Photograph of bridge-deck scuppers draining into the Charles River on State Route 2A in Boston near U.S. Geological Survey bridge-deck-monitoring station 422108071052501 during a rainstorm.
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.
Hydrologic studies include efforts to measure and analyze streamflows to provide flood-flow estimates that are available in the on-line StreamStats applications. Hydraulic studies include efforts to quantify bridge scour, stream-channel geometry, and runoff timing variables. Water-quality studies include efforts to measure, analyze, and model the concentrations, flows, and loads of stormflows. Water-quality studies also include efforts to measure and analyze changes in groundwater quality associated with the construction and operation of the transportation infrastructure. The results of these efforts are designed to provide tools, techniques, and information that can be used by decisionmakers to meet the DOTs missions to provide a transportation infrastructure that is safe, reliable, robust, and resilient while minimizing adverse effects on the environment.
Below are other science projects associated with this project.
Transportation-Related Water Projects
Delineating High-Resolution Urban Drainage Systems for Stormwater Management in the Mystic River Watershed
Quality of Stormwater Runoff Discharged from Connecticut Highways
Effectiveness of Open-Graded Friction Course Pavement in Reducing Suspended-Sediment Loads Discharged from Massachusetts Highways
A Statewide Hydraulic Modeling Tool for Stream Crossing Projects in Massachusetts
Development of Regional Regression Equations to Estimate the Magnitude of Peak Flows for Selected Annual-Exceedance Probabilities in Maine
Development of Regional Regression Equations in Connecticut
SELDM: Stochastic Empirical Loading and Dilution Model - Project page
Below are data or web applications associated with this project.
Highway-Monitoring Data from Segments of Open-Graded Friction Course and Dense-Graded Hot-Mix Asphalt Pavement in Eastern Massachusetts, 2018-2021
Digital Elevation Model and Derivative Datasets to Support the Integration of Stormwater Drainage into the StreamStats Application for the Mystic River Watershed, Massachusetts
Basin Characteristics Data for the StreamStats Application in the Mystic River Basin, Massachusetts
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)
Statistics for simulating structural stormwater runoff best management practices (BMPs) 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 the effects of impervious cover on receiving-water quality with the Stochastic Empirical Loading Dilution Model (SELDM)
Transportation Risk Assessment for Planning and Project Delivery (TRAPPD) Python Script Tool for Maine
Below are multimedia items associated with this project.
Photograph of bridge-deck scuppers draining into the Charles River on State Route 2A in Boston near U.S. Geological Survey bridge-deck-monitoring station 422108071052501 during a rainstorm.
Below are publications associated with this project.
Highway-runoff quality from segments of open-graded friction course and dense-graded hot-mix asphalt pavement on Interstate 95, Massachusetts, 2018–21
Highway runoff is a source of sediment and associated 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; however, few datasets are available in New En
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)
Assessing potential effects of climate change on highway-runoff flows and loads in southern New England by using planning-level space-for-time analyses
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)
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 exceed us
Comparison of SELDM simulated total-phosphorus concentrations with ecological impervious-area criteria
Simulating runoff quality with the highway-runoff database and the Stochastic Empirical Loading and Dilution Model
Characterization of stormwater runoff from bridge decks in eastern Massachusetts, 2014–16
Compilation of streamflow statistics calculated from daily mean streamflow data collected during water years 1901–2015 for selected U.S. Geological Survey streamgages
Estimating total maximum daily loads with the Stochastic Empirical Loading and Dilution Model
Methods for evaluating potential sources of chloride in surface waters and groundwaters of the conterminous United States
Stochastic empirical loading and dilution model for analysis of flows, concentrations, and loads of highway runoff constituents
Below are software products associated with this project.
Stochastic Empirical Loading and Dilution Model (SELDM) software archive
Best Management Practices Statistical Estimator (BMPSE) Version 1.2.0
InterpretSELDM version 1.0 The Stochastic Empirical Loading and Dilution Model (SELDM) output interpreter
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
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
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
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.
Below are partners associated with this project.
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.
Hydrologic studies include efforts to measure and analyze streamflows to provide flood-flow estimates that are available in the on-line StreamStats applications. Hydraulic studies include efforts to quantify bridge scour, stream-channel geometry, and runoff timing variables. Water-quality studies include efforts to measure, analyze, and model the concentrations, flows, and loads of stormflows. Water-quality studies also include efforts to measure and analyze changes in groundwater quality associated with the construction and operation of the transportation infrastructure. The results of these efforts are designed to provide tools, techniques, and information that can be used by decisionmakers to meet the DOTs missions to provide a transportation infrastructure that is safe, reliable, robust, and resilient while minimizing adverse effects on the environment.
Below are other science projects associated with this project.
Transportation-Related Water Projects
Delineating High-Resolution Urban Drainage Systems for Stormwater Management in the Mystic River Watershed
Quality of Stormwater Runoff Discharged from Connecticut Highways
Effectiveness of Open-Graded Friction Course Pavement in Reducing Suspended-Sediment Loads Discharged from Massachusetts Highways
A Statewide Hydraulic Modeling Tool for Stream Crossing Projects in Massachusetts
Development of Regional Regression Equations to Estimate the Magnitude of Peak Flows for Selected Annual-Exceedance Probabilities in Maine
Development of Regional Regression Equations in Connecticut
SELDM: Stochastic Empirical Loading and Dilution Model - Project page
Below are data or web applications associated with this project.
Highway-Monitoring Data from Segments of Open-Graded Friction Course and Dense-Graded Hot-Mix Asphalt Pavement in Eastern Massachusetts, 2018-2021
Digital Elevation Model and Derivative Datasets to Support the Integration of Stormwater Drainage into the StreamStats Application for the Mystic River Watershed, Massachusetts
Basin Characteristics Data for the StreamStats Application in the Mystic River Basin, Massachusetts
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)
Statistics for simulating structural stormwater runoff best management practices (BMPs) 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 the effects of impervious cover on receiving-water quality with the Stochastic Empirical Loading Dilution Model (SELDM)
Transportation Risk Assessment for Planning and Project Delivery (TRAPPD) Python Script Tool for Maine
Below are multimedia items associated with this project.
Photograph of bridge-deck scuppers draining into the Charles River on State Route 2A in Boston near U.S. Geological Survey bridge-deck-monitoring station 422108071052501 during a rainstorm.
Photograph of bridge-deck scuppers draining into the Charles River on State Route 2A in Boston near U.S. Geological Survey bridge-deck-monitoring station 422108071052501 during a rainstorm.
Below are publications associated with this project.
Highway-runoff quality from segments of open-graded friction course and dense-graded hot-mix asphalt pavement on Interstate 95, Massachusetts, 2018–21
Highway runoff is a source of sediment and associated 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; however, few datasets are available in New En
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)
Assessing potential effects of climate change on highway-runoff flows and loads in southern New England by using planning-level space-for-time analyses
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)
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 exceed us
Comparison of SELDM simulated total-phosphorus concentrations with ecological impervious-area criteria
Simulating runoff quality with the highway-runoff database and the Stochastic Empirical Loading and Dilution Model
Characterization of stormwater runoff from bridge decks in eastern Massachusetts, 2014–16
Compilation of streamflow statistics calculated from daily mean streamflow data collected during water years 1901–2015 for selected U.S. Geological Survey streamgages
Estimating total maximum daily loads with the Stochastic Empirical Loading and Dilution Model
Methods for evaluating potential sources of chloride in surface waters and groundwaters of the conterminous United States
Stochastic empirical loading and dilution model for analysis of flows, concentrations, and loads of highway runoff constituents
Below are software products associated with this project.
Stochastic Empirical Loading and Dilution Model (SELDM) software archive
Best Management Practices Statistical Estimator (BMPSE) Version 1.2.0
InterpretSELDM version 1.0 The Stochastic Empirical Loading and Dilution Model (SELDM) output interpreter
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
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
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
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.
Below are partners associated with this project.