Water

A watershed is the boundary of a drainage basin that has an area defined by a common drainage endpoint, the terms watershed and drainage basin commonly are uses synonymously. Natural and anthropogenic land covers within each watershed can affect the receiving water quality and ecology directly and indirectly. Transportation and other developed land covers can generate or convey stormwater.

The United States Environmental Protection Agency (EPA) provides resources on protecting watersheds and other water sources, including the How’s My Waterway tool that provides lists of organizations working to protect local watersheds nationwide.

The U.S. Geological Survey provides the StreamStats tool that can be used for watershed delineation, querying basin properties, and calculating streamflow statistics in many states.

The U.S. Geological Survey investigates the occurrence, quantity, quality, distribution, and movement of surface and underground waters and disseminates the data to the public on the National Water Information Website.

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.

Wetlands are delicate natural resources that serve many functions. Not only do they provide habitat for aquatic species, but they also improve water quality and manage floodwaters.

The Federal Government offers the following resources for minimizing and mitigating the impacts from transportation projects on wetlands:

5 Star Wetland and Urban Waters Restoration Grants - This program brings together students, conservation corps, other youth groups, citizen groups, corporations, landowners and government agencies to provide environmental education and training through projects that restore wetlands and streams. The program provides challenge grants, technical support and opportunities for information exchange to enable community-based restoration projects. Funding levels are modest, from $10,000 to $40,000, with $20,000 as the average amount awarded per project.

Results of the FHWA Domestic Scan of Successful Wetland Mitigation Programs, 2005 - Managing and mitigating wetlands impacts due to highway projects is a significant issue for FHWA and State DOTs. To help find out what kind of issues were most problematic, and to identify successful solutions that were being used, the Office of Environment and Planning conducted an interagency scan of wetland mitigation and impact management practices in eight States. There was a strong focus on mitigation banking, including what issues and solutions have been associated with the development of successful, workable wetland mitigation banks. Where banks were not being used, successful on-site mitigation projects were examined.

Stochastic Empirical Loading and Dilution Model (SELDM) software archive, 2023 - Together with partner organizations, the USGS is involved in data collection, analysis, and synthesis to improve our understanding of wetlands.

Executive Orders

DOT Order 5660.1a "Preservation of the Nation's Wetlands"

Training

FHWA offers the following instructional recording on wetlands:

RIBITS Wetland Mitigation Tool - Live Demonstration
FHWA and the U.S. Army Corps of Engineers (USACE) have produced an instructional recording for transportation users on how to use the Army Corps Regulatory In lieu fee and Bank Information Tracking System (RIBITS) to find mitigation credits for transportation projects. A version of this training was presented as a webinar in December of 2013. RIBITS is a web site that provides information on stream and wetland mitigation banks and in-lieu fee programs across the country. Users can access a wide range of information on wetland mitigation and endangered species conservation banks including the availability of mitigation credits, bank ledgers, service areas, and national and local policies and practices for the use of mitigation and conservation banks. Viewers of this demonstration will learn about:

• Using RIBITS (Regulatory In lieu fee and Bank Information Tracking System) to determine if you can purchase mitigation credits for your transportation project.
• Documentation for these mitigation banking or in-lieu fee programs.
• New RIBITS features for transportation professionals.

Access the recording.

Federal Highway Administration Reports

Models

Note: The older "Driscoll Model" has been superseded by the Stochastic Empirical Loading and Dilution Model (SELDM).

• Driscoll, E.D., Shelley, P.E., and Strecker, E.W., 1990a, Pollutant loadings and impacts from highway stormwater runoff, v. I-Design procedure: Washington, D.C., Federal Highway Administration Final Report FHWA-RD-88-006, 67 p.
• Driscoll, E.D., Shelley, P.E., and Strecker, E.W., 1990b, Pollutant loadings and impacts from highway stormwater runoff, v. II-User’s guide for interactive computer implementation of design procedure: Washington, D.C., Federal Highway Administration Final Report FHWA-RD88-007, 23 p.

Runoff Quality Characterization

• Driscoll, E.D., Shelley, P.E., and Strecker, E.W., 1990c, Pollutant loadings and impacts from highway stormwater runoff, v. III-Analytical investigation and research report: Washington, D.C., Federal Highway Administration Final Report FHWA-RD-88-008, 160 p.
• Driscoll, E.D., Shelley, P.E., and Strecker, E.W., 1990d, Pollutant loadings and impacts from highway stormwater runoff, v. IV-Research report data appendix: Washington, D.C., Federal Highway Administration Final Report FHWA-RD-88-009, 143 p.
• 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: Federal Highway Administration report FHWA-HEP-09-004, 57 p.
• Granato, G.E., Dionne, S.G., Tana, C.T., and King, T.L., 2003, National Highway Runoff Water-Quality Data and Methodology Synthesis, Volume II -- Project documentation: Washington, D.C., U.S. Department of Transportation, Federal Highway Administration, FHWA-EP-03-055, 22 p. with CD-ROM.
• Granato, G.E., Zenone, C., and Cazenas, P.A. (eds.), 2003, National Highway Runoff Water-Quality Data and Methodology Synthesis, Volume I -- Technical issues for monitoring highway runoff and urban stormwater: Washington, D.C., U.S. Department of Transportation, Federal Highway Administration, FHWA-EP-03-054, 479 p.
• Jongedyk, H.A., Bank, Fred, 1999, Is Highway Runoff a Serious Problem? Washington, D.C., U.S. Department of Transportation, Federal Highway Administration, FHWA-RD-98-079, 10 p.
• Strecker, Eric; Mayo, Lynn; Quigley, Marcus; Howell, James, 2001, Guidance manual for monitoring highway runoff water quality: Washington, D.C., U.S. Department of Transportation, Federal Highway Administration, FHWAEP-01-022, 206 p.

Best Management Practices

• Mayfield, M., K. Narayanaswamy, and D. Jackson. 2014. Determining the State of the Practice in Data Collection and Performance Measurement of Stormwater Best Management Practices: Federal Highway Administration Final Report FHWA-HEP-16-021, 102 p.
• Shoemaker, L., Lahlou, M., Doll, A., and Cazenas, P., 2000, Stormwater best management practices in an ultraurban setting: selection and monitoring: Federal Highway Administration Report FHWA-EP-00-002, 287 p.
• Young, G.K., Stein, P.C., Kammer, F.G., and Bank, F., 1996, Evaluation and Management of Highway Runoff Water Quality: Washington, D.C., U.S. Department of Transportation, Federal Highway Administration report FHWA-PD-96-032, 480 p.

Regulatory Compliance

• Granato, G.E., 2003, National Highway Runoff Water-Quality Data and Methodology Synthesis, Volume III -- Availability and documentation of published information for synthesis of regional or national highway-runoff quality data: Washington, D.C., U.S. Department of Transportation, Federal Highway Administration, FHWA-EP-03-056, 71 p.

Watersheds

• Granato, G.E., 2010, Methods for development of planning-level estimates of stormflow at unmonitored stream sites in the conterminous United States: Federal Highway Administration report FHWA–HEP–09–005, 90 p., 1 CD–ROM.
• Granato, G.E., Carlson, C.S., and Sniderman, B.S., 2009, Methods for development of planning-level estimates of water quality at unmonitored stream sites in the conterminous United States: Washington, D.C., Federal Highway Administration report FHWA-HEP-09-003, 53 p.

U.S. Geological Survey Reports

Best Management Practices

• Conlon, K.J., and Journey, C.A., 2008, Evaluation of four structural best management practices for highway runoff in Beaufort and Colleton Counties, South Carolina, 2005–2006: U.S. Geological Survey Scientific Investigations Report 2008–5150, 121 p.
• 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.
• Granato, G.E., 2021, Best Management Practices Statistical Estimator (BMPSE) Version 1.2.0: U.S. Geological Survey software release.
• 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.
• 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.
• Horwatich, J.A., Bannerman, R.T., and Pearson, Robert, 2011, Highway-runoff quality, and treatment efficiencies of a hydrodynamic-settling device and a stormwater-filtration device in Milwaukee, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2010–5160, 75 p.
• 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.
• Smith, K.P., 2002, Effectiveness of Three Best Management Practices for Highway-Runoff Quality along the Southeast Expressway, Boston, Massachusetts: U.S. Geological Survey Water-Resources Investigations Report, 62 p., + 1 CD-ROM.
• Smith, K. P., 2010, Effectiveness of catch basins equipped with hoods in retaining gross solids and hydrocarbons in highway runoff, Southeast Expressway, Boston, Massachusetts, 2008–09: U.S. Geological Survey Scientific Investigations Report 2010–5182, 23 p.

Runoff Quality Characterization

• Buckler, D.R., Granato, G.E., 1999, Assessing biological effects from highway-runoff constituents: U.S. Geological Survey Open-File Report 99-240, 45 p.
• Granato, G.E., 2021, Highway-Runoff Database (HRDB) Version 1.1.0b in 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.
• 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.
• 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.
• 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.
• 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., 1 CD-ROM.
• 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.
• Wagner, C.R., Fitzgerald, S.A., Sherrell, R.D., Harned, D.A., Staub, E.L., Pointer, B.H., and Wehmeyer, L.L., 2011, Characterization of stormwater runoff from bridges in North Carolina and the effects of bridge deck runoff on receiving streams: U.S. Geological Survey Scientific Investigations Report 2011–5180, 95 p., 8 apps.
• 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.

Regulatory Compliance

• Granato, G.E., DeSimone, L.A., Barbaro, J.R., and Jeznach, L.C., 2015, Methods for evaluating potential sources of chloride in surface waters and groundwaters of the conterminous United States: U.S. Geological Survey Open-File Report 2015–1080, 89 p.
• 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.
• 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.
• 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.
• 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.
• 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.

Watersheds

• 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.
• 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.
• Slonecker, E.T. and Tilley, J.S., 2004, An Evaluation of the Individual Components and Accuracies Associated with the Determination of Impervious Area: GIScience & Remote Sensing, v. 41, no. 2, 20 p.
• 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.
• Tilley, J.S. and Slonecker, E.T., 2007, Quantifying the Components of Impervious Surfaces: U.S. Geological Survey Open-File Report 2007-1008, 34 p.

National Cooperative Highway Research Program Reports

Best Management Practices

• Leisenring, M., Hobson, P., Clary, J., and Krall, J., 2013, International stormwater best management practices (BMP) database advanced analysis—Influence of design parameters on achievable effluent concentrations: International Stormwater BMP Database, 74 p.
• Leisenring, M., Hobson, P., Pankani, D., Nguyen, L., Clary, J., Rogers, H., Jones, J., and Strecker, E., 2020, Use of the state department of transportation portal to the international stormwater best management practices database: National Cooperative Highway Research Program Project 25–25, Task 120 final report, 102 p., app.
• National Academies of Sciences, Engineering, and Medicine, 2012, Guidelines for evaluating and selecting modifications to existing roadway drainage infrastructure to improve water quality in ultra-urban areas: National Cooperative Highway Research Program Report 728, 167 p.
• National Academies of Sciences, Engineering, and Medicine, 2014, Measuring and removing dissolved metals from stormwater in highly urbanized areas: Washington, D.C., National Cooperative Highway Research Program Report 767, [variously paged; 172 p.].
• National Academies of Sciences, Engineering, and Medicine, 2015, Volume reduction of highway runoff in urban areas—Guidance manual: Washington, D.C., National Cooperative Highway Research Program Report 802, 132 p., 3 app.
• National Academies of Sciences, Engineering, and Medicine, 2019, Stormwater infiltration in the highway environment—Guidance manual: Washington, D.C., National Cooperative Highway Research Program, Research Report 922, 210 p.
• National Cooperative Highway Research Program, 2006, Evaluation of best management practices for highway runoff control: National Cooperative Highway Research Program Research Report 565, 132 p.
• Taylor, S., Barrett, M., Leisenring, M., Sahu, S., Pankani, D., Poresky, A., Questad, A., Strecker, E., Weinstein, N., and Venner, M., 2014, Long-term performance and life-cycle costs of stormwater best management practices: National Cooperative Highway Research Program Research Report 792, 148 p.

Regulatory Compliance

• Bank, F.G., Cazenas P.A., Cutshall, C.D., Granato, G.E., Iyer B., Jongedyk, H., Palumbo, V.J., Prendergast G., Salter, J., Storey B., Young, G.K., 1997, Water Quality and Hydrology: in Environmental Research Needs in Transportation, Transportation Research Circular 469, Transportation Research Board, National Research Council, Washington D.C. p. 73-80.
• Lantin, A., Larsen, L., Vyas, A., Barrett, M., Leisenring, M., Koryto, K., and Pechacek, L., 2019, Approaches for determining and complying with TMDL requirements related to roadway stormwater runoff: National Academies Press, National Cooperative Highway Research Program Research Report 918, 133 p.
• McGowen, S., Smith, B., Taylor, S., Brindle, F., Cazenas, P.A., Davis, V.W., Hemmerlein, M., Herbert, R., Lauffer, M.S., Lewis, J., and Ripka, T., 2009, Best practices in addressing NPDES and other water quality issues in highway system management: National Cooperative Highway Research Program, Scan Team Report 08–03, [variously paged; 192 p.], accessed March 11, 2023.
• National Academies of Sciences, Engineering, and Medicine, 2017, A watershed approach to mitigating stormwater impacts: National Cooperative Highway Research Program Report 840, 116 p.

The Federal Highway Administration developed a set of stormwater-modeling tools 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 management measures for reducing these risks. These tools include:

• Highway-Runoff Database (HRDB)
• Stochastic Empirical Loading and Dilution Model (SELDM)
• Kendall-Theil Robust Line (KTRLine) analysis tool
• InterpretSELDM a graphical post processor for interpreting SELDM outputs

These tools are documented in the following publications:

• 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.
• 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.
• Granato, G.E., 2019, Highway-Runoff Database (HRDB) Version 1.1.0 - A data warehouse and preprocessor for the stochastic empirical loading and dilution model: U.S. Geological Survey data release.
• Granato, G.E., 2019, InterpretSELDM version 1.0 The Stochastic Empirical Loading and Dilution Model (SELDM) output interpreter: U.S. Geological Survey software release.
• Granato, G.E., 2021, Stochastic Empirical Loading and Dilution Model (SELDM) software archive: U.S. Geological Survey software release.
• 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.
• 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.
• 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.
• 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.

• AASHTO Technical Committee on Hydrology and Hydraulics (TCHH), 2024 - TCHH members actively promote, solicit, and participate in national and state hydraulic engineering research. TCHH collaborates and coordinates with committees of the Transportation Research Board (TRB) and state DOTs to develop research need statements applicable to hydraulic engineering for funding through the National Cooperative Highway Research Program (NCHRP).
• AASHTO Stormwater Working Group of the Committee on Environmental and Sustainability (CES), 2024 - The CES supports its members in delivering a national, regional, and local intermodal transportation system that is safe, resilient, economical, efficient, environmentally sound, and aesthetically and culturally sensitive.
• The International Stormwater Best Management Practices (BMP) Database project website features a database of over 600 BMP studies, performance analysis results, tools for use in BMP performance studies, monitoring guidance and other study-related publications.
• Stormwater Discharges from Transportation Sources (EPA) - Similar to traditional stormwater management authorities (cities and counties), transportation authorities are also responsible for managing the stormwater runoff that discharges to our nation’s waters via regulated municipal separate storm sewer systems (MS4s) along streets, roads, and highways.
• TRB Publications about Environment - The Transportation Review Board maintains an updated list of publications related to transportation and the environment.
• Evaluation of Best Management Practices for Highway Runoff Control, 2006 - This report focuses on improving the scientific and technical knowledge base for the selection of best management practices (BMPs) through a better understanding of BMP performance and application. This report documents an extensive program of research on the characterization of BMPs and stormwater, and the influence of factors such as land use practice, hydraulic characteristics, regional factors, and performance evaluation. The report includes a CD containing a spreadsheet model and three additional volumes: User’s Guide for BMP/LID Selection, Appendices to the User’s Guide, and Low Impact Development Design Manual for Highway Runoff Control.