Testing PESTLA using two modellers for bentazone and ...directory.umm.ac.id/Data Elmu/jurnal/A/Agricultural... · Testing PESTLA using two modellers for bentazone and ethoprophos

Testing PESTLA using two modellers for bentazone

and ethoprophos in a sandy soil

J.J.T.I. Boestena,*, B. GottesbuÈrenb

aAlterra Green World Research, Wageningen University and Research Centre,

PO Box 47, 6700 AA Wageningen, NetherlandsbBASF AG (APD/RB), Landwirtschaftliche Versuchsstation, PO Box 120, 67114 Limburgerhof, Germany

Abstract

Two modellers tested the PESTLA model (version 2.3.1) against results of a ®eld study on

bentazone and ethoprophos behaviour in a sandy soil. Both modellers achieved an acceptable

description of the measured moisture pro®les but only after calibration of the soil hydraulic

properties. Both could describe the bromide-ion concentration pro®les measured at the end of the

®rst winter reasonably well. However, both predicted that practically all bromide had leached out of

the top 50 cm of the soil at the end of the second winter, whereas about 10% of the bromide dose

remained in this layer. This is attributable to a systematic deviation of bromide transport from the

concept assumed in the convection/dispersion equation and/or to the release of bromide from dead

root remnants. Both modellers derived pesticide transformation and sorption parameters from

laboratory studies with soil from the ®eld. Both described bentazone movement reasonably well.

Modeller 1 described the concentration pro®les reasonably well, whereas Modeller 2 strongly

overestimated the concentrations at the end of the study. This difference was mainly attributable to a

difference in interpretation of the temperature dependence of the transformation rate of bentazone.

Only Modeller 2 simulated ethoprophos behaviour. He simulated the persistence of ethoprophos in

the top 20 cm very well during the ®rst 200 days. However, thereafter the transformation in the ®eld

proceeded much faster than simulated. This is probably caused by accelerated transformation

resulting from exposure of the top soil layer to about 1 mg kgÿ1 of ethoprophos over 200 days.

Simulated penetration of ethoprophos was deeper than measured. By including accelerated

transformation (admittedly on an ad-hoc basis) within the simulations, good agreement was

achieved between measured and simulated penetration of ethoprophos. Calculations showed that the

effect of calibrating water ¯ow was substantial for bentazone but small for ethoprophos. However,

the effect of calibration of water ¯ow for bentazone was much smaller than the effect of the

difference between the transformation rate parameters derived by the two modellers. We

recommend that the guidance for deriving pesticide±soil input parameters be improved in order to

Agricultural Water Management 44 (2000) 283±305

* Corresponding author. Tel.: �31-317-47-4343; fax: �31-317-42-4812.

E-mail address: [email protected] (J.J.T.I. Boesten).

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 6 - 7

reduce differences between modellers because a large in¯uence of the person of the modeller on the

outcome of model tests is unacceptable for methodological reasons. # 2000 Elsevier Science B.V.

All rights reserved.

Keywords: Pesticide leaching; Modelling; Modeller subjectivity

1. Introduction

Mathematical leaching models are useful tools for assessing the risk of groundwater

contamination resulting from the agricultural use of pesticides. In general, the validation

status of such models needs to be improved (FOCUS Regulatory Modelling Workgroup,

1995) via testing them against high-quality field data sets. In the Dutch pesticide

registration procedure, the PESTLA model has been used since 1989 for a first

assessment of pesticide leaching potential. This assessment is based on the Dutch

standard scenario as described by Boesten and van der Linden (1991). This scenario is

based on a sandy soil profile which is considered representative of sandy areas in the

Netherlands where groundwater is pumped up to be used as drinking water. The

Vredepeel data set (described by Boesten and van der Pas, 1999, 2000) was collected to

test PESTLA for a realistic field situation similar to the Dutch standard scenario. The aim

of the present study is to test the PESTLA model against this data set. The test is

performed by two modellers (the authors) in order to take into account the possible effect

of modeller subjectivity on the result of the model test (Brown et al., 1996; Boesten,

2000). The modellers are indicated by their initials: JB and BG.

van den Bosch and Boesten (1994) performed the first test of PESTLA against the

Vredepeel data set. The PESTLA version they used (described by van der Linden and

Boesten, 1989; Boesten and van der Linden, 1991) only includes equilibrium sorption. It

has already been recognised for some time that non-equilibrium sorption may influence

leaching considerably (Walker, 1987; Boesten et al., 1989). Therefore, the Vredepeel data

set contains pore water concentrations from which non-equilibrium sorption parameters

can be derived. So, in the present study a PESTLA version is used that includes non-

equilibrium sorption (version 2.3.1). This version will be replaced in the near future by a

PESTLA-3 version (van den Berg and Boesten, 1999) which contains the same

description of non-equilibrium sorption.

As described by Vanclooster et al. (2000), testing of pesticide leaching models should

proceed in three steps: firstly test the water flow sub-model, then test the solute transport

sub-model using a tracer and finally test the pesticide sub-model. This procedure is

followed: Section 3 deals with water flow, Section 4 with tracer movement, Section 5

with bentazone and Section 6 with ethoprophos. BG simulated bentazone behaviour but

made no calculations for ethoprophos.

2. Description of the 2.3.1 version of PESTLA

PESTLA 2.3.1 consists of sub-models for water flow, soil temperature and pesticide

behaviour. Water flow is simulated with the SWACROP model described by Feddes et al.

284 J.J.T.I. Boesten, B. GottesbuÈren / Agricultural Water Management 44 (2000) 283±305

(1978), Belmans et al. (1983) and de Jong and Kabat (1990). It assumes one-dimensional

(vertical), transient, unsaturated/saturated water flow in a heterogeneous soil-root system

using the Darcy flow equation and the conservation equation (including a sink term for

water uptake by the crop). Soil temperatures are simulated using Fourier's law assuming a

heat conductivity and a heat capacity that are functions of the volume fraction of water in

the soil. The temperature at the soil surface is assumed to be equal to the daily average of

air temperature. The boundary condition at the bottom of the soil system is defined as a

constant soil temperature at 10 m depth.

The mass concentration of the pesticide in the soil system, c* [M Lÿ3], is described as

c� � ycL � r�XE � XNE� (1)

in which y is the volume fraction of water in soil, cL the mass concentration of pesticide

in the liquid phase [M Lÿ3], r the dry soil bulk density (M Lÿ3), XE the equilibrium

content sorbed of pesticide [M Mÿ1] and XNE the non-equilibrium content sorbed of

pesticide [M Mÿ1]. The equilibrium content sorbed is described with a Freundlich

sorption isotherm

XE � mOMKOM;EcL;REFcL

cL;REF

� �N

(2)

in which mOM is the mass fraction of soil organic-matter, KOM,E is the organic-matter/

water distribution coef®cient [L3 Mÿ1] for the equilibrium sorption sites, cL,REF is a

reference value of cL (set at 1 mg dmÿ3) and N is the Freundlich exponent. The non-

equilibrium content sorbed is described by ®rst-order kinetics assuming a Freundlich

isotherm for the non-equilibrium sorption sites

@XNE

@t� kD mOMKOM;NEcL;REF

cL

cL;REF

� �N

ÿXNE

" #(3)

in which t is the time [T], kD is the desorption rate constant [Tÿ1] and KOM,NE is the

organic-matter/water distribution coef®cient [L3 Mÿ1] for the non-equilibrium sorption

sites. Boesten and van der Pas (1988) give the theoretical background of Eq. (3) and

Boesten (1991) gives an example of the in¯uence of adding Eq. (3) on the amount

leached. The introduction of the parameter cL,REF in Eqs. (2) and (3) eliminates the

problem that the product mOM KOM has a unit that is a function of N. Pesticide transport in

soil is described with the convection/dispersion equation and pesticide plant uptake with

the concept of the transpiration-stream concentration factor (see Boesten and van der

Linden, 1991).

The rate of transformation in soil, RT [M Lÿ3 Tÿ1], is described with the first-order rate

equation

RT � kc� (4)

in which k is the ®rst-order transformation rate coef®cient [Tÿ1] which depends on soil

moisture, temperature and depth as described by Boesten and van der Linden (1991). Eq.

(4) is used as long as the product rXNE is less than 70% of c* which implies that less than

70% of the total concentration is at the non-equilibrium sorption site. If more than 70% is

J.J.T.I. Boesten, B. GottesbuÈren / Agricultural Water Management 44 (2000) 283±305 285

at the non-equilibrium site at a particular soil depth, the transformation rate is described

as

RT � kLycL (5)

in which kL is the rate coef®cient for transformation in the liquid phase [Tÿ1] which is

calculated as

kL � minkc�

ycL� ��

; kL;MAX

� �(6)

in which kL,MAX is the maximal transformation rate coef®cient in the liquid phase [Tÿ1].

The value of kL,MAX is set at 2 per day in the model (which is an arbitrary high rate). Eqs.

(5) and (6) imply that the description is identical to Eq. (4) as long as this corresponds to a

transformation rate coef®cient in the liquid phase of less than 2 per day. If the rate

becomes higher (because a large fraction of the pesticide is sorbed on the non-equilibrium

sites), the limit of 2 per day will prevent too high a rate of transformation. This somewhat

complicated construction is needed because it is conceptually not probable that the

amount sorbed at the non-equilibrium sites is subject to transformation.

The procedure of the numerical solution of the pesticide part of the model is the same

as described by Boesten and van der Linden (1991). For the bentazone simulations, both

BG and JB used compartments that were 5 cm thick. Only JB performed ethoprophos

simulations. He used compartments of 2 cm in the top 30 cm and of 5 cm below 30 cm.

The thinner compartments for ethoprophos were needed to obtain a solution of sufficient

accuracy for its narrower concentration pattern.

3. Water ¯ow

3.1. Procedure and results of uncalibrated runs

JB divided the soil into three layers (0±30, 30±60 and 60±200 cm) and derived

hydraulic characteristics from the site-specific laboratory measurements described by

Boesten and van der Pas (2000) using the RETC package to fit the Van-Genuchten

parameters. Details of the fitting procedure are described by van den Bosch and Boesten

(1994). BG divided the soil into four layers (0±25, 25±50, 50±100 and 100±200 cm) and

estimated the Van-Genuchten parameters via combining information from pedo-transfer

functions (Vereecken et al., 1989), a Dutch database (WoÈsten, 1987) and the site-specific

measurements. Differences between the estimated hydraulic characteristics were

sometimes very large (see the uncalibrated moisture-retention curves for the top layer

in Fig. 1 as an example).

JB used the Makkink evaporation data from Boesten and van der Pas (2000) to estimate

potential evapotranspiration (see Feddes, 1987, for more information on the Makkink

procedure). BG used global radiation, air humidity and air temperature from Boesten and

van der Pas (1999) and the Makkink calculation procedure in SWACROP to estimate

potential evapotranspiration. We used different options to describe the bottom boundary

condition. JB used the option of a water flux through the bottom of the system, q [L Tÿ1],


that is calculated via q � aeÿbh in which a [L Tÿ1] and b [Lÿ1] are parameters and h is the

distance [L] between the groundwater table and the soil surface. This option results in a

simulated groundwater level. The value of a was 8 mm per day and b was 0.03 cmÿ1. BG

prescribed the groundwater level as a function of time on the basis of the measurements

by Boesten and van der Pas (1999).

The moisture profiles were not simulated well in the uncalibrated runs: JB

overestimated the volume fraction of liquid in the 30±60 cm layer and BG overestimated

the moisture profiles in almost all layers (see Fig. 2). JB simulated a too shallow

groundwater table for most of the experimental period as is shown in Fig. 3. The

systematic difference between measured and calculated moisture profiles shown in Fig.

2a and c is especially remarkable for the calculations by JB because these were based on

the hydraulic properties measured in the laboratory with soil samples from this particular

experimental field. A possible explanation is an inadequate handling of spatial variability

of soil hydraulic properties. As described by Boesten and van der Pas (2000), the core

samples for the measurements of the soil hydraulic properties were taken from only one

pit. It can be expected that the spatial variability within one field is considerable (as is

also indicated by the ranges of the measured moisture profiles in Fig. 2). So measuring

soil hydraulic properties using samples from one pit only may not be reliable. However, it

remains remarkable that JB overestimated the moisture contents in the 30±60 cm layer so

strongly in the uncalibrated runs.

3.2. Procedure and results of calibrated runs

JB changed the moisture-retention curve for the 0±30 cm layer to increase water

retention and he assumed that the hydraulic properties of the 30±60 cm layer were equal

Fig. 1. Calibrated and uncalibrated moisture-retention curves for the 0±25 cm layer of Vredepeel soil. Dashed

curves are uncalibrated (left by GottesbuÈren and right by Boesten) and solid curves are calibrated.


to those estimated for the 60±200 cm layer. The values of a and b were changed into

12 mm per day and 0.025 cmÿ1, respectively, to increase the water flux at the bottom of

the system (resulting in a deeper groundwater table). BG considered both the effects of

changes in hydraulic properties and of the root extraction pattern and the root depth. He

concluded that the effect of the root parameters could practically be ignored. He adjusted

Fig. 2. Comparison of measured and simulated moisture pro®les at Vredepeel after 103 and 278 days. The area

within the solid line segments is the range of the measured averages plus or minus two times the standard

deviation of the average. The dotted line was calculated by GottesbuÈren and the dashed by Boesten. Part A:

uncalibrated after 103 days, part B: calibrated after 103 days, part C: uncalibrated after 278 days, part D:

calibrated after 278 days.


the hydraulic properties by dividing the soil into two layers (0±25 and 25±200 cm)

and taking Van Genuchten parameters estimated by a Dutch database (WoÈsten, 1987).

The difference between the hydraulic relationships calibrated by BG and JB was small

(as is illustrated for the moisture-retention curve of the top layer in Fig. 1). Both

modellers achieved a good description of the measured moisture profiles via the

calibration (see Fig. 2b and d). JB also obtained a reasonably good description of the

groundwater level (Fig. 3), although the level in the field reacts more quickly to rainfall

events than is simulated.

Fig. 2. (Continued ).


4. Bromide movement

4.1. Procedure and results of uncalibrated runs

The uncalibrated runs for bromide-ion were made with the uncalibrated water flow

input. A bromide dose of 111 kg haÿ1 was used (Boesten and van der Pas, 2000). JB used

a dispersion length of 5 cm which was also assumed for the calculations on the Dutch

standard scenario for a soil with similar properties (Boesten and van der Linden, 1991).

BG assumed a dispersion length of 3 cm based on van den Bosch and Boesten (1994).

Both JB and BG assumed a transpiration-stream concentration factor of 1.0. Both

assumed no sorption and no transformation of bromide. JB obtained a reasonable

description of the bromide concentration profiles after 103 and 278 days; after 474 days

the calculated bromide concentrations in the upper 50 cm were below 0.5 mg dmÿ3,

whereas the average measured value was about 2 mg dmÿ3. BG calculated too little

bromide movement after 103 days (as a result of the overestimated water retention). After

278 days, he calculated much lower bromide concentrations than measured . Probably

this was caused by the plant uptake being too high (about 80% of the dose after 278

days). After 474 days, the shape of the concentration profile obtained by BG was similar

to that calculated by JB, but the concentration level was lower.

4.2. Procedure and results of calibrated runs

The calibrated runs for bromide were made with the calibrated water flow input. JB

tried to improve the fit between measured and calculated bromide profiles by varying the

dispersion length between 3 and 10 cm but this did not lead to improvements so the

Fig. 3. Comparison of measured and simulated groundwater level at Vredepeel as a function of time. The points

are measured depths, the solid line is the uncalibrated calculation and the dashed line is the calibrated

calculation (both by Boesten).


dispersion length was kept at 5 cm. BG did not modify the bromide input parameters, so

the only difference between his calibrated and uncalibrated runs was the improved

description of water flow. The results of the calibrated runs in Fig. 4 show that JB and BG

simulated bromide movement after 103 days reasonably well. After 278 days JB

described the bromide profile reasonably well but BG calculated lower concentrations

than measured (probably again caused by overestimation of plant uptake). JB and BG

could not simulate the concentration profile measured after 474 days: according to the

Fig. 4. Comparison of measured and simulated pro®les of bromide ion at Vredepeel after 103, 278 and 474 days

(in parts A, B and C, respectively). The area within the solid line segments is the range of the measured averages

plus and minus two times the standard deviation of the average. The dotted line was calculated by GottesbuÈren

and the dashed by Boesten; only results of the calibrated runs are given.


model almost no bromide was present in the 0±50 cm layer whereas concentrations in the

order of 1 mg dmÿ3 were measured in this layer (see Fig. 4). This discrepancy is possibly

caused by water moving preferentially in flow pathways which do not interact with

bromide present in the finer soil pores during the leaching in the second winter. Another

possibility is the release of bromide ion by dying plant roots. The total amount of bromide

recovered from the soil profile after 474 days corresponds to 20% of the bromide dose of

which about 10% was present in the top 50 cm. It can be expected that significant

amounts of bromide were taken up by the wheat (harvested after about 270 days) and

the mustard crops (grown between 300 and 380 days). Part of this bromide was present in

the wheat and mustard roots at their harvest and was released by diffusion and

mineralisation of the root remnants. A fraction of the bromide may still have been present

in the root remnants at the sampling time and may have been released during the

extraction of the soil in the laboratory. It is practically impossible to quantify the amount

of bromide that was released by the plant roots but it is possible that this was in same

order as the concentrations found in the top 50 cm after 474 days. In view of this

interpretation problem we recommend the measurement of bromide uptake by crops in

future studies.

5. Bentazone behaviour

5.1. Estimation of pesticide input parameters

JB use a bentazone dose of 0.63 kg haÿ1 (amount recovered after one day) and BG

used the calculated dose of 0.80 kg haÿ1 (Boesten and van der Pas, 2000). Pesticide/soil

input parameters were based on the laboratory studies by Boesten and van der Pas (1999,



2000) and were not further calibrated. JB used the parameters for the equilibrium sorption

isotherm (Eq. (2)) recommended by Boesten and van der Pas (2000); so

KOM,E � 2.1 dm3 kgÿ1 and N � 0.82. Parameters for the non-equilibrium sorption sites

(Eq. (3)) were derived from the measurements in the soil pore water during the incubation

of bentazone in top soil material at 5 and 158C (see Boesten and van der Pas, 1999).

Values of kD were 0.01 per day at 58C and 0.02 per day at 158C from which an average of

0.015 per day was derived. Similarly KOM,NE values of 0.7 and 1.6 dm3 kgÿ1 were found

at 5 and 158C, respectively, from which an average of 1.2 dm3 kgÿ1 was derived. BG

estimated all sorption parameters from the measurements in the soil pore water during the

incubation of bentazone in top soil material at 58C (see Boesten and van der Pas, 1999)

using the ModelMaker 2.0 software package. He found KOM,E � 1.7 dm3 kgÿ1, N � 0.73,

KOM,NE � 2.9 dm3 kgÿ1 and kD � 0.015 per day. So differences between the KOM,E, N

and kD values found by BG and JB were small. However, BG found a value of KOM,NE

that is more than two times the value found by JB.

JB used the transformation rate parameters of bentazone recommended by Boesten and

van der Pas (2000): half-life in the top layer of 62 day at 208C with temperature

coefficient g equal to 0.0798 Kÿ1 (for definition of g see Boesten and van der Linden,

1991), assuming no transformation between 50 and 100 cm depth and a transformation

rate below 100 cm depth that is 1.44 times as high as that in the top layer. BG derived a

half-life of 228 days at 58C and of 37 days at 158C. From these values, he estimated the

half-life of bentazone at 208C to be 15 days which he combined with g � 0.08 Kÿ1 (i.e.

the default value in PESTLA). He assumed no transformation between 50 and 100 cm

depth and a transformation rate below 100 cm depth that was 0.9 times the rate in the top

layer. Both JB and BG used the default value of 0.7 for the parameter B (describing the

moisture dependency of the transformation rate); for definition of B see Boesten and van

der Linden, 1991.

5.2. Results of uncalibrated and calibrated runs

Only JB made uncalibrated runs for bentazone, whereas both BG and JB made

calibrated runs for bentazone. Note that the calibration only dealt with the water flow

input for both BG and JB. The results in Fig. 5 shows that there were distinct differences

between bentazone concentration profiles as calculated by JB for uncalibrated and

calibrated water flow. Calibration resulted in some deeper bentazone movement into the

soil profile. This can be explained from the moisture simulation by JB shown in Fig. 2:

the uncalibrated run resulted in higher moisture contents than the calibrated run.

Comparison of the simulations with the measurements in Fig. 5 shows that the movement

of bentazone was simulated reasonably well in all runs after 103 and 278 days (although

BG overestimated the concentrations in the top layer after 278 days). JB overestimated

most bentazone concentrations (average values) after 103 and 278 days. After 474 days,

JB overestimated the bentazone concentrations strongly, whereas the concentration

profile simulated by BG corresponded well with the measured profile (in which all

concentrations were below the detection limit).

As described before, JB used a bentazone half-life of 62 days as input for the top layer

at 208C, whereas BG used a half-life of 15 days. These values differ strongly although


they were both based on the same laboratory studies. The difference is the result of a

difference in interpretation of the half-life at the reference temperature of 208C. JB

followed Boesten and van der Pas (2000) who intended to stick as closely as possible to

the laboratory incubation at 58C because this was closest to the field temperature in the

Fig. 5. Comparison of measured and simulated pro®les of bentazone at Vredepeel after 103, 278 and 474 (in

parts A, B, and C, respectively). The area within the solid line segments is the range of the measured averages

plus and minus two times the standard deviation of the average. For parts B and C the area is bounded by the

vertical axis. The area in part C indicates the detection limit: no bentazone was detected. The dotted line was

calculated by GottesbuÈren with calibrated water ¯ow and the dashed lines were calculated by Boesten (lightly

dashed for uncalibrated water ¯ow and heavily dashed for calibrated water ¯ow). Note that the scale of the

horizontal axis of part C is different.


relevant period (November±March). BG intended to stick as closely as possible to the

official input parameter for the model, i.e. the half-life at 208C which is also used for the

assessments in Dutch pesticide registration (Brouwer et al., 1994). This subtle difference

between the two modellers in interpretation of the operational definition of the reference

half-life has a very large effect on the result of the model test.

The comparison between measured and calculated concentration profiles of bentazone

in Fig. 5 indicates that modeller subjectivity in estimating bentazone input parameters

had a larger effect than the calibration of the water flow parameters: the differences

between the two lines calculated by JB are smaller than the differences between the lines

calculated by JB and BG for calibrated water flow.

JB used the bentazone transformation rate parameters suggested by Boesten and van

der Pas (2000), which implies a half-life of 205 day at 58C at field capacity in the top

25 cm (as was measured in the laboratory incubation at this temperature). The average

total amount of bentazone in the top 90 cm measured after 103 days was only 60% of the

amount simulated by JB. As described by Boesten and van der Pas (2000), the average

soil temperature at 2.5 cm depth over the first 103 days was 28C. So in the first 103 days,

the transformation proceeded considerably faster in the field than expected on the basis of

the laboratory incubation at 58C. As described by Boesten and van der Pas (2000), the

laboratory incubations were carried out with soil sampled before harvesting the preceding

crop (sugar beets). Between this sampling and the application of bentazone to the

experimental field, the sugar beets were harvested and the leaves were chopped and

incorporated into the soil. This may have caused an increased microbial activity in the

field soil. Smelt (personal communication, 1997) incubated bentazone in sterilised and

non-sterilised topsoil from this particular field and found that the transformation was

mainly microbial. So the higher microbial activity in the field soil may have resulted in

faster transformation of bentazone.



As shown by Fig. 5, the shapes of the bentazone concentration profiles simulated by

BG and JB for 103 and 278 days were similar, although BG used a KOM,NE for the non-

equilibrium sorption sites that was more than two times the value used by JB (see Section

5.1). This indicates that including the non-equilibrium sorption process had only a minor

influence on the calculated concentration profiles. JB tested this via an additional

calculation with zero KOM,NE and confirmed that the resulting concentration profiles of

bentazone differed only slightly from those calculated with the standard value of KOM,NE

used by JB. In general, a strong influence of the non-equilibrium sorption process can

only be expected if the transformation proceeds rapidly (Boesten, 1987). So if bentazone

had been applied in spring or summer instead of in autumn, there would have been a

larger influence of the non-equilibrium sorption process (the autumn application in the

Vredepeel experiment was exceptional: the application period of bentazone is restricted

to spring and summer).

6. Ethoprophos behaviour

6.1. Estimation of pesticide input parameters

Only JB made calculations for ethoprophos. The ethoprophos dose was 1.33 kg haÿ1

(as recommended by Boesten and van der Pas (2000), for models that do not include

volatilisation). The pesticide/soil parameters were based on the laboratory studies by

Boesten and van der Pas (1999, 2000) and initially not further calibrated. JB estimated

sorption parameters from the soil-suspension experiments and from the measurements in

the soil pore water during the incubation of ethoprophos in top soil material at 5, 15 and

258C (see Boesten and van der Pas, 1999). The different studies for ethoprophos did not

yield consistent results. Therefore, the ratio between KOM,NE and KOM,E was assumed to

be equal to that for bentazone and also the kD value was set equal to that for bentazone.

The resulting values were KOM,E � 86 dm3 kgÿ1, N � 0.87, KOM,NE � 47 dm3 kgÿ1 and

kD � 0.015 per day.

The transformation parameters recommended by Boesten and van der Pas (2000) were

used; so the half-life at 208C for the top layer was 78 days and g was 0.093 Kÿ1. The

depth-factor for the transformation rate was 1 up to 32 cm depth; it decreased to 0.42 at

50 cm depth and was kept at 0.42 below that depth. The parameter B (describing the

moisture dependency of the transformation rate) was 0.7 and the transformation stream

concentration factor was 0.5 (the default values in PESTLA).

6.2. Results of runs with uncalibrated and calibrated water ¯ow

As with bentazone, the only differences between uncalibrated and calibrated runs were

the water flow input parameters. Fig. 6 shows that uncalibrated and calibrated runs

resulted in almost identical simulations of ethoprophos persistence. The figure shows

further that the persistence of ethoprophos was simulated very well during the first 200

days of the study. Thereafter the measured decline proceeded faster than simulated (both

calibrated and uncalibrated). Surprisingly, the uncalibrated water flow parameters


resulted in a slightly closer fit than the calibrated water flow parameters. As shown by

Fig. 7, the highest simulated concentrations of ethoprophos were near the soil surface.

The decline of ethoprophos is almost entirely the result of transformation (simulated plant

uptake was only 1±2% over the whole period). In the PESTLA model, transformation in

the top layer is influenced by soil temperature and by the quotient between the current

volume fraction of liquid and the volume fraction of liquid at a matric head of 100 cm

(see Boesten and van der Linden, 1991). Differences between soil temperatures as

simulated with calibrated and uncalibrated water flow parameters were found to be

usually less than 0.18C. The quotient of the volume fractions of liquid was systematically

lower for the calibrated water flow case in the period between 200 and 300 days. This

explains the slightly slower transformation for the calibrated water flow case in that

period as shown in Fig. 6.

Fig. 7 shows that calibrating water flow resulted in concentration profiles for

ethoprophos that differed only slightly from those calculated with uncalibrated water flow

parameters. So a good description of water flow is only of limited importance for

simulating behaviour of pesticides such as ethoprophos (with moderate sorption).

Admittedly, the model test for ethoprophos does only include concentration profiles in

soil and no soil leachate concentrations. However, Boesten and van der Pas (2000)

showed that soil concentrations of ethoprophos between 30 and 120 cm depth were below

the detection limit of 0.2 mg dmÿ3 after 474 days. They found a half-life of ethoprophos

of about 600 days for the soil layer between 50 and 100 cm depth. Therefore, it is

unlikely that substantial concentrations of ethoprophos leached below 30 cm depth: the

detection limit of 0.2 mg dmÿ3 implies that less than 0.1% of the assumed dose of

1.33 kg haÿ1 was present in the 30±120 cm layer after 474 days.

Fig. 6. Comparison of measured and simulated areic mass of ethoprophos in the soil pro®le at Vredepeel as a

function of time. The points are measured averages, the bars indicate plus or minus two times the standard

deviation of the average. The solid line was simulated with uncalibrated water ¯ow and the dashed line with

calibrated water ¯ow (both by Boesten).


Fig. 7 shows that PESTLA simulated the movement into the soil profile reasonably

well after 103 days. However, after 278 and 474 days the simulated penetration into the

soil profile was deeper than measured and the concentrations were overestimated

(especially after 474 days).

The amount of ethoprophos sprayed onto the experimental field was about 3 kg haÿ1

(Boesten and van der Pas, 2000). We used as input the value of 1.3 kg haÿ1 that Boesten

and van der Pas (2000) recommend for models that ignore volatilisation. If we would

Fig. 7. Comparison of measured and simulated pro®les of ethoprophos at Vredepeel after 103, 278 and 474 days

(in parts A, B, and C, respectively). The area within the solid line segments is the range of the measured averages

plus and minus two times the standard deviation of the average. The dotted line was calculated with uncalibrated

water ¯ow and the dashed line with calibrated water ¯ow (both by Boesten).


have used the 3 kg haÿ1 as input, the simulation of ethoprophos persistence in soil would

have been poor. So PESTLA is not valid for simulation of the initial persistence of pesticides

that are sprayed onto the soil surface and that have a vapour pressure and a distribution

over the soil phases like ethoprophos (Boesten and van der Pas, (2000), estimated the

ratio between the concentrations of ethoprophos in gas and water to be in the order of 10ÿ6).

The good correspondence between measurements and simulation in the first 200 days

shown in Fig. 6, followed by the systematic deviations in the period thereafter, indicates

that there was an acceleration of the transformation rate in the field after about 200 days

due to some unknown cause. Smelt et al. (1996) showed via laboratory incubations that

accelerated transformation of ethoprophos may occur in Dutch sandy soils after repeated

application. This accelerated transformation is attributed to adaptation of soil microbial

populations. Ethoprophos had never been applied to this experimental field before

(Boesten and van der Pas, 2000), so accelerated transformation was not anticipated

(PESTLA does not consider this acceleration process and it is therefore not meaningful to

test the model for cases where this process is known to occur). The accelerated

transformation was not measured in the laboratory incubations by Boesten and van der

Pas (2000), although these lasted for more than 400 days. Microbial biomass may

decrease considerably in laboratory studies if these last longer than three months

(Anderson, 1987). So this decrease may have delayed microbial adaptation. As shown by

Fig. 7, even after 278 days the highest ethoprophos concentration was found in the top

4 cm. In combination with Fig. 6, it can be estimated that the top 4 cm contained an

ethoprophos content of about 1 mg kgÿ1 over a period of more than 200 days. It is

therefore likely that this exposure to ethoprophos was sufficient to result in adaptation

between 214 and 278 days, especially as there was a full grown wheat crop on the

experimental field in that period and soil temperatures were then usually above 158C(Boesten and van der Pas, 2000).



6.3. In¯uence of including accelerated transformation on calculated ethoprophos

penetration

The comparison of measured and calculated ethoprophos concentration profiles after

474 days in Fig. 7 suggests that the model not only overestimated the concentration level

but also the penetration into the soil. The overestimation of the penetration may be the

result of the bad simulation of the persistence between 200 and 474 days. It is meaningful

Fig. 8. Comparison of measured and simulated pro®les of ethoprophos at Vredepeel after 278 and 474 days

(parts A and B). The area within the solid line segments represents the range of the measured averages plus and

minus two times the standard deviation of the average. The line was calculated with calibrated water ¯ow and

including accelerated transformation simulated by assuming a half-life of 1 day from day 250 onwards.


to check this, because testing of the sub-model describing the partitioning over the phases

in soil (Eqs. (1)±(3)) is also relevant. Therefore, additional calculations were made in

which the half-life of ethoprophos at 208C was set arbitrarily at 1 day after 250 days, to

simulate the accelerated transformation (using calibrated water flow parameters). This

resulted in a good fit of the total amounts of ethoprophos in the soil profile after 278 and

474 days. None of the other model parameters was changed. The comparison of measured

and simulated concentration profiles in Fig. 8 shows reasonably good agreement after 278

days and excellent agreement at the end of the study (after 474 days). So after introducing

accelerated transformation (admittedly on an ad-hoc basis), the model explains the

observed penetration into the soil profile well. This supports the sub-model describing the

non-equilibrium sorption process (Eqs. (1)±(3)) and also the description of the

transformation rate with Eqs. (4)±(6): the half-life of 1 day implies that within about a

week (starting from day 250) the desorption from the non-equilibrium sorption sites

becomes the rate-limiting step in the transformation process. A calculation based on only

equilibrium sorption (via setting KOM,NE to zero), will result in calculated concentrations

that are many orders of magnitude lower than those measured after 278 and 474 days as a

result of the half-life of 1 day starting from day 250.

7. Discussion and conclusions

As described in Section 1, testing of a pesticide leaching model should preferably be

performed in three steps: firstly for water flow, then for solute transport via a tracer and

finally for pesticide behaviour. The interpretation difficulties with the bromide

concentration profile at day 474 as discussed in Section 4.2, indicate that bromide was

not a perfect tracer over the whole experimental period. The possible effect of bromide

uptake and release by plant roots cannot be distinguished from the possible effect of the

diffusion of bromide to finer soil pores outside the flow pathways. The tracer itself then

becomes a subject of the study whereas it was intended only to help with interpreting

pesticide behaviour. Release by root remnants is likely to be less significant for bentazone

because bentazone is transformed within the plants. In general the behaviour of any tracer

in plants will not be similar to pesticide behaviour in plants. So in practice tracers can

only be used without this complication in the absence of significant uptake by a crop

(autumn and winter period).

Figs. 5 and 7 show that the effect of calibrating water flow is larger for bentazone than

for ethoprophos. For bentazone, the shape of the soil concentration profiles is influenced

whereas for ethoprophos the shapes are very similar. For ethoprophos, only the

concentration level is different as a result of the difference in transformation rate as

described in Section 6.2. This difference in sensitivity to soil hydraulic properties is

probably caused by the difference in extent of sorption of the two pesticides: KOM,E, as

defined by Eq. (2), is 2 dm3 kgÿ1 for bentazone and 86 dm3 kgÿ1 for ethoprophos.

According to chromatographic transport theory (based on the convection/dispersion

equation and steady-state water flow), the average solute velocity in soil is inversely

proportional to the capacity factor [r(dXE/dcL) � y]; see Section 2 for the meaning of the

symbols and see Bolt (1979) for the theory. So by comparing the values of r(dXE/dcL)


and of y, the influence of the extent of sorption on solute movement can be compared

with the influence of soil moisture. Assuming a reference concentration cL of 1 mg dmÿ3,

the value for r(dXE/dcL) in the top 25 cm of the soil profile is about 0.15 for bentazone

and about 5 for ethoprophos. Values of the volume fraction of liquid, y, are typically in

the range from 0.1 to 0.3 (Fig. 2). So for ethoprophos r(dXE/dcL) is much larger than y.

This explains why the penetration of ethoprophos into the soil is so insensitive to the soil

hydraulic properties.

For both pesticides, there were problems with describing the transformation rate,

whereas the description of sorption yielded satisfactory results (although it was difficult

to get consistent results for the sorption kinetics of ethoprophos in the laboratory). So the

sorption sub-model tends to be more robust than the sub-model for the transformation

rate. Both for bentazone and for ethoprophos differences between the microbial

population of the soil in the laboratory incubations and that in the field may have been

responsible for the observed discrepancies in transformation rate.

After correcting the dose for the initial loss by volatilisation, PESTLA could simulate

the persistence of ethoprophos in the top 15 cm well during the first 200 days as shown in

Fig. 6. Leistra and Smelt (1981) tested a model similar to PESTLA using ethoprophos

that was incorporated into the top 10 cm of three soils and found a similar

correspondence between calculated and measured persistence over a period of 180 days.

They did not need to correct for an initial volatilisation loss because of the incorporation

into the soil. The model concepts for describing the transformation rate in the top layer in

PESTLA are based on the models developed by Walker (1974) and Walker and Barnes

(1981). These models have been tested extensively for persistence of herbicides in the top

15 cm layer (in total some 100 pesticide±soil combinations; e.g. Walker, 1976; Poku and

Zimdahl, 1980; Walker and Zimdahl, 1981; Nicholls et al., 1982; Walker and Brown,

1983; Walker et al., 1983). These tests showed that there is roughly a probability of 50%

for obtaining good correspondence between measurements and simulations (similar to the

first 200 days in Fig. 6). If there were deviations, nearly always the decline in the field

was faster than expected by the model. So the results obtained for ethoprophos in the first

200 days correspond well with literature experience.

Considering all results from this field study, there is no reason to reject the model

concepts on which PESTLA is based for sandy soils similar to this field soil. BG obtained

good agreement for bentazone. JB did not, but this may have been attributable (as

suggested in Section 5.2) to the microbial activity being comparatively low at the

sampling time of the soil for the incubation study in the laboratory. Variation in microbial

activity over the year seems no reason to reject the model concept for the transformation

rate in PESTLA. As described before, the differences found by JB for ethoprophos are

probably the result of accelerated transformation. PESTLA does not include this

phenomenon so this discrepancy is outside the range of validity. It will be difficult to

develop models which can predict when accelerated degradation will occur.

Implicitly the experimental set-up plays an important role in model tests because the

experimental procedures should be appropriate for a good quantification of the model

parameters. For example, if mixing and sieving of the soil before starting a laboratory

incubation study, change its degradation capability, the resulting input parameters for the

transformation rate will not be valid for the corresponding field situation. A similar


example is the possible effect of variation in microbial activity over the year as mentioned

in the preceding paragraph. Bad results of a model test are then neither attributable to

the model concepts nor to the experience of the model user but are caused by the

experimental procedures. This problem has to be overcome either by improving

experimental procedures or by estimating the parameters from independent field studies.

Pesticide leaching models play an important role in pesticide registration procedures at

the EU level (FOCUS Regulatory Modelling Workgroup, 1995). In regulatory decisions

that are based on model calculations, the validation status of the model needs to be taken

into account. In this context the validation status is considered to be a model property

which may be derived from a range of model tests. Testing of an existing model proceeds

as follows: firstly estimate all input parameters, secondly obtain a numerical solution that

is accurate enough and finally compare the calculated with the measured field behaviour.

As described before, the testing should be performed preferably stepwise for the sub-

models for water flow, solute transport and pesticide behaviour. In this line of thought,

models are tested via a procedure with a reasonably reproducible outcome (the traditional

paradigm). However, this study suggests that the expert judgement of the modeller (so a

human factor) in a limited part of the testing process (i.e. the estimation of input

parameters for the pesticide transformation rate) has such a large influence that the

reproducibility of the outcome of models tests is no longer guaranteed. This conclusion is

supported by the large variability in pesticide input parameters derived by different

modeller-model combinations from the same laboratory studies (Boesten, 2000).

Rejection of the reproducibility paradigm is not acceptable because then modelling

pesticide leaching would be considered more art than science. Moreover, the validation

status would be no definable property of a model (not only the model but also the

modeller becomes subject of the test). So we need to find ways to restore the

reproducibility of model tests. The most stringent solution would be to require that the

manual of the model prescribes exactly how all input parameters need to be measured or

estimated and that the results of laboratory measurements on transformation rate and

sorption are processed by the model itself via separate algorithms (thus excluding the

expert judgement). A less stringent and perhaps more practical solution is to improve the

guidance in the model manual for estimating these input parameters to such an extent that

ring tests with different modellers produce reproducible results.

Acknowledgements

BG thanks Sabine Beulke (SSLRC) and Norbert Vormbrock (BASF AG) for support

with fitting the sorption parameters using ModelMaker 2.0. JB is grateful to Frederik van

den Berg (Alterra Green World Research) for the calculations to fit the non-equilibrium

sorption parameters of the pesticides and to Minze Leistra (DLO Winand Staring Centre)

for useful critical comments on the manuscript. The work by JB was partly funded by the

European Commission (Environmental research programme, contract EV5CV-CT94-

0480). Travel costs for attending the workshops were funded by COST Action 66

`̀ Pesticides in the soil environment'' organised by DG XII of the Commission of the

European Union.


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