Résumés
Résumé
Les outils mathématiques sont de plus en plus utilisés pour simuler la contamination d'origine agricole des eaux souterraines. Le modèle AgriFlux permet, à l'aide du module PestiFlux, de simuler les processus responsables du devenir des pesticides dans le sol: ruissellement, volatilisation, adsorption/désorption rapide, adsorption/désorption lente, complexation par la matière organique dissoute, biodégradation en sous-produits, hydrolyse, drainage et lessivage. AgriFlux est utilisé pour simuler le devenir de l'atrazine et du dééthylatrazine sur une parcelle expérimentale de la région de Québec (Québec, Canada) cultivée en maïs sucré (Zea mays, L.) traité à l'atrazine. Des prélèvements d'eau interstitielle ont été réalisés (1986-1990) à l'aide de lysimètres avec succion (0,5 et 1,0 m de profondeur) et analysés pour leur contenu en atrazine et dééthylatrazine. De manière générale, AgriFlux reproduit bien l'évolution des concentrations mesurées, dans le temps et dans le profil de sol (r=0,76). Certains pics de concentrations observés sur le terrain ne sont toutefois pas représentés ou sont décalés dans le temps, ce qui pourrait être attribué à une sous-estimation de la variabilité spatiale des paramètres. Le rapport dééthylatrazine/atrazine est relativement bien simulé en 1988 à 0,5 m, mais est moins représentatif pour les autres données, ce qui pourrait être dû à une certaine imprécision dans la simulation de la biodégradation. Une analyse de sensibilité du modèle aux variations de différents paramètres a montré que le paramètre le plus influent dans les conditions testées est la constante de biodégradation. Les résultats obtenus montrent la pertinence d'AgriFlux (PestiFlux) dans la simulation du devenir des pesticides dans le sol et donc des risques de contamination des eaux souterraines en région agricole.
Mots-clés:
- AgriFlux,
- modèle,
- eaux souterraines,
- pesticides,
- contamination,
- agriculture
Mots-clés:
- AgriFlux,
- model,
- groundwater,
- pesticides,
- contamination,
- agriculture
Abstract
Groundwater and surface water contamination by agricultural practices has become an increasingly preoccupying problem. Mathematical models are valuable tools to help prevent this type of pollution from non-point sources. AgriFlux is a mechanistic, stochastic model simulating the fate of agricultural contaminants in the unsaturated zone at the scale of the agricultural field. AgriFlux, through the PestiFlux module, now simulates pesticide transformations in the soil from their application to the field until their leaching with percolating water. The processes represented include volatilization, complexation by the soluble organic matter, instantaneous adsorption and desorption, slow adsorption and desorption to less available sites, biodegradation to by-products and hydrolysis to non-toxic compounds. The pesticide freely dissolved in solution or complexed with soluble organic matter can be mobilized with runoff, drainage and leaching water
An application of PestiFlux to an experimental field near Quebec City (Quebec, Canada) is presented. The soil is a well-drained loamy sand cropped from 1986 to 1990 with sweet corn (Zea Mays, L.) receiving atrazine treatments (1.6 to 1.8 kg.ha-1 of active ingredient). Interstitial water was sampled using 12 suction lysimeters located at both the 0.5 and 1.0 m depths in the soil. All stations were sampled monthly in 1986 and 1987 and the collected water was analyzed for atrazine alone. In 1988, the sampling (every two weeks) was limited to the lysimeters which had previously shown the highest pesticide concentrations (two lysimeters at 0.5 m and one lysimeter at 1.0 m). The interstitial water was analyzed for atrazine and deethylatrazine. There was no sampling in 1989. In 1990, all stations were sampled on a weekly basis and a composite water sample obtained for each depth was analyzed for both compounds. Most of the pesticide-related parameters required to run PestiFlux were deduced from the literature, with the exception of the biodegradation rate coefficient which was estimated from field monitoring of atrazine. The parameters required to simulate water fluxes and plant uptake were the same as those used in a previous application of AgriFlux to the same experimental field for the simulation of nitrate fluxes (LAROCQUE and BANTON, 1995).
Results show that PestiFlux generally represents well the measured atrazine and deethylatrazine concentrations in the interstitial water at 0.5 and 1.0 m. A linear regression using all measured and simulated concentrations indiscriminately gives a correlation coefficient of 0.76 when using the logarithm of concentrations. The temporal evolution of the pesticide concentrations is relatively well simulated, especially on the long term with an adequate representation of the increase in pesticide concentrations in the soil profile at 1.0 m. This increase is probably due to the fallow existing in 1985 which would have favored leaching of adsorbed pesticide below the soil profile, leaving only low residual pesticide concentrations. Over one growing season, the transport of atrazine and deethylatrazine is well represented by the model, although some peak concentrations are delayed or attenuated. This result could be due to an underestimation of the spatial variability of the different parameters. It is possible that the coefficient of variation of 10% adopted may not represent adequately the spatial variation of some parameters. Nevertheless, most measured concentrations of both compounds are within the mean simulated concentrations and included between two standard deviations. For 1988, most of the measured concentrations are located near the upper limit of the envelope curve which is consistent with the fact that the sampled lysimeters were those yielding the highest concentrations. The simulated concentrations show a generally good representation of the relative atrazine and deethylatrazine concentrations. The ratio of the mean deethylatrazine to atrazine concentrations provides a closer look at the adequacy between the simulated concentrations of both compounds. A comparison between the measured and the simulated ratios shows a good adequacy at 0.5 m in 1988 and both over- and under-estimation of the ratio for the other available data. This is probably due to an imprecision in the simulation of biodegradation rates during some periods. All the parameters used in the simulation have an important uncertainty, due to the significant spatial variation of the parameters in the field and to the imprecise knowledge of some pesticide characteristics. In order to identify the parameters which have the most important influence on the results, an analysis of the sensitivity of the cumulated leaching mass of both compounds at 1.0 m to variations of the different input parameters was performed. The results show that the biodegradation rate has the greatest influence on the results. This is probably due to the importance of this process in the simulated situation. This result confirms the importance of an adequate quantification of this parameter and of its spatial variation.
PestiFlux offers a comprehensive representation of pesticide transformations in the soil and is easy to use. As a module of AgriFlux, it has the advantage of being integrated into a well-tested and reliable modeling environment. The presented simulation results show that, apart from some limits due to the quantification of some of the parameters, PestiFlux is a useful and comprehensive tool for estimating potential groundwater pollution by pesticides.