Available online at www.sciencedirect.com

Journal of Contaminant Hydrology 94 (2007) 261 – 276
www.elsevier.com/locate/jconhyd

Evaluating equilibrium and non-equilibrium transport of bromide andisoproturon in disturbed and undisturbed soil columns
S. Dousset a,⁎, M. Thevenot b , V. Pot c , J. Šimunek d , F. Andreux ba

UMR 5561-Biogéosciences, UFR Sciences Terre and Environnement, Université de Bourgogne, 6 Bd Gabriel, 21000 Dijon, Franceb
UMR 1229-Microbiologie et Géochimie des Sols, UFR Sciences Terre and Environnement, Université de Bourgogne,
6 boulevard Gabriel, 21 000 Dijon, Francec
UMR INRA-INA-PG-Unité Environnement et Grandes Cultures-BP 01, 78850 Thiverval-Grignon, FrancedDepartment of Environmental Sciences, University of California, Riverside, California, USA
Received 31 July 2006; received in revised form 23 January 2007; accepted 1 July 2007
Available online 17 July 2007

Abstract
In this study, displacement experiments of isoproturon were conducted in disturbed and undisturbed columns of a silty clay
loam soil under similar rainfall intensities. Solute transport occurred under saturated conditions in the undisturbed soil and underunsaturated conditions in the sieved soil because of a greater bulk density of the compacted undisturbed soil compared to the sieved
soil. The objective of this work was to determine transport characteristics of isoproturon relative to bromide tracer. Triplicate
column experiments were performed with sieved (structure partially destroyed to simulate conventional tillage) and undisturbed(structure preserved) soils. Bromide experimental breakthrough curves were analyzed using convective–dispersive and dualpermeability (DP) models (HYDRUS-1D). Isoproturon breakthrough curves (BTCs) were analyzed using the DP model thatconsidered either chemical equilibrium or non-equilibrium transport. The DP model described the bromide elution curves of thesieved soil columns well, whereas it overestimated the tailing of the bromide BTCs of the undisturbed soil columns. A higher
degree of physical non-equilibrium was found in the undisturbed soil, where 56% of total water was contained in the slow-flow
matrix, compared to 26% in the sieved soil. Isoproturon BTCs were best described in both sieved and undisturbed soil columns
using the DP model combined with the chemical non-equilibrium. Higher degradation rates were obtained in the transport
experiments than in batch studies, for both soils. This was likely caused by hysteresis in sorption of isoproturon. However, it cannot
be ruled out that higher degradation rates were due, at least in part, to the adopted first-order model. Results showed that for similar
rainfall intensity, physical and chemical non-equilibrium were greater in the saturated undisturbed soil than in the unsaturated
sieved soil. Results also suggested faster transport of isoproturon in the undisturbed soil due to higher preferential flow and lower
fraction of equilibrium sorption sites.
© 2007 Elsevier B.V. All rights reserved.
Keywords: Bromide; Isoproturon; Breakthrough curves; Modeling; HYDRUS-1D

1. Introduction⁎ Corresponding author. Université de Bourgogne, UFR Sciences
Terre and Environnement, 6 boulevard Gabriel, 21 000 Dijon, France.
Tel.: +33 3 80 39 68 88; fax: +33 3 80 39 63 87.
E-mail address: Sylvie.Dousset@u-bourgogne.fr (S. Dousset).
0169-7722/$ - see front matter © 2007 Elsevier B.V. All rights reserved.
doi:10.1016/j.jconhyd.2007.07.002

Isoproturon is one of the most widely used herbicides
in France. It is used to control weeds in cereal crops andis one of the most frequently detected herbicides insurface and ground waters (IFEN, 2006). This herbicide

262

S. Dousset et al. / Journal of Contaminant Hydrology 94 (2007) 261–276

was measured in concentrations higher than 0.1 μg L− 1,
which is the European Community Council limit forwater consumption (ECC, 1998), in numerous natural
waters around Europe (House et al., 1997; Garmouma
et al., 1998; Spliid and Koppen, 1998). Isoproturon istherefore one of the priority substances that are monitored in European natural waters (OJEC, 2001).
Numerous studies have provided evidence that preferential flow processes are the main mechanisms ofisoproturon leaching in drained heavy clay soils (Haria
et al., 1994; Johnson et al., 1994; Brown et al., 1995;
Heppel et al., 1999). Biopores (worm holes) and mechanical pores (shrinkage cracks, and cracks resulting
from ploughing) were identified as main vertical preferential flow paths (Harris et al., 1994). Preferential transport of isoproturon through earthworm burrows that bypass the soil matrix was shown at the field scale in lower
clay content soils by Zehe and Flühler (2001). Theirstudy emphasized the role of deep penetrating macropores interconnected with the soil surface for the occurrence of preferential flow events.
A better understanding of mechanisms controlling
pesticide behavior in macroporous structured soils with
by-pass flow thus remains a current issue. Conservative
tracers such as bromide, chloride and dyes are traditionally used to determine the main physical transport
processes in soils and to visualize flow pathways in field
and/or laboratory studies (e.g., Seyfried and Rao, 1986;
Andreini and Steenhuis, 1990; Flury and Flühler, 1994;
Zehe and Flühler, 2001). A comparison of water flow
and solute transport in sieved and undisturbed soil columns could help to better identify mechanisms affecting
the transport of solutes. In particular, the importanceof physical non-equilibrium transport stemming fromphysical heterogeneities (macropores) in structured soils
could be identified. The accessibility of pesticide molecules to reactive solid surfaces in undisturbed soils, ascompared to sieved soils, could also be assessed. Somestudies that compared transport in undisturbed anddisturbed soil columns suggest that Cl− (Cassel et al.,
1974; Starret et al., 1996) and atrazine (Zsolnay, 1991)
move faster in undisturbed than in sieved soils. On theother hand, Veeh et al. (1994) showed that the transportof Br− and chlorsulfuron is similar through undisturbed
or sieved soil columns. Sadeghi et al. (2000) found afaster transport of atrazine in either the undisturbed or
sieved soils depending upon the soil's physico-chemical
properties. Finally, Griessbach et al. (1998) showed thatthe leaching of a silicone-polyether was lower in undisturbed than in sieved soil columns. These widely
contrasting results have been reported in the literature,even for conditions where the soil texture and structure

were similar. In most studies, structured soil columns
were prepared by pushing a PVC or metallic tube into
the soil manually or with a hydraulic jack. Possible soil
compaction resulting from the use of this method cannot
be ignored and may partly explain these different observations (Dousset et al., 1995).
We performed bromide and isoproturon displacement
experiments in both disturbed and undisturbed soil columns that were sampled from a silty clay loam soil in an
intensively cultivated agricultural area (Citeaux, Côted'Or, France). In addition, the dye tracer, Brilliant
Blue FCF, was used to visualize and quantify potential
macropore pathways used by water flow in undisturbed
soil columns. Although several authors suggested that due
to its charge Brilliant Blue FCF may sorb somewhat morestrongly than expected to the clay (Perillo et al., 1998;
Kasteel et al., 2002; Nobles et al., 2004) and organiccarbon (Ketelsen and Meyer-Windel, 1999) fractions of
the soil, Brilliant Blue FCF remains to be one of the best
dye tracers available today for identifying water flow
pathways (German-Heins and Flury, 2000).
Our objectives were (i) to assess the importance ofpreferential flow on isoproturon leaching in the silty clay
loam soil of Citeaux and (ii) to evaluate whether a comparison of bromide and isoproturon leaching in disturbed
and undisturbed soil columns could help identify different processes occurring during transport. Displacement experiments were analyzed using multi-processsolute transport models that describe physical equilibrium transport using the convection–dispersion equation(CDE), and physical non-equilibrium transport using thedual-permeability (DP) model that also considers chemical equilibrium (instantaneous sorption) or non-equilibrium (kinetic sorption) processes. This work contributes
to our understanding of non-equilibrium reactive solutetransport processes in undisturbed and sieved laboratory
soil columns and the use of numerical models accounting
simultaneously for both physical and chemical nonequilibrium processes.
2. Materials and methods
2.1. Soils and column sampling
A silty clay loam soil (gleyic luvisol, FAO, 1998) was
sampled from a fallow area of the INRA experimentalsite at Citeaux (Côte d'Or, France). Some young
alfalfa plants (Medicago sativa) were growing on thefallow soil. Three undisturbed soil column monoliths(16-cm i.d., 20-cm long) were prepared by carefully
excavating the surrounding soil using a shovel. A 25 cmlong polyvinyl chloride (PVC) pipe with an internal

S. Dousset et al. / Journal of Contaminant Hydrology 94 (2007) 261–276

diameter of 20 cm was then placed over the soil cylinder.
A minimal-expansion foam was injected into the gap
between the soil column and the PVC pipe to fill empty
space and thus reduce possible sidewall flow. The foam
was then allowed to harden overnight before the columns
were removed by digging under the PVC pipe. A nylon
mesh was placed at the bottom of the columns to retain
the soil base. Three homogenized soil columns, werethen prepared with the same soil collected from the 0–
20 cm horizon. The soil was first air dried and thensieved through 5-mm and, subsequently, 1-mm sieves.
The soil aggregates with equivalent diameters between 1
and 5 mm were packed in a 15-cm i.d. and 20-cm long
PVC pipe. The 0–1 mm diameter aggregates were removed to avoid possible clogging of the soil columns.
Soil analysis has shown that the physico-chemical properties of the 0–1 mm and the 1–5 mm aggregates weresimilar (Table 1). The 0–1 mm fraction represents 17%of the 0–5 mm soil fraction mass. Note that soil aggregates were not dispersed prior to sieving and aggregatedstructural properties of the soil were thus partiallypreserved.
Particle size distribution of the soil was analyzed bysieving and sedimentation after its dispersion in sodium
hexametaphosphate (AFNOR X 31-107). The organic C
concentration was determined by dry combustion (ISO10694). The CaCO3 concentration and pHH2O were
measured by following the ISO 10693 and ISO 10390
standards, respectively. All analyses were carried out at
the Soil Analysis Laboratory INRA-Arras, France.
2.2. Chemicals
Analytical grade reagents were used for the experiments. Isoproturon (3-(4-isopropylphenyl)-1,1-dimethylurea) was purchased from Dr. Ehrenstorfer (Augsburg,
Table 1Main characteristics of the sieved and undisturbed soil (all data except
pH values are in g kg− 1)
Silt
Clay
Organic CaCO3
pH SandH2O (50–2000 μm) (2–50 μm) (b2 μm) carbon
Undisturbed soil depth
0–5 cm
8.0 164
5–10 cm 8.0 163
10–15 cm 8.0 173
15–20 cm 8.0 165

492
486
476
488

343
349
349
347

12
10
11
11

10.6
12.6
12.3
12.6

Sieved soil (1–5 mm fraction)
0–20 cm 8.0 181

459

361

11

16.1

Sieved soil (0–1 mm fraction)
0–20 cm 8.0 172

474

354

11

15.1

263

Germany). Its water solubility is 65 mg L− 1 at 22 °C(Tomlin, 1997). Its half-life varies from 6.5 to 34 days insurface soils (Pieuchot et al., 1996; Walker et al., 2001).
Its normalized adsorption coefficient (Koc) varies from43 to 225 L kg− 1 in surface soil (0–30 cm) (Benoit et al.,
1999; Lennartz, 1999; Spark and Swift, 2002). Large
variations in Koc values may be due to (i) different
experimental conditions among reported studies, (ii)differences in the nature of the soil organic carbon in theanalyzed soils, and (iii) isoproturon adsorption to theclay fraction (Pantani et al., 1997). Bromide was used in
the form of KBr. Depending on pH, the Brilliant BlueFCF dye tracer is either neutral or dissociates into a
mono- or bivalent anions (pKa = 5.83 and 6.58). The
tracer is thus expected to be anionic in our soil with pH
value of 8.
2.3. Soil column setup for displacement experiments
All soil columns were brought back to the laboratory
held at a constant temperature of 20 °C and placed on a
support base. The bottom of each column rested on a
PVC plate perforated with 2-mm diameter holes. A glass
fiber filter was placed on the soil surface to ensure
homogeneous distribution of water over the soil surface.
Distilled water was applied over 12 h to the top of eachsieved and undisturbed soil column at a constant rate of
4 mL min− 1 (1.3 cm h− 1) using a peristaltic pump
(Ismatec MP 25) until steady-state flow was achieved.
An influent aqueous solution (0.25% CH3OH) with
20 mg L− 1 of bromide and 3.5 mg L− 1 of isoproturon
was then applied at the same flow rate over 48 h, followed by an influent distilled water solution applied for
48 h to evaluate also the desorption process. Each undisturbed soil column was then leached with one porevolume of the dye at a concentration of 5 g L− 1. The soilcores were subsequently allowed to drain for 72 h,
extracted from the PVC pipe, and then cut lengthwise
into 2-cm thick soil slices with a knife. Digitized imagesof each slice were taken using the SONY DKC 5000
triCCD camera and treated using OPTIMAS 6.5 software in order to quantify the area dyed with the Brilliant
Blue FCF. The dye coverage is a measure of the volumetric proportion of preferential flow paths, which canconsequently be used to evaluate the mobile zone.
No degradation of isoproturon was detected in theinfluent solution during the injections at 0, 20 and 48 h.
Effluents from the bottom of each soil column werecollected every hour in glass vials using a Foxy 200
fraction collector. Leachate volumes were determined
gravimetrically. The bromide and isoproturon breakthrough curves (BTCs) were constructed using the

264

S. Dousset et al. / Journal of Contaminant Hydrology 94 (2007) 261–276

concentrations measured in the leachates. Recoveries ofbromide and isoproturon were calculated from the
BTCs.
The porosity, w (cm3 cm− 3) of the soil was calculated
as follows (Danielson and Sutherland, 1986):
w ¼ ð1  qb =qp Þð1Þ

where ρp is the particle density (g cm− 3) and ρb is thebulk density (g cm− 3). The bulk density of the undisturbed soil was obtained by averaging measured bulk
densities of 20 soil core samples (100 cm3 volume)
collected in the field. The bulk density of the sieved soil
was determined on small laboratory soil columns(6.8 cm diameter and 6 cm long). Mean bulk densities
were 1.60 ± 0.08 g cm− 3 and 1.07 ± 0.02 g cm− 3 for theundisturbed and sieved soils, respectively. This large
difference in bulk densities may be explained in part by
the removal of the 0–1 mm aggregates from the sieved
soil and by the compaction of the undisturbed soil by the
agricultural machinery, as also previously reported by
Renault et al. (1998) for the same soil. Assuming aparticle density of 2.65 g cm− 3, the porosity was equal
to 0.3956 ± 0.0297 cm3 cm− 3 and 0.5957 ± 0.0066 cm3
cm− 3 for the undisturbed and sieved soils, respectively.
The gravimetric soil water content was measured on thesame small sieved soil columns and on additional small
undisturbed soil columns (6.8 cm diameter and 6 cmlong) after 12 h of water irrigation at 1.3 cm h− 1. The
volumetric water contents, θ, were 0.392 ± 0.030 cm3
cm− 3 and 0.447 ± 0.005 cm3 cm− 3 for the undisturbed
and sieved soil columns, respectively. Volumes of waterin the column, Vp (=θπR2L, where R is the inner diameter of the soil columns (cm) and L is the length of thesoil column (cm)), were 1576.3 cm3 and 1579.8 cm3 forthe undisturbed and sieved soil columns, respectively.
The potential anion exclusion volume for bromide in
the soil columns was calculated using an average valueof the clay surface area of 1.5 × 105 m2 kg− 1 and an
average double layer thickness of 0.5 nm as reported by
Veeh et al. (1994), resulting in an exclusion volume of
0.0375 cm3 g− 1 of clay. The anion exclusion volume,
Vex, of Citeaux soil columns was estimated to be 3.23%
and 5.35% of the pore volume for the sieved and undisturbed soils, respectively.
2.4. Chemical analysis
The column effluent samples were filtered through0.45 μm cellulose nitrate membranes (Sartorius) andanalyzed using a Waters HPLC equipped with a Diode
Array Detector and a 25 cm × 4.6 mm C18-column

packed with Kromasil 5 μm for isoproturon, and a
15 cm × 4.6 mm Waters IC Pack Anion HC for Br−. The
mobile phase was acetonitrile–water at 60/40 v/v for
isoproturon and a 30 mM KH2PO4 solution with 20%
acetonitrile acidified to pH 2.8 for Br− (Bowman, 1984).
The flow rate of the mobile phase was 1 mL min− 1 forisoproturon analysis, and 2 mL min− 1 for Br− analysis.
Detection was performed at 242 nm for isoproturon and
205 nm for Br−. Minimum detectable concentrations
were 0.02 mg L− 1 for isoproturon and 0.1 mg L− 1 forBr−.
2.5. Batch adsorption and degradation coefficientsmeasurement
For the batch adsorption experiments, each sample
consisted of 2 g of soil mixed with 10 mL isoproturon
solution (soil/solution ratio: 1/5, w/v) in a 50 mL
polycarbonate centrifuge tube. Herbicide concentrations
ranged from 0.56 mg L− 1 to 11.47 mg L− 1. The tubes
were agitated on a rotary shaker for 36 h at 20 °C toachieve equilibrium. The suspensions were then centrifuged for 20 min at 4000 g (Beckman-Avanti J-25
centrifuge maintained at 20 ± 1 °C). Blanks without soil,
otherwise prepared in the same way, showed no sorption
to the polycarbonate tubes. The amount of adsorbed
herbicide, x (mg), per mass of soil, m (kg), at equilibrium
was determined by the difference between the initial andequilibrium herbicide concentrations in the solution, Ceq(mg L− 1). Sorption isotherms were obtained by plottingx/m against Ceq and described using the Freundlich
equation (e.g., Fouqué-Brouard and Fournier, 1996;
Benoit et al., 1999; Nemeth-Konda et al., 2002):nx=m ¼ Kf Ceq

ð2Þ

where Kf (mg1−n Ln kg− 1) and n (−) are empirical
sorption coefficients. Three replicates were conducted
for each sample.
For the degradation experiments, 50-g portions of the
1–5 mm sieved soil were put in crystallizers (65 mm
diameter). The soil moisture was brought to 42% with a
3.2 mg L− 1 solution of isoproturon in water + methanol(99.75 + 0.25 by volume), quite similar to the maximum
concentration in the soil columns. Each glass vessel wasplaced in a room at a constant temperature of 20 °C ±1 °C for 16 days. Triplicate soil samples were incubatedfor 4, 10 and 16 days. The remaining isoproturon was
extracted from the soil samples (50 g) with 100 mL of
methanol–water solution (80/20; v/v) by three 12-hourrotary agitations. The slurries were then centrifuged at
8000 g for 10 min. The three extractions were firstS. Dousset et al. / Journal of Contaminant Hydrology 94 (2007) 261–276

combined, then evaporated to dryness with a rotovapor,and finally dissolved in methanol (5 mL) for analysis by
HPLC. Isoproturon degradation was usually describedusing a first-order model (Walker et al., 1999):
C ¼ C0 expðktÞ

ð3Þ

where C is the soil concentration of the parent molecule
at time t (d), C0 is the initial concentration at time 0, andk is the rate constant (d− 1).
2.6. Transport models
The modified one-dimensional transport model
HYDRUS-1D (Šimůnek et al., 1998, 2003; Pot et al.,2005) was used to describe the transport of bromide andisoproturon in the soil columns. The dual-permeability(DP) model (Gerke and van Genuchten, 1993; Šimůnek
et al., 2003) was used to describe the physical nonequilibrium transport. The liquid phase is in this modelis assumed to consist of two mobile flow regions, named
hereafter fracture and matrix regions, each with its own
flow and transport properties. The total water content isdefined as θ = wfθf + (1 − wf)θma, where θf and θma arelocal volumetric water contents in the fracture andmatrix regions, respectively. The water flux density,q (cm h− 1), is similarly defined as q = wfqf + (1 − wf)qma,
where qf and qma are the water flux densities in thefracture and matrix regions, respectively. In both relations, wf is the volumetric weighting factor (−) expressing the ratio of the fracture domain to the total soilvolume. The total contribution of the fracture and matrix
domain to the overall water content are calculated as:c
θfc = wfθf and θma= (1 − wf)θma, respectively.
Assuming that degradation is active only in the liquid
phase, the transport equations for one-dimensional
steady-state water flow conditions for the fracture (4)and matrix (5) regions are written as:

ð4Þ
ACf
ASf
A2 Cf
ACf
þ qb
¼ hf Df
 qf
At
At
Az2
Az
1  wfðCf  Cma Þ  hf ll Cf
 aswf

tion of the solid phase in the matrix (fracture) region (mgg− 1), Dma(f) is the dispersion coefficient in the matrix(fracture) region (cm2 h− 1), μl is the coefficient ofdegradation in the liquid phase (h− 1), and αs is the firstorder mass transfer rate coefficient between the tworegions (h− 1). Following Pot et al. (2005), the physicaland chemical non-equilibrium transport model was
described by combining the dual-permeability modeland the two-site sorption model (Selim et al., 1977; van
Genuchten and Wagenet, 1989). In this latter model, thesorption is assumed to be instantaneous on one fraction of
the sorption sites (named hereafter type-1 sites) and to be atime-dependent, first-order kinetic process on the remaining fraction of the sorption sites (named hereafter type-2
sites). The governing equations for the matrix (6) andfracture (7) regions are written as:
hma

hf

ACma
ASma
A2 CmaACmaþ qb fma¼ hma Dma
 qma
At
At
Az2
Az
þ as ðCf  Cma Þ  hma ll Cman qb ak ð1  fma ÞKf Cma
 Sk;ma
ð6Þ

ACf
ASf
A2 Cf
ACf
þ q b ff
¼ hf Df
 qf
At
At
Az2
Az
1  wfðCf  Cma Þ  hf ll Cf
 as
wf


 qb ak ð1  ff ÞKf Cfn  Sk;fð7Þwhere Sma(f) are the adsorbed concentrations on the type-1
sites in the matrix (fracture) domain (mg g− 1), Sk,ma(f) are
the adsorbed concentrations on the type-2 sites in
the matrix (fracture) domain (mg g− 1), fma(f) are thefractions of the type-1 sorption sites in the matrix(fracture) domain (−). In this work, we assumed that theequilibrium sorption process was described using theFreundlich isotherm.
2.7. Parameter estimation

ACma
ASma
A2 Cma
ACma
hma
þ qb
¼ hma Dma
 qma
2
At
At
Az
Az
þ as ðCf  Cma Þ  hma ll Cma

hf

265

ð5Þ

where t is time (h), z is the vertical coordinate (cm), Cma(f)is the solute concentration of the liquid phase in the matrix(fracture) region (mg L− 1), Sma(f) is the solute concentra-

The inverse problem was solved using the non-linear
least-squares inversion method proposed by Marquardt(1963). Physical transport processes were first determined by analyzing the bromide BTCs. Then the chemical transport processes for isoproturon were determinedby inverting the herbicide BTCs, using the physicaltransport parameters estimated for the bromide transport. For all inversions, the soil water content, θ, and theflux density, q, were fixed to measured values.
For bromide modeling, the molecular diffusion coefficient was set to 0.066 cm2 h− 1 (Weast, 1985). Notethat Parsons (1959) gives a value of similar order of

266

S. Dousset et al. / Journal of Contaminant Hydrology 94 (2007) 261–276

magnitude of 0.075 cm2 h− 1. Estimated transport parameters were qma, λma, λf, wf and αs, while parameters θ⁎f ,θma⁎, qf = (q − (1 − wf)qma) / wf, and the pore water velocities in the fracture (vf = qf / θf) and matrix (vma = qma / θma)domains were calculated from the fitted parameters.
Finally, anion exclusion (for bromide) was addressed by
fixing the retardation factor, R, to 0.97 and 0.95 for thesieved and undisturbed soil columns, respectively, following Veeh et al. (1994).
For isoproturon modeling, we assumed that the herbicide underwent the same physical transport processes
as bromide, so that dispersivities (λma and λf), matrix
and fracture contributions to the overall water contentc(θma
and θfc), a volumetric ratio of the fracture domain(wf), and pore water velocities (vma and vf) were fixed tovalues estimated for the bromide transport. The firstorder mass transfer rate coefficient, αs, was fixed to thebromide value corrected for the molecular diffusion
coefficient of pesticides (taken as 0.0179 cm2 h− 1, Juryet al., 1983). Sorption related parameters, Kf and n, andthe degradation rate, μl, were either fixed to the batchvalues or fitted. Additional parameters fma, ff, and αkwere estimated when considering the chemical nonequilibrium transport model.
3. Results and discussion
3.1. Batch adsorption and degradation experiments
The adsorption isotherm was well described using
the Freundlich equation:
0:88 2x=m ¼ 1:06 Ceqðr ¼ 0:97Þ:

ð8Þ

The Freundlich adsorption coefficient (Kd = 1.06) isin agreement with Kf values published in the literaturefor batch conditions, which vary between 0.52 and1.3 mg1−n Ln kg− 1 (Fouqué-Brouard and Fournier,
1996; Benoit et al., 1999; Nemeth-Konda et al., 2002),
with n values ranging from 0.51 to 0.77.
The incubation experiment on a soil treated with isoproturon showed that the pesticide degradation was
negligible over 4 days; the isoproturon recovery was
93.3 ± 1.3% after 4 days of incubation, compared to 96.2 ±
8.4% at t0. The degradation of isoproturon was welldescribed by a first-order kinetic equation:
x=m ¼ 1:41 expð0:055tÞðr 2 ¼ 0:93Þ

ð9Þ

that resulted in the isoproturon half-life of 12.6 days. This
is in agreement with half-lives between 6.4 and 34 days
reported by Pieuchot et al. (1996) and Walker et al.
(2001), and 19 days measured by Walker et al. (1999).

3.2. Displacement column experiments
3.2.1. Bromide breakthrough curves
Solute breakthrough curves are plotted using therelative concentration measured in the leachate versus
the number of pore volumes eluted, defined as V/V0,
where V is the flux-averaged volume of solute eluted(cm3) and V0 is the volume of water in the column (cm3).
Prior to interpreting the results of the displacement
experiments, we stress here that at the same rainfall
intensity the displacement experiments occurred undersaturated conditions for the undisturbed soil columns
and under unsaturated conditions for the sieved soilcolumns. Thus contrary to the sieved soil, the macropores in the undisturbed soil column were water filled
and involved in solute transport. The sieved columns
were repacked with the soil which was sieved without
first destroying the soil aggregates. Since the particles
that fell through the 1-mm sieve were removed before
packing the column, and only larger particles and aggregates were used to pack the column, the physicalproperties of disturbed and undisturbed columns werequite different. The disturbed soil columns thus did nothave any macro-structural features, such as macropores,
but retained micro-structural features, such as aggregates. The removal of the small particle fraction led torelatively high hydraulic conductivities in the sieved soilcolumns, while still allowing for non-equilibrium flow
due to the presence of aggregates.
Fig. 1 shows that bromide breakthrough curves forboth the sieved (Fig. 1a) and undisturbed (Fig. 1b) soilcolumns were shifted to the left relative to the theoreticalcurve predicted by the equilibrium transport model. This
early arrival of bromide suggests the existence of preferential flow. The shape of bromide breakthrough curves
was similar for the three sieved columns (Fig. 1a). While
the BTCs shape was also similar for columns 1 and 2
in the undisturbed soil, it was different for column 3(Fig. 1b). This difference could be explained by thespatial heterogeneity of the soil structure at the field
scale. The average bromide recoveries were 97.5 ± 0.2%
for the sieved soil and 90.8 ± 0.6% for the undisturbed
soil. The latter value is similar to an average bromide
recovery of 87% reported by Lennartz and Kamra(1998) in undisturbed loamy sand. Bromide concentrations in the column effluent did not reach inflow concentrations even after leaching of 2 pore volumes, but
tended to increase over the whole application period
without reaching inflow concentrations. Such tailing in
the BTC of a tracer is an indication of physical-nonequilibrium. In contrast to the sieved soil, bromide was
detected in the first effluent of the undisturbed soil,

S. Dousset et al. / Journal of Contaminant Hydrology 94 (2007) 261–276

267

Fig. 1. Measured BTCs for bromide (+) and isoproturon (○) in the sieved (a) and undisturbed (b) soil columns.

indicating significant by-pass flow. The number of porevolumes eluted when the outflow concentration reachedhalf of the input concentration was higher for the sieved
soil (0.59 ± 0.03 pore volume) than for the undisturbed
soil (0.47 ± 0.13 pore volume), indicating slower
transport in the sieved soil. These observed differencesemphasized the role of the soil structure and water
saturation. Continuous macropores allowing for shortcircuiting (recall that Br concentrations were found evenin the first effluent samples) and rapid flow were likely

present in the undisturbed soil columns. The highbiological activity due to earthworms and alfalfa rootsthat resulted in the presence of abundant macropores can
explain the significant by-pass flow through theundisturbed soil columns. Indeed, the preferential flow
pathways were highlighted using the brilliant blue dye,in soil slices from the undisturbed columns (Fig. 2). The
dye was found mainly along the biopores, as similarly
observed by Jorgensen et al. (2004). The bromide loss
(10%) in the undisturbed soil, compared to the sieved

268

S. Dousset et al. / Journal of Contaminant Hydrology 94 (2007) 261–276

Fig. 2. Examples of vertical slices of the undisturbed soil in columns 1, 2 and 3 showing pathways stained by the brilliant blue dye.

soil, may be explained by bromide ‘trapped’ in surfaceconnected earthworm macropores that do not connect tothe bottom of the undisturbed soil column.
The dual-permeability model (DP) was used to analyze the bromide BTCs. Note that the equilibriumtransport model (CDE) failed to describe the bromidetransport. The equilibrium transport model did not reproduce tailing for the sieved and undisturbed soil columns and provided unrealistically large dispersivities
for the undisturbed soil columns (data not shown). The
DP model described the bromide elution curves of thesieved soil columns well, whereas it overestimated thetailing of the bromide BTCs for the undisturbed soilcolumns (Fig. 3). We also tried to fit the bromide BTCs
for the undisturbed columns with a more complex model(Pot et al., 2005), in which the liquid phase of the matrix
region is further partitioned into mobile and immobile
regions (data not shown). We could not, however, findbetter fits, although this model can in principle describe
trapped bromide in the immobile region (Köhne et al.,2006) and thus explain the low recovery rates. The DPmodel was thus also used to describe the bromidetransport in the undisturbed soil columns.
In both cases (sieved and undisturbed soil columns)
the matrix conductivities were very small, indicating thatthe water fraction in the matrix domain was quasi
stagnant. Note that, as in Pot et al. (2005), λma was fixed
to 1 cm. Average dispersivities in the fracture domain, λf,were 5.9 ± 1.1 cm and 10.9 ± 5.9 cm for the sieved andundisturbed soil columns, respectively (Table 2). Dispersivity values at the column scale are correlated withthe pore-size distribution and the magnitude of the soil
structure heterogeneity. High λ values indicate a heterogeneous pore system or long flow-path lengths (Shawet al., 2000). Relatively lower λ values were estimatedfor the fracture region of the sieved soil columns,

indicating a relatively homogeneous porous medium.
Pore-size distribution of these columns was indeed
relative homogeneous since only 1–5 mm aggregateswere used to pack the sieved soil columns. The difference in water saturation between the sieved and undisturbed soil columns could also explain thesedifferences. Preferential flow significantly increased in
the undisturbed soil columns, because biopores (mainly
due to earthworm and alfalfa roots) were active for thewater saturated conditions as indicated by patterns of thebrilliant blue (Hutchinson et al., 2003). Higher dispersivities for the undisturbed soil columns were thus
attributed to greater soil structure heterogeneity combined with a higher degree of water saturation.
Average values of wf of 0.74 ± 0.03 and 0.44 ± 0.12
suggested that 26% and 56% of the total water were
contained in the slow-flow matrix domains of the sieved
and undisturbed soil columns, respectively, indicating ahigher degree of non-equilibrium in the undisturbed
soil. Our results are in agreement with findings of van
Genuchten and Wierenga (1977), Nkedi-Kizza et al.
(1984) and Veeh et al. (1994), who showed the presenceof physical non-equilibrium transport also in sieved soilcolumns, contrary to other authors (e.g., Rao et al.,
1979; Gamerdinger et al., 1990; Beigel and Di Pietro,
1999) who could describe their data using equilibrium
models. The average value of the mass transfer rate
coefficient αs in the sieved (undisturbed) soil columns
was 0.02 ± 0.01 h− 1 (0.10 ± 0.05 h− 1), which resulted ina mean transfer time of the solute between the fracture
and matrix domains (tα, defined as 1/αs) of 50 (10)hours. The mean travel time of the solute (tt, defined asL/q) was 15 (16) hours for the sieved (undisturbed) soilcolumns. The longer transfer time of bromide (into thematrix domain) relative to its mean travel time in thecolumn explained the tailing for the sieved soil columns.

S. Dousset et al. / Journal of Contaminant Hydrology 94 (2007) 261–276

269

Fig. 3. Bromide BTCs measured and calculated for the sieved (T) and undisturbed (S) soil columns. Symbols are the experimental data and solid lines
are the fits provided by the DP transport model.

Comparable solute transfer and mean travel times were
found for the undisturbed soil columns, for which thetailing part of the BTCs was underestimated. In contact
to the sieved soil, there was sufficient time for thebromide exchange from the fracture to the matrix domain in the undisturbed soil. This could partly be ex-plained by water saturation of the undisturbed soil andthe undersaturation of the sieved soil.
The basic assumption made in interpreting the dyepatterns was that the more solution passes through agiven point the more darkly stained that point is. Thus
stained regions are interpreted as having relatively fast

270

S. Dousset et al. / Journal of Contaminant Hydrology 94 (2007) 261–276

Table 2
Predicted transport parameters (± Standard Error) for bromide using the dual-permeability model (DP) in HYDRUS-1D; ⁎ denotes fixed parameters,⁎⁎ estimated parameters and ⁎⁎⁎ parameters calculated from the estimated parametersc⁎⁎⁎θma
cm3 cm− 3θcf ⁎⁎⁎
cm3 cm− 3

wf⁎⁎
–

α⁎⁎⁎
s
h− 1

v⁎⁎⁎
ma
cm h− 1v⁎⁎⁎
f
cm h− 1

a
Q⁎⁎⁎
ma ,
–

Qf⁎⁎⁎, a
–

r2

0.129
(0.024)0.106(0.005)0.119(0.004)0.118(0.012)0.318(0.024)0.341(0.005)(0.328(0.004)0.329(0.012)0.7112(0.053)0.7621(0.011)0.7330(0.0088)0.7354(0.0255)

0.0301(0.0450)
0.0169(0.0150)
0.0115(0.0015)0.020(0.010)0.048(0.556)0.149(0.149)0.180(0.081)
0.126(0.069)4.051(1.730)3.920(0.450)4.064(0.297)4.012(0.080)0.0048(0.0048)0.0117(0.0030)
0.0159(0.0027)0.0108(0.0056)

0.9952(0.9988)
0.9883(0.2543)0.9841(0.1676)
0.9892(0.0056)

0.9988

Undisturbed soil columns, θ = 0.392 cm3 cm− 3
Column 1 1.270
1.00 5.31
0.220(0.034)(4.00)(0.044)
Column 2 1.212
1.00 17.03
0.174(0.026)(13.39) (0.058)
Column 3 1.273
1.00 10.39
0.266(0.035)(5.85)(0.013)Mean
1.251
1.00 10.91
0.220(0.036)(5.88)(0.046)0.172(0.044)0.218(0.058)0.126(0.013)0.172(0.046)0.4378(0.1125)
0.5567(0.1487)
0.3215(0.0337)0.4386(0.1176)0.1381(0.1650)
0.1096(0.1500)
0.0445(0.0300)
0.0974(0.0480)

0.051(1.415)0.170(0.156)0.171(0.347)0.131(0.069)7.335(6.778)5.419(2.127)9.740(2.818)7.498(2.165)0.0089(0.0211)0.0243(0.0321)0.0357(0.0282)
0.0230(0.0134)

0.9911(2.3410)0.9757(1.2873)
0.9643(0.7602)0.9770(0.0134)q⁎
cm h− 1

λma⁎
cm

λ⁎⁎
f
cm

Sieved soil columns, θ = 0.447 cm3 cm− 3
Column 1 1.294
1.00 7.24(0.026)(0.76)
Column 2 1.351
1.00 5.18(0.016)(0.38)
Column 3 1.353
1.00 5.33(0.017)(0.39)
Mean
1.333
1.00 5.92(0.034)(1.15)

0.99900.9992–0.99840.99900.9978–a

Qma and Qf are the relative contributions of the matrix and fracture regions to the total flux, respectively.

flow, while unstained regions as having relatively slow
flow. The volume of soil stained with the brilliant blue
was estimated to be 51.7%, 55.4% and 49.7% for undisturbed soil columns 1, 2, and 3, respectively. Dyestained areas were correlated with the ratio relating themobile water content and the total water content by
Shaw et al. (2000). Using their correlation, the ratios ofthe mobile water content to the total water content for
undisturbed soil columns 1, 2, and 3 were calculated tobe 0.46, 0.49 and 0.44, respectively. Thus, on average
54% of water may be assumed to be immobile in theundisturbed soil columns. This value was similar to theaverage value calculated from wf values estimated using
the DP model (56%, Table 2).
3.2.2. Isoproturon breakthrough curves
As for bromide, the isoproturon breakthrough curves
observed in the undisturbed soil columns had earlier
arrival times (0.2 ± 0.1 pore volume) than those observedin the sieved soil columns (0.5 ± 0.1 pore volume),
confirming the faster solute transport in the undisturbed
soil. The isoproturon BTCs were clearly asymmetric andexhibited significant tailing that indicated non-equilibrium transport processes. As in the bromide case, theshape of the isoproturon breakthrough curves was similar for the three sieved soil columns (Fig. 1a), andsimilar for columns 1 and 2 but different for column 3 inthe undisturbed soil columns (Fig. 1b). The isoproturon
average recovery rate was lower in the undisturbed soil

(79.0% ± 0.9%) than in the sieved soil (86.1% ± 2.4%),
as similarly observed for bromide. Degradation and/or
chemical non-equilibrium processes can explain lower
recoveries for isoproturon than for bromide. Since thebatch incubation experiments with the silty clay loam
soil treated with isoproturon showed that degradation
was negligible over 4 days, it can be hypothesized that
isoproturon mass balance could be better explained by
the slow diffusion of isoproturon into soil aggregateswhere it is less available for leaching and/or slow desorption (Beulke et al., 2004). In addition, the highsorption hysteresis found for isoproturon by several
authors (Fouqué-Brouard and Fournier, 1996; Benoit
et al., 1999; Boivin et al., 2005) may also explain lower
recoveries for isoproturon than for bromide.
The dual-permeability models (DP) that either consider chemical equilibrium or chemical non-equilibrium
were used to analyze the isoproturon BTCs. A first seriesof simulations was performed with the Freundlich
adsorption (Kf, n) and degradation (μ) parameters
fixed to their batch values (described in Section 3.1).
The chemical equilibrium model did not describe theisoproturon BTCs well and it particularly failed in
reproducing the early arrival (Fig. 4). The chemical nonequilibrium model provided rather good fits despite ofsystematically overestimating the adsorption and desorption tailings (Fig. 5, Table 4). In order to test both models,a second series of simulations was performed in which theFreundlich adsorption and degradation parameters wereS. Dousset et al. / Journal of Contaminant Hydrology 94 (2007) 261–276

271

Fig. 4. Isoproturon BTCs measured and calculated for the sieved (T) and undisturbed (S) soil columns. Symbols are the experimental data, dashedlines and solid lines are the fits provided by the DP model combined with the equilibrium chemical model with Kf, n and μ1 fixed to the batch values(Model I) and fitted (Model II), respectively.

optimized. Results showed that although the chemical
equilibrium model was now able to reproduce the earlyarrival of isoproturon in the sieved soil columns, it underestimated the desorption tailing (Fig. 4, Table 3). The
model could not reproduce the early solute arrival in theundisturbed soil columns, except for the third column(Fig. 4, Table 3). The chemical non-equilibrium sorption
model appeared to be the best model to describe isoproturon transport in both sieved and undisturbed soilcolumns (Fig. 5, Table 4). Comparing the estimatedtransport parameters, the chemical equilibrium model
provided smaller Kf values than the batch data (Table 3).

272

S. Dousset et al. / Journal of Contaminant Hydrology 94 (2007) 261–276

Fig. 5. Isoproturon BTCs measured and calculated for the sieved (T) and undisturbed (S) soil columns. Symbols are the experimental data, dashedlines and solid lines are the fits provided by the DP model combined with the non-equilibrium chemical model with Kf, n and μ1 fixed to the batchvalues (Model I) and fitted (Model II), respectively.

Higher Kf values, although still smaller than the batchvalue, were estimated using the chemical non-equilibrium
sorption model (Table 4). This was expected since theearly arrival of isoproturon is explained in part by the nonequilibrium chemical transport processes. Lower estimated Kf values as compared to the batch value could be

explained by the fact that adsorption could not reachequilibrium under flow conditions, contrary to batch
conditions.
The optimized degradation rate for both chemical
equilibrium and non-equilibrium models was more than
10 times higher than the batch data value. This increaseS. Dousset et al. / Journal of Contaminant Hydrology 94 (2007) 261–276
Table 3
Predicted transport parameters (± Standard Error) for isoproturon using
the dual-permeability transport model in HYDRUS-1D combined withequilibrium chemical model and fitted sorption and degradation
parameters; ⁎ denotes fixed parameters, ⁎⁎ estimated parameters and⁎⁎⁎ parameters calculated from the estimated parameters
q⁎
Kf⁎⁎
n⁎⁎
cm h− 1 L kg− 1 −

μ⁎⁎
l
h−1

⁎⁎⁎ r 2DT50
dSieved soil columns, θ = 0.447 cm3 cm− 3
Column 1 1.294
0.77
0.91850.0393(0.026) (0.02) (0.0400) (0.0016)
Column 2 1.351
0.75
0.95440.0363(0.016) (0.01) (0.0350) (0.0014)
Column 3 1.353
0.79
0.9606
0.0377(0.017) (0.01) (0.0383) (0.0015)
Mean
1.333
0.77
0.94450.0378(0.034) (0.02) (0.0223) (0.0015)

0.73(0.03)
0.80(0.03)
0.77(0.03)
0.77(0.04)

0.9942

Undisturbed soil columns, θ = 0.392 cm3 cm− 3
Column 1 1.270
0.65
1.0016
0.0584(0.034) (0.03) (0.1386) (0.0077)
Column 2 1.212
0.79
0.98170.0705(0.026) (0.02) (0.0541) (0.0046)
Column 3 1.273
0.35
0.77520.1185(0.035) (0.03) (0.1440) (0.0075)
Mean
1.251
0.60
0.91950.0825(0.036) (0.22) (0.1254) (0.0318)

0.49(0.07)
0.41(0.03)
0.24(0.02)
0.38(0.13)

0.95030.9952
0.9931–0.97490.9705–

allowed a better fit of the BTCs that were otherwise
overestimated. Similar results were found with similartransport models in Pot et al. (2005) and Köhne et al.
(2006). Since these models do not consider sorption

273

hysteresis, the degradation rate acts as a lumped parameter that encompassed both degradation and sorptionthat appears as irreversible at the time scale of thepercolation experiments. Our modeling results may
thus confirm the existence of sorption hysteresis for
isoproturon, which was also demonstrated in batch
experiments by Benoit et al. (1999) and Boivin et al.
(2005). Since the sorption hysteresis is not yet includedin HYDRUS-1D, optimized degradation constants areoften artificially increased, as also observed by Pot et al.
(2005) and Köhne et al. (2006). The effect is particularly
strong when chemical equilibrium is assumed. Altfelder
and Streck (2006) and Sabbah et al. (2005) argued thatsorption hysteresis is an artifact resulting from the use of
an inadequate sorption model. Both Sabbah et al. (2005)
and Altfelder and Streck (2006) demonstrated that thespherical diffusion model performed better than thefirst-order model when describing long-term desorption
in batch experiments. Although the application of thespherical diffusion model could possibly lead to more
realistic estimates of the degradation and sorption rate
coefficients, we are not aware of any application, in
which this model would be coupled with dual-permeability transport models.
Estimated transport parameters showed a higher
degree of non-equilibrium sorption in the undisturbed
soil than in the sieved soil. Indeed, a lower fraction ofequilibrium sorption sites in the fracture region was
found in the undisturbed soil columns (ff = 0.13 ± 0.09)

Table 4
Predicted transport parameters (± Standard Error) for isoproturon using the dual-permeability transport model in HYDRUS-1D combined with nonequilibrium chemical model (instantaneous and first-order kinetic retention) with fitted sorption and degradation parameter; ⁎ denotes fixedparameters, ⁎⁎ predicted parameters and ⁎⁎⁎ parameters calculated from the estimated parameters
q⁎
K⁎⁎
f ⁎⁎
α⁎⁎
μ⁎⁎
n⁎⁎
f⁎
DT⁎⁎⁎
r2
cm h− 1f

L kg− 1Sieved soil columns, θ = 0.447 cm3 cm− 3
Column 1
1.294
0.96(0.026)(0.02)
Column 2
1.351
0.86(0.016)(0.01)
Column 3
1.353
0.90(0.017)(0.01)
Mean
1.333
0.91
(0.034)(0.05)

ma

f

k

l

50

–

–

–

h− 1

h− 1

d

0.904
(0.015)0.950(0.012)0.947(0.018)0.934(0.026)

0.500

0.585
(0.010)0.622(0.010)0.619(0.016)0.609(0.021)0.0741(0.0053)0.1001(0.0066)
0.1072(0.0107)
0.0938(0.0174)

0.0275(0.0008)0.0273(0.0005)
0.0284(0.0008)0.0277(0.0006)

1.05(0.03)
1.06(0.02)
1.02(0.03)
1.04(0.02)

0.99800.028(0.005)0.201(0.019)0.171(0.061)
0.133(0.092)0.1339(0.0055)
0.1411(0.0081)0.0465(0.0099)
0.1072(0.0527)0.0196(0.0008)
0.0437(0.0018)
0.0510(0.0188)
0.0381(0.0164)1.47(0.06)
0.66(0.03)
0.57(0.21)
0.90(0.50)

0.9969

Undisturbed soil columns, θ = 0.392 cm3 cm− 3
Column 1
1.270
0.86
0.835
(0.034)(0.01)(0.003)
Column 2
1.212
0.89
0.802
(0.026)(0.01)(0.021)
Column 3
1.273
0.90
0.515
(0.035)(0.41)(0.057)
Mean
1.251
0.88
0.717
(0.036)(0.02)(0.176)

0.500
0.500
0.500

0.500
0.500
0.500
0.500

0.9976
0.9975–0.99640.9894–

274

S. Dousset et al. / Journal of Contaminant Hydrology 94 (2007) 261–276

than in the sieved soil columns (ff = 0.61 ± 0.02). Similar
kinetic sorption rates were found in both sets of columns(αk = 0.09 ± 0.02 h− 1 and 0.11 ± 0.05 h− 1, respectively)(Table 4). This could be explained by a higher
accessibility of sorption sites in the sieved soil due tothe disrupted soil structure as well as due to shorter timetransfer. Note that results were found to be insensitive tothe fraction of equilibrium sorption sites in the matrix
region, fma. The matrix region was a quasi stagnant
region and thus chemical equilibrium sorption was
sufficient in explaining sorption in the matrix. Attempts
to estimate fma resulted in very broad confidence intervals and thus this parameter was fixed to a prescribedvalue of 0.5 as in Pot et al. (2005). Furthermore, irreversible sorption appeared to be more important in theundisturbed soil columns (μl = 0.038 ± 0.016 h− 1) thanin the sieved soil columns (μl = 0.028 ± 0.001 h− 1).

Our laboratory column experiments carried out atsimilar rainfall intensities demonstrated larger physicaland chemical non-equilibria in the saturated undisturbed
soil columns than in the unsaturated sieved soil columns. The undisturbed soil exhibited more significant
preferential flow and lower fraction of equilibrium
sorption sites than the sieved soil, which resulted infaster transport of isoproturon through the undisturbed
soil. In addition, the undisturbed soil columns reflected
the spatial heterogeneity of the soil structure at the field
scale. Experiments carried out on undisturbed soil columns may thus be irreproducible and may vary fromcolumn to column. Further investigations concerning
the effects of the spatial heterogeneity at the field scaleon the pesticides transport are thus needed.

4. Conclusion

This work was financed by the French Ministry of
Research (Programme National de Recherche Sols et
Erosion). The authors would like to thank Françoise
Gasquez and Thérèse Choné of CNRS (Dijon, 21) for
their technical contributions. The terrestrial Sciences
Program of the Army Research Office (Terrestrial
Processes and Landscape Dynamics and Terrestrial
System Modeling and Model Integration) provided
support to Dr. Jirka Simůnek.

The physical non-equilibrium dual-permeability
model described the bromide BTCs for the three sieved
soil columns very well. This model was also found tobest approximate the bromide BTCs of the undisturbed
soil columns. HYDRUS-1D analysis showed that thetransport regime in the sieved soil with small sieved
aggregates demonstrated more physical equilibriumwith more available equilibrium sorption sites than thenatural undisturbed soil. Physical non-equilibrium in theundisturbed soil columns was attributed to the heterogeneity of the soil structure and higher water saturation.
Biopores were activated at higher saturations, as shownby both modeling and color patterns of the brilliant blue,
and acted as preferential flow paths.
The isoproturon BTCs were also well modeled by thedual-permeability two-site sorption model. The optimized chemical transfer rates were the same for the
disturbed and undisturbed soils, indicating that chemical
characteristics did not change by sieving the soil. However, a higher degree of chemical non-equilibrium wasfound in the undisturbed soil columns than in the sieved
soil columns. Optimized degradation rates were almost
ten times higher in the soil columns than in the batchstudies. This overestimation of optimized degradation
rates may have several explanations. These includea) the existence of sorption hysteresis, b) the formationof non-extractable residues of isoproturon, or c) the
inadequacy of the first-order rate sorption model ascompared to the spherical diffusion model. The
numerical model could thus be improved by includingthese processes and concepts to provide more realistic
degradation rates.

Acknowledgements

References
Altfelder, S., Streck, T., 2006. Capability and limitations of first-orderand diffusion approaches to describe long-term sorption ofchlortoluron in soil. J. Contam. Hydrol. 86, 279–298.
Andreini, M.S., Steenhuis, T.S., 1990. Preferential paths of flow underconventional and conservation tillage. Geoderma 46, 85–102.
Beigel, C., Di Pietro, L., 1999. Transport of triticonazole inhomogeneous soil columns: influence of nonequilibrium sorption.
Soil Sci. Soc. Am. J. 63, 1077–1086.
Benoit, P., Barriuso, E., Vidon, Ph., Real, B., 1999. Isoproturon
sorption and degradation in a soil from grassed buffer strip.
J. Environ. Qual. 28, 121–129.
Beulke, S., Brown, C.D., Fryer, C.J., van Beinum, W., 2004. Influenceof kinetic sorption and diffusion on pesticide movement throughaggregated soils. Chemosphere 57, 481–490.
Boivin, A., Cherrier, R., Schiavon, M., 2005. A comparison of five
pesticides adsorption and desorption processes in thirteen
contrasting field soils. Chemosphere 61, 668–676.
Bowman, R.S., 1984. Analysis of soil extracts for inorganic andorganic tracer anions via high performance liquid chromatography.
J. Chromatogr. 285, 467–477.
Brown, C.D., Hodgkinson, R.A., Rose, D.A., Syers, J.K., Wilcockson,
S.J., 1995. Movement of pesticides to surface waters from a heavy
clay soil. Pestic. Sci. 43, 131–140.
Cassel, D.K., Krueger, T.H., Shroer, F.W., Norum, E.B., 1974. Solute
movement through disturbed and undisturbed soil cores. Soil Sci.
Soc. Am. Proc. 38, 36–40.

S. Dousset et al. / Journal of Contaminant Hydrology 94 (2007) 261–276
Danielson, R.E., Sutherland, P.L., 1986. In: Klute, A. (Ed.), Methodsof Soil Analysis, Part I. Physical and Mineralogical Methods,
2nd edition. Agronomy monograph, vol. 9, pp. 443–461.
Dousset, S., Mouvet, C., Schiavon, M., 1995. Leaching of atrazine andsome of its metabolites in undisturbed field lysimeters of three soils
relation to the physico-chemical properties of three soils. Chemosphere 30 (3), 511–524.
European Community Council, 1998. Directive concerning thequality of water intended for human consumption. Official
Journal of the European Communities, 98/83 EEC L330.
Office for Official Publications of the European Communities,
Luxembourg, L, pp. 32–54.
FAO, 1998. World reference base for soil resources. ISSS-ISRIC-FAO,
FAO, Rome, Italy. World Soil Resources Reports, vol. 84. 109 pp.
Flury, M., Flühler, H., 1994. Brilliant blue FCF as a dye tracer forsolute transport studies — a toxicological overview. J. Environ.
Qual. 23, 1108–1112.
Fouqué-Brouard, C.M., Fournier, J.M., 1996. Adsorption–desorption
and leaching of phenyl-urea herbicides on soils. Talanta 43,
1793–1802.
Gamerdinger, A.P., Wagenet, R.J., van Genuchten, M.Th., 1990.
Application of two-site/ two-region models for studying simultaneous nonequilibrium transport and degradation of pesticides. Soil
Sci. Soc. Am. J. 54, 957–963.
Garmouma, M., Teil, M.J., Blanchard, M., Chevreuil, M., 1998.
Spatial and temporal variations of herbicide (triazines andphenylureas) concentrations in the catchment basin of the Marne
river (France). Sci. Total Environ. 224, 93–107.
Gerke, H.H., van Genuchten, M.Th., 1993. A dual-porosity model for
simulating the preferential movement of water and solutes instructured porous media. Water Resour. Res. 29, 305–319.
German-Heins, J., Flury, M., 2000. Sorption of Brilliant Blue FCF in
Soils as Affected by pH and Ionic Strength. Geoderma 97, 87–101.
Griessbach, E.F.C., Copin, A., Deleu, R., Dreze, P., 1998. Mobility of asilicone polyether studied by leaching experiments through disturbed
and undisturbed soil columns. Sci. Total Environ. 221, 159–169.
Haria, A.H., Johnson, A.C., Bell, J.P., Batchelor, C.H., 1994. Water
movement and isoproturon behavior in a drained heavy clay soil:
1. preferential flow processes. J. Hydrol. 163, 203–216.
Harris, G.L., Nicholls, P.H., Bailey, S.W., Howse, K.R., Mason, D.J.,
1994. Factors influencing the loss of pesticides in drainage from acracking clay soil. J. Hydrol. 159, 235–253.
Heppel, C.M., Burt, T.P., Williams, R.J., Haria, A.H., 1999. The
influence of hydrological pathways on the transport of theherbicide, isoproturon, through an underdrained clay soil. Water
Sci. Technol. 39, 77–84.
House, W.A., Leach, D., Long, J.L.A., Cranwell, P., Smith, C., Bharwaj,
L., Meharg, A., Ryland, G., Orr, D.O., Wright, J., 1997. Micro-organic
compounds in the Humber rivers. Sci. Total Environ. 194/195,
357–371.
Hutchinson, J.M., Seaman, J.C., Aburime, S.A., Radcliffe, D.E., 2003.
Chromate transport and retention in variably saturated soilcolumns. Vadose Zone J. 2, 702–714.
IFEN, 2006. Les pesticides dans les eaux. Données 2003 et 2004. Les
dossiers, vol. 5. 38 pp.
Johnson, A.C., Haria, A.H., Bhardwaj, C.L., Volkner, C., Batchelor,
C.H., Walker, A., 1994. Water movement and isoproturon behavior in a drained heavy clay soil: 2. persistence and transport.
J. Hydrol. 163, 217–231.
Jorgensen, P.R., Hestrup, T., Urup, J., Seifert, D., 2004. Modeling of
non-reactive solute transport in fractured clayey till during variableflow rate and time. J. Contam. Hydrol. 68, 193–216.

275

Jury, W.A., Spencer, W.F., Framer, W.J., 1983. Behavior assessment
model for trace organics in soil: I. model description. J. Environ.
Qual. 12, 558–564.
Kasteel, R., Vogel, H.J., Roth, K., 2002. Effect of non-linear
adsorption on the transport behaviour of brilliant blue in a fieldsoil. Eur. J. Soil Sci. 53, 231–240.
Ketelsen, H., Meyer-Windel, S., 1999. Adsorption of brilliant blue
FCF by soils. Geoderma 90, 131–145.
Köhne, J.M., Köhne, S., Šimůnek, J., 2006. Multi-process herbicidetransport in structured soil columns: experiments and model
analysis. J. Contam. Hydrol. 85, 1–32.
Lennartz, B., 1999. Variation of herbicide transport parameters within
a single field and its relation to water flux and soil properties.
Geoderma 91, 327–345.
Lennartz, B., Kamra, S.K., 1998. Temporal variability of solute transport
under vadose zone conditions. Hydrol. Process. 12, 1939–1949.
Marquardt, D.W., 1963. An algorithm for lest-squares estimation of
nonlinear parameters. J. Soc. Ind. Appl. Math. 11, 431–441.
Nemeth-Konda, L., Füleky, Gy., Morovjan, Gy., Csokan, P., 2002.
Sorption behaviour of acetochlor, atrazine, carbendazim, diazinon,
imidacloprid and isoproturon on Hungarian agricultural soil.
Chemosphere 48, 545–552.
Nkedi-Kizza, P., Biggar, J.W., Selim, H.M., van Genuchten, M.Th.,
Wierenga, P.J., Davidson, J.M., Nielsen, D.R., 1984. On theequivalence of two conceptual models for describing ion exchange
during transport through an aggregated oxisol. Water Resour. Res.
20, 1123–1130.
Nobles, M.M., Wilding, L.P., McInnes, K.J., 2004. Submicroscopic
measurements of tracer distribution related to surface features ofsoil aggregates. Geoderma 123, 83–97.
Official Journal of the European Communities. 2001. Decisionn° fc2455/2001/EC of the European Parliament and of the Councilof 20 November 2001 establishing the list of priority substances in
the field of water policy and amending Directive 2000/60/EC.
L331, 1–5.
Pantani, O.L., Dousset, S., Schiavon, M., Fusi, P., 1997. Adsorption of
isoproturon on homoionic clays. Chemosphere 35, 2619–2626.
Parsons, R., 1959. Handbook of Electrochemical Constants. Academic
Press, New York. 113 pp.
Perillo, C.A., Gupta, S.C., Nater, E.A., Moncrief, J.F., 1998. Flowvelocity effects on the retardation of FD and C blue no 1 food dye
in soil. Soil Sci. Soc. Am. J. 62, 39–45.
Pieuchot, M., Perrin-Ganier, C., Portal, J.M., Schiavon, M., 1996.
Study on the mineralization and degradation of isoproturon in threesoils. Chemosphere 33, 467–478.
Pot, V., Šimůnek, J., Benoit, P., Coquet, Y., Yra, A., Martinez-Cordon,
M.J., 2005. Impact of rainfall intensity on the transport of two
herbicides in undisturbed grassed filter strip soil cores. J. Contam.
Hydrol. 81, 63–88.
Rao, P.S.C., Davidson, J.M., Jessup, R.E., Selim, H.M., 1979.
Evaluation of conceptual model for describing nonequilibrium
adsorption–desorption of pesticides during steady-flow in soils.
Soil Sci. Soc. Am. J. 43, 22–28.
Renault, P., Mohrath, D., Gaudu, J.C., Fumanal, J.C., 1998. Air pressure
fluctuations in a prairie soil. Soil Sci. Soc. Am. J. 62, 553–563.
Sabbah, I., Ball, W.P., Young, D.F., Bouwer, E.J., 2005. Misinterpretations in the modelling of contaminant desorption from environmental
solids when equilibrium conditions are not fully understood. Environ.
Eng. Sci. 22, 350–366.
Sadeghi, A.M., Isensee, A.R., Shirmohammadi, A., 2000. Influence ofsoil texture and tillage on herbicide transport. Chemosphere 41,
1327–1332.

276

S. Dousset et al. / Journal of Contaminant Hydrology 94 (2007) 261–276

Selim, H.M., Davidson, J.M., Rao, P.S.C., 1977. Transport of reactive
solutes through multilayered soils. Soil Sci. Soc. Am. J. 41, 3–10.
Seyfried, M.S., Rao, P.S.C., 1986. Solute transport in undisturbed
columns of an aggregated tropical soil: preferential flow effects.
Soil Sci. Soc. Am. J. 51, 1434–1444.
Shaw, J.N., West, L.T., Radcliffe, D.E., Bosch, D.D., 2000.
Preferential flow and pedotransfer functions for transport properties in sandy kandiudults. Soil Sci. Soc. Am. J. 64, 670–678.
Šimůnek, J., Šejna, M., van Genuchten, M.Th., 1998. The HYDRUS1D Software Package For simulating the One-dimensional
Movement of Water, Heat, and Multiple Solutes in Variablysaturated Media. Version 2.0, IGWMC-TPS-70. International
Ground Water Modeling Center, Colorado School of Mines,
Golden, Colorado. 202 pp.
Šimůnek, J., Jarvis, N.J., van Genuchten, M.Th., Gärdenäs, A., 2003.
Review and comparison of models for describing non-equilibrium
and preferential flow and transport in the vadose zone. J. Hydrol.
272, 14–35.
Spark, K.M., Swift, R.S., 2002. Effect of soil composition anddissolved organic matter on pesticide sorption. Sci. Total Environ.
298, 147–161.
Spliid, N.H., Koppen, B., 1998. Occurrence of pesticides in Danish
shallow ground water. Chemosphere 37, 1307–1316.
Starret, S.K., Christains, N.E., Austin, A.Al., 1996. Comparing
dispersivities and soil chloride concentrations of turfgrass-covered
undisturbed and disturbed soil columns. J. Hydrol. 180, 21–29.

Tomlin, C.D.S., 1997. The Pesticide Manual, 11th ed. British Crop
Protection Council and The Royal Society of Chemistry, UK.
van Genuchten, M.Th., Wagenet, R.J., 1989. Two-site/two-region
models for pesticide transport and degradation: theorical development and analytical solutions. Soil Sci. Soc. Am. J. 53, 1303–1310.
van Genuchten, M.Th., Wierenga, P.J., 1977. Mass transfer studies insorbing porous media II. Experimental evaluation with tritium(3H2O). Soil Sci. Soc. Am. J. 41, 272–285.
Veeh, R.H., Inskeep, W.P., Roe, F.L., Fergusson, A.H., 1994. Transportof chlorosulfuron through soils columns. J. Environ. Qual. 23,
542–549.
Walker, A., Turner, I.J., Cullington, J.E., Welch, S.J., 1999. Aspects of
the adsorption and degradation of isoproturon in a heavy clay soil.
Soil Use Manage. 15, 9–13.
Walker, A., Jurado-Exposito, M., Bending, G.D., Smith, V.J.R., 2001.
Spatial variability in the degradation rate of isoproturon in soil.
Environ. Pollut. 111, 407–415.
Weast, R.C., 1985. Handbook of Chemistry and Physics, 66th edition.
CRC Press, Boca Raton, Florida.
Zehe, E., Flühler, H., 2001. Preferential transport of isoproturon at aplot scale tile-drained site. J. Hydrol. 247, 100–115.
Zsolnay, A., 1991. The use of small columns to estimate the effect ofsoil structure on transport. Chemosphere 23, 107–115.