Distinct influence of filter strips on acute and chronic pesticide aquatic environmental exposure assessments across U.S. EPA scenarios.

Vegetative filter strips (VFS) are proposed for protection of receiving water bodies and aquatic organisms from pesticides in runoff, but there is debate regarding the efficiency and filter size requirements. This debate is largely due to the belief that no quantitative methodology exists for predicting runoff buffer efficiency when conducting acute and/or chronic environmental exposure assessments. Previous research has proposed a modeling approach that links the U.S. Environmental Protection Agency's (EPA's) PRZM/EXAMS with a well-tested process-based model for VFS (VFSMOD). In this research, we apply the modeling framework to determine (1) the most important input factors for quantifying mass reductions of pesticides by VFS in aquatic exposure assessments relative to three distinct U.S. EPA scenarios encompassing a wide range of conditions; (2) the expected range in percent reductions in acute and chronic estimated environmental concentrations (EECs); and (3) the differential influence of VFS when conducting acute versus chronic exposure assessments. This research utilized three, 30-yr U.S. EPA scenarios: Illinois corn, California tomato, and Oregon wheat. A global sensitivity analysis (GSA) method identified the most important input factors based on discrete uniform probability distributions for five input factors: VFS length (VL), organic-carbon sorption coefficient (K(oc)), half-lives in both water and soil phases, and application timing. For percent reductions in acute and chronic EECs, VL and application timing were consistently the most important input factors independent of EPA scenario. The potential ranges in acute and chronic EECs varied as a function of EPA scenario and application timing. Reductions in acute EECs were typically less than percent reductions in chronic EECs because acute exposure was driven primarily by large individual rainfall and runon events. Importantly, generic specification of VFS design characteristics equal across scenarios should be avoided. The revised pesticide assessment modeling framework offers the ability to elucidate the complex and non-linear relationships that can inform targeted VFS design specifications.

Revised framework for pesticide aquatic environmental exposure assessment that accounts for vegetative filter strips.

For pesticides that do not pass higher-level environmental exposure assessments, vegetated filter strips (VFS) are often mandated for use of the compound. However, VFS physiographic characteristics (i.e., width) are not currently specified based on predictive modeling of VFS performance. This has been due to the lack of predictive tools that can explain the wide range of field-reported efficacies. This research hypothesizes that mechanistic modeling of VFS runoff and sediment trapping, integrated with an empirical, regression-based pesticide trapping equation and the U.S. Environmental Protection Agency's (EPA) exposure framework, is able to effectively derive these VFS characteristics. To test this hypothesis, a well-tested process-based model for VFS (VFSMOD) was coupled with the pesticide trapping equation and integrated with EPA's PRZM/EXAMS exposure package. The revised framework was applied to a prescribed U.S. EPA assessment scenario for four hypothetical pesticides: more mobile (i.e., organic carbon (OC) sorption coefficients, K(oc), of 100 L/kg OC) and less mobile (2000 L/kg OC) pesticides that are fast degrading or stable (i.e., 10 or 10,000 d aquatic dissipation half-lives). A nonlinear and complex relationship was observed between pesticide reduction, VFS length, and rainfall plus runon event size. The impact of VFS on environmental exposure concentrations (EECs) was found to be dependent on the pesticide sorption and dissipation half-life and whether calculating an acute or chronic EEC. While acute and chronic EECs were equivalent for stable pesticides, for fast degrading pesticides the acute EEC depended on specific loading events. Therefore, while VFS may reduce the cumulative pesticide loading, a corresponding reduction in the acute EEC may not always be observed. Such results emphasize the need to incorporate physically based modeling of VFS reductions for pesticides that do not pass the current U.S. EPA exposure assessment framework.

Parameter importance and uncertainty in predicting runoff pesticide reduction with filter strips.

Vegetative filter strips (VFS) are an environmental management tool used to reduce sediment and pesticide transport from surface runoff. Numerical models of VFS such as the Vegetative Filter Strip Modeling System (VFSMOD-W) are capable of predicting runoff, sediment, and pesticide reduction and can be useful tools to understand the effectiveness of VFS and environmental conditions under which they may be ineffective. However, as part of the modeling process, it is critical to identify input factor importance and quantify uncertainty in predicted runoff, sediment, and pesticide reductions. This research used state-of-the-art global sensitivity and uncertainty analysis tools, a screening method (Morris) and a variance-based method (extended Fourier Analysis Sensitivity Test), to evaluate VFSMOD-W under a range of field scenarios. The three VFS studies analyzed were conducted on silty clay loam and silt loam soils under uniform, sheet flow conditions and included atrazine, chlorpyrifos, cyanazine, metolachlor, pendimethalin, and terbuthylazine data. Saturated hydraulic conductivity was the most important input factor for predicting infiltration and runoff, explaining >75% of the total output variance for studies with smaller hydraulic loading rates ( approximately 100-150 mm equivalent depths) and approximately 50% for the higher loading rate ( approximately 280-mm equivalent depth). Important input factors for predicting sedimentation included hydraulic conductivity, average particle size, and the filter's Manning's roughness coefficient. Input factor importance for pesticide trapping was controlled by infiltration and, therefore, hydraulic conductivity. Global uncertainty analyses suggested a wide range of reductions for runoff (95% confidence intervals of 7-93%), sediment (84-100%), and pesticide (43-100%) . Pesticide trapping probability distributions fell between runoff and sediment reduction distributions as a function of the pesticides' sorption. Seemingly equivalent VFS exhibited unique and complex trapping responses dependent on the hydraulic and sediment loading rates, and therefore, process-based modeling of VFS is required.

Influence of rainfall distribution on simulations of atrazine, metolachlor, and isoxaflutole/metabolite transport in subsurface drained fields.

This research investigated the impact of modeling atrazine, metolachlor, and isoxaflutole/metabolite transport in artificially subsurface drained sites with temporally discrete rainfall data. Differences in considering rainfall distribution are unknown in regard to estimating agrochemical fluxes in the subsurface. The Root Zone Water Quality Model (RZWQM) simulated pesticide fate and transport at three subsurface drained sites: metolachlor/atrazine field experiment in Baton Rouge, LA (1987), and two isoxaflutole/metabolite field experiments in Allen County and Owen County, Indiana (2000). The modeling assumed linear, equilibrium sorption based on average reported physicochemical and environmental fate properties. Assumed rainfall intensity and duration influenced transport by runoff more than transport by subsurface drainage. As the importance of macropore flow increased, the necessity for using temporally discrete rainfall data became more critical. Long-term simulations indicated no significant difference between average or upper percentile (i.e., <2% difference in percent loss as a function of mass applied) atrazine, metolachlor, or isoxaflutole/metabolite loss through subsurface drainage among the three different rainfall assumptions. It was necessary (i.e., within 7% of predicted loss) to use hourly or average duration storm events as opposed to daily rainfall data for total (i.e., runoff and subsurface drainage) pesticide loss over the long term.

Uncalibrated modelling of conservative tracer and pesticide leaching to groundwater: comparison of potential Tier II exposure assessment models.

The Root Zone Water Quality Model (RZWQM) and Pesticide Root Zone Model (PRZM) are currently being considered by the Office of Pesticide Programs (OPP) in the United States Environmental Protection Agency (US EPA) for Tier II screening of pesticide leaching to groundwater (November 2005). The objective of the present research was to compare RZWQM and PRZM based on observed conservative tracer and pesticide pore water and soil concentrations collected in two unique groundwater leaching studies in North Carolina and Georgia. These two sites had been used previously by the Federal Insecticide, Fungicide and Rodenticide Act (FIFRA) Environmental Model Validation Task Force (EMVTF) in the validation of PRZM. As in the FIFRA EMVTF PRZM validation, 'cold' modelling using input parameters based on EPA guidelines/databases and 'site-specific' modelling using field-measured soil and hydraulic parameters were performed with a recently released version of RZWQM called RZWQM-NAWQA (National Water Quality Assessment). Model calibration was not performed for either the 'cold' or 'site-specific' modelling. The models were compared based on predicted pore water and soil concentrations of bromide and pesticides throughout the soil profile. Both models tended to predict faster movement through the soil profile than observed. Based on a quantitative normalised objective function (NOF), RZWQM-NAWQA generally outperformed or was equivalent to PRZM in simulating pore water and soil concentrations. Both models were more successful in predicting soil concentrations (i.e. NOF < 1.0 for site-specific data, which satisfies site-specific applicability) than they were at predicting pore water concentrations.

Interrelationship of macropores and subsurface drainage for conservative tracer and pesticide transport.

Macropore flow results in the rapid movement of pesticides to subsurface drains, which may be caused in part by a small portion of macropores directly connected to drains. However, current models fail to account for this direct connection. This research investigated the interrelationship between macropore flow and subsurface drainage on conservative solute and pesticide transport using the Root Zone Water Quality Model (RZWQM). Potassium bromide tracer and isoxaflutole, the active ingredient in BALANCE herbicide [(5-cyclopropyl-4-isoxazolyl) [2(methylsulfonyl)-4-(trifluoromethyl)phenyl] methanone], with average half-life of 1.7 d were applied to a 30.4-ha Indiana corn (Zea mays L.) field. Water flow and chemical concentrations emanating from the drains were measured from two samplers. Model predictions of drain flow after minimal calibration reasonably matched observations (slope = 1.03, intercept = 0.01, and R(2) = 0.75). Without direct hydraulic connection of macropores to drains, RZWQM under predicted bromide and isoxaflutole concentration during the first measured peak after application (e.g., observed isoxaflutole concentration was between 1.2 and 1.4 mug L(-1), RZWQM concentration was 0.1 mug L(-1)). This research modified RZWQM to include an express fraction relating the percentage of macropores in direct hydraulic connection to drains. The modified model captured the first measured peak in bromide and isoxaflutole concentrations using an express fraction of 2% (e.g., simulated isoxaflutole concentration increased to 1.7 mug L(-1)). The RZWQM modified to include a macropore express fraction more accurately simulates chemical movement through macropores to subsurface drains. An express fraction is required to match peak concentrations in subsurface drains shortly after chemical applications.