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.

This data release 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 (USGS) developed SELDM and the statistics documented in this report in cooperation with the Federal Highway Administration (FHWA) to indicate the risk for stormwater flows, concentrations, and loads to be above 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 modeled by using the trapezoidal distribution and the rank correlation with the associated highway-runoff variables. This data release also documents statistics for estimating the minimum irreducible concentration (MIC), which is the lowest expected effluent concentration from a 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. In SELDM, BMP performance is the result of random combinations of variables documented in this report and the interplay among the selected distributions and correlations to inflow variables. Granato (2014) and Granato and others (2020) describe the methods used to calculate these statistics and provide summary statistics for these variables. This data release provides the individual at-site statistics. The statistics were calculated by using data extracted from a modified copy of the December 2019 version of International Stormwater Best Management Practices Database. 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 MIC values were developed for 51 runoff-quality constituents commonly measured in highway and urban runoff studies.

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). 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. The SELDM was developed as a database application with a simple graphical user interface (GUI) by using Microsoft Access® to facilitate highway and urban runoff analyses by scientists, engineers, and decisionmakers without specialized modeling skills. 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. 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.

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.

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. This analysis was done with a version 1.1.1 of the Stochastic Empirical Loading and Dilution Model (SELDM) that was populated with regional statistics for southern New England. SELDM uses basin properties and hydrologic statistics to simulate runoff from a site of interest, which may be a highway site or another developed (urban) area, and concurrent stormflow from an upstream basin to calculate downstream values, which are the sum of contributions from the site of interest and the upstream basin. Because there are few monitoring sites with data relative to the number of potential sites of interest, the probability that data will be available at a site of interest is low. Furthermore, much of the data available at monitored sites is not sufficient to characterize long-term stormwater-quality conditions because most water-quality monitoring sites have less than one year of data. 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. The methods and statistics in this study were developed for use with SELDM but may be used with other models. The information provided here can be used for robust decision making by highway practitioners, regulators, and decisionmakers. The project described in this data release was conducted in cooperation with the Federal Highway Administration and the Connecticut, Massachusetts, and Rhode Island Departments of Transportation. The data release contains twenty-one compressed (zip) files, one ReadMe file pertaining to the data release as a whole (ReadMe.txt), and a diagram to illustrate the organization of the zip files and subfolders (ReadMeDiagram.pdf). Please refer to ReadMe files within the zip files and subfolders for more detailed metadata pertaining to the data, statistics, and software provided.

A previously developed groundwater flow model (https://doi.org/10.5066/P9051RUT) was slightly modified to estimate the risk-based discrete relation between groundwater extraction and surface-water/groundwater exchange. Previously, the concept of a ''capture map'' has been put forward as a means to effectively summarize this relation for decision-making consumption. While capture maps have enjoyed success in the environmental simulation industry, they are deterministic, ignoring uncertainty in the underlying model. Furthermore, capture maps are not typically calculated in a manner that facilitates analysis of varying combinations of extraction locations and/or reaches. That is, they are typically constructed with focus on a single reach or group of reaches. The former of these limitations is important for conveying risk to decision makers, while the latter is important for decision-making support related to surface-water management, where future foci may include reaches that were not the focus of the original capture analysis. Herein, we use a MODFLOW-NWT groundwater/surface-water model of the lower San Antonio River, Texas, USA to demonstrate a technique to estimate risk-based and spatially discrete streamflow depletion potential. This USGS data release contains all of the input and output files for the simulations described in the associated journal article (https://doi.org/10.1111/gwat.13080)

This data release contains inputs and outputs for hydrologic simulations of the conterminous United States (CONUS) using the National Hydrologic Model (NHM) application of the Precipitation Runoff Modeling System (PRMS) in ASCII and binary format and explanatory graphics in pdf format. These simulations were developed to provide estimates of water availability for historical conditions for the period October 1, 1980 to September 30, 2016 for five different calibration configurations; the first three years of the simulation should be considered the initialization period and should not be used for subsequent analysis. The five versions of model parameters and associated model output included in this data release are described in table 1 and in the Supplemental Information section of this metadata record. Table 2 provides information about the baseline datasets used for model calibration for each of the five parameter configurations. Figure 1 shows a schematic of the multi-step calibration procedure used to develop the model parameters. Table 3 describes the 36 model output variables that are included in the five attached folders. Five .tar folders are named according to the simulation configuration in table 1 and include the 36-model output variable files. Table 4 provides information about the 8,274 streamgage locations that are included in the NHM-PRMS. The NHM-PRMS parameter and control files for each of the five simulations are located on the child pages associated with this data release. The PRMS climate forcing input files for the simulations are in the DAYMET_CBH.zip folder. Summary files by streamgage of measured and simulated streamflow for the byHRU, byHRU_musk, and byHRU_musk_obs simulations are in the Streamgage_location_simulations_5999.zip folder. Any time series data in the model output files prior to the October 1, 1983 start date should be considered part of the model initialization period and should not be used. Please refer to the Supplemental Information element of this metadata record for more information about the model calibration, inputs, outputs, and summaries included in this data release.