Chuck Peck, Mark Corbin (EPA)

George Noguchi, Karen Myers (FWS)

Tony Hawkes, Scott Hecht (NMFS)

4/28/2015

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Agenda

 ESA Risk Assessment Paradigm

 Conceptual Model and Aquatic Bins / 

Watershed Sizes

 Surface Water Concentration Calculator 

(SWCC) Scenarios and Meteorological Stations

 Downstream Estimated Environmental 

Concentrations (EECs) (“Downstream 

Dilution”)

 Other Considerations

 Case Study – Shortnose Sturgeon

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ESA Risk Assessment Paradigm

Step 1

May Affect?

Step 2

Likely to Adversely

Affect

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Aquatic Bins

Generic Habitat Depth 

(meters)

Width 

(meters)

Length 

(meters)

Flow 

(m3/s)

1 – Aquatic-associated 

terrestrial habitats

NA NA NA NA

2- low-flow 0.1 2 Length of field1 0.001 

3- Moderate-flow 1 8 Length of field 1 

4- High-flow 2 40 Length of field 100 

5 – Low-volume 0.1 1 1 0

6- Moderate-volume 1 10 10 0

7- High-volume 2 100 100 0

8- Intertidal nearshore 0.5 50 Length of field NA

9- Subtidal nearshore 5 200 Length of field NA

10- Offshore marine 200 300 Length of field NA

1

length of field – The habitat being evaluated is the reach or segment that abuts 

or is immediately adjacent to the treated field. The habitat is assumed to run the 

entire length of the treated area. 4
Conceptual Model – Bins and Distance

Treated Field

30 m

Static Water Bodies

Runoff + Drift

(Bins 5, 6, and 7)

Sheet Flow

Flowing Water Bodies

Runoff + Drift

(Bins 2, 3, and 4)

Drift

Static Water Bodies

Drift Only

(Bins 5, 6, and 7)

Estuarine/Marine

Runoff and Drift

(Bins 8 and 9, assumed to 

occur within 30 m of field)

Drift Only beyond 30 m

(Bins 8, 9, and 10)

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Conceptual Model

 For Step 1, to derive the offsite transport extent of the 

action area, model EECs in Bin 2 and couple with 

downstream assessment; model Bin 5 for effects of 

spray drift only

 For Step 2, model all “representative” aquatic bins

 Evaluation of estuarine/marine bins would be limited to 

coastal areas and areas influenced by tidal flux

 Within 30 m, all flowing and static aquatic bins would 

receive runoff and spray drift

 Outside 30 m, static bins would only receive spray drift

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Watershed Sizes – Spatial Context

 Given differences in precipitation and evaporation 

rates across the country, the size of a watershed’s 

contribution to a water body will be different

 Estimate regional watershed size, as well as pesticide 

loading (e.g., surface water modeling), for a waterbody 

via hydrologic unit codes or HUCs

 HUC 2 – 18 regions in the conterminous US, containing 

the drainage area of a major river or series of rivers, as 

well as HI, AK and PR

 Efficient way to assess regional differences in 

environmental concentrations and manage resources 

needed for modeling

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HUC 2 Regions

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Watershed Sizes – Flowing Bins

 Use NHDplus dataset to assess relationships between 

drainage area and stream flow rates

 Confine analysis to streams and rivers and eliminated 

human-modified water bodies (e.g., canals, pipelines, 

etc.) and artificial pathways

 Generate ln-ln regressions between flow and drainage 

area for each HUC2 region

 Estimate drainage areas, or watersheds, for each 

aquatic bin and HUC2

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Watershed Sizes – Static Bins

 Conduct analysis using the SWCC, MS corn scenario 

(determined to be a high runoff scenario) and all 

available SWCC meteorological stations throughout 

the country (237 stations)

 Using the runoff estimates from the SWCC runs, and 

precipitation and evaporation data from 

meteorological station files, estimate the watershed 

size required to maintain the volume in the aquatic 

bins

 Try to achieve a median drainage area to normalized 

capacity (DANC) value of 5-15 m2/m3

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Watershed Sizes – Estuarine/Marine

 Uncertain how to estimate watershed sizes and/or 

model runoff from the watersheds into estuarine/ 

marine water bodies and aquatic-associated terrestrial 

habitats

 Issues regarding tidal flux, salinity of receiving water 

body that current models do not address

 Use static and flowing water body bins as surrogates, 

generally:

 Bin 5 for tidal pools 

 Bins 2 and 3 for low and high tide

 Bins 4 and 7 used for marine species that occasionally 

inhabit offshore areas

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Spatial Modeling - Scenarios

 Over 120 SWCC scenarios are available for modeling 

pesticide releases to surface water

 Agricultural – corn, wheat, citrus, etc.

 Non-agricultural – rights-of-way, impervious surfaces, 

residential

 Weather data are available for over 237 meteorological 

stations throughout the country

 Scenarios not evenly distributed across US

 In some cases, no current scenario exists for regions of 

the country (southwest US)

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Spatial Modeling - Scenarios

 For Step 2 modeling:

 Identify current SWCC scenarios for each HUC2 for each 

of the 11 crop data layer groupings

 For HUC2 regions that do not have SWCC scenarios, 

develop a surrogate scenario for use in the HUC2

 Representative scenario in nearby HUC2 with highest curve 

number

 Replace existing meteorological station with representative(s) 

of the HUC2 region

 Identify most conservative scenario for use in Step 1 

analyses

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Precipitation in United States

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Selection of Meteorological Stations

 Group all available meteorological stations by HUC 2 and 

estimate cumulative 30-year precipitation value

 Use the meteorological station with the median cumulative 

precipitation value for all HUC 2 regions except where 

there is a large difference in the precipitation values (>3x between min and max stations)

 Where large rainfall difference, estimate the median 

precipitation and select a median station for both the 

highest station group and the lowest station group based 

on cumulative precipitation

 For HUCs 15 and 16, large disparity between the highest 

precipitation station and others. Select highest 

precipitation station, along with the median of the 

remaining stations 

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Downstream EECs (“Downstream Dilution”)

 Step 1 –expand action area to include downstream effects

 Estimate required “dilution factor” using EECs and threshold

 e.g. - EEC for Bin 2 is 10 ppb and threshold is 1 ppb, need to reduce 

EEC at least 90% to get below threshold

 Use NHDplus land cover attributes for chemical to determine 

the distance to reach an overall percent use area below 

EEC/threshold dilution factor

 Step 2 –estimate downstream EECs and evaluate 

exceedance of threshold in listed species habitat

 Use of process similar to Step 1, but look at breakdown of 

percent use areas by use category for each chemical to 

evaluate how each SWCC run impacts species

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Downstream EECs (“Downstream Dilution”)

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Other Considerations

 Mixtures

 Qualitative line of evidence in effects determination

 Consider various sources of information

 Tank mixes/co-formulated products

 CDPR mixture analyses

 Labels and recommended tank mixtures

 Environmental mixtures

 ECOTOX plus pile

 NAWQA concentrations and co-occurrence

 Degradates - oxons

 Total residue method

 Estimate a weighted EEC

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Case Studies Species Info

Shortnose Sturgeon 

(Acipenser brevirostrum)

Category Information

Habitat

Rivers and estuaries along east coast from Canada to Florida

Aquatic bins 3 and 4 (flowing), 6 and 7 (static), 8 and 9 

(estuarine/marine)

Presence in 

Freshwater

Juveniles: first 2-3 years

Adults: late winter / early spring

Reproductive

Timing

Late winter / early spring, depending on location along east 

coast

Diet Juveniles: benthic insects and small crustaceans 

Adults: mollusks and large crustaceans

NMFS Website

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Species 

Location

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Fate Properties - Chlorpyrifos

Parameter (units) Input Value

Molecular Weight (g/mol) 350.57

Water Solubility (mg/L) 20 °C 1.4

Vapor Pressure (torr)

25 °C 1.87x10-5

Henry’s Law Constant

(atm - m3/mol) 6.2 x 10-6 

Hydrolysis Half-life (days) 0

Aqueous Photolysis (days) 29.6

Aerobic Soil Metabolism Half-life (days) 170.6

Aerobic Aquatic Metabolism Half-life (days) 91.2

Anaerobic Aquatic Metabolism Half-life (days) 203

Koc (mL/goc) 6040

 Lab studies - degrades in weeks to months

 Terrestrial studies - dissipates in weeks to months

 Slightly Mobile

 Semi-volatile

 Bioconcentrates, but rapid depuration

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Chlorpyrifos Uses – HUCs 1-3

1. HUCs 1 and 2 only

2. HUCs 2 and 3 only.

3. HUC 3 only

3

2

1

2

2

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Chlorpyrifos Effects Thresholds

Effect 

(endpoint)

Value

(μg/L) Test species Duration of exposure

Mortality 

(1/million) 0.088 HC05 from SSD 96 hours

Sublethal 

(growth) 0.28 Atlantic silverside 28 days

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high end (Rutabaga)

Range of EECs

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0.01

0.1

1

01/0101/0901/1701/2502/0202/1002/1802/2603/0503/1303/2103/2904/0604/1404/2204/3005/0805/1605/2406/0106/0906/1706/2507/0307/1107/1907/2708/0408/1208/2008/2809/0509/1309/2109/2910/0710/1510/2310/3111/0811/1611/2412/0212/1012/1812/26

Day

 

median EECs (golf course) Fish and aquatic-phase amphibian mortality Fish and aquatic-phase amphibian growth

Range of EECs Over Course of Year

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Exposure Considerations

 Relevance of environmental exposure models for generating EECs for 

receiving waterbody habitats

 High certainty in models developed to predict concentrations in species’ habitats

 Less certainty in models that were not developed specifically to address species’ habitats, but adapted to achieve this purpose

 Robustness of fate data used to derive EECs

 High certainty in EECs when a robust fate data set is available

 Less certainty in EECs when an incomplete fate data set is available

 Targeted monitoring data comparable to EECs

 Strengthens the confidence in the values, but lack of targeted monitoring data does not weaken it

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Effects Determination

 Use weight of evidence approach to evaluate exposure and effects data 

for multiple lines of evidence

 Mortality

 Growth

 Reproduction

 Impacts to behavior

 Sensory effects

 Indirect Effects

 Other stressors (chemical and non-chemical)

 Evaluate the overlap of exposure and effects (risk) and the confidence 

in the data (weight) for each line of evidence to arrive at effects 

determination

 Lines of evidence for mortality and growth suggest a likely to adversely affect determination, but a thorough evaluation of all of the lines of 

evidence would need to be done before the analysis is completed

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Questions?

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