Document ID: EPA-HQ-OPP-2002-0249-0006
Agency: epa
Document Type: Supporting & Related Material
Title: 
Posted Date: 2002-10-01T04:00Z

UNITED
STATES
ENVIRONMENTAL
PROTECTION
AGENCY
WASHINGTON,
D.
C.
20460
OFFICE
OF
PREVENTION,
PESTICIDES
AND
TOXIC
SUBSTANCES
PC
Code:
035505
DP
Barcode:
D275046
MEMORANDUM
August
27,
2001
SUBJECT:
Drinking
Water
Assessment
for
diuron
and
its
degradates
TO:
Diana
Locke
Reregistration
Actions
Branch
II
Health
Effects
Division
(
7509C)

FROM:
Ibrahim
Abdel­
Saheb/
Agronomist
Environmental
Risk
Branch
II
Environmental
Fate
and
Effects
Division
(
7507C)

PEER
REVIEW:
Sid
Abel/
Environmental
Scientist
Environmental
Risk
Branch
II
Environmental
Fate
and
Effects
Division
(
7507C)

THRU:
Tom
Bailey,
Branch
Chief
Environmental
Risk
Branch
II
Environmental
Fate
and
Effects
Division
(
7507C)

CONCLUSIONS
The
memorandum
transmits
the
estimated
drinking
water
concentrations
for
use
in
the
human
health
risk
assessment.
Griffin
Label
(
EPA
Reg.
No.
1812­
362)
was
used
to
determine
the
estimated
concentrations.

The
Tier
II
screening
models
PRZM1
and
EXAMS2
with
the
Index
2
Reservoir
and
Percent
Crop
Area
adjustment
was
used
to
determine
estimated
surface
water
concentrations
of
diuron
and
its
degradates
dichlorophenylmethylurea
(
DCPMU);
dichlorophenylurea
(
DCPU);
3,4­
dichloraniline
(
3,4­
DCA);
and
N'­(
3­
chlorophenyl)­
N­
Ndimethylurea
(
mCPDMU).
The
Screening
Concentration
in
Groundwater
(
SCI­
GROW3)
model
was
used
to
estimate
groundwater
concentrations
for
Diuron
and
its
degradates.
Modeling
results
are
shown
in
Table
1.

Table
1.
Estimated
environmental
concentrations
in
surface
and
groundwater
for
diuron
and
its
degradates
use
on
citrus.

Toxicity
end
point
model
EECs
(
F
g/
L)
use(
s)
modeled
PCA
Diuron
DCPMU
DCPU
3,4­
DCA
mCPDMU
one
application
of
diuron
on
citrus
@
9.6
lb
ai/
acre,
ground
application
Default
(
0.87)

Surface
water/
peak
1083
48.2
1.91
0.05
58.9
Surface
water/
1­
10­
year
average)
251
8.44
0.33
0.003
13.5
Surface
water/
mean
of
annual
values)
146
5.98
0.24
0.002
9.22
Groundwater/
(
peak
and
long­
term
average)
6.52
2.50
0.09
2X10­
4
0.30
The
IR­
PCA
modeling
results
indicate
that
diuron
and
its
degradates
have
the
potential
to
contaminate
surface
waters
by
runoff
in
areas
with
large
amounts
of
annual
rainfall.
The
degradate
3,4­
DCA
is
commonly
seen
in
surface
water
in
areas
with
high
diuron
and
propanil
usage,
however,
EFED
has
received
no
guideline
studies
on
the
environmental
fate
and
transport
of
3,4­
DCA
or
other
degradate
of
diuron.
EFED
believes
that
additional
studies
are
needed
to
fully
understand
both
the
fate
and
transport
of
these
compounds
in
the
environment.

Modeling
results
were
higher
EECs
than
data
from
existing
diuron
surface
water
monitoring
data
targeted
to
the
pesticide
use
area.
Modeling
values
where
several
magnitude
(
ranging
from
9­
100
times)
higher
than
monitoring
data.

Major
degradates
that
were
determined
by
HED
to
be
of
toxicological
concern
include:
dichlorophenylmethylurea
(
DCPMU),
3
dichlorophenylurea
(
DCPU),
3,4­
dichloroaniline
(
3,4­
DCA),
and
N'­(
3­
chlorophenyl)­
N­
N­
dimethylurea
(
mCPDMU)].
Because
the
EFED
lacks
complete
environmental
fate
data
(
such
as
the
aerobic
aquatic
and
anaerobic
aquatic
studies)
on
any
of
these
degradates,
this
memorandum
addresses
the
estimated
environmental
concentrations
(
EEC's)
for
surface
and
groundwater
based
on
half­
lives
that
were
calculated
on
cumulative
residues.

Usage
map
for
diuron4
is
attached.

Surface
Water
Monitoring
The
EFED
has
targeted,
but,
limited
monitoring
data
on
the
concentrations
of
diuron
and
its
degradates
in
surface
water.

A
study
on
the
occurrence
of
cotton
herbicides
and
insecticides
in
Playa
lakes
of
the
high
plains
of
western
Texas
concluded
that
diuron
was
the
major
pesticide
detected
in
water
samples
collected
from
32
lakes
with
a
mean
concentration
of
2.7
ppb.
Diuron
metabolites
(
DCPMU,
DCPU,
and
3,4­
DCA)
were
found
in
71%
of
the
samples
analyzed.
The
mean
concentrations
of
these
metabolites
were
0.45
ppb
for
DCPMU,
0.31
ppb
for
3,4­
DCA,
and
0.2
ppb
for
DCPU5.
In
this
study,
water
samples
were
taken
within
two
days
after
diuron
application
to
cotton
in
the
region.
Diuron
usage
on
cotton
in
this
part
of
the
state
reached
an
average
of
$
1379
lb
ai/
mile2/
yr.
Even
though,
the
monitoring
of
diuron
concentrations
from
use
on
Cotton
in
this
part
of
the
state
is
an
example
of
targeted
study,
the
frequency
of
surface
water
sampling
and
the
length
of
sampling
period
were
insufficient
to
satisfy
the
temporal
and
spatial
requirements
for
regulatory
purposes.
This
study
has
limited
use
in
a
national
assessment
because
we
do
not
expect
western
Texas
to
be
one
of
the
most
vulnerable
use
areas
for
runoff.
However,
because
the
samples
were
taken
within
two
days
after
application,
the
results
may
represent
a
lower
bound
of
possible
peak
concentrations
that
could
occur
in
drinking
water
in
that
area.

The
US
Geological
Survey
(
USGS)
National
Water
Quality
Assessment
Program
(
NAWQA)
collected
1420
surface
water
samples
4
from
62
agricultural
stream
sites
during
the
period
from
1992­
1998.
One
to
two
samples
was
collected
each
month
during
periods
when
pesticide
transport
in
the
streams
was
expected
to
be
low
throughout
the
year.
At
most
sites,
the
sampling
frequency
was
increased
to
1
to
3
samples
per
week
during
periods
when
elevated
levels
of
pesticides
were
expected
in
the
streams.
Diuron
was
detected
in
7.32%
of
the
samples
(
detection
limit
=
0.05
ppb)
with
concentration
of
0.13
ppb
in
95%
of
samples.
Diuron
maximum
concentration
was
13
ppb
(
estimated
concentration)
6.

Modeling
Tier
II
surface
water
modeling
was
done
using
the
Index
Reservoir
(
IR)
and
Percent
Crop
Area
(
PCA)
modifications
to
PRZM
and
EXAMS.

The
index
reservoir
represents
a
potential
vulnerable
drinking
water
source
from
a
specific
area
(
Illinois)
with
specific
cropping
patterns,
weather,
soils,
and
other
factors.

The
PCA
is
a
generic
watershed­
based
adjustment
factor
which
represent
the
portion
of
a
watershed
planted
to
a
crop
or
crops
and
will
be
applied
to
pesticide
concentrations
estimated
for
the
surface
water
component
of
the
drinking
water
exposure
assessment
using
PRZM/
EXAMS
with
the
index
reservoir
scenario7.

The
IR­
PCA
PRZM/
EXAMS
model
use
and
fate
input
parameters
for
diuron
and
its
degradates
in
surface
water
are
shown
in
Tables
2­
6.
The
IR­
PC
PRZM/
EXAMS
model
input
and
output
files
for
diuron
and
its
degradates
are
shown
in
Appendix
I.
5
Table
2:
IR­
PC
PRZM/
EXAMS
input
parameters
for
diuron.

Input
variable
Input
value
&
calculations
Source/
Quality
of
data
Crop
name
citrus
label
(
EPA
Reg.
No.
1812­
362).

application
rate
(
lb
ai/
acre)
9.6
label
(
EPA
Reg.
No.
1812­
362).

Application
efficiency
0.99
IR­
PC
Guidance7
Spray
drift
fraction
0.064
IR­
PC
Guidance
Application
method
ground
label
(
EPA
Reg.
No.
1812­
362).

DWRATE
(
day­
1)
0.002
MRID#
41719303;
Input
parameters
guidance8
DSRATE
(
day­
1)
0.002
MRID#
41719303;
Input
parameters
guidance
Kd
(
mL/
g)
14
MRID#
44490501;
Input
parameters
guidance
Henry
(
atm.
m3/
mole)
2.2X10­
10
(
calculated)
Product
Chemistry
chapter
for
HED
RED,
2001.

KBACW
(
h­
1)
7.6X10­
5
No
aerobic
aquatic
data
is
available,
the
aerobic
soil
met.
t
½
was
multiplied
by
0.5.
MRID#
41719303.
Input
parameters
guidance.

KBACS
(
h­
1)
5.8X10­
5
No
anaerobic
aquatic
data
is
available,
the
anaerobic
soil
met.
t
½
was
multiplied
by
0.5.
MRID#
41418806.
Input
parameters
guidance.

KDP
(
h­
1)
6.7X10­
4
MRID#
41418805;
Input
parameters
guidance.

KBH,
KNH,
KAH
(
h­
1)
0
(
stable)
MRID#
41418804.
6
KPS
(
mL/
g)
14
MRID#
44490501;
Input
parameters
guidance.

MWT
(
g/
mole)
233.1
The
MERCK
INDEX9
Solubility
@
25
0C
(
ppm)
420
Product
Chemistry
chapter
for
HED
RED,
2001;
Input
parameters
guidance.

Vapor
pressure
(
torr)
2.0X10­
7
Product
Chemistry
chapter
for
HED
RED,
2001.
7
Table
3:
IR­
PC
PRZM/
EXAMS
input
parameters
for
DCPMU.

Input
variable
Input
value
&
calculations
Source/
Quality
of
data
Crop
name
citrus
label
(
EPA
Reg.
No.
1812­
362).

application
rate
(
lb
ai/
acre)
2.03
label
(
EPA
Reg.
No.
1812­
362).
An
equivalent
value
based
on
maximum
conversion
of
diuron
to
degradates
and
the
molecular
weight
ratio
adjustment.

Application
efficiency
0.99
IR­
PC
Guidance7
Spray
drift
fraction
0.064
IR­
PC
Guidance
Application
method
ground
label
(
EPA
Reg.
No.
1812­
362).

DWRATE
(
day­
1)
0.009
MRID#
41719303;
Input
parameters
guidance8
DSRATE
(
day­
1)
0.009
MRID#
41719303;
Input
parameters
guidance
Kd
(
mL/
g)
for
diuron:
14
MRID#
44490501;
Input
parameters
guidance
Henry
(
atm.
m3/
mole)
for
diuron:
2.2X10­
10
(
calculated)
Product
Chemistry
chapter
for
HED
RED,
2001.

KBACW
(
h­
1)
for
diuron:
0.0003
No
aerobic
aquatic
data
is
available,
diruon­
t
½
was
multiplied
by
3,
MRID#
41719303.
Input
parameters
guidance.

KBACS
(
h­
1)
for
diuron:
0.002
No
anaerobic
aquatic
data
is
available,
the
anaerobic
soil
met.
t
½
was
multiplied
by
0.5.
MRID#
41418806.
Input
parameters
guidance.

KDP
(
h­
1)
for
diuron:
0.0007
MRID#
41418805;
Input
parameters
guidance.

KBH,
KNH,
KAH
(
h­
1)
for
diuron:
0
(
stable)
MRID#
41418804.

KPS
(
mL/
g)
for
diuron:
14
MRID#
44490501;
Input
parameters
guidance.

MWT
(
g/
mole)
233.1
The
MERCK
INDEX9
Solubility
@
25
0C
(
ppm)
for
diuron:
420
Product
Chemistry
chapter
for
HED
RED,
2001;
Input
parameters
guidance.
8
Vapor
pressure
(
torr)
for
diuron:
2.0X10­
7
Product
Chemistry
chapter
for
HED
RED,
2001.

Table
4:
IR­
PC
PRZM/
EXAMS
input
parameters
for
DCPU.

Input
variable
Input
value
&
calculations
Source/
Quality
of
data
Crop
name
citrus
label
(
EPA
Reg.
No.
1812­
362).

application
rate
(
lb
ai/
acre)
0.08
label
(
EPA
Reg.
No.
1812­
362).
An
equivalent
value
based
on
maximum
conversion
of
diuron
to
degradates
and
the
molecular
weight
ratio
adjustment.

Application
efficiency
0.99
IR­
PC
Guidance7
Spray
drift
fraction
0.064
IR­
PC
Guidance
Application
method
ground
label
(
EPA
Reg.
No.
1812­
362).

DWRATE
(
day­
1)
0.009
MRID#
41719303;
Input
parameters
guidance8
DSRATE
(
day­
1)
0.009
MRID#
41719303;
Input
parameters
guidance
Kd
(
mL/
g)
for
diuron:
14
MRID#
44490501;
Input
parameters
guidance
Henry
(
atm.
m3/
mole)
for
diuron:
2.2X10­
10
(
calculated)
Product
Chemistry
chapter
for
HED
RED,
2001.

KBACW
(
h­
1)
for
diuron:
0.0003
No
aerobic
aquatic
data
is
available,
diruon­
t
½
was
multiplied
by
3,
MRID#
41719303.
Input
parameters
guidance.

KBACS
(
h­
1)
for
diuron:
0.002
No
anaerobic
aquatic
data
is
available,
the
anaerobic
soil
met.
t
½
was
multiplied
by
0.5.
MRID#
41418806.
Input
parameters
guidance.

KDP
(
h­
1)
for
diuron:
0.0007
MRID#
41418805;
Input
parameters
guidance.

KBH,
KNH,
KAH
(
h­
1)
for
diuron:
0
(
stable)
MRID#
41418804.
9
KPS
(
mL/
g)
for
diuron:
14
MRID#
44490501;
Input
parameters
guidance.

MWT
(
g/
mole)
205.1
The
MERCK
INDEX9
Solubility
@
25
0C
(
ppm)
for
diuron:
420
Product
Chemistry
chapter
for
HED
RED,
2001;
Input
parameters
guidance.

Vapor
pressure
(
torr)
for
diuron:
2.0X10­
7
Product
Chemistry
chapter
for
HED
RED,
2001.

Table
5:
IR­
PC
PRZM/
EXAMS
input
parameters
for
3,4­
DCA.

Input
variable
Input
value
&
calculations
Source/
Quality
of
data
Crop
name
citrus
label
(
EPA
Reg.
No.
1812­
362).

application
rate
(
lb
ai/
acre)
0.0021
label
(
EPA
Reg.
No.
1812­
362).
An
equivalent
value
based
on
maximum
conversion
of
diuron
to
degradates
and
the
molecular
weight
ratio
adjustment.

Application
efficiency
0.99
IR­
PC
Guidance7
Spray
drift
fraction
0.064
IR­
PC
Guidance
Application
method
ground
label
(
EPA
Reg.
No.
1812­
362).

DWRATE
(
day­
1)
0.008
MRID#
41719303;
Input
parameters
guidance8
DSRATE
(
day­
1)
0.008
MRID#
41538701;
Input
parameters
guidance
Kd
(
mL/
g)
for
diuron:
14
MRID#
44490501;
Input
parameters
guidance
Henry
(
atm.
m3/
mole)
for
diuron:
2.2X10­
10
(
calculated)
Product
Chemistry
chapter
for
HED
RED,
2001.

KBACW
(
h­
1)
for
diuron:
0.0003
No
aerobic
a
q
u
a
t
i
c
d
a
t
a
i
s
available,
diruon­
t
½
was
multiplied
by
3,
MRID#
41719303.
Input
parameters
guidance.

KBACS
(
h­
1)
for
diuron:
0.002
No
anaerobic
aquatic
data
is
available,
the
anaerobic
soil
met.
t
½
was
multiplied
by
0.5.
MRID#
41418806.
Input
parameters
guidance.
10
KDP
(
h­
1)
for
diuron:
0.0007
MRID#
41418805;
Input
parameters
guidance.

KBH,
KNH,
KAH
(
h­
1)
for
diuron:
0
(
stable)
MRID#
41418804.

KPS
(
mL/
g)
for
diuron:
14
MRID#
44490501;
Input
parameters
guidance.

MWT
(
g/
mole)
162.1
The
MERCK
INDEX9
Solubility
@
25
0C
(
ppm)
for
diuron:
420
Product
Chemistry
chapter
for
HED
RED,
2001;
Input
parameters
guidance.

Vapor
pressure
(
torr)
for
diuron:
2.0X10­
7
Product
Chemistry
chapter
for
HED
RED,
2001.

Table
6:
IR­
PC
PRZM/
EXAMS
input
parameters
for
mPDMU.

Input
variable
Input
value
&
calculations
Source/
Quality
of
data
Crop
name
citrus
label
(
EPA
Reg.
No.
1812­
362).

application
rate
(
lb
ai/
acre)
2.04
label
(
EPA
Reg.
No.
1812­
362).
An
equivalent
value
based
on
maximum
conversion
of
diuron
to
degradates
and
the
molecular
weight
ratio
adjustment.

Application
efficiency
0.99
IR­
PC
Guidance7
Spray
drift
fraction
0.064
IR­
PC
Guidance
Application
method
ground
label
(
EPA
Reg.
No.
1812­
362).

DWRATE
(
day­
1)
for
diuron:
0.002
MRID#
41719303;
Input
parameters
guidance8
DSRATE
(
day­
1)
for
diuron:
0.002
MRID#
41719303;
Input
parameters
guidance
Kd
(
mL/
g)
for
diuron:
14
MRID#
44490501;
Input
parameters
guidance
Henry
(
atm.
m3/
mole)
for
diuron:
2.2X10­
10
(
calculated)
Product
Chemistry
chapter
for
HED
RED,
2001.

KBACW
(
h­
1)
0.00008
MRID#
42661901.
Input
parameters
guidance.
11
KBACS
(
h­
1)
0.00005
MRID#
42260501.
Input
parameters
guidance.

KDP
(
h­
1)
for
diuron:
0.0007
MRID#
41418805;
Input
parameters
guidance.

KBH,
KNH,
KAH
(
h­
1)
for
diuron:
0
(
stable)
MRID#
41418804.

KPS
(
mL/
g)
for
diuron:
14
MRID#
44490501;
Input
parameters
guidance.

MWT
(
g/
mole)
233.1
The
MERCK
INDEX9
Solubility
@
25
0C
(
ppm)
for
diuron:
420
Product
Chemistry
chapter
for
HED
RED,
2001;
Input
parameters
guidance.

Vapor
pressure
(
torr)
for
diuron:
2.0X10­
7
Product
Chemistry
chapter
for
HED
RED,
2001.

Assumptions
and
Uncertainties7,10
Index
Reservoir
The
index
reservoir
represents
potential
drinking
water
exposure
from
a
specific
area
(
Illinois)
with
specific
cropping
patterns,
weather,
soils,
and
other
factors.
Use
of
the
index
reservoir
for
areas
with
different
climates,
crops,
pesticides
used,
sources
of
water
(
e.
g.
rivers
instead
of
reservoirs,
etc),
and
hydrogeology
creates
uncertainties.
In
general,
because
the
index
reservoir
represents
a
fairly
vulnerable
watershed,
the
exposure
estimated
with
the
index
reservoir
will
likely
be
higher
than
the
actual
exposure
for
most
drinking
water
sources.
However,
the
index
reservoir
is
not
a
worst
case
scenario,
communities
that
derive
their
drinking
water
from
smaller
bodies
of
water
with
minimal
outflow,
or
with
more
runoff
prone
soils
would
likely
get
higher
drinking
water
exposure
than
estimated
using
the
index
reservoir.
Areas
with
a
more
humid
climate
that
use
a
similar
reservoir
and
cropping
patterns
may
also
get
more
pesticides
in
their
drinking
water
than
predicted
using
this
scenario.

A
single
steady
flow
has
been
used
to
represent
the
flow
through
the
reservoir.
Discharge
from
the
reservoir
also
removes
chemical
so
this
assumption
will
underestimate
removal
from
the
12
reservoir
during
wet
periods
and
overestimates
removal
during
dry
periods.
This
assumption
can
both
underestimate
or
overestimate
the
concentration
in
the
pond
depending
upon
the
annual
precipitation
pattern
at
the
site.

The
index
reservoir
scenario
uses
the
characteristics
of
a
single
soil
to
represent
the
soil
in
the
basin.
In
fact,
soils
can
vary
substantially
across
even
small
areas,
and
this
variation
is
not
reflected
in
these
simulations.

The
index
reservoir
scenario
does
not
consider
tile
drainage.
Areas
that
are
prone
to
substantial
runoff
are
often
tile
drained.
Tile
drainage
contributes
additional
water
and
in
some
cases,
additional
pesticide
loading
to
the
reservoir.
This
may
cause
either
an
increase
or
decrease
in
the
pesticide
concentration
in
the
reservoir.
Tile
drainage
also
causes
the
surface
soil
to
dry
out
faster.
This
will
reduce
runoff
of
the
pesticide
into
the
reservoir.
The
watershed
used
as
the
model
for
the
index
reservoir
(
Shipman
City
Lake)
does
not
have
tile
drainage
in
the
cropped
areas.

EXAMS
is
unable
to
easily
model
spring
and
fall
turnover.
Turnover
occurs
when
the
temperature
drops
in
the
fall
and
the
thermal
stratification
of
the
reservoir
is
removed.
Turnover
occurs
again
in
the
spring
when
the
reservoir
warms
up.
This
results
in
complete
mixing
of
the
chemical
through
the
water
column
at
these
times.
Because
of
this
inability,
the
Index
Reservoir
has
been
simulated
without
stratification.
There
is
data
to
suggest
that
Shipman
City
Lake,
upon
which
the
Index
Reservoir
is
based,
does
indeed
stratify
in
the
deepest
parts
of
the
lake
at
least
in
some
years.
This
may
result
in
both
over
and
underestimation
of
the
concentration
in
drinking
water
depending
upon
the
time
of
the
year
and
the
depth
the
drinking
water
intake
is
drawing
from.

Percent
Crop
Area
Correction
Factor
The
PCA
is
a
watershed­
based
modification.
Implicit
in
its
application
is
the
assumption
that
currently­
used
field­
scale
models
reflect
basin­
scale
processes
consistently
for
all
pesticides
and
uses.
In
other
words,
we
assume
that
the
large
field
simulated
by
the
coupled
PRZM
and
EXAMS
models
is
a
reasonable
approximation
of
pesticide
fate
and
transport
within
a
watershed
that
contains
a
drinking
water
reservoir.
If
the
13
models
fail
to
capture
pertinent
basin­
scale
fate
and
transport
processes
consistently
for
all
pesticides
and
all
uses,
the
application
of
a
factor
that
reduces
the
estimated
concentrations
predicted
by
modeling
could,
in
some
instances,
result
in
inadvertently
passing
a
chemical
through
the
screen
that
may
actually
pose
a
risk.
Some
preliminary
assessments
made
in
the
development
of
the
PCA
suggest
that
PRZM/
EXAMS
may
not
be
realistically
capturing
basin­
scale
processes
for
all
pesticides
or
for
all
uses.
A
preliminary
survey
of
water
assessments
which
compared
screening
model
estimates
to
readily
available
monitoring
data
suggest
uneven
model
results.
In
some
instances,
the
screening
model
estimates
are
more
than
an
order
of
magnitude
greater
than
the
highest
concentrations
reported
in
available
monitoring
data;
in
other
instances,
the
model
estimates
are
less
than
monitoring
concentrations.
Because
of
these
concerns,
the
SAP
recommended
using
the
PCA
only
for
"
major"
crops
in
the
Midwest.
For
other
crops,
development
of
PCA's
will
depend
on
the
availability
of
relevant
monitoring
data
that
could
be
used
to
evaluate
the
result
of
the
PCA
adjustment.

The
spatial
data
used
for
the
PCA
came
from
readily­
available
sources
and
have
a
number
of
inherent
limitations:

°
The
size
of
the
8­
digit
HUC
[
mean
=
366,989
ha;
range
=
6.7­
2,282,081
ha;
n
=
2,111]
may
not
provide
reasonable
estimates
of
actual
PCA's
for
smaller
watersheds.
The
watersheds
that
drain
into
drinking
water
reservoirs
are
generally
smaller
than
the
8­
digit
HUC
and
may
be
better
represented
by
watersheds
defined
for
drinking
water
intakes.
°
The
conversion
of
the
county
level
data
to
watershed­
based
percent
crop
areas
assumes
the
distribution
of
the
crops
within
a
county
is
uniform
and
homogeneous
throughout
the
county
area.
Distance
between
the
treated
fields
and
the
water
body
is
not
addressed.
°
The
PCA's
were
generated
using
data
from
the
1992
Census
of
Agriculture.
However,
recent
changes
in
the
agriculture
sector
from
farm
bill
legislation
may
significantly
impact
the
distribution
of
crops
throughout
the
country.
The
methods
described
in
this
report
can
rapidly
be
updated
as
more
current
agricultural
crops
data
are
obtained.
The
assumption
that
yearly
changes
in
cropping
patterns
will
cause
minimal
impact
needs
to
be
evaluated.
14
The
PCA
adjustment
is
only
applicable
to
pesticides
applied
to
agricultural
crops.
Contributions
to
surface
waters
from
nonagricultural
uses
such
as
urban
environments
are
not
wellmodeled
Currently,
non­
agricultural
uses
are
not
included
in
the
screening
model
assessments
for
drinking
water.

The
PCA
does
not
consider
percent
crop
treated
because
detailed
pesticide
usage
data
are
extremely
limited
at
this
time.
Detailed
pesticide
usage
data
are
currently
available
for
only
a
few
states.

Groundwater
Monitoring
EFED
has
limited
targeted
monitoring
data
on
the
concentrations
of
diuron
and
its
degradates
in
groundwater.
Table
7
shows
validated
monitoring
data
for
diuron
that
are
available
for
the
states
of
California
(
CA),
Florida
(
FL),
Georgia
(
GA),
and
Texas
(
TX).

Table
7.
Groundwater
monitoring
data
for
diuron.
Number
of
wells
sampled
(
number
of
wells
with
residues)
11.

State
number
of
well
range
of
conc.
(
ppb)
15
CA
2010
(
82)
0.05
­
3.95
FL
15385
(
9)
1.18
­
5.37
GA
70
(
67)
1.00
­
5.00
TX
31
(
2)
0.01
­
0.02
According
to
the
Ground
Water
Protection
Section
of
the
Florida
Department
of
Environmental
Protection12,
ground
water
samples
from
wells
collected
between
May/
1990
and
November/
1997,
showed
diuron
detections
ranging
from
0.94
­
12
ppb
(
detection
limit
=
0.48
ppb).
The
arithmetic
mean
concentration
was
2.44
ppb.
Well
water
samples
were
collected
from
the
following
counties:
Highlands,
Jackson,
Lake,
Orange,
and
Polk.
With
the
exception
of
the
12
ppb
sample
in
Orange
County,
the
majority
of
the
detections
were
in
Highlands
County
where
citrus
is
grown.
Diuron
concentrations
in
Highlands
County
decreased
with
time
to
about
1
ppb
but
were
detected
every
year.
In
Polk
County,
diuron
concentrations
show
a
seasonal
pattern,
with
highest
concentrations
in
the
spring
and
lowest
concentrations
in
the
fall,
but
was
not
detected
in
all
years.

The
US
Geological
Survey
(
USGS)
National
Water
Quality
Assessment
Program
(
NAWQA)
13
analyzed
pesticide
occurrence
and
concentrations
for
major
aquifers
and
shallow
ground
water
in
agricultural
areas
(
detection
limit
=
0.05
ppb).
Analysis
of
2608
samples
(
major
aquifers
study)
showed
diuron
in
71%
of
the
samples
analyzed
with
a
maximum
concentration
of
0.34
ppb.
Maximum
diuron
concentration
in
897
samples
from
shallow
groundwater
sites
was
2.0
ppb,
with
diuron
detected
in
only
1.23%
of
samples
analyzed
(
USGS,
1998).
A
major
component
of
the
sampling
design
in
the
NAWQA
study
was
to
target
specific
watersheds
and
shallow
ground
water
areas
that
are
influenced
primarily
by
a
single
dominant
land
use(
agricultural
or
urban)
that
is
important
in
the
particular
area.
The
ground­
water
data
were
primarily
collected
from
a
combination
of
production
and
monitoring
wells.
Ground­
water
sampling
sites
were
sampled
for
pesticides
from
a
single
snap­
shot
in
time.

Even
though,
the
groundwater
monitoring
data
collected
by
NAWQA
are
from
sites
considered
typical
for
use
areas,
the
frequency
of
sampling
and
the
length
of
sampling
period
were
not
sufficient
to
represent
the
temporal
and
spatial
requirements
for
regulatory
purposes.
16
Major
component
of
the
sampling
design
in
the
NAWQA
study
was
to
target
specific
watersheds
and
shallow
ground
water
areas
that
are
influenced
primarily
by
a
single
dominant
land
use(
agricultural
or
urban)
that
is
important
in
the
particular
area.
The
ground­
water
data
were
primarily
collected
from
a
combination
of
production
and
monitoring
wells.
Ground­
water
sites
in
the
ground­
water
data
were
sampled
for
pesticides
from
a
single
snap­
shot
in
time.

Modeling
The
SCI­
GROW
model
was
used
to
estimate
potential
groundwater
concentrations
for
diuron
and
its
degradates.

Tables
8,
and
9
show
input
parameters
and
output
for
SCI­
GROW
modeling
of
diuron
and
its
degradates,
respectively.

Table
8.
Input
parameters
for
diuron
and
its
degradates
used
in
the
SCI­
GROW
model.

compound
appl.
rate
(
lb
ai/
acre)
No.
of
appl.
/
year
Aerobic
soil
t1/
2
(
d)
Koc
(
mL/
g)
Source/
Quality
of
data
Diuron
9.6
1
372
468
label
(
EPA
Reg.
No.
1812­
362);
MRID#
44490501;
MRID#
41719303;
Input
parameters
guideline
(
Aug.
2000).
Good
data.

DCPMU
2.03*
1
770
468
label
(
EPA
Reg.
No.
1812­
362);
MRID#
44490501;
MRID#
;
Input
parameters
guideline
(
Aug.
2000).
Good
data.

DCPU
0.08*
1
770
468
label
(
EPA
Reg.
No.
1812­
362);
MRID#
44490501;
MRID#
41719303;
Input
parameters
guideline
(
Aug.
2000).
Good
data.

3,4­
DCA
0.0021*
1
30
468
label
(
EPA
Reg.
No.
1812­
362);
MRID#
44490501;
MRID#
41719303;
MRID#
41538701;
Input
parameters
guideline
(
Aug.
2000).
Good
data.
17
mCPDMU
1.12*
1
115
468
label
(
EPA
Reg.
No.
1812­
362);
MRID#
44490501;
MRID#
41719303;
MRID#
42260501;
Input
parameters
guideline
(
Aug.
2000).
Good
data.

*:
An
equivalent
value
based
on
conversion
of
diuron
to
degradates.

Table
9.
SCI­
GROW
estimated
environmental
concentrations
for
diuron
and
its
degradates
in
groundwater.

Toxicity
end
point
model
EECs
(
F
g/
L)
use(
s)
modeled
Diuron
DCPMU
DCPU
3,4­
DCA
mCPDMU
one
application
of
diuron
on
citrus
@
9.6
lb
ai/
acre
acute
6.52
2.50
0.09
0.0002
0.30
Chronic
(
non
cancer)
6.52
2.50
0.09
0.0002
0.30
Chronic
(
cancer)
6.52
2.50
0.09
0.0002
0.30
The
SCI­
GROW
screening
model
developed
by
EFED
indicates
that
diuron
and
its
degradates
concentrations
are
much
less
than
those
estimated
for
surface
water.
SCI­
GROW
estimated
concentrations
of
diuron
do
fall
within
the
values
from
monitoring
data
shown
in
Table
8,
but
below
some
of
the
reported
monitoring
data.
This
means
that
SCI­
GROW
could
underestimate
chemical
concentrations
in
typical
use
areas
when
the
pesticide
is
used
at
the
maximum
allowed
label
rate
in
areas
with
ground
water
exceptionally
vulnerable
to
contamination
such
as
Florida.

Limitations
of
the
SCI­
GROW2
Analysis
The
SCI­
GROW
model
(
Screening
Concentrations
in
Ground
Water)
is
a
model
for
estimating
concentrations
of
pesticides
in
ground
water
under
"
maximum
loading"
conditions.
SCI­
GROW
provides
a
screening
concentration,
an
estimate
of
likely
ground
water
concentrations
if
the
pesticide
is
used
at
the
maximum
allowed
label
rate
in
areas
with
ground
water
that
is
vulnerable
to
contamination.
In
most
cases,
a
majority
of
the
use
area
will
have
ground
water
that
is
less
vulnerable
to
contamination
than
the
areas
used
to
derive
the
SCI­
GROW
estimate.
18
References:

4.
Carsel,
R.
F.,
J.
C.
Imhoff,
P.
R.
Hummel,
J.
M.
Cheplick
and
J.
S.
Donigian,
Jr.
1997.
PRZM­
3,
A
Model
for
Predicting
Pesticide
and
Nitrogen
Fate
in
Crop
Root
and
Unsaturated
Soil
Zones:
Users
Manual
for
Release
3.0;
Environmental
Research
Laboratory,
Office
of
Research
and
Development,
U.
S.
Environmental
Protection
Agency,
Athens,
GA.

2.
Burns,
L.
A.
March
1997.
Exposure
Analysis
Modeling
System
(
EXAMSII)
Users
Guide
for
Version
2.97.5,
Environmental
Research
Laboratory,
Office
of
Research
and
Development,
U.
S.
Environmental
Protection
Agency,
Athens,
GA.

3.
Barrett,
M.,
1997,
Proposal
For
a
Method
to
Determine
Screening
Concentration
Estimates
for
Drinking
Water
Derived
from
Groundwater
Studies,
EFED/
OPP.

4.
USGS.
1992.
National
Water
Quality
Assessment
(
NWQA),
Pesticides
National
Synthesis
Project,
Annual
Use:
Diuron.

5.
Thurman,
E.
M.,
K.
C.
Bastian,
and
T.
Mollhagen.
Occurrence
of
cotton
herbicides
and
insecticides
in
Playa
lakes
of
the
high
plains
of
western
Texas.
[
Online].
Available
at
http://
toxics.
usgs.
gov/
pubs/
wri99­
4018/
Volume2/
sectionC/
2
403Thurman/
pdf/
2403_
Thurman.
pdf,
May,
2001).

6.
U.
S
GS.
1998.
National
Water
Quality
Assessment
(
NWQA),
Pesticides
National
Synthesis
Project
[
Online]
at
(
http://
ca.
water.
usgs.
gov/
pnsp/
streamsum/
streamT1.
html).

7.
Effland,
W.,
N.
Thurman,
I.
Kennedy,
R.
D.
Jones,
J.
Breithaupt,
J.
Lin,
J.
Carleton,
L.
Libel.
R.
Parker,
and
R.
Matzner.
2000.
"
Guidance
for
use
of
the
index
Reservoir
and
Percent
Crop
Area
Factor
in
drinking
water
exposure
assessment
s.
Office
of
Pesticide
Programs.
8.
Guidance
for
Chemistry
and
Management
Practice
Input
Parameters
For
Use
in
Modeling
the
Environmental
Fate
and
Transport
of
Pesticides.
Version
2.
November
7,
2000.
U.
S.
EPA
Office
of
Pesticide
Programs,
Environmental
Fate
and
Effects
Division.

9.
The
Merck
Index.
1989.
An
encyclopedia
of
chemicals,
drugs,
and
biologicals.
11th
ed.
Rahway,
N.
J.
p.
533.
19
10.
Jones,
R.
D.,
S.
W.
Abel,
W.
Effland,
R.
Matzner,
and
R.
Parker.
1998.
"
An
Index
Reservoir
for
Use
in
Assessing
Drinking
Water
Exposures.
Chapter
IV
in
Proposed
Methods
for
Basin­
Scale
Estimation
of
Pesticide
Concentrations
in
Flowing
Water
and
Reservoirs
for
Tolerance
Reassessment.,
presented
to
the
FIFRA
Science
Advisory
Panel,
July
1998.
http://
www.
epa.
gov/
pesticides/
SAP/
1998/
index.
htm.

11.
U.
S.
EPA.
1992.
Pesticides
in
Ground
Water
Database­
A
compilation
of
Monitoring
Studies:
1971
­
1991.
Office
of
Prevention,
Pesticides,
and
Toxic
Substances,
EPA
734­
12­
92­
001.
12.
Florida
Department
of
Environmental
Protection.
2001.
Personal
communication
with
Bryan
Baker
@
the
Groundwater
Protection
Section
(
850/
921­
9435).

13.
USGS.
1998.
National
Water
Quality
Assessment
(
NWQA),
Pesticides
National
Synthesis
Project,
[
Online]
at
http://
ca.
water.
usgs.
gov/
pnsp/
allsum/#
over.

APPENDIX
I
IR­
PCA
PRZM/
EXAMS
INPUT
AND
OUT
PUT
FILES
FOR
MODELING
DIURON
AND
ITS
DEGRADATES
DIURON
PRZM3.12
Input
File,
flcit.
inp
(
Jan
28
2000)
Location:
Osceola
County,
FL.;
Crop:
citrus;
MLRA
156A
20
0.77
0.15
0
25.00
1
1
4
0.10
0.13
1.00
10
4
1.00
345.0
1
1
0.10
100.00
80.00
3
94
84
89
0.00
100.00
1
3
0101
21
9
2209
0.10
0.10
0.10
.023
.023
.023
36
020148
030148
311248
1
020149
030149
311249
1
020150
030150
311250
1
020151
030151
311251
1
020152
030152
311252
1
020153
030153
311253
1
020154
030154
311254
1
020155
030155
311255
1
020156
030156
311256
1
020157
030157
311257
1
020158
030158
311258
1
020159
030159
311259
1
020160
030160
311260
1
020161
030161
311261
1
020162
030162
311262
1
020163
030163
311263
1
020164
030164
311264
1
020165
030165
311265
1
020166
030166
311266
1
020167
030167
311267
1
020168
030168
311268
1
020169
030169
311269
1
020170
030170
311270
1
020171
030171
311271
1
020172
030172
311272
1
020173
030173
311273
1
020174
030174
311274
1
020175
030175
311275
1
020176
030176
311276
1
020177
030177
311277
1
020178
030178
311278
1
020179
030179
311279
1
020180
030180
311280
1
020181
030181
311281
1
020182
030182
311282
1
020183
030183
311283
1
Application:
3,4­
DCA:
One
ground
appl.
@
9.6
lb
a.
i./
ac
(
10.7
Kg/
h)
@
99%
eff,
w/
6.4%
drift
36
1
0
0
Diuron
070148
0
2
0.00
10.76
0.99
0.064
21
070149
0
2
0.00
10.76
0.99
0.064
070150
0
2
0.00
10.76
0.99
0.064
070151
0
2
0.00
10.76
0.99
0.064
070152
0
2
0.00
10.76
0.99
0.064
070153
0
2
0.00
10.76
0.99
0.064
070154
0
2
0.00
10.76
0.99
0.064
070155
0
2
0.00
10.76
0.99
0.064
070156
0
2
0.00
10.76
0.99
0.064
070157
0
2
0.00
10.76
0.99
0.064
070158
0
2
0.00
10.76
0.99
0.064
070159
0
2
0.00
10.76
0.99
0.064
070160
0
2
0.00
10.76
0.99
0.064
070161
0
2
0.00
10.76
0.99
0.064
070162
0
2
0.00
10.76
0.99
0.064
070163
0
2
0.00
10.76
0.99
0.064
070164
0
2
0.00
10.76
0.99
0.064
070165
0
2
0.00
10.76
0.99
0.064
070166
0
2
0.00
10.76
0.99
0.064
070167
0
2
0.00
10.76
0.99
0.064
070168
0
2
0.00
10.76
0.99
0.064
070169
0
2
0.00
10.76
0.99
0.064
070170
0
2
0.00
10.76
0.99
0.064
070171
0
2
0.00
10.76
0.99
0.064
070172
0
2
0.00
10.76
0.99
0.064
070173
0
2
0.00
10.76
0.99
0.064
070174
0
2
0.00
10.76
0.99
0.064
070175
0
2
0.00
10.76
0.99
0.064
070176
0
2
0.00
10.76
0.99
0.064
070177
0
2
0.00
10.76
0.99
0.064
070178
0
2
0.00
10.76
0.99
0.064
070179
0
2
0.00
10.76
0.99
0.064
070180
0
2
0.00
10.76
0.99
0.064
070181
0
2
0.00
10.76
0.99
0.064
070182
0
2
0.00
10.76
0.99
0.064
070183
0
2
0.00
10.76
0.99
0.064
0.00
1
0.00
0.00
0.000
0.50
Soil
Series:
Adamsville
sand;
Hydrogic
Group
C
100.00
0
0
0
0
0
0
0
0
0
0.0
0.00
00.00
3
1
10.000
1.440
0.086
0.000
0.000
0.000
.002
.002
0.000
0.100
0.086
0.036
0.580
14.00
2
10.000
1.440
0.086
0.000
0.000
0.000
.002
.002
0.000
1.000
0.086
0.036
0.580
14.00
3
80.000
1.580
0.030
0.000
0.000
0.000
.002
.002
0.000
5.000
0.030
0.023
0.116
14.00
22
0
WATR
YEAR
10
PEST
YEAR
10
CONC
YEAR
10
1
6
11
­­­­­
1
DAY
RUNF
TSER
0
0
1.
E0
OUTPUT
FILE
WATER
COLUMN
DISSOLVED
CONCENTRATION
(
PPB)

YEAR
PEAK
96
HOUR
21
DAY
60
DAY
90
DAY
YEARLY
­­­­
­­­­
­­­­­­­
­­­­­­
­­­­­­
­­­­­­
­­­­­­
1948
351.000
340.000
300.000
274.000
249.000
137.000
1949
1920.000
1860.000
1680.000
1450.000
1250.000
448.000
1950
306.000
296.000
264.000
229.000
213.000
112.000
1951
477.000
462.000
406.000
310.000
281.000
135.000
1952
413.000
399.000
350.000
273.000
231.000
95.430
1953
490.000
476.000
438.000
399.000
346.000
143.000
1954
512.000
496.000
446.000
375.000
329.000
158.000
1955
551.000
539.000
498.000
405.000
342.000
137.000
1956
351.000
340.000
307.000
274.000
247.000
110.000
1957
728.000
706.000
621.000
473.000
397.000
181.000
1958
680.000
658.000
576.000
450.000
383.000
175.000
1959
319.000
313.000
280.000
223.000
215.000
119.000
1960
1010.000
975.000
875.000
679.000
566.000
203.000
1961
562.000
545.000
481.000
372.000
321.000
182.000
1962
416.000
403.000
355.000
288.000
248.000
105.000
1963
417.000
404.000
354.000
310.000
267.000
115.000
1964
504.000
495.000
450.000
350.000
312.000
125.000
1965
351.000
340.000
300.000
251.000
219.000
111.000
1966
980.000
951.000
846.000
679.000
575.000
255.000
1967
527.000
510.000
467.000
370.000
308.000
133.000
1968
538.000
526.000
502.000
421.000
358.000
147.000
1969
438.000
425.000
374.000
332.000
291.000
129.000
1970
584.000
573.000
512.000
399.000
332.000
147.000
1971
592.000
577.000
524.000
449.000
382.000
155.000
1972
428.000
418.000
388.000
316.000
265.000
119.000
1973
381.000
370.000
327.000
259.000
219.000
97.670
1974
402.000
389.000
344.000
260.000
227.000
121.000
1975
177.000
171.000
152.000
128.000
109.000
48.160
1976
339.000
329.000
301.000
257.000
236.000
116.000
1977
1560.000
1510.000
1360.000
1190.000
1020.000
369.000
1978
210.000
204.000
187.000
162.000
154.000
78.430
23
1979
2330.000
2260.000
2010.000
1580.000
1330.000
454.000
1980
997.000
969.000
885.000
699.000
613.000
255.000
1981
609.000
591.000
521.000
398.000
349.000
154.000
1982
1110.000
1090.000
994.000
810.000
689.000
255.000
1983
749.000
726.000
686.000
633.000
563.000
218.000
SORTED
FOR
PLOTTING
­­­­­­
­­­
­­­­­­­­

PROB
PEAK
96
HOUR
21
DAY
60
DAY
90
DAY
YEARLY
­­­­
­­­­
­­­­­­­
­­­­­­
­­­­­­
­­­­­­
­­­­­­
0.027
2330.000
2260.000
2010.000
1580.000
1330.000
454.000
0.054
1920.000
1860.000
1680.000
1450.000
1250.000
448.000
0.081
1560.000
1510.000
1360.000
1190.000
1020.000
369.000
0.108
1110.000
1090.000
994.000
810.000
689.000
255.000
0.135
1010.000
975.000
885.000
699.000
613.000
255.000
0.162
997.000
969.000
875.000
679.000
575.000
255.000
0.189
980.000
951.000
846.000
679.000
566.000
218.000
0.216
749.000
726.000
686.000
633.000
563.000
203.000
0.243
728.000
706.000
621.000
473.000
397.000
182.000
0.270
680.000
658.000
576.000
450.000
383.000
181.000
0.297
609.000
591.000
524.000
449.000
382.000
175.000
0.324
592.000
577.000
521.000
421.000
358.000
158.000
0.351
584.000
573.000
512.000
405.000
349.000
155.000
0.378
562.000
545.000
502.000
399.000
346.000
154.000
0.405
551.000
539.000
498.000
399.000
342.000
147.000
0.432
538.000
526.000
481.000
398.000
332.000
147.000
0.459
527.000
510.000
467.000
375.000
329.000
143.000
0.486
512.000
496.000
450.000
372.000
321.000
137.000
0.514
504.000
495.000
446.000
370.000
312.000
137.000
0.541
490.000
476.000
438.000
350.000
308.000
135.000
0.568
477.000
462.000
406.000
332.000
291.000
133.000
0.595
438.000
425.000
388.000
316.000
281.000
129.000
0.622
428.000
418.000
374.000
310.000
267.000
125.000
0.649
417.000
404.000
355.000
310.000
265.000
121.000
0.676
416.000
403.000
354.000
288.000
249.000
119.000
0.703
413.000
399.000
350.000
274.000
248.000
119.000
0.730
402.000
389.000
344.000
274.000
247.000
116.000
0.757
381.000
370.000
327.000
273.000
236.000
115.000
0.784
351.000
340.000
307.000
260.000
231.000
112.000
0.811
351.000
340.000
301.000
259.000
227.000
111.000
0.838
351.000
340.000
300.000
257.000
219.000
110.000
0.865
339.000
329.000
300.000
251.000
219.000
105.000
0.892
319.000
313.000
280.000
229.000
215.000
97.670
0.919
306.000
296.000
264.000
223.000
213.000
95.430
0.946
210.000
204.000
187.000
162.000
154.000
78.430
0.973
177.000
171.000
152.000
128.000
109.000
48.160
1/
10
1245.000
1216.000
1103.800
924.000
788.300
289.200
24
MEAN
OF
ANNUAL
VALUES
=
167.852
STANDARD
DEVIATION
OF
ANNUAL
VALUES
=
91.941
UPPER
90%
CONFIDENCE
LIMIT
ON
MEAN
=
190.542
DCPMU
PRZM3.12
Input
File,
flcit.
inp
(
Jan
28
2000)
Location:
Osceola
County,
FL.;
Crop:
citrus;
MLRA
156A
0.77
0.15
0
25.00
1
1
4
0.10
0.13
1.00
172.8
4
1.00
600.0
1
1
0.10
100.00
80.00
3
94
84
89
0.00
100.00
1
3
0101
21
9
2209
0.10
0.10
0.10
.023
.023
.023
36
020148
030148
311248
1
020149
030149
311249
1
020150
030150
311250
1
020151
030151
311251
1
020152
030152
311252
1
020153
030153
311253
1
020154
030154
311254
1
020155
030155
311255
1
020156
030156
311256
1
020157
030157
311257
1
020158
030158
311258
1
020159
030159
311259
1
020160
030160
311260
1
020161
030161
311261
1
020162
030162
311262
1
020163
030163
311263
1
020164
030164
311264
1
020165
030165
311265
1
020166
030166
311266
1
020167
030167
311267
1
020168
030168
311268
1
020169
030169
311269
1
020170
030170
311270
1
020171
030171
311271
1
020172
030172
311272
1
020173
030173
311273
1
020174
030174
311274
1
25
020175
030175
311275
1
020176
030176
311276
1
020177
030177
311277
1
020178
030178
311278
1
020179
030179
311279
1
020180
030180
311280
1
020181
030181
311281
1
020182
030182
311282
1
020183
030183
311283
1
Application:
DCPMU:
One
ground
appl.
@
2.03
lb
a.
i./
ac
(
2.27
Kg/
h)
@
99%
eff,
w/
6.4%
drift
36
1
0
0
DCPMU
010748
0
2
0.00
2.27
0.99
0.064
010749
0
2
0.00
2.27
0.99
0.064
010750
0
2
0.00
2.27
0.99
0.064
010751
0
2
0.00
2.27
0.99
0.064
010752
0
2
0.00
2.27
0.99
0.064
010753
0
2
0.00
2.27
0.99
0.064
010754
0
2
0.00
2.27
0.99
0.064
010755
0
2
0.00
2.27
0.99
0.064
010756
0
2
0.00
2.27
0.99
0.064
010757
0
2
0.00
2.27
0.99
0.064
010758
0
2
0.00
2.27
0.99
0.064
010759
0
2
0.00
2.27
0.99
0.064
010760
0
2
0.00
2.27
0.99
0.064
010761
0
2
0.00
2.27
0.99
0.064
010762
0
2
0.00
2.27
0.99
0.064
010763
0
2
0.00
2.27
0.99
0.064
010764
0
2
0.00
2.27
0.99
0.064
010765
0
2
0.00
2.27
0.99
0.064
010766
0
2
0.00
2.27
0.99
0.064
010767
0
2
0.00
2.27
0.99
0.064
010768
0
2
0.00
2.27
0.99
0.064
010769
0
2
0.00
2.27
0.99
0.064
010770
0
2
0.00
2.27
0.99
0.064
010771
0
2
0.00
2.27
0.99
0.064
010772
0
2
0.00
2.27
0.99
0.064
010773
0
2
0.00
2.27
0.99
0.064
010774
0
2
0.00
2.27
0.99
0.064
010775
0
2
0.00
2.27
0.99
0.064
010776
0
2
0.00
2.27
0.99
0.064
010777
0
2
0.00
2.27
0.99
0.064
010778
0
2
0.00
2.27
0.99
0.064
010779
0
2
0.00
2.27
0.99
0.064
010780
0
2
0.00
2.27
0.99
0.064
010781
0
2
0.00
2.27
0.99
0.064
010782
0
2
0.00
2.27
0.99
0.064
010783
0
2
0.00
2.27
0.99
0.064
0.00
1
0.00
0.00
0.000
0.50
26
Soil
Series:
Adamsville
sand;
Hydrogic
Group
C
100.00
0
0
0
0
0
0
0
0
0
0.0
0.00
00.00
3
1
10.000
1.440
0.086
0.000
0.000
0.000
.009
.009
0.000
0.100
0.086
0.036
0.580
14.00
2
10.000
1.440
0.086
0.000
0.000
0.000
.009
.009
0.000
1.000
0.086
0.036
0.580
14.00
3
80.000
1.580
0.030
0.000
0.000
0.000
.009
.009
0.000
5.000
0.030
0.023
0.116
14.00
0
WATR
YEAR
10
PEST
YEAR
10
CONC
YEAR
10
1
6
11
­­­­­
1
DAY
RUNF
TSER
0
0
1.
E0
OUTPUT
FILE
WATER
COLUMN
DISSOLVED
CONCENTRATION
(
PPB)

YEAR
PEAK
96
HOUR
21
DAY
60
DAY
90
DAY
YEARLY
­­­­
­­­­
­­­­­­­
­­­­­­
­­­­­­
­­­­­­
­­­­­­
1948
24.990
23.880
21.930
19.630
19.030
7.345
1949
13.850
13.300
11.630
10.240
8.940
3.738
1950
27.340
26.130
23.770
19.860
17.560
6.493
1951
61.630
59.040
50.300
36.310
29.200
9.915
1952
98.750
94.410
78.890
56.350
45.540
15.380
1953
34.930
33.420
28.450
25.060
21.920
8.402
1954
49.500
47.300
43.730
31.770
26.870
9.186
1955
24.200
23.130
19.600
15.180
13.230
5.329
1956
23.340
22.480
19.800
15.370
13.170
4.987
1957
77.010
74.100
62.000
52.420
44.450
14.820
1958
27.160
26.390
23.010
17.690
15.500
5.692
1959
30.280
29.570
27.500
25.120
22.530
7.938
1960
39.220
37.660
33.950
26.420
22.100
8.718
1961
14.690
14.050
12.030
9.927
8.508
3.954
1962
23.590
22.580
20.690
15.960
14.460
5.580
1963
24.690
23.700
21.370
16.260
13.340
5.172
1964
47.560
45.500
38.450
28.970
24.490
9.142
1965
23.240
22.310
19.310
16.740
15.780
6.802
27
1966
19.870
19.010
16.520
13.780
12.080
4.739
1967
39.600
37.840
31.640
28.120
24.630
8.865
1968
25.620
24.510
22.680
18.040
16.100
6.135
1969
34.740
33.230
30.440
27.080
23.370
7.923
1970
15.350
14.730
12.690
9.355
8.026
3.635
1971
16.650
15.910
13.520
12.360
12.330
4.912
1972
40.250
38.840
33.780
27.100
23.140
7.859
1973
18.960
18.240
16.990
14.140
13.370
5.461
1974
21.770
20.830
18.820
14.480
12.230
4.570
1975
25.430
24.310
20.190
16.120
13.640
4.879
1976
29.110
28.180
23.930
17.990
17.420
6.575
1977
21.570
20.610
17.620
15.490
14.370
5.469
1978
5.394
5.227
4.425
3.703
3.483
1.825
1979
29.560
28.280
25.580
20.670
18.000
6.558
1980
35.180
33.620
29.890
26.040
22.060
8.045
1981
49.070
47.300
40.870
32.650
27.050
9.604
1982
7.314
7.062
6.518
5.605
5.538
3.129
1983
52.760
51.190
44.070
32.050
25.940
8.631
SORTED
FOR
PLOTTING
­­­­­­
­­­
­­­­­­­­

PROB
PEAK
96
HOUR
21
DAY
60
DAY
90
DAY
YEARLY
­­­­
­­­­
­­­­­­­
­­­­­­
­­­­­­
­­­­­­
­­­­­­
0.027
98.750
94.410
78.890
56.350
45.540
15.380
0.054
77.010
74.100
62.000
52.420
44.450
14.820
0.081
61.630
59.040
50.300
36.310
29.200
9.915
0.108
52.760
51.190
44.070
32.650
27.050
9.604
0.135
49.500
47.300
43.730
32.050
26.870
9.186
0.162
49.070
47.300
40.870
31.770
25.940
9.142
0.189
47.560
45.500
38.450
28.970
24.630
8.865
0.216
40.250
38.840
33.950
28.120
24.490
8.718
0.243
39.600
37.840
33.780
27.100
23.370
8.631
0.270
39.220
37.660
31.640
27.080
23.140
8.402
0.297
35.180
33.620
30.440
26.420
22.530
8.045
0.324
34.930
33.420
29.890
26.040
22.100
7.938
0.351
34.740
33.230
28.450
25.120
22.060
7.923
0.378
30.280
29.570
27.500
25.060
21.920
7.859
0.405
29.560
28.280
25.580
20.670
19.030
7.345
0.432
29.110
28.180
23.930
19.860
18.000
6.802
0.459
27.340
26.390
23.770
19.630
17.560
6.575
0.486
27.160
26.130
23.010
18.040
17.420
6.558
0.514
25.620
24.510
22.680
17.990
16.100
6.493
0.541
25.430
24.310
21.930
17.690
15.780
6.135
0.568
24.990
23.880
21.370
16.740
15.500
5.692
0.595
24.690
23.700
20.690
16.260
14.460
5.580
0.622
24.200
23.130
20.190
16.120
14.370
5.469
0.649
23.590
22.580
19.800
15.960
13.640
5.461
0.676
23.340
22.480
19.600
15.490
13.370
5.329
0.703
23.240
22.310
19.310
15.370
13.340
5.172
28
0.730
21.770
20.830
18.820
15.180
13.230
4.987
0.757
21.570
20.610
17.620
14.480
13.170
4.912
0.784
19.870
19.010
16.990
14.140
12.330
4.879
0.811
18.960
18.240
16.520
13.780
12.230
4.739
0.838
16.650
15.910
13.520
12.360
12.080
4.570
0.865
15.350
14.730
12.690
10.240
8.940
3.954
0.892
14.690
14.050
12.030
9.927
8.508
3.738
0.919
13.850
13.300
11.630
9.355
8.026
3.635
0.946
7.314
7.062
6.518
5.605
5.538
3.129
0.973
5.394
5.227
4.425
3.703
3.483
1.825
1/
10
55.421
53.545
45.939
33.748
27.695
9.697
MEAN
OF
ANNUAL
VALUES
=
6.872
STANDARD
DEVIATION
OF
ANNUAL
VALUES
=
2.844
UPPER
90%
CONFIDENCE
LIMIT
ON
MEAN
=
7.574
DCPU
PRZM3.12
Input
File,
flcit.
inp
(
Jan
28
2000)
Location:
Osceola
County,
FL.;
Crop:
citrus;
MLRA
156A
0.77
0.15
0
25.00
1
1
4
0.10
0.13
1.00
172.8
4
1.00
600.0
1
1
0.10
100.00
80.00
3
94
84
89
0.00
100.00
1
3
0101
21
9
2209
0.10
0.10
0.10
.023
.023
.023
36
020148
030148
311248
1
020149
030149
311249
1
020150
030150
311250
1
020151
030151
311251
1
020152
030152
311252
1
020153
030153
311253
1
020154
030154
311254
1
020155
030155
311255
1
020156
030156
311256
1
020157
030157
311257
1
020158
030158
311258
1
020159
030159
311259
1
020160
030160
311260
1
020161
030161
311261
1
29
020162
030162
311262
1
020163
030163
311263
1
020164
030164
311264
1
020165
030165
311265
1
020166
030166
311266
1
020167
030167
311267
1
020168
030168
311268
1
020169
030169
311269
1
020170
030170
311270
1
020171
030171
311271
1
020172
030172
311272
1
020173
030173
311273
1
020174
030174
311274
1
020175
030175
311275
1
020176
030176
311276
1
020177
030177
311277
1
020178
030178
311278
1
020179
030179
311279
1
020180
030180
311280
1
020181
030181
311281
1
020182
030182
311282
1
020183
030183
311283
1
Application:
DCPU:
One
ground
appl.
@
0.08
lb
a.
i./
ac
(
0.09
Kg/
h)
@
99%
eff,
w/
6.4%
drift
36
1
0
0
DCPU
010748
0
2
0.00
0.09
0.99
0.064
010749
0
2
0.00
0.09
0.99
0.064
010750
0
2
0.00
0.09
0.99
0.064
010751
0
2
0.00
0.09
0.99
0.064
010752
0
2
0.00
0.09
0.99
0.064
010753
0
2
0.00
0.09
0.99
0.064
010754
0
2
0.00
0.09
0.99
0.064
010755
0
2
0.00
0.09
0.99
0.064
010756
0
2
0.00
0.09
0.99
0.064
010757
0
2
0.00
0.09
0.99
0.064
010758
0
2
0.00
0.09
0.99
0.064
010759
0
2
0.00
0.09
0.99
0.064
010760
0
2
0.00
0.09
0.99
0.064
010761
0
2
0.00
0.09
0.99
0.064
010762
0
2
0.00
0.09
0.99
0.064
010763
0
2
0.00
0.09
0.99
0.064
010764
0
2
0.00
0.09
0.99
0.064
010765
0
2
0.00
0.09
0.99
0.064
010766
0
2
0.00
0.09
0.99
0.064
010767
0
2
0.00
0.09
0.99
0.064
010768
0
2
0.00
0.09
0.99
0.064
010769
0
2
0.00
0.09
0.99
0.064
010770
0
2
0.00
0.09
0.99
0.064
010771
0
2
0.00
0.09
0.99
0.064
010772
0
2
0.00
0.09
0.99
0.064
30
010773
0
2
0.00
0.09
0.99
0.064
010774
0
2
0.00
0.09
0.99
0.064
010775
0
2
0.00
0.09
0.99
0.064
010776
0
2
0.00
0.09
0.99
0.064
010777
0
2
0.00
0.09
0.99
0.064
010778
0
2
0.00
0.09
0.99
0.064
010779
0
2
0.00
0.09
0.99
0.064
010780
0
2
0.00
0.09
0.99
0.064
010781
0
2
0.00
0.09
0.99
0.064
010782
0
2
0.00
0.09
0.99
0.064
010783
0
2
0.00
0.09
0.99
0.064
0.00
1
0.00
0.00
0.000
0.50
Soil
Series:
Adamsville
sand;
Hydrogic
Group
C
100.00
0
0
0
0
0
0
0
0
0
0.0
0.00
00.00
3
1
10.000
1.440
0.086
0.000
0.000
0.000
.009
.009
0.000
0.100
0.086
0.036
0.580
14.00
2
10.000
1.440
0.086
0.000
0.000
0.000
.009
.009
0.000
1.000
0.086
0.036
0.580
14.00
3
80.000
1.580
0.030
0.000
0.000
0.000
.009
.009
0.000
5.000
0.030
0.023
0.116
14.00
0
WATR
YEAR
10
PEST
YEAR
10
CONC
YEAR
10
1
6
11
­­­­­
1
DAY
RUNF
TSER
0
0
1.
E0
OUTPUT
FILE
WATER
COLUMN
DISSOLVED
CONCENTRATION
(
PPB)

YEAR
PEAK
96
HOUR
21
DAY
60
DAY
90
DAY
YEARLY
­­­­
­­­­
­­­­­­­
­­­­­­
­­­­­­
­­­­­­
­­­­­­
1948
0.991
0.947
0.869
0.778
0.754
0.291
1949
0.549
0.527
0.461
0.406
0.354
0.148
1950
1.084
1.036
0.942
0.787
0.696
0.257
1951
2.443
2.341
1.994
1.440
1.158
0.393
1952
3.915
3.743
3.128
2.234
1.805
0.610
1953
1.385
1.325
1.128
0.994
0.869
0.333
31
1954
1.963
1.875
1.734
1.260
1.065
0.364
1955
0.960
0.917
0.777
0.602
0.525
0.211
1956
0.925
0.892
0.785
0.609
0.522
0.198
1957
3.053
2.938
2.458
2.078
1.762
0.588
1958
1.077
1.047
0.913
0.702
0.615
0.226
1959
1.201
1.173
1.090
0.996
0.893
0.315
1960
1.555
1.493
1.346
1.048
0.876
0.346
1961
0.582
0.557
0.477
0.394
0.337
0.157
1962
0.935
0.895
0.820
0.633
0.573
0.221
1963
0.979
0.940
0.847
0.645
0.529
0.205
1964
1.886
1.804
1.525
1.149
0.971
0.362
1965
0.921
0.884
0.766
0.664
0.626
0.270
1966
0.788
0.753
0.655
0.546
0.479
0.188
1967
1.570
1.500
1.255
1.115
0.977
0.352
1968
1.016
0.971
0.899
0.715
0.638
0.243
1969
1.377
1.318
1.207
1.074
0.927
0.314
1970
0.609
0.584
0.503
0.371
0.318
0.144
1971
0.660
0.631
0.536
0.490
0.489
0.195
1972
1.596
1.540
1.339
1.074
0.918
0.312
1973
0.752
0.723
0.674
0.561
0.530
0.216
1974
0.863
0.826
0.746
0.574
0.485
0.181
1975
1.008
0.964
0.800
0.639
0.540
0.193
1976
1.154
1.117
0.949
0.713
0.691
0.261
1977
0.855
0.817
0.699
0.614
0.570
0.217
1978
0.214
0.207
0.175
0.147
0.138
0.072
1979
1.172
1.121
1.014
0.820
0.714
0.260
1980
1.395
1.333
1.185
1.032
0.875
0.319
1981
1.946
1.876
1.621
1.295
1.073
0.381
1982
0.290
0.280
0.258
0.222
0.220
0.124
1983
2.091
2.029
1.747
1.270
1.028
0.342
SORTED
FOR
PLOTTING
­­­­­­
­­­
­­­­­­­­

PROB
PEAK
96
HOUR
21
DAY
60
DAY
90
DAY
YEARLY
­­­­
­­­­
­­­­­­­
­­­­­­
­­­­­­
­­­­­­
­­­­­­
0.027
3.915
3.743
3.128
2.234
1.805
0.610
0.054
3.053
2.938
2.458
2.078
1.762
0.588
0.081
2.443
2.341
1.994
1.440
1.158
0.393
0.108
2.091
2.029
1.747
1.295
1.073
0.381
0.135
1.963
1.876
1.734
1.270
1.065
0.364
0.162
1.946
1.875
1.621
1.260
1.028
0.362
0.189
1.886
1.804
1.525
1.149
0.977
0.352
0.216
1.596
1.540
1.346
1.115
0.971
0.346
0.243
1.570
1.500
1.339
1.074
0.927
0.342
0.270
1.555
1.493
1.255
1.074
0.918
0.333
0.297
1.395
1.333
1.207
1.048
0.893
0.319
0.324
1.385
1.325
1.185
1.032
0.876
0.315
0.351
1.377
1.318
1.128
0.996
0.875
0.314
0.378
1.201
1.173
1.090
0.994
0.869
0.312
32
0.405
1.172
1.121
1.014
0.820
0.754
0.291
0.432
1.154
1.117
0.949
0.787
0.714
0.270
0.459
1.084
1.047
0.942
0.778
0.696
0.261
0.486
1.077
1.036
0.913
0.715
0.691
0.260
0.514
1.016
0.971
0.899
0.713
0.638
0.257
0.541
1.008
0.964
0.869
0.702
0.626
0.243
0.568
0.991
0.947
0.847
0.664
0.615
0.226
0.595
0.979
0.940
0.820
0.645
0.573
0.221
0.622
0.960
0.917
0.800
0.639
0.570
0.217
0.649
0.935
0.895
0.785
0.633
0.540
0.216
0.676
0.925
0.892
0.777
0.614
0.530
0.211
0.703
0.921
0.884
0.766
0.609
0.529
0.205
0.730
0.863
0.826
0.746
0.602
0.525
0.198
0.757
0.855
0.817
0.699
0.574
0.522
0.195
0.784
0.788
0.753
0.674
0.561
0.489
0.193
0.811
0.752
0.723
0.655
0.546
0.485
0.188
0.838
0.660
0.631
0.536
0.490
0.479
0.181
0.865
0.609
0.584
0.503
0.406
0.354
0.157
0.892
0.582
0.557
0.477
0.394
0.337
0.148
0.919
0.549
0.527
0.461
0.371
0.318
0.144
0.946
0.290
0.280
0.258
0.222
0.220
0.124
0.973
0.214
0.207
0.175
0.147
0.138
0.072
1/
10
2.197
2.123
1.821
1.339
1.099
0.384
MEAN
OF
ANNUAL
VALUES
=
0.272
STANDARD
DEVIATION
OF
ANNUAL
VALUES
=
0.113
UPPER
90%
CONFIDENCE
LIMIT
ON
MEAN
=
0.300
3,4­
DCA
PRZM3.12
Input
File,
flcit.
inp
(
Jan
28
2000)
Location:
Osceola
County,
FL.;
Crop:
citrus;
MLRA
156A
0.77
0.15
0
25.00
1
1
4
0.10
0.13
1.00
10
4
1.00
345.0
1
1
0.10
100.00
80.00
3
94
84
89
0.00
100.00
1
3
0101
21
9
2209
0.10
0.10
0.10
.023
.023
.023
36
33
020148
030148
311248
1
020149
030149
311249
1
020150
030150
311250
1
020151
030151
311251
1
020152
030152
311252
1
020153
030153
311253
1
020154
030154
311254
1
020155
030155
311255
1
020156
030156
311256
1
020157
030157
311257
1
020158
030158
311258
1
020159
030159
311259
1
020160
030160
311260
1
020161
030161
311261
1
020162
030162
311262
1
020163
030163
311263
1
020164
030164
311264
1
020165
030165
311265
1
020166
030166
311266
1
020167
030167
311267
1
020168
030168
311268
1
020169
030169
311269
1
020170
030170
311270
1
020171
030171
311271
1
020172
030172
311272
1
020173
030173
311273
1
020174
030174
311274
1
020175
030175
311275
1
020176
030176
311276
1
020177
030177
311277
1
020178
030178
311278
1
020179
030179
311279
1
020180
030180
311280
1
020181
030181
311281
1
020182
030182
311282
1
020183
030183
311283
1
Application:
3,4­
DCA:
One
ground
appl.
@
0.002
lb
a.
i./
ac
(
0.0022
Kg/
h)
@
99%
eff,
w/
6.4%
drift
36
1
0
0
3,4­
DCA
010748
0
2
0.00
0.0022
0.99
0.064
010749
0
2
0.00
0.0022
0.99
0.064
010750
0
2
0.00
0.0022
0.99
0.064
010751
0
2
0.00
0.0022
0.99
0.064
010752
0
2
0.00
0.0022
0.99
0.064
010753
0
2
0.00
0.0022
0.99
0.064
010754
0
2
0.00
0.0022
0.99
0.064
010755
0
2
0.00
0.0022
0.99
0.064
010756
0
2
0.00
0.0022
0.99
0.064
010757
0
2
0.00
0.0022
0.99
0.064
010758
0
2
0.00
0.0022
0.99
0.064
34
010759
0
2
0.00
0.0022
0.99
0.064
010760
0
2
0.00
0.0022
0.99
0.064
010761
0
2
0.00
0.0022
0.99
0.064
010762
0
2
0.00
0.0022
0.99
0.064
010763
0
2
0.00
0.0022
0.99
0.064
010764
0
2
0.00
0.0022
0.99
0.064
010765
0
2
0.00
0.0022
0.99
0.064
010766
0
2
0.00
0.0022
0.99
0.064
010767
0
2
0.00
0.0022
0.99
0.064
010768
0
2
0.00
0.0022
0.99
0.064
010769
0
2
0.00
0.0022
0.99
0.064
010770
0
2
0.00
0.0022
0.99
0.064
010771
0
2
0.00
0.0022
0.99
0.064
010772
0
2
0.00
0.0022
0.99
0.064
010773
0
2
0.00
0.0022
0.99
0.064
010774
0
2
0.00
0.0022
0.99
0.064
010775
0
2
0.00
0.0022
0.99
0.064
010776
0
2
0.00
0.0022
0.99
0.064
010777
0
2
0.00
0.0022
0.99
0.064
010778
0
2
0.00
0.0022
0.99
0.064
010779
0
2
0.00
0.0022
0.99
0.064
010780
0
2
0.00
0.0022
0.99
0.064
010781
0
2
0.00
0.0022
0.99
0.064
010782
0
2
0.00
0.0022
0.99
0.064
010783
0
2
0.00
0.0022
0.99
0.064
0.00
1
0.00
0.00
0.000
0.50
Soil
Series:
Adamsville
sand;
Hydrogic
Group
C
100.00
0
0
0
0
0
0
0
0
0
0.0
0.00
00.00
3
1
10.000
1.440
0.086
0.000
0.000
0.000
.008
.008
0.000
0.100
0.086
0.036
0.580
14.00
2
10.000
1.440
0.086
0.000
0.000
0.000
.008
.008
0.000
1.000
0.086
0.036
0.580
14.00
3
80.000
1.580
0.030
0.000
0.000
0.000
.008
.008
0.000
5.000
0.030
0.023
0.116
14.00
0
WATR
YEAR
10
PEST
YEAR
10
CONC
YEAR
10
1
6
11
­­­­­
1
DAY
RUNF
TSER
0
0
1.
E0
OUTPUT
FILE
35
WATER
COLUMN
DISSOLVED
CONCENTRATION
(
PPB)

YEAR
PEAK
96
HOUR
21
DAY
60
DAY
90
DAY
YEARLY
­­­­
­­­­
­­­­­­­
­­­­­­
­­­­­­
­­­­­­
­­­­­­
1948
0.020
0.018
0.014
0.009
0.009
0.003
1949
0.011
0.010
0.008
0.006
0.005
0.001
1950
0.020
0.018
0.014
0.009
0.007
0.002
1951
0.060
0.053
0.034
0.017
0.012
0.004
1952
0.101
0.089
0.055
0.027
0.019
0.006
1953
0.026
0.023
0.019
0.013
0.010
0.003
1954
0.048
0.042
0.029
0.015
0.011
0.003
1955
0.019
0.017
0.011
0.007
0.006
0.002
1956
0.022
0.020
0.014
0.009
0.007
0.002
1957
0.064
0.056
0.043
0.026
0.019
0.005
1958
0.024
0.021
0.014
0.008
0.006
0.002
1959
0.028
0.025
0.018
0.012
0.010
0.003
1960
0.035
0.031
0.023
0.014
0.012
0.004
1961
0.013
0.011
0.008
0.005
0.004
0.001
1962
0.019
0.017
0.012
0.008
0.007
0.002
1963
0.022
0.020
0.016
0.010
0.008
0.002
1964
0.047
0.042
0.028
0.016
0.012
0.004
1965
0.018
0.016
0.012
0.009
0.008
0.003
1966
0.012
0.011
0.009
0.006
0.005
0.002
1967
0.033
0.029
0.018
0.014
0.011
0.003
1968
0.018
0.016
0.012
0.009
0.007
0.002
1969
0.031
0.027
0.017
0.013
0.010
0.003
1970
0.013
0.012
0.009
0.005
0.004
0.001
1971
0.013
0.011
0.007
0.005
0.005
0.002
1972
0.037
0.033
0.022
0.013
0.010
0.003
1973
0.012
0.010
0.009
0.007
0.006
0.002
1974
0.016
0.014
0.012
0.007
0.005
0.002
1975
0.022
0.019
0.012
0.007
0.005
0.002
1976
0.023
0.021
0.014
0.009
0.008
0.002
1977
0.015
0.014
0.010
0.007
0.006
0.002
1978
0.003
0.002
0.002
0.001
0.001
0.001
1979
0.026
0.022
0.016
0.010
0.008
0.002
1980
0.030
0.026
0.019
0.013
0.009
0.003
1981
0.045
0.042
0.028
0.018
0.014
0.004
1982
0.005
0.005
0.004
0.003
0.002
0.001
1983
0.051
0.047
0.032
0.016
0.011
0.003
SORTED
FOR
PLOTTING
­­­­­­
­­­
­­­­­­­­

PROB
PEAK
96
HOUR
21
DAY
60
DAY
90
DAY
YEARLY
­­­­
­­­­
­­­­­­­
­­­­­­
­­­­­­
­­­­­­
­­­­­­
36
0.027
0.101
0.089
0.055
0.027
0.019
0.006
0.054
0.064
0.056
0.043
0.026
0.019
0.005
0.081
0.060
0.053
0.034
0.018
0.014
0.004
0.108
0.051
0.047
0.032
0.017
0.012
0.004
0.135
0.048
0.042
0.029
0.016
0.012
0.004
0.162
0.047
0.042
0.028
0.016
0.012
0.004
0.189
0.045
0.042
0.028
0.015
0.011
0.003
0.216
0.037
0.033
0.023
0.014
0.011
0.003
0.243
0.035
0.031
0.022
0.014
0.011
0.003
0.270
0.033
0.029
0.019
0.013
0.010
0.003
0.297
0.031
0.027
0.019
0.013
0.010
0.003
0.324
0.030
0.026
0.018
0.013
0.010
0.003
0.351
0.028
0.025
0.018
0.013
0.010
0.003
0.378
0.026
0.023
0.017
0.012
0.009
0.003
0.405
0.026
0.022
0.016
0.010
0.009
0.003
0.432
0.024
0.021
0.016
0.010
0.008
0.003
0.459
0.023
0.021
0.014
0.009
0.008
0.002
0.486
0.022
0.020
0.014
0.009
0.008
0.002
0.514
0.022
0.020
0.014
0.009
0.008
0.002
0.541
0.022
0.019
0.014
0.009
0.007
0.002
0.568
0.020
0.018
0.014
0.009
0.007
0.002
0.595
0.020
0.018
0.012
0.009
0.007
0.002
0.622
0.019
0.017
0.012
0.008
0.007
0.002
0.649
0.019
0.017
0.012
0.008
0.006
0.002
0.676
0.018
0.016
0.012
0.007
0.006
0.002
0.703
0.018
0.016
0.012
0.007
0.006
0.002
0.730
0.016
0.014
0.011
0.007
0.006
0.002
0.757
0.015
0.014
0.010
0.007
0.005
0.002
0.784
0.013
0.012
0.009
0.007
0.005
0.002
0.811
0.013
0.011
0.009
0.006
0.005
0.002
0.838
0.013
0.011
0.009
0.006
0.005
0.002
0.865
0.012
0.011
0.008
0.005
0.005
0.001
0.892
0.012
0.010
0.008
0.005
0.004
0.001
0.919
0.011
0.010
0.007
0.005
0.004
0.001
0.946
0.005
0.005
0.004
0.003
0.002
0.001
0.973
0.003
0.002
0.002
0.001
0.001
0.001
1/
10
0.053
0.049
0.032
0.017
0.013
0.004
MEAN
OF
ANNUAL
VALUES
=
0.003
STANDARD
DEVIATION
OF
ANNUAL
VALUES
=
0.001
UPPER
90%
CONFIDENCE
LIMIT
ON
MEAN
=
0.003
37
mCPDMU
PRZM3.12
Input
File,
flcit.
inp
(
Jan
28
2000)
Location:
Osceola
County,
FL.;
Crop:
citrus;
MLRA
156A
0.77
0.15
0
25.00
1
1
4
0.10
0.13
1.00
172.8
4
1.00
600.0
1
1
0.10
100.00
80.00
3
94
84
89
0.00
100.00
1
3
0101
21
9
2209
0.10
0.10
0.10
.023
.023
.023
36
020148
030148
311248
1
020149
030149
311249
1
020150
030150
311250
1
020151
030151
311251
1
020152
030152
311252
1
020153
030153
311253
1
020154
030154
311254
1
020155
030155
311255
1
020156
030156
311256
1
020157
030157
311257
1
020158
030158
311258
1
020159
030159
311259
1
020160
030160
311260
1
020161
030161
311261
1
020162
030162
311262
1
020163
030163
311263
1
020164
030164
311264
1
020165
030165
311265
1
020166
030166
311266
1
020167
030167
311267
1
020168
030168
311268
1
020169
030169
311269
1
020170
030170
311270
1
020171
030171
311271
1
020172
030172
311272
1
020173
030173
311273
1
020174
030174
311274
1
020175
030175
311275
1
020176
030176
311276
1
020177
030177
311277
1
020178
030178
311278
1
020179
030179
311279
1
38
020180
030180
311280
1
020181
030181
311281
1
020182
030182
311282
1
020183
030183
311283
1
Application:
mCPDMU:
One
ground
appl.
@
2.04
lb
a.
i./
ac
(
2.28
Kg/
h)
@
99%
eff,
w/
6.4%
drift
36
1
0
0
mCPDMU
010748
0
2
0.00
2.28
0.99
0.064
010749
0
2
0.00
2.28
0.99
0.064
010750
0
2
0.00
2.28
0.99
0.064
010751
0
2
0.00
2.28
0.99
0.064
010752
0
2
0.00
2.28
0.99
0.064
010753
0
2
0.00
2.28
0.99
0.064
010754
0
2
0.00
2.28
0.99
0.064
010755
0
2
0.00
2.28
0.99
0.064
010756
0
2
0.00
2.28
0.99
0.064
010757
0
2
0.00
2.28
0.99
0.064
010758
0
2
0.00
2.28
0.99
0.064
010759
0
2
0.00
2.28
0.99
0.064
010760
0
2
0.00
2.28
0.99
0.064
010761
0
2
0.00
2.28
0.99
0.064
010762
0
2
0.00
2.28
0.99
0.064
010763
0
2
0.00
2.28
0.99
0.064
010764
0
2
0.00
2.28
0.99
0.064
010765
0
2
0.00
2.28
0.99
0.064
010766
0
2
0.00
2.28
0.99
0.064
010767
0
2
0.00
2.28
0.99
0.064
010768
0
2
0.00
2.28
0.99
0.064
010769
0
2
0.00
2.28
0.99
0.064
010770
0
2
0.00
2.28
0.99
0.064
010771
0
2
0.00
2.28
0.99
0.064
010772
0
2
0.00
2.28
0.99
0.064
010773
0
2
0.00
2.28
0.99
0.064
010774
0
2
0.00
2.28
0.99
0.064
010775
0
2
0.00
2.28
0.99
0.064
010776
0
2
0.00
2.28
0.99
0.064
010777
0
2
0.00
2.28
0.99
0.064
010778
0
2
0.00
2.28
0.99
0.064
010779
0
2
0.00
2.28
0.99
0.064
010780
0
2
0.00
2.28
0.99
0.064
010781
0
2
0.00
2.28
0.99
0.064
010782
0
2
0.00
2.28
0.99
0.064
010783
0
2
0.00
2.28
0.99
0.064
0.00
1
0.00
0.00
0.000
0.50
Soil
Series:
Adamsville
sand;
Hydrogic
Group
C
100.00
0
0
0
0
0
0
0
0
0
0.0
0.00
00.00
3
39
1
10.000
1.440
0.086
0.000
0.000
0.000
.002
.002
0.000
0.100
0.086
0.036
0.580
14.00
2
10.000
1.440
0.086
0.000
0.000
0.000
.002
.002
0.000
1.000
0.086
0.036
0.580
14.00
3
80.000
1.580
0.030
0.000
0.000
0.000
.002
.002
0.000
5.000
0.030
0.023
0.116
14.00
0
WATR
YEAR
10
PEST
YEAR
10
CONC
YEAR
10
1
6
11
­­­­­
1
DAY
RUNF
TSER
0
0
1.
E0
OUTPUT
FILE
WATER
COLUMN
DISSOLVED
CONCENTRATION
(
PPB)

YEAR
PEAK
96
HOUR
21
DAY
60
DAY
90
DAY
YEARLY
­­­­
­­­­
­­­­­­­
­­­­­­
­­­­­­
­­­­­­
­­­­­­
1948
32.350
31.270
28.580
26.250
25.600
10.820
1949
20.430
19.780
17.480
16.490
14.970
6.406
1950
30.210
29.200
26.920
24.990
22.810
9.550
1951
64.530
62.530
55.440
43.620
36.820
13.800
1952
101.000
97.580
85.300
66.550
56.590
21.830
1953
42.340
40.950
36.420
33.030
30.490
13.130
1954
53.770
51.970
48.960
38.780
34.920
13.490
1955
29.250
28.280
24.900
20.960
19.010
8.566
1956
34.720
33.720
30.750
25.410
21.720
8.536
1957
83.620
81.380
71.240
63.710
57.110
21.030
1958
28.420
27.790
25.390
21.560
20.230
8.797
1959
37.580
36.330
32.620
30.960
29.580
11.640
1960
59.290
57.380
53.630
43.530
36.820
14.270
1961
19.820
19.170
16.830
15.030
13.470
6.971
1962
31.500
30.450
28.390
23.710
20.470
8.866
1963
40.600
39.290
35.770
28.440
23.760
9.124
1964
69.330
67.030
58.670
47.210
41.530
15.710
1965
34.410
33.300
29.830
25.250
23.590
11.500
1966
25.380
24.540
21.700
18.560
16.350
7.429
1967
46.930
45.830
40.590
36.480
33.000
13.160
1968
33.720
32.610
30.210
24.360
22.080
9.560
1969
43.810
42.360
39.240
33.060
30.250
11.660
1970
25.170
24.360
21.530
16.640
14.080
6.370
1971
23.670
23.210
21.000
18.120
17.030
7.783
40
1972
43.930
42.870
39.050
34.580
31.170
11.470
1973
27.960
27.150
24.940
21.080
19.000
8.558
1974
30.230
29.220
26.450
21.250
18.500
7.341
1975
26.370
25.490
22.160
19.640
17.620
7.440
1976
39.500
38.450
34.010
27.280
23.660
10.120
1977
24.680
23.900
21.020
20.040
19.050
8.284
1978
7.142
6.964
6.320
5.438
5.252
3.313
1979
35.850
34.660
30.260
26.710
24.580
9.927
1980
40.150
39.140
36.000
34.330
30.380
11.950
1981
66.900
64.670
58.060
49.800
42.500
15.460
1982
13.060
12.680
11.770
9.561
9.106
5.719
1983
59.320
58.200
51.850
40.740
34.350
12.150
SORTED
FOR
PLOTTING
­­­­­­
­­­
­­­­­­­­

PROB
PEAK
96
HOUR
21
DAY
60
DAY
90
DAY
YEARLY
­­­­
­­­­
­­­­­­­
­­­­­­
­­­­­­
­­­­­­
­­­­­­
0.027
101.000
97.580
85.300
66.550
57.110
21.830
0.054
83.620
81.380
71.240
63.710
56.590
21.030
0.081
69.330
67.030
58.670
49.800
42.500
15.710
0.108
66.900
64.670
58.060
47.210
41.530
15.460
0.135
64.530
62.530
55.440
43.620
36.820
14.270
0.162
59.320
58.200
53.630
43.530
36.820
13.800
0.189
59.290
57.380
51.850
40.740
34.920
13.490
0.216
53.770
51.970
48.960
38.780
34.350
13.160
0.243
46.930
45.830
40.590
36.480
33.000
13.130
0.270
43.930
42.870
39.240
34.580
31.170
12.150
0.297
43.810
42.360
39.050
34.330
30.490
11.950
0.324
42.340
40.950
36.420
33.060
30.380
11.660
0.351
40.600
39.290
36.000
33.030
30.250
11.640
0.378
40.150
39.140
35.770
30.960
29.580
11.500
0.405
39.500
38.450
34.010
28.440
25.600
11.470
0.432
37.580
36.330
32.620
27.280
24.580
10.820
0.459
35.850
34.660
30.750
26.710
23.760
10.120
0.486
34.720
33.720
30.260
26.250
23.660
9.927
0.514
34.410
33.300
30.210
25.410
23.590
9.560
0.541
33.720
32.610
29.830
25.250
22.810
9.550
0.568
32.350
31.270
28.580
24.990
22.080
9.124
0.595
31.500
30.450
28.390
24.360
21.720
8.866
0.622
30.230
29.220
26.920
23.710
20.470
8.797
0.649
30.210
29.200
26.450
21.560
20.230
8.566
0.676
29.250
28.280
25.390
21.250
19.050
8.558
0.703
28.420
27.790
24.940
21.080
19.010
8.536
0.730
27.960
27.150
24.900
20.960
19.000
8.284
0.757
26.370
25.490
22.160
20.040
18.500
7.783
0.784
25.380
24.540
21.700
19.640
17.620
7.440
0.811
25.170
24.360
21.530
18.560
17.030
7.429
0.838
24.680
23.900
21.020
18.120
16.350
7.341
0.865
23.670
23.210
21.000
16.640
14.970
6.971
41
0.892
20.430
19.780
17.480
16.490
14.080
6.406
0.919
19.820
19.170
16.830
15.030
13.470
6.370
0.946
13.060
12.680
11.770
9.561
9.106
5.719
0.973
7.142
6.964
6.320
5.438
5.252
3.313
1/
10
67.629
65.378
58.243
47.987
41.821
15.535
MEAN
OF
ANNUAL
VALUES
=
10.604
STANDARD
DEVIATION
OF
ANNUAL
VALUES
=
3.895
UPPER
90%
CONFIDENCE
LIMIT
ON
MEAN
=
11.565
APPENDIX
II
SCI­
GROW
OUTPUT
FILES
FOE
MODELING
DIURON
AND
ITS
DEGRADATES
RUN
No.
1
FOR
diuron
INPUT
VALUES
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
­­­
APPL
(#/
AC)
APPL.
URATE
SOIL
SOIL
AEROBIC
RATE
NO.
(#/
AC/
YR)
KOC
METABOLISM
(
DAYS)
42
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
­­­
9.600
1
9.600
468.0
372.0
GROUND­
WATER
SCREENING
CONCENTRATIONS
IN
PPB
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
6.521987
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
A=
367.000
B=
473.000
C=
2.565
D=
2.675
RILP=
3.399
F=
­.
168
G=
.679
URATE=
9.600
GWSC=
6.521987
RUN
No.
1
FOR
DCPMU
INPUT
VALUES
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
­­­
APPL
(#/
AC)
APPL.
URATE
SOIL
SOIL
AEROBIC
RATE
NO.
(#/
AC/
YR)
KOC
METABOLISM
(
DAYS)

­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
­­­
2.030
1
2.030
468.0
770.0
GROUND­
WATER
SCREENING
CONCENTRATIONS
IN
PPB
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
2.497237
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
A=
765.000
B=
473.000
C=
2.884
D=
2.675
RILP=
3.821
F=
.090
G=
1.230
URATE=
2.030
GWSC=
2.497237
RUN
No.
2
FOR
DCPU
INPUT
VALUES
43
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
­­­
APPL
(#/
AC)
APPL.
URATE
SOIL
SOIL
AEROBIC
RATE
NO.
(#/
AC/
YR)
KOC
METABOLISM
(
DAYS)

­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
­­­
.080
1
.080
468.0
770.0
GROUND­
WATER
SCREENING
CONCENTRATIONS
IN
PPB
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
.098413
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
A=
765.000
B=
473.000
C=
2.884
D=
2.675
RILP=
3.821
F=
.090
G=
1.230
URATE=
.080
GWSC=
.098413
RUN
No.
3
FOR
3,4­
DCA
INPUT
VALUES
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
­­­
APPL
(#/
AC)
APPL.
URATE
SOIL
SOIL
AEROBIC
RATE
NO.
(#/
AC/
YR)
KOC
METABOLISM
(
DAYS)

­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
­­­
.002
1
.002
468.0
30.0
GROUND­
WATER
SCREENING
CONCENTRATIONS
IN
PPB
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
.000155
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
A=
25.000
B=
473.000
C=
1.398
D=
2.675
RILP=
1.852
F=
­
1.111
G=
.077
URATE=
.002
GWSC=
.000155
44
RUN
No.
4
FOR
mCPDMU
INPUT
VALUES
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
­­­
APPL
(#/
AC)
APPL.
URATE
SOIL
SOIL
AEROBIC
RATE
NO.
(#/
AC/
YR)
KOC
METABOLISM
(
DAYS)

­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
­­­
1.120
1
1.120
468.0
115.0
GROUND­
WATER
SCREENING
CONCENTRATIONS
IN
PPB
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
.287307
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
A=
110.000
B=
473.000
C=
2.041
D=
2.675
RILP=
2.705
F=
­.
591
G=
.257
URATE=
1.120
GWSC=
.287307
45
46
14.
Cullington,
J.
E.,
and
A.
Walker.
1998.
Rapid
degradation
of
diuron,
and
other
phenylurea
herbicides
by
a
soil
bacterium.
Soil
Biology
and
Biochemistry.
31:
677­
686.
15.

9.
Rouchaud
J.,
O.
Neus,
R.
Bulcke,
K.
Cools,
H.
Eelen,
and
T.
Dekkers.
2000.
Soil
dissipation
of
diuron,
chlorotoluron,
simazine,
propyzamide,
and
diflufenican
herbicides
after
repeated
applications
in
fruit
tree
orchards.
Archives
of
Environmental
Contamination
and
Toxicology.
39(
1):
60­
65.

10.
Linuron
Reregistration
Eligibility
Decision.
1994.
United
States
Environmental
Protection
Agency
,
Office
of
Prevention,
Pesticides
And
Toxic
Substances,
[
Online]
at
http://
www.
epa.
gov/
oppsrrd1/
REDs/
0047.
pdf.

Diuron
Surface
Water
Monitoring
Data
Location
Duration
of
Sampling
(
sampling
frequency)
Number
of
samples
(%
detections)
Max
detection
(
ppb)
47
CA
(
mostly
creeks
and
rivers)
1
Nov.
1996­
April
1998
for
most
samples
(
sampling
every
2
weeks)
307
(
48
%)
30.6
CA
(
runoff
studies
from
right
of
way
use
 
edge
of
plot
data)
2
September
1991­
November
1991
(
sampling
during
runoff
events)
47
(
100
%)
2849
(
of
three
studies)

LA
(
mostly
creeks,
bayous
and
rivers)
3
May
1999­
May
2000
(
sampling
every
2
weeks
to
one
month)
83
(
70
%)
3.65
(
estimated)
0.48
(
confirmed)

MS,
MO,
TN,
AR,
and
North
LA
(
mostly
creeks,
bayous
and
rivers)
4
February
1996­
February
2001
(
sampling
every
2
weeks
to
one
month)
219
(
52
%)
2.1
(
estimated)
0.98
(
confirmed)

1
CA
Department
of
Pesticide
Regulation's
surface
water
database,
as
of
July
15,
2000
SWDB
study
37.
Nordmark,
Craig.
1998.
Preliminary
results
of
acute
and
chronic
toxicity
testing
of
surface
water
monitored
in
the
Sacramento
River
watershed,
winter
1997­
98.
Memorandum
to
Don
Weaver,
Environmental
Monitoring
and
Pest
Management,
Department
of
Pesticide
Regulation,
Sacramento,
California.
July
31,
1998.

SWDB
study
41.
Domagalski,
J.,
In
Prep.
Pesticide
monitoring
in
the
Sacramento
River
Basin,
California,
2/
96­
9/
98.
USGS
National
Water­
Quality
Assessment
Program.
USGS
report
in
preparation.

SWDB
study
43.
Foe,
C.
1993.
Pesticides
in
surface
water
from
applications
on
orchards
and
alfalfa
during
the
winter
and
spring
of
1991­
92.
Central
Valley
Regional
Water
Quality
Control
Board,
Sacramento,
California.
February
1993.

SWDB
study
51.
Sacramento
Area
Stormwater
NPDES
Permit
Monitoring
Program:
1990,
1991,
1992,
1994­
95
and
1995­
96.
Submitted
to
County
of
Sacramento
and
cities
of
Sacramento,
Folsom
and
Galt
by
Larry
Walker
and
Associates,
Davis
California.
48
SWDB
study
57.
Nordmark,
Craig.
1999.
Preliminary
results
of
acute
and
chronic
toxicity
testing
of
surface
water
monitored
in
the
Sacramento
River
watershed,
winter
1998­
99.
Memorandum
to
Don
Weaver,
Environmental
Monitoring
and
Pest
Management,
Department
of
Pesticide
Regulation,
Sacramento,
California.
May
26,
1999.

SWDB
study
63.
Nordmark,
Craig.
In
prep.
Preliminary
results
of
acute
and
chronic
toxicity
testing
of
surface
water
monitored
in
the
Sacramento
River
watershed,
winter
1999­
00.
Memorandum
to
Don
Weaver,
Environmental
Monitoring
and
Pest
Management,
Department
of
Pesticide
Regulation,
Sacramento,
California.

2
Powell,
S.,
R.
Neal,
and
J.
Leyva.
1996.
Runoff
and
Leaching
of
Simazine
and
Diuron
used
on
Highway
Rights
of
Way.
CAL
DPR
Report
No.
EH
96­
03,
www.
cdpr.
ca.
ca.
gov/
empm/
pubs/
chapreps/
e9603.
htm.

3
Walters,
D.
2001.
USGS
Spreadsheet
"
Breithaupt.
xls"
sent
to
James
Breithaupt
of
OPP/
EFED
on
5/
23/
2001
in
Response
to
Data
Request.

4
Coupe,
Richard
H.
2001.
USGS
Spreadsheet
"
EPA.
xls"
sent
to
James
Breithaupt
of
OPP/
EFED
on
4/
12/
2001
in
Response
to
Data
Request.

5
Harris,
Jennifer.
2001.
USGS
Spreadsheet
"
DCA.
xls"
sent
to
James
Breithaupt
of
OPP/
EFED
on
5/
21/
2001
in
Response
to
Data
Request.

Discussion
of
the
Surface
Water
Monitoring
Results
for
the
Common
Diuron,
Linuron,
and
Propanil
Degradate
3,4­
Dichloroaniline
(
3,4­
DCA)

Diuron,
linuron,
and
propanil
have
a
common
degradate,
3,4­
DCA.
In
MS,
MO,
TN,
AR,
and
North
LA,
3,4­
DCA
did
not
exceed
8.9
ppb
in
surface
water
(
49
%
detection
rate,
68
samples)
(
Harris,
2001).
In
South
Louisiana,
there
were
only
three
samples
for
3,4­
DCA,
with
a
maximum
concentration
of
0.06
ppb
(
Walters,
2001).
Any
DCA
present
in
MS,
MO,
TN,
AR,
and
North
LA
is
likely
to
be
a
result
of
both
diuron
and
propanil
applications
due
to
both
cotton
and
rice
being
produced.
In
South
Louisiana,
any
3,4­
DCA
present
would
most
likely
be
from
applied
propanil
to
rice.