Gregory E. Granato

Deicing chemicals as source of constituents of highway runoff

The dissolved major and trace constituents of deicing chemicals as a source of constituents in highway runoff must be quantified for interpretive studies of highway runoff and its effects on surface water and groundwater. Dissolved constituents of the deicing chemicals—sodium chloride, calcium chloride, and premix (a mixture of sodium and calcium chloride)—were determined by analysis of salt solutions created in the laboratory and are presented as mass ratios to chloride. Deicing chemical samples studied are about 98 and 97 percent pure sodium chloride and calcium chloride, respectively; however, each has a distinct major and trace ion constituent signature. The greatest impurity in sodium chloride road salt samples was sulfate, followed by calcium, potassium, bromide, vanadium, magnesium, fluoride, and other constituents with a ratio to chloride of less than 0.0001 by mass. The greatest impurity in the calcium chloride road salt samples was sodium, followed by potassium, sulfate, bromide, silica, fluorid...

Automated ground-water monitoring with robowell-Case studies and potential applications

Robowell is an automated system and method for monitoring ground-water quality. Robowell meets accepted manual- sampling protocols without high labor and laboratory costs. Robowell periodically monitors and records water-quality properties and constituents in ground water by pumping a well or multilevel sampler until one or more purge criteria have been met. A record of frequent water-quality measurements from a monitoring site can indicate changes in ground-water quality and can provide a context for the interpretation of laboratory data from discrete samples. Robowell also can communicate data and system performance through a remote communication link. Remote access to ground-water data enables the user to monitor conditions and optimize manual sampling efforts. Six Robowell prototypes have successfully monitored ground-water quality during all four seasons of the year under different hydrogeologic conditions, well designs, and geochemical environments. The U.S. Geological Survey is seeking partners for research with robust and economical water-quality monitoring instruments designed to measure contaminants of concern in conjunction with the application and commercialization of the Robowell technology. Project publications and information about technology transfer opportunities are available on the Internet at URL http://ma.water.usgs.gov/automon/

Estimating Total Maximum Daily Loads with the Stochastic Empirical Loading and Dilution Model

The Massachusetts Department of Transportation (DOT) and the Rhode Island DOT are assessing and addressing roadway contributions to total maximum daily loads (TMDLs). Example analyses for total nitrogen, total phosphorus, suspended sediment, and total zinc in highway runoff were done by the U.S. Geological Survey in cooperation with FHWA to simulate long-term annual loads for TMDL analyses with the stochastic empirical loading and dilution model known as SELDM. Concentration statistics from 19 highway runoff monitoring sites in Massachusetts were used with precipitation statistics from 11 long-term monitoring sites to simulate long-term pavement yields (loads per unit area). Highway sites were stratified by traffic volume or surrounding land use to calculate concentration statistics for rural roads, low-volume highways, high-volume highways, and ultraurban highways. The median of the event mean concentration statistics in each traffic volume category was used to simulate annual yields from pavement for a 29- or 30-year period. Long-term average yields for total nitrogen, phosphorus, and zinc from rural roads are lower than yields from the other categories, but yields of sediment are higher than for the low-volume highways. The average yields of the selected water quality constituents from high-volume highways are 1.35 to 2.52 times the associated yields from low-volume highways. The average yields of the selected constituents from ultraurban highways are 1.52 to 3.46 times the associated yields from high-volume highways. Example simulations indicate that both concentration reduction and flow reduction by structural best management practices are crucial for reducing runoff yields.

Stochastic Empirical Loading and Dilution Model for Analysis of Flows, Concentrations, and Loads of Highway Runoff Constituents

In cooperation with FHWA, the U.S. Geological Survey developed the stochastic empirical loading and dilution model (SELDM) to supersede the 1990 FHWA runoff quality model. The SELDM tool is designed to transform disparate and complex scientific data into meaningful information about the adverse risks of runoff on receiving waters, the potential need for mitigation measures, and the potential effectiveness of such measures for reducing such risks. The SELDM tool is easy to use because much of the information and data needed to run it are embedded in the model and obtained by defining the site location and five simple basin properties. Information and data from thousands of sites across the country were compiled to facilitate the use of the SELDM tool. A case study illustrates how to use the SELDM tool for conducting the types of sensitivity analyses needed to properly assess water quality risks. For example, the use of deterministic values to model upstream stormflows instead of representative variations in prestorm flow and runoff may substantially overestimate the proportion of highway runoff in downstream flows. Also, the risks for total phosphorus excursions are substantially affected by the selected criteria and the modeling methods used. For example, if a single deterministic concentration is used rather than a stochastic population of values to model upstream concentrations, then the percentage of water quality excursions in the downstream receiving waters may depend entirely on the selected upstream concentration.

Assessing roadway contributions to stormwater flows, concentrations, and loads with the StreamStats application

The Oregon Department of Transportation (ODOT) and other state departments of transportation need quantitative information about the percentages of different land cover categories above any given stream crossing in the state to assess and address roadway contributions to water-quality impairments and resulting total maximum daily loads. The U.S. Geological Survey, in cooperation with ODOT and the FHWA, added roadway and land cover information to the online StreamStats application to facilitate analysis of stormwater runoff contributions from different land covers. Analysis of 25 delineated basins with drainage areas of about 100 mi2 indicates the diversity of land covers in the Willamette Valley, Oregon. On average, agricultural, developed, and undeveloped land covers comprise 15%, 2.3%, and 82% of these basin areas. On average, these basins contained about 10 mi of state highways and 222 mi of non-state roads. The Stochastic Empirical Loading and Dilution Model was used with available water-quality data to simulate long-term yields of total phosphorus from highways, non-highway roadways, and agricultural, developed, and undeveloped areas. These yields were applied to land cover areas obtained from StreamStats for the Willamette River above Wilsonville, Oregon. This analysis indicated that highway yields were larger than yields from other land covers because highway runoff concentrations were higher than other land covers and the highway is fully impervious. However, the total highway area was a fraction of the other land covers. Accordingly, highway runoff mitigation measures can be effective for managing water quality locally, they may have limited effect on achieving basin-wide stormwater reduction goals.

Estimating risks for water-quality exceedances of total-copper from highway and urban runoff under predevelopment and current conditions with the Stochastic Empirical Loading and Dilution Model (SELDM)

The Stochastic Empirical Loading and Dilution Model (SELDM) was used to demonstrate methods for estimating risks for water-quality exceedances of event-mean concentrations (EMCs) of total-copper. Monte Carlo methods were used to simulate stormflow, total-hardness, suspended-sediment, and total-copper EMCs as stochastic variables. These simulations were done for the Charles River basin upstream of Interstate 495 in Bellingham, Massachusetts. The hydrology and water quality of this site were simulated with SELDM by using data from nearby, hydrologically similar sites. Three simulations were done to assess the potential effects of the highway on receiving-water quality with and without highway-runoff treatment by a structural best-management practice (BMP). In the low-development scenario, total copper in the receiving stream was simulated by using a sediment transport curve, sediment chemistry, and sedimentwater partition coefficients. In this scenario, neither the highway runoff nor the BMP effluent caused concentration exceedances in the receiving stream that exceed the once in three-year threshold (about 0.54 percent). In the second scenario, without the highway, runoff from the large urban areas in the basin caused exceedances in the receiving stream in 2.24 percent of runoff events. In the third scenario, which included the effects of the urban runoff, neither the highway runoff nor the BMP effluent increased the percentage of exceedances in the receiving stream. Comparison of the simulated geometric mean EMCs with data collected at a downstream monitoring site indicates that these simulated values are within the 95-percent confidence interval of the geometric mean of the measured EMCs. INTRODUCTION Decisionmakers have become increasingly aware of the importance of considering random variation in the quantity and quality of highway runoff, urban runoff, and upstream stormflows for estimating the potential adverse effects of runoff on receiving waters (U.S. Environmental Protection Agency, 1985, 1998, 2002, 2014; Novotny, 2004; Langseth and Brown, 2011). The Stochastic Empirical Loading and Dilution Model (SELDM) uses Monte Carlo methods to generate stormflows, concentrations, and loads from a site of interest and an upstream basin (Granato, 2013a). SELDM is a lumped-parameter mass-balance model that simulates the quality and quantity of runoff from a site of interest and the quality and quantity of total stormflow from an upstream basin. As such, SELDM provides risk-based information needed to assess the

Effects of Water-Management Strategies on Water Resources in the Pawcatuck River Basin, Southwestern Rhode Island and Southeastern Connecticut

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