Stochastic Empirical Loading and Dilution Model (SELDM)
Note: SELDM is now on version 1.0.2 Please use the new version on the software support page here
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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
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
Opent to employees of Federal, State, and Local Governments: We are looking for Fall 2017 - Spring 2018 training locations now.
Opent to the public: We had a one-day class at StormCon2016© and we are looking for a public 3-day class venue for 2017/2018
Technical Reports and Software
Note: The CD-ROM
image files are large and need to be saved to the user's computer to be used.
Right-click the link and use the save as option.
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.
- 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., 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.
- 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.
- 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 20145099, 74 p. Report On Line
- 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 20145037, 37 p. Report On Line
- 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. http://doi.org/10.3141/2436-14
Originally published as:
Granato, G.E., and Jones, S.C., 2014, The Stochastic Empirical Loading and Dilution Model (SELDM) for analysis of flows, concentrations, and loads of highway runoff constituents: in Compendium of Papers for the Transportation Research Board 93rd Annual Meeting, January 12-16, 2014, Washington, D.C., 19 p.
- 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., CDROM.
Report On-Line 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.
-- An ISO image of the
CD-ROM with the model and supporting documentation (0.1 MB).
-- A gi image of the CD-ROM with the model and supporting documentation (0.1 MB).
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 20125110, 47 p., with digital media Report On Line (3.5 MB).
- 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). Poster-overview of report contents (2.7 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.
-- An ISO image of the
CD-ROM with the database and supporting documentation (122 MB).
-- A compressed file containing the ISO image of the CD-ROM with
the database and supporting documentation (70 MB).
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).
- 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 19932005. 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.
-- An ISO image of the
CD-ROM with the database and supporting documentation (73 MB).
-- A compressed file containing the ISO image of the CD-ROM with
the database and supporting documentation (48 MB).
Please see the On-line presentation on the HRDB
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, 200507: U.S. Geological Survey Scientific Investigations Report 20095269, 198 p., Report and database on-line
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. Report
On Line (1.5 MB). Example
Water-Quality Transport Curve Poster On Line (1.7 MB).
- 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.
-- An ISO image of the
CD-ROM with the database and supporting documentation (580 MB).
-- A compressed file containing the ISO image of the CD-ROM with
the database and supporting documentation (275 MB).
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 20081362, 123 p. on
CD-ROM, 5 appendixes. Report On
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. Report On-Line Software
- 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
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. Factsheet On-Line
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. Factsheet On-Line
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. Factsheet On-Line
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. Poster On-Line
- 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 statisics 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
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