1 © 2013 by Pyrethroid Working Group. All rights reserved.

Development and Validation of an 

Approach for Modeling Pyrethroid 

Residues in Urban Streams

Michael Winchell1, Scott Jackson2, Gary Mitchell3

1. Stone Environmental, Inc.

2. BASF Corporation

3. FMC Corporation

EMPM, Crystal City, VA, March 19th, 2013

Presented by Michael Winchell on Behalf of Pyrethroid Working Group member 

companies: AMVAC, Bayer, DuPont, FMC, Cheminova, Syngenta, Valent, 

BASF

3/19/2013 Slide 
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Contents

 Background

 Conceptual Model

 Inputs and Parameterization

 Model Application and Results

 Summary and Conclusions

Mar 2013 Slide © 2013 by Pyrethroid Working Group. All rights reserved
3

Background: Models for Predicting 

Urban Pesticide Concentrations

 Approaches for modeling urban pesticide fate and exposure 

have been reviewed and are still under development. (Cheplick

et. al., 2006)

 Pesticide Root Zone Model (PRZM): US EPA

 Field scale, agricultural model

 Strength in handling of pesticide fate/transport in soils

 Used in regulatory aquatic exposure assessments

 Storm Water Management Model (SWMM): US EPA

 Watershed scale, urban water quantity and quality model

 Strength in handling of sub-hourly runoff and flow routing 

 Not historically used in pesticide regulatory modeling

 This study examines the applicability of the SWMM model.

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Background: Study Location

 Aliso Viejo, Orange 

County, CA

 Drainage area: ~ 66.7 

acres

 307 homes

 Dwelling unit density: 

4.6 units/acre.

 Watershed boundary 

delineated during multiyear monitoring study.

(Haver, 2012a)

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Background:

Study Location, Street View

 Lawns and landscaping are well maintained (i.e., watered) in 

this high density neighborhood.

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Background: Monitoring Data

 A report to the CA State Water 

Resource Control Board 

contained 1 year of chemical 

monitoring data from the Aliso 

Viejo site. (Oki and Haver, 2011)

 Hourly flow data was collected at 

the watershed outfall. (Haver, 

2012b)

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Background:

Chemical Monitoring Data

 31 chemical samples from both dry and storm periods 

were collected from 10/3/2007 – 10/01/2008 and 

published in the 2011 report.

 A representative pyrethroid with a high percentage of 

detections was selected for modeling.

 Dry weather samples 

typically had the highest 

concentrations.

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Conceptual Model:

Assumptions and Approach

 Assumptions for this model:

 Pyrethroids enter urban storm drains via runoff/washoff 

primarily from impervious treated surfaces and potentially 

from pervious treated surfaces during excessive rainfall 

events.

 Runoff from treated surfaces can occur as a results of natural 

rainfall, irrigation, or outdoor residential water use occurring 

on impervious and pervious treated surfaces.

 Landscape features in a residential setting can be 

differentiated based on: pyrethroid inputs, water inputs, and 

hydrologic response (i.e., infiltration rate).

 Approach:

 Divide up the neighborhood into distinct landscape units 

based on unique combinations of these 3 differentiating 

characteristics.

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Conceptual Model: Residential Layout

 Most of the different landscape units in the development 

fall into one of the categories labeled on the image below.

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Conceptual Model:

Spatial Representation

 The neighborhood was 

first spatially delineated 

into 15 landscape units.

 Units were then 

mathematically split to 

allow variable treatment 

timing.

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Inputs and Parameterization:

Pyrethroid Applications/Water Use

 Approach: Characterize pyrethroid use and water use based 

on recent literature and interviews with local experts.

 Primary Sources:

 California 2009 Urban Pesticide Use Pattern Study, PWG and 

Meta Research Group, 2010.

 Darren Van Steenwyk, Technical Director, Clark Pest Control; 

personal communication, June 1, 2012.

 Survey of Residential Pesticide Use and Sales in the San Diego 

Creek Watershed of Orange County, California, C. A. Wilen, 

2001.

 John Horne, California Native Yards, specialist in residential and 

commercial native low-water landscape designs, lives 1⁄4 mile 

from Aliso Viejo site; personal communication, June 6, 2012.

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Inputs and Parameterization:

Water Use

 Pyrethroid concentrations observed during “dry weather” 

conditions were frequently higher than the concentrations 

during storm events.

 Dry weather flows result from outdoor household water use.

 Irrigation: Assumed to occur for all lawn and landscape areas

 Depth and duration varies throughout year; 0.20 – 0.35 in/day

 Time of Irrigation: 7:00 am – 7:30 am

 Area over-spray: 1 foot beyond lawn/landscape area onto 

impervious

 Car washing:

 50% of homeowners wash their cars at home once per month

 volume of water used when washing a car at home is 55 gallons

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Inputs and Parameterization:

Pyrethroid Applications

 Applications at max label rate, differentiated for: foundation 

perimeter, patios/walkways, driveways, lawns/landscaping.

 Different fractions of each landscape class treated always 

(once every 6 weeks), sometimes (once every 12 weeks), or 

never.

 Landscape areas in 4 different sub-catchment zones received 

different timing of application treatment sequences.

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Inputs and Parameterization: 

Impervious Washoff Results

 Data from a study of pyrethroid runoff from concrete 

surfaces was used to calibrate SWMM impervious surface 

washoff. (Jiang et al., 2012)

 Concentrations were well-predicted at days 1 and 47, overpredicted at days 7 and 20, and under predicted at day 89.

Mar 2013 Slide © 2013 by Pyrethroid Working Group. All rights reserved

From Jiang et al. (2012)
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Inputs and Parameterization:

Pervious Washoff Results

 A field study measuring pyrethroid runoff from irrigated 

turfgrass was used to calibrate SWMM pervious surface 

washoff. (Hanzas et al., 2011)

 Runoff volume and pyrethroid mass were calibrated from 3 

over-irrigation events, spanning 1 to 5 days after application.

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Pyrethroid Mass Calibration
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Model Application: 

Daily Flow Simulation

 Mean daily flow is well-simulated: NSE = 0.77; Volume Bias = 

+5%

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 Rainfall input 

from the 

California 

Irrigation 

Management 

Information 

System (CIMIS) 

Irvine hourly 

weather station 

(9 miles away).

 Surface runoff 

came ONLY 

from impervious 

surfaces.
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Model Application:

Hourly Flow Simulation, Dry Period

 Daily flow variability is due to timing of irrigation on adjacent 

impervious surfaces and subsurface drainage from lawns into 

storm drains.

 Range and variability of daily flows is adequately represented.

 Difficult to model the observed behavior precisely but general 

pattern is captured.

 For 10/2007 – 9/2008:

 R-squared = 0.70

 NSE = 0.55

Nov Mar 2013 Slide © 2013 by Pyrethroid Working Group. All rights reserved
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Model Application:

Hourly Flow Simulation, Storm Period

 The largest storm event occurred in January, 2008. 

 Given that hourly rainfall data was from 9 miles away, the 

hourly flows during storm events were well simulated.

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100% of simulated 

surface runoff is from 

impervious surfaces.
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Model Application:

Comparison with Monitoring Data

 Simulated 15-min concentrations were averaged over 6-hr 

and 24-hr periods. The maximum 6-hr average was taken for 

each day.

 Observation grab samples taken between 7 am and 11 am.

 The short duration of 

irrigation runoff

results in mean daily 

concentrations 

significantly lower

than max 6-hr values.

 Observations generally

fall within the range of

the simulated mean 

daily and max 6-hr 

concentrations.

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Model Application: Comparison with 

Monitoring Data, Storm Events

 The observed concentrations on 12/1/2007, 12/7/2007, 

12/19/2007, and 1/5/2008 corresponded with storm events.

 In 3 of 4 events, the 

observed

concentration fell 

in between the 6-hr 

max and daily mean 

simulated 

concentration.

 Sampling time 

was typically in late

morning, which 

agrees well with 

the simulated 7am –

12pm concentration.

Mar 2013 Slide © 2013 by Pyrethroid Working Group. All rights reserved
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Model Application: Simulation of 

Pyrethroid Application BMPs

 Current pyrethroid labels require treatment of horizontal 

impervious surfaces to be limited to “crack and crevice” 

applications.

 This was simulated by 

reducing all 

impervious surface

application areas 20x.

 The new label 

requirements

lowered predicted 

outfall concentrations 

by a factor of 20,

proportional to the

treated area reduction.

Mar 2013 Slide © 2013 by Pyrethroid Working Group. All rights reserved
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Model Application: SWMM-AGRO 

30-Year Simulations

 A 30-year time series of hourly precipitation for Aliso Viejo 

(Irvine/Long Beach) was developed to run SWMM and 

generate a 30-year daily time series of pyrethroid loadings 

from the development.

 The outfall pyrethroid 

loadings from SWMM 

were used as input to 

the standard farm 

pond simulated by the

AGRO model.

 The AGRO model 

was parameterized

as represented in the

PA5 shell. 

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Model Application: SWMM-AGRO 

Ecological Risk Assessment

 The 30-year SWMM-AGRO model was run for both the 

“historical” and the “current” pyrethroid application 

practices.

 Annual maximum 

96-hr EECs in the 

pond water column 

were 10 – 20 times

lower for the new 

label application 

practices compared 

to historical 

practices.

Mar 2013 Slide © 2013 by Pyrethroid Working Group. All rights reserved
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Summary and Conclusions

 SWMM proved to be a useful, and potentially accurate tool at 

predicting concentrations of urban applied pyrethroids.

 Modeling pesticide fate and transport in an urban setting 

required:

 Discretization of the environment into distinct landscape areas 

 Ability to route flows 

 Operation on a sub-hourly time step

 Accounting for pesticide fate and transport processes

 Recent adoption of BMPs have been shown to significantly 

reduce pyrethroid runoff in plot field studies (PWG Pathways 

ID) as well as when simulated at the watershed scale.

 Linking of SWMM with a receiving water body model (AGRO) 

can serve as a framework for exposure prediction in ecological 

risk assessments.

Mar 2013 Slide © 2013 by Pyrethroid Working Group. All rights reserved
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THANK YOU

Mar 2013 Slide © 2013 by Pyrethroid Working Group. All rights reserved

(Image from: archive.cityofdavis.org)
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References

 Cheplick, J.M., S. Dasgupta, A.M. Ritter, and W.M. Williams. 2006. Model 

Review and Scenario Development for Urban/Residential Pesticide Runoff 

Model. Prepared by Waterborne Environmental, Inc. for Crop Life America.

 Jiang, W., D. Haver, M. Rust, J. Gan. 2012. Runoff of pyrethroid insecticides 

from concrete surface following simulated and natural rainfalls. Water 

Research 36, 645-652.

 Hanzas, J. P., R. L. Jones, and J. W. White. 2011. Runoff Transport of 

Pyrethroids from a Residential Lawn in Central California. Journal of 

Environmental Quality 40:587–597.

 Haver, D. 2012a. Watershed Boundary for Aliso Viejo Subdivision. Personal 

Communication, Darren Haver, South Coast Research & Extension Center.

 Haver, D. 2012b. Hourly Flow Data for Aliso Viejo Subdivision. Personal 

Communication, Darren Haver, South Coast Research & Extension Center.

 Oki, L, and D. Haver. 2009. Pollutants In Runoff From Residential Sources. 

ACS National Meeting, Washington, D.C.

 Oki, L, and D. Haver. 2011. Evaluating Best Management Practices (BMPs) 

Effectiveness to Reduce Volumes of Runoff and Improve the Quality of 

Runoff from Urban Environments.

Mar 2013 Slide © 2013 by Pyrethroid Working Group. All rights reserved