Publications by authors named "Robert J Gilliom"

Trends in pesticide concentrations in 38 major rivers of the United States were evaluated in relation to use trends for 11 commonly occurring pesticide compounds. Pesticides monitored in water were analyzed for trends in concentration in three overlapping periods, 1992-2001, 1997-2006, and 2001-2010 to facilitate comparisons among sites with variable sample distributions over time and among pesticides with changes in use during different periods and durations. Concentration trends were analyzed using the SEAWAVE-Q model, which incorporates intra-annual variability in concentration and measures of long-term, mid-term, and short-term streamflow variability.

View Article and Find Full Text PDF

Accurately quantifying nitrate (NO3-) loading from the Mississippi River is important for predicting summer hypoxia in the Gulf of Mexico and targeting nutrient reduction within the basin. Loads have historically been modeled with regression-based techniques, but recent advances with high frequency NO3- sensors allowed us to evaluate model performance relative to measured loads in the lower Mississippi River. Patterns in NO3- concentrations and loads were observed at daily to annual time steps, with considerable variability in concentration-discharge relationships over the two year study.

View Article and Find Full Text PDF

During the 20 years from 1992 to 2011, pesticides were found at concentrations that exceeded aquatic-life benchmarks in many rivers and streams that drain agricultural, urban, and mixed-land use watersheds. Overall, the proportions of assessed streams with one or more pesticides that exceeded an aquatic-life benchmark were very similar between the two decades for agricultural (69% during 1992-2001 compared to 61% during 2002-2011) and mixed-land-use streams (45% compared to 46%). Urban streams, in contrast, increased from 53% during 1992-2011 to 90% during 2002-2011, largely because of fipronil and dichlorvos.

View Article and Find Full Text PDF

The national occurrence of 83 pesticide compounds in groundwater of the United States and decadal-scale changes in concentrations for 35 compounds were assessed for the 20-year period from 1993-2011. Samples were collected from 1271 wells in 58 nationally distributed well networks. Networks consisted of shallow (mostly monitoring) wells in agricultural and urban land-use areas and deeper (mostly domestic and public supply) wells in major aquifers in mixed land-use areas.

View Article and Find Full Text PDF

Watershed Regressions for Pesticides for multiple pesticides (WARP-MP) are statistical models developed to predict concentration statistics for a wide range of pesticides in unmonitored streams. The WARP-MP models use the national atrazine WARP models in conjunction with an adjustment factor for each additional pesticide. The WARP-MP models perform best for pesticides with application timing and methods similar to those used with atrazine.

View Article and Find Full Text PDF

Relationships between sediment toxicity and sediment chemistry were evaluated for 98 samples collected from seven metropolitan study areas across the United States. Sediment-toxicity tests were conducted with the amphipod Hyalella azteca (28 day exposures) and with the midge Chironomus dilutus (10 day exposures). Overall, 33 % of the samples were toxic to amphipods and 12 % of the samples were toxic to midge based on comparisons with reference conditions within each study area.

View Article and Find Full Text PDF

Organic contaminants and trace elements were measured in bed sediments collected from streams in seven metropolitan study areas across the United States to assess concentrations in relation to urbanization. Polycyclic aromatic hydrocarbons, polychlorinated biphenyls, organochlorine pesticides, the pyrethroid insecticide bifenthrin, and several trace elements were significantly related to urbanization across study areas. Most contaminants (except bifenthrin, chromium, nickel) were significantly related to the total organic carbon (TOC) content of the sediments.

View Article and Find Full Text PDF

A nationally consistent approach was used to assess the occurrence and potential sources of pyrethroid insecticides in stream bed sediments from seven metropolitan areas across the United States. One or more pyrethroids were detected in almost half of the samples, with bifenthrin detected the most frequently (41%) and in each metropolitan area. Cyhalothrin, cypermethrin, permethrin, and resmethrin were detected much less frequently.

View Article and Find Full Text PDF

Tobit regression models were developed to predict the summed concentration of atrazine [6-chloro--ethyl--(1-methylethyl)-1,3,5-triazine-2,4-diamine] and its degradate deethylatrazine [6-chloro--(1-methylethyl)-1,3,5,-triazine-2,4-diamine] (DEA) in shallow groundwater underlying agricultural settings across the conterminous United States. The models were developed from atrazine and DEA concentrations in samples from 1298 wells and explanatory variables that represent the source of atrazine and various aspects of the transport and fate of atrazine and DEA in the subsurface. One advantage of these newly developed models over previous national regression models is that they predict concentrations (rather than detection frequency), which can be compared with water quality benchmarks.

View Article and Find Full Text PDF

Trends in the concentrations and agricultural use of four herbicides (atrazine, acetochlor, metolachlor, and alachlor) were evaluated for major rivers of the Corn Belt for two partially overlapping time periods: 1996-2002 and 2000-2006. Trends were analyzed for 11 sites on the mainstems and selected tributaries in the Ohio, Upper Mississippi, and Missouri River Basins. Concentration trends were determined using a parametric regression model designed for analyzing seasonal variability, flow-related variability, and trends in pesticide concentrations (SEAWAVE-Q).

View Article and Find Full Text PDF

Mixtures of organochlorine compounds have the potential for additive or interactive toxicity to organisms exposed in the stream. This study uses a variety of methods to identify mixtures and a modified concentration-addition approach to estimate their potential toxicity at 845 stream sites across the United States sampled between 1992 and 2001 for organochlorine pesticides and polychlorinated biphenyls (PCBs) in bed sediment. Principal-component (PC) analysis identified five PCs that account for 77% of the total variance in 14 organochlorine compounds in the original dataset.

View Article and Find Full Text PDF

Empirical regression models were developed for estimating concentrations of dieldrin, total chlordane, and total DDT in whole fish from U.S. streams.

View Article and Find Full Text PDF

Results of publised pesticide mixure toxicity experiments conducted with aquatic organisms were compiled and evaluated to assess the accuracy of predictive mixture models. Three types of models were evaluated: Concentration addition (CA), independent action (IA), and simple interaction (SI). The CA model was the most often tested (207 experiments), followed by SI (59) and IA (37).

View Article and Find Full Text PDF

To evaluate the relative toxicity and the occurrence patterns of pesticide mixtures in streams draining agricultural watersheds, a 3-step approach was used. First, a landscape of interest was identified, defined, and isolated. Second, the relative toxicity of mixtures, on the basis of pesticide toxicity index scores, was compared with the relative toxicity of the highest individual pesticide, on the basis of highest toxicity quotient values.

View Article and Find Full Text PDF

A PHP Error was encountered

Severity: Notice

Message: fwrite(): Write of 34 bytes failed with errno=28 No space left on device

Filename: drivers/Session_files_driver.php

Line Number: 272

Backtrace:

A PHP Error was encountered

Severity: Warning

Message: session_write_close(): Failed to write session data using user defined save handler. (session.save_path: /var/lib/php/sessions)

Filename: Unknown

Line Number: 0

Backtrace: