SELDM: Stochastic Empirical Loading and Dilution Model - Project page

Please use the new version on the software support page here.

The U.S. Geological Survey (USGS) and the Federal Highway Administration (FHWA) are currently cooperating in a national project to redesign the FHWA's highway-runoff quality planning model. The FHWA initiated the project to update the 1990 FHWA highway runoff quality model to reflect changes in runoff quality and to address the importance of upstream receiving-water concentrations for assessing the potential effects of runoff in these receiving waters. We developed the SELDM as a database application so that users can easily create and run highway-runoff simulations. SELDM simulates storm flows, concentrations, and loads. SELDM calculates the risk of exceeding water-quality criteria with and without user-defined BMPs. SELDM calculates annual runoff loads and is able to do a simple annual lake-loading analysis. We also developed national data sets for highway-runoff quality, precipitation, streamflow, runoff coefficients, and background water quality for use with the model. We developed these data sets so that users can easily select choices that represent the site a site of interest to use with the model. SELDM uses Monte-Carlo methods to quantify the effects of precipitation characteristics, streamflow, estimated runoff quantity and quality, and best management practices on the probability distribution of receiving-water concentrations. This web page will provide a catalog of reports and other information as these materials become available.

SELDM was developed in cooperation with the FHWA Office of Project Development and Environmental Review please see the: FHWA Natural Environment Web Page

This effort is an update of the FHWA 1990 model, which is now available here

This effort is an offshoot of the National Highway Runoff Water-Quality Data and Methodology Synthesis

Model Manual

Granato, G.E., 2013, Stochastic empirical loading and dilution model (SELDM) version 1.0.0: U.S. Geological Survey Techniques and Methods, book 4, chap. C3, 112 p., CD–ROM. https://doi.org/10.3133/tm4C3

Upcoming Training

Open to employees of Federal, State, and Local Governments:
We have held classes in cooperation with the FHWA and State DOTs in California, Colorado, Massachusetts, Oregon, Nevada, North Carolina, Texas, and Washington DC. If you are an employee of a Federal, State, or local government agency, then please send an email expressing your interest in a training class to the USGS project contact on this page. 

Spaetzel, A.B., Granato, G.E., and Wares, K. M., 2024, Highway-Runoff Database (HRDB) Version 1.2.0: U.S. Geological Survey data release, https://doi.org/10.5066/P1KXPEBW.

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; 2019; Granato and others, 2018; Granato and Friesz, 2021). 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 with the FHWA in 2009 (Granato and Cazenas, 2009). The second version (1.0.0a) was published in cooperation with the Massachusetts Department of Transportation Highway Division to include data from Ohio and Massachusetts (Smith and Granato, 2010). The third version (1.0.0b) was published in cooperation with FHWA to include a substantial amount of additional data (Granato and others, 2018; Granato and Jones, 2019). The fourth version (1.1.0) was updated with additional data and modified to provide data-quality information within the Graphical User Interface (GUI), calculate statistics for multiple sites in batch mode, and output additional statistics. The fifth version (1.1.0a) was published in cooperation with the California Department of Transportation to add highway-runoff data collected in California. The sixth version published in this release (1.2.0) has been updated to include additional data, correct data-transfer errors in previous versions, add new parameter information, and modify the statistical output. This version includes data from 270 highway sites across the country (26 states); data from 8,108 storm events; and 119,224 concentration values with data for 418 different water-quality constituents or parameters. 

Granato, G.E., Stillwell, C.C., Weaver, J.C., McDaniel, A.H., Lipscomb, B.S., Jones, S.C., and Mullins, R.M., 2023, Development of the North Carolina stormwater-treatment decision-support system by using the Stochastic Empirical Loading and Dilution Model (SELDM): U.S. Geological Survey Scientific Investigations Report 2023–5113, 25 p., https://doi.org/10.3133/sir20235113.

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 (NCDOT), developed a decision-support software tool based on a statewide version of the Stochastic Empirical Loading and Dilution Model (SELDM). This decision-support tool is designed to identify potential adverse effects of highway runoff by using a criterion based on a measurable change in water quality from a surrogate pollutant. The NCDOT worked with the North Carolina Department of Environmental Quality to select a 25-percent change in suspended sediment concentration as the decision-rule criterion for identifying measurable downstream water-quality change; this selection was based on available data and widely accepted stormwater monitoring uncertainties. Development of the statewide tool and its application to the Piedmont ecoregion are described in this report. Because SELDM can be applied to build a similar decision-support tool in any State, this report describes practice-ready methods that other State departments of transportation and municipal permittees can use to streamline environmental permitting and project delivery while protecting the environment.

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.

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.

Jeznach, L. C., Granato, G. E., Sharar-Salgado, D., Jones, S. C., and Imig, D., 2023, 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 Research Record, v. 2677, no. 7, p. 570–581, https://doi.org/10.1177/03611981231155183.

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 Dilution Model to perform space-for-time stormwater quality analyses. This study indicated that spatial variations in precipitation statistics within and adjacent to southern New England are greater than projected climate-related changes for the centroid of this region. A dilution-factor analysis indicated that highway runoff would become a greater proportion of downstream flows if average event volumes or time between event midpoints increase and would become a smaller proportion of downstream flows if event durations increase. Highway-runoff yield analyses for total phosphorus (TP) indicate that uncertainty in water quality statistics results in variations in long-term average yields from about 1.69 to 7.96 times higher than the lowest TP values simulated. In comparison, variations in precipitation statistics cause yield variations that ranged from 1.41 to 1.76 for the different simulated concentrations. An analysis of stormwater treatment indicated that uncertainties in runoff treatment variables are also larger than the magnitude of climate variations. This study does not question the potentially large climate-related changes in hydrologic and hydraulic variables expected to occur in the foreseeable future. It does indicate that uncertainties in the current data and potential effects of land use change on stormwater quality and treatment variables are larger than the projected effects of climate change.

Granato, G.E., Spaetzel, A.B., and Jeznach, L.C., 2022, 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): U.S. Geological Survey data release, https://doi.org/10.5066/P9CZNIH5.

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. The statistics for highway and upstream basin properties, hydrologic variables, and stormwater quality provided in this data release can be used to represent long-term conditions throughout southern New England. The simulated populations of flows, concentrations, and loads documented in this data release represent long-term conditions at representative sites of interest. This data release also documents results of sensitivity analyses designed to guide the selection of input variables for runoff quality simulations and selected example simulations that illustrate use of simulation results for decision making.

Stonewall, A.J., Yates, M.C., and Granato, G.E., 2022, Assessing the impact of chloride deicer application in the Siskiyou Pass, southern Oregon: U.S. Geological Survey Scientific Investigations Report 2022–5091, 94 p., https://doi.org/10.3133/sir20225091.

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 transport of goods and people through adverse weather conditions, particularly snow and ice. The Stochastic Empirical Loading and Dilution Model (SELDM) was used to estimate combinations of prestorm-streamflow, stormflow, highway-runoff, and event mean constituent concentrations (EMCs), as well as stormwater-constituent loads at sites of interest. Results of the study showed that for chloride modeling in the Siskiyou Pass area, (1) the inclusion of local streamflow data is important for obtaining accurate downstream EMCs, (2) the inclusion of precipitation data is important for highway and concurrent runoff load calculations, and (3) water-quality constituent EMC data from highway runoff and upstream stormflows are the most important data to collect for highway runoff and upstream water-quality constituent concentration statistics.

Granato, G.E., 2021, Stochastic Empirical Loading and Dilution Model (SELDM) software archive: U.S. Geological Survey software release, https://doi.org/10.5066/P9PYG7T5

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). This software archive is designed to document different versions of SELDM that have been used by the USGS, Federal and State transportation engineers, and others since version 1.0 was published as a USGS techniques and methods report (Granato 2013). Versions 1.0.1 through 1.0.3 were developed to implement minor modifications to the software. Version 1.1.0 was developed to provide an interface to run multiple analyses in one session, which facilitates use of the model for scenario and sensitivity analyses. Details about version changes are provided within SELDM’s GUI and in the “ReadMe” files within this software release.

Granato, G.E., and Friesz, P.J., 2021, 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): U.S. Geological Survey Scientific Investigations Report 2021–5043, 37 p., https://doi.org/10.3133/sir20215043

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 (BMPs). Although its National Pollution Discharge Elimination System stormwater permit is focused on areas subject to total maximum daily load (TMDL) regulations, CalTrans builds and maintains BMPs to minimize the adverse effects of roadway runoff on receiving waters throughout the State. This report describes approaches used by the U.S. Geological Survey in cooperation with CalTrans for using the Stochastic Empirical Loading and Dilution Model (SELDM) to assess long-term annual yields of highway and urban runoff in selected areas of California. In this study, a series of regional and local yields were simulated to provide statewide planning-level estimates and more refined TMDL-specific yield values. SELDM was used to analyze 368 State roadway and urban runoff yields for 53 runoff quality constituents. The analyses included 222 random-seed analyses, 60 regional State roadway-runoff analyses, 24 regional urban roadway-runoff analyses, and 62 focused TMDL-area analyses.

This report describes approaches and statistics used to analyze available hydrologic and runoff quality data in all analyses. Results for all analyses are provided in the model archive, but only a selected subset of results are presented as examples in this report. State roadway runoff, urban runoff, and BMP discharge yields for total suspended solids, total nitrogen, total phosphorus, and total zinc were selected as examples because they are widespread constituents of concern with substantial amounts of State roadway and urban runoff monitoring data. In this report, a hypothetical basin was specified by using available geographic information to demonstrate use of the State roadway and urban runoff yields to estimate long-term annual stormwater loads from developed areas. Application of these yields to the hypothetical basin indicates that although State-roadway yields may be higher than urban-runoff yields for some constituents, State-roadway loads may be a small proportion of total stormwater loads because State roadways themselves are a small fraction of the total impervious area in such basins. Although application of results from this study may have considerable uncertainty for any particular stormwater outfall, the study does provide robust estimates to support basin-scale runoff-load analyses in California. These analyses also provide estimates for the 12 U.S. Environmental Protection Agency level III ecoregions that are completely or partially within the boundaries of the State of California.

Granato, G.E., and Friesz, P.J., 2021, 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): U.S. Geological Survey data release, https://doi.org/10.5066/P9B02EUZ.

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 and Dilution Model (SELDM). In this study SELDM was used to do 368 analyses to examine highway- and urban-runoff yields for 53 runoff-quality constituents. The analyses include 222 random-seed analyses, 60 regional highway-runoff analyses, 24 regional urban-runoff analyses, and 62 focused TMDL-area analyses. Results for all these analyses are provided in this model archive. Although application of results from this study may have considerable uncertainty for predicting loads from any particular stormwater outfall, the results do provide robust estimates to support basin-scale planning-level analyses in California. These analyses also provide regional estimates inside and outside California for the 12 U.S. Environmental Protection Agency level III ecoregions that lie in-whole or in-part within the state of California.

Weaver, J.C., Stillwell, C.C., Granato, G.E., McDaniel, A.H., Lipscomb, B.S., and Mullins, R.M, 2021, Application of the North Carolina Stochastic Empirical Loading and Dilution Model (SELDM) to Assess Potential Impacts of Highway Runoff: U.S. Geological Survey data release, https://doi.org/10.5066/P9LCXHLN.

In 2018, The USGS, in cooperation with the North Carolina Department of Transportation (NCDOT) and the Federal Highway Administration (FHWA) developed a version of SELDM with North-Carolina specific data. In the current effort the USGS completed numerous model simulations to develop an NC_SELDM_Catalog (Microsoft Excel spreadsheet) of outputs for a wide range of highway catchment and upstream basin variables. A total of 74,880 SELDM simulations were completed across the Piedmont, Blue Ridge, and Coastal Plain regions (24,960 per region) in North Carolina. Within each region, the completed simulations represented 12,480 design scenarios (one each using the grass swale and bioretention BMP device for treatment of runoff). The overall purpose of the catalog is to provide a tool to NCDOT and others to use during the transportation design process to rapidly assess the potential level of BMP that may be needed for treatment of highway runoff. This tool is designed to identify potential adverse effects of runoff by using a criterion based on a measurable change in water quality from a surrogate pollutant and establish stormwater treatment goals for any highway improvement project in the state.

Granato, G.E., Spaetzel, A.B., and Medalie, L., 2021, Statistical methods for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM): U.S. Geological Survey Scientific Investigations Report 2020–5136, 41 p., https://doi.org/10.3133/sir20205136.

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 user-selected water-quality goals and the potential effectiveness of mitigation measures to reduce such risks. In SELDM, three treatment variables—hydrograph extension, volume reduction, and water-quality treatment—are simulated by using the trapezoidal distribution and the rank correlation with the associated runoff variables. This report describes methods for calculating the trapezoidal distribution statistics and rank correlation coefficients for these treatment variables and methods for estimating the minimum irreducible concentration (MIC), which is the lowest expected effluent concentration from a BMP site or a category of BMPs. Analyses for this study were done with data extracted from a modified copy of the December 2019 version of the International Stormwater Best Management Practices Database. Statistics for volume reduction, hydrograph extension, and water-quality treatment were developed with selected data. The medians of the best-fit statistics for selected constituents were used to construct generalized cumulative distribution functions for the three treatment variables. For volume reduction and hydrograph extension, selection of a Spearman’s rank correlation coefficient (rho) value that is the average of the median and maximum values for the BMP category may help generate realistic simulation results in SELDM. The median rho value may be selected to help generate realistic simulation results for water-quality treatment variables. Water-quality treatment statistics, including trapezoidal ratios and MIC values, were developed for 51 runoff-quality constituents commonly measured in highway and urban runoff studies. Statistics were calculated for water-quality properties, sediment and solids, nutrients, major and trace inorganic elements, organic compounds, and biologic constituents.

Granato, G.E., 2021, Best Management Practices Statistical Estimator (BMPSE) Version 1.2.0: U.S. Geological Survey software release, https://doi.org/10.5066/P9XBPIOB.

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. 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 best management practices (BMPs). This information was used to calculate at-site statistics that were used to calculate categorical statistics for BMP analysis. The BMPSE was assembled by using a Microsoft Access database application to facilitate calculation of BMP performance statistics.

Granato, G.E., Medalie, Laura, and Spaetzel, A.B., 2021, Statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM): U.S. Geological Survey data release, https://doi.org/10.5066/P9X3ECTD.

This data release documents statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM). In SELDM, three treatment variables, hydrograph extension, runoff volume reduction, and water-quality treatment are modeled by using the trapezoidal distribution and the rank correlation with the associated highway-runoff variables. The statistics in this data release were calculated by using the Best Management Practices Statistical Estimator (Granato, 2021) and the spreadsheet tools within this data release. The statistics were calculated by using data extracted from a modified copy of the December 2019 version of International Stormwater Best Management Practices Database. This data release provides the individual at-site statistics used by Granato and others (2021). Sufficient data were available to estimate statistics for 8 to 12 BMP categories by using data from 44 to more than 265 monitoring sites. Water-quality treatment statistics, including trapezoidal ratios and minimum irreducible concentration (MIC) values were developed for 51 runoff-quality constituents commonly measured in highway and urban runoff studies.

Weaver, J.C., Stillwell, C.C., Granato, G.E., McDaniel, A.H., Lipscomb, B.S., and Mullins, R.M, 2021, Application of the North Carolina Stochastic Empirical Loading and Dilution Model (SELDM) to Assess Potential Impacts of Highway Runoff: U.S. Geological Survey data release, https://doi.org/10.5066/P9LCXHLN.

In 2018, USGS and North Carolina Department of Transportation (NCDOT) initiated a study for the NC Stochastic Empirical Loading Dilution Model (SELDM) to complete numerous model simulations to develop decision-support tool for a wide range of highway catchment and upstream basin variables. A total of 74,880 SELDM simulations were completed across the Piedmont, Blue Ridge, and Coastal Plain regions (24,960 per region) in North Carolina. Within each region, the completed simulations represented 12,480 design scenarios (one each using the grass swale and bioretention BMP device for treatment of runoff). The overall purpose of the catalog is to provide a tool to NCDOT and others to use during the transportation design process to rapidly assess the potential level of Best Management Practices (BMPs) that may be needed for treatment of highway runoff at any site in the state.

Spaetzel, A.B., Steeves, P.A., and Granato, G.E., 2020, 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: U.S. Geological Survey data release, https://doi.org/10.5066/P9VK1MCG.

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 were defined for sites within CT, MA, and RI and include the following: drainage area, 10-85 slope, longest flow path, number of road crossings by road class, impervious cover, length of roads by road class, and length of streams. Coordinates, street name, and road classification associated with the road crossing point also are included. Users can delineate basins and compute these characteristics, among others, on the USGS StreamStats web application. This data release contains one shapefile in a zipped folder and two tables: RoadCrossingsShapefile.zip, BasinCharacteristics.txt, and BasinCharacteristics_Definitions.txt. The basin characteristics are included in the metadata file and as a separate table for the user’s preference.

Jeznach, L.C., and Granato, G.E., 2020, Comparison of SELDM simulated total-phosphorus concentrations with ecological impervious-area criteria: Journal of Environmental Engineering: v. 146, No. 8, 10 p. https://doi.org/10.1061/(ASCE)EE.1943-7870.0001763.

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 Stochastic Empirical Loading and Dilution Model (SELDM). Hydrologic and physiographic variables representative of southern New England were used to simulate receiving water quality in a basin with IC ranging from 0.1% to 30%. Simulation results mirror the results of ecological studies; event mean concentrations (EMCs) of total phosphorus (TP) increase proportionally to the logarithms of imperviousness for a given risk percentile. Simulation results indicated that commonly used stormwater treatment methods may be insufficient for mitigating the effects of imperviousness. Therefore, disconnection, rather than treatment, may be needed to protect water quality, and efforts to preserve undeveloped stream basins may be more effective than efforts to remediate conditions in highly developed basins. Results also indicate that commonly used water-quality criteria may be too restrictive for stormwater because TP EMCs frequently exceed these criteria, even in minimally developed basins.

Granato, G.E., and Jeznach, L.C., 2020, Model archive for analysis of the effects of impervious cover on receiving-water quality with the Stochastic Empirical Loading Dilution Model (SELDM): U.S. Geological Survey data release, https://doi.org/10.5066/P9K0Y7XR.

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 and physiographic basin properties in southern New England was simulated using the Stochastic Empirical Loading and Dilution Model (SELDM) to do a numerical experiment designed to explore relations between impervious cover and receiving-water quality. These simulations included a range of impervious cover from 0.1 to 30 percent. These relations were examined to provide planning-level estimates of a population of concentrations and dilution factors as explanatory variables for the changes in stream biota commonly seen as the percentage of impervious areas increase. SELDM is a runoff-quality model developed by the U.S. Geological Survey in cooperation with the Federal Highway Administration to simulate the adverse effects of runoff on receiving waters and provide meaningful information about the potential effectiveness of management measured to reduce water quality risks. This is a model archive for these numerical experiments documenting the input statistics and the simulation results. Model development files include details of simulated hydrology, basin properties, upstream undeveloped area water quality, and developed (impervious area) area runoff quality. Model results include downstream water quality with and without structural best management practices.

Granato, G.E., and Jones, S.C., 2019, Simulating runoff quality with the Highway-Runoff Database and the Stochastic Empirical Loading and Dilution Model: Transportation Research Record, Journal of the Transportation Research Board, v. 2673, no. 1, p. 136-142, https://doi.org/10.1177/0361198118822821.

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 scale. This paper describes the datasets that are available in version 1.1 of the HRDB and demonstrates how data and statistics from the HRDB can be used with the Stochastic Empirical Loading and Dilution Model (SELDM) to simulate highway runoff. The HRDB includes 249 sites, 6,849 runoff events, and 106,869 event mean concentra-tions (EMCs) collected during the 1975–2017 period. It includes data from 16 States in the conterminous United States and from Hawaii. The EMCs in the HRDB include measurements for 415 different water-quality constituents. These water-quality measurements include 32,944 trace-metal; 27,496 organic; 15,684 nutrient; 13,016 physical property; 10,307 major inorganic; 6,773 sediment; and 649 other constituent values. There are large variations in the data. For example, EMCs for total sus-pended solids and total phosphorus range from 0.4 to 5,440 mg/L and 0.004 to 22 mg/L, respectively; geometric means range from 1.58 to 1,379 mg/L and 0.017 to 2.82 mg/L for these constituents, respectively. The example simulations indicate that risks for adverse effects of runoff can vary by orders of magnitude; the HRDB and SELDM facilitate selection of representa-tive statistics from available datasets. 

Granato, G.E., 2019, InterpretSELDM version 1.0 The Stochastic Empirical Loading and Dilution Model (SELDM) output interpreter: U.S. Geological Survey software release, https://doi.org/10.5066/P9395YHY.

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 produces results in (relatively) easy-to-use tab delimited output files that are designed for use with spreadsheets and graphing packages. However, time is needed to learn, understand, and use the SELDM output formats. Also, the SELDM output requires post-processing to extract the specific information that commonly is of interest to the user (for example, the percentage of storms above a user-specified value). Because SELDM output files are comprehensive, the locations of specific output values may not be obvious to the novice user or the occasional model user who does not consult the detailed model documentation. The InterpretSELDM program was developed as a post processor to facilitate analysis and presentation of SELDM results. The program provides graphical results and tab-delimited text summaries from simulation results.  InterpretSELDM provides data summaries in seconds. It has an easy-to-use graphical user interface designed to quickly extract dilution factors, constituent concentrations, annual loads, and annual yields from all analyses within a SELDM project. The program provides the methods necessary to create scatterplots and boxplots for the extracted results. 

Granato, G.E., 2019, Highway-Runoff Database (HRDB) Version 1.1.0: U.S. Geological Survey data release, https://doi.org/10.5066/P94VL32J.

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. 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 with the FHWA in 2009 (Granato and Cazenas, 2009). The second version (1.0.0a) was published in cooperation with the Massachusetts DOT Highway Division to include data from Ohio and Massachusetts (Smith and Granato, 2010). The third version (1.0.0b) was published in cooperation with the Federal Highway Administration to include a substantial amount of additional data (Granato and others, 2018; Granato and Jones, 2019). This version includes data from 242 highway sites across the country; data from 6,837 storm events; and 106,441 concentration values with data for 414 different water-quality constituents. This new version (1.1.0) of the database contains software updates to provide data-quality information within the Graphical User Interface (GUI), calculate statistics for multiple sites in batch mode, and output additional statistics.

Stonewall, A.J., Granato, G.E., and Glover-Cutter, K.M., 2019, 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: U.S. Geological Survey Scientific Investigations Report 2019–5053, 116 p., https://doi.org/10.3133/sir20195053.

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 stormwater constituent loads from a site of interest. In addition, SELDM can be used to assess the effects of stormwater Best Management Practices (BMPs), which are designed to mitigate the adverse effects of runoff into a waterbody.

Adverse effects of stormwater on receiving waters are one of the greatest unsolved water-quality problems Nationwide. State DOTs, municipalities, Federal facilities, and private property owners who manage impervious surfaces need information about the potential magnitude of their contributions and the potential effectiveness of methods to mitigate the adverse effects of runoff. Because the efficacy of at-site controls are limited, information about the potential effectiveness of alternative strategies is needed.

The USGS, in cooperation with the Oregon Department of Transportation (ODOT), conducted a study to research methods in which SELDM can be used to enhance the efficiency of ODOT’s stormwater program, support the development of a stormwater banking program, and meet environmental goals. Results can be used to develop a strategic, systems-level approach to stormwater management by considering entire watersheds instead of individual road crossings. Two watersheds, Bear Creek and Mill Creek, in western Oregon were selected for analysis. Within each watershed, seven road crossings were selected for demonstrating the utility of SELDM in nested basins.

Precipitation statistics, pre-storm streamflow, runoff coefficients, and hydrograph recession factors were calculated for each location and used in SELDM to simulate flow, water-quality concentrations, and constituent loads in the upstream basin, from the highway (or developed area), and downstream from the road crossing. Three water-quality constituents were selected for modeling: suspended-sediment concentration (SSC), total phosphorus (TP), and total copper (TCu). Using water-quality transport curves, the relations between streamflow and SSC and between streamflow and TP were simulated. Concentrations of TCu were simulated by configuring a linear relation between SSC and TCu. A generic BMP was simulated using the median treatment statistics for flow reductions, hydrograph extensions, concentration reductions, and minimum irreducible concentrations from nine BMP categories with data from the 2012 International BMP database.

Five simulation scenarios were modeled for demonstrative purposes. These simulations were used to evaluate potential effects of different watershed properties, water-quality inputs, and stormwater mitigation measures. Instream EMCs were compared to hypothetical water-quality criteria for suspended sediment, total phosphorus, and total copper to demonstrate the concept of water-quality risk analysis. For all five scenarios, it was assumed that highway- runoff concentrations were independent of location or average annual daily traffic.

Weaver, J.C., Granato, G.E., and Fitzgerald, S.A., 2019, Assessing water quality from highway runoff at selected sites in North Carolina with the Stochastic Empirical Loading and Dilution Model (SELDM): U.S. Geological Survey Scientific Investigations Report 2019–5031, 99 p., https://doi.org/10.3133/sir20195031.

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 selected simulation scenarios. The USGS developed the national SELDM in cooperation with the Federal Highway Administration to provide the tools and techniques necessary for performing stormwater-quality simulations. SELDM uses a stochastic mass-balance approach to estimate combinations of flows, concentrations, and loads of stormwater constituents from the site of interest (often a highway catchment; nonhighway areas, such as a large impervious area at a shopping center complex, also can be used) and the basin upstream from the stormwater outfall to assess the risk for adverse effects of runoff. SELDM also can be used to simulate the effectiveness of volume reduction, hydrograph extension, and water-quality concentration reductions by stormwater best management practices (BMPs), which are designed to help mitigate the effects of runoff on receiving water bodies.

Some of the statistical inputs needed for the North Carolina-enhanced SELDM were either calculated or augmented using local or regional data from North Carolina. Streamflow statistics used by SELDM were determined for 266 streamgages across North Carolina on the basis of data available through the 2015 water year. Recession ratio statistics used for triangular hydrographs were also developed for 30 streamgages across the State. The NCDOT identified previous research reports on highway-runoff and BMP studies in North Carolina for review of potential data addition to the national FHWA Highway-Runoff Database (HRDB). Following USGS review of these data, a total of 25,087 event mean concentration values and 1,140 storm events for 39 highway-runoff sites and 195 analytes were uploaded to the national HRDB from six North Carolina highway-runoff research reports and a recent USGS bridge deck runoff study. Using data for 27 streamgages in North Carolina, a total of 57 water-quality transport curves were developed for seven constituents for use in simulating water-quality conditions in the upstream basin. Performance data for three BMPs (bioretention, grass strip or swale, and wetland channel) from NCDOT research data were incorporated into the North Carolina-enhanced SELDM for volume-reduction statistics, including the effectiveness of treating four water-quality constituents (total suspended solids, total nitrogen, total phosphorus, nitrate plus nitrite) and turbidity. 

Simulations using the North Carolina-enhanced SELDM are presented for two hypothetical upstream basins in the Piedmont ecoregion and one hypothetical highway site to demonstrate how simulations can be used to provide risk-based information about potential effects of stormwater runoff on downstream water quality and the potential for mitigating those risks by using BMPs. The first group of simulations explores the stochastic variability in dilution factors (the ratio of the highway runoff to the total downstream stormflow) for a hypothetical Piedmont rural creek having drainage areas ranging from 1 to 100 square miles. The second group of simulations examines dilution factors based on variations in precipitation, streamflow, and recession ratios for two hypothetical Piedmont upstream basins (rural and urban) where the drainage area was held constant at 25 square miles. These simulations indicate the sensitivity of results to variations in each of the three variables. The third group of simulations examines the effects of varied concentrations in the upstream basin on water-quality conditions downstream from the highway crossing. Variations in upstream water-quality conditions for three constituents (suspended sediment concentration, total nitrogen, and total phosphorus) are based on water-quality transport curves selected from among the 57 curves developed as part of this study to represent low-, medium-, and high-concentration statistics. Simulations completed for this third group also examine the potential effects of grass swale and bioretention BMP treatment on total nitrogen and total phosphorus concentrations in highway runoff. The BMP performance data from the NCDOT research reports were applied in this group of simulations.

The stochastic mass-balance approach used in SELDM analyses and simulations provides a strong tool for engineers and water-resource managers to use in exploring a wide range of possible hydrologic and water-quality inputs and their effects on downstream water quality. The results of this study can not only aid engineers and managers in planning for potential adverse effects of runoff at site-specific locations, they can also help the USGS and other Federal and State agencies with oversight responsibilities in stormwater-quality issues to continue gathering data on potential water-quality effects in receiving streams. 

Granato, G.E., Desmarais, K.L., Smith, K.P., Weaver, J.C., Glover-Cutter, K.M., Stonewall, A.J., and Fitzgerald, S.A., 2018, Highway-Runoff Database (HRDB) Version 1.0.0b: U.S. Geological Survey data release, https://doi.org/10.5066/P9YG44VQ.

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. The dataset was compiled from 37 studies as documented in 113 scientific or technical reports. The dataset includes data from 242 highway sites across the country. It includes data from 6,837 storm events with dates ranging from April 1975 to November 2017. Therefore, these data span more than 40 years; vehicle emissions and background sources of highway-runoff constituents have changed markedly during this time. For example, some of the early data are affected by use of leaded gasoline, phosphorus-based detergents, and industrial atmospheric deposition. The dataset includes 106,441 concentration values with data for 414 different water-quality constituents. This dataset was assembled from various sources and the original data were collected and analyzed by using various protocols. Where possible, the USGS worked with State departments of transportation and the original researchers to obtain, document, and verify the data that were included in the HRDB. However, inclusion in this dataset does not constitute endorsement by the USGS or the FHWA. People who use these data are responsible for ensuring that the data are complete and correct and that it is suitable for their intended purposes.

Smith, K.P., Sorenson, J.R., and Granato, G.E., 2018, Characterization of stormwater runoff from bridge decks in eastern Massachusetts, 2014–16: U.S. Geological Survey Scientific Investigations Report 2018–5033, 73 p., https://doi.org/10.3133/sir20185033.

Version 1.0.2 of the Stochastic Empirical Loading and Dilution Model was used to simulate long-term (29–30-year) concentrations and annual yields of SS, TP, and TN in bridge-deck runoff and in discharges from a hypothetical stormwater treatment best-management practice structure. Three methods (traditional statistics, robust statistics, and L-moments) were used to calculate statistics for stochastic simulations because the high variability in measured concentration values during the field study resulted in extreme simulated concentrations. Statistics of each dataset, including the average, standard deviation, and skew of the common (base 10) logarithms, for each of the three bridges, and for a lumped dataset, were calculated and used for simulations; statistics representing the median of statistics calculated for the three bridges also were used for simulations. These median statistics were selected for the interpretive simulations so that the simulations could be used to estimate concentrations and yields from other, unmonitored bridges in Massachusetts. Comparisons of the standard and robust statistics indicated that simulation results with either method would be similar, which indicated that the large variability in simulated results was not caused by a few outliers. Comparison to statistics calculated by the L-moments methods indicated that L-moments do not produce extreme concentrations; however, they also do not produce results that represent the bulk of concentration data.

The runoff-quality risk analysis indicated that bridge-deck runoff would exceed discharge standards commonly used for large, advanced wastewater treatment plants, but that commonly used stormwater best-management practices may reduce the percentage of exceedances by one-half. Results of simulations indicated that long-term average yields of TN, TP, and SS may be about 21.4, 6.44, and 40,600 pounds per acre per year, respectively. These yields are about 1.3, 3.4, and 16 times simulated ultra-urban highway yields in Massachusetts; however, simulations indicated that use of a best-management practice structure to treat bridge-deck runoff may reduce discharge yields to about 10, 2.8, and 4,300, pounds per acre per year, respectively.

Stonewall, A.J., Granato, G.E., and Haluska, T.L., 2018, Assessing roadway contributions to stormwater flows, concentrations and loads by using the StreamStats application: Transportation Research Record, Journal of the Transportation Research Board, Volume: 2672 issue: 39, p. 79-87.  https://doi.org/10.1177/0361198118758679.

Originally published as:
Stonewall, A.J., Granato, G.E., and Haluska, T.L., 2018, Assessing roadway contributions to stormwater flows, concentrations and loads by using the StreamStats application: in Compendium of Papers for the Transportation Research Board 97th Annual Meeting, January 7–11, 2018, Washington, D.C., Paper number: 18-05240, 21 p. 

The Oregon Department of Transportation (ODOT) and other state departments of transportation need quantitative information about the percentages of different land-cover categories above any given stream crossing in the state to assess and address roadway contributions to water-quality impairments and resulting Total Maximum Daily Loads. The U.S. Geological Survey, in cooperation with ODOT and the FHWA, added roadway and land-cover information to the online StreamStats application to facilitate analysis of stormwater runoff contributions from different land covers. Analysis of 25 delineated basins with drainage areas of about 100 square miles indicates the diversity of land covers in the Willamette Valley, Oregon. On average, agricultural, developed, and undeveloped land covers comprise 15, 2.3, and 82 percent of these basin areas. On average, these basins contained about 10 miles of State highways and 222 miles of non-state roads. The Stochastic Empirical Loading and Dilution Model was used with available water-quality data to simulate long-term yields of total phosphorus from highways, non-highway roadways, and agricultural-, developed-, and undeveloped-areas. These yields were applied to land cover areas obtained from StreamStats for the Willamette River above Wilsonville, Oregon. This analysis indicated that highway yields were larger than yields from other land covers because highway-runoff concentrations were higher than other land covers and the highway is fully impervious. However, the total highway area was a small fraction of the other land covers. Consequently, while highway-runoff mitigation measures can be effective for managing water quality locally, they may have limited effect on achieving basin-wide stormwater reduction goals.

Granato, G.E., and Jones, S.C., 2017, Estimating Total Maximum Daily Loads with the Stochastic Empirical Loading and Dilution Model: Transportation Research Record, Journal of the Transportation Research Board, No. 2638, p. 104-112. https://doi.org/10.3141/2638-12.

Originally published as:
Granato, G.E., and Jones, S.C., 2017, Estimating long-term annual highway-runoff loads for total maximum daily load analyses with the Stochastic Empirical Loading And Dilution Model (SELDM): in Compendium of Papers for the Transportation Research Board 96th Annual Meeting, January 8-12, 2017, Washington, D.C., 16 p. USGS version of report on-line.

The Massachusetts Department of Transportation (DOT) and the Rhode Island DOT are assessing and addressing roadway contributions to total maximum daily loads (TMDLs). Example analyses for total nitrogen, total phosphorus, suspended sediment, and total zinc in highway runoff were done by the U.S. Geological Survey in cooperation with FHWA to simulate long-term annual loads for TMDL analyses with the stochastic empirical loading and dilution model known as SELDM. Concentration statistics from 19 highway runoff monitoring sites in Massachusetts were used with precipitation statistics from 11 long-term monitoring sites to simulate long-term pavement yields (loads per unit area). High-way sites were stratified by traffic volume or surrounding land use to calculate concentration statistics for rural roads, low-volume highways, high-volume highways, and ultraurban highways. The median of the event mean concentration statistics in each traffic volume category was used to simulate annual yields from pavement for a 29- or 30-year period. Long-term average yields for total nitrogen, phosphorus, and zinc from rural roads are lower than yields from the other categories, but yields of sediment are higher than for the low-volume highways. The aver-age yields of the selected water quality constituents from high-volume highways are 1.35 to 2.52 times the associated yields from low-volume highways. The average yields of the selected constituents from ultra-urban highways are 1.52 to 3.46 times the associated yields from high-volume highways. Example simulations indicate that both concentration reduction and flow reduction by structural best management practices are crucial for reducing runoff yields.

Granato, G.E., and Jones, S.C., 2017, Estimating risks for water-quality exceedances of total-copper from highway and urban runoff under predevelopment and current conditions with the Stochastic Empirical Loading and Dilution Model (SELDM): in Proceedings of the 2017 World Environmental & Water Resources Congress, Sacramento, CA, May 21-25, 2017, Reston, VA, American Society of Civil Engineers, 15 p. Conference Paper.                USGS version of report on-line.

The Stochastic Empirical Loading and Dilution Model (SELDM) was used to demonstrate methods for estimating risks for water-quality exceedances of event-mean concentrations (EMCs) of total-copper. Monte Carlo methods were used to simulate stormflow, total-hardness, suspended-sediment, and total-copper EMCs as stochastic variables. These simulations were done for the Charles River basin upstream of Interstate 495 in Bellingham, Massachusetts. The hydrology and water quality of this site were simulated with SELDM by using data from nearby, hydrologically similar sites. Three simulations were done to assess the potential effects of the highway on receiving-water quality with and without highway-runoff treatment by a structural best-management practice (BMP). In the low-development scenario, total copper in the receiving stream was simulated by using a sediment transport curve, sediment chemistry, and sediment-water partition coefficients. In this scenario, neither the highway runoff nor the BMP effluent caused concentration exceedances in the receiving stream that exceed the once in three-year threshold (about 0.54 percent). In the second scenario, without the highway, runoff from the large urban areas in the basin caused exceedances in the receiving stream in 2.24 percent of runoff events. In the third scenario, which included the effects of the urban runoff, neither the highway runoff nor the BMP effluent increased the percentage of exceedances in the receiving stream. Comparison of the simulated geometric mean EMCs with data collected at a downstream monitoring site indicates that these simulated values are within the 95-percent confidence interval of the geometric mean of the measured EMCs.

Granato G.E., Ries, K.G., III, and Steeves, P.A., 2017, Compilation of streamflow statistics calculated from daily mean streamflow data collected during water years 1901–2015 for selected U.S. Geological Survey streamgages: U.S. Geological Survey Open-File Report 2017–1108, 17 p., https://doi.org/10.3133/ofr20171108.

Streamflow statistics are needed by decision makers for many planning, management, and design activities. The U.S. Geological Survey (USGS) StreamStats Web application provides convenient access to streamflow statistics for many streamgages by accessing the underlying StreamStatsDB database. In 2016, non-interpretive streamflow statistics were compiled for streamgages located throughout the Nation and stored in StreamStatsDB 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 named “GNWISQ” (Get National Water Information System Streamflow (Q) files), updated to version 1.1.1, and “QSTATS” (Streamflow (Q) Statistics), updated to version 1.1.2.

Statistics for 20,438 streamgages that had 1 or more complete years of record during water years 1901 through 2015 were calculated from daily mean streamflow data; 19,415 of these streamgages were within the conterminous United States. About 89 percent of the 20,438 streamgages had 3 or more years of record, and about 65 percent had 10 or more years of record. Drainage areas of the 20,438 streamgages ranged from 0.01 to 1,144,500 square miles. The magnitude of annual average streamflow yields (streamflow per square mile) for these streamgages varied by almost six orders of magnitude, from 0.000029 to 34 cubic feet per second per square mile. About 64 percent of these streamgages did not have any zero-flow days during their available period of record. The 18,122 streamgages with 3 or more years of record were included in the StreamStatsDB compilation so they would be available via the StreamStats interface for user-selected streamgages. All the statistics are available in a USGS ScienceBase data release

Granato, G.E., 2017, Streamflow statistics calculated from daily mean streamflow data collected during water years 1901–2015 for selected U.S. Geological Survey streamgages: U.S. Geological Survey data release, accessed October 2017 at https://doi.org/10.5066/F71V5CFT.

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 named “GNWISQ” (Get National Water Information System Streamflow (Q) files) and “QSTATS” (Streamflow (Q) Statistics). Statistics for 20,438 streamgages that had 1 or more complete years of record during water years 1901 through 2015 were calculated from daily mean streamflow data; 19,415 of these streamgages were within the conterminous United States. About 89 percent of the 20,438 streamgages had 3 or more years of record, and 65 percent had 10 or more years of record. Drainage areas of the 20,438 streamgages ranged from 0.01 to 1,144,500 square miles. The magnitude of annual average streamflow yields (streamflow per square mile) for these streamgages varied by almost six orders of magnitude, from 0.000029 to 34 cubic feet per second per square mile. About 64 percent of these streamgages did not have any zero-flow days during their available period of record. The 18,122 streamgages with 3 or more years of record were included in the StreamStatsDB compilation so they would be available via the StreamStats interface for user-selected streamgages.

Granato, G.E., and Jones, S.C., 2016, Modeling stormflow, total hardness, suspended sediment, and total copper to assess risks for water-quality exceedances with the Stochastic Empirical Loading and Dilution Model (SELDM): Proceedings of StormCon, August 22-25, 2016, Indianapolis, IN: Santa Barbara, CA, Forester Media Inc., 14. p. 

In this study, the Stochastic Empirical Loading and Dilution Model (SELDM) was used to demonstrate methods for estimating event mean concentrations (EMCs) of total hardness, suspended sediment, and total copper in receiving waters where robust datasets are not available. These simulations also were done to examine the potential effects of highway runoff and highway-swale discharges on the risk for water-quality exceedances in a receiving stream with a low-development scenario and a two-part current-conditions scenario. The hypothetical simulations were done by using properties of the Charles River basin at and upstream of Interstate 495 (I-495) in Bellingham, Massachusetts (MA). The hydrology and water quality of this site were simulated with SELDM by using data from nearby, hydrologically similar sites.

Monte Carlo methods were used to simulate stormflow, total-hardness, suspended-sediment, and total-copper EMCs as stochastic variables. In the low-development scenario, total-copper concentrations upstream of the highway discharge were simulated by using suspended sediment concentrations, sediment-quality concentrations, and sediment-water distribution coefficients. In the current-conditions scenario upstream water quality was simulated by using loadings from low-development areas and urban runoff from developed areas in the basin. Comparison of the simulated concentrations from the current-conditions scenario with measured EMC data collected at a downstream monitoring site indicates that the simulated geometric mean total-copper concentrations are within the 95-percent confidence interval of the geometric mean of the measured EMCs.

These simulations indicate that neither highway runoff nor highway-swale discharge substantially change the risks for exceeding the MA criterion for total copper in the Charles River (26.8 µg/L). In comparison, a U.S. Environmental Agency (USEPA) hardness-based total-copper criterion would be about 5 µg/L if simulated hardness values are used to set the criterion. In the first scenario, none of the upstream total-copper EMCs in the 28 year simulation exceeded the MA whole water criterion. However, the simulated upstream total-copper concentrations did not meet the hardness based criterion within the USEPA once in three-year allowable exceedance risk of 0.58 percent of runoff events. Only one highway-runoff EMC exceeded the MA criterion and use of a simple grassy swale to treat highway runoff eliminated this exceedance. In the second scenario, urban runoff from the upstream Municipal Separate Storm Sewer System (MS4) areas increased the percentage of MA-criterion exceedances to 2.24 percent (36 events in 28 years), which is greater than the 0.58 percent allowable exceedances. In the second scenario, the percent of MA-criterion exceedances downstream of the highway was 2.3 percent (37 events in 28 years) with highway runoff and 2.24 percent (36 events in 28 years) with highway-swale discharge.

Granato, G.E., and Jones, S.C., 2015, Estimating the risks for adverse effects of total phosphorus in receiving streams with the Stochastic Empirical Loading and Dilution Model (SELDM) in Proceedings of the 2015 International Conference on Ecology and Transportation (ICOET 2015), September 20-24, 2015, Raleigh, North Carolina: Raleigh, North Carolina, Center for Transportation and the Environment, 18 p. Report On-Line. 

Studies from North Carolina (NC) indicate that increasing concentrations of total phosphorus (TP) and other constituents are correlated to adverse effects on stream ecosystems as evidenced by differences in benthic macroinvertebrate populations in streams across the state. As a result, stringent in-stream criteria based on the Water Quality Assessed by Benthic macroinvertebrate health ratings (WQABI) have been proposed for regulating TP concentrations in stormwater discharges and for selecting stormwater best management practices (BMPs). The WQABI criteria concentrations may not be suitable for evaluating stormwater discharges because they are based on baseflow concentration statistics, the criteria do not include a clearly defined allowable exceedance frequency, and there are substantial uncertainties in estimating the quality of runoff, BMP discharge, and receiving waters for sites without monitoring data.

The Stochastic Empirical Loading and Dilution Model (SELDM), which was developed by the U.S. Geological Survey in cooperation with the Federal Highway Administration, was used to simulate the quality of runoff, BMP discharge, and receiving waters to evaluate risks for water-quality exceedances with different criteria concentrations, allowable exceedance frequencies, and selected water-quality statistics. Water-quality data from two neighboring basins in the Piedmont ecoregion in NC were used to simulate in-stream stormwater quality. Data collected at 15 sites in NC were used to simulate runoff quality. Statistics for stochastic modeling of volume reduction, hydrograph extension, and water-quality treatment by BMPs, were used to simulate potential effect of these treatments on discharge quality and downstream stormwater quality. Results of these long-term 30-year simulations were used to evaluate criteria concentrations, the potential frequency of water-quality exceedances, and the effect of data selection on risks for water-quality exceedances.

The simulations indicate that the potential frequency for exceeding instream and stormwater discharge criteria depend on the detailed definition of the criteria and the data that are selected for simulating water quality. Data and simulation results indicate that the baseflow concentrations do not represent stormwater concentrations, even in predominantly forested basins. There is substantial uncertainty in applying stormwater statistics to unmonitored sites, even if these statistics are applied to neighboring basins such as in this example. Over a period of several years (or more) it would be impossible to meet many of the proposed instream and stormwater discharge quality criteria unless these criteria include an allowable exceedance frequency because stormwater concentrations commonly vary by orders of magnitude. Selection of BMPs by using concentration reduction as the sole criteria may underestimate potential benefits of BMPs that also provide volume reduction, which reduces discharge loads, and hydrograph extension, which increases the dilution of runoff into a larger proportion of the upstream stormflow.

Results of this study indicate the potential benefits of the multi-decade simulations that SELDM provides because these simulations quantify risks and uncertainties that affect decisions made with available data and statistics. Results of the SELDM simulations indicate that the WQABI criteria concentrations may be too stringent for evaluating the stormwater quality in receiving streams, highway runoff, and BMP discharges; especially with the substantial uncertainties inherent in selecting representative data.

Granato, G.E., and Jones, S.C., 2015, A case study demonstrating analysis of stormflows, concentrations, and loads of nutrients in highway runoff and swale discharge with the Stochastic Empirical Loading and Dilution Model (SELDM) in Proceedings of StormCon, August 2-6, 2015, Austin, Texas: Santa Barbara, CA, Forester Media Inc., 19 p. Report On-Line.           

Decisionmakers need information about the quality and quantity of stormwater runoff, the risk for adverse effects of runoff on receiving waters, and the potential effectiveness of mitigation measures to reduce these risks. The Stochastic Empirical Loading and Dilution Model (SELDM) uses Monte Carlo methods to generate stormflows, concentrations, and loads from a highway site and an upstream basin to provide needed risk-based information. SELDM was designed to help inform water-management decisions for streams and lakes receiving runoff from a highway or other land-use site. The purpose of this paper is to provide a brief description of SELDM and a hypothetical case study demonstrating the type of risk-based information that SELDM can provide. Total nitrogen (TN) and total phosphorus (TP) were selected as example constituents because nutrients are a common concern throughout the Nation and data for receiving waters, highway runoff, and the performance of best management practices (BMPs) are readily available for these constituents.

The case study is hypothetical, but was formulated by using actual data from selected monitoring sites in New England. Data representing streamflow and water-quality were collected at U.S. Geological Survey (USGS) streamgage 01208950 Sasco Brook near Southport, CT, which has a drainage area of 7.38 square miles. In this hypothetical case study a 4-lane highway would replace the current 2-lane road and would have a contributing area of 2.2 acres between the topographic basin divides. Concentrations of TN and TP in highway runoff were simulated with data from USGS highway-runoff monitoring station 423027071291301 along State Route 2 in Littleton Massachusetts. Results of a highway-runoff analysis are shown in relation to three hypothetical discharge criteria for TN and two hypothetical discharge criteria for TP. The risks for exceeding TN discharge criteria of 3, 5, and 8 mg/L for highway runoff are 7.4, 0.83, and 0.13 percent of 1,721 runoff events that may occur during a stochastic 30-year simulation. If a grassy swale is used to treat the runoff, the risks for TN exceedances are reduced to 3.2, 0.33 and 0.03 percent, respectively. The risks for exceeding TP discharge criteria of 0.1 and 0.5 mg/L for highway runoff are 49 and 1.2 percent, respectively. If a grassy swale is used to treat the runoff, the risks for TP exceedances are 57 and 0.8 percent, respectively. The risks for the 0.1 mg/L criterion increase because swales can be a source of TP if pavement concentrations are low. The risks for the 0.5 mg/L criterion decrease because the swale is effective for reducing high TP concentrations. Although the results are mixed for storm-event concentrations, the grassy swale effectively reduces annual loads. Annual loads from the swale are, on average, about 22 percent of highway loads for TN and 62 percent of highway loads of TP because the swale reduces high runoff concentrations and stormflow volumes. Analysis of upstream and downstream concentrations indicates that runoff from the site of interest does not have a substantial effect on instream stormflow concentrations in this example simulation.

Risley, J.C., and Granato, G.E., 2014, Assessing potential effects of highway runoff on receiving-water quality at selected sites in Oregon with the Stochastic Empirical Loading and Dilution Model (SELDM): U.S. Geological Survey Scientific Investigations Report 2014–5099, 74 p., https://doi.org/10.3133/sir20145099.

This report provides case studies and examples to demonstrate stochastic-runoff modeling concepts and to demonstrate application of the model. Basin characteristics from six Oregon highway study sites were used to demonstrate various applications of the model. The highway catchment and upstream basin drainage areas of these study sites ranged from 3.85 to 11.83 acres and from 0.16 to 6.56 square miles, respectively. The upstream basins of two sites are urbanized, and the remaining four sites are less than 5 percent impervious. Concentrations and loads of cadmium, chloride, chromium, copper, iron, lead, nickel, phosphorus, and zinc were simulated at the six Oregon highway study sites by using statistics from sites in other areas of the country. Water-quality datasets measured at hydrologically similar basins in the vicinity of the study sites in Oregon were selected and compiled to estimate stormflow-quality statistics for the upstream basins. The quality of highway runoff and some upstream stormflow constituents were simulated by using statistical moments (average, standard deviation, and skew) of the logarithms of data. Some upstream stormflow constituents were simulated by using transport curves, which are relations between stormflow and constituent concentrations. Stochastic analyses were done by using SELDM to demonstrate use of the model and to illustrate the types of information that stochastic analyses may provide. Additional analyses using surrogate water-quality datasets for the upstream basin and highway catchment were provided for six Oregon study sites to illustrate the risk-based information that SELDM will produce. These analyses show that the potential effects of highway runoff on receiving-water quality downstream of the outfall depends on the ratio of drainage areas (dilution), the quality of the receiving water upstream of the highway, and the concentration of the criteria of the constituent of interest. These analyses also show that the probability of exceeding a water-quality criterion may depend on the input statistics used, thus careful selection of representative values is important.

Granato, G.E., 2014, Statistics for stochastic modeling of volume reduction, hydrograph extension, and water-quality treatment by structural stormwater runoff best management practices (BMPs): U.S. Geological Survey Scientific Investigations Report 2014–5037, 37 p., https://doi.org/10.3133/sir20145037.

The U.S. Geological Survey (USGS) developed the Stochastic Empirical Loading and Dilution Model (SELDM) in cooperation with the Federal Highway Administration (FHWA) to indicate the risk for stormwater concentrations, flows, and loads to be above user-selected water-quality goals and the potential effectiveness of mitigation measures to reduce such risks. SELDM models the potential effect of mitigation measures by using Monte Carlo methods with statistics that approximate the net effects of structural and nonstructural best management practices (BMPs). In this report, structural BMPs are defined as the components of the drainage pathway between the source of runoff and a stormwater discharge location that affect the volume, timing, or quality of runoff. SELDM uses a simple stochastic statistical model of BMP performance to develop planning-level estimates of runoff-event characteristics. This statistical approach can be used to represent a single BMP or an assemblage of BMPs. The SELDM BMP-treatment module has provisions for stochastic modeling of three stormwater treatments: volume reduction, hydrograph extension, and water-quality treatment. In SELDM, these three treatment variables are modeled by using the trapezoidal distribution and the rank correlation with the associated highway-runoff variables. This report describes methods for calculating the trapezoidal-distribution statistics and rank correlation coefficients for stochastic modeling of volume reduction, hydrograph extension, and water-quality treatment by structural stormwater BMPs and provides the calculated values for these variables. This report also provides robust methods for estimating the minimum irreducible concentration (MIC), which is the lowest expected effluent concentration from a particular BMP site or a class of BMPs. These statistics are different from the statistics commonly used to characterize or compare BMPs. They are designed to provide a stochastic transfer function to approximate the quantity, duration, and quality of BMP effluent given the associated inflow values for a population of storm events. A database application and several spreadsheet tools are included in the digital media accompanying this report for further documentation of methods and for future use.

Granato, G.E., and Jones, S.C., 2014, Stochastic Empirical Loading and Dilution Model for analysis of flows, concentrations, and loads of highway runoff constituents: Transportation Research Record, Journal of the Transportation Research Board, No. 2436, p. 139-147. https://doi.org/10.3141/2436-14.

The Stochastic Empirical Loading and Dilution Model (SELDM) was developed by the U.S. Geological Survey in cooperation with the Federal Highway Administration (FHWA) to supersede use of the 1990 FHWA runoff-quality model. SELDM is designed to be a tool that can be used to transform disparate and complex scientific data into meaningful information about the risk for adverse effects of runoff on receiving waters, the potential need for mitigation measures, and the potential effectiveness of such measures for reducing these risks. SELDM is easy to use because much of the information and data needed to run SELDM are embedded in the model and are obtained by defining the location of the site of interest and five simple basin properties. Information and data from thousands of sites across the country were compiled to facilitate use of SELDM. Use of SELDM for doing the types of sensitivity analyses needed to properly assess water-quality risks are provided in a case study. For example, use of deterministic values to model upstream stormflows instead of representative variations in prestorm flow and runoff may substantially overestimate the proportion of highway runoff in downstream flows. Also, risks for total phosphorus excursions are substantially affected by the selected criteria and the modeling methods used. For example, if a single deterministic concentration rather than a stochastic population of values is used to model upstream concentrations, then the percentage of water-quality excursions in the downstream receiving waters may depend entirely on the selected upstream concentration.

Granato, G.E., 2013, Stochastic empirical loading and dilution model (SELDM) version 1.0.0: U.S. Geological Survey Techniques and Methods, book 4, chap. C3, 112 p., CD–ROM, https://doi.org/10.3133/tm4C3.                     Software On-Line.

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. The U.S. Geological Survey developed SELDM in cooperation with the Federal Highway Administration to help develop planning-level estimates of event mean concentrations, flows, and loads in stormwater from a site of interest and from an upstream basin. Planning-level estimates are defined as the results of analyses used to evaluate alternative management measures; planning-level estimates are recognized to include substantial uncertainties (commonly orders of magnitude). SELDM uses information about a highway site, the associated receiving-water basin, precipitation events, stormflow, water quality, and the performance of mitigation measures to produce a stochastic population of runoff-quality variables. SELDM provides input statistics for precipitation, prestorm flow, runoff coefficients, and concentrations of selected water-quality constituents from National datasets. Input statistics may be selected on the basis of the latitude, longitude, and physical characteristics of the site of interest and the upstream basin. The user also may derive and input statistics for each variable that are specific to a given site of interest or a given area.

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 variable. SELDM calculates the dilution of runoff in the receiving waters and the resulting downstream event mean concentrations and annual average lake concentrations. Results are ranked, and plotting positions are calculated, to indicate the level of risk of adverse effects caused by runoff concentrations, flows, and loads on receiving waters by storm and by year. Unlike deterministic hydrologic models, SELDM is not calibrated by changing values of input variables to match a historical record of values. Instead, input values for SELDM are based on site characteristics and representative statistics for each hydrologic variable. Thus, SELDM is an empirical model based on data and statistics rather than theoretical physiochemical equations.

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 variable. SELDM calculates the dilution of runoff in the receiving waters and the resulting downstream event mean concentrations and annual average lake concentrations. Results are ranked, and plotting positions are calculated, to indicate the level of risk of adverse effects caused by runoff concentrations, flows, and loads on receiving waters by storm and by year. Unlike deterministic hydrologic models, SELDM is not calibrated by changing values of input variables to match a historical record of values. Instead, input values for SELDM are based on site characteristics and representative statistics for each hydrologic variable. Thus, SELDM is an empirical model based on data and statistics rather than theoretical physiochemical equations

SELDM is a lumped parameter model because the highway site, the upstream basin, and the lake basin each are represented as a single homogeneous unit. Each of these source areas is represented by average basin properties, and results from SELDM are calculated as point estimates for the site of interest. Use of the lumped parameter approach facilitates rapid specification of model parameters to develop planning-level estimates with available data. The approach allows for parsimony in the required inputs to and outputs from the model and flexibility in the use of the model. For example, SELDM can be used to model runoff from various land covers or land uses by using the highway-site definition as long as representative water quality and impervious-fraction data are available.

Granato, G.E., 2012, Estimating basin lagtime and hydrograph-timing indexes used to characterize stormflows for runoff-quality analysis: U.S. Geological Survey Scientific Investigations Report 2012–5110, 47 p., with digital media https://doi.org/10.3133/sir20125110.

A nationwide study to better define triangular-hydrograph statistics for use with runoff-quality and flood-flow studies was done by the U.S. Geological Survey (USGS) in cooperation with the Federal Highway Administration. Although the triangular hydrograph is a simple linear approximation, the cumulative distribution of stormflow with a triangular hydrograph is a curvilinear S-curve that closely approximates the cumulative distribution of stormflows from measured data. The temporal distribution of flow within a runoff event can be estimated using the basin lagtime, (which is the time from the centroid of rainfall excess to the centroid of the corresponding runoff hydrograph) and the hydrograph recession ratio (which is the ratio of the duration of the falling limb to the rising limb of the hydrograph). This report documents results of the study, methods used to estimate the variables, and electronic files that facilitate calculation of variables.

Ten viable multiple-linear regression equations were developed to estimate basin lagtimes from readily determined drainage basin properties using data published in 37 stormflow studies. Regression equations using the basin lag factor (BLF, which is a variable calculated as the main-channel length, in miles, divided by the square root of the main-channel slope in feet per mile) and two variables describing development in the drainage basin were selected as the best candidates, because each equation explains about 70 percent of the variability in the data. The variables describing development are the USGS basin development factor (BDF, which is a function of the amount of channel modifications, storm sewers, and curb-and-gutter streets in a basin) and the total impervious area variable (IMPERV) in the basin. Two datasets were used to develop regression equations. The primary dataset included data from 493 sites that have values for the BLF, BDF, and IMPERV variables. This dataset was used to develop the best-fit regression equation using the BLF and BDF variables. The secondary dataset included data from 896 sites that have values for the BLF and IMPERV variables. This dataset was used to develop the best-fit regression equation using the BLF and IMPERV variables.

Analysis of hydrograph recession ratios and basin characteristics for 41 sites indicated that recession ratios are random variables. Thus, recession ratios cannot be estimated quantitatively using multiple linear regression equations developed using the data available for these sites. The minimums of recession ratios for different streamgages are well characterized by a value of one. The most probable values and maximum values of recession ratios for different streamgages are, however, more variable than the minimums. The most probable values of recession ratios for the 41 streamgages analyzed ranged from 1.0 to 3.52 and had a median of 1.85. The maximum values ranged from 2.66 to 11.3 and had a median of 4.36.

Granato, G.E., 2010, Methods for development of planning-level estimates of stormflow at unmonitored sites in the conterminous United States: Washington, D.C., U.S. Department of Transportation, Federal Highway Administration, FHWA-HEP-09-005, 90 p. Report On Line (3.5 MB). 

This report documents methods for data compilation and analysis of statistics for stormflows that meet data-quality objectives for order-of-magnitude planning-level water-quality estimates at unmonitored sites in the conterminous United States. Statistics for prestorm streamflow, precipitation, and runoff coefficients are used to model stormflows for use with the Stochastic Empirical Loading and Dilution Model (SELDM), which is a highway-runoff model. SELDM is designed to better quantify the risk of exceeding water-quality criteria as precipitation, discharge, ambient water quality, and highway-runoff quality vary from storm to storm. Summary statistics also may be used to help estimate annual- average water-quality loads. Streamflow statistics are used to estimate prestorm flows. Streamflow statistics are estimated by analysis of data from 2,873 U.S. Geological Survey streamgages in the conterminous United States with drainage areas ranging from 10 to 500 square miles and at least 24 years of record during the period 1960-2004. Streamflow statistics are regionalized using U.S. Environmental Protection Agency Level III nutrient ecoregions. Storm-event precipitation statistics are estimated by analysis of data from 2,610 National Oceanic and Atmospheric Administration hourly-precipitation data stations in the conterminous United States with at least 25 years of data during the 1965-2006 period. Storm-event precipitation statistics are regionalized using U.S. Environmental Protection Agency rain zones. Statistics to characterize volumetric runoff coefficients are estimated using data from 6,142 storm events at 306 study sites. Runoff coefficient statistics are not regionalized, but are organized by total impervious area. All of the geographic information system files, computer programs, data files, and regression results developed for this study are included on the CD-ROM accompanying this report.

Granato, G.E., and Cazenas, P.A., 2009, Highway-Runoff Database (HRDB Version 1.0)--A data warehouse and preprocessor for the stochastic empirical loading and dilution model: Washington, D.C., U.S. Department of Transportation, Federal Highway Administration, FHWA-HEP-09-004, 57 p. Report On Line (3 MB). Database-Design Map On Line (0.22 MB). RosaP link.
Software support page

This report documents highway-runoff database (HRDB), which 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). The HRDB currently includes 37 tables with data for 39,713 event mean concentration (EMC) measurements (including over 100 water-quality constituents) from 2,650 storm events, monitored at 103 highway-runoff monitoring sites in the conterminous United States, as documented in 7 selected highway-runoff data sets. These data include the 1990 FHWA runoff-quality model data compilation and results from 6 other data sets collected during the period 1993–2005. The HRDB application, which is the graphical-user interface and associated computer code, can be used to facilitate estimation of statistical properties of runoff coefficients, runoff-quality statistics, and relations between water-quality variables in highway runoff from the available data. The database application facilitates retrieval and processing of the available data.

Note: The Washington State Department of Transportation (WSDOT) has issued a data advisory indicating that their data do not meet data-quality standards. The WSDOT advises HRDB users not to use the data designated as the WA2005 data set. These data will be removed from a future version of the HRDB.

Note: Version 1.0.0a of the HRDB was published with a with a new MA data set in a USGS report during 2010; that report is:
Smith, K.P., and Granato, G.E., 2010, Quality of stormwater runoff discharged from Massachusetts highways, 2005–07: U.S. Geological Survey Scientific Investigations Report 2009–5269, 198 p., https://doi.org/10.3133/sir20095269.

Granato, G.E., Carlson, C.S., and Sniderman, B.S., 2009, Methods for development of planning-level stream-water-quality estimates at unmonitored sites in the conterminous United States: Washington, D.C., U.S. Department of Transportation, Federal Highway Administration, FHWA-HEP-09-003, 53 p. RosaP link.

This report documents methods for data compilation and analysis of water-quality-transport curves that meet data-quality-objectives for order-of-magnitude planning-level estimates of stream-water quality at unmonitored sites in the 84 U.S. Environmental Protection Agency Level III nutrient ecoregions in the conterminous United States. The water-quality- transport curves developed in this analysis are intended for use with a stochastic data-generation algorithm, for use with a highway-runoff model designed to better quantify the risk of exceeding water-quality criteria as precipitation, discharge, ambient water quality, and highway-runoff quality vary from storm to storm. Transport curves are regression relations used to estimate constituent concentrations from measured or estimated water-discharge values. Three constituents, total phosphorus, total hardness, and suspended sediment, were selected for regression analysis to develop transport curves for each ecoregion. However, the data compilation and interpretation methods described herein may be used with other water-quality constituents. A total of 24,581 USGS surface-water-quality monitoring stations with drainage areas ranging from 0.002 to 1,140 square miles were identified in the conterminous United States and cataloged for retrieval of water-quality data. The number of paired water-discharge and water-quality samples for total phosphorus, total hardness, and suspended sediment concentrations was 246,403; 107,289; and 275,950, respectively. Examination of transport curves developed with these data indicate that these curves are appropriate models describing the underlying processes of washoff or dilution expected for each constituent, and that predictions made using these transport curves are comparable with published estimates for each water-quality constituent. All of the geographic information system files, computer programs, data files, and regression results developed for this study are included on the CD-ROM accompanying this report. The CD-ROM also contains a data directory with more than 1,876,000 paired discharge and water-quality measurements that include 21 other constituents commonly studied in highway- and urban-runoff studies.

Granato, G.E., 2009, Computer programs for obtaining and analyzing daily mean streamflow data from the U.S. Geological Survey National Water Information System Web Site: U.S. Geological Survey Open-File Report 2008–1362, 123 p., 5 appendixes, https://doi.org/10.3133/ofr20081362.                       Software On-Line.

Software Update-Support Page.

These programs may be used to get data from the USGS NWISWeb, calculate flow-duration statistics, do flow extension for short term or partial-record streamflow stations, calculate basic streamflow statistics, and creat batch input files for the USEPA DFLOW program.

These programs were used as part of this project to calculate streamflow statistics for 2,783 selected U.S. Geological Survey streamflow-gaging stations among U.S. Environmental Protection Agency Level III ecoregions.

Granato, G.E., 2006, Kendall-Theil Robust Line (KTRLine--version 1.0)—A visual basic program for calculating and graphing robust nonparametric estimates of linear-regression coefficients between two continuous variables: Techniques and Methods of the U.S. Geological Survey, book 4, chap. A7, 31 p., https://doi.org/10.3133/tm4A7.                Software On-Line.                Software Update-Support Page.

The KTRLine program may be used to calculate parameters for robust, nonparametric estimates of linear-regression coefficients between two continuous variables. The Kendall-Theil robust line was selected because this robust nonparametric method is resistant to the effects of outliers and nonnormality in residuals that commonly characterize hydrologic data sets. The slope of the line is calculated as the median of all possible pairwise slopes between points. The intercept is calculated so that the line will run through the median of input data. A single-line model or a multisegment model may be specified. The KTRLine software is a graphical tool that facilitates development of regression models by use of graphs of the regression line with data and the regression residuals. The user may individually transform the independent and dependent variables to reduce heteroscedasticity and to linearize data. The program plots the data and the regression line. The program prints model specifications and regression statistics to the screen and saves the results to a user-specified output file in a format suitable for use with other programs.

The KTRLine program was used as part of this project to develop water-quality transport curves, relations between TSS and suspended sediment concentrations for highway runoff, relations between watershed area and pre-storm streamflow statistics and relations between the total-impervious fraction and runoff coefficient statistics of highway sites and upstream basins.

Other Products

Jones, S.C., 2017, FHWA and USGS Cooperate to Provide Environmental Engineering/Science Curricula Developed for the Stochastic Empirical Loading and Dilution Model (SELDM) to Universities and Colleges: Federal Highway Administration, Office of Planning, Environment, and Realty, Educational-Outreach Factsheet, 2 p. 

Jones, S.C., 2014, The Stochastic Empirical Loading and Dilution Model (SELDM): Federal Highway Administration, Office of Planning, Environment, and Realty, MAP-21 Factsheet, 2p. 

Jones, S.C., 2014, The Stochastic Empirical Loading and Dilution Model (SELDM)–The new Federal Highway Administration runoff-quality model: Federal Highway Administration, Office of Project Development and Environmental Review Factsheet, 2 p. 

Granato, G.E., Cazenas, P.A., Jones, S.C., and Osterhues, Marlys, 2013, The Highway Runoff Database (HRDB) is a data warehouse and preprocessor for the new FHWA-USGS Stochastic Empirical Loading and Dilution Model (SELDM): Poster presented at 2013 International Conference on Ecology and Transportation-- Canyons, Crossroads, Connections Meeting Today's Transportation Ecology Challenges with Innovative Science & Sustainable Solutions, June 23-27, 2013 in Scottsdale, Arizona, Organized by the Center for Transportation and the Environment, Raleigh, North Carolina, 36 by 58 inches. 

The USGS, in cooperation with the FHWA developed the Highway Runoff Database (HRDB) as a data warehouse and preprocessor for the new Stochastic Empirical Loading and Dilution Model (SELDM). The HRDB is data rich. The latest version of the highway runoff database includes 54,384 event-mean concentrations (EMCs), from 4,186 storm events monitored at 117 study sites across the United States. The HRDB includes data for 194 highway-runoff constituents. Most of the constituents of greatest interest for highway-runoff characterization have more than 500 EMC samples in the database. The HRDB is easy to use. Data and statistics in the HRDB are readily available in easy-to-use formats with just a few mouse-clicks. Availability of this highway-runoff data in a standard format and the ease of use of the graphical user interface should provide information to improve highway-project delivery without compromising environmental protection.