Including Spatial Variability in Monte Carlo Simulations of Pesticide Leaching

• Published in: Environmental science & technology Vol. 41; no. 21; pp. 7444 - 7450
• Main Authors: Leterme, Bertrand, Vanclooster, Marnik, van der Linden, Ton, Tiktak, Aaldrik, Rounsevell, Mark D. A
• Format: Journal Article
• Language: English
• Published: Washington, DC American Chemical Society 01.11.2007
• Subjects: Adsorption; Agronomy. Soil science and plant productions; Applied sciences; Atrazine - chemistry; Belgium; Biological and medical sciences; Biological and physicochemical properties of pollutants. Interaction in the soil; Computer Simulation; Earth sciences; Earth, ocean, space; Engineering and environment geology. Geothermics; Environmental science; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; Herbicides - chemistry; Leaching; Models, Theoretical; Monte Carlo Method; Monte Carlo simulation; Pesticides; Pollution; Pollution, environment geology; Reproducibility of Results; Risk assessment; Rivers; Simulation; Soil and sediments pollution; Soil and water pollution; Soil Pollutants - chemistry; Soil science; Uncertainty; Water Movements; Belgium; Europe; Belgium, Brabant, Dyle R; Stochastic model; Monte Carlo method; Uncertainty; Organic matter; Spatial variability; Pollutant behavior; Pesticides; Property of soil; Environmental factor; Soil pollution; Herbicide; Case study; Watershed; Triazine derivatives; Lixiviation; Numerical simulation; Organic compounds; Atrazine
• ISSN: 0013-936X; 1520-5851
• DOI: 10.1021/es0714639

A methodology is developed to quantify the uncertainty in a pesticide leaching assessment arising from the spatial variability of non-georeferenced parameters. A Monte Carlo analysis of atrazine leaching is performed in the Dyle river catchment (Belgium) with pesticide half-life (DT50) and topsoil organic matter (OM) content as uncertain input parameters. Atrazine DT50 is taken as a non-georeferenced parameter, so that DT50 values sampled from the input distribution are randomly allocated in the study area for every simulation. Organic matter content is a georeferenced parameter, so that a fixed uncertainty distribution is given at each location. Spatially variable DT50 values are found to have a significant influence on the amount of simulated leaching. In the stochastic simulation, concentra tions exist above the regulatory level of 0.1 μg L-1, but virtually no leaching occurs in the deterministic simulation. It is axiomatic that substance parameters (DT50, sorption coefficient, etc.) are spatially variable, but pesticide registration procedures currently ignore this fact. Including this spatial variability in future registration policies would have significant consequences on the amount and pattern of leaching simulated, especially if risk assessments are implemented in a spatially distributed way.