Simulation of water and solute transport in ®eld
soils with the LEACHP model
M. Dust
a,*, N. Baran
b, G. Errera
c, J.L. Hutson
d, C. Mouvet
e,
H. SchaÈfer
f, H. Vereecken
g, A. Walker
haInstitut fuÈr Chemie und Dynamik der GeosphaÈre: ICG-5, Radioagronomie,
Forschungszentrum JuÈlich GmbH, D-52425, Germany
bChambre d'Agriculture de L'Aisne, 38 Boulevard de Lyon, 02007 Laon Cedex, France cIstituto Chimica Agraria ed Ambientale, Universita Cattolica del Sacro Cuore,
Via Emilia Parmense 84, I-29100 Piacenza, Italy
dSchool of Earth Sciences, Faculty of Science and Technology, Flinders University of South Australia,
GPO Box 2100, Adelaide, SA 5001, Australia
eBRGM, Avenue de Concyr B.P. 6009, F-45060 OrleÂans cedex 2, France fBayer AG, Landwirtschaftszentrum Monheim, D-51368 Leverkusen/Bayerwerk, Germany gInstitut fuÈr Chemie und Dynamik der GeosphaÈre: ICG-4, ErdoÈlchemie und organische Geochemie,
Forschungszentrum JuÈlich GmbH, D-52425, Germany
hHorticulture 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).
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).
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),
ha 1ÿY=Ys
andyc2bys/(12b). For the hydraulic conductivity the following equation is available:
K Y Ks Y=Ys2b2p (2)
whereK(y) is the hydraulic conductivity (mm per day),Ksis 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 YsÿYr
andmthe 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
CsKdCl (5)
whereKdis the linear distribution coef®cient (dm3kgÿ1).Kdcan vary with depth. For
pesticides,Kdvalues are calculated from the organic carbon partition coef®cientKocand
the organic carbon fraction (foc) as
KdKocfoc (6)
Non-linear sorption is described with the Freundlich isotherm
Cskf Cnf (7)
wherekfandnfare constants. Non-equilibrium linear sorption assumes that a fraction of
sites (f) display local chemical equilibrium and a fraction (1ÿf) 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 soluteJa(mg kgÿ1) between the
kinetic sites and solution phase C (mg dmÿ3) is assumed to depend upon the current degree of non-equilibrium
Jaarb 1ÿfkdCÿs2 (8)
wherea is a phase transfer rate coef®cient andrbthe soil bulk density (kg dmÿ3).
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 temperaturet(8C) is calculated as
TcfQ0:1 tÿtbase
10 (9)
whereQ10is a constant andtbaseis 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 betweenymaxandymin. Ifyis higher than the optimum,Wcf
becomes
Wcf Wcfsat 1ÿWcfsat YsÿY
YsÿYmax (10)
whereWcfsatis the relative rate constant at saturation,ysthe saturated water content. If the
soil moisture is lower than the optimum water content range the correction factor is
Wcf
max Y;YWP ÿYWP
YminÿYWP (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.
was calculated wherenis the number of observations,Oiare the observed values,Pithe
predicted values andO the average of the observed data. The SRMSE normalises the 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±hvalues 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 derivedKocvalues
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 half-life 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
Table 1
Discretisation of the soil pro®le and hydraulic parameters for the Vredepeel simulations
Parameter Group A Group B Group C Group D
Soil pro®le depth (cm) 120 112 200 195
Depth of layers (cm) 5 4 10 7.5
Retentivity model Eqs. (1a) and (1b) Eqs. (1a) and (1b) Eqs. (1a) and (1b) Eqs. (1a) and (1b)
Parameter estimation ptf by Thomasson and
Carter, 1992
ptf by Thomasson and Carter, 1992
ptf by Rawls and Brakensiek, 1982
®tting of measuredy±h
Calibration No No No Yes
Initial pro®le y, from report y, from report y, from report y, from report
Lower boundary condition Free drainage Free drainage Measured ground water level Measured ground water level
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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 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
Degradation First-order,f(T,y) First-order,f(T,y) First-order,f(T,y) First-order
Volatilisation Yes None None Yes
Table 3
Values of the ethoprophos and bentazone sorption in the Vredepeel study (calibrated values in brackets)
Group A Group B Group C Group D
Koc f a Koc Kfoc n Kfoc n
Ethoprophos 158.3a (0.85)b (0.002)b 125.0a 152.0a 0.9a 135.0a(200)c 0.85a
Bentazone 4.8a 5.6a 3.7a 1.0a 5.0a 0.9a
aMean from all laboratory sorption experiments at 5 and 158C. bEstimated from soil residue extraction.
cEstimated value.
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)
Parameters Group A Group B Group C Group D
cm DT50 cm DT50 cm DT50 cm DT50
Ethoprophos 0±120 347 0±25 132 0±30 154 0±60 107
(0±25) (347) 25±100 198 30±60 301 60±195 277
(25±100) (630) 100±120 264
(100±120) (433)
Bentazone 0±120 204 0±25 37 0±30 50 0±30 50
(0±25) (204) 25±100 56 30±60 100 30±105 693
(25±100) (815) 100±120 75 (139)
Saturated vapour density [mg dmÿ3]
Ethoprophos 0.0045 (0.0009) 1.6 E-5 (1.4 E-3)
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 reducedKsatin 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 5
Hydraulic parameters for the Weiherbach simulations
Parameters Field trial Lysimeters
Soil pro®le depth (cm) 95 45
Depth of layers (cm) 5 5
Retentivity model parametrisation Eq. (3) from report Eq. (3) from report
Conductivity model parametrisation Eq. (4) from report Eq. (4) from report
Initial pro®le Preliminary simulations Preliminary simulations
Lower boundary condition Fixed water table at 13.5 m Lysimeter condition
Table 6
Solute input parameters for the Weiherbach data set
[m] DT50[days] ymax ymin Wcfsat Q10 tbase[8C] kd[l kgÿ1]
aDerived from laboratory studies of top soil layer at 258C and 20, 40 and 60 % water holding capacity. bDerived from laboratory studies of 100±200 cm soil layer at 208C.
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 fromy±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 pedo-transfer 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
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
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 EF
Volumetric water contents day 103, 278 and 474
A 0.15 to 0.39 ÿ0.1 to 0.7
B 0.16 to 0.93 ÿ4.1 toÿ0.1
C 0.28 to 0.54 ÿ5.5 to 0.1
D 0.16 to 0.34 ÿ0.3 to 0.9
Bromide pro®le day 103, 278 and 474
A 0.95 to 1.13 ÿ11.6 toÿ1.9
B 0.77 to 1.77 ÿ33.2 toÿ0.8
C 0.60 to 0.96 ÿ1.8 toÿ1.1
D 0.42 to 0.94 ÿ0.4 to 0.5
Bentazone pro®le day 103 and 278
A 0.81 to 1.12 ÿ0.5 toÿ7.0
B 2.34 ÿ45.3 toÿ1.1
C 0.50 to 0.81 ÿ0.3 to 0.3
D 0.39 to 0.49 ÿ2.3 toÿ0.5
Ethoprophos pro®le day 103, 278 and 474
A 0.78 to 3.14 ÿ5.7 to 0.7
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 theKfoc-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 calibratedKfoc
value (Fig. 5). Ethoprophos residues in the soil profile 474 days after application were
Fig. 2. Bromide pro®les on day 103, 278 and 474 at the Vredepeel site: experimental results and LEACHP-simulations 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. 4. Total ethoprophos residues in the soil pro®le at the Vredepeel site: experimental results and LEACHP-simulations of four groups.
Fig. 5. Ethoprophos pro®les on day 103, 278 and 474 at the Vredepeel site: experimental results and LEACHP-simulations of four groups.
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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April, when the winter wheat started to shoot, a slight over prediction of soil moisture was observed. The soil water profiles of the evaluation period from May to June 1995 were not accurately predicted (Fig. 7, Table 8: negative EF). In the top soil layer (0±30 cm) soil moisture was constantly over predicted by the model. Soil cultivation could have changed the hydraulic properties of the soil. Crop canopy interception of water was not considered in the model, but could have reduced actual water input in the soil profile. Underestimation of the potential evapotranspiration rate would have caused the same effect. Additionally, the modelled soil water extraction by plants could have been inadequate for the 1995 period of growing barley, as indicated by the late April results from 1993/1994.
Total amounts of bromide were accurately predicted without fitting of solute transport parameters for the 1993/1994 field study. However, bromide residues in the top soil layer were over predicted (Fig. 6). Consideration of bromide uptake by the winter wheat crop might lead to more accurate predictions. Bromide profiles of 1995 were accurately simulated until the end of May (Fig. 7). The loss of bromide in the soil profile during June was not predicted by the LEACHP model (Table 8: negative EF). As in 1993/1994 bromide uptake by plants could have been considerable in conjunction with high transpiration rates. Values for Ks (Eq. (4)) were derived from inverse modelling from
outflow data of 0.1 dm3soil cores. Schierholz et al. (2000) mentioned that field scaleKs
values might be larger due to macropores. In this way, the LEACHP model might have underestimated field scale fluxes of water and solute, especially considering the intense irrigation regime of 240 mm of water within four weeks.
Accurate total amounts of isoproturon soil residues could not be simulated without calibration of the half-life value and soil moisture correction parameters (Table 6). Despite calibration the LEACHP model overestimated the penetration depths of isoproturon and residues in the top soil 1993/1994 (Fig. 6). The low accuracy of the predicted pesticide residue profiles are also reflected in high values for the SRMSE and negative EF-values (Table 8). Applying a non-linear sorption isotherm would possibly improve the residue profile simulation. Observed dissipation of isoproturon in 1995 was more intense than predicted with the calibrated degradation parameters (Fig. 7). The additional irrigation that started at the end of May 1995 favoured downward movement of the pesticide. In contrast to 1993/1994 the observed isoproturon front was deeper than predicted at all times. Downward fluxes of water were more intense than simulated by the model as also indicated by the 1995 bromide results. Isoproturon and bromide profiles
Table 8
Ranges of statistical criteria for LEACHP model performance on soil moisture, bromide and isoproturon pro®les for the Weiherbach ®eld plot
Fig. 7. Soil water contents, pro®les of bromide and isoproturon at the Weiherbach ®eld plot, 1995; experimental results and simulations with the LEACHP model: evaluation.
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were not similar at all sampling dates. For instance, on 26 May a relatively high portion of the pesticide had been found in the 45±55 cm soil layer whereas little bromide was determined at that depth (Fig. 7). These differences might be due either to spatial variability of soil hydraulic properties or to two-dimensional flow patterns of solutes in the field soil as reported by Flury (1996) for a variety of soils. It is probable that representative sampling was not obtained under the conditions of 1995. Compared to the winter season in 1993/1994 enhanced degradation of isoproturon was observed in spring 1995. Soil moisture conditions were similar, but in May/June higher temperatures and intense drying wetting cycles imposed by the irrigation regime probably promoted degradation of isoproturon. Calibrated parameter values that describe complex processes like pesticide degradation only seem valid for specific conditions.
3.3. Weiherbach lysimeters
Drainage volumes of lysimeters showed considerable variation between replicates in 1993/1994. After calibration the prediction was within the upper experimental range (Fig. 8). Observed bromide leaching also displayed a broad range, the LEACHP-simulation being close to the lowest values. Isoproturon loads in drainage displayed the largest differences between lysimeters. Physical non-equilibrium flow processes like `preferential flow' might have occurred, since few leaching events carried large loads of isoproturon. There was no clear correlation between solute loads and drainage volumes (Fig. 8). The LEACHP predictions of isoproturon loads were within the variation observed between four replicates.
Additional irrigation led to intense drainage in 1995 (Fig. 9). Duplicate lysimeters showed similar behaviour under both irrigation regimes in this period. FuÈhr and Hance
Fig. 8. Drainage volumes, bromide and isoproturon loads in leachates from lysimeters at the Weiherbach site, 1993/1994; experimental results and simulations with the LEACHP model: calibration.
(1992) observed that keeping lysimeters idle for one growing season after filling before starting an experiment significantly decreased differences in drainage volumes. For both lysimeter groups predicted drainage volumes exceeded observed drainage starting on day 20. Bromide loads were over predicted after day 25. No correlation was found between observed drainage volumes and bromide loads in 1995, like in 1993/1994. Additionally, bromide and isoproturon loads were contrary in both lysimeter groups (Fig. 9). Total isoproturon loads were well predicted for irrigation regime I, but the early breakthrough of the pesticide was not calculated (Fig. 9). Although predicted total pesticide loads were within the considerable experimental range for lysimeters under irrigation regime II, pesticide breakthrough was observed around 10 days earlier in the experiment (Fig. 9). The one-dimensional convection±dispersion equation therefore does not appear suitable for describing the preferential solute transport occurring in these small-scale lysimeters.
4. Conclusions
Hydraulic parameters derived from multi-step outflow experiments by an inverse modelling technique described soil moisture profile of the loamy soil (Weiherbach) well without further fitting. On the sandy soil (Vredepeel) hydraulic functions fitted to measuredy±h relationships gave better results than the use of pedo-transfer functions. Whenever direct measurements of hydraulic properties are available they should be preferred to pedo-transfer functions. However, soil cultivation affects soil porosity and
thus its hydraulic properties, leading to a temporal variability of these properties that should be considered in future studies. Considering the predictions of soil moisture profiles and drainage volumes it can be concluded that the water flow module of LEACHP can be used with confidence. This is especially true if hydraulic properties were measured in the laboratory and preferential flow is not predominating. Calibration further increased reliability of predictions.
The LEACHP model requires potential evapotranspiration rates as input for description of the upper boundary condition. Accurate estimations are inevitable to accurately simulate the soil water balance. The simulation of soil water extraction by plants predicted by LEACHP does not necessarily reflect all the processes that occur in a field soil. Direct measurements of all terms of the soil water balance together with detailed crop growth observations would allow a more thorough evaluation of the soil hydraulic component of the LEACHP model.
Lysimeters of the Weiherbach site were sub samples from the field plot. Measured drainage fluxes displayed a huge variation in the first year. The extent to which physical non-equilibrium transport processes that were observed on the lysimeter scale also occurred on the field scale is unclear. With the one-dimensional mechanistic± deterministic LEACHP model, solute transport in these lysimeters could not be precisely predicted. Field scale water flux and solute transport can probably be better estimated with a large number of replicates of such small-scale lysimeters.
The static laboratory experiments under controlled conditions did not reflect all the processes affecting pesticide transformation in a dynamic system like a field soil thus emphasising the findings of BergstroÈm and Jarvis (1994). The amounts of soil residues could not be simulated accurately for either ethoprophos, bentazone or isoproturon without calibration of degradation parameters. For the Vredepeel study, the pesticide half-life values derived from laboratory batch experiments differed between modelling groups, depending on the data subset chosen for analysis. The resulting predictions of pesticide profiles covered a broader range than the sampling and/or measurement error. First-order kinetics with soil moisture and temperature correction did not allow accurate predictions of bentazone soil residue profiles. Accounting for volatilisation of ethoprophos increased the accuracy of the LEACHP model predictions. Calibration of isoproturon degradation rates at the Weiherbach site 1993/1994 was only valid for the specific winter season conditions. For the period of May/June 1995 additional calibration would be necessary. Different approaches to model pesticide sorption in the Vredepeel simulations were overshadowed by differences in parametrisation of pesticide degradation and water flow predictions. Calibration of sorption parameters increased the accuracy of model predictions for the sandy soil where zones of immobile soil water effectively retarded solute transport.
Despite the quality of the data sets provided for the estimation of input parameters of the soil hydraulic functions and pesticide sorption and degradation behaviour the quality of uncalibrated predictions with the LEACHP model remained poor for both sites. The gap in scale between laboratory experiments and field conditions could only be decreased with repeated calibrations. Calibration is an subjective process, largely affected by the modeller. Therefore, clear documentation and justification of input parameters is necessary for interpretation of the model calculations. When using LEACHP in a
regulatory context this fact should be kept in mind. Field scale variability, which limits the usefulness of the deterministic modelling approach, was not addressed in neither of the field studies. However, the modelling exercises proved to be useful to identify dominant processes that affect water flow and pesticide transport in field soils. Calibration of input parameters helps to critically evaluate results from laboratory experiments.
Acknowledgements
This project was carried out within the framework of the mathematical modelling working group of COST Action 66 `Pesticide fate in the soil environment' organised by DGXII of the EU.
References
BergstroÈm, L.F., Jarvis, N.J., 1994. Evaluation and comparison of pesticide leaching models for registration purposes. J. Environ. Sci. Health A 29(6), 1061±1072.
Boesten, J.J.T.I., Businelli, M., Delmas, A., Edwards, V., Helweg, A., Jones, R., Klein, M., Kloskowski, R., Layton, R., Marcher, S., SchaÈfer, H., Smeets, L., Styczen, M., Travis, K., Walker, A., Yon, D., 1995. Leaching models and EU registration. The ®nal report of the work of the Regulatory Modelling Work Group of FOCUS, Forum for the Coordination of Pesticide Fate Models and their Use, 123 pp.
Boesten, J.T.T.I., Van der Pas, L.J.T., 2000. Movement of water, bromide and the pesticides ethoprophos and bentazone measured in a sandy soil: description of the Vredepeel data set. Agric. Water Mgmt., this issue. Cohen, S.Z., Wauchope, R.D., Klein, A.W., Eadsforth, C.V., Graney, R., 1995. Offsite transport of pesticides in
water: mathematical models of pesticide leaching and runoff. Pure Appl. Chem. 67(12), 2109±2148. Flury, M., 1996. Experimental evidence of transport of pesticides through ®eld soils Ð a review. J. Environ.
Qual. 25, 25±45.
FuÈhr, F., Hance, R.J., 1992. Lysimeter studies of the fate of pesticides in the soil. BCPC Monograph 53, British Crop Protection Council, Farnham, UK, 192 pp.
Hutson, J.L., Cass, A., 1987. A retentivity function for use in soil-water simulation models. J. Soil Sci. 38, 105± 113.
Hutson, J.L., Wagenet, R.J., 1992. LEACHM, Leaching Estimation And Chemistry Model, a process-based model of water and solute movement, transformations, plant uptake and chemical reactions in the unsaturated zone, version 3, Research Series No. 92-3. Department of Soil, Crop and Atmospheric Sciences, Cornell University, NY, USA, September 1992.
Jury, W.A., Grover, R., Spencer, W.F., Farmer, W.J., 1983. Behaviour assessment model for trace organics in soil. I. Model description. J. Environ. Qual. 12, 558±564.
Mualem, Y., 1976. A new model for predicting conductivity of unsaturated porous media. Water Resour. Res. 13(4), 773±780.
Pennell, K.D., Hornsby, A.G., Jessup, R.E., Rao, P.S.C., 1990. Evaluation of ®ve simulation models for predicting aldicarb and bromide behaviour under ®eld conditions. Water Resour. Res. 26(11), 2679± 2693.
Rawls, W.J., Brakensiek, D.L., 1982. Estimating soil water retention from soil properties. J. Irrig. Drain. Div. ASCE 108, 166±171.
Russell, M.H., 1995. Recommended approaches to assess pesticide mobility in soil. In: Roberts, T.R., Kearny, P.C. (Eds.), Environmental Behaviour of Agrochemicals, vol. 9. Wiley, New York, pp. 57±129.
Thomasson, A.J., Carter, A.D., 1992. Current and future uses of the UK soil water retention data set. In: van Genuchten, M.Th., Leij, F.J., Lund, L.J. (Eds.), Proceeding of the International Workshop on Indirect Methods for Estimating the Hydraulic Properties of Unsaturated Soils, University of California, Riverside, USA, pp. 355±358.
Van Genuchten, M.T., 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J. 44, 892±898.
Vanclooster, M., Boesten, J.T.T.I., Trevisan, M., Brown, C., Capri, E., Eklo, O.M., GottesbuÈren, B., Gouy, V., Van der Linden, A.M.A., 2000. A European test of pesticide-leaching models: methodology and major recommendations. Agric. Water Mgmt., this issue.
Walker, A., Calvet, R., Del Re, A.A.M., Pestemer, W., Hollis, J., 1995. Evaluation and improvement of mathematical models of pesticide mobility in soils and assessment of their potential to predict contamination of water systems, Mitt. Biol. Bundesanstalt f. Land- und Forstwirtschaft, Berlin-Dahlem, 307, pp. 1±115.
