Effects of stormwater runoff from selected bridge decks on conditions of water, sediment, and biological quality in receiving waters in South Carolina, 2013 to 2018

Journey, Celeste A.; Petkewich, Matthew D.; Conlon, Kevin J.; Caldwell, Andral W.; Clark, Jimmy M.; Riley, Jeffrey W.; Bradley, Paul M.

doi:10.3133/sir20205046

Scientific Investigations Report

2020

DOI: 10.3133/sir20205046

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Effects of stormwater runoff from selected bridge decks on conditions of water, sediment, and biological quality in receiving waters in South Carolina, 2013 to 2018

Celeste A. Journey¹,

Matthew D. Petkewich²,

Kevin J. Conlon³

et al.

Abstract: Cover. A, U.S. Geological Survey hydrologist collecting a storm sample at the downstream location on Lynches River near Effingham, South Carolina, using a tag line and inflatable boat; and, B, the downstream bridge span on Lynches River near Effingham, South Carolina, with storm runoff entering the river through downspouts, 2014.

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2023

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Cited by 1 publication

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Development of the North Carolina stormwater-treatment decision-support system by using the Stochastic Empirical Loading and Dilution Model (SELDM)

Granato,

Stillwell,

Weaver

et al. 2023

Scientific Investigations Report

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The Federal Highway Administration and State departments of transportation nationwide need an efficient method to assess potential adverse effects of highway stormwater runoff on receiving waters to optimize stormwater-treatment decisions. To this end, the U.S. Geological Survey, in cooperation with the Federal Highway Administration and the North Carolina Department of Transportation (NCDOT), developed a decision-support software tool based on a statewide version of the Stochastic Empirical Loading and Dilution Model (SELDM). This decision-support tool is designed to identify potential adverse effects of highway runoff by using a criterion based on a measurable change in water quality from a surrogate pollutant. The NCDOT worked with the North Carolina Department of Environmental Quality to select a 25-percent change in suspended sediment concentration as the decision-rule criterion for identifying measurable downstream water-quality change; this selection was based on available data and widely accepted stormwater monitoring uncertainties. Development of the statewide tool and its application to the Piedmont ecoregion are described in this report. Because SELDM can be applied to build a similar decision-support tool in any State, this report describes practice-ready methods that other State departments of transportation and municipal permittees can use to streamline environmental permitting and project delivery while protecting the environment.Hydraulic design engineers can use this decision-support tool to establish stormwater-treatment goals for highway construction or improvement projects without having to learn SELDM or interpret its statistical output. The tool is a spreadsheet that determines if a selected highway segment can directly discharge highway runoff, if the highway segment can discharge runoff following treatment using a basic vegetated conveyance best management practice (BMP), or if treatment using an advanced BMP is needed to minimize

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Development of the North Carolina stormwater-treatment decision-support system by using the Stochastic Empirical Loading and Dilution Model (SELDM)

Granato,

Stillwell,

Weaver

et al. 2023

Scientific Investigations Report

View full text Add to dashboard Cite

show abstract

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Effects of stormwater runoff from selected bridge decks on conditions of water, sediment, and biological quality in receiving waters in South Carolina, 2013 to 2018

Cited by 1 publication

References 30 publications

Development of the North Carolina stormwater-treatment decision-support system by using the Stochastic Empirical Loading and Dilution Model (SELDM)

Development of the North Carolina stormwater-treatment decision-support system by using the Stochastic Empirical Loading and Dilution Model (SELDM)

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