International Journal of Environment Science and Technology Center for Environment and Energy Research and Studies (CEERS) ISSN: 1735-1472 EISSN: 1735-2630 Vol. 6, Num. 2, 2009, pp. 233-242

International Journal of Enviornmental Science and Technology, Vol. 6, No. 2, Spring, 2009, pp. 233-242

Pesticide transport and transformation modeling in soil column and groundwater contamination prediction

*S. A. Mirbagheri; S. A. Hashemi Monfared

Department of Civil Engineering, K. N. Toosi University of Technology, Tehran, Iran
*Corresponding Author Email: mirbagheri@kntu.ac.ir Tel.: +9821 137 4357; Fax:+9821 880 35 516

Received 13 August 2008; revised 8 October 2008; accepted 26 October 2008

Code Number: st09026

ABSTRACT

Pesticide transport and transformation were modeled in soil column from the soil surface to groundwater zone. A one dimensional dynamic mathematical and computer model is formulated to simulate two types of pesticides namely 2,4-dichlorophenoxy acetic acid and 1,2-dibromo 3-chloro propane in soil column. This model predicts the behavior and persistence of these pesticides in soil column and groundwater. The model is based on mass balance equation, including convective transport, dispersive transport and chemical adsorption in the phases such as solid, liquid and gas. The mathematical solution is obtained by finite difference implicit method. The model was verified with experimental measurements and also with analytical solution. The simulation results are in good agreement with measured values. The major findings of this research are the development of the model which can calculate and predict the concentration of pesticides in soil profiles, as well as groundwater after 4, 12, 31 days of pesticide application under steady state and unsteady water flow condition. With the results of this study, the distribution of various types of pesticides in soil column to groundwater table can be predicted.

Keywords: Water movement, finite difference, soil system, numerical method, pollution

INTRODUCTION

There is evidence that chemicals applied to the soil surface may be transported rapidly to groundwater passing the unsaturated soil zone (Johnson et al., 1995). Toxic materials especially pesticides are being used for many purposes in the environment. These substances are adsorbed in soil environment through natural processes occurring in soil water plant relationships. Adsorption is one of the most important factors that affects fate of pesticide in soils and determines their distribution in the soil/water environment (Kah and Brown, 2007). Concern about the environmental impact of repeated pesticide use has prompted research into the environmental fate of these agents, which can emigrate from treated fields to air, other land and waterbodies (Arias-Estevez et al., 2008). Two types of pesticides namely 2,4-dichlorophenoxy acetic acid (2, 4-D) and 1, 2 dibromo 3chloro propane (DBCP) in soil column were considered. The positive attributes of DBCP as a nematocide are as follows: 1) it is less volatile than many of the other soil fumigants of the time period; 2) it remains active in the soil for a long time; 3) it is very effective in killing nematodes and 4) it does not penetrate the roots of plants. The negative attributes of DBCP as a nematocide are that 1) it is relatively mobile in soils with high groundwater recharge rates, 2) it is fairly persistent, 3) there is strong evidence that it causes sterility in human males and 4) it is likely to be carcinogenic (Babich and Davis, 1981).

Several studies have utilized laboratory-scale columns filled with compacted municipal refuse in landfills (Qasim and Burchinal, 1970; Rovers and Farquhar, 1973; Walsh and kinman, 1979). Mc Creanor and Reinhart (2000) developed a mathematical model for the leachate of landfill in the United States. A huge volume of annually precipitation infiltrates in to the ground surface of various catchment's areas in the world and produces extensive water resources under the ground surface (Bodaghpour et al., 2007). After precipitation and infiltration of surface water to soil, toxic materials coming to groundwater and contaminate this region. Therefore, studying pollutant behavior of pesticides in soil column is an important problem. In recent years, water and pollution movement in soil were modeled. Some of them were based on movement of soluble and washed samples in soil column. Others were the result of changing concentration of toxic materials in agricultural soils. The pesticide transport and transformation processes in soil column under transient flow condition are complex. Several complicating factors which control transport of different types of pesticides include: a) pore water velocity, b) evaporation and transformation fluxes, c) concentration gradient and d) seasonal rise and fall of the water table. In general, contamination of soil and groundwater by pesticides are the result of mass flow and concentration gradient. Physical, chemical and microbial factors affect the process. Selenium transport and transformation in soil column and groundwater contamination was studied with other researchers (Mirbagheri, 1995; Mirbagheri and Kazemi, 2008; Mirbagheri et al., 2008). Some researches provided a model for predicting the fate of nonvolatile pesticides (Wagenet and Huston, 1986; 1987; Wagenet et al.,1989). In many cases, they considered a distribution coefficient for this case (Deeley et al., 1991). Developing models with molecular diffusion and other important factors have been done by other researchers (Jury et al., 1983; Kalita et al., 1998). Kloos (1983) investigated pesticide in drinking water wells in Fresno and other communities in the Central Valley of California. Stevenson et al. (1997) considered the influence of pesticides in groundwater pollution. Leaching pesticides from biological wastes modeled by others (Taube et al., 2002; Vorkamp et al., 1997; 1999). DBCP and 2,4-D effects in soil column in unsaturated zone and in groundwater were studied comparing with experimental works (Loague et al., 1996; 1998). Models for long-term fate of pesticides in soils is considered in recent years (Scholtz and Bidleman, 2007). Muller et al. (1998) investigate a method for cleaning water polluted with pesticides. Also a study was carried out on the sorption of the sparingly water-soluble pesticide in various types of soil with different levels of organic matter by Zbytniewski and Buszewski (2002). Also USDA, forest service, forest health protection (2006) performed experimental works on 2, 4-D transport in soil column. This paper presents a model which considers all phases of transport and transformation of pesticide in soil column.

MATERIALS AND METHODS

Water flow model formulation

Obviously, it is not possible to unequivocally validate the models already used to predict subsurface fluid flow and solute transport (Oreskes et al., 1994).

Water flow is calculated using a one-dimensional finite difference solution to the soil-water flow equation:

Where, h is a soil water pressure head (mm); θ is volumetric water content (m ³/m³); t is time (day); H is hydraulic head (h+z); z is soil depth (mm); k is hydraulic conductivity (cm/day); is differential water capacity and u is a sink term representing water loss by transpiration.

There is a two part function that describes the general shape of θ(h) relationships (Hutson and Cass, 1987).

Where, h_i= a[2b /(1+ 2b)]^-b and θ_i = 2bθ_s/(1+2b)

is the point h_i, θ_i intersection of the two curves, θ_s is water content at saturation, a and b are constants. The two curves are exponential and parabolic for dry and saturated soil, respectively. Similarly the equations for hydraulic conductivity can be described as a function of soil water pressure head. When soil water pressure head is greater than h_i, the following equation is used to calculate hydraulic conductivity:

K (θ ) = K_s (θ /θ_s )^{2b + 2 +p} (4)

Where, K_s is hydraulic conductivity at saturation (θ_s) and P is pore water interaction parameter. When soil water pressure head is less than h_i, the equation for the calculation of hydraulic conductivity is:

K = K_s (a/h)^{2 + (2 +p)/ b}(5)

Solving Eq. 1 using finite difference techniques provides estimated values at each depth, node used in differencing equations. Water contents are calculated using Eq. 2 and water flux densities (q) are calculated over each depth interval using darceys equation (q = K(θ) ΔH/ΔZ). Finally, the values of q are then used to estimate pesticide transport in the soil profile.

Pesticide transport model formulation

Movement of a soluble and volatile pesticide in soil column is described in three shapes:

• Chemical transportation in liquid phase because of liquid concentration gradient;
• Gas transportation because of gas concentration gradient and
• Convection of pesticide can occur as a result of movement of water in response to pore water velocity gradient and gas partial pressure gradient

Thus the transportation of a pesticide is described as:

J_t = J_dl + J_cl + J_dg + J_cg (6)

Where,

J_t: Total transportation of pesticide

J_dl: Liquid diffusion flux

J_cl: Liquid convection flux

J_dg: Gas diffusion flux

J_cg: Gas convection flux

Movement in liquid phase

When, flow is in a porous media, J_dl is:

J_dl = -D_p(θ , q)dC_l / dZ (7)

Where, C_l is the concentration in liquid phase (mg/L) and D_p(θ) is the molecular diffusion coefficient decribed as below:

D_p (θ) = D_ol× ae^-bθ` (8)

Where, D_ol is molecular dispersion coefficient in liquid phase (cm²/day); a and b are constant.

Where, q is water flux (cm³ /cm/day) and D_M (θ,q) is the hydrodynamic dispersion coefficient and is obtained as follow:

D_M (θ , q) = λ V (10)

Where, V is the velocity of water flux (cm/day) and λ is propagation coefficient generally considerd as:

2mm < λ< 80mm

Movement in gas phase

Gas diffusion flux in porous media results from the following processes:

J_dg = -D_g (ε ) × dC_g / dZ (11)

Where, D_g is the average gas diffusion coefficient (cm²/day) in gas phase and is:

D_g (ε ) = D_og× γ(ε ) (12)

Where, ε are voids including gas and calculated as:

ε = θ_s - θ

And D_og is the gas diffusion coefficient in air and γ (ε ) is a coefficient:

Changing in soil water content, barometric pressure and temperature may cause air flow to the soil column. Since changes are periodic, it is possible to simulate these effects with increasing in gas diffusion coefficient.

For volatile composes liquid and gas concentration are related with Henry law.

C _g = K _H C_l (14)

Where, K_H is the Henry coefficient.

Therefore, transports of pesticide in phase can be calculated as:

More pesticide transports are in steady-state water flow condition. In this condition, water content (θ) and water flux (q) are variable with time and depth.

Mass balance equation

When a volatile pesticide in adsorbed solution phase contacts with soil, the concentration of pesticide in solution is:

C_t =θC_l + qC_s +εC_g (17)

Where, ρ is the soil bulk density (kg/m³) and C_s is the concentration of pesticide (mg/L). Assuming that the pesticide adsorption is sudden and reversible then:

C_s = K_dC_l (18)

Where, K_d is the distribution coefficient (m³/kg). Substituting this equation in Eq. 16:

C_t = C_l (θ + ρK_d + εK_H ) (19)

Now all parameters of Eq. 15 can be determined, therefore:

Solution method

Eq. 20 may discrete with non-equal steps like Bersler method. In point i and time j:

Where

Replacing above contents in Eq. 20:

If define new parameters like following:

The general shape of this equation is:

Where, A_i, B_i and CC_i are constant in each time step. This equation may be solved with one of the solution methods for three diagonal matrixes (Fig. 1).

Upper and lower boundary condition

The boundary conditions for solute and water flux are not always the same algebraic sign within each time interval since water is evaporated from the soil surface while pesticide accumulation. For example, water in each time step may be evaporated from soil surface. Upper bound needs to be defined for zero flux, infiltration and evaporation. For zero flux, C₁^j = C_w , . In infiltration stage C₁^j = C_w and where, C_w is the pesticide infiltration in water and pesticide flux that is in the soil column is and in evaporation stage from soil surface, C₁^j = 0 and

Lower bound needs to be defined for zero flux, unit hydraulic gradient and constant water head. In point and C_k= 0.

If C_gw is the groundwater surface then and concentration in point k is equal to C_k = C_gw.

Model application

The model was applied to simulate the transport and transformation of DBCP concentration in soil depth. The selected physico-chemical data for panochi soil measured by Leachm (Wagenet et al., 1989) and shown in Table 1 and 2 was used for the model calibration and verification. The data is collected for the parameters such as hydraulic conductivity (K), soil water content (θ) and soil pressure head (h) expressed as functions in Eqs. 2, 3, 4, 5. Other parameters such as saturated hydraulic conductivity (K_s) and a and b constants are summarized in Table 2 for soil depth from 0 to 200 mm down to 1200-1500 mm. The DBCP data was collected for water flow under steady state and unsteady conditions for 150 mm irrigation water in a soil plot 6.1 by 6.1 m. The bulk density (ρ) of soil used in this study was 1.4 kg/dm² with matric potential of -9 kpa.

RESULTS AND DISCUSSION

The pesticide simulation model developed for this study facilitates the construction of distribution curves to show the fate of DBCP and 2,4-D in soil column under transient flow conditions. The soil column assumed to be unsaturated under both conditions. For calibration and validation of model, the data collected by Wagenet et al. (1989) was used. Measured concentration of DBCP ranging from 55 mg/L after 4 days of pesticide application to 21 mg/L in 200 mm of soil depth after 31 days. The simulated value for DBCP ranging from 52 mg/L after 4 days of application to 50 mg/L after 31 days in the same soil depth under steady state water flow condition. But under unsteady water flow condition, measured value of DBCP in 200 mm soil depth after 4 days was 30 mg/L and after 31 days decreases to 3 mg/L and simulated values from 28 mg/L decrease to 4 mg/L that means unsteady state water flow conditions prevails in the study area. This is partly due to evaporation and uptake of water by plants. Table 3 shows the summary of measured and simulated data. Figs. 2, 3, 4, 5, 6, and 7 shows that the distribution of DBCP concentrations in soil profile from the surface to 1000 mm depth follows the same pattern for measured and simulated values under both conditions (steady and unsteady). As the wetted front of soil profile proceed to the bottom of the column, the concentration of pesticide decreases with depth. The simulated values by pesticide model were compared with Loague et al. (1998) and Jurys model (1983) as shown in Table 4 . The results are almost the same. Also Fig. 8 shows the comparison of calculated values for DBCP concentrations with the simulated model presented by loague et al. (1998). Fig. 9 shows such comparison with BAM model (Jury et al., 1983). Fig. 10 shows the calculated value for 2,4-D concentration in soil depth after 4 days under steady state water flow condition which is different from the concentration of 2,4-D under unsteady state (Fig. 11) because of evaporation of the pesticide at the soil surface and leaching though the soil profile and accumulation in 400 mm of soil depth. Since the velocity gradient in horizontal and lateral direction of soil column in water flow model is negligible, therefore a one dimensional model for pesticide transport in soil column in vertical direction is dominate in compare to two and three dimensions. A mass balance for concentration of pesticide in vertical direction for two and three dimensional model is almost the same as one dimensional. This is the reason that the reliability of one dimensional model for pesticide transport in soil column is confirmed. Overall, the simulated values for pesticides by pesticide model are in good agreement with measured values.

CONCLUSION

A one dimensional dynamic mathematical model was developed to simulate the transport and transformation of pesticides concentration namely BDCP (1, 2 dibromo 3chloro propane) and 2, 4-D (2, 4-dichlorophenoxy acetic acid) in soil column. This model is based on the mass balance equation including advective and diffusive transport and chemical adsorption in the phases such as liquid, solid and gas. The solution obtained by a finite difference cranck nickolson method provides for a temporal and spatial description of the DBCP and 2, 4-D in soil column. The model was calibrated and confirmed using data collected by Wagenet et al. (1989). The model also was compared with analytical solution, Jurys and Loagues models. The simulated results are in good agreement with measured values. The model is a useful tool and allows to look well in to the future to use pesticides in agricultural soils and consider alternative management strategies.

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