sustainable pesticide use practices for the protection of
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Sustainable pesticide use practices for the protection of water resources
Jeffrey Jenkins and Phil JanneyDepartment of Environmental and Molecular ToxicologyAgricultural Experiment Station and Extension Service
Oregon State University
Impact of Agriculture and Forestry on Salmonids in the Pacific Northwest
10/17/2019 2
ESA-listed salmon and steelhead
Oncorhynchus keta
28 Evolutionarily Significant Units
Oncorhynchus nerka
Oncorhynchus mykiss
Oncorhynchus tshawytscha
Oncorhynchus kisutch
Washington Toxics Coalition v EPANinth Circuit Court of Appeals (2001)
EPA failure to consult with NOAA regarding the registration of 54 pesticides.
10/17/2019 3
PNW Stakeholders
• Pesticide users– Industry– Agriculture– Forestry– Rights of Way– Municipal– Residential
• Federal Government• State Government/PSP/WQPMT• Tribes• Land Grant universities• Watershed Councils• Non-Governmental Organizations• Soil and Water Conservation Districts• Irrigation districts• Public
10/17/2019 4
Pacific Salmonid Pesticide Opportunities for Exposure
Salmonid Biology• Life history • Habitat
preference
Pesticide Occurrence• Use practices• Site specific
conditions
5EX
POSU
RE
10/17/2019
Pesticide Surface Water Monitoring in the U.S. and Oregon
• USGS Monitoring• National Water Quality
Assessment Program (NAWQA)
• Clackamas studies
• DEQ/ODA Monitoring• Pesticide Stewardship
Partnership (PSP)• 9 Watersheds• 4 in Willamette Valley
610/17/2019
ESA/FIFRA - National Research Council Review (2013)
• Evaluate current pesticide risk assessment approaches relating to ESA listed species (biological opinions)
• Reach consensus on common risk assessment methods– Modelling/model assumptions– Geospatial information– Characterize effects direct, indirect, sublethal
and cumulative; mixtures and inert ingredients– Characterize uncertainty
710/17/2019
8
Willamette Basin (HUC 4) 12 HUC 8 subbasins388 HUC12 watersheds
Diverse agriculture (170 crop varieties), forestry, urban pesticide use practices
More than 500 pesticide active ingredients registered in Oregon
Pesticide co-occurrence with salmon/food web life histories?
Willamette Basin Salmonid Critical Habitat
10/17/2019
FIFRA/FQPA Federal – State Partnerships designed to Achieve Safe and Beneficial Pesticide Use
Risk characterization through sound
science
Cost effective requirements to insure safe use
Clear understanding
of label restrictions and use mandates
Informed decision-making at the frontline of pesticide use
10/17/2019 9
Scott Hecht, NMFS 10
Pacific Salmonid Biology, Food Web and Critical Habitat
10/17/2019
Fig. 1. Consistent exposure and effect assessment is possible if processes in the environmental system and in the organisms (biological system) are treated with the same modeling structure and tools.
René P. Schwarzenbach et al. Science 2006;313:1072-1077
David Buchwalter
David Buchwalter
Katherine Palmquist
Jason Sandahl
Jason Sandahl
Fig. 1. Consistent exposure and effect assessment is possible if processes in the environmental system and in the organisms (biological system) are treated with the same modeling structure
and tools.
René P. Schwarzenbach et al. Science 2006;313:1072-1077
Risk: Conceptual Framework
Pesticide Use Practices
Human/wildlife Susceptibility and Behavior
RiskOpportunities for Pesticide
Exposure
10/17/2019 13
Sustainable Agriculture and Forestry
• The core concept of sustainability1 is that lasting success requires an integrated approach to:
• producing food, fiber, and other products • farm and forest profitability • quality of life for farmers, foresters, and communities • stewardship of natural resources
• Sustainability requires recognizing and acting upon productivity, economic, social, and environmental goals as a simultaneous set of system attributes.
14
1Brundtland, G. H. (1987). Our Common Future. Annex to U.N. General Assembly document A/42/427.10/17/2019
Technology to Enable Sustainable Production
• Farm/forest operations management• Agronomy/horticulture/animal science/forest science• Pest management/IVM• Nutrient management• Water Management • Natural resource stewardship• Supply chain management• Information management
15
Farm/Forest ProductionSystem
Digital Agriculture and Forestry10/17/2019
WEATHER LAND MANAGEMENT PESTICIDE PROCESSES
NUTRIENT PROCESSES
PRECIPITATION
GROUNDWATER RUNOFF
HYDROLOGY
PESTICIDE PROCESSES
SEDIMENT PROCESSES
NUTRIENT PROCESSES
GROUNDWATERINPUTS
UPSTREAMINPUTS
RUNOFFINPUTS
DOWNSTREAMOUTPUTS
EROSION
HYDROLOGY
CROP GROWTH
WATER MANAGEMENT
Water quality stewardship - conceptual model
Terrestrial ProcessesIn-Stream
Processes
Water Q
uality Monitoring 1610/17/2019
Herbicides Commonly Used in the Pacific Northwest
Trade Common ½ life Koc water sol vapor pressurename name (days) mg/L (mm Hg)Sencor metribuzin 40 60 1220 1.0x10-5Banvel Dicamba (acid) 14 2 400000 3.4x10-5Milestone aminopyralid 35 11 2480 7.1x10-11Garlon trichlopyr 30 210 260 3.0x10-8Dual metolachlor 90 200 530 3.1x10-5Roundup glyphosate 47 24000 530000 02,4-D 2, 4 D acid 10 20 89 1.1x10-72,4-D ester 2,4-D butoxyethyl ester 7 500 100 1.0X10-7Chopper imazapyr 90 100 1100 1.3x10-11Velpar hexazinone 90 54 3300 8.2x10-11Kerb pronamide 60 800 15 8.5x10-5Oust Sulfometuron methyl 28 78 70 1.7x10-16Goal oxyfluorfen 35 100000 0.1 2.0x10-7Prowl pendimethalin 90 500 0.3 9.4x10-6Buctril bromoxynil 7 10000 0.8 4.8x10-6Dachthal DCPA 100 5000 0.5 2.5x10-6
OSU Extension Pesticide Properties Database EM 8709
Pesticide Loss at the Watershed Scale
1810/17/2019
Soil and Water Assessment Tool (SWAT)
19
Conceptual model Process model - computer
Conceptual model
Process model (computer)
ArcSWAT (GIS), use of spatial data (maps)
Describe daily changes in watershed
Pesticides in surface water
Soil and Water Assessment Tool (SWAT)• Watershed scale model1
• Developed by USDA Agricultural Research Service
• Based on over 40 years of expertise
• Developed to evaluate the impact of land management practices on:
• Hydrology• Erosion/Sediment transport• Nutrient fate• Pesticide fate
• Physically based process model that operates on a daily time step
• GIS interface, ArcSWAT, used for spatially explicit parameterization using readily available data
2010/17/2019
Watershed scale modeling of pesticide fate
21
Zollner Creek Watershed, Willamette Basin, Oregon
• HUC12 - 15mi2 watershed
• Watershed area 90% agriculture: > 600 fields, >30 crops
• Pesticide surface water monitoring since 1993 (USGS and Oregon DEQ)
• Contains critical habitat for Upper Willamette chinook and steelhead ESUs
• Weather characterized by dry summers and wet winters
• USGS stream flow gage (Station ID: 14201300)
2210/17/2019
23
J a n -10
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0
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2 5 0
2 0 1 0 -2 0 1 1 O b s e rv e d a n d S W A T E s tim a te dA v e ra g e D a ily S tr e a m F lo w fo r Z o lln e r C r e e k
D a te
Av
era
ge
Da
ily
Str
ea
m F
low
(C
MS
)P
rec
ipita
tion
(mm
)
U S G S O b s e rv e d F lo w (C M S ) C a lib ra te d S W A T E s tim a te d F lo w (C M S ) P re c ip ita tio n (m m )
Flow StatisticsNSE = 0.75PBIAS = -17.1%RSR = 0.25R2= 0.77
SWAT Hydrologic Characterization1
1Janney, P., and J. Jenkins. 2019. A Systems Approach to Modeling Watershed Ecohydrology and Pesticide Transport. J. Environ. Qual. 48:1047-1056.10/17/2019
Characterizing Pesticide Use Patterns
• All authorized uses (federal/state labeled uses)
• Actual use records • Proprietary • Logistically difficult• Retrospective
• Probabilistic methods based on local knowledge• Realistic boundary conditions (pest management
along crop timelines)• Characterize complex decision making process
(producers, CCAs, Extension)• Both retrospective and prospective – evaluate future
outcomes24
Labels for Oregon – PICOL database
Collaborate with CCAs and growers to refine use
estimates
Create boundary conditions for probabilistic analysis of
application practices
10/17/2019
10/17/2019 25
Atrazine Authorized Use in the Zollner Creek Watershed
10/17/2019 26
Chlorpyrifos Authorized Use in the Zollner Creek Watershed
10/17/2019 27
Trifluralin Authorized Use in the Zollner Creek Watershed
Trifluralin Use - PNW Herbicide Handbook • Pre-plant soil incorporated:
• Broccoli: May-July; 0.5-1 lb AI/A; 3-4” incorporation• Cauliflower: May-July; 0.5-1 lb AI/A; 3-4” incorporation• Green beans: May-July; 0.5-0.75 lb AI/A; 2-3” incorporation• Peas: May-July; 0.5-0.75 lb AI/A; 1-2” incorporation
• Spring pre-emergent:• Caneberries (nonbearing): March-April; 2.5-5lb AI/A; activate
with single rain event or 0.5” irrigation or mechanically incorporate
• Field grown nursery: March-April; 2-5lb AI/A; activate with single rain event or 0.5” irrigation or mechanically incorporate
• Filberts: March-April; 0.5-1lb AI/A; activate with single rain event or 0.5” irrigation or mechanically incorporate
• Fall pre-emergent:• Alfalfa: September-October; 2lb AI/A; activate with single rain
event or 0.5” irrigation or mechanically incorporate• Grass seed: September-October; 2lb AI/A; activate with single
rain event or 0.5” irrigation or mechanically incorporate• Winter wheat: October-November; 0.5-1lb AI/A; activate with
single rain event or 0.5” irrigation or mechanically incorporate 2810/17/2019
Probabilistic Assessment of Application Patterns
• Management operations randomized by field• Applications limited to workable days• Application rates were both probabilistic and deterministic• Pesticides Properties DataBase1 representative values
• Monte Carlo methods utilized to create spatial and temporal distribution of application patterns
• 500 SWAT scenarios generated and run
• Generate a distribution of spatial and temporal patterns of pesticide use practices
• Estimate likely pesticide use patterns
291 PPDB: Pesticide Properties DataBase, University of Hertfordshire.10/17/2019
Generalized (not actual) Distribution of ChlorpyrifosApplications - 2011
CROP TYPE # POTENTIAL APPLICATION SITES
APPLICATION PERIOD
PROBABILITY OF APPLICATION
# WORKABLE
DAYS
Seed/Sod Grass 82 Sept-Oct 0.1 15Nursery 35 Apr-July 0.4 36
Orchard 3 Mar-Apr 0.75 123 May-Aug 0.1 54
Vegetable
2 Apr-May 1 1410 Apr-June 1 167 May-July 1 331 June-July 1 231 Aug-Sept 1 30
1 of 500 daily simulations
10/17/2019 30
SWAT Estimates of Daily Chlorpyrifos Concentration
31
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Oc t-1
0
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0
2 0
4 0
6 0
8 0
1 0 02 0 0
2 5 0
3 0 0
3 5 0
4 0 0
4 5 0
5 0 0 0
2 0
4 0
6 0
8 0
1 0 0
1 2 0
1 4 0
1 6 0
1 8 0
2 0 0
D a ily S W A T E s t im a te d C h lo rp y r ifo s C o n c e n tra t io n s : 2 0 1 0
D a te
Ch
lorp
yri
fos
Co
nc
en
tra
tio
n (
ng
/L)
Pre
cip
itatio
n (m
m)
S W A T M e a n D a ily C o n c e n tra t io n (n g /L ) D E Q C h lo rp y r ifo s (n g /L )N o n -d e te c ts
O P P A c u te In v e r t e b r a t e B e n c h m a r k
O P P C h r o n ic In v e r t e b r a t e B e n c h m a r k
P re c ip ita t io n (m m )
J a n -11
F e b -11
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0
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D a ily S W A T E s t im a te d C h lo rp y r ifo s C o n c e n tra t io n s : 2 0 1 1
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lorp
yri
fos
Co
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ng
/L)
Pre
cip
itatio
n (m
m)
S W A T M e a n D a ily C o n c e n tra t io n (n g /L ) U S G S C h lo rp y r ifo s (n g /L )
D E Q C h lo rp y r ifo s (n g /L )N o n -d e te c ts
O P P A c u te In v e r t e b r a t e B e n c h m a r k
O P P C h r o n ic In v e r t e b r a t e B e n c h m a r k
P re c ip ita t io n (m m )
10/17/2019
SWAT Estimates of Daily Atrazine Concentration
10/17/2019 32
Jan -1
0
Ma r -1
0
A p r -10
Ma y -1
0
Jun -1
0
Jul-1
0
A u g -10
S e p -10
Oc t -1
0
N o v -10
D e c -10
0
1 0 0
2 0 0
3 0 0
4 0 0 0
1 0 0
2 0 0
3 0 0
2 0 1 0 Z o lln e r C re e k S W A T E s t im a te d
A v e r a g e D a ily A tra z in e S u r fa c e W a te r C o n c e n tr a t io n
D a t e
Atr
azi
ne
Co
nce
ntr
ati
on
(n
g/L)
Pre
cipita
tion
(mm
)
P r e c ip it a t io n (m m )
O b s e r v e d A tr a z in e C o n c e n tr a t io n s (n g / L )
M e a n S W A T E st im a te d C o n c e n tr a t io n (n g / L )
G r e y A re a = 5 th -9 5 th p e r c e n t ile
Jan -1
1
F e b -11
Ma r -1
1
A p r -11
Ma y -1
1
Jun -1
1
Jul-1
1
A u g -11
S e p -11
Oc t -1
1
N o v -11
D e c -11
0
1 0 0
2 0 0
3 0 0
4 0 0
0
1 0 0
2 0 0
3 0 0
1 0 0 0
2 0 0 0
3 0 0 0
4 0 0 0
5 0 0 0
2 0 1 1 Z o lln e r C re e k S W A T E s t im a te d
A v e r a g e D a ily A tra z in e S u r fa c e W a te r C o n c e n tr a t io n
D a t e
Atr
azi
ne
Co
nce
ntr
ati
on
(n
g/L)
Pre
cipita
tion
(mm
)
M e a n S W A T E st im a te d C o n c e n tr a t io n (n g / L )
G r e y A re a = 5 th -9 5 th p e r c e n t ile
O b s e r v e d A t r a z in e C o n c e n tr a t io n (n g / L )
P r e c ip it a t io n (m m )
OPP Acute Nonvascular Plant Benchmark: 1000 ng/LOPP Chronic Fish Benchmark: 5000 ng/L
OPP Acute Nonvascular Plant Benchmark: 1000 ng/LOPP Chronic Fish Benchmark: 5000 ng/L
SWAT Estimates of Daily Trifluralin Concentration
10/17/2019 33
0 3 0 6 0 9 0 1 2 0 1 5 0 1 8 0 2 1 0 2 4 0 2 7 0 3 0 0 3 3 0 3 6 00
2 0
4 0
6 0
8 0
1 0 0
1 2 0
1 4 0
1 6 0
1 8 0
2 0 0
2 2 0 0
5 0
1 0 0
1 5 0
2 0 0
2 0 1 0 T r if lu ra lin D a ily C o n c e n tra t io n E s t im a te s
J D
Tri
flu
rali
n C
on
ce
ntr
ati
on
(n
g/L
)
Precip
itatio
n(m
m)
D E Q G ra b S a m p le N o n D e te c ts (n g /L )
S W A T M e d ia n D a ily T riflu ra lin C o n ce n tra tio n (n g /L ) P re c ip ita tio n (m m )
0 3 0 6 0 9 0 1 2 0 1 5 0 1 8 0 2 1 0 2 4 0 2 7 0 3 0 0 3 3 0 3 6 00
2 0
4 0
6 0
8 0
1 0 0
1 2 0
1 4 0
1 6 0
1 8 0
2 0 0
2 2 0 0
5 0
1 0 0
1 5 0
2 0 0
2 0 1 1 T r if lu ra lin D a ily C o n c e n tra t io n E s t im a te s
J D
Tri
flu
rali
n C
on
ce
ntr
ati
on
(n
g/L
)
Precip
itatio
n(m
m)
U S G S G ra b S a m p le D e te c ts (n g /L )D E Q G ra b S a m p le N o n D e te c ts (n g /L )
S W A T M e d ia n D a ily T riflu ra lin C o n ce n tra tio n (n g /L ) P re c ip ita tio n (m m )
OPP Acute Fish Benchmark: 9250 ng/LOPP Chronic Fish Benchmark: 1900 ng/L
OPP Acute Fish Benchmark: 9250 ng/LOPP Chronic Fish Benchmark: 1900 ng/L
Passive Sampling Device 21 day Time Weighted Average Pesticide Concentrations in Surface Water
34
Lay Flat Tubing (LFT) passive samplers deployed continuously every ~21 days
J a n- 1
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2 0 1 0 - 2 0 1 1 Z o l l n e r C r e e k S i m u l a t e d a n d O b s e r v e d
C h l o r p r y i f o s T i m e - W e i g h t e d A v e r a g e C o n c e n t r a t i o n s ( n g / L )
D a t e
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itatio
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m)
L F T C h lo r p y r i f o s C o n c e n t r a t i o n ( n g / L )
O P P A c u t e I n v e r t e b r a t e B e n c h m a r k
O P P C h r o n i c I n v e r t e b r a t e B e n c h m a r k
P r e c i p i t a t i o n ( m m )
D E Q N o n d e t e c t C h l o r p y r i f o s G r a b S a m p l e s ( n g / L )
U S G S D e t e c t C h lo r p y r i f o s G r a b S a m p l e s ( n g / L )10/17/2019
10/17/2019 35
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0
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1
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1
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0
5
1 0
1 5
2 0
2 54 0
4 5
5 0
5 5
6 0 0
5 0
1 0 0
1 5 0
2 0 0
2 0 1 0 -2 0 1 1 Z o lln e r C re e k S im u la te d a n d O b s e rv e dC h lo rp ry ifo s T im e -W e ig h te d A v e ra g e C o n c e n tra t io n s (n g /L )
D a te
Ch
lorp
yri
fos
Tim
e-W
eig
hte
d A
ve
rag
e C
on
ce
ntr
ati
on
(n
g/L
)
Pre
cip
itatio
n (m
m)
L F T C h lo rp y r ifo s C o n c e n tra t io n (n g /L )
O P P A c u te In v e r t e b r a t e B e n c h m a r k
O P P C h r o n ic In v e r t e b r a t e B e n c h m a r k
9 5 th P e rc e n tile S W A T C h lo rp y r ifo s C o n c e n tra to n (n g /L )
5 th P e rc e n t ile S W A T C h lo rp y rifo s C o n c e n tra to n (n g /L )
M e d ia n S W A T C h lo rp y r ifo s C o n c e n tra to n (n g /L )
P re c ip ita t io n (m m )
D E Q N o n d e te c t C h lo rp y rifo s G ra b S a m p le s (n g /L )
U S G S D e te c t C h lo rp y rifo s G ra b S a m p le s (n g /L )
10/17/2019 36
J a n -10
F e b -10
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J a n -11
F e b -11
Ma r -1
1
A p r -11
Ma y -1
1
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J u l-11
A u g -11
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Oc t-1
1
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D e c -11
0
1 0
2 0
3 0
4 0
5 0
6 0 0
5 0
1 0 0
1 5 0
2 0 0
L F T a n d S W A T E s t im a te d T im e -W e ig h te d A v e ra g eC o n c e n tr a t io n s o f T r if lu ra lin
D a te
Tri
flu
rali
n C
on
ce
ntr
ati
on
(n
g/L
)P
rec
ipita
tion
(mm
)
L F T T riflu ra lin C o n ce n tra tio n (n g /L )
U S G S T riflu ra lin G ra b S a m p le D e te c ts (n g /L )
D E Q T riflu ra lin G ra b S a m p le N o n D e te c ts (n g /L )
9 5 th P e rc e n tile S W A T T rif lu ra lin C o n c e n tra tio n (n g /L )
5 th P e rc e n tile S W A T T riflu ra lin C o n c e n tra t io n (n g /L )
M e d ia n S W A T T riflu ra lin C o n ce n tra tio n (n g /L )
P re c ip ita tio n (m m )
O P P F is h A c u te B e n c h m a r k : 9 2 5 0 n g /LO P P F is h C h r o n ic B e n c h m a r k : 1 9 0 0 n g /L
Transferability of Watershed Assessment Framework
10/17/2019 37
South Yamhill Forest Watersheds
OSU application of SWAT:Integrate Institutional knowledge/local expertise Evaluate forestry IVM/herbicides in surface waterEstimate daily loading – benchmark exceedancesInform best management practices/success stories
Fostering sustainable practices through participative modeling
39
OSU Extension Watershed Assessment Framework
(powered by SWAT)
Local knowledge and expertise
Institutional knowledge and expertise
Rapid evaluation of sustainable practices
Demonstrated Stewardship10/17/2019
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