Tools for use in Oregon with the Stochastic Empirical Loading Dilution Model created for U.S. Geological Survey Scientific Investigations Report 2019-5053, 116 p., https://doi.org/10.3133/sir5053

공공데이터포털

A series of tools (spreadsheets, a database and a document) to be 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

Guidance document for using the Stochastic Empirical Loading Dilution Model created for U.S. Geological Survey Scientific Investigations Report 2019-5053, 116 p., https://doi.org/10.3133/sir20195053

공공데이터포털

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

Guidance document for using the Stochastic Empirical Loading Dilution Model created for U.S. Geological Survey Scientific Investigations Report 2019-5053, 116 p., https://doi.org/10.3133/sir20195053

공공데이터포털

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 in MS Access created for U.S. Geological Survey Scientific Investigations Report 2019-5053, 116 p., https://doi.org/10.3133/sir20195053

공공데이터포털

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 in MS Access created for U.S. Geological Survey Scientific Investigations Report 2019-5053, 116 p., https://doi.org/10.3133/sir20195053

공공데이터포털

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

R programming code for analyzing output from the Stochastic Empirical Loading Dilution Model created for U.S. Geological Survey Scientific Investigations Report 2019-5053, 116 p., https://doi.org/10.3133/sir20195053

공공데이터포털

This R script can be used to analyze SELDM results. The script is specifically tailored for 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

R programming code for analyzing output from the Stochastic Empirical Loading Dilution Model created for U.S. Geological Survey Scientific Investigations Report 2019-5053, 116 p., https://doi.org/10.3133/sir20195053

공공데이터포털

This R script can be used to analyze SELDM results. The script is specifically tailored for 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

Excel spreadsheet used for calculating hydrograph recession values use in the Stochastic Empirical Loading Dilution Model created for U.S. Geological Survey Scientific Investigations Report 2019-5053, 116 p., https://doi.org/10.3133/sir5053

공공데이터포털

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

Excel spreadsheet used for calculating hydrograph recession values use in the Stochastic Empirical Loading Dilution Model created for U.S. Geological Survey Scientific Investigations Report 2019-5053, 116 p., https://doi.org/10.3133/sir5053

공공데이터포털

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

Excel spreadsheet used for calculating hydrograph recession parameter statistics used in the Stochastic Empirical Loading Dilution Model created for U.S. Geological Survey Scientific Investigations Report 2019-5053, 116 p., https://doi.org/10.3133/sir5053

공공데이터포털

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.