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). Highway 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 average 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 ultraurban 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.

In cooperation with FHWA, the U.S. Geological Survey developed the stochastic empirical loading and dilution model (SELDM) to supersede the 1990 FHWA runoff quality model. The SELDM tool is designed to transform disparate and complex scientific data into meaningful information about the adverse risks of runoff on receiving waters, the potential need for mitigation measures, and the potential effectiveness of such measures for reducing such risks. The SELDM tool is easy to use because much of the information and data needed to run it are embedded in the model and obtained by defining the site location and five simple basin properties. Information and data from thousands of sites across the country were compiled to facilitate the use of the SELDM tool. A case study illustrates how to use the SELDM tool for conducting the types of sensitivity analyses needed to properly assess water quality risks. For example, the 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, the risks for total phosphorus excursions are substantially affected by the selected criteria and the modeling methods used. For example, if a single deterministic concentration is used rather than a stochastic population of values to model upstream concentrations, then the percentage of water quality excursions in the downstream receiving waters may depend entirely on the selected upstream concentration.

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 concentrations (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 suspended 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 representative statistics from available datasets. State departments of transportation (DOTs) need quantitative information about the properties of highway runoff, including event mean concentrations (EMCs) of water-quality constituents, runoff flows, and runoff loads to assess and mitigate potential adverse effects of highway runoff on the Nation's receiving waters. Organization and centralization of highway-runoff data from various sources has consistently been identified as a high-priority environmental research need by the Federal Highway Administration (FHWA), the Transportation Research Board (TRB), and the National Cooperative Highway Research Program (NCHRP) (1-5). To meet this need, the U.S. Geological Survey developed and published the Highway Runoff Database (HRDB) in cooperation with the FHWA (6-8). The HRDB is a data warehouse and a preprocessor for the Stochastic Empirical Loading and Dilution Model (SELDM) (6, 9). Since the initial publication in 2009, the HRDB has been used in research efforts to evaluate potential effects of runoff on receiving waters (10-12), evaluate the performance of post-construction stormwater best management practices (11, 13-15), and estimate total maximum daily loads (TMDLs) (16-18) for national and state research efforts.

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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 sedimentwater 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.