Stochastic Empirical Loading and Dilution Model (SELDM) software archive
Dates
Publication Date
2021-05-14
Revision
2022-12-16
Citation
Granato, G.E., 2021, Stochastic Empirical Loading and Dilution Model (SELDM) software archive: U.S. Geological Survey software release, https://doi.org/10.5066/P9PYG7T5.
Summary
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 [...]
Summary
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. Version 1.1.1 was developed to allow SELDM to run within the 64-bit Microsoft Office environment. Details about version changes are provided within SELDM’s GUI and in the “ReadMe” files within this software release.
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.
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.
All software files are available in this software release.
Purpose
This data release is a software archive to document different versions of the Stochastic Empirical Loading and Dilution Model (SELDM).
Rights
This software is a product of the U.S. Geological Survey, which is part of the U.S. Government. This software is freely distributed. There is no fee to download and (or) use this software.
As a work of the United States Government, this USGS product is in the public domain (https://www.usa.gov/government-works) within the United States. You can copy, modify, distribute, and perform the work, even for commercial purposes, all without asking permission. Additionally, USGS waives copyright and related rights in the work worldwide through CC0 1.0 Universal Public Domain Dedication (https://creativecommons.org/publicdomain/zero/1.0/ ).
This software has been approved for release by the U.S. Geological Survey (USGS). Although the software has been subjected to rigorous review, the USGS reserves the right to update the software as needed pursuant to further analysis and review. No warranty, expressed or implied, is made by the USGS or the U.S. Government as to the functionality of the software and related material nor shall the fact of release constitute any such warranty. Furthermore, the software is released on condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from its authorized or unauthorized use.
Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.