Monte Carlo method applied to modeling copper transport in river sediments

• Published in: Stochastic environmental research and risk assessment 2012-12, Vol.26 (8), p.1063-1079
• Main Authors: Corazza, Marcela Z., Abrão, Taufik, Lepri, Fábio Grandis, Gimenez, Sonia M. N., Oliveira, Elisabeth, Santos, Maria Josefa
• Format: Article
• Language: English
• Subjects: Aquatic ecosystems; Aquatic environment; Aquatic Pollution; Chemistry and Earth Sciences; Computational Intelligence; Computer Science; Copper; Earth and Environmental Science; Earth Sciences; Environment; Environmental risk; Fluvial sediments; Math. Appl. in Environmental Science; Monte Carlo simulation; Organic matter; Original Paper; Physics; Pollution dispersion; Probability Theory and Stochastic Processes; River basins; Rivers; Sediment transport; Statistics for Engineering; Waste Water Technology; Water column; Water Management; Water Pollution Control
• ISSN: 1436-3240; 1436-3259
• DOI: 10.1007/s00477-012-0564-2

Monte Carlo simulation (MCS) methodology has been applied to explain the variability of parameters for pollutant transport and fate modeling. In this study, the MCS method was used to evaluate the transport and fate of copper in the sediment of the Tibagi River sub-basin tributaries, Southern Brazil. The statistical distribution of the variables was described by a dataset obtained for copper concentration using sequential extraction, organic matter (OM) amount, and pH. The proposed stochastic spatial model for the copper transport in the river sediment was discussed and implemented by the MCS technique using the MatLab 7.3™ mathematical software tool. In order to test some hypotheses, the sediment and the water column in the river ecosystem were considered as compartments. The proposed stochastic spatial model makes it possible to predict copper mobility and associated risks as a function of the organic matter input into aquatic systems. The metal mobility can increase with the OM posing a rising environmental risk.