This document discusses using the PRZM model to evaluate the effectiveness of best management practices (BMPs) for reducing atrazine concentrations in surface runoff from agricultural fields in the MO-07 watershed. The PRZM model was used to predict hydrology, atrazine concentrations, and the impact of soil incorporation and split atrazine application on reducing surface runoff concentrations. Model results showed that soil incorporation reduced predicted atrazine concentrations by around 43% on average, while split applications showed more variable effectiveness.

1. PRZM to Predict Hydrology, Atrazine
Concentrations, & BMP Effectiveness
Lula Ghebremichael, Clint Truman, Sunmao Chen, Mark White
Syngenta Crop Protection, LLC
SWCS 2015 Conference July 26- 29, 2015, Greensboro, NC

2. 2
Outline
● Goal
● Model description
● MO-07 watershed
● Model performance
● BMP effectiveness
Classification: Public

3. 3
Goal
Evaluate BMPs using a modeling approach to select effective BMPs
and enhance stewardship programs
Classification: Public

4. 4
Model Description
● PRZM (Pesticide Root Zone Model)
● Developed by U.S.EPA (Carsel et. al.1985)
● Official core model for pesticide registration at U.S. EPA
Classification: Public
Hydrological & Erosion Processes
Surface runoff SCS curve number
Water balance (Inflow = Outflow + ΔStorage)
Erosion MUSLE
Pesticide Processes
Application method Various methods
Partitioning (Sorption/desorption) Equilibrium; Linear
Degradation First-order
Plant Uptake, Runoff, Erosion, Volatilization, Foliar Wash-off
ModelFeatures

5. 5
PRZM Application for Regulatory Environmental Exposure
Assessment
● Runoff Events and Pesticide loading  Pesticide Concentration in
Standard pond
● Pesticide mass predicted for Runoff Events only
Classification: Public
PRZM EXAMS
1 hectare
(2 m pond)
10 hectare
field area

6. 6
PRZM Application On MO-07 Watershed
Classification: Public
PRZM Model
Atrazine mass from
runoff events (multiple
fields in a watershed)
Stream flow “measured”
Atrazine Concentration

7. 7
PRZM Model Inputs
Classification: Public
Land use
Soil Inputs
Precipitation (cm/day)
Pan evaporation data (cm/day)
Temperature (Celsius)
Wind speed (cm/sec)
Solar radiation (Langley)
Weather
Chemical
Legend
OM_MO07N_proj
SdvOutpu_1
1.25 - 1.5
1.50 - 2.0
2.00 - 2.4
2.4 - 2.6
2.60 - 3.0
Legend
BD_MO07N_proj
SdvOutpu_1
1.29-1.31
1.31-1.4
1.4-1.480
Legend
ST_MO07N_proj
(Surface Layer), {DCD, <}
Clay loam
Fine sandy loam
Loam
Loamy sand
Sandy loam
Silt loam
Silty clay loam
Not rated or not available
BDOM Texture

8. 8
Model Evaluations
Classification: Public
Hydrology Atrazine concentrations
Lack of field-level data for model evaluation
Runoff events aggregated from watershed
compared to “measured runoff” (baseflow
separation)

9. 9
Predicted Atrazine Concentration: 2010-2014
Limitations
● Incomplete to reflect stream
flow concentrations
● Used single atrazine
application date for all fields
in the watersheds
● Need to use crop planting
progress data to schedule
application dates across corn
fields
● Runoff timing and travel time
Classification: Public

10. 10
Best Management Practices Modeled
● Soil Incorporation (e.g. Phillips Harrow  spray followed by
incorporation in one pass, ~ 5 cm incorporation depth and complete
mixing)
● Split application (pre-, post-emergence)
Classification: Public

11. 11
Model Predicted BMPs Effectiveness
Classification: Public
Concentration vs. Mass
2010
2011
2012
2013
2014
Concentration vs. Mass

12. 12
Summary
● PRZM performances in predicting hydrology and atrazine concentration
- incomplete picture of flow and atrazine conc. in streams
- may be beneficial to add baseflow, runoff timing & travel time
components
- need refinement to model inputs (e.g. application date; rainfall)
● PRZM application for assessing BMPs effectiveness
- relative BMPs effectiveness at field-level in surface runoff
- limited number of BMP can be assessed
● BMP effectiveness
- incorporation (~43%); split application (~ variable)
- concentration vs. mass
Classification: Public