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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)

Scientific Investigations Report 2023-5087
Prepared in cooperation with the Federal Highway Administration and the Connecticut, Massachusetts, and Rhode Island Departments of Transportation
By: , , and 
https://doi.org/10.3133/sir20235087

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  • Document: Report (8.64 MB pdf) , HTML , XML
  • Data Releases:
    • USGS data release - 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)
    • USGS data release - Model archive for analysis of long-term annual yields of highway and urban runoff in selected areas of California with the Stochastic Empirical Loading Dilution Model (SELDM)
    • USGS data release - Model archive for analysis of the effects of impervious cover on receiving-water quality with the Stochastic Empirical Loading Dilution Model (SELDM)
    • USGS data release - 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
  • Software Releases:
  • Download citation as: RIS | Dublin Core

Abstract

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.S. Geological Survey, in cooperation with the Federal Highway Administration and the Connecticut, Massachusetts, and Rhode Island Departments of Transportation, documents approaches for assessing flows, concentrations, and loads of highway- and urban-runoff and receiving-stream stormwater in southern New England with SELDM. In this report, the term “urban runoff” is used to identify stormwater flows from developed areas with impervious fractions ranging from 10 to 100 percent without regard to the U.S. Census Bureau designation for any given location. There are more than 48,000 delineated road-stream crossings in southern New England, but because there are relatively few precipitation, streamflow, and water-quality monitoring sites in this area, methods were needed to simulate conditions at unmonitored sites. This report documents simulation methods, methods for interpreting stochastic model results, sensitivity analyses to identify the most critical variables of concern, and examples demonstrating how simulation results can be used to inform scientific decision-making processes. Results of 7,511 SELDM simulations were used to do the sensitivity analyses and provide information decisionmakers can use to address runoff-quality issues in southern New England and other areas of the Nation.

The sensitivity analyses indicate the relatively strong effect of input variables on variations in output results. These analyses indicate that highway and urban runoff quality and upstream water-quality statistics that vary considerably from site to site have the greatest effect on simulated results. Further data are needed to improve available water-quality statistics, and because the number of monitored sites will never approach the number of sites of interest for water-quality management, research is needed to identify methods to select statistics for unmonitored sites and quantify the uncertainties in the selection process. Hydrologically, prestorm streamflows with and without zero flows are the most sensitive and therefore the most important hydrologic variables to quantify. Results of analyses also are sensitive to statistics used for simulating structural best management practices.

Although the focus of the report is on data, statistics, simulation methods, and methods to interpret stochastic simulations, the examples in this report provide results that can be used to inform scientific decision-making processes. The results of 441 simulations that provide regional and site-specific highway and urban runoff yields across southern New England can be used for total maximum daily load analyses. The example stormwater load analysis done for 16 tributaries of the Narragansett Bay demonstrates that highway nitrogen loads are a small fraction of stormwater loads (about 3.6 percent), and a much smaller fraction of all nitrogen loads to the bay, primarily because highways have a small footprint on the land. Examples evaluating the potential effectiveness of end-of-pipe treatment indicate that offsite treatment is warranted in developed areas, and land conservation may be an effective mitigation strategy. The results of these analyses are consistent with conclusions from other simulation and monitoring studies.

Suggested Citation

Granato, G.E., Spaetzel, A.B., and Jeznach, L.C., 2023, 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): U.S. Geological Survey Scientific Investigations Report 2023–5087, 152 p., https://doi.org/10.3133/sir20235087.

ISSN: 2328-0328 (online)

Study Area

Table of Contents

  • Acknowledgments
  • Abstract
  • Introduction
  • Simulation Methods
  • Simulation Results
  • Summary
  • References Cited
Publication type Report
Publication Subtype USGS Numbered Series
Title 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)
Series title Scientific Investigations Report
Series number 2023-5087
DOI 10.3133/sir20235087
Year Published 2023
Language English
Publisher U.S. Geological Survey
Publisher location Reston, VA
Contributing office(s) New England Water Science Center
Description Report: xii, 152 p.; Software Release; 4 Data Releases
Country United States
State Connecticut, Massachusetts, New Hampshire, Rhode Island, Vermont
Online Only (Y/N) Y
Additional Online Files (Y/N) N
Google Analytic Metrics Metrics page
Additional publication details