Assessing Potential Effects of Highway Runoff on Receiving-Water Quality in Oregon using Surrogate Water-Quality Data Sets John Risley, Gregory E. Granato,

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Presentation transcript:

Assessing Potential Effects of Highway Runoff on Receiving-Water Quality in Oregon using Surrogate Water-Quality Data Sets John Risley, Gregory E. Granato, and William Fletcher Eugene, Oregon April 22, 2015

USGS – ODOT Study In 2012 the U.S. Geological Survey Oregon Water Science Center and the Oregon Department of Transportation began a jointly funded study assessing the potential effects of highway runoff on receiving-water quality at selected sites in Oregon using the Stochastic Empirical Loading and Dilution Model (SELDM)

USGS - ODOT Study Report Risley, J.C., and Granato, G.E., 2014, Assessing potential effects of highway runoff on receiving-water quality at selected sites in Oregon with the Stochastic Empirical Loading and Dilution Model (SELDM): U.S. Geological Survey Scientific Investigations Report 2014–5099, 74 p.

USGS – ODOT Study Objectives: 1. Refine precipitation/runoff data inputs for Oregon SELDM applications. 2. Evaluate impacts of storm-water runoff for six highway sites. 3. Compute upstream basin and highway water-quality statistics and transport curves for Oregon SELDM applications. 4. Provide a report describing Oregon SELDM applications.

SELDM Overview SELDM estimates combinations of contaminant loads/concentrations from a highway and an upstream basin using Monte Carlo methods. Created by Greg Granato--USGS Massachusetts Water Science Center Funded by Federal Highway Administration

SELDM Overview

SELDM Components 1. Storm-event precipitation 2. Upstream basin streamflow 3. Highway storm runoff 4. Upstream basin and highway runoff water quality 5. Optional – Lake basin analysis 6. Optional – Evaluation of BMPs 7. SELDM model output files

Best Management Practices 1.Flow volume reduction option --Infiltration, evaporation, and absorption 2.Hydrograph extension option --Allows better downstream dilution 3.Water-quality modification option --Settling and filtration

Water-Quality Treatment: TSS Reduction

Six Study Sites

Highway catchment drainage areas: 3.85 to acres Upstream basin drainage areas: 0.16 to 6.56 square miles Two sites: Urbanized Four remaining sites: Forest or agricultural with < 5% imperviousness

Modeling Water-Quality Constituents Chemical concentrations from the highway catchment and upstream basin can be defined in SELDM as: 1. Random Mean, SD, and skew 2. A transport curve A function of streamflow 3. Dependent on another constituent Example: Sediment

Constituents of Interest CadmiumLead ChlorideNickel ChromiumPhosphorus CopperZinc Iron

Oregon Department of Environmental Quality Criteria

Constituents of Interest Concentrations and loads were simulated for the six study site highway catchments and upstream basins using surrogate water-quality data.

Water-Quality Surrogate Data Highway Catchments: Measured QW data from similar U.S. highway sites with similar climate, road width, catchment size, and average daily traffic (ADT) load. Highway-Runoff Database (HRDB). Data from California, Massachusetts, Pennsylvania, Florida, and Wisconsin sites.

Water-Quality Surrogate Data Upstream Basins: Measured water ‑ quality data from nearby urban and rural USGS streamflow sites within the same ecoregion. Random statistics used for non-urban Willamette ecoregion sites. Transport curves created for urban sites. Random statistics and transport curves used for southern Wall Creek site.

Tyron Creek at Interstate 5 Upstream basin Basin area (square miles)0.63 Percent forest11.2 Percent urban99.8 Impervious fraction0.48 Highway catchment Area (acres)11.8 Impervious fraction0.99 Total lanes10 Average daily traffic21,400 -

Tyron Creek at Interstate 5

Flows at Tyron Creek at Interstate 5

Copper Concentrations at Tyron Creek at Interstate 5

Copper Loads at Tyron Creek at Interstate 5

Take Home Message Analyses show that potential effects of highway runoff on receiving-water quality downstream of the highway depends on: (1) The ratio of the upstream and highway catchment drainage areas (dilution). (2) The quality of the water upstream of the highway.

Take Home Message These analyses also show that the probability of exceeding a water-quality criterion may depend on the input statistics used, thus careful selection of representative values is important. If time and funding are available-- measuring streamflow and water-quality data at a site of interest is preferable to surrogate data.

Questions?