Prediction of potential groundwater contamination by herbicides: integrated use of a leaching model and GIS in the north of Italy

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1 Agricultural Effects on Ground and Surface Waters: Research at the Edge of Science and Society (Proceedings of a symposium held at Wageningen. October 2000). IAI IS Publ. no Prediction of potential groundwater contamination by herbicides: integrated use of a leaching model and GIS in the north of Italy TULLIA BONOMI CNR. Centra cli Studio per la Geodinamica Alpina e Qualernaria. Seiione Ambientale. Piazza Scienza I Milano, Italy bonomi@disat.unimib.it Geologia CARLO RIPARBELLI & EMANUELA CLERICI Dipartinienlo di Scienze dell 'Ambiente e del Territorio, Università degli Studi di Milano-Bicocea, Piazza Scienza I, Milano, Italy Abstract In this study the mathematical model CMLS (Chemical Movement in Layered Soils Model; Nofziger & Hornsby, 1994) has been applied to quantify the amount of selected herbicides present at the bottom of the vadose zone so as to estimate pesticide transport and degradation in the soil. CMLS model results have been integrated into a geographic information system (GIS) by means of raster techniques to produce maps of leaching potential for several herbicides under different management practices. Integrated use of GIS and pre-vision models can be considered as a powerful tool to support decisions. The selected area, about 30 km", is located in the Lombardy Po plain (Italy). Key words estimating pesticide transport; GIS; groundwater contamination; herbicides; Italy; leaching models; maps of leaching potential; travel time INTRODUCTION The extensive use of pesticides in agriculture can entail risks for human health, the environment and non-target organisms. Hence the need to assess the nature and degree of the risk and at the same time to take preventive measures aimed at minimizing possible damage. Integrated use of geographic information system (GIS) and prevision models can be a powerful tool to support decision makers evaluating groundwater resource assessments and for predicting groundwater contamination deriving from the use of pesticides in agriculture. Several simulation models are available to identify areas at risk of pesticide contamination. They simulate the pesticide behaviour in soil systems within and be the plant root zone and estimate the amount of the contaminant in leachate at a certain depth. DESCRIPTION OF THE METHOD In this study two models has been combined and applied to quantify the amount of selected herbicide accumulation at the bottom of the vadose zone: the CMLS94 (Chemical Movement in Layered Soils Model; Nofziger & Hornsby, 1994) has been identified and used to estimate pesticide transport and degradation in the soil; a simple

2 56 Tullia Bonomi et al. methodology (AF/RF; Rao et al, 1985) based on travel time of contaminant in the vadose zone, has been applied to calculate the balance between pesticide degradation and leaching time (Facchino & Giuliano, 1996). CMLS94 is a one-dimensional, dynamic, compartment model that estimates the depth of the centre of mass of a nonpolar organic chemical as a function of time after application, and also calculates the relative amount of chemical in the soil profile as a function of time. The model assumes that chemicals move only in the liquid phase in response to soil water movement, considered as a piston-like f. Movement of the chemical is retarded by its sorption on the solid soil surfaces, which is described by a linear reversible equilibrium model. Model output may be expressed in the form of: pesticide travel time through soil, 7s, and pesticide attenuation factor in soil, Afs (ratio between residual chemical mass and initial mass). The above parameters have been used as inputs for the estimation of pesticide migration through the vadose zone. The foling parameters have been defined: Travel time If a simplified vertical steady state f field is assumed, the time taken for a pesticide to reach the saturated zone Tt, is obtained by summing the transit time through the soil zone, estimated by CMLS94, and the transit time through the unsaturated zone Tns, where the compound is assumed to be transported at the same rate as water: 7>, J = * + & + ^ (1) Vg Vs Va where Sg, Ss and Sa are the thickness of gravel, sand and clay equivalent layers in the vadose zone [m]; and Vg, Vs and Va are the vertical saturated hydraulic conductivities defined for gravel, sand and clay respectively 10"', 10" 4 and 10" 7 cms - 1. Attenuation of the pollutant load The reduction of the pollutant load which takes place during leaching through the profile can be expressed in the form of an attenuation factor AFt, which is given by the product of AFs, estimated by means of CMLS94 considering both adsorption and degradation effects, and the attenuation factor in the unsaturated zone AFns estimated according to Rao et al. (1985) considering only pesticide degradation with the foling: Ml w where M2 is the amount of compound (kg ha" 1 ) leaving the vadose zone and Ml is the amount calculated by CMLS94 at the base of the soil. The half-life of the pesticide in the unsaturated zone (DT 50m ), which appears in equation (2) is assumed to be equal to the half-life value calculated at the base of the soil zone (boundary with the unsaturated zone) using the equation proposed by Jury et o/. (1987): DT, 0l, s =^r (3) exp Y/

3 Prediction of potential groundwater contamination by herbicides 57 where DT 5Q is the half-life of the pesticide in the soil, / is the soil zone thickness and the coefficient y is proportional to the increase ofdt^o with depth. The proposed assessment method implies management and processing of different types of spatially distributed data concerning the soil, unsaturated zone and groundwater table, as well as the mapping of the results. This kind of data is conveniently managed by a GIS. The GIS IL WIS has been used for processing the output of the models, producing vector and raster maps of contamination potential according to the spatial variability of soil properties, weather conditions, crop type and patterns, and pesticide application. Discretizations of the test site areas have been defined according to the input data density distribution. A 20 m grid has been used to define the study area, resulting in a matrix of 800 rows and 800 columns. Dedicated external software linked to the GIS was also employed to process subsoil textural data. Information about textural features of the unsaturated zone was derived from the analysis of water well logs, which were georeferenced and stored in the database TANGRAM (Bonomi etal, 1995). THE CASE STUDY The selected area, about 30 km 2, is located in the Lombardy Po plain (Italy) (Fig. 1); this area is characterized by intensive agriculture, mainly maize, heavy anthropological activity with a considerable impact on the environment (wastes and quarries) and a to degree of groundwater vulnerability. Input data In order to run the models data collection has been organized in the area and data are stored in a database: Soil: texture, organic carbon, bulk density, field capacity, wilting point; the soil data have been derived from the pedological survey at scale 1: (ERSAL, 1988). Geological and hydrographie data: lithological units, hydrographie network. Soil and unsaturated zone data: these have been defined by means of well logs. Hydrogeological data: well data, water table depth (Fig. 2), hydraulic conductivity. Meteorology: daily data to calculate the potential évapotranspiration. Crop: root depth, leaf area index, height. Agricultural practices: time of planting, harvesting, irrigation times and amount. Pesticide: physico-chemical properties, see Table 1 (Wauchope et ai, 1992). Land use: agriculture, industrial and housing activities. Tabic 1 Main properties of the selected pesticides. Herbicide K oc (ml g"') DT ia (day) Amount (kg ha" 1 ) Atrazine Metolachlor Dicamba

4 58 Tullia Bonomi et al LI.' 10-15EU 15-20H >40 Fig. 2 Groundwater table depth MODEL APPLICATIONS The proposed methodology was applied to consider the herbicides Atrazine, Metolachlor and Dicamba. Three different scenarios were simulated for the period , according to the three major crops in the area: maize, wheat and soybean.

5 Prediction of potential groundwater contamination by herbicides 59 For maize, an application of Atrazine for each of the 6 years (Fig. 3) was considered, adding to the rainfall a total irrigation amount of mm year 1 ; for soybean an application of Metolachlor for each of the 6 years (Fig. 4) was considered with the same total irrigation as maize; for wheat a single application of Dicamba for each of the 6 years (Fig. 5) was considered without any irrigation applications. The CMLS94 model was applied to the different cartographic soil units for each compound simulation (i.e. Atrazine, Metolachlor, Dicamba) assuming a uniform distribution of the herbicide over all of the area. The worst case (i.e. est fraction of substance leached at the bottom of the soil at 1 m depth, AFs) calculated for each compound by the CMLS94 model for the 6 years was used as input to equation (2) to estimate the total fraction of pesticide (AFt) reaching the bottom of the vadose zone, potentially contaminating the groundwater, and the travel time (Tt) from the soil surface to the bottom of the vadose zone. The attenuation factor (AFns) and travel time (Tns) for the vadose zone, constant for every computed year, were calculated on the basis of groundwater table depth (Fig. 2). Given the pesticide application amount Q (kg ha year 1 ), the calculated fraction AFt has been diluted in the recharge water R (400 nr'm" year 1 ) estimated for the area in order to obtain the concentration C pcsi of pesticide in the water leaching at the bottom of the vadose zone with the foling equation: QxAft C p c s l = ^ ^ (4) R The results calculated for each grid cell have been classified into seven leaching potential classes (Table 2) (Figs 3, 4 and 5). Table 2 Concentration classes of pesticide leaching. Herbicide leaching potential Very sensitivity <0.00i Low sensitivity Moderately sensitivity Moderate sensitivity Moderately sensitivity 1-5 High sensitivity 5-10 Very sensitivity >10 Concentration classes (ug 1*') RESULT AND DISCUSSION Results show that Atrazine (Fig. 3) has a er contamination potential with respect to Metolachlor (Fig. 4) and Dicamba (Fig. 5), due to its longer half-life time, despite its er mobility. Attenuation in soil (Afs) accounts for at least 90% of the total pesticide attenuation, AFt. Attenuation in the vadose zone (AFns) is almost similar for all three herbicides and appears to strongly depend on the groundwater table depth; it is very near to the soil surface (0-5 m) in the southern area where AFns is very. Travel time Tns through the unsaturated zone, which is independent of pesticide characteristics, accounts for at least 50% of the total travel time. Values range from less than 10 days, where gravel is predominant, to about 3000 days, where clay prevails.

6 L2 very "V^t ^ moderately very 0 m 2500 \. J very ' [ [ 1 moderately - f 1 J T J F ] very i 0 m 2500 Fig. 3 Concentration classes of Atrazine on maize: in the soil (left) and at the bottom of the vadose zone (right). [s \ û r" 1 very \ { 1 /, moderately - very \ k 0 m 2500 u -,j l very x «, I I I 1 moderately! I J CJ very I Fig. 4 Concentration classes of Metolachlor on soybean: in the soil (left) and at the bottom of the vadose zone (right). very, 1! moderately very (TO m,2500 very x moderately very J 0 m 2500 Fig. 5 Concentration classes of Dicamba on wheat: in the soil (left) and at the bottom of the vadose zone (right).

7 Prediction of potential groundwater contamination by herbicides 61 It should be noted that the estimates of the different parameters are directly affected by the figures adopted for the site characteristics (infiltration rate, matrix hydraulic conductivity, soil texture, etc.) as are the chemical compound's properties (partition coefficients, half-life, etc.). The variability of the values implies an uncertainty in potential quality degradation assessment. Variations in the applied dose may induce significant changes in the concentration estimates. The problem is hard to solve definitively owing to the difficulties inherent in the determination of the real chemodynamic properties of the substances in the underground environment, and to the natural variability of the elements of the hydrological cycle. CONCLUSIONS The application of models integrated with GIS techniques can be considered a useful tool for the identification of risk areas in regulatory and planning activities. Based on thematic maps identifying risk areas, health and environmental authorities may activate consistent monitoring plans for surface and groundwater. The maps obtained by the elaboration and the analysis of these data, are powerful tools in managing the use of pesticide according to the characteristics of the crop to be treated, soil sensitivity and the value of groundwater sources. The study presented can be considered a pilot approach to validation of models, procedures and systems for collecting, storing and managing geographically based data. The database itself and the assemblage of tools applied in this study to environmental problems, permit the use of the same data set for different evaluations (land planning, quarries, etc.), or updating the system with new input data. In fact the application of mathematical models within the framework of GIS als one to continually update, standardize and integrate data and results and to minimize errors linked to single data points. REFERENCES Bonomi, T., Cavallin, A. & De Amicis, M. ( 1995) Un database per pozzi: Tangram (A well database: Tangram) (in Italian with English summary). Quad. Geul. Appl. 3(1/95), ERSAL ( 1988) / suoli deltapkmura bresciana fra ifiumi Mella e Chiese. SSR1. ERSAE, Italy. Facchino, F. & Giuliani), G. ( 1996) Assessing the pollution potential of pesticides lor groundwater. In: Pesticide Chemistry (ed. by T. Del Re, G. Capri, R. Evans & U. Trevisan) (Proc. Castelnuovo Fogliani (PC) Italy, X Symp., October 1996), Ea Gogliarclica Pavese, Pavia, Italy. Jury, W., Focht, D. & l'armer, W. I. (1987) Evaluation of pesticide groundwater pollution potential from standard indices of soil-chemical adsorption and biodégradation.,/. Environ. Qual. 16(4), Nofziger, D. E. & Hornsby, A. G. (1994) CMLS94 Chemical Movement in Layered Soils. Division of Agricultural Sciences and Natural Resources, Oklahoma State University, USA. Rao, P. S. C, Hornsby, A. G. & Jcssup, R. E. (1985) Indices for ranking the potential for pesticide contamination of groundwater (In: Proc. Florida Symp. on Fate and Transport of Agrochemicals. 1985). Soil Crop Sci. Soc. of Florida 44, Wauchope, R. D., Bultlcr, T. M., Hornsby, A. G., Augustin-Beekcrs, P. N. P. & Burt,.1. P. (1992) The SCS/ARS/CES pesticides properties database for environmental decision making. Environ. Contain. Toxicol. 123,