CropLife America & RISE Spring Conference
Crystal City, Virginia
Mark Corbin
Office of Pesticide Programs
April 23, 2015
Overview
 Tiered Approach
 Current Models
 Future Directions
 Monitoring Data
 Refinements
The Problem: Large Area to Assess
Tiered Assessment Process
Assessment Uncertainties and Risk Management Decisions
Low spatial
and temporal resolution
General assessment
endpoints
Deterministic
Ecological Risk Assessment
PROBLEM FORMULATION
ANALYSIS
Characterization
of
Characterization
of
Exposure
Ecological
Effects
Ecological Risk Assessment
PROBLEM FORMULATION
RISK CHARACTERIZATION
ANALYSIS
Characterization
of
Characterization
of
Exposure
Ecological
Effects
Ecological Risk Assessment
PROBLEM FORMULATION
RISK CHARACTERIZATION
ANALYSIS
Characterization
of
Characterization
of
Exposure
Ecological
Effects
RISK CHARACTERIZATION
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Site-specific
resolution
Species/habitatspecific endpoints
Probabilistic
Tier 1 Single Scenario
Pass
Fail
General concept: Single high-exposure
scenario used to determine whether
potential exceedance of level of concern
exists
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Not necessarily single scenario…
National/regional
Standard corn scenarios
 Some no
longer run
single
scenario
screen
 Screening
approach
changing,
but
multiple
scenarios
are for
different
purposes
Scenarios developed for
cumulative assessments
6
Current Models
 PRZM-GW
 Surface Water Concentration Calculator
(SWCC)
 PRZM Update
 Variable Volume Water Model (VVWM)
 Pesticide in Flooded Applications Model
(PFAM)
 E-FAST
 KABAM
 AgDrift
Tier 2 Groundwater Conceptual Model
Simulated Concentrations
Non targeted NAWQA Data
Observed Concentrations
Targeted Prospective Groundwater Study with
Known Use
PGW Max = 4.55 ppb
PRZM GW Context
Karst
Unconsolidated Aquifers
Implementation Results
 One year period to evaluate by running both SciGrow
and PRZM GW
 43 DWA conducted during this period
 8 chemicals indicated some risk at Tier I
 Of these, 5 were due to groundwater concerns and were
result of PRZM GW outputs
 Of these 5, 4 were of concern because of inclusion of
degradates using a total toxic residues (TTR) approach
 All 5 were based on long term (e.g. chronic) exposure
concerns
 Only 1 chemical failed the Tier I solely because of PRZM
GW
Surface Water Concentration Calculator
(SWCC)
 Replacement for PE5 & EXPRESS
 Current PRZM/EXAMS user interfaces
 Incorporates updated version of PRZM (version 5.0)
 Faster version of PRZM
 Incorporates Variable Volume Water Model (VVWM)
 Taken to SAP in support of SWAMP model
 Allows for multiple receiving water body configurations
and flow regimes
 Improved graphical user interface
 Compatible with Windows 7
PRZM & EXAMS OVERVIEW
Runoff Pesticide ( only top 2 cm)
Volatilization
Washout
2 cm
Hydrolysis,
Biodegradation
Eroded Pesticide
(only from top 0.1 cm)
2m
Inter-Compartment
Mass Transfer
Benthic region
0.05 m
Pond Scenario and Reservoir Scenario
10 hA
172 hA
1 ha
No Outflow
5.2 hA
Outflow
Other Aquatic Models
 Pesticides in Flooded Agriculture Model (PFAM)
 Replaces Tier I Rice Model
 Currently developed for estimates in paddy water
 E-fast
 Developed by OPPT
 OPP uses Down the Drain component for selected
indoor uses
 KABAM
 Estimates pesticide concentrations for compounds with
Log Kow between 4 to 8 in tissues of aquatic organisms
resulting from bioaccumulation
 AgDrift
On-going Efforts
 PFAM DW
 Builds on current version
 Considers paddy water released into flowing waters
 Audrey III
 Replaces and upgrades current plant exposure model
 Three modules (terrestrial, semi-aquatic, & aquatic)
 Spatial Aquatic Model (SAM)
 GIS based modeling that relies on PRZM and VVWM
 Replaces place based scenarios with spatially
referenced estimates of aquatic exposure at the
national, regional and local scale for both drinking
water and ecological risk
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EFED Conceptualization of Field/Water Body
Event-Based Runoff
from Non-Rice Areas
Rice Field
Index Reservoir
(large body,
relatively little
flow)
Runoff Generated
By Rice Areas
Semi-Aquatic Plant Conceptual Model
10 Hectare field
100% Treated
(PRZM)
Runoff,
Sediment, &
Pesticide
1 hectare
water body
Water +
Pesticide
water body
(VVWM or PFAM)
19
Depth
= 15 cm
What We Want In a Spatial Model
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How SAM Differs from the Current Aquatic
Screening Approach
(a) Current Approach:
Single, uniform watershed
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(b) Soil map – land cover patterns
In SAM
Example Output: Frequency of Exceeding Toxicity
Threshold
Percent of HUC12s
exceeding the
toxicity threshold
for the pilot area in
any given year:
Max
+1 SD
Avg
- 1 SD
Min
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14.7%
10.8%
8.0%
5.3%
2.0%
Monitoring Overview
 OPP makes use of all reliable monitoring data it is aware of
 Data sources include federal, state, academic, and other





sources
Data varies tremendously in quality
How the monitoring results are used depends upon the
nature of the data
Ancillary data enables interpretation of monitoring results
Monitoring and modeling generally complement each
other, strengthen assessment
OPP Guidance on Evaluation and Use of Monitoring Data
 http://www2.epa.gov/pesticidereevaluation/evaluation-and-use-water-monitoringdata-pesticide-aquatic-exposure
Quantitative vs Qualitative Use of Monitoring Data
 Issues to consider
 Was the study targeted to the use pattern?
 Was the use pattern (i.e., application method) representative of the






use pattern?
Was the study targeted to the time of application?
Was the sample frequency relevant to the endpoint of concern (e.g.,
daily vs weekly relative to acute risk)?
Was the study conducted at a time of unusual weather conditions
(e.g., drought)?
Was the study conducted in water bodies relevant to the issue of
concern (e.g., flowing water vs. static)?
Were the analytical detection limits relevant to the toxicity endpoint?
Was the study conducted to capture a range of use patterns (range in
intensity vs. high-use, high-ag)?
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Current Efforts to Characterize Pesticide
Occurrence in Surface Water
 Complex spatial patterns
 Related to pesticide use, rainfall patterns, soil/hydrologic
vulnerabilities
 Complex temporal patterns
 Often low or non-detectable levels
 Infrequent sampling
 Year-to-year variation related to cropping patterns,
pesticide usage, rainfall patterns, climate change
 Temporal autocorrelation
 OPP evaluating multiple approaches to characterize
uncertainty in estimates from monitoring data
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Uncertainty Analysis
 EPA analysis of sample frequency began in late 2000’s and
was presented to several SAP
 Goal is to address uncertainty associated with capturing
peak concentrations from monitoring data sampled
infrequently
 Leverage existing daily data sets to evaluate impact of less
than daily sample frequencies (e.g. weekly) relative to
various durations of concern (e.g. peak)
 Techniques under consideration will include
 Bias Factors (presented at SAP)
 Kriging/Sequential Stochastic Simulations
 SEAWAVEQ Regression Modeling
 Ultimate goal is to include uncertainty predictions into
estimation of exposure from monitoring data
Modeling Refinements
 Examples of refinement include
 Geographic variability (multiple scenarios)
 Regional PCA (SW only)
 Typical rates (lbs/acre and no. of apps)
 Timing
 Degradates (whether to include)
 Fate data gaps and how to select inputs
 Treatment effects (if data available)
 PCT for SW (not there yet)
 GW well setbacks & subsurface processes
(degradation and flow rates)
Questions?
[email protected]
703-605-0033