Pestic. Sci. 1986, 17,256264

Modelling the Behaviour of Organic Chemicals in Soil and Ground Water"

Minze Leistra

Institute for Pesticide Research, PO Box 650, 6700 A R Wageningen, The Netherlands

(Manuscript received 7 December 198s)

The development, testing and application of computer models for the behaviour of organic chemicals, especially pesticides, in soil and ground water has been reviewed. Detailed data are needed on the structure and properties of the soil and ground-water systems, and on the flow of water through these systems. Adsorption and transformation of organic chemicals can be studied in the laboratory and the results introduced into the models. The mathematical techniques most frequently used for the solution of the differential equations are briefly discussed. Some models for the behaviour of pesticides in the root zone have been tested against results of field trials and some interesting deviations between computations and measurements emerged. Techniques for the simulation of the behaviour of organic chemicals in the ground-water zone are also available. However input data for the models are often lacking, as are also results of field studies for testing the models.

1. Introduction

Terrestrial systems can be divided into a water-unsaturated zone (including the soil) and a water-saturated or ground-water zone. The upper part of the water-unsaturated zone is strongly influenced by atmospheric conditions. It often supports vegetation and the activity of soil organisms is often quite high. Water flow and transport of chemicals is mainly downward, and residence times of water and weakly-adsorbed substances may range from less than one year to a few years.

Conditions in the water-saturated zone are often fairly constant over time and microbial activity is usually low. Besides the vertical component, the horizontal components of water flow are important. The residence time of water and solutes in this zone is usually at least a few years and may range up to many decades.

2. Water-unsaturated zone 2.1. Description of the water-unsaturated zone Soil water is the main carrier for the transport of most chemicals in soil. Thus the first point of attention is a description of water balance of the soil system and of water flow in soil. Water arrives in the soil system from rain and it can be supplemented by sprinkler or surface irrigation. Afterwards, a fraction of this water will gradually return to the atmosphere by evaporation from surfaces and by transpiration by vegetation. Capillary rise of water from the saturated zone into the unsaturated zone occurs, especially when the water table is fairly shallow.

The accurate description and prediction with models of water balance and of water flow in soil

"Based on a paper presented at the Symposium Physicochemical Properties and Their Role in Environmental Hazard Assessment, 1-3 July 1985 organised by the Society of Chemical Industry (Pesticides Group and Physicochemical and Biophysical Panel) and the Royal Society of Chemistry (Industrial Division, Environmental Group).

256

Prediction of fate of chemicals in soil systems 257

0

0 10 20 30 0 10

Concentration (rnM m-3,

Figure 1. Computed concentrations of ethoprophos in the liquid phase of (left) a sandy loam and (right) a humic sand soil, 0,20, 40 and 60 days after application in spring (from Leistra).'

is a physical and hydrological problem. Some calibration of the sub-model for water flow to a particular field situation will often be needed.

The composition of a particular soil and its properties are important when considering interactions with organic chemicals. The following factors should be considered: organic-matter content, clay content, p H , and the nature and activity of the microbial population. A particular problem is the enormous variation in soil characteristics: there are numerous soil types and even within a field the soil properties may vary considerably.

2.2. Adsorption, movement and transformation Adsorption can be measured fairly quickly in the laboratory by shaking a solution of the chemical in water with soil. In addition, various procedures are available t o estimate adsorption of organic chemicals. The resulting adsorption coefficient or isotherm can be introduced into a computer model to simulate the availability and movement of the chemical in soil. The behaviour of the insecticide and nematicide ethoprophos in two soils in spring has been simulated' and some of the results are shown in Figure 1. In a loamy soil with moderate adsorption, the availability of the pesticide was higher than in a humic sandy soil with stronger adsorption. Further, a greater redistribution of the pesticide was simulated when adsorption was only moderate.

The rate of transformation of an organic chemical in soil can be measured in incubation studies in the laboratory. Factors such as temperature and soil moisture have a great effect on the transformation rate. An interesting development is the prediction of the transformation rate under the variable conditions encountered in the field on the basis of measurements in the laboratory. The effects of temperature and soil moisture should then be measured in the laboratory and the resulting relationships introduced into the c o m p ~ t a t i o n s . ~ , ~ The rates of transformation of eight herbicides in a sandy loam soil under field conditions were simulated' and compared with measured rates. Some results for simazine and propyzamide are shown in

258 M. Lcistra

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Figure 2. Persistencc of the hcrbicidcs simazine (left) and propyzamide (right) in soil under field conditions. (0): observed. Vertical bars represent standard deviation. (0): computer simulated (from Walker).'

Figure 2. In these cases, as in various other cases, reasonable agreement between simulated and measured rates was found. However there were clear deviations in some other cases, for example when volatilisation or photodegradation contributed significantly to the decline.

The nature of the transformation products of an organic chemical in soil is usually determined by incubation studies with the radio-labelled compound in the laboratory. The rate of formation and transformation of the reaction products can also be simulated. A well-known example deals with the insecticide and nematicide aldicarb, which is transformed into two oxidation products with high biological activity: its sulphoxide and sulphone. The reaction kinetics as measured and simulated' is shown in Figure 3.

Figure 3. Concentration-time relationships of (0) aldicarb, (0) its sulphoxide and (A) its sulphone after incubation of aldicarb in a sandy loam soil at 15°C. Lines indicate relationships computed with first-order kinetics (from Smelt ei a1.) .5 -e

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Prediction of fate of chemicals in soil systems

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The behaviour of the parent compound and of the main transformation products in soils in the field can be simulated together in numerical models. In computations,6 the transformation and leaching of aldicarb and its two oxidation products in soil columns under field conditions was simulated. The results of the computations were compared with those of measurements (Figure 4).

2.3. Model development and testing The development of computation models for the behaviour of chemicals in the field starts with the formulation of concepts for the various processes involved. Subsequently the concepts are described quantitatively by physicochemical laws, often in the form of a differential equation. The various equations may be combined into a general partial differential equation, describing transport and the various source and sink terms.

The types of mathematical solution most frequently used for these differential equations are: analytical solutions, consisting of mathematical functions; and numerical solutions, particularly finite-difference approximations. The analytical solutions require drastic simplifications, such as the assumption of uniform soil profiles and of steady-state water flow. Thus their utility for simulating field conditions is limited. Finite-difference methods are flexible in handling heterogeneities and changes in time, and can easily be extended.

Detailed descriptions of comprehensive computation models for the behaviour of pesticides in soil under field conditions have been given before.',

Some numerical models have been developed and tested by comparison with measurements in the field. Transformation and movement of the pesticide ethoprophos in three soils in winter was computer-simulated9 with laboratory data for the pesticide-soil combinations. The results of the computations were compared with those of measurements. The transformation rates were fairly well described, whereas movement of the pesticide in two loamy soils was somewhat overestimated. 18

260 M. Leistra

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Figure 5. Amount of fluometuron per layer in clay loam soil columns in winter. Blocks, measured values; bars represent range between duplicates. Broken lines, simulated with two models, A and B (from Nicholls er nl.).'' Left. day 66; right, day 143.

Movement of the herbicide fluometuron in a well structured clay-loam soil was studied in winter." Measured results were compared with the computed results of two diverse models (Figure 5). Both models somewhat overestimated movement of the herbicide after the first few months. The model accounting for mobile and stagnant fractions of the water phase (Model B) provided a better description of the penetration of low concentrations to depths around 0.3 m.

New research into the computer simulation of pesticide behaviour in soils deals mainly with deviations from the comparatively simple concepts used in the first sub-models. The sub-model with instantaneous equilibration of adsorption and desorption may be too simple for long-term movement in the field. A kinetic model involving a gradual increase in adsorption strength with time may be expected to apply better to field conditions.'' In other models, mobile and stagnant water phases in soil are distinguished, and diffusion in the stagnant phase to and from adsorption-desorption sites is introduced as the rate-limiting step in adsorption equilibration. The mobile phase corresponds to particular flow pathways in soil and such models especially apply to situations with highly uneven water flow.

In sub-models on the rate of transformation, the first-order rate equation is often used, with the rate coefficient derived from an incubation study. An increasing number of studies indicates that soil microorganisms can adapt to a particular compound or to a group of compounds.I2 Even after a few applications of a pesticide to a soil, microbial transformation rate is sometimes enhanced.

3. Ground-water zone

3.1. Geohydrological investigations The first requirement in the computer simulation of transport of an organic chemical in the ground-water zone is that the water flow should be known. This flow is strongly dependent on the local geological situation, which should be investigated to locate the position of well conducting (aquifer) and poorly conducting (aquitard) layers. The nature of the materials in the various layers and the arrangement of the particles determine the geometry of the pore system and thus the water-conducting properties.

Prediction of fate of chemicals in soil systems 261

The rates of flow into the ground-water zone of the area should be known. Water percolates through the unsaturated zone in periods of rainfall surplus and water can infiltrate from water courses into the ground-water zone. Ground water may be discharged to drainage ditches, creeks and rivers. Further the inflow and outflow of water through the various aquifers and aquitards should be estimated. Hydraulic pressures must be measured at various points in an aquifer and attempts made to compute a coherent pattern of isohypses and flow lines. The gradient of hydraulic pressure is the driving force for water flow, which is further determined by the hydraulic conductivity and thickness of the layer. The uncertanty about values of parameters to be introduced in geohydrological models is fairly great, so a model is usually calibrated against measurements of hydraulic pressures in the area.

3.2. Adsorption and transformation The content of materials such as organic matter and clay minerals in the various layers of the ground-water zone affects the extent to which an organic chemical is adsorbed. The composition of layers in, for example, sedimentary deposits can be very different; the layers may contain gravel, sand, silt, clay and peat in various proportions. Adsorption data can be obtained with the same methods as used for top soils.

Transformation rates of organic chemicals in subsoil materials can be measured in incubation studies in the laboratory, if the subsoil conditions in the field are closely imitated. The geochemical conditions in the subsoil layers may be expected to have a great effect on transformation rate. A well-known factor affecting reaction rates is pH. Microbial activity generally decreases with depth in the soil, but microorganisms are found even in deep aquifers, although their density is low. For some pesticides, the oxidation-reduction condition in the subsoil had a great effect on transformation rate. Very fast transformation of some carbamoylox- ime pesticides has been found under reducing sub-soil conditions, presumably because of catalysis by soil component^.'^ A complication is that oxidation-reduction conditions in subsoils can be very different at different positions in the ground-water zone. In general, information on the transformation of organic chemicals in the ground-water zone is scarce.

3.3. Modelling techniques The derivation of partial differential equations describing water flow and chemical behaviour in the ground-water zone has been given, for instance, by Mercer and Faust.14 In most investigations of complex field systems, these equations are solved by using a numerical method, either a finite-difference method or a finite-element method.

Finite-difference methods can be fairly easily programmed and are used by researchers in various disciplines. Advantages are the flexibility in the insertion of all kinds of interactions between chemical and system, and the ease with which the various sub-models can be modified. An example of a finite-difference grid for an aquifer is given in Figure 6a.

Finite-element methods require a fairly high degree of specialisation in mathematics and they can be considered for use in multidisciplinary groups. The correct programming of these methods for the computer is difficult. An advantage is the great flexibility in the selection of the sites for the grid points, and of the shape and size of the corresponding elements. Figure 6b shows an example of a finite-element configuration for an aquifer.

An introduction to these numerical-solution techniques has been given by Mercer and Faust,14 together with references to more advanced literature.

3.4. Applications Accurate prediction of the behaviour of chemicals in ground-water systems is hardly possible yet. Computer models for ground-water pollution have mainly been used to describe existing cases of p~l lu t ion . '~ The results of the first computations on the behaviour of the contaminant are usually compared with the results of measurements in a particular area, after which the computations are calibrated. Attempts can then be made to reconstruct the history of the pollution and the chemical serves as a tracer at this stage. Ultimately, the combination of information from

262 M. Leistra

b finite difference grid block

Figure 6. a. Top view of a typical finite-difference grid for aquifer modelling. b. Top view of a typical finite-element configuration for aquifer modelling. b=thickness of block (6a) and of element (6b) which equal aquifer thickness (from Mercer and Faust).14

Figure 7. Observed (A) and simulated (B) chloride concentrations in an aquifer near Denver, Colorado, for January 1961 Lines indicate equal chloride concentration (mg litre-'). Shaded areas, very low hydraulic conductivity (from Konikow).16

Prediction of fate of chemicals in soil systems 263

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t t t + + + + + + Figure 8. Concentration pattern of a hypothetical pesti- cide in an aquifer, computed with a finite-difference solution. Pesticide had hKKn applied in the shaded area fo< 20 years. Concentrations in pglitre '. Abstraction rate t + t + + + + + + from the well 3x1Obn3 per year (from Peters and den

Blanken)." P 500 rn

computations and from measurements may lead to a semi-quantitative description of contami- nant behaviour in that area. This yields a tool to estimate how the pollution will develop and what will be the effect of various control measures.

A well known example of a model study on the transport of a pollutant in an aquifer is the study of Konikow." Liquid waste had been disposed in ponds in an area near Denver, Colorado, after which various pollutants penetrated into the ground water. The waste contained a high concentration of chloride ion and the spread of this ion in the aquifer had been followed by measurements (Figure 7A). A model with a finite-difference solution was used to simulate the spread of chloride ion in the aquifer. After various cycles of calibration, a computed pattern was obtained (Figure 7B). Finally, the model was used to estimate the effect of alternative methods to alleviate the pollution.

The number of reports in the open literature on computations for organic micro-contaminants adsorbed and transformed in the ground-water zone is very small. Peters and den Blanken" computer-simulated the behaviour of a hypothetical pesticide in an aquifer. They used a numerical model of Konikow and Bredehoeft'' based on a finite-difference solution. The model was extended with descriptions of adsorption and transformation. A fraction of the pesticide dose applied to a field was assumed to leach to the aquifer, after which residues moved with the water flow to a drinking well some distance away. An example of the concentration patterns obtained with their computations is given in Figure 8. Measured data for testing these computed results were not then available.

The application of computation models to questions on the behaviour of organic chemicals in the ground-water zone is still in its infancy. References

1. 2. 3. 4. 5 . 6.

Lcistrd, M. Soil. Sci. 1979. 128, 30.3-311. Walker, A . J . Environ. Qualiy 1974. 3, 396401. Walker, A , ; Barnes, A . Pesric. Sci. 1981, 12, 12.L132. Walker, A . Weed Res. 1978. 18, 305-313. Smelt, J . H.: Leistra. M.; Houx. N . W . H . : Dekker. A . Pesfic. Sci. 1978. 9, 29S300. Leistra. M.; Smelt, J . H. Qualiry ofgroundwurer. Sfudies in Environ. Sci. 17 (van Duijvenbooden, W.; Glasbergen. P.; van Lelyveld. H. Eds), Elsevier Scientific Publishing Company. Amsterdam, 1981, pp. 941-952.

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7. Boesten, J . J. T. 1.; Leistra, M. Application of Ecological Modelling in Environmental Management, Parf B (J~rgensen, S . E.; Mitsch, W. J., Eds), Elsevier Scientific Publishing Company, Amsterdam, 1983, pp. 3564.

8. Carsel, R. F.; Smith, C. N ; Mulkey, L. A.; Dean, J. D. ; Jowise, P. Users manualfor the Pesticide Root Zone Model (PRZMJ. Report EPA-600/3-84-109. US Environmental Protection Agency, Athens, Georgia, 1984,216 pp.

9. Leistra, M.; Smelt, J. H. SoilSci. 1981, 131, 296-301. 10. Nicholls, P. H.; Bromilow, R. H.; Addiscott, T. M. Pesfic. Sci. 1982. 13, 47W83. 11. Boesten, J . J. T. 1.; van der Pas, L. J . T. Aspects of Applied Biology Vol. 4, Association of Applied Biologists,

Wellesbourne, Wanvick, UK, 1983, pp. 495-501. 12. Walker, A,; Entwistle, A. K.; Dearnaley, N. J. Soils and Crop Protection Chemicals. BCPC Monograph No. 27, (Hance,

R. J., Ed.) , British Crop Protection Council, Croydon, UK, 1984, pp. 117-123. 13. Smelt, J . H.; Dekker, A. ; Leistra, M.; Houx, N. W. H. Pestic. Sci. 1983, 14, 17S181. 14. Mercer, J. W.; Faust, C. R.. Ground-wafer Modelling. GeoTrans Inc., Reston, Virginia, USA, 1981, 60 pp. 15. Anderson, M. P. CRC Critical Reviews in Environmental Control 9, (Straub, C. P., Ed.) CRC Press, Boca Raton.

Florida, USA, 1979, pp. 97-156. 16. Konikow. L. F. Modelling Chloride Movement in the Alluvial Aquifer at the Rocky Mounfain Arsenal, Colorado. US

Geological Survey Water Supply Paper 2044, 1977. 43 pp. 17. Peters, J . H.; den Blanken, M. G. M. Wafer Supply 1985, 3, 179-185. 18. Konikow, L. F.; Bredehoeft, J . D:Techniques of Wafer-resources lnvesfigafions of the Unifed States Geological Survey.

B w k 7, Chapter C2, US Govern. Printing Office, Washington DC. 1978. 90 pp.