July 2010 EMPM Agenda and Abstracts 

PRESENTER Time TOPIC Duration 

Peck/Baris 9:00 am Welcome and Introduction 5 minutes 

Michael Barrett, U.S. EPA 

Ian Kennedy, PMRA 

9:05 am A Look at Prospective Ground-Water Monitoring 

Studies and their Utility for Developing Leaching 

Models 

35 minutes

Marty Williams, P.E. 

Waterborne Environmental 

Inc. 

9:40 am Screening Approaches for Predicting Pesticide 

Concentrations in Groundwater 

35 minutes

10:15 am Break 10 minutes

David Valcore, 

Valcore Consulting 

Harold Thistle, 

USDA 

10:25 am Mechanistic Ground Spray Boom Drift Model 

Development 

35 minutes

Nathan Snyder 

Waterborne Environmental 

Inc. 

11:00 am Using Modern Watershed and Cropping Data as a 

Basis for Estimating Percentage Crop Treatment 

35 minutes

Jack Barbash and Frank 

Voss, USGS 

11:35 am Design and Testing of a Process-Based Groundwater 

Vulnerability Assessment (P-GWAVA) System for 

Predicting the Concentrations of Agrichemicals in 

Ground Water Across the Conterminous United 

States Using Data from the National Water-Quality 

Assessment (NAWQA) Program 

35 minutes

12:10 pm Lunch 80 minutes

Michael Winchell, 

Stone Environmental 

Russell Jones, 

Bayer Cropscience 

1:30 pm Comparison of Models for Estimating the Removal 

of Pesticides by Vegetative Buffer Strips 

35 minutes

Marty Williams, P.E. 

Waterborne Environmental 

Inc. 

2:05 pm Advances in Modeling Urban/Residential Pesticide 

Runoff 

35 minutes

2:40 pm Break 5 minutes 

Nick Poletika, 

Dow Agrosciences 

2:45 pm Spray Drift Exposure Refinements for Salmonid 

Off-Channel Habitat 

35 minutes

Mark Velleux, 

HydroQual, Inc 

3:20 pm Spatially-Distributed Watershed Model for 

Chemical Exposure Assessment: Case Study of 

Antimicrobial Copper Uses in Urbanized Areas 

35 minutes

Peck/Baris 3:55 PM Wrap-up, Next Meeting 5 minutes 

Peck/Baris 4:00 PM Adjournment 
A Look at Prospective Ground-Water Monitoring Studies and their Utility for 

Developing Pesticide Leaching Models 

Ian Kennedy1

, James Wolf2, and Michael Barrett2, 1 PMRA, Ottawa, Canada 

2 USEPA, Washington, DC 

The datasets from prospective groundwater (PGW) monitoring studies, required by EPA 

for registration of pesticides thought likely to leach to groundwater are being used by 

EPA and Health Canada's Pest Management Regulatory Agency (PMRA) to evaluate and 

develop ground-water exposure models. PMRA and OPP's Environmental Fate and 

Effects Division (EFED) examined and modeled a number of completed PGW study 

reports for the utility of the datasets for use in testing leaching models. A number of 

factors have been identified which commonly limit the use of these data, including: 

 Uncertainties in pesticide and degradate fate properties. 

 Data censoring, or reporting/detection limits which are set too high to accurately 

establish breakthrough patterns with depth for the pesticide or degradates. 

 The conducting of studies under conditions where precipitation or irrigation for 

long periods were insufficient to promote ground water recharge - this is often 

associated with a high rate of soil-pore water sample collection failure. 

 Temporal and spatial variability in the soil matrix is often high and the sampling 

frequency and sampling locations may be insufficient to track water and solute 

movement. 

 Study was ended before a complete breakthrough curve was observed. 

Screening Approaches for Predicting Pesticide Concentrations in Groundwater 

Dazhi Mao, Marty Williams, Mark Cheplick, Amy Ritter, and Robert Morris 

Waterborne Environmental Inc., Leesburg, VA 

The presentation compares three modeling approaches for estimating pesticide exposure 

in groundwater: SCIGROW, an empirical model derived from the results of controlled, 

field-scale groundwater monitoring studies; 2) PRZM-GW, an adaption of the Pesticide 

Root Zone Model (PRZM) to estimate pesticide concentrations in shallow ground water; 

and PRZM-ADAM, the linkage of PRZM to an aquifer dispersion and advection model 

based on Darcy's law to estimate concentrations in ground water. The methodology and 

the ability of all three approaches to reproduce the results of prospective groundwater 

monitoring studies are compared. 

Mechanistic Ground Spray Boom Drift Model Development 

David L. Valcore1

, Harold W. Thistle2, P. C. H. Miller3, and Clare Butler-Ellis3

1 Valcore Consulting 

2 USDA-USFS 

3 Silsoe Applic. Unit, The Arable Group, UK

A number of high quality spray drift datasets exist internationally that have provided 

empirical drift deposition curves for spray drift risk exposure assessments to sensitive 

areas. Existing agricultural ground spray drift deposition models are empirical. There is a 
need for more accurate drift predictions to greater distances than the typical 30-100 

meters or even the 300 meter distance available from the EPA AgDRIFT model. A 

multi-phase international effort to develop a robust mechanistic ground boom spray drift 

model is underway to address the need to evaluate mitigation options that modify 

application parameters including spray boom and nozzle type, meteorology and low drift 

technologies. An updated random walk multi-nozzle spray deposition drift model 

developed by Silsoe Spray Application Unit, UK was chosen as the basis of current 

efforts. Initial comparisons of this model with EPA’s accepted Spray Drift Task Force 

data have been made and show that the model can successfully predict ground deposits 

up to 200 meters downwind, and potentially beyond. Preliminary sensitivity analysis of 

the key parameters in the model algorithms will be discussed. A brief summary of 

development status, current insights, research and verification plans will also be 

presented, including benefits expected for drift risk assessments, drift mitigation options, 

and support of EPA’s Drift Reduction Technology program. 

Using Modern Watershed and Cropping Data as a Basis for Estimating Percentage 

Crop Treatment 

Nathan J. Snyder1

, Joshua J. Amos1, Peggy S. Lee1, and Aldos C. Barefoot2

1 Waterborne Environmental Inc. Leesburg, VA 

2 DuPont Crop Protection, Newark, DE

Distributing pesticide use data or determining percent of crop treatment is dependent on 

estimates of cropping information. If an attempt is made to distribute sales or use data to 

a geographic area smaller than the collection resolution (i.e. CRD/county/zipcode data 

distributed to a small watershed), spatially accurate cropping estimates are required. The 

use of modern watershed and cropping information (and a comparison to traditional 

county level data) will be presented through a case study. Examples of improvement to 

the traditional regional PCA values currently being used for drinking water modeling will 

be discussed. Two areas of the USEPA regional PCA methodology will be evaluated 1) 

Regional default PCAs developed from large watersheds (8-digit Hydrologic Unit 

Codes), and 2) concerns with scale and uncertainty of crop distribution within 

watersheds. Regional PCAs were an interim step in moving from national PCAs to PCAs 

developed from actual drinking watersheds. In the 10-years since the 1999 SAP review 

and seven years since the development of regional PCAs, updates to watersheds and crop 

coverages have become available. Concerns with limitations in PCAs for individual 

crops for development of protective residue values for drinking water assessments can be 

addressed through the recently available data. It is appropriate to move beyond an 

interim step and improve drinking water estimates using cropping and pesticide use data 

distributed through PCA adjusted EECs in actual drinking watersheds. 
Design and Testing of a Process-Based Groundwater Vulnerability Assessment (PGWAVA) System for Predicting the Concentrations of Agrichemicals in Ground Water 

Across the Conterminous United States Using Data from the National Water-Quality 

Assessment (NAWQA) Program 

Jack E. Barbash and Frank D. Voss 

U.S. Geological Survey, Tacoma, WA 

Over the past two decades, many tools have been employed to predict the likelihood of 

detecting surface-derived contaminants in ground water. Statistical relations have been 

used at large spatial scales to predict contaminant occurrence from various site-based 

parameters. At such scales, however, process-based simulations of the transport and fate 

of the compounds of interest have been relatively uncommon. This presentation will 

describe an approach that (1) employs a geographic information system to provide 

spatially-structured data input to a process-based vadose-zone model (PRZM or 

RZWQM) for any location in the conterminous United States, (2) simulates the transport 

and fate of pesticides, pesticide transformation products and nitrate to estimate their 

concentrations in the vadose zone beneath each selected location, and (3) compares the 

simulated concentrations with those measured in shallow ground water sampled from 

over 1,900 wells across the Nation between 1992 and 2007 by the U.S. Geological 

Survey’s National Water-Quality Assessment (NAWQA) program. 

Comparison of Models for Estimating the Removal of Pesticides by Vegetative Buffer 

Strips 

Michael Winchell1

, Russell Jones2, and Tammara Estes1

1 Stone Environmental, Montpelier, VT 

2 Bayer CropScience, Stilwell, KS 

Vegetated buffer areas established between agricultural fields and receiving waters have 

long been recommended as a best management practice to reduce the amount of 

sediment, nutrients, and pesticides entering water bodies and recently intensively 

managed vegetated filter strips have been mandated as label requirements for plant 

protection products in both Europe and North America. Also recently, models have been 

developed to predict the amount of active ingredients and their metabolites removed from 

runoff flowing through these strips. This presentation reviews the features of five models 

(APEX, PRZM, REMM, SWAT, and VFSMOD-WQ) which can be used to predict the 

reduction in pesticide loss in runoff passing through a vegetative buffer strip. The 

predictions from four of these models are compared using three common data sets, one 

from Europe and the other two from the United States. The conditions modeled include a 

range of soils properties, slopes, rainfall events, and pesticide sorption characteristics. 

All four models predicted significant reductions of pesticides in the buffer consistent with 

the observed reductions, providing strong support for the use of these models as tools for 

estimating buffer effectiveness. A sensitivity analysis was conducted with the four 

models to determine the effects of input parameter uncertainty on the predictions of 

pesticide reduction in the buffer. 
Advances in Modeling Urban/Residential Pesticide Runoff 

Marty Williams, Amy Ritter, Megan White, and Mark Cheplick 

Waterborne Environmental Inc., Leesburg, VA 

The U.S. Environmental Protection Agency's (USEPA's) Storm Water Management 

Model (SWMM) is widely used for urban water management and water quality analysis. 

The model is limited in its ability to simulate pesticides because of a general lack of 

knowledge of washoff coefficients values for hard surface runoff and the inability to 

specify discrete pesticide applications. USEPA's Pesticide Root Zone Model (PRZM) 

was developed to simulate pesticide runoff and leaching in agricultural environments and 

is limited in its ability to urban drainage features. Recent enhancements have been to both 

models to overcome these deficiencies. Pesticide and water runoff predictions from both 

models are compared. 

Spray Drift Exposure Refinements for Salmonid Off-Channel Habitat 

Nick Poletika1, Rick Reiss2, Steve Cryer1, and Stever Cramer3

1 Dow AgroSciences LLC 

2 Exponent, Inc 

3 Cramer Fish Sciences 

Off-channel stream habitat is viewed by the National Marine Fisheries Service as the 

habitat type in which Pacific Coast threatened/endangered salmonids are most vulnerable 

to adverse impacts from spray drift residues resulting from applications of agricultural 

pesticides. Data describing the water body characteristics of off-channel habitat 

associated with agricultural landscapes were collected and used to conduct refined spray 

drift and aquatic dissipation modeling. Flowing water was found to be a key 

characteristic influencing exposure magnitude and duration in off-channel stream features 

relevant to agricultural settings. Based on advanced technical modeling approaches and 

representative, best available measurement data, time-varying exposure assessments for 

the three main types of important off-channel habitat (side channels, alcoves, and 

backwater pools) were completed for durations consistent with acute toxicity testing. The 

exposure assessments were compared to screening-level exposure predictions assuming 

typical off-channel habitat is represented by shallow static water bodies. 

Spatially-Distributed Watershed Model for Chemical Exposure Assessment: Case 

Study of Antimicrobial Copper Uses in Urbanized Areas 

Mark Velleux, Paul Paquin, Aaron Redman, and Robert Santore 

HydroQual, Inc. 

Copper is used as an antimicrobial agent in building materials such as algae-resistant 

shingles and treated wood. In urbanized areas, copper-containing building materials may 

be present in roofs, wood decks, wood fences, and utility poles installed in densely 

clustered and widely dispersed locations across the landscape. Releases from these 

materials may pose risks to aquatic and terrestrial organisms. The TREX (Twodimensional Runoff Erosion and Export) watershed model was used to simulate spatiallydistributed copper releases, runoff, and estimated exposure concentrations in surface 
water, soil, and sediment for an urbanized setting. Setting design was based on typical 

housing densities and upper-end copper use patterns in building materials to provide a 

representative “worst-case” scenario with respect to spatial distributions and variability of 

copper sources at the watershed scale. Copper release rates from building materials were 

defined as functions of surface area and rainfall using measurements from manufacturers 

or other field study results. The model requires data to define watershed boundaries, the 

stream network, land surface elevations, soils, land use, physical processes that control 

runoff and soil and sediment transport, as well as rainfall. Data were obtained from 

standard sources including the U.S. Geological Survey, Natural Resource Conservation 

Service, National Weather Service, and Census Bureau. The watershed area was 21.4 

km2. The model grid was defined at a 90 meter resolution and includes 2,558 cells. 

Simulations were performed for a 10-year period with 772 storms defined using 15-

minute rainfall data. Results were analyzed in terms of the frequency with which modeled 

exposure concentrations exceeded benchmarks for water, sediment or soil. Surface water 

benchmarks were determined with the biotic ligand model (BLM) for copper. Simulated 

copper exposures from algae-resistant shingles were relatively low and did not result in 

exceedances in any media. Simulated exposures from treated wood were larger than those 

for shingles and resulted in two water quality benchmark exceedances (i.e. 2 days in 10 

years).