Directory UMM :Data Elmu:jurnal:A:Agricultural Water Management:Vol44.Issue1-3.Apr2000:
Agricultural Water Management 44 (2000) 225±245
Simulation of water and solute transport in ®eld
soils with the LEACHP model
M. Dusta,*, N. Baranb, G. Errerac, J.L. Hutsond, C. Mouvete,
H. SchaÈferf, H. Vereeckeng, A. Walkerh
a
Institut fuÈr Chemie und Dynamik der GeosphaÈre: ICG-5, Radioagronomie,
Forschungszentrum JuÈlich GmbH, D-52425, Germany
b
Chambre d'Agriculture de L'Aisne, 38 Boulevard de Lyon, 02007 Laon Cedex, France
c
Istituto Chimica Agraria ed Ambientale, Universita Cattolica del Sacro Cuore,
Via Emilia Parmense 84, I-29100 Piacenza, Italy
d
School of Earth Sciences, Faculty of Science and Technology, Flinders University of South Australia,
GPO Box 2100, Adelaide, SA 5001, Australia
e
BRGM, Avenue de Concyr B.P. 6009, F-45060 OrleÂans cedex 2, France
f
Bayer AG, Landwirtschaftszentrum Monheim, D-51368 Leverkusen/Bayerwerk, Germany
g
Institut fuÈr Chemie und Dynamik der GeosphaÈre: ICG-4, ErdoÈlchemie und organische Geochemie,
Forschungszentrum JuÈlich GmbH, D-52425, Germany
h
Horticulture Research International, Wellesbourne, Warwick CV35 9EF, UK
Abstract
LEACHP is a modular package for calculating the one-dimensional vertical water and solute ¯ux
in horizontally layered soils under transient conditions. Data from ®eld studies conducted in a sandy
soil (Vredepeel, The Netherlands) and in a loamy soil (Weiherbach, Germany) were used by ®ve
groups to simulate water ¯ow and bromide and pesticide transport with the LEACHP model.
Calibrated outputs were compared to the actual ®eld values.
Soil hydraulic properties derived from laboratory measurements performed best to predict soil
moisture pro®les of ®eld soils. For small-scale lysimeters calibration was necessary to simulate
drainage ¯uxes that were within the wide range of experimental values. These calibrated parameters
failed to predict increased drainage volumes observed under additional irrigation. Measurement of
all soil water balance terms would allow a more thorough evaluation of the hydraulic component of
LEACHP.
Bromide pro®les were not well simulated on the sandy soil where considerable plant uptake was
observed. Additionally, zones of immobile soil water might have been present. Residue pro®les of
the volatile pesticide ethoprophos in soil were best simulated by groups that accounted for
*
Corresponding author. Present address: DuPont de Nemours (France) S.A., European Research and
Development Center, F-68740 Nambsheim, France.
E-mail address: martin.dust@fra.dupont.com (M. Dust).
0378-3774/00/$ ± see front matter # 2000 Elsevier Science B.V. All rights reserved.
PII: S 0 3 7 8 - 3 7 7 4 ( 9 9 ) 0 0 0 9 3 - 1
226
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
volatilisation in their simulations. Different descriptions of the soil sorption process for the mobile
pesticide bentazone between groups were dominated by different input of half-life values and
hydraulic properties. Although bromide residue pro®les were predicted reasonably well in the
loamy soil, it was not possible to predict isoproturon dissipation during summer with degradation
parameters calibrated in a winter simulation.
Predictions of soil water content pro®les and leaching volumes can be used with con®dence
especially after calibration given that preferential ¯ow processes are not predominant. Although
important input data for pesticide transformation and transport could be derived from extensive
laboratory scale experiments, these did not represent all processes that could affect pesticide fate
and behaviour under ®eld conditions. Calibration did not signi®cantly enhance the predictive
capability of the solute transport simulations. # 2000 Elsevier Science B.V. All rights reserved.
Keywords: Pesticide leaching modelling; Model validation; LEACHP; Risk assessment
1. Introduction
Simulation models are increasingly used to predict pesticide leaching (Cohen et al.,
1995). Deterministic±mechanistic models consist of representations of single processes
based on physical principles formulated as mathematical equations. Solution of these
equations requires a full specification of the boundary conditions of the system in space
and time and the initial conditions for each of the state variables. These models are
comprehensive; simulation results allow insight into the mechanisms and identify
sensitive parameters that govern water and solute fluxes in the dynamic soil±water±air
system. Therefore, simulation models currently present a useful tool to assess pesticide
fate and behaviour in soil (Russell, 1995).
Elaborate input parameters describing hydraulic and solute properties are often
lacking, which prevents proper use of research models like LEACHP (Walker et al.,
1995). In order to gain confidence in the model performance, repeated testing of
predictions against field data is necessary. However, accurate measurements of solute
concentration distributions are not often available (Pennell et al., 1990). As a result,
currently used models within the EU registration process have a vague validation status
(Boesten et al., 1995). It is thus unclear how accurately pesticide leaching models reflect
solute transport in field studies where a chemical is exposed to all of the dynamic
processes that determine its fate.
In this paper, the mechanistic±deterministic one-dimensional LEACHP model (Hutson
and Wagenet, 1992) was tested by several groups against data from field studies
conducted in the Netherlands at Vredepeel (Boesten and Van der Pas, 2000) and in
Weiherbach, Germany (Schierholz et al., 2000).
Within this exercise the modelling protocol described by Vanclooster et al. (2000) was
followed. In a first step the predictive capability of the LEACHP model was tested on two
data sets. This situation reflects the use of models in a regulatory context where
calibration is generally not done. In a second step the model was calibrated with regard to
hydrology, solute transport and pesticide related parameters and further tested on new
results. Evaluation of the model performance in terms of soil and solute water balance
227
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
terms and state variables was carried out to determine the degree of confidence in the
model calculations.
2. Materials and methods
2.1. Model description
LEACHM (Leaching Estimation And CHemistry Model) is a modular package for
calculating the one-dimensional water flux and solute movement in vertically layered
soils under transient conditions. The latest version is described in detail by Hutson and
Wagenet (1992). LEACHM has several component models, each of which describes a
different class of chemical. The water flow module is common to all components. In this
work we used LEACHP which simulates pesticide fate and transport.
Water flow is modelled with the one-dimensional Richards' equation. The y±h
relationship is described with a two-part function (Hutson and Cass, 1987),
h
a 1 ÿ Y=Ys 0:5 Yc =Ys ÿb
1 ÿ Yc =Ys 0:5
h a Y=Ys ÿb ;
;
0 > h > hc
(1a)
hc > h > ÿx
(1b)
3
ÿ3
where h is the pressure potential, ys the saturated water content (m m ) and a, b are
constants. hc,yc de®nes the point of intersection of the two curves hc a[2b/(1 2b)]ÿb
and yc 2bys/(1 2b). For the hydraulic conductivity the following equation is available:
K Y Ks Y=Ys 2b2p
(2)
where K(y) is the hydraulic conductivity (mm per day), Ks is the hydraulic conductivity at
saturation ys and p is a pore interaction parameter. Alternatively, for the K±y±h
relationship the following equations are available (Mualem, 1976; Van Genuchten, 1980):
Y h Yr
Ys ÿ Yr
m
1 ajhjn
(3)
where y is the volumetric water content (m3 mÿ3), h the pressure head (mm), yr the
residual water content (m3 mÿ3), and a (mmÿ1), n (±), and m (±) are empirical
parameters.
m 2
(4)
K Se Ks Sle 1 ÿ 1 ÿ Se1=m
where Se is the effective saturation (y ÿ yr/ys ÿ yr), l the pore connectivity parameter (±),
and m the empirical parameter from Eq. (3).
The water flow equation is combined with the convection±dispersion equation in
LEACHP. Solute sorption to soil can either be described with a linear Eqs. (5) and (6) or
non-linear Eq. (7) isotherm or by two site sorption Eq. (8). For a linear isotherm
Cs Kd Cl
(5)
228
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
where Kd is the linear distribution coef®cient (dm3 kgÿ1). Kd can vary with depth. For
pesticides, Kd values are calculated from the organic carbon partition coef®cient Koc and
the organic carbon fraction (foc) as
Kd Koc foc
(6)
Non-linear sorption is described with the Freundlich isotherm
Cs kf C nf
(7)
where kf and nf are constants. Non-equilibrium linear sorption assumes that a fraction of
sites (f) display local chemical equilibrium and a fraction (1 ÿ f) is subject to kinetically
controlled sorption and desorption. The sorbed concentration is the sum of sorption to the
kinetic (s1) and equilibrium (s2) sites. Flux density of solute Ja (mg kgÿ1) between the
kinetic sites and solution phase C (mg dmÿ3) is assumed to depend upon the current
degree of non-equilibrium
Ja arb 1 ÿ f kd C ÿ s2
(8)
ÿ3
where a is a phase transfer rate coef®cient and rb the soil bulk density (kg dm ).
The liquid±vapour partition is represented by a modified Henry's law as proposed by
Jury et al. (1983). Degradation of pesticides is assumed to follow first-order kinetics. The
rate constant may be adjusted for temperature and/or water effects. The temperature
correction factor (Tcf) at a temperature t (8C) is calculated as
0:1 tÿtbase
Tcf Q10
(9)
where Q10 is a constant and tbase is the base temperature for which the rate constants are
speci®ed in the data ®le. The water correction factor (Wcf) is set to one in the optimum
water content range, which is between ymax and ymin. If y is higher than the optimum, Wcf
becomes
Wcf Wcfsat
1 ÿ Wcfsat Ys ÿ Y
Ys ÿ Ymax
(10)
where Wcfsat is the relative rate constant at saturation, ys the saturated water content. If the
soil moisture is lower than the optimum water content range the correction factor is
Wcf
max Y; YWP ÿ YWP
Ymin ÿ YWP
(11)
so that the correction factor is zero at wilting point YWP. Furthermore, uptake of
pesticides in the transpiration stream can be included if desired.
In addition to graphical display of the results, statistical criteria, as reported by
Vanclooster et al., (2000) were applied to compare the results from different
groups. Apart from the Modelling Efficiency (EF) the Scaled Root-Mean-Square-Error
(SRMSE)
n
1 1X
Pi ÿ Oi 2
SRMSE
O n i1
(12)
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
229
was calculated where n is the number of observations, Oi are the observed values, Pi the
the average of the observed data. The SRMSE normalises the
predicted values and O
overall sum of squares to the number of observations and the observed mean. EF values
below zero indicate a model performance which is poorer than simply using the average
value of the observations. A perfect match between observed and predicted data is
indicated by values of zero for the SRMSE and 1 for the EF, respectively. Both criteria are
dimensionless. In order to match the horizons for pesticide residue sampling, simulated
results were integrated over the respective layer depth for statistical analysis.
2.2. Input parameters
2.2.1. Vredepeel
Four groups worked with the Vredepeel data set (groups A, B, C and D). Parameters
were calibrated after the first simulation exercise if considered justified and/or necessary.
This paper will only report these calibrated runs.
All participants used climate data, including potential evapotranspiration rates,
provided with the data set for the simulation period from 23 November 1990 until 10
March 1992. Apart from sowing dates, crop development dates were estimated by the
modellers. The description of the water retention characteristics and discretisation of the
soil profiles are given in Table 1. Groups A, B and C used soil texture information that
was provided with the Vredepeel report for input to pedo-transfer functions that are part
of the LEACHP model and performed no calibration. Group D fitted Eqs. (1a) and (1b) to
y±h values measured with the evaporation method (Table 1). For the initial soil moisture
profile, all groups used reported data. Due to difficulties in simulating the groundwater
level as a function of time either free drainage or measured groundwater levels were
chosen as a lower boundary condition.
The major differences in assumptions made by each group for calculating the solute
fate and transport are presented in Table 2. Linear equilibrium sorption was assumed by
group A for bentazone and for both pesticides by group B. For ethoprophos group A
considered linear non-equilibrium sorption. Each group independently derived Koc values
from raw data of laboratory sorption experiments conducted at 5 and 158C (Table 3).
Parameters for non-linear equilibrium sorption were also derived from sorption
experiments that were provided with the Vredepeel report (groups C and D). Sorption
parameters were calibrated either according to soil residue extraction results (group A,
ethoprophos) or expert judgement (group D, ethoprophos) (Table 3).
Half-life values for the pesticides were derived from laboratory degradation
experiments (Table 4). Differences in resulting input parameters for the calibrated
runs were either due to a different choice of laboratory studies for the fitting procedure or
to interpolation of data from different soil layers. Group A initially used a uniform halflife value for the 0±120 cm soil layer from laboratory degradation studies conducted at
58C with ethoprophos and bentazone, respectively. In the calibrated runs, additional
data were used that were derived from laboratory experiments with subsurface soil of the
100 and 200 cm soil layer at 108C for both pesticides (Table 4). Group B used laboratory
degradation data from the 0±25 cm soil layer at 158C for ethoprophos and bentazone,
assuming a decline of degradation with depth. No calibration of pesticide half-life
230
Parameter
Group A
Group B
Group C
Group D
Soil pro®le depth (cm)
Depth of layers (cm)
Retentivity model
Parameter estimation
120
5
Eqs. (1a) and (1b)
ptf by Thomasson and
Carter, 1992
No
y, from report
Free drainage
112
4
Eqs. (1a) and (1b)
ptf by Thomasson and
Carter, 1992
No
y, from report
Free drainage
200
10
Eqs. (1a) and (1b)
ptf by Rawls and Brakensiek,
1982
No
y, from report
Measured ground water level
195
7.5
Eqs. (1a) and (1b)
®tting of measured y±h
Calibration
Initial pro®le
Lower boundary condition
Yes
y, from report
Measured ground water level
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
Table 1
Discretisation of the soil pro®le and hydraulic parameters for the Vredepeel simulations
231
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
Table 2
Model assumptions for solute fate and transport for the Vredepeel study for the calibrated runs
Parameter
Group A
Group B
Group C
Group D
Sorption
Ethoprophos
Linear non-equilibrium
Linear
equilibrium
Linear
equilibrium
Non-linear
equilibrium
Non-linear
equilibrium
Non-linear
equilibrium
Non-linear
equilibrium
No
No
No
First-order, f(T,y)
None
No
No
No
First-order, f(T,y)
None
No
No
No
First-order
Yes
Bentazone
Linear equilibrium
Plant uptake
Bromide
Ethoprophos
Bentazone
Degradation
Volatilisation
No
Yes
Yes
First-order, f(T,y)
Yes
values was carried out. Group C and D also used the information of ethoprophos
and bentazone degradation in the 0±25 cm soil layer at 158C. For the subsoil group
C assumed decreased half-lives in proportion to the decreasing organic carbon contents
of the soil. Group D simulated ethoprophos degradation in the 60±195 cm soil layer
by using data from laboratory degradation studies conducted at 108C with soil from
the 100±200 cm soil layer. Bentazone subsoil degradation data of group D were derived
from laboratory degradation experiments. For the 30±105 cm soil layer they used
laboratory degradation data from the 50±100 cm soil layer at 108C, whereas for the 105±
195 cm soil layer the experiments with soil from the 100±200 cm soil layer were used.
Calibration of the half-life value of bentazone in the 30±105 cm soil layer was performed
(Table 4).
Groups A, B and C accounted for the effect of soil moisture contents on
pesticide degradation with estimated parameters. Group A calibrated Wcfsat. Group D
ran LEACHP with the degradation rate kept constant at different soil moisture and/
or temperature conditions. Group A found it necessary to calibrate tbase and/or the
originally chosen Q10-value for the temperature correction of the degradation rate
constant (Table 4). Parameters for volatilisation of ethoprophos were calibrated as
indicated in Table 4.
Table 3
Values of the ethoprophos and bentazone sorption in the Vredepeel study (calibrated values in brackets)
Group A
Koc
Ethoprophos
Bentazone
a
a
f
a
158.3
4.8a
b
(0.85)
b
(0.002)
Group B
Group C
Koc
Kfoc
a
125.0
5.6a
n
a
152.0
3.7a
Mean from all laboratory sorption experiments at 5 and 158C.
Estimated from soil residue extraction.
c
Estimated value.
b
Group D
Kfoc
a
0.9
1.0a
n
a
c
135.0 (200)
5.0a
0.85a
0.9a
232
Table 4
Parameters for pesticide degradation, soil moisture and temperature correction of the degradation rate constant and parameters for volatilisation: Vredepeel study,
ethoprophos and bentazone (calibrated values in brackets)
Ethoprophos
Bentazone
Q-10 value
tbase[8C]
ymax
ymin
Wcfsat
Group A
Group B
Group C
Group D
cm
DT50
cm
DT50
cm
DT50
cm
DT50
0±120
(0±25)
(25±100)
(100±120)
0±120
(0±25)
(25±100)
(100±120)
3.0 (3.85)
20 (5)
0.08
ÿ300
0.6 (0.87)
347
(347)
(630)
(433)
204
(204)
(815)
(96)
0±25
25±100
100±120
132
198
264
0±30
30±60
154
301
0±60
60±195
107
277
0±25
25±100
100±120
37
56
75
0±30
30±60
50
100
0±30
30±105
50
693
(139)
87
2.2
15a/20b
0.08
ÿ300
1.0
2.0
10
0.08
ÿ300
0.6
105±195
±
Saturated vapour density [mg dmÿ3]
Ethoprophos
0.0045 (0.0009)
Bentazone
0.00004
1.6 E-5 (1.4 E-3)
1.6 E-5
Water solubility [mg dmÿ3]
Ethoprophos
Bentazone
750.0 (700.0)
500.0
a
b
For ethoprophos.
For bentazone.
750.0
500.0
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
Parameters
233
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
Table 5
Hydraulic parameters for the Weiherbach simulations
Parameters
Field trial
Lysimeters
Soil pro®le depth (cm)
Depth of layers (cm)
Retentivity model parametrisation
Conductivity model parametrisation
Initial pro®le
Lower boundary condition
95
5
Eq. (3) from report
Eq. (4) from report
Preliminary simulations
Fixed water table at 13.5 m
45
5
Eq. (3) from report
Eq. (4) from report
Preliminary simulations
Lysimeter condition
2.2.2. Weiherbach
Only one group used the Weiherbach data set. Results from the 1993/1994 field trial
and lysimeter study were used for calibration of parameters. The simulation period was
from 6 December 1993 to 26 April 1994. The calibrated parameters were then
independently tested against the 1995 studies in simulations starting from 11 May to 23
June. In this paper only the performance of the calibrated parameters for the 1993/1994
and 1995 studies will be presented. In 1995 additional irrigation of 260 mm was applied
between 22 May and 19 June on the field plot. Four lysimeters were divided into two
groups that received 140 mm (irrigated I) and 280 mm (irrigated II), respectively, in this
period. In all simulations climate data was used from the report, including potential
evapotranspiration rates. Crop development dates were estimated for winter wheat (1993/
1994) and summer barley (1995).
For the simulations, the soil profile was divided into 5 cm segments. Soil profile depths
and bottom boundary conditions are given in Table 5. Soil hydraulic parameters for Eqs.
(3) and (4) as reported by Schierholz et al. (2000) were used. Calibration of soil hydraulic
properties were conducted for lysimeters, but not for the field experiment. Daily potential
evapotranspiration rates were multiplied by the factor 1.25 to account for increased
evapotranspiration. Additionally, a reduced Ksat in the lowest layer of the lysimeter due to
its boundary construction was assumed (36 mm per day instead of 72 mm per day).
Plant uptake and volatilisation were not considered for bromide or isoproturon. For the
pesticide a linear equilibrium sorption isotherm was assumed. Kd-values determined in
batch-experiments with soil from different layers and provided with the report were used
(Table 6). No calibration was performed on the sorption parameters. Half-life values for
Table 6
Solute input parameters for the Weiherbach data set
[m]
DT50 [days]
Original values
0.0±0.3
14.7a
0.3±2.0
138.6b
Calibrated values
0.0±0.3
7.4
0.3±2.0
69.3
a
b
ymax
ymin
Wcfsat
Q10
tbase [8C]
kd [l kgÿ1]
0.28a
0.28a
ÿ202a
ÿ202a
0.0a
0.0a
2.0
2.0
25.0
25.0
2.00
1.69
0.20
0.20
ÿ500
ÿ500
0.6
0.6
2.0
2.0
25.0
25.0
2.00
1.69
Derived from laboratory studies of top soil layer at 258C and 20, 40 and 60 % water holding capacity.
Derived from laboratory studies of 100±200 cm soil layer at 208C.
234
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
the pesticides and parameters for the soil moisture correction were derived from
laboratory degradation experiments from the two soil layers at different soil moisture
contents (Table 6). Isoproturon profiles of the 1993/1994 field experiments were
successfully simulated only after calibration of the half-life value and the soil moisture
correction parameters (Table 6).
3. Results and discussion
3.1. Vredepeel
Soil moisture profiles were simulated best using parameters for the water retention
characteristic derived from y±h data from laboratory experiments (group D, Fig. 1). In
these simulations the lowest values of SRMSE and positive values of the EF were
observed (Table 7). Further calibration of hydraulic parameters would be indispensable to
more accurately predict soil moisture conditions. The use of different pedo-transfer
functions resulted in different soil moisture profiles (groups A, B against C, Fig. 1).
Different estimation of soil water uptake by plants might have led to differences in
simulated soil moisture profiles between groups A and B, which used identical pedotransfer functions and bottom boundary conditions (Fig. 1).
Bromide transport was rather poorly predicted by all LEACHP-simulations, as
indicated by the high values for the SRMSE and the low or negative numbers of the EF
(Table 7). The somewhat better statistical values of bromide for group D than for groups
A, B and C are probably a direct consequence of the better simulation of soil moisture,
achieved with the assumptions of group D. The field observation of bromide remaining in
Fig. 1. Soil moisture pro®les on day 103, 278 and 474 at the Vredepeel site: experimental results and LEACHPsimulations of four groups.
235
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
Table 7
Ranges of the statistical criteria for LEACHP model performance on soil moisture, bromide and pesticide
pro®les for the Vredepeel data set after calibration
Group
SRMSE
Volumetric water contents day 103, 278 and 474
A
0.15
B
0.16
C
0.28
D
0.16
Bromide pro®le day 103, 278 and 474
A
0.95
B
0.77
C
0.60
D
0.42
Bentazone pro®le day 103 and 278
A
0.81
B
2.34
C
0.50
D
0.39
Ethoprophos pro®le day 103, 278 and 474
A
0.78
B
1.36
C
0.78
D
0.99
Total ethoprophos
A
0.38
B
1.46
C
1.08
D
0.98
EF
to
to
to
to
0.39
0.93
0.54
0.34
ÿ0.1
ÿ4.1
ÿ5.5
ÿ0.3
to
to
to
to
1.13
1.77
0.96
0.94
ÿ11.6 to ÿ1.9
ÿ33.2 to ÿ0.8
ÿ1.8 to ÿ1.1
ÿ0.4 to 0.5
to 1.12
to 0.81
to 0.49
ÿ0.5 to ÿ7.0
ÿ45.3 to ÿ1.1
ÿ0.3 to 0.3
ÿ2.3 to ÿ0.5
to
to
to
to
ÿ5.7 to 0.7
ÿ159.8 to 0.1
ÿ114.8 to 0.7
ÿ0.9 to 0.6
3.14
14.98
11.64
7.58
to
to
to
to
0.7
ÿ0.1
0.1
0.9
0.6
ÿ4.9
ÿ3.8
0.7
the top soil layer was not predicted by any of the simulations, suggesting the occurrence
of immobile soil water zones after application (Fig. 2). Plant uptake of bromide was not
accounted for in any of the runs, but was observed in considerable amounts in the winter
wheat plants (Boesten and Van der Pas, 2000). Additionally, turnover of plant litter may
have released amounts of bromide during the study, leading to a steady supply of solute at
the surface.
Calculated bentazone profiles had a larger variance between groups compared to the
measurement/sampling variability observed in the Vredepeel soil (Fig. 3). According to
the statistical criteria, the bentazone profiles were not accurately predicted even after
calibration of sorption and degradation parameters (Table 7). Parameters derived from
laboratory studies under controlled conditions did not reflect pesticide behaviour in a
dynamic system like the field soil. Differences between predicted bentazone profiles were
observed between the four groups despite similar half-life values and sorption parameters
(Tables 3 and 4). Apart from differences in predicted water fluxes, diverse values for the
temperature correction (Table 4) of the degradation process might be an explanation for
this variability.
Total ethoprophos residues were best predicted by group A and D during the 474 days
of the field study (Fig. 4, Table 7). Both groups accounted for volatilisation of the
236
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
Fig. 2. Bromide pro®les on day 103, 278 and 474 at the Vredepeel site: experimental results and LEACHPsimulations of four groups.
pesticide in the LEACHP-simulations, although some calibration of parameters was
necessary (Table 4). Predictions of the ethoprophos profiles were more accurate
compared to the bentazone simulations (Fig. 5). Calibration of either two site sorption
parameters (group A) or the Kfoc-value (group D) resulted in better predictions compared
to those without calibration. Leaching of ethoprophos was overestimated by groups A, B
and C, penetration of ethoprophos was best simulated by group D, using a calibrated Kfoc
value (Fig. 5). Ethoprophos residues in the soil profile 474 days after application were
Fig. 3. Bentazone pro®les on day 103, 278 and 474 at the Vredepeel site: experimental results and LEACHPsimulations of four groups.
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
237
Fig. 4. Total ethoprophos residues in the soil pro®le at the Vredepeel site: experimental results and LEACHPsimulations of four groups.
overestimated by all groups, illustrating the problems of transferring results from
laboratory experiments to the field scale under outdoor conditions.
3.2. Weiherbach ®eld plot
Soil water profiles were reasonably well simulated for the 1993/1994 period
(December±April) without fitting of the hydraulic parameters (Fig. 6). At the end of
Fig. 5. Ethoprophos pro®les on day 103, 278 and 474 at the Vredepeel site: experimental results and LEACHPsimulations of four groups.
238
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
Fig. 6. Soil water contents, pro®les of bromide and isoproturon at the Weiherbach ®eld plot, 1993/1994; experimental results and simulations with the LEACHP model:
calibration.
239
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
Table 8
Ranges of statistical criteria for LEACHP model performance on soil moisture, bromide and isoproturon pro®les
for the Weiherbach ®eld plot
Volumetric water contents
Bromide pro®le
Isoproturon profile
Calibration 1993/1994
day 10, 17, 56 and 141
Evaluation 1995 day 10,
17, 56 and 141
SRMSE
EF
SRMSE
EF
0.09 to 0.22
0.58 to 1.11
1.22 to 3.31
ÿ3.3 to 0.01
ÿ0.4 to 0.7
ÿ0.4 to 0.3
0.30 to 0.55
0.57 to 7.57
1.35 to > 100.0
ÿ25.9 to ÿ2.6
ÿ343.5 to 0.3
Simulation of water and solute transport in ®eld
soils with the LEACHP model
M. Dusta,*, N. Baranb, G. Errerac, J.L. Hutsond, C. Mouvete,
H. SchaÈferf, H. Vereeckeng, A. Walkerh
a
Institut fuÈr Chemie und Dynamik der GeosphaÈre: ICG-5, Radioagronomie,
Forschungszentrum JuÈlich GmbH, D-52425, Germany
b
Chambre d'Agriculture de L'Aisne, 38 Boulevard de Lyon, 02007 Laon Cedex, France
c
Istituto Chimica Agraria ed Ambientale, Universita Cattolica del Sacro Cuore,
Via Emilia Parmense 84, I-29100 Piacenza, Italy
d
School of Earth Sciences, Faculty of Science and Technology, Flinders University of South Australia,
GPO Box 2100, Adelaide, SA 5001, Australia
e
BRGM, Avenue de Concyr B.P. 6009, F-45060 OrleÂans cedex 2, France
f
Bayer AG, Landwirtschaftszentrum Monheim, D-51368 Leverkusen/Bayerwerk, Germany
g
Institut fuÈr Chemie und Dynamik der GeosphaÈre: ICG-4, ErdoÈlchemie und organische Geochemie,
Forschungszentrum JuÈlich GmbH, D-52425, Germany
h
Horticulture Research International, Wellesbourne, Warwick CV35 9EF, UK
Abstract
LEACHP is a modular package for calculating the one-dimensional vertical water and solute ¯ux
in horizontally layered soils under transient conditions. Data from ®eld studies conducted in a sandy
soil (Vredepeel, The Netherlands) and in a loamy soil (Weiherbach, Germany) were used by ®ve
groups to simulate water ¯ow and bromide and pesticide transport with the LEACHP model.
Calibrated outputs were compared to the actual ®eld values.
Soil hydraulic properties derived from laboratory measurements performed best to predict soil
moisture pro®les of ®eld soils. For small-scale lysimeters calibration was necessary to simulate
drainage ¯uxes that were within the wide range of experimental values. These calibrated parameters
failed to predict increased drainage volumes observed under additional irrigation. Measurement of
all soil water balance terms would allow a more thorough evaluation of the hydraulic component of
LEACHP.
Bromide pro®les were not well simulated on the sandy soil where considerable plant uptake was
observed. Additionally, zones of immobile soil water might have been present. Residue pro®les of
the volatile pesticide ethoprophos in soil were best simulated by groups that accounted for
*
Corresponding author. Present address: DuPont de Nemours (France) S.A., European Research and
Development Center, F-68740 Nambsheim, France.
E-mail address: martin.dust@fra.dupont.com (M. Dust).
0378-3774/00/$ ± see front matter # 2000 Elsevier Science B.V. All rights reserved.
PII: S 0 3 7 8 - 3 7 7 4 ( 9 9 ) 0 0 0 9 3 - 1
226
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
volatilisation in their simulations. Different descriptions of the soil sorption process for the mobile
pesticide bentazone between groups were dominated by different input of half-life values and
hydraulic properties. Although bromide residue pro®les were predicted reasonably well in the
loamy soil, it was not possible to predict isoproturon dissipation during summer with degradation
parameters calibrated in a winter simulation.
Predictions of soil water content pro®les and leaching volumes can be used with con®dence
especially after calibration given that preferential ¯ow processes are not predominant. Although
important input data for pesticide transformation and transport could be derived from extensive
laboratory scale experiments, these did not represent all processes that could affect pesticide fate
and behaviour under ®eld conditions. Calibration did not signi®cantly enhance the predictive
capability of the solute transport simulations. # 2000 Elsevier Science B.V. All rights reserved.
Keywords: Pesticide leaching modelling; Model validation; LEACHP; Risk assessment
1. Introduction
Simulation models are increasingly used to predict pesticide leaching (Cohen et al.,
1995). Deterministic±mechanistic models consist of representations of single processes
based on physical principles formulated as mathematical equations. Solution of these
equations requires a full specification of the boundary conditions of the system in space
and time and the initial conditions for each of the state variables. These models are
comprehensive; simulation results allow insight into the mechanisms and identify
sensitive parameters that govern water and solute fluxes in the dynamic soil±water±air
system. Therefore, simulation models currently present a useful tool to assess pesticide
fate and behaviour in soil (Russell, 1995).
Elaborate input parameters describing hydraulic and solute properties are often
lacking, which prevents proper use of research models like LEACHP (Walker et al.,
1995). In order to gain confidence in the model performance, repeated testing of
predictions against field data is necessary. However, accurate measurements of solute
concentration distributions are not often available (Pennell et al., 1990). As a result,
currently used models within the EU registration process have a vague validation status
(Boesten et al., 1995). It is thus unclear how accurately pesticide leaching models reflect
solute transport in field studies where a chemical is exposed to all of the dynamic
processes that determine its fate.
In this paper, the mechanistic±deterministic one-dimensional LEACHP model (Hutson
and Wagenet, 1992) was tested by several groups against data from field studies
conducted in the Netherlands at Vredepeel (Boesten and Van der Pas, 2000) and in
Weiherbach, Germany (Schierholz et al., 2000).
Within this exercise the modelling protocol described by Vanclooster et al. (2000) was
followed. In a first step the predictive capability of the LEACHP model was tested on two
data sets. This situation reflects the use of models in a regulatory context where
calibration is generally not done. In a second step the model was calibrated with regard to
hydrology, solute transport and pesticide related parameters and further tested on new
results. Evaluation of the model performance in terms of soil and solute water balance
227
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
terms and state variables was carried out to determine the degree of confidence in the
model calculations.
2. Materials and methods
2.1. Model description
LEACHM (Leaching Estimation And CHemistry Model) is a modular package for
calculating the one-dimensional water flux and solute movement in vertically layered
soils under transient conditions. The latest version is described in detail by Hutson and
Wagenet (1992). LEACHM has several component models, each of which describes a
different class of chemical. The water flow module is common to all components. In this
work we used LEACHP which simulates pesticide fate and transport.
Water flow is modelled with the one-dimensional Richards' equation. The y±h
relationship is described with a two-part function (Hutson and Cass, 1987),
h
a 1 ÿ Y=Ys 0:5 Yc =Ys ÿb
1 ÿ Yc =Ys 0:5
h a Y=Ys ÿb ;
;
0 > h > hc
(1a)
hc > h > ÿx
(1b)
3
ÿ3
where h is the pressure potential, ys the saturated water content (m m ) and a, b are
constants. hc,yc de®nes the point of intersection of the two curves hc a[2b/(1 2b)]ÿb
and yc 2bys/(1 2b). For the hydraulic conductivity the following equation is available:
K Y Ks Y=Ys 2b2p
(2)
where K(y) is the hydraulic conductivity (mm per day), Ks is the hydraulic conductivity at
saturation ys and p is a pore interaction parameter. Alternatively, for the K±y±h
relationship the following equations are available (Mualem, 1976; Van Genuchten, 1980):
Y h Yr
Ys ÿ Yr
m
1 ajhjn
(3)
where y is the volumetric water content (m3 mÿ3), h the pressure head (mm), yr the
residual water content (m3 mÿ3), and a (mmÿ1), n (±), and m (±) are empirical
parameters.
m 2
(4)
K Se Ks Sle 1 ÿ 1 ÿ Se1=m
where Se is the effective saturation (y ÿ yr/ys ÿ yr), l the pore connectivity parameter (±),
and m the empirical parameter from Eq. (3).
The water flow equation is combined with the convection±dispersion equation in
LEACHP. Solute sorption to soil can either be described with a linear Eqs. (5) and (6) or
non-linear Eq. (7) isotherm or by two site sorption Eq. (8). For a linear isotherm
Cs Kd Cl
(5)
228
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
where Kd is the linear distribution coef®cient (dm3 kgÿ1). Kd can vary with depth. For
pesticides, Kd values are calculated from the organic carbon partition coef®cient Koc and
the organic carbon fraction (foc) as
Kd Koc foc
(6)
Non-linear sorption is described with the Freundlich isotherm
Cs kf C nf
(7)
where kf and nf are constants. Non-equilibrium linear sorption assumes that a fraction of
sites (f) display local chemical equilibrium and a fraction (1 ÿ f) is subject to kinetically
controlled sorption and desorption. The sorbed concentration is the sum of sorption to the
kinetic (s1) and equilibrium (s2) sites. Flux density of solute Ja (mg kgÿ1) between the
kinetic sites and solution phase C (mg dmÿ3) is assumed to depend upon the current
degree of non-equilibrium
Ja arb 1 ÿ f kd C ÿ s2
(8)
ÿ3
where a is a phase transfer rate coef®cient and rb the soil bulk density (kg dm ).
The liquid±vapour partition is represented by a modified Henry's law as proposed by
Jury et al. (1983). Degradation of pesticides is assumed to follow first-order kinetics. The
rate constant may be adjusted for temperature and/or water effects. The temperature
correction factor (Tcf) at a temperature t (8C) is calculated as
0:1 tÿtbase
Tcf Q10
(9)
where Q10 is a constant and tbase is the base temperature for which the rate constants are
speci®ed in the data ®le. The water correction factor (Wcf) is set to one in the optimum
water content range, which is between ymax and ymin. If y is higher than the optimum, Wcf
becomes
Wcf Wcfsat
1 ÿ Wcfsat Ys ÿ Y
Ys ÿ Ymax
(10)
where Wcfsat is the relative rate constant at saturation, ys the saturated water content. If the
soil moisture is lower than the optimum water content range the correction factor is
Wcf
max Y; YWP ÿ YWP
Ymin ÿ YWP
(11)
so that the correction factor is zero at wilting point YWP. Furthermore, uptake of
pesticides in the transpiration stream can be included if desired.
In addition to graphical display of the results, statistical criteria, as reported by
Vanclooster et al., (2000) were applied to compare the results from different
groups. Apart from the Modelling Efficiency (EF) the Scaled Root-Mean-Square-Error
(SRMSE)
n
1 1X
Pi ÿ Oi 2
SRMSE
O n i1
(12)
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
229
was calculated where n is the number of observations, Oi are the observed values, Pi the
the average of the observed data. The SRMSE normalises the
predicted values and O
overall sum of squares to the number of observations and the observed mean. EF values
below zero indicate a model performance which is poorer than simply using the average
value of the observations. A perfect match between observed and predicted data is
indicated by values of zero for the SRMSE and 1 for the EF, respectively. Both criteria are
dimensionless. In order to match the horizons for pesticide residue sampling, simulated
results were integrated over the respective layer depth for statistical analysis.
2.2. Input parameters
2.2.1. Vredepeel
Four groups worked with the Vredepeel data set (groups A, B, C and D). Parameters
were calibrated after the first simulation exercise if considered justified and/or necessary.
This paper will only report these calibrated runs.
All participants used climate data, including potential evapotranspiration rates,
provided with the data set for the simulation period from 23 November 1990 until 10
March 1992. Apart from sowing dates, crop development dates were estimated by the
modellers. The description of the water retention characteristics and discretisation of the
soil profiles are given in Table 1. Groups A, B and C used soil texture information that
was provided with the Vredepeel report for input to pedo-transfer functions that are part
of the LEACHP model and performed no calibration. Group D fitted Eqs. (1a) and (1b) to
y±h values measured with the evaporation method (Table 1). For the initial soil moisture
profile, all groups used reported data. Due to difficulties in simulating the groundwater
level as a function of time either free drainage or measured groundwater levels were
chosen as a lower boundary condition.
The major differences in assumptions made by each group for calculating the solute
fate and transport are presented in Table 2. Linear equilibrium sorption was assumed by
group A for bentazone and for both pesticides by group B. For ethoprophos group A
considered linear non-equilibrium sorption. Each group independently derived Koc values
from raw data of laboratory sorption experiments conducted at 5 and 158C (Table 3).
Parameters for non-linear equilibrium sorption were also derived from sorption
experiments that were provided with the Vredepeel report (groups C and D). Sorption
parameters were calibrated either according to soil residue extraction results (group A,
ethoprophos) or expert judgement (group D, ethoprophos) (Table 3).
Half-life values for the pesticides were derived from laboratory degradation
experiments (Table 4). Differences in resulting input parameters for the calibrated
runs were either due to a different choice of laboratory studies for the fitting procedure or
to interpolation of data from different soil layers. Group A initially used a uniform halflife value for the 0±120 cm soil layer from laboratory degradation studies conducted at
58C with ethoprophos and bentazone, respectively. In the calibrated runs, additional
data were used that were derived from laboratory experiments with subsurface soil of the
100 and 200 cm soil layer at 108C for both pesticides (Table 4). Group B used laboratory
degradation data from the 0±25 cm soil layer at 158C for ethoprophos and bentazone,
assuming a decline of degradation with depth. No calibration of pesticide half-life
230
Parameter
Group A
Group B
Group C
Group D
Soil pro®le depth (cm)
Depth of layers (cm)
Retentivity model
Parameter estimation
120
5
Eqs. (1a) and (1b)
ptf by Thomasson and
Carter, 1992
No
y, from report
Free drainage
112
4
Eqs. (1a) and (1b)
ptf by Thomasson and
Carter, 1992
No
y, from report
Free drainage
200
10
Eqs. (1a) and (1b)
ptf by Rawls and Brakensiek,
1982
No
y, from report
Measured ground water level
195
7.5
Eqs. (1a) and (1b)
®tting of measured y±h
Calibration
Initial pro®le
Lower boundary condition
Yes
y, from report
Measured ground water level
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
Table 1
Discretisation of the soil pro®le and hydraulic parameters for the Vredepeel simulations
231
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
Table 2
Model assumptions for solute fate and transport for the Vredepeel study for the calibrated runs
Parameter
Group A
Group B
Group C
Group D
Sorption
Ethoprophos
Linear non-equilibrium
Linear
equilibrium
Linear
equilibrium
Non-linear
equilibrium
Non-linear
equilibrium
Non-linear
equilibrium
Non-linear
equilibrium
No
No
No
First-order, f(T,y)
None
No
No
No
First-order, f(T,y)
None
No
No
No
First-order
Yes
Bentazone
Linear equilibrium
Plant uptake
Bromide
Ethoprophos
Bentazone
Degradation
Volatilisation
No
Yes
Yes
First-order, f(T,y)
Yes
values was carried out. Group C and D also used the information of ethoprophos
and bentazone degradation in the 0±25 cm soil layer at 158C. For the subsoil group
C assumed decreased half-lives in proportion to the decreasing organic carbon contents
of the soil. Group D simulated ethoprophos degradation in the 60±195 cm soil layer
by using data from laboratory degradation studies conducted at 108C with soil from
the 100±200 cm soil layer. Bentazone subsoil degradation data of group D were derived
from laboratory degradation experiments. For the 30±105 cm soil layer they used
laboratory degradation data from the 50±100 cm soil layer at 108C, whereas for the 105±
195 cm soil layer the experiments with soil from the 100±200 cm soil layer were used.
Calibration of the half-life value of bentazone in the 30±105 cm soil layer was performed
(Table 4).
Groups A, B and C accounted for the effect of soil moisture contents on
pesticide degradation with estimated parameters. Group A calibrated Wcfsat. Group D
ran LEACHP with the degradation rate kept constant at different soil moisture and/
or temperature conditions. Group A found it necessary to calibrate tbase and/or the
originally chosen Q10-value for the temperature correction of the degradation rate
constant (Table 4). Parameters for volatilisation of ethoprophos were calibrated as
indicated in Table 4.
Table 3
Values of the ethoprophos and bentazone sorption in the Vredepeel study (calibrated values in brackets)
Group A
Koc
Ethoprophos
Bentazone
a
a
f
a
158.3
4.8a
b
(0.85)
b
(0.002)
Group B
Group C
Koc
Kfoc
a
125.0
5.6a
n
a
152.0
3.7a
Mean from all laboratory sorption experiments at 5 and 158C.
Estimated from soil residue extraction.
c
Estimated value.
b
Group D
Kfoc
a
0.9
1.0a
n
a
c
135.0 (200)
5.0a
0.85a
0.9a
232
Table 4
Parameters for pesticide degradation, soil moisture and temperature correction of the degradation rate constant and parameters for volatilisation: Vredepeel study,
ethoprophos and bentazone (calibrated values in brackets)
Ethoprophos
Bentazone
Q-10 value
tbase[8C]
ymax
ymin
Wcfsat
Group A
Group B
Group C
Group D
cm
DT50
cm
DT50
cm
DT50
cm
DT50
0±120
(0±25)
(25±100)
(100±120)
0±120
(0±25)
(25±100)
(100±120)
3.0 (3.85)
20 (5)
0.08
ÿ300
0.6 (0.87)
347
(347)
(630)
(433)
204
(204)
(815)
(96)
0±25
25±100
100±120
132
198
264
0±30
30±60
154
301
0±60
60±195
107
277
0±25
25±100
100±120
37
56
75
0±30
30±60
50
100
0±30
30±105
50
693
(139)
87
2.2
15a/20b
0.08
ÿ300
1.0
2.0
10
0.08
ÿ300
0.6
105±195
±
Saturated vapour density [mg dmÿ3]
Ethoprophos
0.0045 (0.0009)
Bentazone
0.00004
1.6 E-5 (1.4 E-3)
1.6 E-5
Water solubility [mg dmÿ3]
Ethoprophos
Bentazone
750.0 (700.0)
500.0
a
b
For ethoprophos.
For bentazone.
750.0
500.0
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
Parameters
233
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
Table 5
Hydraulic parameters for the Weiherbach simulations
Parameters
Field trial
Lysimeters
Soil pro®le depth (cm)
Depth of layers (cm)
Retentivity model parametrisation
Conductivity model parametrisation
Initial pro®le
Lower boundary condition
95
5
Eq. (3) from report
Eq. (4) from report
Preliminary simulations
Fixed water table at 13.5 m
45
5
Eq. (3) from report
Eq. (4) from report
Preliminary simulations
Lysimeter condition
2.2.2. Weiherbach
Only one group used the Weiherbach data set. Results from the 1993/1994 field trial
and lysimeter study were used for calibration of parameters. The simulation period was
from 6 December 1993 to 26 April 1994. The calibrated parameters were then
independently tested against the 1995 studies in simulations starting from 11 May to 23
June. In this paper only the performance of the calibrated parameters for the 1993/1994
and 1995 studies will be presented. In 1995 additional irrigation of 260 mm was applied
between 22 May and 19 June on the field plot. Four lysimeters were divided into two
groups that received 140 mm (irrigated I) and 280 mm (irrigated II), respectively, in this
period. In all simulations climate data was used from the report, including potential
evapotranspiration rates. Crop development dates were estimated for winter wheat (1993/
1994) and summer barley (1995).
For the simulations, the soil profile was divided into 5 cm segments. Soil profile depths
and bottom boundary conditions are given in Table 5. Soil hydraulic parameters for Eqs.
(3) and (4) as reported by Schierholz et al. (2000) were used. Calibration of soil hydraulic
properties were conducted for lysimeters, but not for the field experiment. Daily potential
evapotranspiration rates were multiplied by the factor 1.25 to account for increased
evapotranspiration. Additionally, a reduced Ksat in the lowest layer of the lysimeter due to
its boundary construction was assumed (36 mm per day instead of 72 mm per day).
Plant uptake and volatilisation were not considered for bromide or isoproturon. For the
pesticide a linear equilibrium sorption isotherm was assumed. Kd-values determined in
batch-experiments with soil from different layers and provided with the report were used
(Table 6). No calibration was performed on the sorption parameters. Half-life values for
Table 6
Solute input parameters for the Weiherbach data set
[m]
DT50 [days]
Original values
0.0±0.3
14.7a
0.3±2.0
138.6b
Calibrated values
0.0±0.3
7.4
0.3±2.0
69.3
a
b
ymax
ymin
Wcfsat
Q10
tbase [8C]
kd [l kgÿ1]
0.28a
0.28a
ÿ202a
ÿ202a
0.0a
0.0a
2.0
2.0
25.0
25.0
2.00
1.69
0.20
0.20
ÿ500
ÿ500
0.6
0.6
2.0
2.0
25.0
25.0
2.00
1.69
Derived from laboratory studies of top soil layer at 258C and 20, 40 and 60 % water holding capacity.
Derived from laboratory studies of 100±200 cm soil layer at 208C.
234
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
the pesticides and parameters for the soil moisture correction were derived from
laboratory degradation experiments from the two soil layers at different soil moisture
contents (Table 6). Isoproturon profiles of the 1993/1994 field experiments were
successfully simulated only after calibration of the half-life value and the soil moisture
correction parameters (Table 6).
3. Results and discussion
3.1. Vredepeel
Soil moisture profiles were simulated best using parameters for the water retention
characteristic derived from y±h data from laboratory experiments (group D, Fig. 1). In
these simulations the lowest values of SRMSE and positive values of the EF were
observed (Table 7). Further calibration of hydraulic parameters would be indispensable to
more accurately predict soil moisture conditions. The use of different pedo-transfer
functions resulted in different soil moisture profiles (groups A, B against C, Fig. 1).
Different estimation of soil water uptake by plants might have led to differences in
simulated soil moisture profiles between groups A and B, which used identical pedotransfer functions and bottom boundary conditions (Fig. 1).
Bromide transport was rather poorly predicted by all LEACHP-simulations, as
indicated by the high values for the SRMSE and the low or negative numbers of the EF
(Table 7). The somewhat better statistical values of bromide for group D than for groups
A, B and C are probably a direct consequence of the better simulation of soil moisture,
achieved with the assumptions of group D. The field observation of bromide remaining in
Fig. 1. Soil moisture pro®les on day 103, 278 and 474 at the Vredepeel site: experimental results and LEACHPsimulations of four groups.
235
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
Table 7
Ranges of the statistical criteria for LEACHP model performance on soil moisture, bromide and pesticide
pro®les for the Vredepeel data set after calibration
Group
SRMSE
Volumetric water contents day 103, 278 and 474
A
0.15
B
0.16
C
0.28
D
0.16
Bromide pro®le day 103, 278 and 474
A
0.95
B
0.77
C
0.60
D
0.42
Bentazone pro®le day 103 and 278
A
0.81
B
2.34
C
0.50
D
0.39
Ethoprophos pro®le day 103, 278 and 474
A
0.78
B
1.36
C
0.78
D
0.99
Total ethoprophos
A
0.38
B
1.46
C
1.08
D
0.98
EF
to
to
to
to
0.39
0.93
0.54
0.34
ÿ0.1
ÿ4.1
ÿ5.5
ÿ0.3
to
to
to
to
1.13
1.77
0.96
0.94
ÿ11.6 to ÿ1.9
ÿ33.2 to ÿ0.8
ÿ1.8 to ÿ1.1
ÿ0.4 to 0.5
to 1.12
to 0.81
to 0.49
ÿ0.5 to ÿ7.0
ÿ45.3 to ÿ1.1
ÿ0.3 to 0.3
ÿ2.3 to ÿ0.5
to
to
to
to
ÿ5.7 to 0.7
ÿ159.8 to 0.1
ÿ114.8 to 0.7
ÿ0.9 to 0.6
3.14
14.98
11.64
7.58
to
to
to
to
0.7
ÿ0.1
0.1
0.9
0.6
ÿ4.9
ÿ3.8
0.7
the top soil layer was not predicted by any of the simulations, suggesting the occurrence
of immobile soil water zones after application (Fig. 2). Plant uptake of bromide was not
accounted for in any of the runs, but was observed in considerable amounts in the winter
wheat plants (Boesten and Van der Pas, 2000). Additionally, turnover of plant litter may
have released amounts of bromide during the study, leading to a steady supply of solute at
the surface.
Calculated bentazone profiles had a larger variance between groups compared to the
measurement/sampling variability observed in the Vredepeel soil (Fig. 3). According to
the statistical criteria, the bentazone profiles were not accurately predicted even after
calibration of sorption and degradation parameters (Table 7). Parameters derived from
laboratory studies under controlled conditions did not reflect pesticide behaviour in a
dynamic system like the field soil. Differences between predicted bentazone profiles were
observed between the four groups despite similar half-life values and sorption parameters
(Tables 3 and 4). Apart from differences in predicted water fluxes, diverse values for the
temperature correction (Table 4) of the degradation process might be an explanation for
this variability.
Total ethoprophos residues were best predicted by group A and D during the 474 days
of the field study (Fig. 4, Table 7). Both groups accounted for volatilisation of the
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M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
Fig. 2. Bromide pro®les on day 103, 278 and 474 at the Vredepeel site: experimental results and LEACHPsimulations of four groups.
pesticide in the LEACHP-simulations, although some calibration of parameters was
necessary (Table 4). Predictions of the ethoprophos profiles were more accurate
compared to the bentazone simulations (Fig. 5). Calibration of either two site sorption
parameters (group A) or the Kfoc-value (group D) resulted in better predictions compared
to those without calibration. Leaching of ethoprophos was overestimated by groups A, B
and C, penetration of ethoprophos was best simulated by group D, using a calibrated Kfoc
value (Fig. 5). Ethoprophos residues in the soil profile 474 days after application were
Fig. 3. Bentazone pro®les on day 103, 278 and 474 at the Vredepeel site: experimental results and LEACHPsimulations of four groups.
M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
237
Fig. 4. Total ethoprophos residues in the soil pro®le at the Vredepeel site: experimental results and LEACHPsimulations of four groups.
overestimated by all groups, illustrating the problems of transferring results from
laboratory experiments to the field scale under outdoor conditions.
3.2. Weiherbach ®eld plot
Soil water profiles were reasonably well simulated for the 1993/1994 period
(December±April) without fitting of the hydraulic parameters (Fig. 6). At the end of
Fig. 5. Ethoprophos pro®les on day 103, 278 and 474 at the Vredepeel site: experimental results and LEACHPsimulations of four groups.
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M. Dust et al. / Agricultural Water Management 44 (2000) 225±245
Fig. 6. Soil water contents, pro®les of bromide and isoproturon at the Weiherbach ®eld plot, 1993/1994; experimental results and simulations with the LEACHP model:
calibration.
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Table 8
Ranges of statistical criteria for LEACHP model performance on soil moisture, bromide and isoproturon pro®les
for the Weiherbach ®eld plot
Volumetric water contents
Bromide pro®le
Isoproturon profile
Calibration 1993/1994
day 10, 17, 56 and 141
Evaluation 1995 day 10,
17, 56 and 141
SRMSE
EF
SRMSE
EF
0.09 to 0.22
0.58 to 1.11
1.22 to 3.31
ÿ3.3 to 0.01
ÿ0.4 to 0.7
ÿ0.4 to 0.3
0.30 to 0.55
0.57 to 7.57
1.35 to > 100.0
ÿ25.9 to ÿ2.6
ÿ343.5 to 0.3