Pesticide displacement along preferential flow pathways in a Brazilian Oxisol

Geoderma 110 (2002) 63 – 86 www.elsevier.com/locate/geoderma

Pesticide displacement along preferential flow pathways in a Brazilian Oxisol S. Reichenberger a,*,1, W. Amelung a,2, V. Laabs a, A. Pinto b, K.U. Totsche a, W. Zech a b

a Institute of Soil Science and Soil Geography, University of Bayreuth, D-95440 Bayreuth, Germany Projeto Ecologia do Gran Pantanal, Universidade Federal de Mato Grosso, 78060 Cuiaba´, MT, Brazil

Received 5 January 2001; received in revised form 18 February 2002; accepted 21 May 2002

Abstract Previous studies conducted in tropical soils showed that pesticides of different polarity reached subsoil lysimeters within the same time intervals. This cannot be explained by pesticide transport under matrix flow conditions. The objective of this study was to elucidate pesticide transport in an Oxisol under preferential flow conditions. In a field experiment near Cuiaba´, Brazil, alachlor, atrazine, chlorpyrifos, E-cyhalothrin, deltamethrin, endosulfan-a, metolachlor, monocrotophos, simazine, and trifluralin were applied onto a Typic Haplustox. Afterwards, 40 mm day 1 of tracer solution (containing 5 g l 1 of the dye Brilliant Blue FCF and 0.015 M KBr) were applied in duplicate experiments over a period of 3 days, using either a tension infiltrometer (3.3 cm tension) or manual irrigation with a watering can. Soil monoliths were laid open, and the soil layers of 0 – 5, 5 – 10, 10 – 20, 20 – 30, and 30 – 40 cm were quantitatively removed. The soil of each depth interval was separated into a ‘‘blue’’, a ‘‘nonblue’’, and, if necessary, into a ‘‘nonseparable’’ fraction. Pesticide concentrations in 10 – 30 cm soil depth were 2.0 – 3.5 times higher at the dye front than in the entirely blue fraction. In the Oxisol under study, transport along preferential flow pathways contributed a major part to total pesticide displacement. This relative contribution was two to five times higher for the nonpolar than for the polar pesticides. The measured pesticide displacement reached deeper soil layers than that simulated for these compounds with the leaching model PEARL. Can irrigation, causing an occasional ponding, enhanced leaching of the corn herbicides (simazine, atrazine, alachlor, metolachlor) from the top 5 cm by a factor of 2.8 – 4.2, compared with strictly unsaturated

*

Corresponding author. Tel.: +49-641-9937390; fax: +49-641-9937389. E-mail address: [email protected] (S. Reichenberger). 1 Present address: Department of Agricultural Ecology and Natural Resources Management, University of Gießen, 35392 Gießen, Germany. 2 Present address: Department of Soil Science, Institute for Ecology, TU Berlin, 10587 Berlin, Germany. 0016-7061/02/$ - see front matter D 2002 Elsevier Science B.V. All rights reserved. PII: S 0 0 1 6 - 7 0 6 1 ( 0 2 ) 0 0 1 8 2 - 9

64

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

infiltrometer irrigation. For the other compounds, differences in leaching behaviour between plots exceeded those between the different infiltration regimes. D 2002 Elsevier Science B.V. All rights reserved. Keywords: Pesticides; Tracers; Brilliant Blue FCF; Preferential flow; Oxisol

1. Introduction Corn and soybean cropping has been strongly intensified in the Brazilian Cerrado region during the last 20 years (Goedert, 1983). Both monocultures require a high degree of mechanization and input of agrochemicals. Whereas the environmental fate of pesticides has been extensively studied in temperate zones (e.g., Flury et al., 1995; Funari et al., 1998), little is known about pesticide dynamics in tropical regions (e.g., Nakagawa et al., 1996; de Andre´a et al., 1997). Many tropical soils exhibit different adsorption properties for pesticides compared with temperate soils (Barriuso and Calvet, 1992). Moreover, higher rainfall intensities and surface temperatures may favour pesticide dissipation from the surface soil (Laabs et al., 2000). Thus, knowledge of pesticide dynamics under temperate conditions may be of limited value for predicting pesticide fate in tropical regions. In temperate soils, pesticide displacement in soil often occurs along preferential flow paths (Lennartz, 1999). Under preferential flow conditions, water and solutes move only through a portion of the available pore space (Flury, 1996) or at least markedly faster in certain soil parts than in others. Preferential flow can occur in well-structured clayey soils (Flury et al., 1994) as well as in poorly structured sandy soils (Ghodrati and Jury, 1990). Lysimeter experiments in an Oxisol near Cuiaba´, Mato Grosso, revealed that polar and nonpolar pesticides were leached from the soil surface to 35 cm soil depth within the same period (Laabs et al., 2000). The authors suggested that this was an indication of pesticide transport by preferential flow. However, our knowledge concerning the contribution of preferential flow to pesticide leaching under field conditions is still scarce, especially for tropical soils and climates. Grid sampling with soil cores has been shown to be unsuitable for quantifying solute transport along preferential flow pathways, because (i) the leading edge of chemicals is probably missed due to the spatial variability of the flow pattern, and (ii) the chemical concentrations along the preferential flow channels are diluted by the surrounding matrix (Flury, 1996). These problems can be avoided when flow paths are marked by tracers (Flury et al., 1994) and sampled quantitatively. Tracer experiments showed that the flow regime in soils depends, apart from soil tillage, also on the irrigation method (Ghodrati and Jury, 1990). For instance, ponding infiltration causes rapid, saturated flow in cracks and earthworm channels, which would not occur in the case of unsaturated infiltration. Therefore, the flow patterns resulting from flood irrigation can be markedly different from those resulting from unsaturated sprinkling irrigation (Flury et al., 1994; Ghodrati and Jury, 1990). Ghodrati and Jury (1992) found a greater leaching for atrazine under continuous ponding than under intermittent ponding, whereas the contrary was the case

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

65

for prometryn and napropamide. Different sprinkling irrigation affected leaching only for napropamide. Obviously, the influence of different irrigation methods on pesticide displacement is still not elucidated sufficiently. Inorganic ions as well as dyes are often used as tracers in soils and aquifers. Inorganic anions, such as bromide, are used to trace water flow because they behave nearly conservative in most soils (Boulding, 1995, p. 449). The advantage of bromide in comparison with other anions employed as conservative tracers (e.g., Cl , NO3 ) is that natural background concentrations in soils are very low and, therefore, only small amounts of bromide have to be applied. Dyes are applied to visualize flow paths and to mimic the transport behaviour of adsorbing and nonadsorbing solutes (Flury and Flu¨hler, 1995). A dye tracer frequently used to stain flow paths in porous media is the nonfluorescent food dye Brilliant Blue FCF (C.I. 42090). Advantages of this dye are its (i) low toxicity (Flury and Flu¨hler, 1994), (ii) good visibility in the soil, and (iii) chemical stability. However, the mobility of Brilliant Blue FCF in soils depends on soil properties as well as experimental conditions: Ketelsen and Meyer-Windel (1999) reported that the sorption capacity for Brilliant Blue FCF in soil increased with clay content and decreased with organic carbon content. The authors did not find an increasing adsorption of Brilliant Blue FCF due to protonation with decreasing pH. Column experiments showed that the retardation of this dye in soil increases with decreasing infiltration rate (Perillo et al., 1998) and with the simultaneous use of other ionic tracers such as KBr (Allaire-Leung et al., 1999). Yet, Germa´n-Heins and Flury (2000) concluded that despite its disadvantages, Brilliant Blue FCF may still be one of the best compromises available to date as dye tracer in temperate soils. Little information is available concerning the transport behaviour of Brilliant Blue FCF in tropical soil matrices, whose clay fraction is commonly dominated by oxides and two-layer clay minerals. Schwartz et al. (1998) reported an increasing adsorption of the dye with increasing depth in an Ultisol. Also, Germa´n-Heins and Flury (2000) hypothesized a correlation between the soil sorption capacity for Brilliant Blue FCF and the iron oxide content. Therefore, especially in soils that contain large amounts of iron and aluminium oxides, the transport behaviour of Brilliant Blue FCF should be examined. The objective of our experiment was to: (i) characterize the flow patterns of bromide and of the dye tracer Brilliant Blue FCF in a Brazilian Oxisol, (ii) relate the displacement of the tracers to that of different pesticides, in order to quantify the effect of compound properties on pesticide transport, (iii) assess the minimum portion of pesticides that is displaced by preferential flow transport in the Oxisol, and (iv) elucidate the effect of the infiltration regime on pesticide transport in this soil.

2. Materials and methods 2.1. Field experiment The study area (15j42V43WS, 55j15V33WW) is situated ca. 100 km east of Cuiaba´, the capital of the state of Mato Grosso in the central-western region of Brazil. Its climate is of

66

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

the savanna type, with a distinct rainy (November – April) and dry season (June – September). The mean annual precipitation is 1900 mm, the mean annual temperature is 23 jC. The soil of the study site was classified as fine, mixed, isohyperthermic Typic Haplustox (Soil Survey Staff, 1998; Table 1). The experimental field had been ploughed (ploughing depth ca. 30 cm) and harrowed 4 weeks before carrying out the experiment and had prior served as pasture for 3 years, as part of a corn –soybean – pasture rotation. Crop – pasture rotation is commonly practised in this area to prevent loss of humus and aggregate structure. In the rainy season 1998/1999, 2 days before the experiment started, a square area of 4.50 m  4.50 m was broken up with a hoe to a depth of 10 cm to simulate the tillage used in local agriculture. Vegetation residues were removed, and the surface was levelled with a rake. Subsequently, we covered the experimental area with a plastic tilt to let the moist soil drain to field capacity and to avoid surface sealing by heavy rainstorms before and during the experiment. This practice also minimized differences in initial water contents among the plots. Immediately before pesticide application, we levelled four plots (50 cm  50 cm) to V 3 mm unevenness with trowel and water-level, strictly avoiding soil compaction or surface blurring. A drainage trench around the experimental field protected the plots from lateral surface runoff. We used 10 pesticides frequently employed in corn and soybean cropping, with different physical and chemical properties (Table 2) in our experiments. The following commercial pesticide formulations (all emulsifiable concentrates) were used: alachlor (2chloro-2V,6V-diethyl-N-methoxymethyl-acetanilide): Alachlor Nortox, Nortox, Arapongas, PR, Brazil; atrazine (2-chloro-4-ethylamino-6-isopropylamino-1,3,5-triazine) + simazine (2-chloro-4,6-bis(ethylamino)-1,3,5-triazine): Triamex, Rhodia Agro, Sa˜o Paulo, SP, Brazil; chlorpyrifos (O,O-diethyl O-3,5,6-trichloro-2-pyridyl phosporothioate): Lorsban, Dow Elanco, Sa˜o Paulo, SP, Brazil; E-cyhalothrin ((RS)-a-cyano-3-phenoxybenzyl (Z)(1RS)-cis-3-(2-chloro-3,3,3-trifluoro-propenyl)-2,2-dimethylcyclopropanecarboxylate): Karate, Zeneca, Sa˜o Paulo, SP, Brazil; deltamethrin ((S)-a-cyano-3-phenoxybenzyl (1R, 3R)-3-(2,2-dibromovinyl)-2,2-dimethyl-cyclopropan-1-carboxylate): Decis 50 SC, Hoechst Schering AgrEvo do Brasil, Santo Amaro, SP, Brazil; endosulfan-a (6,7,8,9,10,10-hexachloro-1,5,5a,6,9,9a-hexahydro-6,9-methano-2,4,3-benzodioxathiepin 3-oxide): Thiodan, Hoechst Schering AgrEvo do Brasil, Santo Amaro, SP, Brazil; metolachlor (2-chloro-6V-ethyl-N-(2-methoxy-1-methylethyl)acet-o-toluidide): Dual,

Table 1 Properties of the Typic Haplustox under study Depth (cm)

Horizon

0 – 10 40 – 50 90 – 100

A BA Bo

a b

Organic C (g kg 1)

Texture (g kg Sand

Silt

30.6 10.4 8.2

517 525 525

43 26 14

b

1

Clay

Dry bulk density (g cm 3)

pH (water)

pH (1 M KCl)

a CECpot (cmolc kg

440 449 461

0.94 0.97 0.98

6.06 5.90 5.05

5.62 4.73 5.03

17.5 9.1 –

)

CECpot: potential cation exchange capacity (measured in 1 M NH4OAc). 2 – 20 Am.

1

)

Table 2 Basic properties of pesticides and applied amount Pesticide

a b c d e f g h i j k l

H H I I I I H I H H

Chemical class acetamide triazine organophosphorus pyrethroid pyrethroid organochlorine acetamide organophosphorus triazine dinitroaniline

Solubility (in H2O)b (20 jC) [mg l 1]

Vapour pressureb (25 jC) [mPa]

c,d KOC [l kg

240 33 0.4 0.005 < 0.002k 0.32 530 1 000 000 6.2 0.3

1.9 0.04 2.3j 0.0002j 0.002k 0.02 4.2 9.3j 0.0029 14.7

180 189 7247 > 80 000 > 80 000 5713 123 48 269 8016

1

OC]

e,f DT50 field [days]

e DT50 lab [days]

Applied amount (a.i.)g [g ha 1]

6.0 7.8 0.7 11.0 11.0 1.6 20.0 1.7 17.0 4.0

4.3h 12.2i 19.6h 11.0i 11.0h 13.6h 20.0i 1.7h 26.6h 60.0h

3360 2000 1500 30 20 660l 3840 1100 2000 1600

H: herbicide; I: insecticide. Hornsby et al. (1996). KOC: partitioning coefficient between soil and water, normalized for organic carbon (OC) content of the soil [measured for the Typic Haplustox (0 – 10 cm) under study]. Laabs et al. (2000). DT50: dissipation time for 50% of applied amount. Measured in our experimental area in the rainy season 1998/1999. a.i.: active ingredient. Determined with 14C-labelled compounds by Laabs et al. (in press) in the Typic Haplustox (0 – 10 cm) at 30 jC and 40% water-holding capacity. Values were estimated from laboratory degradation half-lives of related compounds. Determined at 20 jC. Hartley and Kidd (1987). Only a-isomer.

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

Alachlor Atrazine Chlorpyrifos E-Cyhalothrin Deltamethrin Endosulfan-a Metolachlor Monocrotophos Simazine Trifluralin

Typea

67

68

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

Novartis, Rescende, RJ, Brazil;monocrotophos (3-dimethoxyphosphinyloxy)-N-methylisocrotonamide): Nuvacron, Novartis, Resende, RJ, Brazil; and trifluralin (2,6-dinitro-N, Ndipropyl-4-trifluoromethylaniline): Trifluralina, Defensa, Porto Alegre, RS, Brazil. Pesticides were uniformly applied onto the 4.50 m  4.50 m area at application rates representative for the local agricultural practice (Table 2). Three application suspensions, each containing two to five pesticide formulations, were successively applied crisscross with a handheld spraying apparatus. Miscibility of formulations and uniformity of application had been ensured before in preliminary trials. The volume of water applied with all applications to the soil amounted to 0.13 mm. Afterwards, the plots were immediately covered with aluminium foil to minimize volatilization and prevent photolysis of pesticides. The foil was removed only during irrigation. Three times 40 mm of tracer solution were then uniformly applied to each plot within 3 days (40 mm day 1). The tracer solution contained 5 g l 1 of the anionic dye Brilliant Blue FCF (C.I. 42090) (N-ethyl-N-(4-((4-(ethyl((3-sulfophenyl)methyl)-amino)phenyl)(2sulfophenyl)methylene)-2,5-cyclohexadien-1-ylidene)-3-sulfobenzenemethanaminium hydroxide inner salt, disodium salt) as adsorbing tracer and 0.015 M KBr as conservative tracer. Brilliant Blue FCF is a triphenylmethane dye with a molar mass of 792.85 g mol 1. Its water solubility is 200 g l 1, KOW at pH 5.7 is < 10 4, pKa1 = 5.83, pKa2 = 6.58. For further properties, see Flury and Flu¨hler (1994, 1995). Preliminary experiments showed that Brilliant Blue FCF did not interfere with pesticide analysis. The colorant Brilliant Blue FCF was courtesy of Clariant Deutschland (Frankfurt/Main, Germany). Two plots were irrigated under unsaturated conditions using a tension infiltrometer. This device provided irrigation solution at adjustable tension to a circular area of 39.9 cm diameter (used irrigation tension: 3.3 cm). The necessary intimate contact between the infiltrometer disk and the irrigation area was ensured with a thin ( V 3 mm) layer of medium quartz sand (250 – 500 Am in diameter), leading to a spatially absolutely uniform infiltration surface. From the 1st to the 3rd irrigation, infiltration time increased from 45 to 120 min due to increasing soil moisture content. The other two plots were irrigated on a 35 cm  35 cm area with a watering can to simulate a high-intensity rainstorm. As soon as ponding occurred, irrigation was stopped until the excess solution had infiltrated. Thus, at some spots, infiltration occasionally took place as ponding infiltration. Consequently, even with sprinkling being as uniform as possible, infiltration was spatially not homogeneous. This is, however, also the case for the infiltration during natural rainfall events. The time required for can irrigation increased from 15 to 30– 40 min from the 1st to the 3rd irrigation. One day after the 3rd irrigation, we excavated the plots. A soil monolith (25 cm  25 cm  40 cm) was laid open, and its vertical profiles were photographed (Fig. 1). The depth intervals of 0 – 5, 5 – 10, 10 – 20, 20 – 30, and 30 – 40 cm were marked and successively removed with spatulas. Except for one can-irrigated plot with a maximum penetration depth of 32 cm, the 30 – 40-cm intervals of the soil monoliths were completely unstained. A maximum sampling depth of 40 cm was therefore considered as sufficient to catch the leading edges of all pesticides and to exclude migration of pesticides beyond this depth. The quantitatively removed soil material of each interval was separated in situ into a ‘‘blue’’ (BL), a ‘‘nonblue’’ (NB), and, if necessary, a

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

69

Fig. 1. Vertical profile of a soil monolith (can irrigation). The dimensions of the monolith were 25 cm  25 cm  40 cm.

‘‘nonseparable’’ (NS) fraction. Soil material was considered nonseparable when the staining pattern was too fine structured to separate stained and unstained soil with a spatula. Each fraction of each depth interval was collected in a bucket, homogenized, weighed, and sampled. Soil samples were immediately stored on ice in a thermo-box and were frozen within 6 h after sampling. 2.2. Analysis of pesticides and tracers 2.2.1. Pesticides Pesticide analysis was performed as outlined by Laabs et al. (1999). In brief, soil samples (25 g) were spiked with surrogate standards (a-HCH: 1a,2a,3h,4a,5h,6hhexachloro-cyclohexane; terbuthylazine: 2-tert-butylamino-4-chloro-6-ethylamino-1,3,5triazine; ditalimfos: O,O-diethyl phthalimidophosponothioate; 10 Ag each in 50 Al acetone), shaken end-over-end for 4 h with 50 ml of a mixture of acetone/ethylacetate/ water (2:2:1 v/v/v), centrifuged for 10 min, and filtered with a paper filter (S&S 597 1/2, Schleicher & Schuell, Dassel, Germany). After removing the bulk of organic solvents with a rotary evaporator (adding 0.2 ml toluene as keeper), 40 ml of saturated NaCl solution was added, and a liquid –liquid extraction was conducted using 3  25 ml dichloromethane. Then the organic phase was dried over Na2SO4, and 0.1 ml toluene was again added as keeper. Samples were concentrated and transferred to autosampler vials. Pesticides were quantified using GC/MSD (HP 6890/5972) under the following conditions (Laabs et al., 2000, modified): fast hot-splitless injection (injection volume: 1 Al), injector block temperature: 250 jC; carrier gas: helium; front inlet pressure: constant at 84 kPa; oven temperature: ramped from 92 jC up to 280 jC with three isothermic phases; transfer-line

70

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

temperature: 290 jC. The MSD operated in the selected ion monitoring (SIM) mode, recording one target ion and two qualifier ions per substance. Calibration was done with four-point linear functions, using internal and external standards. Internal and pesticide standards were supplied by Novartis Crop Protection (Basel, CH), Dow Agrosciences (Norfolk, UK), and Aventis CropScience (Frankfurt/Main, Germany), or purchased from Promochem (Wesel, Germany) with a purity greater than 99%. Routine limits of determination were 0.5 – 2.5 Ag kg 1 dry soil, depending on substance properties. Pesticide recoveries from Oxisol samples were z 85% of the spiked amount for all compounds. The water phase from the sorption experiment (Section 2.3) was liquid – liquid extracted using a 10-ml aliquot of the liquid phase, 40 ml of saturated NaCl solution, and 3  25 ml dichloromethane. Otherwise, pesticide analysis was handled as described above. 2.2.2. Tracers For bromide analysis, 5 g soil was shaken end-over-end for 1 h with 50 ml deionized water (Millipore) at 70 rpm. After centrifugation for 15 min at 2000  g, the supernatant was decanted and filtered with a paper filter (S&S 597 1/2, Schleicher & Schuell). The filtrates were analyzed using an ICP/MSD (VG Plasma Quad PQ2 Turbo Plus, Fisons Instruments, Australia). The limit of determination for bromide was 10 Ag l 1 extract, which corresponds to 0.125 mg kg 1 dry soil. In spiking experiments, using a concentration range of 0.24 – 479 mg Br kg 1 dry soil, bromide recovery was 94.5 F 1.3% of the applied amount for both 0 – 10 and 35– 45 cm soil depth. Measured concentrations were corrected by this value. Quantification of the dye was performed with the same extracts that were used for bromide analysis, using a spectrophotometer (Cary 50 Conc UV-Visible Spectrophotometer, Varian Australia, Mulgrave, Australia) operated at a wavelength of 630 nm. The lower limit of quantification for Brilliant Blue FCF was 0.1 mg l 1 extract or 1.25 mg kg 1 dry soil. However, photometrical analysis turned out to be problematic for extracts with high blank extinctions (soil samples with high contents of sesquioxides and DOC) and with low dye concentrations (below 5 mg l 1 extract). Recoveries of Brilliant Blue FCF decreased with increasing soil depth from 76.9 F 5.3% in 0– 10 cm to 58.1 F 2.1% in 35– 45 cm soil depth (over a concentration range of 1 –2000 mg kg 1 dry soil). As for bromide, measured concentrations of Brilliant Blue FCF were corrected for recoveries within the respective sampling depths. 2.3. Sorption study To determine the effect of the dye on pesticide sorption, we conducted a batch experiment with Brilliant Blue FCF, pesticides, and the soil under study. To this aim, 10 g of air-dry Oxisol (0– 10 cm depth) was shaken in duplicate end-over-end for 1, 3, 6, 12, or 24 h with 50 ml of a solution containing (a) 0.015 M KBr and a mixture of the 10 pesticides used in the field (25 Ag each) or (b) the same as in (a) with the addition of 5 g l 1 of the dye. Thereafter, we determined pesticides in both liquid and solid phases as outlined above. The experiment was performed with various shaking times to account for

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

71

possible differences in pesticide sorption kinetics between dye-containing and dye-free batch systems. 2.4. Data analysis From substance concentrations and soil masses of the fractions in every sampling depth, we calculated pesticide and tracer masses in the respective fractions. These were subsequently normalized to the total mass of each substance found in a given plot. The obtained mass portions as well as substance concentrations for every fraction served as bases for statistical analysis. Statistical analyses (ANOVA, cluster analysis, correlation and rank correlation analysis) were performed using the software package Statistica for Windows 5.1 (StatSoft, 1996). For the cluster analysis, we used the tree clustering method with the Euclidean distance as distance measure. Input data for cluster analysis were (a) the measured pesticide mass portions in the single fractions of all four plots (n = 41) and (b) the simulated pesticide mass portions in the depth intervals 0– 5, 5 –10, 10– 20, 20 –30, and 30– 40 cm. 2.5. Modelling of pesticide leaching To enable a comparison between our field results and expected results assuming a uniform matrix flow of water and a sorption of pesticides according to their sorption isotherms, we conducted simulations with a leaching model for all ten pesticides and for bromide. For the simulations, we chose the model PEARL 1.1.1 (Pesticide Emission Assessment at Regional and Local Scales; Tiktak et al., 2000) because of its wide acceptance (PEARL is an official tool for leaching risk assessment according to EU regulations) and its mechanistic modelling approach. PEARL calculates water flow using the Richards equation and the Van-Genuchten – Mualem relationships (van Genuchten, 1980) and solute transport using the convection –dispersion equation (CDE), all on a daily basis. It also accounts for the transport of substances in the gas phase. The model was run with the simulated soil conditions being as close as possible to those of our field experiment. (i) Soil properties: A soil profile was specified with soil layers corresponding to our sampling depth intervals. Texture, organic matter content, pH, and dry bulk density values were measured in the field or interpolated from field measurements. The Van-Genuchten parameters for water transport were estimated for each soil layer from texture and bulk density, using the program Rosetta (Schaap, 1999). The groundwater level was set to 25 m depth, and the lower boundary condition to free drainage. (ii) Climatic conditions: Original weather data from a Brazilian weather station (Planaltina, DF), measured over 12 months with daily resolution and rescaled to the climatic conditions at the experimental site, were used as meteorological input file. The model run started 1 year before the beginning of our experiment to allow the soil water budget to equilibrate. (iii) Substance parameters: Bromide was assumed to be nonsorbing. For the pesticides, linear equilibrium sorption and first-order degradation were assumed. We used the site-

72

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

specific sorption coefficients (Table 2) according to Laabs et al. (2000) and laboratory degradation half-lives (Table 2) determined for the specific Typic Haplustox (Laabs et al., in press). The depth-reduction factor for pesticide degradation rates was set to 1.0 in 0– 30 cm, 0.5 in 40 –70 cm, and 0.3 in 70 –150 cm soil depth. (iv) Experimental setup: The timing of tillage, pesticide application, and irrigation was specified according to our field experiment. Before the first tillage, the soil was defined as grass covered, reflecting that it was used as pasture before ploughing. During the period in which the plots had been covered in the field, soil evaporation was set to zero. Pesticide application rates in PEARL were adjusted to the pesticide concentrations determined in the surface soil sampled immediately after application. However, some experimental conditions could not be reproduced completely in PEARL. (i) The irrigation method in PEARL is always a sprinkler irrigation. Thus, infiltrometer irrigation could not be simulated. (ii) It was not possible to apply substances (e.g., bromide) with the irrigation water. Therefore, in the model calculation, bromide was applied as pulse before the irrigation onto the soil surface on the 3 days with irrigation events. Thus, the upper boundary condition for the application of bromide differed from that in the field experiment. However, as bromide was set nonsorbing, this difference should not have affected the simulation results for bromide. (iii) It was not possible to enter irrigation intensities. Consequently, in PEARL, the amount applied in each irrigation event was always applied over 24 h. However, as neither volatilization (due to zero evaporation) nor kinetic sorption (not specified due to lack of data) occurred in this PEARL scenario, the smaller irrigation intensity, resulting in slower water flow relative to the field experiment, should not have significantly altered the modelled final depth distribution of pesticides. (iv) PEARL is a one-dimensional model. Although PEARL can calculate lateral flow of water and solutes to drainage systems, this lateral outflow option could not be calibrated well enough to the lateral losses of tracer solution from the sampled soil area that occurred in our experiment. Therefore, the simulations were performed without the occurrence of lateral flow, and only vertical flow was allowed. As a consequence, the percolate volume was overestimated compared with the field experiment. Hence, water flow in the simulations represented a worst-case scenario for leaching of solutes by matrix flow in this soil. The PEARL scenarios were identical for all pesticides except for compound properties and application rates.

3. Results and discussion 3.1. Tracer dynamics Preliminary infiltration experiments revealed a high plot-to-plot variability of the stained flow patterns. Moreover, between the plots infiltration rates varied by a factor of 3 (values between 14 and 48 cm h 1), and maximum infiltration depths of the dye by a

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

73

factor of 2. In the tilled layer (0 – 10 cm depth), the soil was stained uniformly blue, while fingering patterns, if present, started directly at the interface between tilled and untilled soil. Obviously, the infiltration occurred more or less homogeneously in the mechanically mixed topsoil layer, while beyond the tillage depth, the undisturbed soil structure led to the development of preferential flow zones. The high variability of flow patterns and infiltration behaviour among the experimental plots was attributed to a high spatial heterogeneity of soil physical properties, especially of bulk density and pore structure, on a meter scale. The mass recovery (mass found per area of soil in percentage of the mass applied) of a chemical in a solute transport study is a crucial measure for the quality of a field experiment. It may vary considerably in the field, even for conservative compounds (Flury, 1996). In our study, bromide recoveries were 32.3 F 9.5% for infiltrometer and 45.7 F 4.9% for can irrigation; dye recoveries totalled 46.9 F 12.6% and 61.2 F 10.6% of the applied amount, respectively. Obviously, the ratio of irrigated area to sampling area (2:1) was not sufficiently large to eliminate border effects like lateral flow of tracer mass out of the sampled soil monolith. Lower tracer recovery for infiltrometer irrigation in comparison with can irrigation can be explained by higher lateral losses due to slower infiltration. Losses of bromide by leaching beyond the maximum sampling depth of 40 cm can also not be ruled out; however, bromide mass portions in the 30– 40-cm depth interval were only 1.9 F 1.8% of the total amount found in the 0 –40-cm depth. Vertical losses of bromide beyond the sampling depth can therefore be considered as not significant. The higher recovery of Brilliant Blue FCF as compared with bromide reflects smaller lateral losses of this dye due to its retardation by adsorption in the soil. Since the lateral losses of a compound decrease with decreasing mobility in the soil, the relative losses of the pesticides (possibly with the exception of monocrotophos) should be markedly smaller than the tracer losses. Therefore, the obtained pesticide displacement data can still be considered meaningful, if one keeps in mind that only about 40% of the amount of water used for irrigation contributed to vertical seepage in the sampling area. In general, soils containing substantial amounts of sesquioxides may potentially adsorb anions, due to a point of zero charge (PZC) of iron and aluminium oxides at relatively high pH values (pH 8– 9; Schachtschabel et al., 1992). Yet, the presence of organic matter lowers both the overall PZC of the soil and, by sorption of SOM on oxide surfaces, the PZC of the iron and aluminium oxides themselves (Gillman, 1985). For instance, van Raij and Peech (1972) found a PZC at pH V 4 in the topsoil (2.5% Corg) of a Brazilian Oxisol. In the subsoil (0.7% Corg), however, which had the same mineralogical composition as the topsoil, the PZC was reached at a pH of 6. As the Oxisol in our study had even higher organic carbon contents (Table 1) than the soil profile studied by van Raij and Peech (1972), the PZC in the Typic Haplustox studied likely occurred at pH values lower than 4 in the topsoil and lower than 6 in the subsoil. At the given pH values (Table 1), a significant adsorption of bromide may thus only occur in the subsoil of the Oxisol, i.e., beyond the investigated sampling depths. A negative difference between the pH (KCl) and the pH (H2O) down to 1 m soil depth (Table 1), and the lack of Cl retardation in column breakthrough experiments with topsoil material from the same site (unpublished data), support this conclusion.

74

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

The mass distribution of the tracer in the plots provides information about water flow and the transport behaviour of bromide and Brilliant Blue FCF. Tracer masses found per depth interval exhibited a maximum in the 0– 10-cm depth and then decreased with increasing depth (Table 3). Within the depth intervals, concentrations of both tracers decreased in the order BL>NS>NB. Over the range of all plots, bromide concentrations were 1.1 –50 times, dye concentrations 2.9 –80 times higher in BL than in NB within the same depth interval in the same plot. These concentration differences between BL and NB were significant for both bromide ( p < 0.05) and Brilliant Blue FCF ( p < 0.001, ANOVA). Differences in tracer mass distribution between the two irrigation methods were not significant ( p = 0.66 and 0.90 for bromide and Brilliant Blue FCF, respectively, one-way ANOVA) and smaller than differences between the replicates of one irrigation treatment. Thus, soil spatial heterogeneity among the plots affected water flow and tracer dynamics in this Oxisol stronger than did the irrigation method. Flury and Flu¨hler (1995) reported that Brilliant Blue FCF was retarded in soils relative to the inorganic tracers bromide and iodide. To identify such processes, we calculated the ratio of dye to bromide concentrations in soil. This ratio, normalized to the dye to bromide concentration ratio in the irrigation solution, reveals whether Brilliant Blue FCF is enriched or depleted relative to bromide in a given sample (Table 4). For each depth interval, the ratio of dye to bromide concentrations consistently decreased in the order BL (0.9 – 1.9)>NS (0.3 – 1.7)>NB (0 – 0.7). This observation indicated that bromide exhibited, in comparison with the dye tracer, a higher lateral mobility and therefore a more homogeneous distribution in the soil, leading to higher concentrations of bromide also in the NS and NB soil fractions. This can be attributed to both a higher adsorption of the dye in soil and a slower diffusion of the large Brilliant Blue FCF molecule relative to the bromide anion. Dye to bromide concentration ratios exhibited a maximum in the BL fraction of the 5 –10-cm interval and then decreased in all fractions with increasing depth (Table 4). This, in turn, reflects the higher vertical mobility of bromide compared with the dye. For a rough assessment of this phenomenon, we divided for each plot the dye to bromide concentration ratio in 0 – 5 cm soil depth (reflecting both vertical and lateral retardation) by the dye to bromide mass recovery ratio (reflecting only lateral retardation). For either irrigation method, this approach yielded a vertical retardation factor of 1.2 for Brilliant Blue FCF relative to the conservative tracer bromide (and thus to water) in the surface soil. As the adsorption of Brilliant Blue FCF increases with decreasing organic matter content (Ketelsen and Meyer-Windel, 1999), the retardation factor of Brilliant Blue FCF relative to water should increase with soil depth. Thus, as already observed in temperate soils (e.g., Flury and Flu¨hler, 1995), the leading edge of a water front may be missed with Brilliant Blue FCF also in this tropical soil. 3.2. Sorption study Totsche et al. (1997) showed that the presence of dissolved organic matter (DOM) strongly affected the breakthrough behaviour of hydrophobic organic contaminants

Table 3 Soil, tracer, and pesticide mass distributions upon depths and fractions, relative to the total mass found per plot, averaged over all four plots (standard errors in parentheses) Sampling depth (cm) 5 – 10

BL

BL

10 – 20 NB

NS

BL

20 – 30

30 – 40

NB

NS

BL

NB

NS

BL

NB

7.9 (2.7) 5.1 (2.9) 0.89 (0.24) 0.07 (0.05) n.d. 0.19 (0.08) 0.12 (0.02) 0.09 (0.02) 0.12 (0.02) 0.09 (0.02) 0.10 (0.03) n.d. n.d.

6.7 (3.4) 7.1 (4.5) 4.8 (3.4) 0.22 (0.14) 5.5 (4.5) 0.53 (0.35) 0.57 (0.33) 0.60 (0.34) 0.71 (0.51) 0.63 (0.35) 0.35 (0.22) n.d. n.d.

2.6 (2.0) 3.0 (2.2) 3.8 (3.2) 0.08 (0.06) 0.16 (0.16) 0.16 (0.11) 0.12 (0.08) 0.16 (0.12) 0.14 (0.08) 0.17 (0.11) 0.10 (0.07) 0.05 (0.05) n.d.

21.8 (3.5) 8.5 (3.4) 0.91 (0.35) 1.04 (0.35) 5.4 (5.4) 1.01 (0.53) 1.1 (0.85) 0.95 (0.80) 1.5 (1.3) 1.1 (0.9) 0.68 (0.36) n.d. n.d.

2.6 (2.2) 2.3 (2.3) 1.9 (1.9) 0.13 (0.12) 3.6 (3.2) 0.36 (0.34) 0.30 (0.28) 0.37 (0.35) 0.37 (0.35) 0.39 (0.37) 0.27 (0.26) 0.05 (0.05) n.d.

0.73a 0.99a 0.64a 0.004a n.d.a tr.a 0.012a 0.007a 0.009a 0.008a 0.011a n.d.a n.d.a

23.7 (0.5) 1.6 (1.5) 0.07 (0.07) 0.28 (0.20) n.d. 0.36 (0.21) 0.40 (0.10) 0.24 (0.07) 0.49 (0.24) 0.24 (0.06) 0.34 (0.07) n.d. n.d.

(% of total mass found per plot, averaged over all four plots) Soil 10.2 Bromide 24.9 BB FCF 29.6 Trifluralin 85.3 Monocrotophos 55.5 Endosulfan-a 96.2 Simazine 88.5 Atrazine 81.7 Alachlor 85.9 Metolachlor 83.6 Chlorpyrifos 97.6 E-Cyhalothrin 99.6 Deltamethrin 100.0

(0.2) (3.7) (4.6) (7.4) (10.0) (1.1) (3.4) (6.1) (5.1) (6.3) (0.7) (0.4) (0.0)

10.0 (1.3) 23.3 (1.4) 31.1 (3.2) 12.1 (7.7) 24.6 (7.2) 0.76 (0.19) 7.9 (3.6) 14.1 (6.1) 9.7 (5.3) 12.3 (6.2) 0.42 (0.12) n.d. n.d.

BB FCF: Brilliant Blue FCF. BL: blue fraction. NB: nonblue fraction. NS: nonseparable fraction. n.d.: not detectable. tr.: only traces, compound not determinable. a Single fraction occurred only once.

0.72 (0.29) 1.6 (1.0) 0.73 (0.42) 0.11 (0.06) 0.10 (0.10) 0.04 (0.02) 0.05 (0.02) 0.07 (0.03) 0.04 (0.01) 0.06 (0.02) 0.02 (0.01) n.d. n.d.

1.8 (1.3) 6.0 (5.0) 6.2 (5.0) 0.80 (0.74) 3.7 (2.7) 0.19 (0.16) 0.49 (0.36) 0.95 (0.72) 0.42 (0.28) 0.63 (0.43) 0.13 (0.12) 0.46 (0.46) n.d.

13.8 (3.5) 19.5 (3.1) 22.5 (4.8) 0.17 (0.06) 4.3 (2.5) 0.43 (0.09) 0.74 (0.28) 1.2 (0.58) 0.94 (0.42) 1.2 (0.64) 0.20 (0.06) n.d. n.d.

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

0–5

75

76

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

Table 4 Dye to bromide concentration ratios in the plots, normalized to the dye to bromide concentration ratio in the irrigation solutiona (standard errors in parentheses) Depth (cm)

Irrigation method

Fraction BL NB NS Total depth interval (normalized dye to bromide concentration ratio)

0–5

infiltrometer sprinkling can

1.8 (0.0) 1.5 (0.0)

1.8 (0.0) 1.5 (0.0)

n.e. n.e.

n.e. n.e.

5 – 10

infiltrometer sprinkling can

1.8 (0.2) 1.8 (0.1)

1.9 (0.1) 1.8 (0.1)

0.7b 0.7 (0.1)

1.5b 1.7 (0.2)

10 – 20

infiltrometer sprinkling can

1.1 (0.3) 1.3 (0.2)

1.5 (0.5) 1.6 (0.1)

0.4 (0.3) 0.4 (0.3)

0.6 (0.4) 1.3 (0.4)

20 – 30

infiltrometer sprinkling can

0.2b 0.7 (0.6)

1.2 (0.6) 1.4 (0.6)

0.1c 0.2 (0.1)

0.3b 1.2b

30 – 40

infiltrometer sprinkling can

0b 0.1 (0.1)

n.e. 0.9b

0b 0.03 (0.03)

n.e. n.e.

BL: blue fraction. NB: nonblue fraction. NS: nonseparable fraction. n.e.: single fraction not existent. a The dye to bromide concentration ratio in the irrigation solution was 4.17 (g l bromide). b Single fraction occurred only in one replicate. c Quantification of Brilliant Blue FCF was impossible in one replicate.

1

Brilliant Blue FCF/g l

1

(polycyclic aromatic hydrocarbons) in soil columns. Therefore, for a valid interpretation of our pesticide displacement data, it is crucial that Brilliant Blue FCF in the irrigation solution (in a concentration of 5 g l 1, which corresponds to 2.8 g l 1 DOC) did not affect pesticide leaching by cosorption or cosolubilization. Although the probability of dye– pesticide interactions is small due to the high polarity of Brilliant Blue FCF (even in its neutral state Brilliant Blue FCF is an ion with one negative and one positive charge), we conducted a batch experiment to examine the interaction between the dye tracer and the pesticides. This batch experiment showed that the mass recovery of each pesticide in the solution phase was not significantly affected by the presence of Brilliant Blue FCF in the solution (one-way ANOVA, p>0.05; Fig. 2). Pesticide sorption kinetics in the first 24 h after incubation were also not affected by the presence of the dye (data not shown). Apart from the pyrethroids (E-cyhalothrin: 38%; deltamethrin: 49%), which were found only sporadically in the solution phase, the average relative difference in recoveries between dye-containing and dye-free solutions ranged from 5% (monocrotophos) to 16% (chlorpyrifos) of the mass recovery in the solution with KBr only. Total mass recoveries of pesticides in the soil and solution phase were not significantly affected by the presence of Brilliant Blue FCF either. Thus, we concluded that for our field experiment, dye– pesticide interactions can be assumed to be negligible.

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

77

Fig. 2. Pesticide mass recovery in solution for the two batch treatments (KBr; KBr + Brilliant Blue FCF), relative to spiked amount. Error bars denote standard errors (n = 5). BB: Brilliant Blue FCF; MOF: monocrotophos; MET: metolachlor; ALA: alachlor; ATR: atrazine; SIM: simazine; END: endosulfan-a; CLP: chlorpyrifos; TRF: trifluralin; DEL: deltamethrin; LCY: E-cyhalothrin.

3.3. Pesticides Before making inferences about pesticide transport in soil, the mass recoveries of the pesticides have to be discussed. For pesticides, which are subject to several dissipation processes (degradation, volatilization, formation of bound residues), the mass recovery is even more variable than for conservative tracers, and complete mass balances are extremely difficult to obtain (Flury, 1996). The experimental mass recoveries ranged between 66.6 F 15.1% of the applied amount for trifluralin and 8.2 F 0.2% for monocrotophos (data not shown). For comparison, we calculated predicted residues at sampling time, using the site-specific laboratory degradation half-lives (Table 2). For this calculation, we assumed (as an approximation) monoexponential first-order degradation kinetics and uniform degradation rates within the relevant soil depth. Except for monocrotophos (28%), our measured pesticide recoveries totalled 52 – 75% of the predicted recoveries (data not shown), which is likely due to a high temporal and spatial variability of degradation parameters common under field conditions. For the most polar compound monocrotophos, however, some losses due to lateral outflow of irrigation solution may have occurred. Significant pesticide losses due to leaching beyond the

78

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

maximum sampling depth of 40 cm appear unlikely, because in the 30– 40-cm depth interval, the concentrations of all pesticides were already close to the limit of determination, and even bromide recovery in this depth accounted for only 1.9 F 1.8% of the total bromide mass in the soil profile. The mass distribution of pesticides and tracers in the plots (Table 3) provides information about the mobility and the transport behaviour of the applied compounds. The mass portions (normalized to the total mass recovered of the respective compound per plot) retained in the top 5 cm were two to four times higher for pesticides than for tracers. Among pesticides, vertical displacement was most pronounced for monocrotophos, while deltamethrin (KOC>80 000 l kg 1 organic carbon) was never found below 5 cm soil depth. Considering all single fractions of all plots, pesticide mass portions were significantly higher in the BL fraction than in the NB fraction (one-way ANOVA, p < 0.01 for monocrotophos, atrazine, and metolachlor; p < 0.05 for the other seven compounds) and, except for endosulfan-a, chlorpyrifos, E-cyhalothrin, and deltamethrin, were also significantly higher than in the NS fraction ( p < 0.05). This result confirms that the transport paths of the pesticides were traced by the dye. The suitability of a tracer to label the flow paths of pesticides can be assessed by the strength of the correlation between pesticide and tracer mass distributions. In our study, a correlation analysis of pesticide with tracer mass portions in all samples yielded coefficients of determination (r2) of 0.25– 0.54 for bromide and 0.25 –0.55 for Brilliant Blue FCF ( p < 0.001 each), suggesting that up to 75% of the pesticide mass distribution in the soil monolith remained unexplained by the tracer distribution. For both tracers, the tracer-pesticide r2 increased with increasing water solubility (Spearman rank correlation coefficient R = 0.81, p < 0.01) and decreasing KOC (R = 0.83, p < 0.01) of the pesticides. Hence, as expected from the polarity of the tracers, both tracers characterized pesticide transport paths better for polar than for nonpolar compounds. For all pesticides, correlations with the dye tracer were not significantly better than those with the mass distribution of bromide ( p = 0.44– 0.50). Thus, despite its greater physicochemical similarity to the pesticides, Brilliant Blue FCF did not characterize pesticide transport paths better than did bromide. This may be partly due to the problematic quantification of Brilliant Blue FCF at low dye concentrations and at high blank extinctions of samples, as it was frequently the case for NB samples in depths >20 cm. At 10 –30 cm soil depth, concentrations of polar and nonpolar pesticides were 2.0– 3.5 times higher in the NS fraction (representing the dye tracer front) than in the BL fraction, while dye concentrations were still higher in the BL fraction. This difference in pesticide concentrations between NS and BL was significant for endosulfan-a and chlorpyrifos ( p < 0.05). Apparently, the dye tracer front coincided with the displacement front of the (mostly much less polar) pesticides. This again emphasizes the importance of preferential flow phenomena especially for the transport of nonpolar solutes in this tropical soil. Pesticide distribution in soil reflects both the different physicochemical properties of the compounds and the transport regime for water and solutes in the soil. Ranking the pesticides according to the mass portions found below 5 cm depth (u5) showed that vertical displacement increased with decreasing KOC (Spearman R = 0.83, p < 0.01; Fig. 4a) and increasing water solubility (R = 0.82, p < 0.01). This finding reflects that vertical displacement was more pronounced for polar than for nonpolar pesticides. In contrast, relating the ratio of the mass portions below 20 cm and below 5 cm depth (u20/u5) with

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

79

log KOC (Fig. 4b) yielded a completely different result. The u20/u5 quotient is a measure for the minimum contribution of preferential flow transport to the total pesticide displacement in the soil (>5 cm), because pesticides do not significantly leach below 20 cm soil depth by matrix flow transport. The u20/u5 quotient increased with increasing KOC (Spearman R = 0.73, p < 0.05), decreasing water solubility (R = 0.72, p < 0.05) and also with decreasing u5 (R = 0.93, p < 0.001). Hence, the less polar a pesticide and the less pronounced its overall vertical displacement, the higher the portion of its displacement caused by preferential flow transport. This agrees with the findings of Ghodrati and Jury (1992) in a Californian loamy sand. The u20/u5 quotient was 2 –5 times higher for the nonpolar insecticides than for the corn herbicides, reflecting the higher contribution of preferential flow to the displacement of the former. The nonpolar herbicide trifluralin appears to be an exception to this scheme (Fig. 4a and b). Due to its high volatilization tendency (Ru¨del, 1997), it is probable that this compound moves significantly by diffusion in the gas phase of the soil, resulting in a higher vertical displacement relative to other pesticides of similar KOC. To classify the transport behaviour of pesticides, we performed a cluster analysis based on their spatial distribution in the soil monoliths. Using pesticide mass portions in all single fractions (n = 41) as input data and the Euclidean distance as distance measure, tree clustering (StatSoft, 1996) yielded the following four pesticide groups of similar dynamics (Fig. 5a): (i) monocrotophos, (ii) trifluralin, (iii) simazine/atrazine/alachlor/metolachlor, and (iv) endosulfan-a/chlorpyrifos/E-cyhalothrin/deltamethrin. K-means clustering (StatSoft, 1996) with a fixed number of four clusters yielded the same classification. Cluster 1 only contains monocrotophos, a highly polar and water soluble, easily degradable compound. Cluster 2 is formed by the nonpolar, highly volatile herbicide trifluralin. Cluster 3 consists of pesticides with medium polarity (KOC = 123 – 269 for the soil under study), relatively high persistence, and enhanced leaching tendency under can irrigation, which may be called ‘‘corn herbicides’’. The compounds in Cluster 4 can be designated as ‘‘nonpolar insecticides’’ (KOC z 5700). This cluster comprises two subgroups: the extremely nonpolar pyrethroids, which remained immobile in the soil, and endosulfan-a and chlorpyrifos, which exhibited significant vertical displacement by preferential flow transport. Thus, cluster analysis results confirmed our findings about the differences in transport dynamics between the applied pesticides. Hence, apart from KOC (separating three groups of pesticides), vapour pressure (one group) also needs to be considered for predicting short-term depth displacement of pesticides in tropical soils. According to objective (iv), we performed our experiment with two types of infiltration. The tension infiltrometer provided irrigation water at 3.3 cm tension, i.e., pores larger than 0.9 mm in diameter were not filled with water during infiltration. Infiltration was spatially uniform and strictly unsaturated. In contrast, for can irrigation, at some spots, infiltration took occasionally place as ponding infiltration. Thus, rapid, saturated flow along macropores did occur during can irrigation, and even with irrigation as uniform as possible, infiltration was spatially not uniform. Nevertheless, similarly to the tracer compounds, the displacement of most pesticides was not markedly influenced by the type of infiltration. However, vertical displacement of the four corn herbicides (simazine, atrazine, alachlor, metolachlor) was distinctly more pronounced under can than under infiltrometer irrigation (Fig. 3). Under can irrigation, leaching from the top 5 cm was 2.8 – 4.2 times higher for all

80

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

Fig. 3. Mass portions of the corn herbicides in fraction BL for the two irrigation methods at selected depth intervals. Error bars denote standard errors. T: tension infiltrometer irrigation; C: can irrigation; BL: blue fraction.

four compounds than under strictly unsaturated conditions (detailed data not shown). These findings point to a strongly enhanced leaching tendency for the four corn herbicides under heavy rainstorms, like they are common in the study area during the rainy season. 3.4. PEARL simulations The leaching simulations with the PEARL model forecast the vertical displacement of pesticides with the matrix flow in soil, which may be compared with pesticide displacement in our field experiments. A comparison of bromide mass distributions in the soil profile revealed that in the simulation, bromide was leached deeper than in the field. At the sampling date, the simulated bromide mass portion in 30– 40 cm soil depth was 17.1% of the total mass found in the 0 –40-cm depth, vs. 1.9 F 1.8% measured in the field. Of the total bromide applied, 8.5% was leached beyond 40 cm soil depth in the model calculation and 0.04% beyond 70 cm soil depth. The transport of bromide to deeper soil layers in the simulation than in the field may be attributed to the higher percolation rate of water in the simulation, as in the field experiment, substantial losses of irrigation solution occurred due to lateral outflow. Although the infiltration regime in the model represented a worst case in terms of percolate volume, the simulated maximum displacement depths of most pesticides (Table 5) were much shallower than observed in the field. While in the field,

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

81

Table 5 Modelleda bromide and pesticide mass distributions upon depths, relative to the mass present in 0 – 40 cm soil depth 3 days after pesticide application Compound

Depth (cm) 0–5

5 – 10

10 – 20

20 – 30

30 – 40

40 – 70

(% of total compound mass in 0 – 40 cm soil depth 3 days after application) Bromide Trifluralin Monocrotophos Endosulfan-a Simazine Atrazine Alachlor Metolachlor Chlorpyrifos E-Cyhalothrin Deltamethrin a

10.54 99.90 24.93 99.79 69.87 59.81 58.92 45.69 99.87 100.00 100.00

14.35 0.10 34.43 0.21 27.91 34.50 34.68 40.69 0.13 0.00 0.00

30.80 0.00 36.15 0.00 2.22 5.68 6.37 13.54 0.00 0.00 0.00

27.19 0.00 4.24 0.00 0.00 0.01 0.02 0.08 0.00 0.00 0.00

17.12 0.00 0.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

9.26 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Using the leaching model PEARL (Tiktak et al., 2000).

all pesticides except for the pyrethroids (extremely nonpolar) and monocrotophos (rapid dissipation, high detection limit) were found below 30 cm soil depth, in the simulations, only the most polar compound monocrotophos was leached deeper than 30 cm. In the PEARL simulation, both the u5 value and the u20/u5 quotient (see above) regularly increased with decreasing KOC values (Spearman R = 1). The latter result clearly contrasts the results of our field experiment, where the u20/u5 quotient increased with increasing KOC (Fig. 4b). This discrepancy reflects the fact that PEARL considers only matrix flow, while in the field, substantial transport of pesticides by preferential flow occurred. In analogy to the classification of pesticides by their measured distribution in soil (Section 3.3), we also performed a cluster analysis with the simulated depth distribution of the pesticides. Using the pesticide mass portions (in % of total mass found in 0 –40 cm) calculated with PEARL for the depth intervals 0 – 5, 5 – 10, 10– 20, 20 –30, and 30 – 40 cm, tree clustering with the Euclidean distance as distance measure (StatSoft, 1996) yielded only three groups of pesticides (Fig. 5b): (i) monocrotophos, (ii) the four corn herbicides (simazine, atrazine, alachlor, metolachlor), and (iii) all nonpolar compounds with a KOC z 5700. In contrast to the field experiment, in the simulations, trifluralin behaved similar to chlorpyrifos and endosulfan-a despite its higher volatility. Obviously, the substantial transport of this pesticide presumably by gas diffusion was not reflected in the simulations. Furthermore, differences between the mass distributions of the four nonpolar insecticides were much smaller than those observed in the field. The comparison of the two dendrograms (Fig. 5a and b) therefore provides further evidence that pesticide transport in the Oxisol under study was markedly influenced by processes not accounted for in the model, such as preferential flow transport. Since it was not possible to fully reproduce our experimental conditions in the PEARL calculations, the simulation results cannot be used to quantify exactly the amounts of

82

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

Fig. 4. Leaching of pesticides in relation to log KOC. In (a), the degree of leaching is expressed as the pesticide mass portion found below the 5-cm depth (u5) 3 days after application, and in (b) it is expressed as the quotient of the pesticide mass portion found below the 20-cm depth to the portion found below the 5-cm depth (u20/u5). Error bars denote standard errors (n = 4 except for LCY in (b), where n = 2). MOF: monocrotophos; MET: metolachlor; ALA: alachlor; ATR: atrazine; SIM: simazine; END: endosulfan-a; CLP: chlorpyrifos; TRF: trifluralin; DEL: deltamethrin; LCY: E-cyhalothrin.

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

83

Fig. 5. Dendrogram of the applied 10 pesticides resulting from a hierarchical cluster analysis of (a) measured and (b) modelled data. MOF: monocrotophos; ALA: alachlor; MET: metolachlor; ATR: atrazine; SIM: simazine; DEL: deltamethrin; LCY: E-cyhalothrin; CLP: chlorpyrifos; END: endosulfan-a; TRF: trifluralin.

pesticides transported by matrix and by preferential flow in the field. Nevertheless, the simulation results provide a worst-case estimate of pesticide leaching by matrix flow in the Oxisol studied and underline the importance of preferential flow in this soil. For instance, in our field experiment, the nonpolar compounds trifluralin, endosulfan-a, and chlorpyrifos were leached four times as deep as in the worst-case matrix flow scenario simulated with PEARL.

84

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

4. Conclusions This study revealed that: (i) Below the tilled topsoil, Brilliant Blue FCF and bromide infiltrated along preferential flow paths, with the dye being retarded relative to bromide in this Typic Haplustox. (ii) Nevertheless, the flow pattern stained by Brilliant Blue FCF well visualized the flow paths of the pesticides. Thus, it can be used as a guidance for an effective sampling strategy for pesticides in the Oxisol. (iii) It was not possible to quantitatively determine the portion of total pesticide displacement caused by preferential flow transport. Nevertheless, beyond the main dye tracer front at soil tillage depth, transport along preferential flow pathways was obviously responsible for the major portion of total pesticide displacement. This portion was about two to five times higher for the nonpolar than for the polar pesticides. Compared with simulation results in PEARL under worst-case conditions for matrix flow, leaching measured in the field was twice as deep for the medium polar pesticides simazine, atrazine, and alachlor, and four times as deep for the nonpolar pesticides trifluralin, endosulfan-a, and chlorpyrifos. (iv) Differences in irrigation methods only affected the vertical transport of the corn herbicides. For these four compounds, can irrigation with occasional ponding caused enhanced leaching compared with strictly unsaturated infiltrometer irrigation. For the other compounds, soil spatial heterogeneity among plots exerted a stronger influence on solute transport than did the infiltration regime.

Acknowledgements This work was made possible by the cooperation between the University of Bayreuth (Germany) and the Universidade Federal de Mato Grosso (Cuiaba´, MT, Brazil) as part of the SHIFT program (Studies on Human Impact on Forests and Floodplains in the Tropics), financed by the Bundesministerium fu¨r Bildung, Wissenschaft und Forschung (BMBF, Germany) - FKZ 01LT0003/7, the Conselho Nacional de Pesquisa e Tecnologia (CNPq, Brazil), and the Instituto Brasileiro de Meio Ambiente e Recursos Naturais Renova´veis (IBAMA, Brazil). We thank Novartis Crop Protection, Dow Agrosciences, and Aventis CropScience for supplying pesticide standards, and Clariant Deutschland for supplying the dye tracer. For the analysis of bromide, we are indebted to the Bayreuther Institut fu¨r ¨ kologie (BITO ¨ K, Bayreuth, Germany). We also thank Markus Flury and an Terrestrische O anonymous reviewer for their constructive criticism.

References Allaire-Leung, S.E., Gupta, S.C., Moncrief, J.F., 1999. Dye adsorption in a loam soil as influenced by potassium bromide. J. Environ. Qual. 28, 1831 – 1837. Barriuso, E., Calvet, R., 1992. Soil type and herbicides adsorption. Int. J. Environ. Anal. Chem. 46, 117 – 128. Boulding, J.R., 1995. Soil, Vadose Zone, and Groundwater Contamination. Assessment, Prevention, and Remediation. Lewis Publishers, Boca Raton, USA.

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

85

de Andre´a, M.M., Matallo, M.B., Tomita, R.Y., Luchini, L.C., 1997. Effect of temperature on dissipation of 14Catrazine in a Brazilian soil. Pesqui. Agropec. Bras. 32, 95 – 100. Flury, M., 1996. Experimental evidence of transport of pesticides through field soils—a review. J. Environ. Qual. 25, 25 – 45. Flury, M., Flu¨hler, H., 1994. Brilliant blue FCF as a dye tracer for solute transport studies—a toxicological overview. J. Environ. Qual. 23, 1108 – 1112. Flury, M., Flu¨hler, H., 1995. Tracer characteristics of Brilliant blue FCF. Soil Sci. Soc. Am. J. 59, 22 – 27. Flury, M., Flu¨hler, H., Jury, W.A., Leuenberger, J., 1994. Susceptibility of soils to preferential flow of water: a field study. Water Resour. Res. 30 (7), 1945 – 1954. Flury, M., Leuenberger, J., Studer, B., Flu¨hler, H., 1995. Transport of anions and herbicides in a loamy and a sandy field soil. Water Resour. Res. 31 (4), 823 – 835. Funari, E., Barbieri, L., Bottoni, P., Del Carlo, G., Forti, S., Giuliano, G., Marinelli, A., Santini, C., Zavatti, A., 1998. Comparison of the leaching properties of alachlor, metolachlor, triazines and some of their metabolites in an experimental field. Chemosphere 36 (8), 1759 – 1773. Germa´n-Heins, J., Flury, M., 2000. Sorption of Brilliant Blue FCF in soils as affected by pH and ionic strength. Geoderma 97, 87 – 101. Ghodrati, M., Jury, W.A., 1990. A field study using dyes to characterize preferential flow of water. Soil Sci. Soc. Am. J. 54, 1558 – 1563. Ghodrati, M., Jury, W.A., 1992. A field study of the effects of soil structure and irrigation method on preferential flow of pesticides in unsaturated soil. J. Contam. Hydrol. 11, 101 – 125. Gillman, G.P., 1985. Influence of organic matter and phosphate content on point of zero charge of variable charge components in oxidic soils. Aust. J. Soil Res. 25, 643 – 646. Goedert, W.J., 1983. Management of the Cerrado soils of Brazil: a review. J. Soil Sci. 34, 405 – 428. Hartley, D., Kidd, H., 1987. The Agrochemicals Handbook, 2nd edn. The Royal Society of Chemistry Information Service, University of Nottingham. Unwin Brothers, Old Woking/Surrey, UK. Hornsby, A.G., Wauchope, R.D., Herner, A.E., 1996. Pesticide Properties in the Environment. Springer-Verlag, New York. Ketelsen, H., Meyer-Windel, S., 1999. Adsorption of Brilliant Blue FCF by soils. Geoderma 90, 131 – 145. Laabs, V., Amelung, W., Zech, W., 1999. Multi-residue analysis of corn and soybean pesticides in Brazilian Oxisols using gas chromatography and mass selective detection. J. Environ. Qual. 28, 1778 – 1786. Laabs, V., Amelung, W., Pinto, A., Altstaedt, A., Zech, W., 2000. Leaching and degradation of corn and soybean pesticides in an Oxisol of the Brazilian Cerrados. Chemosphere 41, 1441 – 1449. Laabs, V., Amelung, W., Fent, G., Zech, W., Kubiak, R., 2002. Fate of 14C-labeled soybean and corn pesticides in tropical soils of Brazil under laboratory conditions. J. Agric. Food Chem., in press. 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. Nakagawa, L.E., Luchini, L.C., Musumeci, M.R., Matallo, M., 1996. Behavior of atrazine in soils of tropical zone. Degradation, mobility and uptake of atrazine residues from soils in a crop rotation system (maize/ beans). J. Environ. Sci. Health, B 31 (2), 203 – 224. Perillo, C.A., Gupta, S.C., Nater, E.A., Moncrief, J.F., 1998. Flow velocity effects on the retardation of FD and C Blue no. 1 food dye in soil. Soil Sci. Soc. Am. J. 62, 39 – 45. Ru¨del, H., 1997. Volatilisation of pesticides from soil and plant surfaces. Chemosphere 35, 143 – 152. Schaap, M.G., 1999. Rosetta Version 1.0. U.S. Salinity Laboratory, Riverside, CA. Schachtschabel, P., Blume, H.-P., Bru¨mmer, G., Hartge, K.-H., Schwertmann, U., 1992. Scheffer/Schachtschabel: Lehrbuch der Bodenkunde. Ferdinand Enke Verlag, Stuttgart, Germany (In German). Schwartz, R., Juo, A., McInnes, K., Cervantes, C., 1998. Anion transport in a fine-textured Ultisol in Costa Rica. Proceedings of the 16th World Congress of Soil Science in Montpellier, France, August 20 – 26. Symp. No. 5, scientific registration number 1773. ISSS, CD-ROM, n Cirad, 1998. Soil Survey Staff, 1998. Keys to Soil Taxonomy, 8th edn. Pocahontas Press, Blacksburg, VA, USA. StatSoft, 1996. Statistica for Windows, Version 5.1: User Manual. StatSoft, Tulsa, OK. Tiktak, A., van den Berg, F., Boesten, J.J.T.I., Leistra, M., van der Linden, A.M.A., van Kraalingen, D., 2000. Pesticide Emission Assessment at Regional and Local Scales: User Manual of FOCUS Pearl version 1.1.1. RIVM Report 711401008, Alterra Report 28. RIVM, Bilthoven, NL.

86

S. Reichenberger et al. / Geoderma 110 (2002) 63–86

Totsche, K.U., Danzer, J., Ko¨gel-Knabner, I., 1997. Dissolved organic matter-enhanced retention of polycyclic aromatic hydrocarbons in soil miscible displacement experiments. J. Environ. Qual. 26, 1090 – 1100. van Genuchten, M.Th., 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J. 44, 892 – 898. van Raij, B., Peech, M., 1972. Electrochemical properties of some Oxisols and Alfisols of the tropics. Soil Sci. Soc. Am. Proc. 36, 587.