Evaluation of pesticide dynamics of the WAVE-model
M. Vanclooster
a,*, S. Ducheyne
b, M. Dust
c, H. Vereecken
d aDepartment of Environmental Sciences and Land Use Planning, Unite GeÂnie Rural,Universite Catholique de Louvain, Place Croix du Sud 2/2, B-1348 Louvain-la-Neuve, Belgium
bInstitute for Land and Water Management, Katholieke Universiteit Leuven, Vital Decosterstraat 102,
B-3000 Leuven, Belgium
cDuPont de Nemours SA, ERDC rue du Moulin 21, F-68740, Nambsheim, France dInstitut fuÈr Chemie und Dynamik der GeosphaÈre, Forschungszentrum JuÈlich GmbH (KFA),
Wilhelm Johnen Strasse, D-5170 JuÈlich, Germany
Abstract
A validation study of the physical based pesticide leaching model WAVE is presented. The model considers a mechanistic description of 1-D water, solute and heat transport. Linear sorption isotherms and ®rst order degradation sub-models are used to simulate pesticide sorption and transformation. The ®rst order degradation rates are reduced when temperature and moisture stress in the soil pro®le occur. The model is conceived to describe pesticide fate within rigid mineral soils. Model tests were therefore done using data collected at a sandy (Vredepeel) and a loamy soil (Weiherbach). Both ®eld data and lysimeter data were used to evaluate the performance to describe water, bromide, ethoprophos, bentazone and isoproturon transport in soil. The evaluation procedure presented by Vanclooster et al. (Agric. Water Mgmt., Vol. 44, pp. 1±19) was completely adopted. The measured soil moisture in the sandy soil could only successfully be described after calibrating the hydraulic functions using ®eld observed soil moisture pro®les. In addition, the predicted balance terms, such as the soil water drainage, were subject to a lot of uncertainty. Bromide transport in the sandy soil was poorly described with the equilibrium solute transport model. Anomalies were also observed when simulating the transport of the inert tracer in the lysimeter at the loamy site. The fate of the weakly sorbing bentazone component was appropriately described at the Vredepeel ®eld site. However, the retardation of the strongly sorbing ethoprophos and isoproturon components was poorly simulated. Further, the pesticide dissipation varied considerably in time, which could not be accounted for with the ®rst order degradation model.
The need for model calibration illustrates the constraints when using mechanistic models such as WAVE to predict ®eld scale pesticide fate and transport. The adoption of a mechanistic model for registration purposes may therefore be subjected to a lot of uncertainty. In addition, processes affecting pesticide fate and transport are still poorly represented within the model. De®ciencies are
*Corresponding author. Tel.:32-10-473710; fax:33-10-473833.
E-mail address: [email protected] (M. Vanclooster).
0378-3774/00/$ ± see front matter#2000 Elsevier Science B.V. All rights reserved.
related to the description of non-linear sorption, time dependent pesticide degradation, and pesticide volatilisation. Future developments with the model should therefore envisage to improve the parametrisation reduce the output uncertainty, and improve process descriptions of essential processes.#2000 Elsevier Science B.V. All rights reserved.
Keywords:Pesticide leaching modelling; Validation; Solute transport
1. Introduction
Pesticide residues are retrieved in groundwater bodies all over Europe (Leistra and Boesten, 1989) and US. The impact of pesticide residues in groundwater is poorly understood. Yet, it is generally accepted that leaching losses from agricultural soils should be minimised as much as possible.
Pesticide leaching towards subsurface groundwater bodies is controlled by a range of soil and environmental conditions which are extremely variable in time and space. This makes the quantification of pesticide leaching a tedious task (Brown et al., 1995). Yet, in order to develop efficient farm management strategies, it is crucial to have correct information on the amount of pesticide lost, and this in terms of variable soil conditions, agricultural practices, meteorological and geo-hydrological conditions. Mechanistic pesticide fate and transport models are accepted as being powerful tools to deliver such information. Mechanistic models describe pesticide transport and dissipation based on well established basic physical, biological and chemical laws. However, the use of mechanistic models is jeopardised by badly defined model parameters which are hard to identify in a statistical sense. In addition, there is a shortage of sufficiently detailed experimental data to allow appropriate validation of mechanistic models. In a recent review for instance, Jarvis et al. (1995) noted that eight popular pesticide leaching models were only tested on 26 active components. This is definitely very few, given the amounts of components currently used. The low validation level of pesticide leaching models is a critical issue, especially if models are adopted within the pesticide registration process (Boesten et al., 1995). Particular attention should therefore be devoted to improve the general validation status of pesticide leaching models.
In this paper, a validation study is reported of the mechanistic±deterministic leaching model WAVE (Vanclooster et al., 1994). The model has been conceived to describe pesticide fate within rigid mineral soils. Earlier tests and application studies with the model have been summarised by Muno-Carpena et al. (1998). Model tests in the present study are performed on a dataset collected on a sandy and a loamy soil (Vredepeel site: Boesten and Van der Pas, 2000; Weiherbach site: Shierholz et al., 2000). Both field and lysimeter data were used to evaluate the performance of the different components of the model. The evaluation procedure presented by Vanclooster et al. (2000) was completely adopted. In order to elucidate the ability of the model to predict pesticide fate from laboratory data, uncalibrated model results are shown. These results illustrate the validity of the model when used for instance in a registration context. In addition, results with calibrated model parameters are shown. The calibration allows to scale up laboratory-scale input parameters to effective field-laboratory-scale input parameters.
2. Materials and methods
2.1. The model
A detailed description of the WAVE-model can be found in Vanclooster et al. (1994). The WAVE-model combines different ad-hoc state-of-the-art models like SWATRER (Belmans et al., 1983), SUCROS (Spitters et al., 1988) and modules of LEACHM (Wagenet and Hutson, 1989). The model is a revised version of the SWATNIT-model (Vereecken et al., 1991). The model is programmed in a modular way and can easily be expanded to model the fate of other agro-chemicals in the soil-crop environment. The WAVE-model is mechanistic and deterministic. It can handle different soil horizons which are divided into equidistant soil compartments. A water, heat and solute mass balance equation is developed for each compartment, taking into consideration different sink/source terms. Physical transport equations are implemented which are solved numerically using finite difference techniques.
Water transport is modelled using Richards' equation, which is obtained by combining Darcy's law with the mass conservation equation:
C h@h
where C(h) is the differential moisture capacity; K(h) the hydraulic conductivity relationship;h[L] the soil water pressure head; Sinkwat [Tÿ1], the water sink term; andz
[L],t[T] the space and time co-ordinates. The water transport model assumes that soil water ¯ow occurs in response to a hydraulic potential gradient which in this case obeys the capillary ¯ow theory. This means that preferential water ¯ow, by-passing the soil matrix, is not explicitly accounted for with the present model. Yet, it should be noted that fast ¯ow in larger pores can partially be simulated by adopting a heterogeneous pore size distribution, and hence a heterogeneous soil moisture retention characteristic and hydraulic conductivity relationship (Durner, 1994). Alternatively, ®eld scale water transport, and hence water ¯ow as well in large and small pores, can often successfully be described using a stochastic description for the water transport parameters in a Monte Carlo type of analysis. In this case, the 1-D ¯ow equation of WAVE is solved iteratively for a representative sample of the adopted probability density function of the water transport parameters (Mallants et al., 1996). Parametric forms of van Genuchten (1980) were adopted to model moisture retention:
y ys
1
1 ahn
m (2)
whereys[±] is the saturated moisture content;a[Lÿ1] the inverse of the air entry value; and n a shape parameter. Hydraulic conductivity was modelled with the Brooks and Corey (1964) relationship at Vredepeel:
and the van Genuchten±Mualem model (van Genuchten, 1980) at Weiherbach:
whereKs[L Tÿ1] is the saturated hydraulic conductivity;yr[±] the residual soil moisture content; andl,tshape parameters of the conductivity curve.
Water uptake by the crops is described with a macroscopic uptake term. The maximum uptake rate by the roots defined by Belmans et al. (1983) was modified. In the present study a weighing function, frac(x), is defined which is proportional to the root density distribution:
Z root depth
0
frac xdx1 (5)
where root_depth [L], is the actual rooting depth. The actual root uptake rate is de®ned as the potential transpiration rate,Tpot[L Tÿ1] multiplied with the weighing function [±] and reduced for water stress or
RTEX x Tpotfrac xa h (6)
wherea(h) is an Arrhenius type of reduction function in terms of soil water pressure head
h[L].
A hybrid model, considering physical non-equilibrium solute transport, is available in the code. The model considers convective dispersive flow in the mobile soil region together with a rate limited exchange between the mobile and the immobile soil regions. In the present validation study, equilibrium solute transport was considered such that the transport equation reduces to the well known convection±dispersion equation:
@ yC
whereC[M Lÿ3] is the volume averaged pesticide concentration of the soil solution;y [L3Lÿ3] the volumetric water content; Kd [L3Mÿ1] the distribution coef®cient; D [L2Tÿ1] the apparent dispersion coef®cient; qw [L Tÿ1] the Darcian water ¯ux; r [M Lÿ3] the apparent density and Sinksol [M Tÿ1] the solute sink term. The apparent dispersion coef®cient is a composite of the chemical diffusion and hydrodynamic dispersion coef®cient (Wagenet and Hutson, 1989):
D0:01D0exp 10y
Potential first order degradation constants are reduced in terms of soil moisture and soil temperature based on the approach suggested by Walker (1974):
kdecfyfTkpot (9)
Heat transport is modelled using Fourier's law as illustrated by Tillotson et al. (1980) and Wagenet and Hutson (1989): properties in the model are calculated as suggested by de Vries (1952).
For the Vredepeel dataset no attempt was made to model crop growth with the available crop growth simulator. The evolution of crop leaf area and rooting depth and distribution were estimated from the available literature data. On the contrary, for the Weiherbach dataset, the integrated crop module was adopted to generate crop leaf area index from meteorological and plant phenological data.
2.2. Initial model parametrisation and input estimation
The data used to test the model are the field data collected at Vredepeel, The Netherlands and Weiherbach, Germany. A detailed description of the dataset can be found in Boesten and Van der Pas (2000) and Shierholz et al. (2000). For the Vredepeel soil, numerical grids of 100 mm were used. The Weiherbach soil was descretised in 38 soil layers of 50 mm.
2.2.1. The water balance component
Climatological data measured at Vredepeel (precipitation, air temperature) were collected from the nearby meteorological stations in Beek and Arcen (global radiation, wind speed) and were processed to calculate the potential reference evapotranspiration according to an update of the Penman±Monteith method (Allen et al., 1994). The total potential reference evapotranspiration obtained for the simulation period (23/11/1990±3/ 10/1992) was 754 mm. This value overestimates substantially the total Makkink reference evapotranspiration of 599 mm as provided in the dataset report by the Koninklijk Nederlands Meteorologisch Instituut (Fig. 1). For the Weiherbach site, the available daily potential Penman evapotranspiration rates were directly used as model input (Shierholz et al., 2000). Measured moisture contents at the onset of the simulation were used to initialise the model at Vredepeel. Initial soil moisture conditions for
Fig. 1. Comparison of the FAO and Makkink reference evapotranspiration for the Vredepeel dataset.
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Weiherbach were obtained through previous simulations starting from 1 January assumingÿ100 hPa tension.
The development of crop LAI for winter wheat at Vredepeel was taken from literature data collected in similar conditions (Groot and Verberne, 1991). Musterd grass LAI was set equal to 2. The crop factorsKc were estimated from relevant data sources (Feddes, 1987). The crop growth parameters reported in the WAVE manual for winter wheat (1993±1994) and summer barley (1995) were used as input for the crop growth simulator at the Weiherbach site. For the lysimeter data, the literature inferred Kc factor was multiplied with 1.25 in order to account for increased evapotranspiration that often occurs in small lysimeters compared to the field situation (Boesten, 1994).
Available laboratory measured data of the drying moisture release curve and the hydraulic conductivity curve were fitted to Eqs. (2) and (3) to yield an initial estimate of the hydraulic properties at Vredepeel. Results are given in Tables 1 and 2. Following Fuentes et al. (1992) the shape parameterm was set equal to 1ÿ(2/n). The saturated hydraulic conductivities as measured on duplicate soil cores were not used to parametrise the hydraulic conductivity model since these values are subjected to a huge variability and prone to experimental artefacts.
For the two soil horizons at the Weiherbach site, the hydraulic parameters of Eqs. (2) and (6) as reported by Shierholz et al. (2000) were directly used. For this sitemwas set Table 1
Moisture retention parameters for the Vredepeel and Weiherbach ®eld site
Dataset Layer (cm) Uncalibrated Calibrated
ys[±] yr[±] a(cmÿ1) n[±] ys[±] yr[±] a(cmÿ1) n[±]
Vredepeel 0±30 0.369 0 0.037 2.655 0.369 0 0.02 2.655
30±60 0.393 0 0.033 2.623 0.393 0 0.06 2.623
60±100 0.29 0 0.020 3.327 0.29 0 0.025 3.327
100±140 0.29 0 0.020 3.327 0.35 0 0.02 3.327
Weiherbach 0±30 0.46 0.03 0.015 1.30 0.46 0.03 0.015 1.30
30±200 0.45 0.08 0.005 2.25 0.45 0.08 0.005 2.25
Table 2
Hydraulic conductivity parameters for the Vredepeel and the Weiherbach ®eld site
Dataset Layer (cm) Uncalibrated Calibrated
Ksat(cm per day) Z Ksat(cm per day) Z
Vredepeel 0±30 10 4.2 10 4.9341
30±60 10 6.5 10 5.2235
60±100 10 3.1 10 2.36
100±140 10 3.1 10 2.437
Weiherbach 0±30 12.0 0.5 12.0 0.5
30±195 7.2 0.5 7.2 0.5
195±200 7.2 0.5 3.6a 0.5
aOnly for the lysimeters.
equal to 1ÿ(1/n) andtto 0.5. Saturated water content (water content at 15 538 hPa) and saturated hydraulic conductivity were measured directly. The shape parameters were estimated using inverse modelling based on the measured outflow curves according to the method reported by Van Dam et al. (1994).
2.2.2. The solute and heat balance components
The default parametrisation of the heat transport model as reported in the WAVE manual was adopted in the study. The hydrodynamic dispersivity was set equal to 3 cm for the sandy soil and 10 cm for the loamy soil. The soil chemical diffusion was set to 1.6 mm2per day for bromide, 35 mm2per day for ethoprophos and bentazone, and 5 mm2 per day for isoproturon. Since bromide is an anion, root uptake of the ``tracer'' was considered for Vredepeel (51 kg total uptake in the winter wheat crop and 14 kg in the mustard).
2.2.3. The pesticide balance component
To account for pesticide volatilisation, total pesticide input was reduced in Vredepeel as suggested by Van den Bosch and Boesten (1994). Bentazone and ethoprophos distribution constants were inferred from theKomandfommeasurements reported by Van der Pas (1994). For isoproturon, the batch experiments reported by Shierholz et al. (2000) were used (Table 3).
The potential first order degradation rate constants were inferred from the batch experiments reported by Van der Pas (1994) and Shierholz et al. (2000) (Table 4). The base temperature withinfT(Eq. (11)) was set to 158C for ethoprophos and bentazone and 258C for isoproturon. TheQ10value was set equal to 2. The exponent withinfy(Eq. (10)) was set equal to 0.053 for Vredepeel, while the batch experiments measured at 20, 40 and 60% ofysatenabled this exponent to be set equal to 0.2 for the Weiherbach soil. Uptake of pesticide was never considered but lumped within the decay process.
2.3. Model calibration
For illustrating the impact of using effective calibrated field parameters instead of laboratory scale parameters, calibrated modelling results are shown as well. Calibration was performed on a trial and error basis, using the field scale observed moisture content, bromide content, and pesticide content as objects.
Table 3
Pesticide sorption properties for the Vredepeel and Weiherbach ®eld sites
Dataset Layer (cm) Kd(uncalibrated) (l kgÿ1) Kd(calibrated) (l kgÿ1)
At Vredepeel, the field data of 1990 and 1991 was used for calibration, while the data of 1992 were used for the evaluation. Observed soil moisture profiles at day 103 and 278 were used to refine initial estimates of the hydraulic properties. Theavalue (Eq. (2)) for all layers was calibrated assuming equilibrium with the groundwater table at day 103. Further, the soil porosity of the layer below 1 m was increased and the conductivity of the 30±60 cm soil layer was augmented as recommended by Van den Bosch and Boesten (1994). The final parameter estimates are also given in Tables 1 and 2.
The initial retardation of the strongly sorbing ethoprophos was underestimated which was compensated by calibrating theKdconstant. The laboratory determined decay rate of ethoprophos was calibrated to account for the overestimated dissipation at the soil surface.
For the Weiherbach site, data for the year 1993±1994 were used to calibrate the model, while the results for the year 1995 were used to validate the model. For the lysimeter data at Weiherbach, theKsatin the lowest layer (0.05 m thick) was set to 36 mm per day, i.e. 50% of the measured value to account for decreased conductivity due to the nature of the lysimeter boundary construction.
3. Results and discussion
The uncalibrated and calibrated soil moisture and soil bromide profiles at days 103, 278 and 474 at Vredepeel are given in Fig. 2. The simulated concentration profiles of bentazone and ethoprophos are given in Fig. 3.
For modelling the soil moisture profiles in Vredepeel, calibration was needed to account for the scale gap between the laboratory measured retention and hydraulic conductivity curves and the effective field hydraulic properties. The porosity (ys) of the bottom layers was considered to be higher in order to describe the moisture content at the bottom of the soil profile on 27/8/91 (Fig. 2c). The air entry value of all layers was changed assuming hydraulic equilibrium with the shallow groundwater on 5/3/1991, similar to Van den Bosch and Boesten (1994). Given these calibrations, the soil moisture profile of the spring of 1992 could reasonably well be predicted. It should be mentioned, however, that the calibration of the soil moisture profiles proved to be a tedious job. In total, 18 trials were made before the calibration was accepted. This large number of Table 4
Pesticide degradation parameters
Dataset Layer (cm) kdec(uncalibrated) (per day) kdec(calibrated) (per day)
Vredepeel±ethoprophos 0±40 0.089 0.012
underestimated. The measured bromide at the soil surface could be a result of the internal entrapment of bromide within soil immobile zones upon its application. These solutes, situated at the soil surface, slowly get released from the immobile towards the mobile regions by a diffusion controlled process. In addition, mineralisation of structural root bio-mass after harvest or root exudates can explain the presence of bromide close to the soil surface. We believe that the adoption of a more appropriate non-equilibrium solute Fig. 3. Simulated bentazone and ethoprophos pro®les at Vredepeel on days: (a) 103, (b) 278 and (c) 474.
transport concept with appropriate descriptions of the solute boundary conditions, and a more mechanistic approach for describing bromide turn-over in the rhizosphere would improve the simulation of the solute transport component at Vredepeel.
The simulated ethoprophos and bentazone concentration profiles are given in Fig. 3. The overall migration of ethoprophos was overestimated given the kom and fom. Increasing the Kd value did allow a correct description of the centre of mass of the ethoprophos plume but not its dispersion. The measured ethoprophos profiles show a rather sharp boundary, which is typical for non-linear sorbing pesticides. Non-linear sorption is however not accounted for in the present version of the model, and the model will therefore fail to describe appropriately the migration of non-linear sorbing pesticide components if laboratory sorption data are used.
The dissipation rate of ethoprophos in the early season was overestimated. This could be due to an inappropriate estimation of the pesticide volatilisation (which was arbitrarily set equal to 50% of the pesticide applied), or due to an appropriate modelling of the biotic and abiotic transformation processes in the early season. The overestimation of the dissipation rate was corrected by calibrating kdec. Given these corrections, the ethoprophos content was still overestimated in the summer season. This could again be corrected by calibrating the Tb value of Eq. (11). The time dependent degradation resulting from this calibration could probably account for the adaptation of the soil bio-mass, a mechanism which is not considered in the present version of the model.
Fig. 4. Soil water contents, pro®les of bromide and isoproturon at the Wieherbach ®eld plot, 1993/1994, experimental results and simulation: calibration.
The profiles of the mobile bentazone component could successfully be simulated without any calibration. The surface accumulation which was pronounced for the bromide profiles becomes nearly insignificant in the spring of 1991. The successful simulation of the bentazone profile in contrast to the bromide profile indicates the dominant sensitivity of degradation and sorption parameters to describe pesticide behaviour in soil.
In contrast to the Vredepeel site, good accordance was found between simulated and field measured soil moisture profiles during the first growing season using the laboratory measured hydraulic parameters at Weiherbach (Fig. 4). This could be due to a better performing parameter identification procedure based on inverse modelling. It should also be noted that only winter data were used to assess the model performance during this season. Total mass and distribution of bromide were well predicted without further calibration of the solute transport parameters. Under soil moisture conditions of 1993/ 1994 the laboratory derived value of 0.715 of the Walker-parameterb(Eq. (10)) predicted unrealistic dissipation of the pesticide in the 0±0.95 m soil layer. Decreasingbto 0.2 led to adequate mass predictions of isoproturon. Downward transport of the herbicide was slightly overpredicted during the 141 days of the field experiment whereas dissipation at the top 15 cm of the soil was underpredicted. Again, invoking a non-linear sorption isotherm would improve this simulation. Using the calibrated dissipation parameters it was possible to simulate realistic residue profiles of isoproturon.
Fig. 5. Drainage volumes, bromide and isoproturon loads in leachates from lysimeters at the Wieherbach site, 1993/1994, experimental results and simulation: calibration.
Drainage fluxes and accordingly bromide loads observed in the lysimeters displayed a considerable variation (Fig. 5). The model predicted leachate volumes are within the experimental range. The starting of drainage was also matched. Timing of bromide breakthrough was also well predicted, but total loads were matched only once and underpredicted for the other three lysimeters. Accordingly, we were not able to predict the isoproturon load in the drainage water. In three replicates less isoproturon was measured than simulated, revealing an underestimation of the pesticide retardation. In the fourth lysimeter, most probably preferential flow contributed to an early breakthrough. Considering the experimental variations the mechanistic±deterministic modelling approach proved to be limited to predict leaching processes in the lysimeter system under investigation.
In 1995 the field plot in Weiherbach received an irrigation of 260 l mÿ2in addition to the rainfall of 285 l mÿ2. Soil hydraulic parameters proven to be valid for the 1993/1994 did no longer allow to predict accurately the moisture profiles. In the 36 days period of this experiment soil moisture was overpredicted (Fig. 6). Bromide profiles were accurately predicted in the first 22 days of the simulation, but dissipation of bromide in the 0.95 m soil profile was underestimated at the end of the study. Obviously, the change of porosity due to tillage or other processes that affected water flow and solute transport in 1995 is not accounted for within the present model concept. In addition, the model did not accurately predict total amounts of isoproturon in the 1995 soil profile. Dissipation of
Fig. 6. Soil water content, pro®les of bromide and isoproturon at the Weiherbach ®eld plot 1995, experimental results and simulations: evaluation.
the pesticide was faster in the field than simulated. As for the Vredepeel dataset, enhanced microbial activity and increased degradation rates could be invoked.
On the lysimeters two irrigation regimes were imposed. Group I received 140 l mÿ2 and group II 280 l mÿ2. Drainage volumes were always overpredicted (Fig. 7). However, the prediction of the start of bromide breakthrough was successful. Again, transport mechanisms other than convection dispersion must have occurred since in the lysimeter 3 a smaller bromide load was detected than in lysimeter 4 which had a smaller drainage. Breakthrough of isoproturon was observed in all lysimeters. In group I the duplicates behaved similar, but the model overestimated pesticide loads and predicted a late start of the isoproturon breakthrough. Again, non-linear sorption mechanisms and enhanced degradation could be invoked. Huge differences of isoproturon loads in the leachates were observed in group II that do not correspond to the observations of the bromide loads. More information of the governing transport mechanism is needed to understand pesticide fate in these conditions.
4. Conclusions
In this study, the different components of the integrated pesticide leaching model WAVE were systematically evaluated using two datasets collected on a sandy (Vredepeel, Netherlands) and a loamy (Weiherbach, Germany) soil.
Fig. 7. Drainage volumes, bromide and isoproturon loads in leachates from lysimeters at the Weiherbach site, 1995, experimental results and simulation: evaluation.
Predicting field measured soil moisture profiles from laboratory measured soil moisture retention and hydraulic conductivity relationships is limited. The laboratory inferred model parameters do not consider the same heterogeneity as present within the field. In addition, temporal dynamics (effect of soil tillage, etc.) are not correctly accounted for when using parameters inferred from laboratory cores sampled at a fixed time. From the difference in performance of the uncalibrated soil water flow model between Vredepeel and Weiherbach, it can be learned that hydraulic parameters inferred from dynamic flow experiments, such as the multi-step outflow method, are more appropriate than parameters inferred from classical soil physical set-ups.
No direct measurements of the different water balance terms are available in Vredepeel. Identifying the correct atmospheric evapotranspiration demand was proven to be problematic for this dataset, yielding a serious uncertainty on predicted drainage fluxes at this site. Predicting the balance terms measured within lysimeters at the Weiherbach field proved also to be limited. Lysimeters are point samples collected within a heterogeneous field. Large variations are therefore observed in the measured drainage fluxes. These variations could not be described with the presented deterministic modelling approach.
The classical convection dispersion equation did not allow to explain the accumulation of the bromide at the soil surface of the sandy soil. Apparently, some soil regions at the soil surface catch the bromide within an immobile zone which slowly releases its tracer to the mobile soil solution. In addition, bromide±crop interaction was proven to be important and more information on the solution±crop interaction is needed to understand the fate of this ``inert'' ionic tracer. Solute profiles in loamy soil on the other hand were successfully described with the equilibrium transport model. Yet, when analysing the lysimeter flow terms at this site, again non-equilibrium phenomena become more pronounced, resulting in high bromide load for lysimeters showing small drainage.
The linear sorption isotherm model was inadequate for describing isoproturon and ethoprophos retardation. This modelling approach resulted in an overestimate of the dispersion of the pesticide in the profile and did not correctly describe the self-sharpening migration front of highly sorbing pesticides. This modelling approach was however more successful for the mobile bentazone component. The rather good description of the pesticide fate in comparison to the tracer fate is an indication of the small sensitivity of pesticide transport to solute transport parameters.
A first order degradation model is limited for describing pesticide dissipation. Temporal dynamics of dissipation rates can partly be accounted for by manipulating the temperature and soil moisture stress reduction function of the first order degradation constant. Yet, it is our belief that a more mechanistic model of the micro-biological activity is needed to appropriately describe the enhanced or retarded pesticide degradation. The overestimate of the ethoprophos content in the early summer season at the Vredepeel site could also be due to an inappropriate estimate of the volatilisation losses. More appropriate descriptions for pesticide volatilisation losses would therefore definitely increase the validation status of the present model.
on the model parameter and model input estimates were considered in the present study. A more advanced validation strategy, including sensitivity analysis and uncertainty propagation analysis should be considered in future in order to be able to compare ranges of measurements with ranges of simulation. In addition, more objective and automated calibration procedures based on direct field measurement should be further developed. Using deterministic models helps to identify crucial processes with regard to water, solute and pesticide fate in soils, but their potential for accurate predictions is currently still limited.
Acknowledgements
We thank Peter Viaene for programming the pesticide module within the existing WAVE code. The European Communities are acknowledged for their support of this work through the COST66 action on `Pesticide fate in the soil environment'. We thank Dr. Boesten and Dr. Shierholz for providing the experimental data which helped to carry out this study.
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