Minutes of the July 27, 2010 Exposure Modeling Public Meeting 

U.S. Environmental Protection Agency, Office of Pesticide Programs (OPP) 

One Potomac Yard, S-4370/4380 

2777 South Crystal Drive 

Arlington, VA 22202 

Attendees: 

Name Association 

Uwe Wanner Chemtura 

Thuang Xiao Dupont 

Natalia Peranginangin Syngenta 

Chris Burnside Toxcel 

Russell Jones Bayer Cropsciences 

Mark Velleux HydroQual 

Catherine Aubee USEPA/EFED 

Aaron Harding Environmental & Turf Services, Inc. 

Paul Henley Syngenta 

LaJan Barnes Environmental & Turf Services, Inc. 

Mortin Williams Waterborne 

Stephen Kraemer USEPA/ORD 

Kurt Pluntke USEPA/EFED 

William Eckel USEPA/EFED 

Katherine Carr Monsanto 

James Lin USEPA/EFED 

Donald Brady USEPA/EFED 

Brannon Walsh USEPA/AD 

David Valcore Valcore Consulting 

David Healy Stone Environmental 

Tom Nolan USGS 

Isha Khanijo Waterborne 

Qingli Ma Exponent 

Al Barefoot Dupont 

Andy Newcombe Arcadis 

Ian Kennedy CAN/PMRA 

Stuart Cohen Evnironmental & Turf Services, Inc. 

Nick Poletika Dow Agrosciences 

Faruque Kahn USEPA/EFED 

Robert Miller USEPA/EFED

Scott Jackson BASF 

Iwona Maher USEPA/EFED 

Chris Koper USEPA/EFED 

Subijoy Dutta USEPA/EFED 

Andrew Shelby USEPA/EFED 
Paige Doelling NOAA/NMFS 

Michael Winchell Stone Environmental 

Paul Paquin HydroQual 

Jane Tang Bayer Cropsciences 

Robert Joseph Syngenta 

Nathan Snyder Waterborne 

John Weeks S.C. Johnson 

Greg Orrick USEPA/EFED 

Dirk Young USEPA/EFED 

Michael Barrett USEPA/EFED 

Yan Donovan USEPA/PRD 

Ronald Parker USEPA/EFED 

Jim Wolf USEPA/EFED 

R. David Jones USEPA/EFED 

Siros Mostayhimi USEPA/AD 

Tanja Crk USEPA/EFED 

Has Shah American Chemistry

Dial In Participants 

Name Association 

Jeff Giddings Compliance Services 

James Cooper et al Florida Dept. of Agriculture and Consumer Services 

Ann Pitchford USEPA, NERL 

Bill Mahlburg Nufarm Americas Inc 

Richard Allen Bayer Cropsciences 

Kelly Moran TDC Environmental 

Jack Barbash USGS 

Frank Voss USGS 

Vincent Leopold Monsanto 

Nick Hart OMB 

Monica Ball Dupont Crop Protection 

Cecil Dharmasri Syngenta Crop Protection 

Eric Weber EPA ORD 

Tim Negley ARCADIS US, Inc 

Susan Youngren BERGESON & CAMPBELL, P.C. 

Kent Kabler et al Syngenta Crop Protection 

Gerhard Goerlitz Bayer Cropsciences 

Jim Warren USDA-APHIS 

Mark Schocken Schocken Consulting 

Barbara Pugh AMEC Earth and Environmental 

Jay Nag Chemtura 

John Schnupner Cheminova 

Joe Zachmann Minnesota Dept of Ag 

Ron Struss Minnesota Dept of Ag 

Heather Johnson Minnesota Dept of Ag 
Joe Bagdon USDA 

Greg Malis PMRA 

Les Carver Waterborne 

Joy Honegger Monsanto 

John Troiano CDPR 

Allan Rose Valent 

Roy Meyer NJDEP 

Kristian Paul DuPont Crop Protection 

Welcome and Introductions 

The USEPA/OPP/EFED hosts these biannual meetings that are open to the public to provide a forum 

for exchange of information between EFED and stakeholders with similar technical expertise of 

current issues related to pesticide exposure modeling in support of risk assessment. The 

overarching theme of this meeting was “Ground Water Modeling and Pesticide Modeling 

Refinements in Agricultural and Urban Environments.” Reuben Baris and Charles Peck (both of 

USEPA/OPP/EFED) co-chaired the meeting in the capacity of co-chairs of the Water Quality 

Technical Team (WQTT). 

The minutes and presentation slides for the July 27, 2010 EMPM are posted in the docket (EPAHQ-OPP-2009-0879), which can be accessed at http://www.regulations.gov/. The docket ID # is 

reported on the EMPM webpage: http://www.epa.gov/oppefed1/models/water/empm_top.htm.

Brief Updates 

None 

Presentations 

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 groundwater 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. 

Presentation Notes: 

Monitoring data from prospective groundwater (PGW) studies can be used to develop and 

evaluate exposure models 

Uncertainties must be identified and addressed to design and implement more relevant and useful 

studies 

Uncertainties in fate studies (Lack of information on site-specific degradation and sorption 

purposes) 

Finding the right balance: simplicity v. refinement (can be data intense) 

Uncertainties associated with temperature 

Limitations of data censoring 

• Breakthrough patterns cannot be accurately established 

• Reporting limits, detection limits set too high 

Application rate v. water detection limits 

• Identify fraction of nominal (target) application rate detectable in water samples 

Issue: Only transformation product has well-defined breakthrough (Must simulate formation of the 

transformation product) 

Issue: Insufficient irrigation or precipitation 

Issue: Studies that end too early 

Issue: Increased spatial and temporal variability in the soil matrix 

Critical elements of effective PGW studies 

• Complete and accurate weather data 

• Detailed soil characterization 

• Preparation and performance testing 

Suction lysimeters have been found useful at many sites, but not always. Success has improved, 

as shown by the data, but it is a learning process. 

Study design could be improved based on chemical- and site-specific leaching predictions. 

There is a fair amount of confidence in modeling of extreme leaching situations. Need to balance 

reasonable objectives of the study, e.g., with chemicals expected to leach very slowly (perhaps 

many years): One might be able to characterize breakthrough but not detect GW concentrations 

within a reasonable timeframe. 

Need to know the relationship between physical soil characteristics and chemical degradation. 

Transformation gets slower with soil depth, and thus [the characterized transformation process?] 

may not be representative, when the rate of change in transformation rate with soil depth is 

unknown. Timing is important. 

*************************************************************************** 

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. 

Presentation notes: 

Mr. Williams compared three models for estimating pesticide exposure in ground water. These 

models were 1) SCI-GROW, a Tier I screening empirical model, 2) the Tier II screening model 

PRZM parameterized for the N-methylcarbamate cumulative risk assessment (PRZM-NMC), and 

3) PRZM linked to ADAM, an aquifer dispersion and advection model based on Darcy's law 

(PRZM-ADAM). Model results were evaluated with soil and vadose zone (5- to 6-foot depth) 

sampling data from five prospective ground water (PGW) monitoring studies. 

Soil concentrations of pesticides and bromide were predicted fairly well with PRZM. However, 

PRZM tended to flush bromide through the vadose zone too quickly and pesticide concentrations 

in soil pore water were over-estimated by less than an order of magnitude. Bromide 

concentrations in ground water were 1) over-estimated with SCI-GROW by approximately two 

orders of magnitude, 2) over-estimated by PRZM-NMC by 4X to 8X, and 3) similar to PRZMADAM estimates. Pesticide concentrations in ground water were 1) similar to SCI-GROW 

estimates, 2) under-estimated by PRZM-NMC, and 3) under-estimated much more by PRZMADAM. Differences between estimates from PRZM-NMC and PRZM-ADAM may have been 

due to their simulation of different mixing depths (1-m versus 5-m, respectively). Further research 

may include analysis of additional study data, calibration for bromide timing, and sensitivity 

analyses. 

*************************************************************************** 

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. 

Presentation Notes:

Current Status on Ground Boom Spray Drift Models: deposition based on empirically determined 

curve fits as a function of drop size distribution; does not account for wind speed effects on spray 

droplets 

Current Ground Boom Spray Drift Model Development: Silsoe drift model (UK) which accounts 

for multiple boom nozzles, sprayer flow, evaporation/entrainment, and sprayer designs. Model 

can be run in a probabilistic mode. 

Evaluation of Silsoe drift model – comparison to Spray Drift Task Force field data and sensitivity 

analysis conducted (e.g. nozzle porosity parameters, humidity, volatilization, boom height, wind 

speed, entrained air velocity, and droplet size distribution) 

Results 

 Model tended to over-predict for short distances from sprayer 

 Most important environmental parameters to deposition – boom height, wind speed, 

evaporation rate, and minimum droplet size 

 Most important nozzle-specific parameters to deposition – droplet size distribution and 

entrainment 

Future Work 

 Refine model to address air induction nozzles 

 Further investigate multiple nozzles 

 Perform more studies to retrieve more input data 

 Improve computational fluid dynamics model 

Discussion 

 Investigation on impact of adjuvants needed 

 Largest reductions in hot, dry environments with tank mixes using non-volatile oils 

 Drop sizes may be most modified in the upper portions of spectra > 100μm

*************************************************************************** 

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. 

Presentation Notes:

Presentation on the use of percent cropped area (PCA) estimates to refine drinking water 

assessments. Review of EPA’s development of PCA values and their current approach to 

implementing PCAs. Discussion of the current limitations to EPA’s method: 

 PCAs too coarse for use with minor crops, so EPA uses default PCA 

 PCA for multiple crops based on single watershed w/ highest percent of crops being 

 modeled 

 HUC-8s may not provide reasonable estimates for smaller watersheds 

 Assumes uniform and homogeneous distribution of crops 

Need for development of Tier 3 approach that combines local knowledge of drinking water 

supplies, actual watersheds, and spatial distribution of crops with regional scenarios and weather. 

Use of GIS with SDWIS, NHDPlus, and DWMA to delineate water intakes and watersheds. Use 

of NASS Crop Data Layers to delineate spatial crop areas. Good agreement between CDL data 

and Ag Census data. 

Development of a Tier 3 assessment and PCAs is feasible, will help identify vulnerable 

monitoring locations, will help identify areas requiring possible stewardship activities, and protect 

important use areas that fall outside potentially vulnerable drinking water supplies. 

*************************************************************************** 

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 

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. 

Presentation Notes:

This presentation described the design and testing of the Process-Based Groundwater 

Vulnerability Assessment (P-GWAVA) System. The principal objective of P-GWAVA is to make 

the most informed predictions possible of agrichemical concentrations in ground water, anywhere 

in the lower 48 states. To make informed predictions P-GWAVA: 

• incorporates as much process understanding as possible 

• uses only on data sources covering all areas of the lower 48 states 

• employs only public domain models 

P-GWAVA is designed to simulated concentrations of agrichemicals in the vadose zone as 

indicator concentrations in shallow groundwater. Since there are more monitoring data on atrazine 

and its degradates, deethyl atrazine (DEA) and nitrate, these compounds were used exclusively in 

development of the model. During the development of P-GWAVA predicted concentrations in the 

vadose zone were compared with concentrations measured in shallow groundwater by NAWQA. 

Since atrazine is most commonly used on corn, use on corn is simulated at all sites. 

The PRZM (Pesticide Root Zone Model) and RZWQM (Root Zone Water Quality Model) models 

were employed. 

The P-GWAVA system was designed for running unsaturated zone simulations at multiple sites. 

CLIGEN and SSURGO Data were used for RZWQM Inputs. 

For Phase 1 (PRZM) of the system development study, 42 areas (1254 well sites) were selected 

relative to where atrazine use was employed in an agricultural setting throughout the country. For 

phase 2 (RZWQM), 435 wells were selected relative to where atrazine was used in an agricultural 

setting within the Corn Belt. In PRZM, soil column data is presented in uniform composition to a 

depth of one meter. For PRZM, the soils data taken from STATSGO, weighted by depth and area. 

For RZWQM all soil layers are represented to a depth of 3 meters. Soil Data for RZWQM was 

data taken from SSURGO. 

Only 7% of the mass balance of the compound was detected in soil after seven years of annual 

atrazine applications (2 kg/ha/yr) in southwestern Indiana. Only 0.26% of DEA was found in the 

soil. This was mainly due to plant uptake and mineralization. 

P-GWAVA was also used to predict nitrate concentrations in the same area of southwest Indians. 

Nitrate concentrations of 0.08 mg/L were predicted in the vadose zone. 

Observed atrazine, DEA, and nitrate groundwater concentrations were higher than those predicted 

in the RZWQM vadose zone. Observed DEA and nitrate concentrations were higher than 

predicted vadose zone concentrations from PRZM. The statistical correlation between predicted 

and observed solute concentrations in both the Corn Belt and nationwide had low R squares. 

*************************************************************************** 
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. 

Presentation Notes:

In this study, four different models were evaluated (APEX, PRZM-BUFF, REMM, and 

VFSMOD) using three case studies. 

Vegetative filter strips have long been recognized as successful at reducing runoff concentrations 

to receiving streams and recently have been mandated in many cases. 

A qualitative way of evaluating filter strips has become necessary. This can be done through 

either field work (looking at soil, weather, topography, climate, etc.) or by using mechanistic 

models that can account for different levels and balances of the previous listed inputs. 

The 3 objectives of this presentation were to: 

1. Evaluate the four models 

2. Understand the sensitivity of the 4 models 

3. Analyze the models for use 

APEX 

o This model is mostly used for agricultural non-point source and nutrient evaluation. 

o The study area is divided into subareas, with the subareas having the possibility of being 

 different (for example, overland flow versus channel flow). 

PRZM-BUFF 

o This model is used in pesticide exposure and for other non-point source issues 

o It is divided into a main treated field run and a second run that involves the outflow from 

 the main treated field through the vegetation in the buffer 

REMM 

o Used for nutrient management, multi-zone uses mostly with pesticides 

o There is no field component (only buffer) 

o Has 3 parts to the buffer. 

1 Vegetative filter strip 

2 Managed strip (for example, woody vegetation) 

3 Unmanaged (for example, stream bank) 

VFSMOD 

o Sub-daily time step model used for non-point source 

o Flow and sediment loads are input into the model in a time series 

o Equations are used to estimate infiltration and sediment deposition 
o Pesticide reduction is a function of infiltration, deposition, chemical characteristics, and 

 soil clay 

Discussion 

1) In PRZM-BUFF, the Curve No (CN) was made artificially high because it was designed for 

daily sensitivity, not hourly. 

2) Differences in parameterizations could have been why there was more error in some models 

(REMM) over others. However, evaluators only looked at inputs and outputs parameterized for 

REMM as one grass filter strip divided into the three parts. 

*************************************************************************** 

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. 

Presentation Notes:

In 2006, a model evaluation compared the Stormwater Management Model (SWMM) and the 

Pesticide Root Zone Model (PRZM). 

The objective was to present recent advances in modeling pesticide runoff urban/residential 

landscapes. Model pesticide applications and pesticide washoff from hard surfaces with SWMM. 

Model runoff and pesticide washoff from hard surfaces with PRZM. 

Within SWMM, pesticide application is added as a continuous buildup; whereas within PRZM, 

the pesticide can be added at a distinct interval. 

Simulation of Storm Water Runoff with SWMM and PRZM showed comparable results. 

Enhancements within both models allow for refined runoff concentrations. 

SWMM (beta) now has the ability to simulate discrete applications of chemicals. 

PRZM (WinPRZMwdv) now has the ability to simulate hard surface runoff of chemicals 

SWMM and PRZM reasonably simulated hydrologic response of UK roadway and an Oregon 

residential area 

SWMM and PRZM reasonably simulated atrazine and glyphosate from a UK roadway 

Data is becoming available to develop washoff coefficients for hard surfaces (pesticide 

properties/formulations vs. surface conditions) 

Discussion: 

It was unclear as to whether the weather data presented in Oregon dataset was representative of a 

national scenario. 

*************************************************************************** 
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 offchannel 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. 

Presentation Notes:

The impetus of the spray drift exposure modeling work relating to salmonid off-channel habitats 

stems from the first NMFS biological opinion (BiOp) of Nov. 18, 2008. Several off-channel 

habitats were proposed in the BiOp but not all were deemed necessary (at least for this 

presentation) for modeling. Off-channel areas considered in the presentation include side channels, 

alcoves, and backwater pools. Relatively high shade % values were also considered, as they would 

be indicative of quality salmon habitat as well as riparian habitat (and thus spray drift interception 

zones). All three off-channel areas have characteristic flows: channel flow, hyporheic flow & 

mixing with main channel, and eddy current mass exchange, respectively. A different model 

construct is used for each off-channel habitat to generate time-weighted average concentrations 

(i.e., a change in concentration over time) that are consistent with acute toxicity test times (24-96 

hours): Stream Assessment Tool (SAT) in AgDrift 2.0.05, AgDrift 2.0.05 & dye study 

measurements, and AgDrift 2.0.05 & channel flow data & fluid dynamic modeling, respectively. 

Representative locations (in OR, CA) for data needs were based on NLCD 2001 land cover data 

(open water 11, pasture/hay 81, and cultivated crops 82) that indicated whether the site of interest 

was representative of agricultural areas. Several model assumptions were considered conservative. 

The worst-case results for both aerial and ground scenarios for each habitat (1-day averages) 

indicate that the greater the distance between application site and water the lower the chemical 

concentration in water. However, the backwater habitat appears to have the greatest chemical 

concentrations of the three habitat types. 

*************************************************************************** 

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 (Two-dimensional Runoff Erosion and Export) watershed 

model was used to simulate spatially-distributed 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). 

Presentation Notes: 

The main focus of the presentation was on antimicrobial pesticides. It is well documented in EPA 

websites and elsewhere that determining human and ecological risks from exposure to 

antimicrobial pesticides requires different types of measurements and models than those needed 

for pesticides largely applied to crops and other plants. Specific applications could be any variants 

of the following: 

 Antifoulants, biocides wood preservatives, etc. 

 Antimicrobial copper use in building products... 

Different field settings were considered such as – 

 Agricultural Use: 

 Farm fields 

 Uniform application 

 Building Products: 

 Urbanized areas 

 Spatially variable! 

 biocide mass released not equal to mass installed 

 Address variability with watershed approach 

TREX Watershed Model: Two-Dimensional Runoff, Erosion & Export 

This model is available to anyone and can be downloaded from: 

http://www.engr.colostate.edu/~pierre/ce_old/Projects/TREX%20Web%20Pages/TREXHome.html 

This chemical transport model followed EPA’s WASP model to some extent. The following 

diagram provides an overall view of the major input components in the model. 

Major Inputs for the TREX Model include: 

• Topography (DEM) 
• Soil characteristics 

• Land cover 

• Stream and sediment characteristics 

• Rainfall 

• Chemical application and release rates 

• Chemical partitioning and fate parameters 

A few Case Studies were presented – 

Antimicrobial Copper – Examined two separate copper uses using 90m x 90m boxes: 

 Algae-resistant (AR) Shingles and 

 Treated Wood 

Uses and setting differ from agricultural case. The case studies were undertaken in – 

1. Urban setting with spatially-variable landscape conditions; rainfall-driven releases from 

 roofs, decks, fences, and poles... 

2. Lake setting with marina and inputs from upstream 

 Simulated copper transport and fate to calculate estimated environmental concentrations 

 (EECs). 

The setting was based on real watershed 

The information was used to calibrate the model for these parameters. Information on 

Slide Fences – treated wood fences, Toledo, OH were used to represent the urban setting. 

Copper sources in urban setting were a combination treated wood decks and fences 

Overall summary Cu Release rate – 20% CCA, 80% non-CCA, overall 14.1 mg/m2 /day. 

The Environmental Benchmarks for Cu in Surface Water, Soil, and Sediment were checked and 

compared with the release rates. Results for Algae-Resistant Shingles for over 10 years indicated 

that Cu releases driven by Rainfall. Sediment – stream segment – 9% of Cu deposits ends up in 

stream beds. EECs and Benchmarks indicated monthly change and time variable change. 

Simulated Cu Mass Fate – over 10 years didn’t see much leaching. In treated wood there were 

two Benchmark exceedances in 10-year period for the average concentrations. Results are 

expected to be conservative. According to the author/presenter’s interpretation – both urban and 

aquatic setting EECs are not expected to exceed the benchmarks. 

Discussion: 

1. GIS mapping of the study area was used to estimate the total drainage and copper source from 

the urban setting; it was unclear as to how any errors associated with this data were corrected.

2. The accuracy of the concentrations of Cu in water measured and whether there were any 

special measurements for hot-spots would be presented in follow-on material.

3. At the time of the evaluation, there were no considerations given or a study undertaken to 

estimate possible high concentrations of Cu in the surface water from AR Shingles in areas with 

acid rain and from treated woods in acidic waters. If there is a primary application in such 

environments, assessors would evaluate this in future work would assess.

Wrap Up

The Next EMPM will be held on December 7, 2010. The meeting theme will be announced 

through the “empm listserve” forum on the LYRIS list serve at: 

https://lists.epa.gov/read/?forum=empmlist.