- Email: [email protected]
Implication of spatial variability of organic carbon on predicting pesticide mobility in soil
GEODE.P~MA ELSEVIER
Geoderma65 (1995) 331-338
Implication of spatial variability of organic carbon on predicting pesticide mobility in soil P. Lafrance *, O. Banton INRS-Eau, Universit~ du Qudbec, 2800 rue Einstein, C.P. 7500, Sainte-Foy, Quebec, Canada, G1V 4C7
Received 23 December1993;acceptedafterrevision 18 July 1994
Abstract In this study, the depth distribution of organic carbon (OC) content in a sandy soil was characterized for a small agricultural plot ( 1.5 ha). The means and the distributions for measured OC were used as sorption-related parameters in a solute transport model to predict the movement of the herbicide atrazine in the unsaturated zone. Simulations were performed in order to assess the impact of OC variability in the evaluation of the herbicide concentration reaching the water table. The frequency distributions for soil OC at various depth intervals followed typical normal laws. The value for the coefficient of variation was lower at the first depth interval than at deeper soil intervals, possibly as a result of soil tillage practices. In predicting pesticide transport, the deterministic approach was shown to be sensitive to the variability of the soil sorption coefficient controlled by OC content. However a stochastic approach showed that in actual field situations, the in situ variability of soil parameters that control the soil-water flow could have a greater influence than the sorption-related parameter such as OC content. In this case, the field characterization of the horizontal distribution of OC may not improve the representativeness of the simulation results.
I. Introduction
Use of stochastic procedures to evaluate pesticide transport in agricultural soils (Nielsen et al., 1986; Carsel et al., 1988a, b) require the characterization of the field distributions of the soil chemical properties (e.g., organic carbon content) that affect solute migration via sorption processes (Jury, 1986; Wagenet, 1986). However, the horizontal distribution and the depth-variation for the organic carbon content have rarely been characterized in solute transport studies applicable to small scale agricultural areas (Rao et al., 1986). Soil organic carbon content is widely used in transport models to estimate the adsorption ( soil-water distribution coefficient) and the retardation factor for pesticide transport (Wa* Corresponding author. 0016-7061/95/$9.50 © 1995 ElsevierScienceB.V. All rights reserved SSDIO016-7061 (94) 00051-4
332
P. Lafrance, O. Banton / Geoderma 65 (1995) 331-338
genet and Rao, 1990). Stochastic modelling of the processes that control the fate of pesticides is best suited for the evaluation of the quantity of contaminant likely to reach the water table. This is because a stochastic approach takes into account the spatial variability of the physical, hydrodynamic, and physico-chemical characteristics of the soil. The VULPEST model (Villeneuve et al., 1990; Banton et al., 1992b) is an example of a tool for the evaluation of groundwater contamination by pesticides based on stochastic modelling of solute transport. It was used in this study to evaluate the impact of variations in the sorptionrelated input parameters on the simulated results of pesticide transport in the soil. The VULPEST model simulates pesticide transport through the unsaturated soil zone, integrating advection, dispersion (by a stochastic approach), adsorption and degradation. The model uses an analytical solution of the partial differential equation. The VULPEST model performs up to 1000 transport simulations, each with parameters randomly chosen by the software. The user of the model chooses the type of statistical distribution to be applied to the random selections. In this study, the statistical distribution for the soil organic carbon content was determined by field measurements. The Monte Carlo procedure allows for the simulation of the wide range of conditions that can be encountered at the site. The final result is not a single average quantity, but rather a series of quantities resulting from a great number of combinations of parameter values.
2. Methods and techniques 2.1. Sampling and analysis
The study site (Fig. 1) is managed by the Quebec Department of Agriculture and is located at St-Augustin-de-Desmaures, Portneuf County (25 km west of Quebec City, Canada). The size of the sampled area, 1.5 ha, was typical of other sites undergoing both unsaturated and saturated soil monitoring for pesticide contamination (Jones, 1990). The soil is classified as St-Antoine series, an Orthic Humo-Ferric Podzol (Haplorthod). Its texture ranges from fine to a gravelly sandy loam. Since 1987, the site has been seeded to Zea mays (corn) and Solanum tuberosum (potato) in plots which have changed in size and location from one year to another. Fig. l presents the approximate location of the corn (in sampling series 1) and potato plots (in sampling series 2 and 3) in 1989; the other parts were fallow land. Annual tillage was carried out in September 1988 and 1989 to a depth of 7-13 cm. Chemical fertilization for corn (series 1) consisted of 567 kg h a - ~ of 8-16-8 ( N - P - K ) and was applied to the furrows at the time of planting (late May 1988 and 1989). Fertilizer for potato crops ( series 2 and 3) consisted of 1700 kg ha -1 and 1400 kg ha l of 8-12-12 ( N - P - K ) , applied to the furrows at the time of planting during May 1988 and 1989, respectively. The herbicide atrazine was applied at the recommended rate of 1.6 kg ha- l in June of each year on a plot seeded to corn (series I). The soil sampling was carried out at three depth intervals following a regular grid pattern (Fig. 1). Soil samples were taken from series 1 in June 1988 and from series 2 and 3 in June 1989. The sampling locations were spaced 15 × 6 m apart in series 1 and 2 and 15 × 12 m apart in series 3. A total of 110 points sampled at three depths yielded 330 soil samples.
P. Lafrance, O. Banton/ Geoderma 65 (1995) 331-338
Op •
• •
~ ~
//e2/H/)i////lff
I
"
•
• • ~.~ •
o~.
P
°
•
•
•
•
///////F////J~ • •
•
@
•
•y///AI¢lll%////I////lO
•
•
•
•
•
•
•
SCALE : O , I
•
O
•
•
P"
•
•
.
i
2,5
i
r
5Ore i
•
"////:/I///~////u////_//J •
• •
•
/I/4r//I/|////t////~l'~ °
333
: NUMBERS CROP IN C : CORN
ARE SAMPLING SERIES 1989 ,,,,,,,H,, )
POTATO
.
I/ I / I/ g.
•
•
H H H
•
•
•
"I~46° 70"
Fig. 1. Location of the studied site and distribution of sampling points (dots) at St-Augustin-de-Desmaures (Quebec. Canada). The depth intervals were located at 5-15 cm, 40-50 cm and 85-95 cm below the ground surface, corresponding to horizons A, B and C, respectively. Soil samples were obtained using a hand auger (diameter: 10 cm) and chemical analyses were performed after ovendrying at 65°C for 16 hours and sieving to less than 2 mm. The total carbon (C) content was determined using a NCS Analyzer Carlo Erba (model MA 1500). Prior to analysis, 10 g of homogenized soil from each sample were ground using an agate mortar and then a 5 to 10 mg subsample ( < 180/zm) was removed for analysis. Certified carbon standard, a reference marine sediment with 29.9 _ 0.9 g k g - ~ C (MESS-I, Inst. Environ. Chem., Nat. Res. Council Canada, Ottawa), was used after every 10th soil sample to control the quality of the analysis. Carbon standards (Carlo Erba) were used for the calibration of the apparatus. The relative limit of precision for 5 measurements on 10 mg samples containing 15 g k g - ~carbon was 0.6%. The relative detection limit for 10 measurements made on 10 mg soil samples was 0.5 g k g - ~for C. Results were expressed on a soil dry weight basis. All of the soil horizons were acidic with mean pH values (for 10 determinations) of 5.65, 5.27 and 5.87, respectively, for horizons A, B and C. It could be assumed that no free carbonate was present and that the total carbon (C) determined with the NCS Analyzer was entirely organic carbon (OC). The measured C content was thus considered to be a direct estimate of the OC content.
334
P. Lafrance, O. Banton / Geoderma 65 (1995) 331-338
The statistical moments of the OC variable (mean, standard deviation and coefficient of variation) were calculated as a function of soil depth. Statistics were performed using " S t a t g r a p h i c s " software (version 3; STSC Plus*Ware, Rockvill, MA, U S A ) . 2.2. Simulation o f herbicide transport (VULr'EST model)
The values for measured OC were used in deterministic and stochastic approaches to estimate the transport of the herbicide atrazine in the unsaturated zone. Atrazine (solubility: 33 mg 1- ~ at 20°C) is a widely used systemic herbicide of the s-triazine group; its detection in groundwater is commonly 10 to 20 times more frequent than the next most frequently detected pesticide (Belluck et al., 1991 ). The stochastic VULPEST model requires a number of parameters related to soil, pesticides, crops and climate. The soil parameters include: depth to the water table and, for each horizon, the thickness, hydraulic conductivity, OC content, porosity and soil density. The pesticide parameters include: rate, day and depth of application, solubility, soil distribution coefficient (determined from OC content) and degradation constant. The crop parameters include the dates of emergence and maturation and the water requirements. Monthly averages for rain, snow, evaporation and temperature are needed. The simulations of atrazine transport were performed under the field conditions encountered at the site. The physical and hydraulic soil parameters (Table 1 ) are those determined by Banton et al. (1992a). For these parameters, undisturbed soil core samples (60 mm length and 53 mm in diameter) were collected over a regular grid using a soil sampler driven into the ground with a hammer. The soil texture was determined by grain size curves and hydrometer sedimentometry of the fraction < 2 mm; the porosity and the field capacity were determined as the water saturated content and the gravity retained moisture content; the bulk density was determined from soil dry weight; the saturated hydraulic conductivity was evaluated by Darcy's method (Sheldrick, 1984). Table 1 Statistical characteristics [mean (standard deviation)] for soil parameters used for the simulation of atrazine transport Parameter
Sand (%) Silt (%) Clay (%) Porosity (%) Field capacity (%) Bulk density (Mg m- 3) Hydraulic conductivitya ( × 10_6 m s t ) Degradation rate coefficient (day ~)
Horizons (depths) 0-35 cm
35-75 cm
> 75 cm
53.3 (3.0) 25.1 (2.0) 21.6 (2.4) 46.7 (7.7) 42.6 (5.8) 1.50 ( 0.11 ) 30.8 (83.4) 0.015h
54.6 (7.6) 25.9 (3.8) 19.5 (4.9) 46.5 (5.4) 44.7 (5.3) 1.42 (0.15) 55.9 (120) 0.01 Ic
66.6 (7.2) 18.8 (4.7) 14.5 (3.6) 45.3 (6.7) 43.2 (6.9) 1.50 (0.16) 54.4 (190) 0.006c
aMean and standard deviation adjusted for a log-normaldistribution. bMeasured in the field ( 0 - 10 cm) following herbicide application. CEstimatedvalues.
P. Lafrance, O. Banton/ Geoderma65 (1995) 331-338
335
The atrazine concentrations were calculated for the 1.6 m depth. A vertical variability for the atrazine degradation rate constant (k) was considered in order to account for the decrease in bioactivity with depth. For the first soil layer, the k value was 0.015 day- Tas measured in the field (0-10 cm) following the application of atrazine in June 1990. For the other soil layers, k values were attributed according to the assumption that the vertical variation for k is the same as the one for OC (i.e., bioactivity is well correlated with soil OC). A first set of simulations was performed to evaluate the impact of soil OC variability when using a deterministic approach for the other parameters (means for hydraulic conductivity and soil physical properties). The objective was to evaluate the sensitivity of the modelling to the variability of OC alone. The simulations consisted of finding the deterministic analytical solution of the transport equation which includes the dispersion term (Van Genuchten and Alves, 1982). The dispersivity used was 10 cm, a value representative of the soil conditions encountered in this study. The pore-water velocity was calculated with Darcy's law using the unsaturated hydraulic conductivity corresponding to the mean soil water content during the period of simulation. The cubic relation used to calculate the unsaturated hydraulic conductivity (Ku) from the measured saturated hydraulic conductivity (Ks) was the one proposed by Irmay (1954 in Bear, 1972): Ku=Ks [ ( w . c . - f . c . ) / (n--f.c.)] 3, where w.c. is the mean water content, f.c. is the field capacity and n is the porosity. The sorption-related input parameters were the mean and the distribution for the measured OC content. The OC content was used to estimate the soil-water partition coefficient (KD) which represents the extent of sorption for hydrophobic contaminants including many pesticides. A second set of simulations was performed to evaluate the impact of soil OC variability when using a stochastic approach (VULPESTmodel) for all the model parameters (distributions for hydraulic conductivity and soil physical properties). The objective was to evaluate the relative impact of OC variability when considering the variability of the other transport parameters. The sorption-related input parameters were the same as those used in the first set of simulations. 3. Results 3.1. Distributions for organic carbon
The frequency distributions (not shown) indicate that the OC variable is normally distributed. Such normality was observed for the various depth intervals as well as for the totality of the samples ( i.e., considering all the results obtained from each one of the 3 depth intervals). Table 2 summarizes the statistics for the variability of OC. The CV value is lower at the first depth interval than at deeper soil intervals indicating a lower variability of OC, perhaps as a result of the soil tillage practices. Moreover, the greater CV value at lower depths could be explained by the lower mean values, causing the technical errors in measurement to become relatively more important in absolute value. 3.2. Effect of sorption variability on predicting atrazine transport
The results obtained from the VULPESTmodel are the stochastic breakthrough curves, i.e., the distribution over time of concentrations (resulting from Monte Carlo simulations)
336
P. Lafrance, O. Banton / Geoderma 65 (1995) 331-338
Table 2 Statistics for the OC variable at each depth interval and for the totality of the samples Depth (cm)
Mean ( g k g t)
SD"
CV h
5-15 40-50 85-95 Totality
19.0 9.4 5.5 13.6
5.7 4.4 3.0 7.4
0.30 0.47 0.55 0.54
"Standard deviation. bCoefficient of variation = SD/mean.
reaching a given surface such as the water table. Fig. 2 shows the effect of OC variability on the breakthrough curve for atrazine when using a deterministic approach (constant values) or a stochastic approach (distributions) for the other input parameters. For the deterministic approach (analytical solution), the result obtained from the mean OC shows a greater peak concentration and a larger peak arrival time for atrazine than those obtained from distributed OC. Also, the curve obtained from the mean is symmetrical whereas the one obtained from the distribution is asymmetrical with earlier breakthrough and increased time for elution at the front tailing. In comparison with the mean, the distribution show a decrease in the peak arrival time (10%) and in the peak concentration (60%). Thus, the primary effect of distributed values for OC is a "spreading" of the concentration zone in the soil profile which results in a smaller peak reaching the water table during a longer period of time. For the stochastic approach (VULPESTmodel), Fig. 2 shows the effect of OC variability on the atrazine breakthrough curve when using actual distributions for the other transport parameters. The main result of these simulations is the apparent insensitivity of the breakthrough curve to the use of the mean or the distribution for OC. This insensitivity of the model to variations in OC results mainly from the significant effect of the variability of 5.0
4.0
I / I
~-
-
Analyt.
&
mean
OC
Anaty f,
& disfr.
OC
3.0 E 0 o--
I I
"~
0 1.0
---
20
25
30
35
Vulpest
40
45
&
Date (weeks)
mean
OC
50
55
60
Fig. 2. Effect of the use of mean or distribution of OC on the simulated breakthrough curve for atrazine for both the deterministic approach (analytical solution) and the stochastic approach (VULPEST model),
P. Lafrance, O. Banton/ Geoderma 65 (1995) 331-338
337
other parameters. Indeed, the CV for OC measured in this study was generally smaller than 0.5 (Table 2). Some other soil properties exhibit higher variations, for example hydraulic conductivity with a CV near 3.5. Such a large variability plays a major role in the control of the pore-water velocity and has a much greater impact on the simulated results than the variations in OC content. In a stochastic approach, the spatial heterogeneity of the parameters controlling the soil-water flow may hide the effect of the variations of the sorption-related parameters on solute transport.
4. Conclusion The representativeness of the modelling results in the evaluation of subsurface solute migration may be affected by the field variations in soil organic carbon. The deterministic approach is sensitive to the variability of the soil sorption coefficient controlled by the organic carbon content; the use of the mean value, instead of the distribution, could result in an overestimation of the herbicide concentration reaching the water table and hence a higher predicted vulnerability of groundwater to contamination. The application of a stochastic approach in predicting pesticide transport showed that in actual field situations, the in situ variability of the soil parameters that control the soil-water flow could be greater than that of the sorption-related parameters such as organic carbon. In this case, the field characterization of the horizontal distribution for organic carbon may not improve the representativeness of the simulation results.
Acknowledgements We are grateful to Lise Gauthier from the Quebec Department of Agriculture for providing information and facilities on the site. This study was funded by the Natural Sciences and Engineering Research Council of Canada.
References Banton, O., Lafrance, P., Martel, R. and Villeneuve, J.P., 1992a. Planning of soil-pore water sampling campaigns using pesticide transport modeling. Ground Water Monit. Rev., Aug., 1992: 195-202. Banton, O., Lafrance, P. and Villeneuve, LP., 1992b. D61imitation des p6rim~tres de protection des puits de pompage en zone agricole h l'aide de la simulation math6matique. Rev. Sci. I' Eau, 5:211-227. Bear, J., 1972. Dynamics of Fluids in Porous Media. Dover, New York, NY, 764 pp. Belluck, D.A., Benjamin, S.L. and Dawson, T., 1991. Groundwater contamination by atrazine and its metabolites. In: L. Somasundaram and J.R. Coats (Editors), Pesticide Transformation Products. Fate and Significance in the Environment. Am. Chem. Soc. Symp. Series 459, Washington, DC, pp. 254-273. Carsel, R.F., Parrish, R.S., Jones, R.L., Hansen, J.L. and Lamb, R.L., 1988a. Characterizing the uncertainty of pesticide leaching in agricultural soils. J. Contam. Hydrol., 2:111-124. Carsel, R.F., Jones, R.L., Hansen, J.L., Lamb, R.L. and Anderson, M.P., 1988b. A simulation procedure for groundwater quality assessments of pesticides. J. Contain. Hydrol., 2: 125-138. Jones, R.L., 1990. Pesticides in groundwater: Conduct of field research studies. In: D.H. Hudson and T.R. Roberts (Editors), Environmental Fate of Pesticides. Series Progress in Pesticide Biochemistry and Toxicology, Vol. 7, pp. 27-46.
338
P. Lafrance, O. Banton / Geoderma 65 (1995) 331-338
Jury, W.A., 1986. Spatial variability of soil properties. In: S.C. Hem and S.M. Melancon (Editors), Vadose Zone Modeling of Organic Pollutants. Lewis, Chelsea, MI, pp. 245-269. Nielsen, D.R., Van Genuchten, M.Th. and Biggar, LW., 1986. Water flow and solute transport processes in the unsaturated zone. Water Resour. Res., 22: 895-1086. Rao, P.S.C., Edvardsson, K.S.V., Ou, L.T., Jessup, R.E., Nkedi-Kizza, P. and Hornsby, A.G., 1986. Spatial variability of pesticide sorption and degradation parameters. In: W.Y. Garner, R.C. Honeycutt and H.N. Nigg (Editors), Evaluation of Pesticides in Ground Water. Am. Chem. Soc. Symp. Series 315, Washington, DC, pp. 100-115. Sheldrick, B.H., 1984. Analytical Methods Manual 1984. Land Resource Research Institute, Agriculture Canada, Research Branch, LRRI No 84-30, Ottawa, Ont. Van Genuchten, M.Th. and Alves, W.J., 1982. Analytical solutions of the one-dimensional convective-dispersive solute transport equation. U.S. Salinity Lab., Riverside, CA. Villeneuve, J.P., Banton, O. and Lafrance, P., 1990. A probabilistic approach lbr the groundwater vulnerability to contamination by pesticides: the VULPEST model. Ecol. Modelling, 51 : 47-58. Wagenet, R.J., 1986. Principles of modeling pesticide movement in the unsaturated zone. In: W.Y. Garner, R.C. Honeycutt and H.N. Nigg (Editors), Evaluation of Pesticides in Ground Water. Am. Chem. Soc. Symp. Series 315, Washington, DC, pp. 330--341. Wagenet, R.J. and Rao, P.S.C., 1990. Modeling pesticide fate in soils. In: H.H. Cheng (Editor), Pesticides in the Soil Environment: Processes, Impacts, and Modeling. Soil Sci. Soc. Am. Book Series, 2. Soil Sci. Soc. Am., Madison, WI, pp. 351-399.
Geoderma65 (1995) 331-338
Implication of spatial variability of organic carbon on predicting pesticide mobility in soil P. Lafrance *, O. Banton INRS-Eau, Universit~ du Qudbec, 2800 rue Einstein, C.P. 7500, Sainte-Foy, Quebec, Canada, G1V 4C7
Received 23 December1993;acceptedafterrevision 18 July 1994
Abstract In this study, the depth distribution of organic carbon (OC) content in a sandy soil was characterized for a small agricultural plot ( 1.5 ha). The means and the distributions for measured OC were used as sorption-related parameters in a solute transport model to predict the movement of the herbicide atrazine in the unsaturated zone. Simulations were performed in order to assess the impact of OC variability in the evaluation of the herbicide concentration reaching the water table. The frequency distributions for soil OC at various depth intervals followed typical normal laws. The value for the coefficient of variation was lower at the first depth interval than at deeper soil intervals, possibly as a result of soil tillage practices. In predicting pesticide transport, the deterministic approach was shown to be sensitive to the variability of the soil sorption coefficient controlled by OC content. However a stochastic approach showed that in actual field situations, the in situ variability of soil parameters that control the soil-water flow could have a greater influence than the sorption-related parameter such as OC content. In this case, the field characterization of the horizontal distribution of OC may not improve the representativeness of the simulation results.
I. Introduction
Use of stochastic procedures to evaluate pesticide transport in agricultural soils (Nielsen et al., 1986; Carsel et al., 1988a, b) require the characterization of the field distributions of the soil chemical properties (e.g., organic carbon content) that affect solute migration via sorption processes (Jury, 1986; Wagenet, 1986). However, the horizontal distribution and the depth-variation for the organic carbon content have rarely been characterized in solute transport studies applicable to small scale agricultural areas (Rao et al., 1986). Soil organic carbon content is widely used in transport models to estimate the adsorption ( soil-water distribution coefficient) and the retardation factor for pesticide transport (Wa* Corresponding author. 0016-7061/95/$9.50 © 1995 ElsevierScienceB.V. All rights reserved SSDIO016-7061 (94) 00051-4
332
P. Lafrance, O. Banton / Geoderma 65 (1995) 331-338
genet and Rao, 1990). Stochastic modelling of the processes that control the fate of pesticides is best suited for the evaluation of the quantity of contaminant likely to reach the water table. This is because a stochastic approach takes into account the spatial variability of the physical, hydrodynamic, and physico-chemical characteristics of the soil. The VULPEST model (Villeneuve et al., 1990; Banton et al., 1992b) is an example of a tool for the evaluation of groundwater contamination by pesticides based on stochastic modelling of solute transport. It was used in this study to evaluate the impact of variations in the sorptionrelated input parameters on the simulated results of pesticide transport in the soil. The VULPEST model simulates pesticide transport through the unsaturated soil zone, integrating advection, dispersion (by a stochastic approach), adsorption and degradation. The model uses an analytical solution of the partial differential equation. The VULPEST model performs up to 1000 transport simulations, each with parameters randomly chosen by the software. The user of the model chooses the type of statistical distribution to be applied to the random selections. In this study, the statistical distribution for the soil organic carbon content was determined by field measurements. The Monte Carlo procedure allows for the simulation of the wide range of conditions that can be encountered at the site. The final result is not a single average quantity, but rather a series of quantities resulting from a great number of combinations of parameter values.
2. Methods and techniques 2.1. Sampling and analysis
The study site (Fig. 1) is managed by the Quebec Department of Agriculture and is located at St-Augustin-de-Desmaures, Portneuf County (25 km west of Quebec City, Canada). The size of the sampled area, 1.5 ha, was typical of other sites undergoing both unsaturated and saturated soil monitoring for pesticide contamination (Jones, 1990). The soil is classified as St-Antoine series, an Orthic Humo-Ferric Podzol (Haplorthod). Its texture ranges from fine to a gravelly sandy loam. Since 1987, the site has been seeded to Zea mays (corn) and Solanum tuberosum (potato) in plots which have changed in size and location from one year to another. Fig. l presents the approximate location of the corn (in sampling series 1) and potato plots (in sampling series 2 and 3) in 1989; the other parts were fallow land. Annual tillage was carried out in September 1988 and 1989 to a depth of 7-13 cm. Chemical fertilization for corn (series 1) consisted of 567 kg h a - ~ of 8-16-8 ( N - P - K ) and was applied to the furrows at the time of planting (late May 1988 and 1989). Fertilizer for potato crops ( series 2 and 3) consisted of 1700 kg ha -1 and 1400 kg ha l of 8-12-12 ( N - P - K ) , applied to the furrows at the time of planting during May 1988 and 1989, respectively. The herbicide atrazine was applied at the recommended rate of 1.6 kg ha- l in June of each year on a plot seeded to corn (series I). The soil sampling was carried out at three depth intervals following a regular grid pattern (Fig. 1). Soil samples were taken from series 1 in June 1988 and from series 2 and 3 in June 1989. The sampling locations were spaced 15 × 6 m apart in series 1 and 2 and 15 × 12 m apart in series 3. A total of 110 points sampled at three depths yielded 330 soil samples.
P. Lafrance, O. Banton/ Geoderma 65 (1995) 331-338
Op •
• •
~ ~
//e2/H/)i////lff
I
"
•
• • ~.~ •
o~.
P
°
•
•
•
•
///////F////J~ • •
•
@
•
•y///AI¢lll%////I////lO
•
•
•
•
•
•
•
SCALE : O , I
•
O
•
•
P"
•
•
.
i
2,5
i
r
5Ore i
•
"////:/I///~////u////_//J •
• •
•
/I/4r//I/|////t////~l'~ °
333
: NUMBERS CROP IN C : CORN
ARE SAMPLING SERIES 1989 ,,,,,,,H,, )
POTATO
.
I/ I / I/ g.
•
•
H H H
•
•
•
"I~46° 70"
Fig. 1. Location of the studied site and distribution of sampling points (dots) at St-Augustin-de-Desmaures (Quebec. Canada). The depth intervals were located at 5-15 cm, 40-50 cm and 85-95 cm below the ground surface, corresponding to horizons A, B and C, respectively. Soil samples were obtained using a hand auger (diameter: 10 cm) and chemical analyses were performed after ovendrying at 65°C for 16 hours and sieving to less than 2 mm. The total carbon (C) content was determined using a NCS Analyzer Carlo Erba (model MA 1500). Prior to analysis, 10 g of homogenized soil from each sample were ground using an agate mortar and then a 5 to 10 mg subsample ( < 180/zm) was removed for analysis. Certified carbon standard, a reference marine sediment with 29.9 _ 0.9 g k g - ~ C (MESS-I, Inst. Environ. Chem., Nat. Res. Council Canada, Ottawa), was used after every 10th soil sample to control the quality of the analysis. Carbon standards (Carlo Erba) were used for the calibration of the apparatus. The relative limit of precision for 5 measurements on 10 mg samples containing 15 g k g - ~carbon was 0.6%. The relative detection limit for 10 measurements made on 10 mg soil samples was 0.5 g k g - ~for C. Results were expressed on a soil dry weight basis. All of the soil horizons were acidic with mean pH values (for 10 determinations) of 5.65, 5.27 and 5.87, respectively, for horizons A, B and C. It could be assumed that no free carbonate was present and that the total carbon (C) determined with the NCS Analyzer was entirely organic carbon (OC). The measured C content was thus considered to be a direct estimate of the OC content.
334
P. Lafrance, O. Banton / Geoderma 65 (1995) 331-338
The statistical moments of the OC variable (mean, standard deviation and coefficient of variation) were calculated as a function of soil depth. Statistics were performed using " S t a t g r a p h i c s " software (version 3; STSC Plus*Ware, Rockvill, MA, U S A ) . 2.2. Simulation o f herbicide transport (VULr'EST model)
The values for measured OC were used in deterministic and stochastic approaches to estimate the transport of the herbicide atrazine in the unsaturated zone. Atrazine (solubility: 33 mg 1- ~ at 20°C) is a widely used systemic herbicide of the s-triazine group; its detection in groundwater is commonly 10 to 20 times more frequent than the next most frequently detected pesticide (Belluck et al., 1991 ). The stochastic VULPEST model requires a number of parameters related to soil, pesticides, crops and climate. The soil parameters include: depth to the water table and, for each horizon, the thickness, hydraulic conductivity, OC content, porosity and soil density. The pesticide parameters include: rate, day and depth of application, solubility, soil distribution coefficient (determined from OC content) and degradation constant. The crop parameters include the dates of emergence and maturation and the water requirements. Monthly averages for rain, snow, evaporation and temperature are needed. The simulations of atrazine transport were performed under the field conditions encountered at the site. The physical and hydraulic soil parameters (Table 1 ) are those determined by Banton et al. (1992a). For these parameters, undisturbed soil core samples (60 mm length and 53 mm in diameter) were collected over a regular grid using a soil sampler driven into the ground with a hammer. The soil texture was determined by grain size curves and hydrometer sedimentometry of the fraction < 2 mm; the porosity and the field capacity were determined as the water saturated content and the gravity retained moisture content; the bulk density was determined from soil dry weight; the saturated hydraulic conductivity was evaluated by Darcy's method (Sheldrick, 1984). Table 1 Statistical characteristics [mean (standard deviation)] for soil parameters used for the simulation of atrazine transport Parameter
Sand (%) Silt (%) Clay (%) Porosity (%) Field capacity (%) Bulk density (Mg m- 3) Hydraulic conductivitya ( × 10_6 m s t ) Degradation rate coefficient (day ~)
Horizons (depths) 0-35 cm
35-75 cm
> 75 cm
53.3 (3.0) 25.1 (2.0) 21.6 (2.4) 46.7 (7.7) 42.6 (5.8) 1.50 ( 0.11 ) 30.8 (83.4) 0.015h
54.6 (7.6) 25.9 (3.8) 19.5 (4.9) 46.5 (5.4) 44.7 (5.3) 1.42 (0.15) 55.9 (120) 0.01 Ic
66.6 (7.2) 18.8 (4.7) 14.5 (3.6) 45.3 (6.7) 43.2 (6.9) 1.50 (0.16) 54.4 (190) 0.006c
aMean and standard deviation adjusted for a log-normaldistribution. bMeasured in the field ( 0 - 10 cm) following herbicide application. CEstimatedvalues.
P. Lafrance, O. Banton/ Geoderma65 (1995) 331-338
335
The atrazine concentrations were calculated for the 1.6 m depth. A vertical variability for the atrazine degradation rate constant (k) was considered in order to account for the decrease in bioactivity with depth. For the first soil layer, the k value was 0.015 day- Tas measured in the field (0-10 cm) following the application of atrazine in June 1990. For the other soil layers, k values were attributed according to the assumption that the vertical variation for k is the same as the one for OC (i.e., bioactivity is well correlated with soil OC). A first set of simulations was performed to evaluate the impact of soil OC variability when using a deterministic approach for the other parameters (means for hydraulic conductivity and soil physical properties). The objective was to evaluate the sensitivity of the modelling to the variability of OC alone. The simulations consisted of finding the deterministic analytical solution of the transport equation which includes the dispersion term (Van Genuchten and Alves, 1982). The dispersivity used was 10 cm, a value representative of the soil conditions encountered in this study. The pore-water velocity was calculated with Darcy's law using the unsaturated hydraulic conductivity corresponding to the mean soil water content during the period of simulation. The cubic relation used to calculate the unsaturated hydraulic conductivity (Ku) from the measured saturated hydraulic conductivity (Ks) was the one proposed by Irmay (1954 in Bear, 1972): Ku=Ks [ ( w . c . - f . c . ) / (n--f.c.)] 3, where w.c. is the mean water content, f.c. is the field capacity and n is the porosity. The sorption-related input parameters were the mean and the distribution for the measured OC content. The OC content was used to estimate the soil-water partition coefficient (KD) which represents the extent of sorption for hydrophobic contaminants including many pesticides. A second set of simulations was performed to evaluate the impact of soil OC variability when using a stochastic approach (VULPESTmodel) for all the model parameters (distributions for hydraulic conductivity and soil physical properties). The objective was to evaluate the relative impact of OC variability when considering the variability of the other transport parameters. The sorption-related input parameters were the same as those used in the first set of simulations. 3. Results 3.1. Distributions for organic carbon
The frequency distributions (not shown) indicate that the OC variable is normally distributed. Such normality was observed for the various depth intervals as well as for the totality of the samples ( i.e., considering all the results obtained from each one of the 3 depth intervals). Table 2 summarizes the statistics for the variability of OC. The CV value is lower at the first depth interval than at deeper soil intervals indicating a lower variability of OC, perhaps as a result of the soil tillage practices. Moreover, the greater CV value at lower depths could be explained by the lower mean values, causing the technical errors in measurement to become relatively more important in absolute value. 3.2. Effect of sorption variability on predicting atrazine transport
The results obtained from the VULPESTmodel are the stochastic breakthrough curves, i.e., the distribution over time of concentrations (resulting from Monte Carlo simulations)
336
P. Lafrance, O. Banton / Geoderma 65 (1995) 331-338
Table 2 Statistics for the OC variable at each depth interval and for the totality of the samples Depth (cm)
Mean ( g k g t)
SD"
CV h
5-15 40-50 85-95 Totality
19.0 9.4 5.5 13.6
5.7 4.4 3.0 7.4
0.30 0.47 0.55 0.54
"Standard deviation. bCoefficient of variation = SD/mean.
reaching a given surface such as the water table. Fig. 2 shows the effect of OC variability on the breakthrough curve for atrazine when using a deterministic approach (constant values) or a stochastic approach (distributions) for the other input parameters. For the deterministic approach (analytical solution), the result obtained from the mean OC shows a greater peak concentration and a larger peak arrival time for atrazine than those obtained from distributed OC. Also, the curve obtained from the mean is symmetrical whereas the one obtained from the distribution is asymmetrical with earlier breakthrough and increased time for elution at the front tailing. In comparison with the mean, the distribution show a decrease in the peak arrival time (10%) and in the peak concentration (60%). Thus, the primary effect of distributed values for OC is a "spreading" of the concentration zone in the soil profile which results in a smaller peak reaching the water table during a longer period of time. For the stochastic approach (VULPESTmodel), Fig. 2 shows the effect of OC variability on the atrazine breakthrough curve when using actual distributions for the other transport parameters. The main result of these simulations is the apparent insensitivity of the breakthrough curve to the use of the mean or the distribution for OC. This insensitivity of the model to variations in OC results mainly from the significant effect of the variability of 5.0
4.0
I / I
~-
-
Analyt.
&
mean
OC
Anaty f,
& disfr.
OC
3.0 E 0 o--
I I
"~
0 1.0
---
20
25
30
35
Vulpest
40
45
&
Date (weeks)
mean
OC
50
55
60
Fig. 2. Effect of the use of mean or distribution of OC on the simulated breakthrough curve for atrazine for both the deterministic approach (analytical solution) and the stochastic approach (VULPEST model),
P. Lafrance, O. Banton/ Geoderma 65 (1995) 331-338
337
other parameters. Indeed, the CV for OC measured in this study was generally smaller than 0.5 (Table 2). Some other soil properties exhibit higher variations, for example hydraulic conductivity with a CV near 3.5. Such a large variability plays a major role in the control of the pore-water velocity and has a much greater impact on the simulated results than the variations in OC content. In a stochastic approach, the spatial heterogeneity of the parameters controlling the soil-water flow may hide the effect of the variations of the sorption-related parameters on solute transport.
4. Conclusion The representativeness of the modelling results in the evaluation of subsurface solute migration may be affected by the field variations in soil organic carbon. The deterministic approach is sensitive to the variability of the soil sorption coefficient controlled by the organic carbon content; the use of the mean value, instead of the distribution, could result in an overestimation of the herbicide concentration reaching the water table and hence a higher predicted vulnerability of groundwater to contamination. The application of a stochastic approach in predicting pesticide transport showed that in actual field situations, the in situ variability of the soil parameters that control the soil-water flow could be greater than that of the sorption-related parameters such as organic carbon. In this case, the field characterization of the horizontal distribution for organic carbon may not improve the representativeness of the simulation results.
Acknowledgements We are grateful to Lise Gauthier from the Quebec Department of Agriculture for providing information and facilities on the site. This study was funded by the Natural Sciences and Engineering Research Council of Canada.
References Banton, O., Lafrance, P., Martel, R. and Villeneuve, J.P., 1992a. Planning of soil-pore water sampling campaigns using pesticide transport modeling. Ground Water Monit. Rev., Aug., 1992: 195-202. Banton, O., Lafrance, P. and Villeneuve, LP., 1992b. D61imitation des p6rim~tres de protection des puits de pompage en zone agricole h l'aide de la simulation math6matique. Rev. Sci. I' Eau, 5:211-227. Bear, J., 1972. Dynamics of Fluids in Porous Media. Dover, New York, NY, 764 pp. Belluck, D.A., Benjamin, S.L. and Dawson, T., 1991. Groundwater contamination by atrazine and its metabolites. In: L. Somasundaram and J.R. Coats (Editors), Pesticide Transformation Products. Fate and Significance in the Environment. Am. Chem. Soc. Symp. Series 459, Washington, DC, pp. 254-273. Carsel, R.F., Parrish, R.S., Jones, R.L., Hansen, J.L. and Lamb, R.L., 1988a. Characterizing the uncertainty of pesticide leaching in agricultural soils. J. Contam. Hydrol., 2:111-124. Carsel, R.F., Jones, R.L., Hansen, J.L., Lamb, R.L. and Anderson, M.P., 1988b. A simulation procedure for groundwater quality assessments of pesticides. J. Contain. Hydrol., 2: 125-138. Jones, R.L., 1990. Pesticides in groundwater: Conduct of field research studies. In: D.H. Hudson and T.R. Roberts (Editors), Environmental Fate of Pesticides. Series Progress in Pesticide Biochemistry and Toxicology, Vol. 7, pp. 27-46.
338
P. Lafrance, O. Banton / Geoderma 65 (1995) 331-338
Jury, W.A., 1986. Spatial variability of soil properties. In: S.C. Hem and S.M. Melancon (Editors), Vadose Zone Modeling of Organic Pollutants. Lewis, Chelsea, MI, pp. 245-269. Nielsen, D.R., Van Genuchten, M.Th. and Biggar, LW., 1986. Water flow and solute transport processes in the unsaturated zone. Water Resour. Res., 22: 895-1086. Rao, P.S.C., Edvardsson, K.S.V., Ou, L.T., Jessup, R.E., Nkedi-Kizza, P. and Hornsby, A.G., 1986. Spatial variability of pesticide sorption and degradation parameters. In: W.Y. Garner, R.C. Honeycutt and H.N. Nigg (Editors), Evaluation of Pesticides in Ground Water. Am. Chem. Soc. Symp. Series 315, Washington, DC, pp. 100-115. Sheldrick, B.H., 1984. Analytical Methods Manual 1984. Land Resource Research Institute, Agriculture Canada, Research Branch, LRRI No 84-30, Ottawa, Ont. Van Genuchten, M.Th. and Alves, W.J., 1982. Analytical solutions of the one-dimensional convective-dispersive solute transport equation. U.S. Salinity Lab., Riverside, CA. Villeneuve, J.P., Banton, O. and Lafrance, P., 1990. A probabilistic approach lbr the groundwater vulnerability to contamination by pesticides: the VULPEST model. Ecol. Modelling, 51 : 47-58. Wagenet, R.J., 1986. Principles of modeling pesticide movement in the unsaturated zone. In: W.Y. Garner, R.C. Honeycutt and H.N. Nigg (Editors), Evaluation of Pesticides in Ground Water. Am. Chem. Soc. Symp. Series 315, Washington, DC, pp. 330--341. Wagenet, R.J. and Rao, P.S.C., 1990. Modeling pesticide fate in soils. In: H.H. Cheng (Editor), Pesticides in the Soil Environment: Processes, Impacts, and Modeling. Soil Sci. Soc. Am. Book Series, 2. Soil Sci. Soc. Am., Madison, WI, pp. 351-399.