Model
Stormwater practitioners need quantitative information about the quality and volume of highway runoff to assess and mitigate potential adverse effects of runoff on the Nation’s receiving waters. The U.S. Geological Survey developed the Highway Runoff Database (HRDB) in cooperation with the FHWA to provide practice-ready information to meet these information needs on the local or national...
Authors
Gregory E. Granato, Susan C. Jones
User guide for the Massachusetts Sustainable-Yield Estimator (MA SYE—version 2.0) computer program User guide for the Massachusetts Sustainable-Yield Estimator (MA SYE—version 2.0) computer program
This report is a user guide for 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...
Authors
Gregory E. Granato, Sara B. Levin
Methods used to estimate daily streamflow and water availability in the Massachusetts Sustainable-Yield Estimator version 2.0 Methods used to estimate daily streamflow and water availability in the Massachusetts Sustainable-Yield Estimator version 2.0
The Massachusetts Sustainable-Yield Estimator is a decision support tool that provides estimates of daily unaltered streamflow, water-use-adjusted streamflow, and water availability for ungaged, user-defined basins in Massachusetts. Daily streamflow at the ungaged site is estimated for unaltered (no water use) and water-use scenarios. The procedure for estimating streamflow was developed...
Authors
Sara B. Levin, Gregory E. Granato
Non-USGS Publications**
Granato, G.E., Church, P.E., and Stone V.J., 1995, Mobilization of Major and Trace Constituents of Highway Runoff in Groundwater Potentially Caused by Deicing-Chemical Migration, Transportation Research Record 1483: Transportation Research Board, National Research Council, Washington D.C., p. 92-104
Church, P.E., and Granato, G.E., 1996, Bias in groundwater data caused by well-bore flow in long-screen wells: Groundwater, Vol. 34, No. 2, p. 262-273. https://dx.doi.org/10.1111/j.1745-6584.1996.tb01886.x
Granato, G.E., 1996, Deicing chemicals as a source of constituents in highway runoff: Transportation Research Record 1533, Transportation Research Board, National Research Council, Washington D.C., p. 50-58. https://doi.org/10.3141/1533-08
Bank, F.G., Cazenas P.A., Cutshall, C.D., Granato, G.E., Iyer B., Jongedyk, H., Palumbo, V.J., Prendergast G., Salter, J., Storey B., Young, G.K., 1997, Water Quality and Hydrology: in Environmental Research Needs in Transportation, Transportation Research Circular 469, Transportation Research Board, National Research Council, Washington D.C. p. 73-80.
Granato, G.E., and Smith, K.P., 1999, Robowell An automated process for monitoring groundwater quality using established sampling protocols. Groundwater Monitoring and Remediation, v. 19, no. 4, p. 81-89. https://dx.doi.org/10.1111/j.1745-6592.1999.tb00243.x
Buckler, D.R., and Granato, G.E., 1999, Assessing biological effects from highway-runoff constituents: U.S. Geological Survey Open File Report 99-240, 45 p. https://pubs.usgs.gov/of/1999/ofr99-240/
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Filter Total Items: 13
Stochastic Empirical Loading and Dilution Model (SELDM) software archive Stochastic Empirical Loading and Dilution Model (SELDM) software archive
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...
Best Management Practices Statistical Estimator (BMPSE) Version 1.2.0 Best Management Practices Statistical Estimator (BMPSE) Version 1.2.0
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...
InterpretSELDM version 1.0 The Stochastic Empirical Loading and Dilution Model (SELDM) output interpreter InterpretSELDM version 1.0 The Stochastic Empirical Loading and Dilution Model (SELDM) output interpreter
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...
Highway-Runoff Database (HRDB) Version 1.1 Highway-Runoff Database (HRDB) Version 1.1
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...
Connecticut Streamflow and Sustainable Water Use Estimator (CTSSWUE Version 1.0) application software Connecticut Streamflow and Sustainable Water Use Estimator (CTSSWUE Version 1.0) application software
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...
Massachusetts Sustainable-Yield Estimator (MASYE) application software (version 2.0) Massachusetts Sustainable-Yield Estimator (MASYE) application software (version 2.0)
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...
HyDroDSS: Hydrologic Drought Decision Support System - Software page HyDroDSS: Hydrologic Drought Decision Support System - Software page
The HyDroDSS is designed to provide water managers with risk-based information for balancing water-supply needs and aquatic-habitat protection goals to mitigate potential effects of hydrologic drought.
SELDM: Stochastic Empirical Loading and Dilution Model - Software page SELDM: Stochastic Empirical Loading and Dilution Model - Software page
Overview The Stochastic Empirical Loading and Dilution Model (SELDM) is designed 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.
HRDB: Highway Runoff DataBase - Software page HRDB: Highway Runoff DataBase - Software page
Overview The highway-runoff database (HRDB) was developed to serve as a data warehouse for current and future highway-runoff data sets. The database can be used by transportation agencies and researchers as a data warehouse to document information about a data set, monitoring site(s), highway-runoff data (including precipitation, runoff, and event mean concentrations).
SWQDM: Surface Water Quality Data Miner - Software page SWQDM: Surface Water Quality Data Miner - Software page
Overview The SWQDM database application was developed by the U.S. Geological Survey in cooperation with the Federal Highway Administration for use in the analysis of regional and national hydrologic data sets. The surface-water quality data miner (SWQDM) database application was developed to coordinate use of NWIS Web, NWiz, and the Kendall-Theil Robust Line analysis software.
Data mining and analysis software for USGS NWIS Web streamflow data Data mining and analysis software for USGS NWIS Web streamflow data
Overview Five computer programs were developed for obtaining and analyzing streamflow from the National Water Information System (NWISWeb). The programs were developed as part of a study by the U.S. Geological Survey, in cooperation with the Federal Highway Administration, to develop a stochastic empirical loading and dilution model.
KTRLine: Kendall-Theil Robust Line - Software page KTRLine: Kendall-Theil Robust Line - Software page
Overview The Kendall-Theil Robust Line software (KTRLine—version 1.0) is a Visual Basic program that may be used with the Microsoft Windows operating system to calculate parameters for robust, nonparametric estimates of linear-regression coefficients between two continuous variables.