Spreadsheet for identifying individual storms for the Stochastic Empirical Loading Dilution Model (SELDM) . The spreadsheet was used in conjunction with the SELDM simulations used in the publication: Stonewall, A.J., and Granato, G.E., 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.

Spreadsheet used to calculated hydrograph recession statistical parameters (Minimum, Most Probable Value, and Maximum) for the Stochastic Empirical Loading Dilution Model (SELDM) . The spreadsheet was used in conjunction with the SELDM simulations used in the publication: Stonewall, A.J., and Granato, G.E., 2018, 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, and after using the Hydrograph.xlsx spreadsheet.

Spreadsheet used to calculated hydrograph recession parameters (Minimum, Most Probable Value, and Maximum) for the Stochastic Empirical Loading Dilution Model (SELDM) . The spreadsheet was used in conjunction with the SELDM simulations used in the publication: Stonewall, A.J., and Granato, G.E., 2018, 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

Spreadsheet used to calculated hydrograph recession parameters (Minimum, Most Probable Value, and Maximum) for the Stochastic Empirical Loading Dilution Model (SELDM) . The spreadsheet was used in conjunction with the SELDM simulations used in the publication: Stonewall, A.J., and Granato, G.E., 2018, 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

Spreadsheet used to calculate Highway Site characteristics (Drainage area, slope and impervious fraction) for the Stochastic Empirical Loading Dilution Model (SELDM) . The spreadsheet was used in conjunction with the SELDM simulations used in the publication: Stonewall, A.J., and Granato, G.E., 2018, 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.

This document provides guidance for using the Stochastic Empirical Loading Dilution Model (SELDM) in the state of Oregon. The document is meant as an accompaniment to the publication: Stonewall, A.J., and Granato, G.E., 2018, 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

This document provides guidance for using the Stochastic Empirical Loading Dilution Model (SELDM) in the state of Oregon. The document is meant as an accompaniment to the publication: Stonewall, A.J., and Granato, G.E., 2018, 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

Stochastic Empirical Loading and Dilution Model (SELDM) utilizes Microsoft Access databases to build and run model simulations. The compiled database was used for all simulations related to the publication: Stonewall, A.J., and Granato, G.E., 2018, 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

Stochastic Empirical Loading and Dilution Model (SELDM) utilizes Microsoft Access databases to build and run model simulations. The compiled database was used for all simulations related to the publication: Stonewall, A.J., and Granato, G.E., 2018, 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

In 2013, the U.S. Geological Survey (USGS) in partnership with the U.S. Federal Highway Administration (FHWA) published a new national stormwater quality model called the Stochastic Empirical Loading Dilution Model (SELDM; Granato, 2013). The model is optimized for roadway projects but in theory can be applied to a broad range of development types. SELDM is a statistically-based empirical model pre-populated with much of the data required to successfully run the application (Granato, 2013). The model uses Monte Carlo methods (as opposed to deterministic methods) to generate a wide range of precipitation events and stormwater discharges coupled with water-quality constituent concentrations and loads from the upstream basin and highway site. SELDM is particularly useful for stormwater managers in its ability to provide the statistical probability of a water-quality standard exceedance that could occur downstream of a stormwater discharge location during the period of record simulated as part of a SELDM analysis. SELDM can be used to model a variety of Best Management Practices (BMPs), which allows the user to evaluate the subsequent instream water-quality benefit of different stormwater treatment devices. This functionality makes the model well suited for supporting BMP-specific cost/benefit analyses. In 2015, the North Carolina Department of Transportation (NCDOT) initiated a partnership with the USGS South Atlantic Water Science Center (Raleigh, North Carolina office) to enhance the national SELDM model with additional data specific to North Carolina (NC) to improve the model’s predictive performance across the State. Specific USGS data incorporated to enhance the NC SELDM model included selected North Carolina streamflow data as well as water-quality transport curves for selected constituents. SELDM streamflow statistics (based on data through the 2015 water year) were computed for 266 continuous-record streamgages and updated in the StreamStats database, which is accessible from the USGS StreamStats application for North Carolina (available online via https://streamstats.usgs.gov/ss/). Instantaneous streamflow data available at 30 selected continuous-record streamgages across North Carolina, with drainage areas ranging from 4.12 to 63.3 square miles, were used to develop site-specific recession ratio statistics. Water-quality data through the 2016 water year were used to develop water-quality transport curves for 27 streamgages for the following constituents: suspended sediment concentration, total nitrogen, total phosphorus, turbidity, copper, lead, and zinc. The NCDOT identified NC highway-runoff research reports containing water-quality and quantity data available from non-USGS sources. These data were reviewed by USGS and – where deemed acceptable – were uploaded into the FHWA Highway-Runoff Database, the data warehouse and preprocessor for SELDM (Granato and others, 2018; Granato and Cazenas, 2009; Smith and Granato, 2010). Based on the analysis techniques documented by Granato (2014) in a national BMP study and using available water-quality sample data from selected highway-runoff and BMP site pairs, performance data from the NC highway-runoff research reports were also analyzed and incorporated into the NC SELDM model for three BMP types. Results of analyses completed during development of the NC SELDM model are documented in Weaver and others (2019). In 2018, USGS and NCDOT initiated an additional “phase 2” study for the NC SELDM model to complete 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