The Variable Volume Water Model
USEPA/OPP 734F14003
June 12, 2014
Dirk F. Young
Environmental Fate and Effects Division
Office of Pesticide Programs
U.S. Environmental Protection Agency
Washington, D.C. 20460
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Hydrologic Washout — 6
Contents
1 Introduction 1
2 The Varying Volume Water Body Model 1
2.1 Conceptualization and Mathematics 1
2.2 Solute Holding Capacity Ratio (0) 5
2.3 Effective Water Column Dissipation (Fi) 6
2.3.1
2.3.2 Metabolism (fibio i) 6
2.3.3 Hydrolysis ((Jhydri) 7
2.3.4 Photolysis (|j,photo) 7
2.3.5 Volatilization (^volatilization) 8
2.4 Effective Benthic Region Dissipation (TV) 11
2.4.1 Benthic Hydrolysis (|j,hydr 2) 11
2.4.2 Benthic Metabolism (|j,bio 2) 11
2.5 Mass Transfer Coefficient (Q) 12
2.6 Daily Piecewise Calculations 14
2.6.1 Volume Calculations 14
2.6.2 Initial Conditions 14
2.7 Analytical Solution 15
3 The USEPA Standard Water Bodies 16
3.1 Farm Pond 19
3.2 Index Reservoir 20
3.3 Custom Water Body 20
4 VVWM Evaluations 20
4.1 Solute Holding Capacity Ratio Sensitivity 20
4.2 Washout and Overflow Sensitivity 22
4.3 Photolysis Sensitivity 24
4.4 Volatilization 26
5 Testing and Comparison of VVWM Solution with EXAMS 28
6 Computer Program Implementation 29
6.1 Executable and the Command Line 29
6.2 Input Files 30
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6.2.1 General Input File 30
6.2.2 ZTS Input File 32
6.2.3 Meteorological File 33
6.3 Output Files 34
6.3.1 Regulatory Summary Output File 34
6.3.2 Daily Values Output File 34
Summary 34
References 35
11
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1 Introduction
USEPA's Office of Pesticide Programs (OPP) uses computer models to estimate
pesticide exposure in surface waters resulting from pesticide applications to agricultural fields.
These models are used to simulate pesticide applications to agricultural fields, the subsequent
fate and transport in surface waters, and ultimately, estimated environmental concentrations
(EECs) that are both protective and scientifically defensible. Using historical meteorological
data from the region specified in the risk assessment, PRZM (Carsel et. a/, 1997) calculates daily
runoff and spray drift fluxes from "standard" fields over a simulation period (typically 30 years).
These standard fields are parameterized to represent particular crops and regions of the United
States (e.g., corn grown in Ohio). Another model EXAMS (Burns, 1985) simulates standard
water bodies, that receive pesticides from the standard fields. Because EXAMS is difficult to
implement in a user-friendly environment, OPP has created a new program, the Variable
Volume Water Body Model (VVWM). VVWM behaves much like EXAMS, simulating the
USEPA standard water bodies (i.e., farm pond and index reservoir) but with greater efficiency
and flexibility for incorporation into a user interface. The VVWM also allows for variations in
water body volume on a daily basis due to runoff, precipitation, and evaporation. Temperature,
wind speeds, and pesticide dissipation processes are also allowed to vary daily.
2 The Varying Volume Water Body Model
2.1 Conceptualization and Mathematics
The VVWM is conceptualized in Figure 1 and consists of two regions: a water column
and a benthic region. Each individual region is completely mixed and at equilibrium with all
phases in that region, with equilibrium described by a linear isotherm. The two regions are
coupled by a turbulent-mixing, first-order mass-transfer process. As Figure 1 also shows, the
pond volume may vary by inputs of precipitation and runoff and by outputs of evaporation and
overflow.
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Direct pesticide
application to littoral
region by runoff,
erosion and spraydrift
evaporation Preciptation
Direct pesticide
application to benthic
region by erosion
solids
volatilization
Littoral region
Washout During Overflow
littoral region degradation
due to metabolism,
hydrolysis, and photolysis
littoral/benthic mass transfer
benthic region
*•
benthic region
degradation due
to metabolism
and hydrolysis
Figure 1. Graphic of the standard water body showing inputs, outputs, and transformation
processes.
The mathematics are solved by daily piecewise analytic solutions. The temporal
resolution is one day because daily inputs are readily acquired (i.e., runoff, rainfall, and
evaporation data are 24-hour totals), and regulatory needs seldom require finer resolution. The
water body volumes and flow rates are also daily values, consistent with the input data
resolution. For the analytic solution, water body properties are held constant each day, but may
vary from day to day.
All individual dissipation processes (e.g., metabolism, hydrolysis, and volatilization) are
represented as first-order in concentration, as described later. On any given day, solute mass in
the water body is described by two differential equations, namely a mass balance on the water
column:
ds.
m.
sed I
•sed I
dt
ds,
bio I
dsr
io I
-m
'DOC I
- + v,
dc,
dt u^-1 dt l dt
-Q<\ ~QCsedssed -QCblosblo-QCDOCsDOC -a(Cl -c2)
(1)
sed\Ssed ~
'bio DOCl^DOC
biota\Sbiota
and a mass balance on the benthic region:
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dssed_2 dsblo_2 dsD^^
sedi -i bio2 / DOC2 / 2 / 2ibio—a2 2 2ihydr2 2 V 1 2 ^
at at at at
/ ?•
~ msedLlbio-sed2Ssed2 ~ mbiota^bio-biota2Sbiota2 \*
~mDOcf*bio-DOC2SDOC2 ~"Ssed2
Where
B = burial rate of sediment, [kg/s]
ci = aqueous concentration in water column, [kg/ m3]
C2 = aqueous concentration in benthic region, [kg/ m3]
Csed = concentration of suspended sediment in water column = nised i/vi [kg/m3]
CDOC = concentration of DOC in water column = mooc/vi, [kg/m3]
Cbio = concentration of biota in water column = nibio/vi, [kg/m3]
msed i = mass of suspended sediment in water column, [kg]
rnooc i = mass of DOC in water column, [kg]
nibio i = mass of suspended biota in water column, [kg]
nised 2 = mass of suspended sediment in water column, [kg]
niooc 2 = mass of DOC in benthic region, [kg]
nibio 2 = mass of biota in benthic region, [kg]
Ssed i = sorbed concentration on suspended sediment in water column, [kg/ kg]
SDOC i = sorbed concentration on suspended DOC in water column, [kg/ kg]
Sbio i = sorbed concentration on suspended biota in water column, [kg/ kg]
Ssed2 = sorbed pesticide concentration on benthic sediment, [kg/ kg]
SDOC 2 = sorbed pesticide concentration on benthic DOC, [kg/ kg]
Sbio 2 = sorbed pesticide concentration on benthic biota, [kg/ kg]
vi = volume of water in region 1 on the specific day, [m3]
V2 = volume of water in region 2, [m3]
Q = volumetric flow rate of water out of water column, [m3/s]
a = 1st order water column-to-benthic mass transfer coefficient, [mVs]
Hhydr = 1st order hydrolysis rate coefficient, [s"1]
Uphoto =lst order photolysis rate coefficient, [s"1]
|j,voi = effective 1st order volatilization rate coefficient, [s"1]
Ubio ai=lst order aqueous-phase metabolic degradation rate coefficient in water column, [s"1]
|j,bio sedi = 1st order sediment-sorbed metabolic degradation rate coefficient in water column, [s"1]
Ubio bioi = 1st order biota-sorbed metabolic degradation rate coefficient in water column, [s"1]
|j,bio DOCI = 1st order DOC-sorbed metabolic degradation rate coefficient in water column, [s"1]
|j,bio a2 =lst order aqueous-phase metabolic degradation rate coefficient in benthic region, [s"1]
Ubio sed2 = 1st order sediment-sorbed metabolic degradation rate coefficient in benthic region, [s"1]
|j,bio bio2 = 1st order biota-sorbed metabolic degradation rate coefficient in benthic region, [s"1]
Ubio Doc2 = 1st order DOC-sorbed metabolic degradation rate coefficient in benthic region, [s"1]
The following assumptions are made: (1) suspended matter in the water column has
negligible volume, (2) hydrolysis, photolysis, and volatilization act only on dissolved species, (3)
within a single region (water column or benthic), the rate coefficient for biological metabolism is
the same for both dissolved and sorbed forms of pesticide (e.g., |j,bio i = |J,bio ai = |J,bio sedi =
|j,bio DOCI = |J,bio biotai, and |j,bio 2 = |J,bio a2 = |J,bio sed2 = |J,bio DOC2 = |J,bio biota2), (4) the hydrolysis rate
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coefficient in the benthic region is the same as that in the water column, (5) linear isotherm
equilibrium exists within each region among all sorbed species. With these assumptions, we can
rewrite equations (1) and (2) in a simpler form as follows:
He
(3)
-c2 (4)
dt
where
— + ("photo + ^hydr + Hvol Xvl + Utrio (5)
rr*
=f
sed_2 sed_2 ~*~ mbio_2 bio_2 ~*~ mDOC_2 DOC_2 ~*~ V2
inlSed_2KSed_2 + mbio_2Kbio_2 + mDOC_2KDOC_2 + V2
Ked lKsed 1 +mbIO lKbIO 1 +mDOC 1KDOC 1 +V
,o^
(o)
where fwi and fW2 are the fractions of solute in the aqueous phase within the water column and
benthic regions, respectively, as defined by the following equations:
f = _ Xl _ (9)
(mSedJKsedJ + mbio_lKbio_l + mDOCJKDOCJ
(10)
w27 ^ - - ^ \
Vmsed_2Ksed_2 + mbio_2Kbio_2 + mDOC_2KDOC_2 + V2/
and where Ksed i, Kbio i, KDOC i are the linear isotherm partitioning coefficients for suspended
sediments, biota, and DOC in the water column, and Ksed 2, Kbio 2, KDOC 2 are the linear isotherm
partitioning coefficients for sediments, biota, and DOC in the benthic region (all with units of
m3/kg).
The term, fwi, varies daily depending on the volume of the water body (vi) as described
below in Section 2. 6 Daily Piecewise Calculations. We assume that the mass of sediment, biota,
and DOC remain constant. However, this assumption has very little impact on the model output
since partitioning to these species is insignificant, except when given extremely high
partitioning coefficients.
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Given a set of initial conditions, equations (3) and (4) completely describe the standard
water bodies. It is clear that there are only four parameters that influence the concentration—Fi,
F2, Q, and 0. Fi is the effective overall degradation rate in the water column, [s"1]. F2 is the
effective overall degradation rate in the benthic region, [s"1]. Q is a mass transfer coefficient
describing transfer between the benthic and water column, [s"1]. 0 is the ratio of solute holding
capacity in the benthic region to that in the water column, [unitless]. The sections that follow
describe the details of the components of these equations with respect to the standard water
bodies.
2.2 Solute Holding Capacity Ratio (&)
The solute holding capacity ratio (0) is the ratio of solute holding capacity in the benthic
region to the solute capacity in the water column, as defined by equation (8). The individual
partitioning coefficients (Kd sed, Kd biota, and Kd DOC) used in equation (8) are generally not
directly measured for a pesticide assessment. To account for these unknown coefficients, the
standard water bodies use various estimation means that relate the various partitioning
coefficients to the organic carbon partitioning coefficient (Koc), which is usually known in a
pesticide assessment process.
For the sediment, the partitioning coefficient is directly proportional to Koc, with the
constant of proportionality being the amount of organic carbon in the sediment, which is a set to
standard values for the standard water bodies (see Table 1). The fraction of organic carbon (foc)
is assumed to be the same in the benthic and water column. The sediment partitioning
coefficients can thus be determined from the following equation:
Kd,Sed_l =Kd,sed_2 =focKoc\°-00lJ|j7rJ (H)
where Koc = organic carbon partitioning coefficient, [mL/g]
foe = fraction of organic carbon in sediment [unitless]
Note that the units of the coefficients in equations (1) to (10) are all given in s.i. form, which is
maintained throughout this document. However, for some fundamental parameters such as Koc,
which is usually presented in units of mL/g, common units and conversion factors are used.
The partitioning coefficients for DOC are determined from the default empirical
relationships described in the EXAMS documentation (Burns, 2000). The VVWM incorporates
the notion of Burns (2000) that benthic DOC has higher partitioning characteristics than water
column DOC for standard water bodies:
ATDOC_1= 0.2114^(0.001^) (12)
(13)
The partitioning coefficients for biota are also determined from default empirical
relations described in the EXAMS documentation:
(K Y'907/ 3/t\
K, =Kh ,=0.436^- O.OOl^M (14)
fa°-1 bl°-2 10.35 J V ml/g/
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By inserting equations (11) through (14) into equation (8) and substituting specific values
from Table 1 into equation (8), the solute holding capacity (0) can be written as a function of
solely Koc, as presented in Figure 2 for both the standard pond and reservoir.
2.3 Effective Water Column Dissipation (Fi)
The overall dissipation rate in the water column (Fi), as defined in equation (5) is the
sum of contributions from hydrologic washout and degradation by mechanisms of biological
metabolism, photolysis, and hydrolysis. The specific methods and assumptions that are used in
the VVWM to determine these individual first-order dissipation processes are described below.
2.3.1 Hydrologic Washout —
1VJ
The first term in equation (5), Q/vi, represents the effective first-order dissipation rate
due to flow moving pesticide out of the water body. Flow out of the water body only occurs if
meteorological conditions produce enough water inflow to cause the water body to overflow (see
Section 2.6 Daily Piecewise Calculations). The washout term acts on all forms of pesticide
(aqueous dissolved and sorbed to suspended matter), as is apparent from equation (1) and the
definitions for Xsed, Xbio, and XDOC. This means that the settling of suspended solids is not
explicitly considered in the VVWM, and pesticides in both dissolved and suspended sorbed
forms can flow out of the reservoir.
Flow is obtained from an input file or entered as a constant baseflow. The input file
provides a daily flow and is typically generated by the PRZM model as a zts file (see section
6.22) Baseflow will work is additive to any flow from the zts file.
2.3.2 Metabolism (Hbio_i)
In the registration process of pesticides, an estimate of the aqueous degradation rate under
aerobic conditions is supplied by the registrant. Such estimates are derived from laboratory tests
following standard EPA-approved protocols, which are typically conducted in aqueous/sediment
systems at 20 to 25° C. These tests generally do not differentiate between degradation occurring
on the dissolved and sorbed forms of the pesticide; an overall degradation rate is generally all
that is available. Therefore, the VVWM treats the sorbed-phase and aqueous-phase degradation
rates as the same, which makes both equal to the overall rate.
As temperature varies in a water body, the USEPA has established a standard for
temperature adjustments of the aerobic metabolism rate when regulating pesticides as follows:
u,IOJ=u,5x2 10 (15)
where |j,25 = laboratory measured aerobic metabolism rate at 25°C, [s"1]
T = temperature of modeled water body, [°C]
Tref = temperature at which laboratory study was conducted, [°C]
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This temperature adjustment doubles the metabolism rate for every 10°C rise in temperature, and
halves the rate for every 10°C decrease. Air temperature is taken from the meteorological data
that corresponds to the crop/location scenario being simulated. The VVWM uses the previous
30-day average temperature and adjusts the temperature daily. (Note: EXAMS made
temperature adjustments on a monthly calendar basis, which required tracking of the Gregorian
calendar).
2.3.3 Hydrolysis (M.hydr_i)
The hydrolysis rate is directly obtained from experimental measurements, as supplied by
pesticide registrant data submissions. In the VVWM, the effective hydrolysis rate is the
experimentally-determined overall hydrolysis rate from tests conducted at the pH of interest. In
a typical USEPA assessment, the pH is 7 (Note: Because pH is not included explicitly in the
VVWM, the appropriate input is the overall hydrolysis rate, not the specific neutral-, base-, or
acid-catalyzed hydrolysis rate coefficients, as in EXAMS).
Unlike the metabolism rate, temperature adjustments of the hydrolysis rate are not made
by the VVWM. Temperature-dependent hydrolysis characterizations are not generally made for
the registration process, and the USEPA has not adopted a standard adjustment for temperature
effects on hydrolysis. Therefore, the hydrolysis rate is as follows:
M- hydrj = M- overall, pH \*-®)
where Coverall, pH = laboratory-measured overall hydrolysis rate at pH of interest, [s"1].
The VVWM uses the assumption that hydrolysis acts only on dissolved species.
Therefore, the effective hydrolysis rate is reduced by the fraction of total pesticide that is present
in dissolved aqueous form (fwi), as defined in equation (9) and implemented in equation (5).
2.3.4 Photolysis (jlphoto)
Photolysis rates are derived from standard laboratory tests following USEPA-approved
protocols. These tests are designed to estimate the photodegradation rate for near-surface
conditions at a specific latitude and under clear-sky conditions. The VVWM adopts the methods
given by EXAMS (Burns 1997, 2000) to account for latitude adjustments, light attenuation, and
cloud cover:
M-photolysis ~~ lat cloud atten ^measured ^ >
where fiat = latitude adjustment factor, [unitless]
fcioud = cloudiness adjustment factor, [unitless]
fatten = attenuation factor to absorption, [unitless]
^measured = measured near-surface photolysis rate coefficient at reference latitude and clear
atmospheric conditions [sec"1]
Although cloudiness does not affect the current standard water bodies (fcioud is set to a
standard value of 1), fcioud is included here for the purposes of formality and because it may be
considered in future versions.
The latitude of the standard water body varies, depending on the desired location in the
U.S. where the pesticide assessment is being made. The effect that latitude has on incident light
7
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is accounted for by the latitude adjustment factor (fiat), which the VVWM adopts from EXAMS
(Burns, 2000). Full details of the reasoning behind fiat can be found in the EXAMS
documentation, and only the resulting equation is given here:
_ 191700 + 87050cos(0.0349xLsim)
hat ~ 1917oo + 87050cos(0.0349xLref)
where Lref = reference latitude at which the measured photolysis rate was determined, [degrees]
Lsim = latitude of the simulated scenario, [degrees]
The light attenuation factor (fatten) described by Burns (2000) has also been adopted; the
full details are available in the EXAMS documentation:
l-exp[-(DfecXd1)a]
atten
where Dfac = EXAMS-defmed distribution factor default value = 1.19, [unitless]
di = depth of water column, [m]
a = total absorption coefficient, [m"1]
The absorption coefficient (a) is calculated from EXAMS default conditions—that is,
from the spectral absorption coefficient assuming that the wave length of maximum absorption
occurs at 300 nm:
a = 0.141 + 101[CCHL] + 6.25[CDOC] + 0.34[CSed] (20)
where CDOC, Csed have been previously defined under equation (1), and CCHL is the chlorophyll
concentration [mg/L].
Temperature effects are not considered in the above equations, except when the water
temperature is 0°C or below. Photolysis is inhibited, as in EXAMS. Temperature effects are
not considered since the USEPA generally does not receive temperature dependent data for the
registration process and has not adopted a standard temperature adjustment for photolysis.
2.3.5 Volatilization ((ivoiatuization)
The VVWM uses a two-film model for volatilization calculations and all of the default
volatilization assumptions as described in the EXAMS documentation (Burns, 2000). The
concentration of a pesticide in the atmosphere is assumed to be negligible, and thus volatilization
becomes a first-order dissipation process. The overall volatilization rate coefficient is expressed
as follows:
Mw=^EfflL (21)
where A = surface area of water column, [m2]
kvoi = volatilization exchange coefficient, [m/s]
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and the volatilization exchange coefficient comprises liquid-phase and gas-phase resistances:
If If .
Kvoi Kw VRT
where kw = liquid-phase resistance [m/s]
ka = gas-phase resistance, [m/s]
H = Henry's law constant (m3atm/mol)
R = the universal gas constant (8.206 x 10"5 m3atm/mol/K)
T= temperature (K)
The VVWM uses the EXAMS methods of referencing the liquid exchange resistance of
pesticides to the liquid resistance of oxygen, and uses molecular weight as the sole surrogate for
molecular diffusivity variations among compounds. Further details can be found in the EXAMS
documentation (Burns, 2000), but the resulting relationship is as follows:
(23)
where ko2 = oxygen exchange constant at 20°C, [m/s]
MW = molecular weight of pesticide, [g/mol]
The oxygen exchange constant is determined from the empirical relationship of Banks
(1975). Adjustments are also made for temperatures other than 20°C. Note that although
EXAMS uses a reference temperature of 20°C for the Banks (1975) relationship, it is not clear
from Banks (1975) what the actual reference temperature should be. Schwarzenbach et al.
(1992) used a 10°C reference for the same relationship. Until further clarified, a 20°C reference
temperature is used. For wind velocities (vwind) less than 5.5 m/s, ko2 is calculated as:
k02=(4.19xlO-6Vu7)(l.024(T-20))
(24)
and for wind velocities greater than or equal to 5.5 m/s, ko2 is:
k02 =3.2xl(T7(u10)2(l.024(T-20)) (25)
where uio = wind velocity at 10 m above water surface [m/s].
Wind speeds measured at 10 m above the surface are read from the meteorological files.
To convert to wind speeds at a different height, the following equation is used:
Uj_ _ log(Zl/z0)
~ 1 / / \ \- '
u2 Iog(z2/z0j
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where zo is the boundary roughness height, which is assumed to be 1 mm for the standard water
bodies. Given a wind speed (measured at 10m) from the meteorological file, the equivalent
wind speed at 0.1 m is:
log(0.1/0.001) „<
Un , = —^ : rUln = 0.5u
Iog(l0/0.00l)
10
10
(27)
In the VVWM, wind speed varies on a daily basis, unlike in EXAMS where the average monthly
wind speed varies on a monthly basis.
The gas-phase resistance is referred to as water vapor resistance, and an empirical
relationship based on a linear regression of laboratory-derived data from Liss (1973) relates the
water vapor exchange velocity to wind speed:
ka,H2o = 0.00005+ 0.0032uai
where ka,H2o = the water vapor exchange velocity (m/s)
uo.i = wind speed velocity measured at 0.1 m above the surface (m/s)
The exchange rate of a pesticide is then related to the exchange rate of water by:
D
k =k
a,H2O
D
a,H2O
(28)
where a (not to be confused with the alpha in equation 1 and 2) is a value that depends on the
conceptual model believed to describe volatilization and ranges from 0.5 for the surface renewal
model to 1.0 for the stagnant film model (Cusler,1984 ; Schwarzenbach et al., 1993). The
VVWM uses a value of 1.0 for a; thus, implying a stagnant film model. However, some
laboratory data suggest that a may be better represented with a value of 0.67 (Mackay and Yuen,
1983). The diffusion coefficient of the pesticide is related to the diffusion coefficient of water by
the common approximate relationship (e.g., Schwarzenbach et al., 1993):
i,H,O
18
MW
(29)
Substituting (29) into (28) gives:
k - k
K ~~ K
18
MW
0.5
(30)
The resulting relationship is:
10
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k = [0.00005+ 0.0032uni I (31)
a L U.I J\ I -» r~f-\ T ^ '
The Henry's Law constant is generally not available from pesticide registration
submissions, so it is approximated in the VVWM from vapor pressure and solubility. The
Henry's Law constant also is not adjusted for temperature, as this information is not supplied in
the pesticide registration, and OPP has not adopted a standard temperature adjustment factor.
The resulting relationship is:
H= (vP/76°)
(Sol/MW)
where vp = vapor pressure [torr]
Sol = solubility [mg/L]
2.4 Effective Benthic Region Dissipation
The overall benthic degradation in the VVWM, as defined in equation (6), is only
affected by biodegradation and hydrolysis. As with the water column, OPP assumes that
biodegradation in the benthic region affects all forms of pesticide (both dissolved and sorbed
forms) and that hydrolysis affects only aqueous dissolved forms (see equation 6 and definition of
fw2).
2.4.1 Benthic Hydrolysis (Hhydr_2)
In the current standard water bodies, the pH of the entire system (benthic and water
column) are held at a constant pH of 7, although a subsequent paper will suggest using scenario-
specific pH values. Benthic hydrolysis is assumed to occur at the same rate as hydrolysis in the
water column; the previous discussion of hydrolysis in the water column applies to the benthic
region:
M-hvdr 2 = M-hvdr 1
2.4.2 Benthic Metabolism (Hbio_2)
In the VVWM, benthic metabolism is assumed to occur under anaerobic conditions.
Therefore, anaerobic metabolism rates are derived from laboratory tests following standard EPA-
approved protocols. These studies are typically conducted in aqueous/sediment systems at 20 -
25°C. As with water column metabolism, OPP assumes that sorbed-phase degradation occurs at
the same rate as aqueous-phase degradation, and temperature effects on metabolism are handled
in the same way. Thus, the effective rate is the following:
M-bio 2 = M-measured X 2 (34)
where (^measured = laboratory measured anaerobic metabolism rate at Tref
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T = temperature of modeled water body [°C]
Tref = temperature at which anaerobic laboratory study was conducted [°C].
2. 5 Mass Transfer Coefficient (Q)
The mass transfer coefficient (Q) defined in equation (7) is an overall coefficient that
includes all means of pesticide exchange between the water column and benthic regions. This
includes exchange through the aqueous phase as well as by mixing of sediments between the two
compartments. The physical process of this combined mixing is assumed to be completely
described by a first-order mass transfer coefficient (a). The parameter a is referenced to the
aqueous phase, but implicitly includes exchange due to mixing of sediments as well as aqueous
exchange. In compartment modeling, it is unnecessary to explicitly model the individual
exchange mechanisms (as EXAMS does) since all phases of pesticide within a compartment are
at equilibrium. Therefore, the concentration of a pesticide in any given form (aqueous or sorbed)
dictates the concentration of the other forms of the pesticide.
In the VVWM, the a term is based upon parameters and assumptions given in the
EXAMS documentation. Although not explicitly presented as such, EXAMS uses a boundary
layer model to exchange pesticide mass between the water column and benthic regions. EXAMS
defines the parameter DSP, which represents a Fickian-type dispersion coefficient in the benthic
sediment. This dispersion coefficient acts on the total concentration within the benthic region,
implying that sediment-sorbed pesticide moves through the benthic region at the same rate as
dissolved-phase pesticide (e.g., via bioturbation). The rate of mass change in the benthic region
is approximated under steady state conditions across a boundary layer of constant thickness:
-CT2) (35)
dt Ax
where M2 = total pesticide mass in benthic region
A = area of benthic/water column interface, [m2]
D = effective overall dispersion coefficient in benthic media (includes both sorbed and
dissolved phases), [m2/s]; DSP in EXAMS
Ax = thickness of boundary layer, [m]
yi = total partition coefficient for total concentrations, [unitless]
Cxi = total concentration in water column, [kg/m3]
Ci2 = total concentration in benthic region, [kg/m3]
The total concentrations in the water column and benthic regions are calculated as follows:
(36)
VT1
12
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where ci and vi are the aqueous-phase concentration and the aqueous volume, as previously
defined under equation (1); Z(miKdi) and Z(ni2Kd2) are short-hand notation for the sum of all
solid masses and the respective Kds presented under equation (1) for the water column and
benthic regions, respectively; VTI and Vi2 are the total volumes of the water column and benthic
region, respectively, which include both the water and the solids volumes. The total pesticide
mass in the benthic region is expressed as follows:
M2=c2(v2+^m2Kd2) (38)
The total partitioning coefficient is defined as the ratio of Ci2 to Cxi when the system is at
equilibrium:
C
9? = —— (when benthic region is at equilibrium with water column) (39)
LT1
By substituting in the definitions of Cxi and Ci2 from equations (36) and (37) and recognizing
that at equilibrium ci = C2, the total partitioning coefficient becomes:
(40)
V
VT2
Substituting equations (36) to (40) into equation (35) yields the following:
dM2 _ AD (v2 +Xm2Kd2^ \
dt Ax VT2
(41)
Comparing equation (41) with equation (2), we can see that:
a = APv^+l^KW (42)
Ax VT2
and that Q is:
AT"»
(43)
VT2Ax
where D = overall water column -to-benthic dispersion coefficient (m2/s)
Ax = boundary layer thickness (m)
A = area of water body (m2)
D in the above equation is set to a constant (Table 1) for the USEPA standard pond. The
value of D was originally chosen to be on the order of Fickian-type dispersion coefficients in
sediments, as observed in field studies reported in the EXAMS documentation. Although
equation (42) implies a mechanistic meaning to a, it is difficult to adequately transform
13
-------
Fickian-type dispersion coefficients into first-order mass transfer coefficients for finite volume
compartments, and it is equally difficult to define a boundary layer thickness, especially when
there is sediment and aqueous mixing. EXAMS suggests that the boundary layer thickness be
equal to the distance between the center of the water column and the center of the benthic region,
but the actual boundary layer thickness is difficult to estimate and likely is more related to
benthic animal life than water column depth.
Attempting to model the benthic mass transfer parameter as a function of water column
depth would be speculative, so the WWM currently maintains a constant thickness.
2.6 Daily Piecewise Calculations
Because we retain an analytical solution, the WWM is solved in a daily piecewise
fashion, in which the volume of the water column changes at the beginning of the day and
remains constant for the duration of that day. Mass is conserved in the water column by
recalculating a new beginning day concentration with any volume change.
2.6.1 Volume Calculations
The volume of the water column aqueous phase is calculated from daily runoff,
precipitation, and evaporation for any day as follows:
Vj =v0+R+P-E-S for0
-------
Calculations); thus the concentration in the water column is adjusted accordingly. The initial
concentrations, upon addition of new pesticide mass, are then expressed as follows:
Mrmoff+(l-Xd)Memsion
(45)
J wl, prior
C20 =^(XdM_)+C20 pnor (46)
where Mnmoff = mass of pesticide entering water body via runoff (kg)
Merosion = mass of pesticide entering water body via erosion (kg)
Mdrift = mass of pesticide entering water body via spray drift (kg)
Cio,Prior = aqueous concentration in water column before new mass additions (kg/m3)
C2o!prior = aqueous concentration in benthic region before new mass additions (kg/m3)
vi, prior = the water column volume from the previous day (m3)
fwi,Prior = fwi from the previous day
Xd = fractional initial distribution (between water column and benthic region) of the
pesticide associated with eroded solids as it enters the water body
2. 7 Analytical Solution
Equations (3) and (4) along with the initial conditions represent the two equations
describing the standard water bodies. These equations are in the form of the following:
(47)
dt
where
dt
(48)
E = Q
Equations (47) and (48) have the solution:
(49)
15
-------
where
A + F-
B
B
(50)
-4(FA-BE)
-4(FA-BE)
c -c
r—in '—9
B
— An
c -
Average concentrations can be determined over any interval in which all parameters
remain constant. In the VVWM, parameters change on a daily basis, so the average water
column concentration is expressed as follows:
C -^L
Lavg , /.
Y
Y
r2(t2-t!)
(51)
where Ci,avg = average water column concentration of time from ti to ii [kg/m3]
ti = beginning of the time interval considered [s"1], (zero for our case of daily estimates)
t2= end of the time interval considered [s"1], (86,400 seconds for our case of daily
estimates)
3 The USEPA Standard Water Bodies
All parameters in the above equations, except for the pesticide-specific parameters, have
standard values set by the USEPA for the standard farm pond and index reservoir scenarios
(Table 1). Many of these values have no documentation and simply have evolved over many
years of repeated, unquestioned use. Table 2 shows how the parameters in the VVWM simplify
and replace previous EXAMS parameters and expressions, and Table 3 lists the original EXAMS
standard parameters. The VVWM also gives the option to define a custom-sized water body.
16
-------
Table 1. Standard Parameter Values for the VVWM.
Parameter
VI
V2
A
di
d2
msed 1
mbio i
rnooc i
toe
msed 2
mbio 2
mooc i
PH
CcHL
CDOC
Csed 1
Cbio
D
Ax
VT2
Units
m3
m3
m2
m
m
kg
kg
kg
—
kg
kg
kg
mg/L
mg/L
mg/L
mg/L
m2/s
m
Farm Pond
Values
20,000
249.8
10,000
2.0
0.05
600
8.0
100
0.04
6.752 x\05
0.0600
1.249
7
0.005
5
30
0.4
8.33x ID'9
1.02
500
Index
Reservoir
Values
144,000
1,314
52,555
2.74
0.05
4,320
57.60
720
0.04
3.552x 106
0.3156
6.570
7
0.005
5
30
0.4
8.33x 10-9
1.39
2,630
Notes
water column volume
aqueous benthic volume(a)
surface area, calculated (vi/di)
water column depth
benthic depth
based on suspended solids concentration
of 30 mg/L (see Csed i)
based on biota concentration of 0.4 mg/L
based on DOC concentration of 5 mg/L
fraction of organic carbon (water column
and benthic)
(b)
(c)
(d)
chlorophyll concentration
DOC concentration
suspended solids concentration
biomass concentration
sediment dispersion coefficient
benthic/water column boundary layer
thickness
total volume of benthic region (di x A)
® calculated from: VOL2*BULKD*(1.-100./PCTWA)
W calculated from: (BULKD)(VOL2)(100000)/PCTWA (see Table 2)
(c) calculated from: BNMAS*AREA*.001(see Table 2)
® calculated from: DOC*v2/l000
Table 2. VVWM Equivalents of EXAMS Parameters.
VVWM
Parameters
mi
ni2
VI
V2
Q
HAI
M.SI
[kg]
[kg]
[m3]
[m3]
[m3/s]
[s-1]
[s-1]
Expressed in Terms of EXAMS Parameters
(SUSED)(VOLi) (10-3)
( BULKD \ / mLY 3 kg^
^PCTWA/100jv \ m3 j{ g J
VOLi
(VOL YBIJLFD/I 10° 1 *
v 2 A ^ PCTWAj
STFLO (3600 s/hr)
(KBACWi)(BACPL)/(3600s/hr)
(KBACW2)(BACPL)/(3600s/hr)
17
-------
\JiA2
\JiS2
Kdl
Kd2
[s-1]
[s-1]
[s-1]
m3/kg
m3/kg
(KBACS1)(BNBAC2)r 2 lOOgY 1 hr^
f PCTWA ^ I g Jlseoo s J
I 100 J
(KBACSjXBNBACjf 2 lOOgY 1 hr^
rpciwA ^ [ g J^seoo s J
I 100 J
(AREA)(DSP)
(CHARL)(VOL2)
(KOC)(FROC)(10-3 m3/L)
(KOC)(FROC)(10-3 m3/L)
* Assumes that the density of water is 1,000 kg/m
18
-------
Table 3. EXAMS Standard Parameters.
EXAMS Parameter
PRBEN
PCTWA
BULKD
FROC
CHARL
DSP
AREA
VOLi
VOL2
DEPTHi
SUSED
CHL
DOC1
DOC2
LAT
BNMAS
BNBACi
BNBAC2
BACPLi
BACPL2
DFAC
WIND
STFLO
TCEL
—
—
g/mL
—
m
m2/hr
m2
m3
m3
m
mg/mL
mg/L
mg/L
mg/L
g/m2
~
cfu/lOOg
cfu/mL
—
—
m/s
m3/hr
°C
EXAMS
Value for
Standard
Pond
0.5
137
1.85
0.04
1.05
3.00 xlO'5
10000
20,000
500
2
30
0.005
5.0 mg/L
5.0 mg/L
34
0.006
—
37
1
—
1.19
metfile
0
monthly avg
EXAMS Value for
Standard Drinking
Water Reservoir
0.5
137
1.85
0.04
3.00 xlO'5
52600
144,000
2,630
2.74
0.005
0.005
5.0 mg/L
5.0 mg/L
39.1
0.006
—
37
1
1.19
metfile
Average daily
rainfall (from 36
years of data)
monthly avg
3.1 Farm Pond
The standard farm pond, representing a highly vulnerable exposure scenario, is a pond
located at the edge of a pesticide-treated field. The pond dimensions (1 ha area by 2 m depth),
originally based on a Georgian farm pond size, are in accordance with USDA guidance for pond
construction for an appropriately-sized pond fed by a 10-ha watershed—that is, approximately 2
acres of drainage per acre-ft of storage in central Georgia (USDA, 1982). In the farm pond,
where inflow is assumed to exactly balance evaporative losses (leaching is not modeled). Table 1
gives some of the standard parameters for the pond.
19
-------
3.2 Index Reservoir
The index reservoir represents a natural or artificial lake fed by perennial and ephemeral
streams, varying in flow due to precipitation, evaporation, and runoff from the surrounding
watershed and groundwater discharge. The reservoir is a potential drinking water source that
may be affected by pesticide runoff, spray drift, and leaching to groundwater. The reservoir is a
fixed volume water body with outflow equated to runoff that enters the reservoir. Table 1 gives
some of the standard parameters for the index reservoir.
3.3 Custom Water Body
A custom water body also can be defined in the VVWM with specific dimensions,
including the field area [m2], water body area [m2], initial depth [m], maximum depth [m], and
hydraulic length [m]. The custom water body can be of varying volume, or of constant volume
with (or without) flow through. This third option allows for greater flexibility in evaluating
pesticide fate and transport in a non-standard receiving water body.
4 WWM Evaluations
4.1 Solute Holding Capacity Ratio Sensitivity
As Figure 2 shows, the standard index reservoir has a lower solute holding capacity ratio
than the standard pond, and this is due to the greater water column depth of the reservoir. The
point where 0 is equal to 1 represents the Koc for which the solute capacity in the benthic region
is equal to that in the water column. For the pond, equal capacities occur at Koc of 730 mL/g,
and for the reservoir, the equal capacities occur at 1,000 mL/g. Of course, the water column and
benthic regions are not at equilibrium, so the actual distribution of solute will not be evenly split
between benthic and water column at these Koc values. These values and Figure 2, however,
give some physical insight into how the standard water bodies can potentially distribute solute.
It is also of interest to examine the relative significance of the individual media within
each region with regard to the distribution of solute among them. Figure 3 shows the relative
capacities of the individual media (aqueous and sorbed to biota, DOC, and suspended sediment)
within the water column as a function of Koc. Up to a Koc value of-10,000 mL/g, only the water
phase is significant. Up to Koc values of 100,000, biota partitioning is not significant, and at a
Koc value of 100,000, the combined capacities of all sorbed species amounts to less than 20
percent of the total water column capacity. It can also be seen that, for the standard water
bodies, DOC and suspended sediments have nearly equal capacities for solute.
Figure 4 shows the relative capacities for the benthic region. For the benthic region of
the standard water bodies, DOC and biota partitioning are not significant at any Koc value; the
relative fractions for DOC and biota are on the order of 10"7 to 10"5, which cannot be seen in the
Koc range shown (Figure 4). At a Koc of about 9 mL/g, solute is evenly distributed between the
pore-water-dissolved fraction and the sediment-sorbed fraction. At Koc values above 1,000 mL/g,
the vast majority of solute in the benthic region is sorbed to sediment.
20
-------
1000
100
10
0.1
0.01
10
100 1000
Koc
10000 100000
Figure 2. Solute holding capacity as a function of Koc for the USEPA standard water
bodies.
1 .£.
,c
— 1
o
Q.
n
O
^ 0
£ DC. n R
TJ — U.D
"o •-
w %
$ J
n n A
o u.*!-
•^
O
0
•f no
o u-^
n
ul
n
^^^
Oanar*it\/ nf \A/atpr
Capacity of DOC
Cspscity of Biots
_^
10
100 1000
Koc (ml/g)
10000 100000
Figure 3. Relative solute holding capacity of individual components in water column.
21
-------
Capacity of Water
- Capacity of DOC
Capacity of Sediment
Capacity of Biota
10
100 1000
Koc (ml/g)
10000
100000
Figure 4. Relative solute holding capacity of individual components in benthic region.
4.2 Washout and Overflow Sensitivity
Figures 5 and 6 show how the VVWM overflow modification affects pesticide
dissipation in the standard pond and standard reservoir, respectively. The effective dissipation
half-life due to washout of a pesticide is shown for a range of typical annual average runoff flow
rates as determined from OPP's standard scenarios. This figure only gives an idea of the
potential long-term effect of the VVWM washout addition. Short-term effects will be quite
variable since washout is calculated on a daily basis, and during overflow events, the effective
half-life may differ greatly from long-term averages.
22
-------
Effective Half Life (days)
1 UUU
onn
yuu
Pnn
ynn
/ uu
finn
DUU
cnn
ouu
ADD
'tUU
onn
onn
inn
n
I
\
\
\
\
\
\
\
^~~~~—^^^
0.0005 0.001 0.0015 0.002 0.0025 0.003
Flow Rate (m3/s)
Figure 5. Effective half-life of pesticide due to washout in the standard pond as currently
parameterized (1 hA area, 2 m deep). Range of flow rates are for the current standard field
size (10 hA).
450
400
w 350
re
~ 300
^ 250
»-
ra
I 200
100
50
0.01 0.02 0.03
Flow Rate (m3/s)
0.04
0.05
Figure 6. Effective half-life of pesticide due to washout in the standard reservoir as
currently parameterized (5.26 hA, 2 m deep). Range of flow rates are for the current
standard field size (10 hA).
23
-------
4.3 Photolysis Sensitivity
With the above considerations, the effective photolysis rate in the standard water bodies
only depends on the laboratory-measured photolysis rate, the latitude of the water body, and the
reference latitude of the measured photolysis rate. The effective photolysis rate can be written in
terms of these parameters. For the farm pond, the effective rate is calculated from the following
equation:
JlatJatten
1913 + 868.8cos(0.0349xLsim) Tl-exp[-(Dfac)(d1)a]"
191700 + 87050cos(0.0349xLref)
(52)
Values for the standard water bodies are given in Table 1. Given the values for standard water
bodies in Table l(a = 42.096 m'1); fatten = 0.009981 for the farm pond; fatten = 0.007286 for the
reservoir; and fiat =s 0.804 for 34°.
From equation (52) for a standard farm pond at latitude of 34° and with a reference
laboratory latitude of 0°, the effective aqueous-phase photolysis rate is 124 times lower than the
measured laboratory rate. For the standard reservoir at the same latitude, the rate is 170 times
less than the laboratory determined value. As with hydrolysis, photolysis is assumed to act upon
only dissolved forms of pesticide; therefore, the overall effective hydrolysis rate is further
reduced by the factor fw in equation (5).
A plot of the inverse of equation (52) shows its effect on the half-life as given in Figure
7. This figure shows that depth is nearly proportional to the increase in half-life at the scale
shown. A closer look at depth in Figure 8 shows that the direct proportional relationship begins
at about 0.02 m, indicating that the photolysis has fully attenuated by this depth. Further
increases in half-life are simply due to the greater amount of volume in the water column.
24
-------
200 n
180
.160
1140
120
c 100
o
•-F3
ro
i so
I
0 60
40
20
0.5
1 1.5 2
Depth (m)
2.5
Figure 7. The effect of depth on the effective half-life due to photolysis, showing the
almostproportional linear relationship of half-life with depth.
a 4
m ~
O -3
•5 3
CD
Ll_
I 2
"co
3'
CD
Sz 0
"3
I 0
0.02 0.04 0.06
Depth (m)
0.08
0.1
Figure 8. Smaller scale depth figure, showing that reductions in photolysis half-life become
proportional (linear) with depth after about 0.02 m.
25
-------
4.4 Volatilization
The effect that wind speed has on effective half-life is given in Figure 9 for the standard
pond. The figure shows that wind speed variations will have an increasingly dramatic effect as
Henry's law coefficient is reduced. The use of daily wind speeds in the VVWM thus has
significant short-term implications (acute concentrations) for low Henry's law compounds.
Volatilization as calculated by the VVWM is relatively insensitive to changes in
temperature because OPP has not adopted a temperature adjustment standard for the Henry's
Law coefficient and volatilization data (as a function of temperature) required for registration.
Thus, OPP currently assumes that the Henry's Law coefficient is constant regardless of
temperature.
•v,
a
2=
us
an
ftp. -
70. -
fin -
en
ACl
90 -
m -
n -
i
i
i
i
i
i
i
\
i
\
• ! windsp
• \
\
eed = 1 m/s
eed = 2 m/s
\
•. v
1 "X X^
V ""--.. ^""^ — --.
^
20
40
60
80
100
120
140
160
Henry's Law Constant (m3 atm/mol x 10s)
Figure 9. Effect of Henry's Law Constant and wind speed (measured at 6m) on effective
volatilization half-life of aqueous phase. MW= 100, Temp = 25 °C.
26
-------
tfi
>,
03
03
I
300
250
200
150
100
50
Temp = 30C
Temp = 20C
Temp = 5 C
20
40
60
80
100
120
140
160
Henry's Law Constant (m3 atm/mol x 106)
Figure 10. Effect of Henry's Law Constant and temperature on effective volatilization half-
life of aqueous phase. The lack of temperature sensitivity is a result of not considering the
effect of temperature on Henry's Law Constant. Wind speed = 1 m/s, MW=100.
27
-------
1 *-
— VVWM
0 EXAMS
O)
0.2
20
40
60
80
100
days
Figure 11. Comparison of the volatilization mechanisms of the VVWM and EXAMS for
conditions: solubility = 100 mg/L, MW=100, vapor pressure = 0.1 torr, Koc = 1 mL/g, wind
speed = 1 m/s, temperature = 25° C, and an input mass of 0.02 kg to the water column. A
constant volume condition was used for the VVWM.
5 Testing and Comparison of WWM Solution with EXAMS
Individual processes of the VVWM analytical solution were tested by comparing the
output with that of EXAMS. For these tests, a constant volume condition was imposed on the
VVWM, so that only the processes common to both EXAMS and the VVWM were tested.
Individual processes were tested by either zeroing out all other dissipation or making them
insignificant, and using a single initial aqueous-phase input. The results from a test of the
volatilization routine are shown in Figure 11. Here the analytical solution for volatilization in the
VVWM is captured and correctly formulated. Other processes such as hydrolysis, photolysis,
metabolism, and benthic mass transfer were tested in a similar manner, and all tested equally
well. Combined processes with multiple inputs, including spray drift, erosion, and runoff, as
read from PRZM output files, were also tested. An example is given in Figure 12, which shows
excellent agreement with EXAMS, and further verifies the proper formulation of the processes
within the VVWM.
28
-------
0
100
days
200
300
Figure 12. Comparison of VVWM with EXAMS for the following conditions: MW = 100,
solubility = 100 mg/L, vapor pressure = 0.01 torr, aerobic half-life = 10 days, anaerobic
half-life = 100 days, KoC = 100 mL/g, wind speed = 1 m/s, temperature = 25 °C, and
arbitrarily selected PRZM input fluxes. A constant volume condition was used for the
VVWM.
6 Computer Program Implementation
6.1 Executable and the Command Line
Running the VVWM requires the executable and three input files: a general input file, a
"ZTS" file, and a meteorological file. The executable is run from a command line with the
following command:
fortranvvwm.exe "inputfilename"
wherefortranvvwm.exe is the name of the executable, and inputfilename is a command line
argument that specifies the path and name of the General Input File. For example,
C:\> fortranvvwm.exe "C:\My Documents\Test\MyFirstInputFile.txt"
In this case, the fortranvvwm.exe file is located on the C: directory and the input file is named
MyFirstInputFile.txt and located in the C:\My Documents\Test\ directory. Note: Quotation
marks around the command line argument are necessary if there are any blank spaces in the
argument.
29
-------
6.2 Input Files
6.2.1 General Input File
The input file is a text file with the structure given in Table 4. For lines that hold
multiple inputs, the data is separated by a comma or space. The first line specifies where
additional input will be read and where the output will be delivered.
Table 4. General Input File Format.
Line
1
2
o
J
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Fortran Variable Name
output filename
UNUSED
nchem
is_koc
koc_all(i)
aer_aq_all(i)
temp_ref_aer_all(i)
anae_aq_all(i)
temp_ref_anae_all(i)
photo_all(i)
RFLAT_all(i)
hydro_all(i)
UNUSED
UNUSED
UNUSED
MWT(i)
VAPR_all(i)
SOL_all(i)
xAerobic(i)
xBenthic(i)
Type
character(256)
integer
logical
real
real
real
real
real
real
real
real
real
real
real
real
Real
Description
Full path and name of main output file (less suffix).
This establishes the base name and location of the output
files.
This also specifies the name of the *.zts file that will be
read for the mass and water flow. This input file must be
named outputfilename.zts where outputfilename is the
string defined by the variable outputfilename.
1 = parent only, 2 = parent and degradate, 3= parent,
degradate 1, degradate 2 (sequential)
Establishes whether the sorption coefficient is Koc or Ka;
True = Koc , False = Ka
Sorption coefficient (mL/g); the number of values
should match nchem
Water column degradation half-life (days); the number
of values should match nchem
Reference temperature for water column degradation;
the number of values should match nchem
Benthic degradation half-life (days); the number of
values should match nchem
Reference temperature for benthic degradation; the
number of values should match nchem
Photolysis half-life (days); the number of values should
match nchem
Reference latitude for photolysis; the number of values
should match nchem
Hydrolysis half-life (days); the number of values should
match nchem
Molecular Weight; the number of values should match
nchem
Vapor Pressure (torr); the number of values should
match nchem
Solubility (mg/L); the number of values should match
nchem
Molar Conversion Factor for water column degradation;
the number of values should match (nchem- 1): parent to
degradate 1, degradate 1 to degradate 2
Molar Conversion Factor for benthic degradation; the
number of values should match (nchem- 1): parent to
degradate 1, degradate 1 to degradate 2
30
-------
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
xPhoto(i)
xHydro(i)
UNUSED
UNUSED
UNUSED
UNUSED
UNUSED
QT
scenario_id
metfilename
UNUSED
UNUSED
UNUSED
burialflag
UNUSED
UNUSED
UNUSED
UNUSED
D_over_dx
PRBEN
benthic depth
porosity
bulk_density
FROC2
DOC2
BNMAS
DFAC
SUSED
CHL
FROC1
DOC1
PLMAS
UNUSED
UNUSED
UNUSED
napp
appdate_sim_ref(i)
simtypeflag
Real
real
real
Character(50)
Character(256)
logical
real
real
real
real
real
real
real
real
real
real
real
real
real
real
integer
integer
integer
Molar Conversion Factor for photolysis; the number of
values should match (nchem-1): parent to degradate 1,
degradate 1 to degradate 2
Molar Conversion Factor for hydrolysis; the number of
values should match (nchem-1): parent to degradate 1,
degradate 1 to degradate 2
Q10 factor by which degradation increases for every 10
°C rise in temperature.
Text to describe the field scenario. Used for naming
output files.
Full path and file name of the meteorological file.
If set to .TRUE, this will activate pesticide removal by
sediment burial.
Mass transfer coefficient (m/s) as defined by D/Ax in
Eqn . 46
Xa in equation 40 and 4 1
Depth of benthic region (m)
Porosity of benthic region (--)
Bulk density of benthic region (g/mL). Mass of solids
per total volume.
Fraction of organic carbon on sediment in benthic
region.
Concentration of dissolved organic carbon in benthic
region (mg/L)
Areal concentration of biosolids in benthic region (g/m2)
Photolysis parameter defined in eqn. 23
Suspended solids concentration in water column (mg/L)
Chlorophyll concentration in water column (mg/L)
Fraction of organic carbon on suspended sediment in
water column.
Concentration of dissolved organic carbon in water
column (mg/L)
Concentration of biosolids in water column (mg/L)
Number of spray drift events that will be used to apply
pesticide mass to pond
Dates of spray drift events reference to days of the
simulation (first day of simulation =1)
Flag to identify the type of water body: 1= User defined
parameters; 2=USEPA Pond; 3=USEPA Reservoir; 4 =
-------
59
60
61
62
63
64
65
66
afield
area
depth_0
depth max
spray(i)
flow_averaging
baseflow
Cropped fraction
real
real
real
real
real
integer
real
real
Reservoir with f
Area of adjacent runoff producing field. This is used to
convert area-normalized pesticide mass in the mass-
input file to actual mass (m2).
Area of water body (m2).
Depth at which the input concentrations of physical
parameters (e.g., suspended solids, CHL., etc) were
measured.
Maximum depth that water can rise before overflow (m).
Mass of pesticide (kg) delivered from spray drift
corresponding to dates of appdate sim ref(i)
Number of days that are used to average the influent
water flow. If = 0, then the flow rate to be used in the
program is the average flow rate of the entire simulation.
Provided an additional constant flow through the
waterbody m3/s
Holds the Fraction of Cropped Area. Of the watershed.
Only used so that it is recorded in the output. Program
does not use these values for calculations
6.2.2 ZTS Input File
The ZTS file contains daily mass inputs, water flows, and sediment deliveries. The ZTS file is
automatically created by the PRZM model or it may be manually created. It must be named as:
inputftlename.zts
where inputfilename is the same as that used above for the Input File and likewise specifies the
full path and name of the file. The ZTS file has a format as shown in Table 5. Each line (except
the first three) represents the daily values for each input variable. Data on each line may be
separated by a space or comma. The number of data lines in the file must correspond to the
number of days in the meteorological file.
TableS. ZTS File Format.
Line#
1
2
O
4
N
Data
not read
not read
not read
X, X, X,
Q, B, MRp, MEp, MR1, ME1, MR2, ME2
X, X, X,
Q, B, MRp, MEp, MR1, ME1, MR2, ME2
Where
N refers to the last line in the ZTS file. It corresponds to the number of records in the
meteorological file.
X is dummy data that is not used, but must be in place. In a PRZM-generated ZTS file
these are the year, month, and day values.
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Q is the daily water per field area that flows into the water body (cm/ha/day). This is
used for calculating washout and volume changes of the water body, if these options
are chosen.
B is the daily solids per field area that enters the water body (tonnes/ha/day) and is used
for burial if that option is chosen.
MRp is mass of pesticide per field area entering water body by runoff (g/ha/day)
MEp is mass of pesticide per field area entering water body by erosion (g/ha/day)
If degradate 1 is being simulated (nchem >1), then the following would be entered:
MR1 is mass of degradate 1 per field area entering water body by runoff (g/ha/day)
ME1 is mass of degradate 1 per field area entering water body by erosion (g/ha/day)
If degradate 2 is being simulated (nchem =2), then the following would be entered:
MR2 is mass of degradate 2 per field area entering water body by runoff (g/ha/day)
ME2 is mass of degradate 2 per field area entering water body by erosion (g/ha/day)
6.2.3 Meteorological File
The meteorological file is specified in line 30 of the input file. This file has the same formatting
as that required by PRZM. The fortran formatting for each line is:
IX, 312, 4F10.0
With the input variable of: MM, MD, MY, PRECIP, PEVP, TEMP, WIND
where
MM = meteorological month
MD = meteorological day
MY = meteorological year
PRECIP = precipitation (cm/day)
PEVP = pan evaporation data (cm/day)
TEMP = temperature (°C)
WIND = wind speed (cm/sec)
Example Partial Meteorological File:
010161 0.00 0.30 9.5 501.6 240.3
010261 0.10 0.21 6.3 368.0 244.3
010361 0.00 0.28 3.5 488.3 303.0
The meteorological file determines the simulation time. The simulation will start at the first date
and end with the last date in this file. Dates must be continuous in the file. The file does not
have to start or end on any particular calendar date; the program accepts partial years.
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6.3 Output Files
6.3.1 Regulatory Summary Output File
A summary file that contains USEPA regulatory values for concentration is produced for
each chemical simulated and is named:
outputfilename_scenario_ID_waterbodytext_Parent-Degradate.txt
where
outputfilename - as specified in Line 1 of input file.
scenario ID - as specified in Line 29 of input file.
waterbodytext - Depending on the water body simulated, this will be "Custom", "Pond",
or "Reservoir" if simtypeflag (Input Line 57) = 1, 2, or 3, respectively
Parent-Degradate - This will be "Parent", "Degradatel", or "Degradate2" and indicates
which of the products are contained in the file.
6.3.2 Daily Values Output File
An output file that contains the daily values for water body depth, water column
concentration, and benthic pore water concentration is created with the name:
outputftlename_scenario_ID_waterbodytext_Parent-Degradate_daily.txt
7 Summary
Many of the individual processes and components of the USEPA VVWM (e.g.,
metabolism, photolysis, volatilization) are consistent with EXAMS. The VVWM differs from
EXAMS in ways that are intended to improve upon modeling methods. This includes improving
the characterization of temporal variability, hydrologic balances, and the efficiency and speed at
which computations are made. These differences are summarized below:
1. The VVWM changes parameter values on a daily basis (e.g., temperature, wind, flow),
corresponding to the daily input data from the meteorological file and from PRZM.
EXAMS changes parameters on a monthly basis, using calendar month averages for
values.
2. The VVWM can implement daily changes in temperature, which are based on the
preceding 30-day average air temperature, thereby simulating the temperature lag of
water bodies with air temperature. EXAMS can only make changes on a monthly basis,
and temperatures used in the standard water bodies do not lag air temperatures, but
instead are current calendar month averages.
3. The VVWM considers variations in the water body volume due to hydrologic inputs;
EXAMS does not.
4. The VVWM is solved analytically and is specifically designed to solve the standard two-
region OPP water body scenarios.
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8 References
Banks, R. B., 1975. Some Features of Wind Action on Shallow Lakes. Journal of the
Environmental Engineer ing Division., ASCE. 101(EE5), 813-827.
Burns, L.A., Cline, D.M., and Lassiter, R.P., 1982. Exposure Analysis Modeling System
(EXAMS): User Manual and System Documentation. EPA-600/3-82-023, U.S. EPA.
Burns, L.A., 1997. Exposure Analysis Modeling System (EXAMS II) Users Guide to Version
2.97.5, EPA/600R-97/047, U.S. EPA
Carsel, R., J. Imhoff, P. Hummel, J. Cheplick, and A. Donigan, 1997. PRZM 3.1 Users Manual,
National Exposure Research Lab, Office of Research and Development, U.S. Environmental
Protection Agency, Athens, Georgia.
Burns, L.A., 1985. Models for predicting the fate of synthetic chemicals in aquatic ecosystems,
in: Validation and Predictability of Laboratory Methods for Assessing the Fate and Effects of
Contaminants in Aquatic Ecosystems, ASTM STP 865, T.P. Boyle, Ed., American Society of
Testing Materials, Philadelphia, pp 176-190.
Cusler, E.L., 1984. Diffusion: Mass Transfer in Fluid Systems, Cambridge University Press, New
York
Liss, P.S., 1973. Processes of Gas Exchange Across an Air-Water Interface. Deep Sea Research,
20(3), 221-238.
Shwarzenbach, R.P., Gschwend, P.M., and Dieter, D.M., 1993. Environmental Organic
Chemistry, John Wiley & Sons, New York.
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