Pesticide Aquatic Exposure 

Scenarios and Modeling for 

Juvenile Pacific Salmonid Floodplain 

Habitat

Nick Poletikaa

Zhenxu Tangb

Scott Jacksonc

a Dow AgroSciences LLC

b Bayer CropScience

c BASF Corporation 1
Background

 In recent biological opinions from the National 

Marine Fisheries Service addressing concerns with 

the impact of pesticides on Pacific salmonid

populations listed as endangered/threatened, there 

has been a great emphasis on juveniles occupying 

shallow habitat in floodplains.

 Current exposure models and scenarios do not 

represent this habitat well.

 We present an approach to exposure modeling and 

risk assessment for commercial agriculture in 

floodplains where pesticide use is frequent and flood 

control systems are present. 2
Off-Channel Features of 

Importance in Agricultural Areas

 Three basic types with connection to the main 

channela

 Side channels

• Flowing water bodies with clearly identifiable upstream and 

downstream connections to the main channel

 Alcoves

• Water bodies that maintain a downstream connection to the 

main channel at summer low flow, but have no upstream 

connection during low flow

 Backwater pools

• A pool formed in free-flowing streams by an eddy along 

channel margins downstream from obstructions such as 

bars, rootwads, or boulders

a http://oregonstate.edu/dept/ODFW/freshwater/inventory/index.htmc 3
Examples of Side Channels and 

Alcoves

4

Source: http://www.fsl.orst.edu/pnwerc/wrb/Atlas_web_compressed/3.Water_Resources/3d.off-channel%20habs_web.pdf

Side Channel

Alcove

Alcove

Side Channel
5

Example of Backwater Pool

Pool

Hwy 99
Scenario Selection

 Different transport/mixing mechanisms

 Side channels – stream flow

 Alcoves – hyporheic flow

 Backwater pools – eddy current exchange

 Imply the need for different process models

 Stream flow – advection/dispersion

 Hyporheic flow – empirical decay model 

based on dye studies

 Backwater pools – computational fluid 

dynamics

6
Scenario Selection, Cont.

 Side channel advection/dispersion can be 

simulated by existing research and 

regulatory models.

 Alcoves and backwater pools require more 

novel approaches.

 Selected side channel to take advantage 

of existing models (and measured data)

7
Data for Side Channel Scenario

 Lower Mokelumne River, CA, below 

Camanche Dam

 Data collected by biologists from the East Bay 

Municipal Utility Districta

 Habitat was measured in conjunction with 

seining to sample fish in four side channels.

 Depth and velocity taken at the seining 

location; width also measured

 133 measurements from 1996-2004

a Joe Merz, personal communication 8
Mokelumne River Side Channel Locations in Relation to Ag. Land

9
Downstream Side Channel Landscape Features

10
Are Variables Correlated?

DEPTH (m)

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6

VELOCITY (m sec-1) 0.0

0.2

0.4

0.6

0.8

1.0

1.2

r

2 = 0.179

p<0.001

WIDTH (m)

8 9 10 11 12 13 14 15 16

VELOCITY (m sec-1) 0.0

0.2

0.4

0.6

0.8

1.0

1.2

r

2 = 0.107

p<0.001

11

Depth, Width vs Velocity
Are Variables Correlated?

Month vs Depth, Velocity, Pesticide

TIME (Month)

1 2 3 4 5 6 7 8 9 10 11 12

DEPTH (m)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

TIME (Month)

1 2 3 4 5 6 7 8 9 10 11 12

VELOCITY (m sec-1) 0.0

0.2

0.4

0.6

0.8

1.0

1.2

12

TIME (Month)

1 2 3 4 5 6 7 8 9 10 11 12

PESTICIDE FLUX IN RUNOFF (g cm-2 day-1) 0.00

0.05

0.10

0.15

0.20

1961

All 30 Years

1990
Compound Probability

 Overall scenario target probability for 

exposure potential (p)

 Example: p = 0.05 to 0.1, a typical worst case

 If controlling variables are independent, then

 p = p1 x p2 x p3 . . . x pn, where

• n = number of variables

• p1,2,3 ... n = probability of a value for each variable

 Assume independence of key variables 

driving exposure in the side channel

 Depth (D), width (W), velocity (V), pesticide mass 

in runoff (M)

13
Compound Probability, Cont.

 Example scenarios for p = 0.05 to 0.1

 pM = 0.1, pD = 0.5, W, V fixed for pD = 0.5

 pM = 0.1, pV = 0.5, D, W fixed for pV = 0.5

 p = 0.1 x 0.5 = 0.05

 Definitions

• pM = USEPA OPP 90th percentile annual maximum 

pesticide mass in runoff in 30 years of simulation

• Fixed is the mean measured value of the variable 

associated with all instances of the variable set to 

p = 0.5

14
Field-Scale Exposure Models

 Individual spray drift and daily runoff events 

simulated using the Pesticide Root Zone 

Model (PRZM) as implemented in a 

customized version of the PRZM-EXAMS 

(PE) Version 5 shella

 Fate and transport simulated by a customized 

spreadsheet implementation of the AGRO 

Quantitative Water Air Sediment Interaction 

(QWASI) fugacity modelb

 Both models were run on a 1-day time step

15

a http://www.epa.gov/oppefed1/models/water/index.htm

b http://www.trentu.ca/academic/aminss/envmodel/models/AGROv120.html
Scenario Definition - PRZM

 EPA farm pond standard scenario (10-ha field)

 Crop and location

• CAcotton_WirrigSTD.txt

 Fresno County, CA - MLRA 17

 Weather

• w93193.dvf

 Fresno

 Chemical

• Chlorpyrifos

 1 application on 1 Jul at 1.12 kg a.i./A

 Aerial application with 76.2-m spray drift buffer resulting in 1.7% 

drift

 Runoff the same day: p = 0.5 in irrigation scenario

16
Scenario Definition – AGRO

17

Name Farm Pond

Dimensions

Water Surface Area (m2) 10000

Water Volume (m3

) 20000

Sediment Active Layer Depth (m) 0.05

Concentration of Solids

Aerosol Particles (ug/m3

) 30

Inflow Particles (mg/L) 2

Suspended Sediment (mg/L) 30

Sediment Particles (m3

/m3

) 0.5

Density of Solids (kg/m3

)

in Water 2400

in Sediment 2400

in Aerosols 1500

Organic Carbon Fraction of Solids

in Water 0.067

in Sediment 0.04

in Inflow 0.067

in Resuspended Sediment 0.04

Flows

River water inflow (m3/h) 0.0001

Water outflow (m3/h) 0.0001

Deposition rate of solids to sediment (g/m2/day) 80

Burial Rate of Solids (g/m2/day) 40

Resuspension Rate of Solids (g/m2/day) 40

Mass Transfer Coefficients

Aerosol Dry Deposition (m/h) 10

Scavenging Ratio (vol air/vol rain) 200000

Rain Rate (m/y) 1

Volatilization (air side) (m/h) 1

Volatilization (water side) (m/h) 0.01

Sediment-Water diffusion (m/h) 0.0004

Variable Sedimentation

Settling Time 90% (days) 7

Resuspension Percentage (% of deposition) 50

Side Channel

pD

a = 0.5 = 0.66 m pVb= 0.5 = 0.19 m sec-1

10405 m2 10244 m2

6818 m3 3747 m3

11994 m3 h-1 3116 m3 h-1

11994 m3 h-1 3116 m3 h-1

a V = 0.393 m sec-1, W = 12.93 m

b D = 0.366 m, W = 12.73 m

Mokelumne River typical velocities

below Camanche Dam:

0.8 m sec-1 (low discharge)

1.4 m sec -1 (high discharge)

Pasternack et al., 2003. River Res

Appl 19:1-21.
Relative Sensitivity of Sorption and 

Flow for pV and pD = 0.5

(Flows of 3116 and 11994 m3 h-1, respectively)

18

Chlorpyrifos

Koc = 6070, log Kow = 4.7

[Channel] / [Pond]

pV = 0.5 0.272 0.275 0.277

pD = 0.5 0.0712 0.0726 0.0738

Koc = 60.7, log Kow = 2.7 Koc = 607,000, log Kow = 6.7

EXAMS Peak = 3159 ng L-1
Effects Data

 Sensitive aquatic invertebrate, Daphnia 

magnaa

 Short term exposure to chlorpyrifos evaluated 

for survival at 21 days

• 120 ng L-1, 24 h resulted in 95 ± 5% survival

• 250 ng L-1, 24 h resulted in 85 ± 10% survival

 Conclude that EC50 > 250 ng L-1 for 24-h 

exposure with no latent responses

 (Guideline study 48-h EC50 = 100 ng L-1)

19 a Naddy et al. 2000. Environ Toxicol Chem 19:423-431.
Risk Assessment

 Risk Quotient (RQ)

 Estimated Environmental Concentration / 

EC50

 Standard EFED RQ: EXAMS EEC, Peak / 

Guideline Study EC50 = 3159 / 100 = 31.6

 AGRO Farm Pond, p = 0.1, 48 h

• RQ = 1054 / 100 = 10.5

 AGRO Side Channel, p = 0.05, 24 h

• pD = 0.5: RQ = 77 / > 250 = < 0.31

• pV = 0.5: RQ = 293 / > 250 = < 1.2

20
Conclusions

 Pesticide exposure can be estimated in low velocity shallow 

water representing vulnerable juvenile salmonid habitat at the 

field scale using available models.

 With sufficient uncorrelated measurement data, a specific 

scenario vulnerability level can be set assuming simple 

compound probability.

 At a scenario probability level of p = 0.05, our example 

demonstrated that flow velocity limited predicted dissolved 

concentrations. 

 Short-term effects data can be used with time-weighted 

average exposures to assess risk at times as short as 1 day. 

 When this is done, the RQs decrease significantly, suggesting 

that the risk to the juvenile salmonid prey base is less than 

that predicted by standard scenarios.

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